The PR2 databases

Database management

Sat, 01 Sep 2018 00:00:00 +0000

Management of MySQL database

The PR2 MySQL database is accessed and edited by the Navicat software

Importing and verifying new or updated data

Importation and verification of updated annotation or new data is done under R using in particular the tidyverse and Biostrings libraries.

Here are some examples of scripts:

PR2 version 5.1.1 that includes the eKOI database - PR2 primers version 2.1.0

Mon, 27 Oct 2025 00:00:00 +0000

We are pleased to announce the release of PR² version 5.1.1.

This release includes a web interface to version 1.0 of the Eukaryotic mitochondrial cytochrome oxidase subunit I gene (eKOI) database is now integrated in the Web interface.

Please note that the flat files for the SSU rRNA genes have very little changes. So you can use either version 5.1.0 or 5.1.1 to annotate metabarcoding data.

González-Miguéns, R., Gàlvez-Morante, À., Skamnelou, M., Antó, M., Casacuberta, E., Richter, D.J., Lara, E. et al. 2025. A novel taxonomic database for eukaryotic mitochondrial cytochrome oxidase subunit I gene (eKOI), with a focus on protists diversity. Database (Oxford). 2025:baaf057.

Also at the same time we are releasing version 2.1.0 of the pr2-primers database which now uses PR2 version 5.1.1 as its reference database for in silico amplification.

Please let us know of any problem you encounter with this release on GitHub.

metaPR2 version 3.0.0

Fri, 26 Sep 2025 00:00:00 +0000

We are very pleased to announce version 3.0.0 of the metapr2 database.

This version contains 8 new datasets from the Arctic and the South-West Pacific
ASVs are now assigned with PR2 database version 5.1 released last spring.

More information here

Please let us know of any problem you encounter with this release on GitHub.

PR2 version 5.1.0: Taxonomy, functional annotations and ROD database

Wed, 02 Apr 2025 00:00:00 +0000

We are very pleased to announce the new PR² version 5.1.0.

Very big thanks to all the contributors - see list.

Here are some significant changes:

The web interface now provides access to the ROD database that contains full-length eukaryotic ribosomal operons.
A few taxonomic groups have been updated from work performed during the 2023 Barcelona EukRef workshop and from individual contributions including:
- Picozoa
- Choropicophyceae
- Rhodophyta
- Dinophyceae
- Foraminifera
A large number of newly published GenBank sequences have been added
Some functional traits have been added:
- HAB (Harmful Algal Bloom) species
- ecological function - from Sommeria-Klein et al. 2021
Some changes have been also done to the web interface allowing more options to select sequences.

The complete list of changes is available from here.

Please let us know of any problem you encounter with this release on GitHub.

Annotation Workshop Barcelona 2023

Sun, 25 Jun 2023 00:00:00 +0000

Our fourth EukRef workshop took place at the Institute of Marine Sciences in Barcelona, Spain from July 3 to July 7 2023.

The workshop was made possible thanks to the generous contribution of the Moore Foundation.

Organizers

Javier del Campo, Barcelona
Daniel Vaulot, CNRS Roscoff
Chris Lane, University of Rhode Island

Participants

Tomas Panek, Charles University in Prague
Sebastian Metz, University of York
Lilith South, UBC Vancouver
Eric Salomaki, Brown University
Tristan Henderson, Michigan State
Nina Pohl, Umea University
Anthony Bonacolta, University of Miami
Liz Cooney, UBC Vancouver
Cédric Berney, Barcelona
Ramon Massana, Barcelona
Jesus Lozano, Barcelona
Pierre Ramond, Barcelona
Joana Krause, Barcelona
Mattia Giacomelli, Barcelona
Sofiya Bondarenko, Barcelona

Schedule

Group annotated

Archaeplastida
- Picozoa
- Chloropicophyceae
- Picocystophyceae
- Trebouxiophyceae
- Chlorodendrophyceae
- Ceramiales
- Batrachospermales
Metazoa
- Cnidaria
- Ctenophora
- Ctenophora
- Porifera
- Chelicerata
Alveolata
- Suessiales
- Dinophyceae
- Apicomplexa
- Chrompodellids
- Alveolata_X
Amoebozoa
- Archamoebea
- Eumycetozoa
- Variosea
- Tubulinea
- Centramoebia
- Flabellinia
- Stygamoebida
Fungi
- Microsporidia
- Nucleophaga
- Chytridiomycota

Data

GitHub repository

metaPR2 version 2.1.0

Mon, 15 May 2023 00:00:00 +0000

To finalize the update of the different interconnected PR2 databases, we are very pleased to announce version 2.1.0 of the metapr2 database.

This version contains the same set of samples and metabarcodes (ASVs) than metapr2 version 2.0 but ASVs are now assigned with PR2 database version 5.0.0 that implements a new taxonomy structure with 9 levels instead of 8.

Please let us know of any problem you encounter with this release on GitHub.

PR2-primers version 2.0.0

Sat, 15 Apr 2023 00:00:00 +0000

We are very pleased to announce the new pr2-primers version 2.0.0.

The major change is the use of PR2 database version 5.0.0 that implements a new taxonomy structure with 9 levels instead of 8. Moreover the inclusions of prokaryotic and plastid sequences in PR2 allows to test primers against these groups.

The application should also load faster because of the use the qs R library for file storage.

Finally 24 primers and 9 primer sets have been added to the database.

Please let us know of any problem you encounter with this release on GitHub.

PR2 version 5.0.0: 9 levels taxonomy and other changes

Thu, 06 Apr 2023 00:00:00 +0000

We are very pleased to announce the new PR² version 5.0.0.

Very big thanks to all the contributors - see list.

Taxonomy evolving from 8 to 9 levels

The eukaryotic tree. From Burki et al. 2020. The New Tree of Eukaryotes. Trends in Ecology & Evolution. DOI: 10.1016/j.tree.2019.08.008.

Eukaryote taxonomy is evolving very quickly fostered by the discovery of novel taxa and by phylogenomics. Therefore the structure of taxonomy database needs to evolve to reflect these changes. Following the structure outline by Burki et al. (2019) we modified the primary structure of the PR2 database adding a new level subdivision between division and class. Moreover the top level previously called kingdom has been renamed to domain. These changes and their rationale are detailed in the following article.

Taxonomy updates

The taxonomy of a number of major groups has been updated.

Bacteria and Archaea

Supergroups have been added.

Stramenopiles

Diatoms: Classes which were missing from previous versions have been added from WoRMS and Algaebase.
Chrysophyceae: The taxonomy of the full class has been updated.
Olisthodiscophyceae : new class added.

Alveolates

Ciliates: Finally Spirotrichea have been updated to be coherent with the other ciliates groups as annotated in the EukRef workshop of 2016 and new sequences added.
Dinoflagellates: A number of groups have updated taxonomy and new sequences added.
Perkinsea: The taxonomy of the group has been completely updated and new sequences added.

Fungi

Chytrids and Fungi_X: Taxonomy has been completely edited and new sequences added.

Others groups

New organelles sequences (plastids and mitochondria)
Spumellaria, Percolomonads, Picozoa, Microsporidia: taxonomy updated and sequences added
Myxogastria taxonomy updated.
New supergroup added: Provora

Link to other databases

Although PR2 tries to keep updated annotations, it is necessary to also correlate this information such as Silva or EukRibo, a newly developed SSU rRNA database. Another important link is with functional traits associated to the taxa or to the sequences. Although some of the fields of PR2 provide some functional information, novel database are developed such as the Mixoplankton Database which provides a reference list of planktonic taxa wit mixotrophic capacity. In this new update of PR2 we have linked this information to the PR2 entries. More will come in the future as more functional databases are developed.

Eukribo

EukRibo is a new database that has developed by Berney et al. (2023) and available from Zenodo. It is characterized by a very high quality of annotation. It also labels sequences that contain either the V4 or V9 region.

Please see this tutorial to make use of this new PR2 feature.

Mixoplankton Database

The Mixoplankton Database (MDB, DOI 10.5281/zenodo.7560582) has been developed by Mitra et al. 2023 (https://doi.org/10.1111/jeu.12972). It tabulates species that belong to the mixoplankton. This database has been linked to the PR database which contains a new field called mixoplankton: * CM - Constitutive Mixoplankton * GNCM - Generalist Non-Constitutive Mixoplankton * pSNCM - plastidic Specialist Non-Constitutive Mixoplankton * eSNCM - endosymbiotic Specialist Non-Constitutive Mixoplankton

Please see this tutorial to make use of this new PR2 feature.

WoRMS database

WoRMS database is an authoritative and comprehensive list of names of marine organisms, including information on synonymy. The content of WoRMS is controlled by taxonomic and thematic experts, not by database managers. For species in PR2 that have an entrin WoRMS we have now added a link to the AphaID (worms_id field) as well as information on the distribution of the species (maine, brackish, freshwater, terrestrial).

The complete list of changes is available from here.

Please let us know of any problem you encounter with this release on GitHub.

PR2 version 4.14.1: new web interface.

Fri, 25 Nov 2022 00:00:00 +0000

The web interface allows to download sequences and metadata from specific taxonomic groups. There is no change in the database itself.

metapr2 - version 2.0 is released.

Wed, 23 Nov 2022 00:00:00 +0000

See major changes here

PR2 scientific committee meeting by Zoom - 2022-11-10.

Wed, 09 Nov 2022 00:00:00 +0000

Participants: ramonm@icm.csic.es” ramonm@icm.csic.es; “Parfrey, Laura” lwparfrey@botany.ubc.ca; “Luciana Santoferrara” Luciana.Santoferrara@hofstra.edu; “kolisko@paru.cas.cz” kolisko@paru.cas.cz; “Javier del Campo” fonamental@gmail.com; “Ian Probert” probert@sb-roscoff.fr; “Guillou Laure” laure.guillou@sb-roscoff.fr; “Geisen, Stefan” stefan.geisen@wur.nl; “Fabien Burki” fabien.burki@ebc.uu.se; “Adriana Lopes dos Santos (Asst Prof)” adriana.lopes@ntu.edu.sg

Full list of PR2 team can be found here: https://pr2-database.org/team/

Presentations

Daniel: the current state of the PR2 ecosystem (see attached pdf)
Javier: the future implementation of PR2_annotation, the successor of EukRef pipeline (see attached pdf)

Open discussion

Annotation

Laura suggested to better acknowledge annotators. Daniel mentioned that they already appear in the web site. One easy way to acknowledge them better would be to put them as co-authors to the Zenodo release which has DOI number (just checked this is really easy to do…)
We should try to have an annotation workshop in 2023 in Barcelona which may be funded by the Moore Foundation. The new implementation of EukRef should make things more easy and efficient.
Fabien asked how sequences were added to PR2. Daniel answered that at present it was a bit random and really dependent on the annotators.
Ian suggested to have confidence levels for sequences. We have now “reference” sequences but this is not really very well managed. This could be maybe improved during a workshop by testing a confidence level system
Ramon mentioned that there were some chimera in Stramenopiles in particular some in the last part of the sequence in V9. He will try to report them as time goes.

Improvements

Number of taxonomic levels - We discussed whether we should increase the number of levels to accommodate recent changes at the root of the eukaryotic tree. Daniel think this not a good idea as more levels make annotation more complex. However, Daniel proposed that the work which has been done with Fabien, Mahwash and Javier will be adapted for the current eight levels. In fact Ramon is using a reduced number of levels which he thinks is often more adapted for analysis. He will send an example to Daniel for possible implementation into PR2.
Long reads - Everyone agreed that it would be interesting to add long reads in view of the current development of long read metabarcoding. Javier proposed to provide a first set of several thousands full operon sequences he extracted from genomes. The idea of adding data from metagenomes would need to be carefully examined. Adriana mentioned the existence of chimera in MAG assembled from Tara. In contrast Ramon indicated that he obtained full operon from sorted cells using PacBio sequencing which were of very good quality. Initially the long reads will not be annotated but we could also extract the different genes (18S, 28S, ITS1 and 2) without modifying too much the structure of the database since the PR2 accession number is based on the GenBank accession number plus the localization of the sequence (start_end).

Project structure

Daniel proposed to reduce the “Core Team” to Daniel and Javier and to have Fred Mahé and Laure part of the Scientific Committee (SC).
In addition Adriana, Stefan and Ian will be part of the SC.
The SC should try to meet more often (at least once every 6 months) and maybe also for specific topics.

Funding

It is critical at least to fund at least the infrastructure (MySQL database, Google Cloud virtual machine) which would be around 3 to 4,000 euros per year.
One idea that emerged could be to link PR2 to the Roscoff Culture Collection which will ensure long term survival of the structure as well as the possibility to more easily get funding. in fact Silva is now moving under the umbrella of the DSMZ and we could discuss collaboration with them.

Presentations

metapr2 - a new 18S metabarcode database.

Mon, 01 Aug 2022 00:00:00 +0000

The pr2-primers web interface.

We are very pleased to announce the new metaPR² metabarcode database.

In recent years, metabarcoding has become the method of choice for investigating the composition and assembly of microbial eukaryotic communities. The number of environmental datasets published has increased very rapidly. Although unprocessed sequence files are often publicly available, processed data, in particular clustered sequences, are rarely available in a usable format. Clustered sequences are reported as operational taxonomic units (OTUs) with different similarity levels or more recently as amplicon sequence variants (ASVs). This hampers comparative studies between different environments and datasets, for example examining the biogeographical patterns of specific groups/species, as well analysing the genetic micro-diversity within these groups. We developed the metaPR² database of processed 18S rRNA metabarcodes that are annotated with the PR² reference sequence database. Version 1.1 of the database contains 41 datasets corresponding to more than 4,000 samples and 90,000 ASVs. The database, which is accessible through both a web-based interface (https://shiny.metapr2.org) and an R package, should prove very useful to all researchers working on protist diversity in a variety of systems.

Resources

Releated projects

Ocean Barcode Atlas - Restricted to Tara V9 and Malapsina V4; taxonomy not up to date.
GlobalFungi - Using the ITS markers and the UNITE reference database.
MyGOD - The aim of the VDGOB project is to provide interfaces to visualize, explore, analyze and interpret Genomic Observatories data.

Maintainers

Daniel Vaulot: vaulot@gmail.com
Adriana Lopes dos Santos: lopesas.ufrj@gmail.com

Citation

Vaulot, D., Sim, C.W.H., Ong, D., Teo, B., Biwer, C., Jamy, M., Lopes dos Santos, A., 2022. metaPR2: a database of eukaryotic 18S rRNA metabarcodes with an emphasis on protists. Molecular Ecology Resources. DOI: 10.1111 / 1755-09

PR2 version 4.14.0

Fri, 25 Jun 2021 00:00:00 +0000

We are very pleased to announce the new PR² version 4.14.0.

Very big thanks to all the contributors (Alex Schoenle, Miguel Sandin - Radiolaria, Raphael Morard, Frédéric Mahé, Anna Maria Fiore-Donno) and especially Javier del Campo who curated three important groups (Apicomplexa, Labyrinthulids and Excavata) …

A single SSU database

The most important change of this version is that we are now providing a single SSU database which contains sequences for:

18S rRNA from nuclear and nucleomorph
16S rRNA from plastid, apicoplast, chromatophore, mitochondrion
16S rRNA from a small selection of bacteria

We have added about 7,000 bacterial sequences so that the database can now be used to detect bacterial sequences that are amplified with either 18S or “universal” (i.e. amplifying both 18S and 16S) rRNA primers. These sequences can be further assigned with Silva or GTDB.

In order to allow correct assignation with software such as DECIPHER (IDTax), each taxonomy level is appended with 4 letters corresponding to the organelle (e.g. Chlorophyceae:plas for a sequence from the plastid assigned to Chlorophyceae).

Organelle	Taxonomy suffix
nucleus
nucleomorph	:nucl
plastid	:plas
apicoplast	:apic
chromatophore	:chrom
mitochondrion	:mito

Taxonomy updates

The taxonomy of a number of major groups has been updated:

Apicomplexa
Labyrinthulids
Radiolaria
Foraminifera
Radiolaria

The complete list of changes is available from here.

DECIPHER training set

DECIPHER is package that provides a function (IDTaxa) to assign metabarcodes. This function is quite fast once a training set has been created. We now provide a trained data set as well as a tutorial on how to create a training set and use it to assign metabarcodes.

Please let us know of any problem you encounter with this release on GitHub.

PR2 version 4.13.0

Wed, 17 Mar 2021 00:00:00 +0000

We are very pleased to announce the new PR² version 4.13.0. This version is a minor release focusing on updating the taxonomy and adding new sequences from the following groups.

Dinophyceae, Suessiales (J. del Campo)
Stramenopiles, Diatoms, Thalassiosirales (L. Arsenieff)
Stramenopiles, Pelagophyceae (Ana Maria Cabello)
Stramenopiles, Chrysophyceae (D. Vaulot)

We have also added some new sequences from cultures from the Roscoff Culture Collection and sequences from the Silva database that were identical to existing sequences in PR2. We removed sequences that were either potential chimera or contained more than 2 consecutives N. Finally we added one field adding the Silva taxonomic annotation when available and a small tutorial on how to use this feature has been added the R package documentation.

The complete list of changes is available from here.

We will be soon releasing a new update with more taxonomical updates, stay tuned.

Please let us know of any problem you encounter with this release on GitHub.

Announcing pr2-primers - a new interactive primer database.

Fri, 15 Jan 2021 00:00:00 +0000

The pr2-primers web interface.

The PR² primer database database lists about 180 primers and 80 primer pairs that have been used for eukaryotic 18S rRNA metabarcoding. Performance of primer pairs was tested against two sequence databases: PR2 for eukaryotes and a subset of Silva for prokaryotes. This allowed to determine the taxonomic specificity of primer pairs, the location of mismatches as well as amplicon size. We developed a R-based web application that allows to browse the database, visualize the taxonomic distribution of the amplified sequences with the number of mismatches, and to test any user-defined primer set.

Maintainers

Daniel Vaulot: vaulot@gmail.com
Fréderic Mahé: frederic.mahe@cirad.fr

Citation

Vaulot, D., Mahé, F., Bass, D., & Geisen, S. (2021). pr2-primer : An 18S rRNA primer database for protists. Molecular Ecology Resources, in press. DOI: 10.1111 / 1755-0998.13465

R package web site

Sat, 01 Aug 2020 00:00:00 +0000

We are very pleased to announce that the PR² web site R package has now a documentation web site which has been built with the R package pkgdown. It contains the documentation of the package as well as news about updates and tutorials.

To access it: https://pr2database.github.io/pr2database

Welcome to the new PR2 web site

Fri, 13 Dec 2019 00:00:00 +0000

We are very pleased to announce the new PR² web site. This new website represents a new phase in the life of the project. For months we have been quietly updating the database and releasing new versions on regular basis. We are going to keep doing so but from now on we will announce our releases trough the website, our twitter account @PR2database and our mailing list. PR² is going to be an active and lively database in constant communication with our final users in order to improve it continuously. We would like to build a community around the PR² database that includes a wide range of people interested in protists and more widely eukaryotes, from clinical parasitologists to taxonomists and microbial ecologist in order to provide the best curated data and the best tools. As well, another important change in this new phase of PR² is the integration with EukRef, the 18S annotation initiative, that was announced some months ago. This integration is already happening but one of the most obvious signs of this merge will happen now when the EukRef website will disappear and all the contents will be available from now on at the PR² web site. The eukref.org domain will remain active and will be redirecting to the PR² web site.

You will find on the Web site the information which was previously on the PR² wiki pages as well as on the EukRef web site plus novel information, including:

Please get back to us for any problem you may find or if you have suggestions or comments to improve the site.

The Scientific Committee of PR2 has been formed

Sun, 24 Nov 2019 00:00:00 +0000

We have very pleased to announce the establishment of the PR2 scientific committee which is composed of:

Laura Parfrey - University of British Columbia, Canada
Fabien Burki - Uppsala University, Sweden
Bente Edvardsen - U. of Oslo, Norway
Martin Kolisko - Institute of Parasitology, Czech Republic
Ramon Massana - ICM, Barcelona, Spain
Luciana Santoferrara - University of Connecticut, USA
Fabrice Not - CNRS Roscoff, France

Thanks you all for accepting to guide the future development of PR2²

See the full PR2² team

PR2 version 4.12

Thu, 08 Aug 2019 00:00:00 +0000

Contributors

Javier del Campo - U of Miami - Apicomplexa
Ramon Massana - ICM, Barcelona - Stramenopiles
Daniel Vaulot - CNRS Roscoff - Metadata geolocalisation - based on a idea of Margaret Brisbin
Johan Decelle and Daniel Vaulot - CNRS Grenoble and Roscoff - Plastid sequences (PhytoRef database)
Chetan Gaonkar - Naples - Chaetoceros - with help from B. Edvardsen

Database structure

Table pr2_main - add fields
- gene - 18S_RNA, 16S_RNA
- organelle - nucleus, plastid, mitochondria, nucleomorph, apicoplast (left empty for cyanobacteria)
Table pr2_metadata - add or modify fields
- gb_organelle - import the corresponding gb field
- pr2_sequence_origin - add other possibilities such as genome and metagenome
- pr2_continent, pr2_country, pr2_country_lat, pr2_country_lon - geographical origin extracted from gb_country field
- pr2_location, pr2_location_lat, pr2_location_lon - geographical origin extracted from gb_country field.
- pr2_ocean, pr2_sea, pr2_sea_lat, pr2_sea_lon - extracted from gb_country field and gb_isolation_source
Table pr2_sequences - add fields
- sequence_hash - hash value of the sequence (using R function digest::sha1, see https://cran.r-project.org/web/packages/openssl/vignettes/crypto_hashing.html)
Table pr2_taxonomy - add fields
- taxon_trophic_mode - detailed trophic mode (e.g. “C-fixation constitutive; Mixotroph”)

Clean up

1692 sequences that had more than 2 consecutive “NN” have been removed

Files provided

We are now providing separate files for 18S nuclear and 16S plastid sequences for UTAX, dada2, fasta and mothur/Qiime formats.
The merged file contains both 18S and 16S sequences.
The metadata file is not provided any more since metadata can be found in the merged file.
The whole pr2 database is also provided as an SQLite file. It contains the different tables making up pr2.

Taxonomy changed

Apicomplexa
- Taxonomy completely revised following del Campo et al. (2019)
- New sequences: 2619
- Updated sequences: 5889+239
- Removed sequences: 89
Stramenopiles - Higher ranks changed according to Massana et al. 2014, Derelle et al 2016, and Adl et al. 2019 compiled by R. Massana.
Diatoms - Chaetoceros - 196 new sequences have been added from Gaonkar et al. (2019) with help from B. Edvardsen
Chlorophyta
- Mamiellophyceae - Micromonas clades have been updated according to Tragin and Vaulot 2019.
- Prasinophytes clade IX - Separation between clades IXA and IXB removed waiting for analysis.
Cryptophyceae - Cryptomonadales moved from family to order.
Cercozoa - Class Chlorarachniophyceae replaces Filosa-Chlorarachnea

Plastid 16S sequences and cyanos

Data originate from the PhytoRef database (Decelle et al. 2015). Taxonomy has been harmonized with the PR2 taxonomy framework. In particular going from 12 levels to 8 taxonomy levels. This integration of plastid sequences should be helpful to researchers that get metabarcodes for both 16S and 18S rRNA. * 16S plastid sequences added: 6049 * 16S cyanobacteria sequence added: 42

Metadata

Sequence geo-localisation : Following up on the very good post of Margaret Brisbin, the geoname server (http://www.geonames.org/export/geonames-search.html) and the fuzzywuzzy Python library has been used to provide information about sequence location origin. Country and/or ocean are now provided for 90,788 GenBank entries with countries/ocean coordinates.

References

Adl, S.M., Bass, D., Lane, C.E., Lukeš, J., Schoch, C.L., Smirnov, A., Agatha, S. et al. 2019. Revisions to the Classification, Nomenclature, and Diversity of Eukaryotes. J. Eukaryot. Microbiol. 66:4–119.
Decelle, J., Romac, S., Stern, R.F., Bendif, E.M., Zingone, A., Audic, S., Guiry, M.D. et al. 2015. PhytoREF: a reference database of the plastidial 16S rRNA gene of photosynthetic eukaryotes with curated taxonomy. Mol. Ecol. Resour. 15:1435–1445.
Derelle, R., López-García, P., Timpano, H. & Moreira, D. 2016. A Phylogenomic Framework to Study the Diversity and Evolution of Stramenopiles (=Heterokonts). Mol. Biol. Evol. 33:2890–8.
Gaonkar, C.C., Piredda, R., Minucci, C., Mann, D.G., Montresor, M., Sarno, D. & Kooistra, W.H.C.F. 2018. Annotated 18S and 28S rDNA reference sequences of taxa in the planktonic diatom family Chaetocerotaceae. PLoS One. 13:e0208929.
Massana, R., del Campo, J., Sieracki, M.E., Audic, S. & Logares, R. 2014. Exploring the uncultured microeukaryote majority in the oceans: reevaluation of ribogroups within stramenopiles. ISME J. 8:854–66.
del Campo J., Heger T., Rodríguez-Martínez R., Worden AZ., Richards TA., Massana R., Keeling PJ. 2018. A new framework for the study of apicomplexan diversity across environments. bioRxiv 1. DOI: 10.¹¹⁰¹⁄₄₉₄₈₈₀.

R Scripts used

About EukRef

Thu, 08 Aug 2019 00:00:00 +0000

In 2001 the first clone library based eukaryotic environmental surveys were published using the 18S rRNA gene as a barcode. Since then a lot of studies have used this approach to describe protistan communities in a wide range of environments. The emergence of high-throughput sequencing (HTS) techniques has made this approach even easier to apply. Consequently, the amount of data retrieved has dramatically increased and our knowledge of diversity is ever increasing. But there are pitfalls behind the HTS approaches, which require using, and trusting, reference databases to annotate our data. These databases sometimes contain curation errors and other mistakes that potentially alter our overall view of protistan diversity within and across ecosystems.

The 18S rRNA Collaborative Annotation Initiative is a community-wide effort that addresses these challenges by bringing together people with expertise in diverse eukaryotic lineages to curate 18S rDNA data using phylogenetic methods. Our goal is to assemble a curated reference database spanning the eukaryotic tree of life. This will be a community resource consisting of curated sequences, flexible taxonomy, phylogenetic trees and their underlying sequence alignments. This database will increase the power of HTS-based studies to uncover fundamental patterns in microbial ecology and diversity. Along the way, individual curators are quite likely to identify novel eukaryotic clades and gain new insight into the environmental distribution patterns of eukaryotic microbes.

Eukref pipeline

Curators

EukRef curators

Workshops

Constructing your EukRef database

Thu, 08 Aug 2019 00:00:00 +0000

During the curation phase, you will go back and forth between your tree, a tab delimited database file, and the literature to curate taxonomy strings and add environmental metadata. You should work with the database file in excel or similar program. Remember to save often and back up this file.

Database Structure

At its most basic, your database will consistent the GenBank accession number, taxonomy, species (or clone) name, and environmental metadata in tab delimited format. The taxonomy and environmental metadata will each be composed of multiple columns. You will modify these through your curation efforts using your tree and additional information as necessary. You must keep track of annotation decisions and sources in a notes file so these can be documented in publications and/or used as the reference in the future. In the curation pipeline, you used the script eukref_gbmetadata.py to pull most of the following information from GenBank. This is your starting point for manual curation.

Structure of your metadata database

See example file on the ciliates ciliates_metadata_db.

Accession: In all cases use the GenBank accession number as the sequence identifier.

Taxonomy: see the EukRef Classification guidelines.

Unlimited ranks: The curated taxonomy should be included in your database as multiple columns, with each column being roughly equivalent in level (evolutionary distance). You can use as many columns as needed.
Gaps in the taxonomy: Of course, not all lineages require the same number of ranks, so you will have gaps. Deal with these by repeating the rank below (column to the right). Blanks will cause problems during annotation.
Initial population of taxonomy: Taxonomy strings can originally be populated using GenBank taxonomy.

For more information regarding Taxonomy check our Classification guidelines.

Name: Species name or clone name from GenBank. Even if the species/genus name is wrong! You should correct the name in the taxonomy entries.

Metadata: Use the automatically entered metadata columns from the eukref_gbmetadata.py script as a starting point, and add the columns requested below. You can add additional columns that are informative. Information will come from the GenBank entry and also from the publications related to this sequence. Columns requested document the origin of the sequence and the environmental information pertaining to this sequence. You will have several categories of metadata information. This information will enable you to make ecological insights from your database. We adopted standardized metadata annotation: MIxS (Minimum Information about any (x) Sequence) and EnvO (Environmental Ontology):

source*: does this sequence come from a culture or an environmental sequence? Three options here: [culture | isolate | environmental]. You can add this information by parsing the source column.
env_material: The environmental material level refers to the material that was displaced by the sample, or material in which a sample was embedded, prior to the sampling event. Environmental material terms are generally mass nouns. Examples include air, soil, or water. EnvO (v 2013-06-14) terms can be found via the link: www.environmentontology.org/Browse-EnvO. You can add this information by parsing the environmental_sample column.
env_biome: Biomes are defined based on factors such as plant structures, leaf types, plant spacing, and other factors like climate. Biome should be treated as the descriptor of the broad ecological context of a sample. Examples include: desert, taiga, deciduous woodland, or coral reef. EnvO (v 2013-06-14) terms can be found via the link: www.environmentontology.org/Browse-EnvO. You can add this information by parsing the environmental_sample column.
biotic_relationship: [free living|parasite|commensal|symbiont]. You can infer this information from the host column.
specific_host: For symbiotic lineages. Host taxonomy ID (taxid) from NCBI. Should be automatically populated with eukref_gbmetadata.py script. If it is not, search at NCBI using the host as the query.
geo_loc_name: The geographical origin of the sample as defined by the country or sea name followed by specific region name. Country or sea names should be chosen from the INSDC country list, or the GAZ ontology (v 1.512). You can add this information by parsing the country and environmental_sample column.

source is not MIMARKS items

If you have any question or suggestion please feel free to add it to the comment section below, visit our forum or send us an e-mail

EukRef curators

Thu, 08 Aug 2019 00:00:00 +0000

Amoebozoa

Curator	e-mail	Affiliation	Group to curate
Matt Brown	mbrown[a]biology.msstate.edu	Mississippi State University	Coordinator
Anna Maria Fiore-Donno	afiore-donno6[a]infomaniak.ch	University of Cologne	Myxogastria
Thierry Heger	thierry.heger[a]changins.ch	CHANGINS	Arcellinida
Alexander Kudryavtsev	alexander.kudryavtsev[a]spbu.ru	Saint Petersburg University	Himatismenida
Tomas Panek	mistrpanek[a]seznam.cz	Charles University in Prague	Archamoebae
Alexander Tice	at1422[a]msstate.edu	Mississippi State University	Variosea (Evosa)
Tomas Tyml	tomastyml[a]gmail.com	Joint Genome Institute	Eudiscosea
Laura M. Walker	lmw.bio[a]gmail.com	Washington University in Sant Louis	Myxogastria

Archaeplastida

Green Algae

Curator	e-mail	Affiliation	Group to curate
Frederik Leliaert	frederik.leliaert[a]gmail.com	Botanic Garden Meise	Coordinator / Ulvophyceae: Cladophorales / Dasycladales / Trentepohliales / Bryopsidales
Tatyana Darienko	tdarien[a]gwdg.de	University of Göttingen	Trebouxiophyceae: Chlorellales & Chlorophyceae: DO clade
Charles Bachy	charles.bachy[a]gmail.com	Station Biologique Roscoff - CNRS	Palmophyllophyceae / Nephroselmidophyceae / Pedinophyceae
Thais Garcia da Silva	thais.garcia.bio[a]gmail.com	Universidade Federal de São Carlos	Chlorophyceae: Selenastraceae
Sebastian Metz	metz.seba91[a]gmail.com	Universidad Nacional de San Martín	Trebouxiophyceae: Trebouxiales
Thomas Proeschold	thomas.proeschold[a]uibk.ac.at	University of Innsbruck	Chlorophyceae & Ulvophyceae: Ulvales / Ulotrichales
Daniel Vaulot	vaulot[a]gmail.com	Station Biologique Roscoff - CNRS	Chloropicophyceae / prasinophyte clade IX / prasinophyte clade VIII / Mamiellophyceae

Red Algae

Curator	e-mail	Affiliation	Group to curate
Sandra Lindstrom	sandra.lindstrom[a]botany.ubc.ca	University of British Columbia	Rhodophyta
Eric Salomaki	eric.salomaki[a]gmail.com	Institute of Parasitology Biology Centre - ASCR	Rhodophyta

Cryptista

Curator	e-mail	Affiliation	Group to curate
Fabien Burki	fabien.burki[a]ebc.uu.se	Uppsala University	Kathablepharida
Markus Majaneva	markus.majaneva[a]gmail.com	University of Helskinki	Cryptomonadales

Excavates

Curator	e-mail	Affiliation	Group to curate
Vera Tai	vtai4[a]uwo.ca	University of Western Ontario	Coordinator / Parabasalia & Oxymonads
Olga Flegontova	olga[a]paru.cas.cz	Institute of Parasitology Biology Centre - ASCR	Kinetoplastea
Anna Karnkowska	ankarn[a]biol.uw.edu.pl	University of Warsaw	Euglenophyceae
Martin Kolisko	kolisko[a]paru.cas.cz	Institute of Parasitology Biology Centre - ASCR	Metamonada
Gordon Lax	gordon.lax[a]dal.ca	Dalhousie University	Heteronematida (Heterotrophic euglenids + Symbiontida)
Julia Maritz	jmm1005[a]nyu.edu	Merck Exploratory Science Center	Trichomonadea
Tomas Panek	mistrpanek[a]seznam.cz	Charles University in Prague	Discoba except Euglenozoa

Haptista

Curator	e-mail	Affiliation	Group to curate
Fabien Burki	fabien.burki[a]ebc.uu.se	Uppsala University	Centrohelida
Bente Edvardsen	bente.edvardsen[a]ibv.uio.no	Univeristy of Oslo	Haptophyta

Obazoa

Metazoa

Curator	e-mail	Affiliation	Group to curate
Clara Maria Hereu	hereu[a]cicese.mx	Centro de Investigación Científica y de Educación Superior de Ensenada	Urochordata / Thaliacea
Inga Martinek	inga.mw[a]gmail.com	Institute of Parasitology Biology Centre - ASCR	Myxozoa
Konstantina Mitsi	kcmitsi[a]gmail.com	Institut de Biologia Evolutiva UPF-CSIC	Gastrotricha
Alicia Sánchez-Arroyo	alicia.arroyo[a]ibe.upf-csic.es	Institut de Biologia Evolutiva UPF-CSIC	Acoelomorpha

Others

Curator	e-mail	Affiliation	Group to curate
Javier del Campo	jdelcampo[a]rsmas.miami.ed	RSMAS - University of Miami	Unicellular Opisthokonts
Becca Lensing	blensing[a]hawaii.edu	University of Hawaiʻi	Choanoflagellatea
Aaron Heiss	aheiss[a]amnh.org	American Museum of Natural History	Apusomonada and Breviatea
Guiffré Torruella	guifftc[a]gmail.com	Université Paris-Sud	Nucleariidae

Stramenopiles

Diatoms

Curator	e-mail	Affiliation	Group to curate
David G. Mann	d.mann[a]rbge.org.uk	Royal Botanic Garden Edinburgh	Bacillariaceae
Matt Ashworth	mashworth[a]utexas.edu	University of Texas Austin	Diatoms
Andrea de Oliveira da Rocha Franco	andrea_lisandra[a]hotmail.com	Federal University of Rio Grande	Rhaphoneidales
Katarina Kajan	kkajan[a]irb.hr	Ruđer Bošković Institute	Thalassiosirophycidae
Luis Demetrio Mora Hernandez	demetriomora[a]gmail.com	Freie Universität Berlin	Sellaphorineae
Teofil Nakov	teofiln[a]gmail.com	University of Arkansas	Diatoms
Anh Tu Van	anh.van[a]uni-rostock.de	Universität Rostock	Cymbellales

Other Ochrophyta

Curator	e-mail	Affiliation	Group to curate
Chang Jae Choi	cjchoi[a]mbari.org	Monterey Bay Aquarium Research Institute	Pelagophyceae and Dictyochophyceae
Javier del Campo	jdelcampo[a]rsmas.miami.ed	RSMAS - University of Miami	Chrysophytes
Samuel Starko	samuel.starko[a]gmail.com	University of Victoria	Phaeophyceae and Xantophyceae
Vasily Zlatogursky	v.zlatogursky[a]gmail.com	Saint Petersburg University	Actinophrydae

Heterotrophic Stramenopiles

Curator	e-mail	Affiliation	Group to curate
Vincent Billy	vbilly[a]zoology.ubc.ca	University of British Columbia	Opalozoa
Javier del Campo	jdelcampo[a]rsmas.miami.ed	RSMAS - University of Miami	Labyrinthulomycetes
Ramon Massana	ramonm[a]icm.csic.es	Institut de Ciències del Mar - CSIC	MAST

Alveolates

Dinoflagellates

Curator	e-mail	Affiliation	Group to curate
Solenn Mordret	solenn.mordret[a]szn.it	Stazione Zoologica Anton Dohrn	Coordinator / Amphidomataceae
Hiroshi Funaki	hiroshifunakisci[a]gmail.com	Ehime University	Gonyaulacales
María García Portela	maria.garcia[a]ieo.es	Spanish Institute of Oceanography	Dinophysales
Elisabeth Hehenberger	helisabe[a]mail.ubc.ca	University of British Columbia	Suessiales
Albert Reñé	albertrene[a]icm.csic.es	Institut de Ciències del Mar - CSIC	Gymnodiniales
Teng Sing Tung	tsteng[a]unimas.my	Universiti Malaysia Sarawak	Kareniaceae
Lu Wang	607wanglu[a]sina.com	University of Connecticut	Alexandrium

Ciliates

Curator	e-mail	Affiliation	Group to curate
Vittorio Boscaro	vittorio.boscaro[a]gmail.com	University of British Columbia	Coordinator / Postciliodesmatophora
Eleni Gentekaki	gentekaki.ele[a]mfu.ac.th	Mae Fah Luang University	Ciliophora
Luciana Santoferrara	luciana.santoferrara[a]uconn.edu	University of Connecticut	Oligotrichia and Choreotrichia
Qiangqian Zhang	qqzhang[a]yic.ac.cn	Yantai Institute of Coastal Zone Research - CAS	Ciliophora

Others

Curator	e-mail	Affiliation	Group to curatee
Javier del Campo	jdelcampo[a]rsmas.miami.ed	RSMAS - University of Miami	Apicomplexa and Chrompodellids
Évelyne Derelle	evelyne.derelle[a]univ-brest.fr	Station Biologique Roscoff - CNRS	Perkinsea

Rhizaria

Curator	e-mail	Affiliation	Group to curate
David Bass	d.bass[a]nhm.ac.uk	Cefas and Natural History Museum	Coordinator / Endomyxa
Cedric Berney	cedric.berney[a]sb-roscoff.fr	Station Biologique Roscoff - CNRS	Endomyxa
Clément Duckert	clement.duckert[a]unine.ch	Université de Neuchâtel	Euglyphida
Kenneth Dumack	kenneth.dumack[a]uni-koeln.de	University of Cologne	Cercozoa (Thecofilosea)
Raphael Morard	rmorard[a]marum.de	University of Bremen	Foraminifera (Planktonic)
Magali Schweizer	magali.schweizer[a]univ-angers.fr	Université d’Angers	Foraminifera (Rotaliida)
Ivan Voltski	ivanku[a]post.bgu.ac.il	Zoological INstitute - RAS	Foraminifera (Allogromida)
Vasily Zlatogursky	v.zlatogursky[a]gmail.com	Saint Petersburg University	Clathrulinidae

Others

Curator	e-mail	Affiliation	Group to curate
Aaron Heiss	aheiss[a]amnh.org	American Museum of Natural History	Ancyromonads
Mary Thaler	mary.thaler.1[a]ulaval.ca	Universitè Laval	Picozoa and Cryomonadida and Telonemia

Pipeline overview

Thu, 08 Aug 2019 00:00:00 +0000

A. IN-HOUSE INSTALLATION

Software needed.

Tools necessary to install to run the pipeline are listed below. You should install each of these programs on your computer.

usearch (version 7.01 or 8.*; free 32-bit version is fine)
vsearch
MAFFT; If preferred other software like SINA* or INFERNAL can be also used
trimAL (version 1.2)
RAxML (version 8 or newer). You can find some tips on the use of RAxML at the bottom of the page.
FastTree
BLAST+ (version 2.2.22)
Python (should already be installed)
Biopython
AliView
FigTree
EukRef pipeline

Please remember, if you choose to use SINA alignment, that you have to provide a reference alignment in ARB format. Easiest way to get one is to downloaded from https://www.arb-silva.de/download/arb-files/

Use TextWrangler or equivalent text editor for taking notes about the curation process, modifying scripts, and viewing files. Do NOT use Word or equivalent.

B. DOWNLOAD AND INSTALL VIRTUAL MACHINE FILE

This is an alternative for users who have trouble installing all the software components or users who just want to get a “ready-to-use” package.

Virtual machine installation:

Step 1. install Vagrant software for your operating system (in Ubuntu and other Linux distributions you can use the distributions package installer, i.e.: sudo apt-get install vagrant).

Step 2. Install the necessary plugin:

vagrant plugin install vagrant-disksize

Step 3. Deploy and start the virtual machine

cat > Vagrantfile <<EOF
Vagrant.configure("2") do |config|
  config.vm.box = "serafimn/eukref"
  config.disksize.size = "80GB"
end
EOF

vagrant up

Step 4. log into the virtual machine

vagrant ssh

Step 5. Download nucleotide NCBI database using provided script

cd eukref
./download_NCBI_nt_db.sh

Step 6. Start using the eukref pipeline

C. EUKREF PIPELINE

This document outlines the procedure for gathering sequences and generating an alignment and tree.

Step 0 - Decide upon the scope of the group you will initially curate

Your group should be of a manageable size in terms of taxonomic breadth and total available sequences (e.g. a subset of Rhizaria or diatoms rather than the entire clade). It will be more useful for you and EukRef in general to finish curation of a smaller group. You can expand later.

Step 1 - Generate a curated starting sequence set, alignment, and tree for your group

This initial sequence set will form the basis of your entire curation effort. Therefore it is critical that these sequences are well-curated, and you need an alignment of these sequences and a reliable phylogenetic tree built from them. There are multiple ways to get this initial sequence set, but in each case, you should ensure it meets the criteria below. Additionally, you need a file that contains diverse outgroups: 5-10 sequences from all of the neighboring clades (e.g., if you are working on ciliates you should include apicomplexa, dinoflagellates, and stramenopiles). This alignment MUST be untrimmed (e.g. contain all gaps) so that additional sequences can be added. The initial tree must be checked to make sure it covers the diversity of the group and reflects phylogenetic relationships expected based on current research/literature. Any errant sequences need to be removed from the alignment.

Criteria for the initial set of sequences, alignment, and tree:

The initial set of sequences should be small, ~200 sequences or fewer, so that you can easily check the resulting alignment and tree.
Sequences should cover the breadth of the clade, including divergent groups.
The alignment and tree should have outgroups included to detect sequences that branch outside of your clade.
The alignment should be untrimmed
The tree produced from this alignment should display expected relationships and problematic sequences should be removed.

Three possible ways to get your initial alignment:

You may already have a curated starting alignment and tree from previous work. In this case, you are ready to go after checking your tree and alignment. Proceed to Step 5.
Download sequences from GenBank based on taxonomy. This will target the sequences from cultured isolates or those that were identified in other ways (e.g. morphologically identified and picked). Proceed to Step 2.
Alternatively, you may wish to start with the SILVA or PR2 set of sequences for your group. You must ensure that these sequences meet the criteria above. Proceed to Step 2.

Step 2. Retrieve an initial set of sequences and cluster

NOTE 1: Users can choose a different similarity threshold if desired. For example, you may wish to work at 99% identity for small clades. In this case, replace 0.97 with 0.99 throughout.

NOTE 2: In all commands, you must substitute your clade name for “NAME”.

2a - Retrieve initial sequences using GenBank, PR2 or SILVA

Recommended: SILVA or PR2 database. Use the grep command to pull out your sequences of interest. Note that clade names often differ in these different databases.

grep –A 1 -i “NAME” silva_reference_database.fasta > NAME.fasta

grep –A 1 -i “NAME” PR2_reference_database.fasta > NAME.fasta

GenBank - use advanced search at NCBI, or add the text below to the NCBI query box. Replace XXXX with the Taxonomy ID. Find the Taxonomy ID by searching NCBI taxonomy:

txidXXXXOrganism:exp NOT (mitochondrial OR mitochondria OR complete genome)

This will target targeted cultured isolates or isolates that were morphologically identified

After you have downloaded your sequences, clean fasta headers to contain the GenBank accession number only.

sed 's/gi\|[0-9]*\|gb\|//' NAMEgb.fasta | sed 's/\..*//' > NAME.fasta

2b - Cluster your sequences to produce a manageable number of sequences using usearch (two commands).

Similarity threshold is set at 97% here but can be adjusted by changing the “-id” command. These commands choose the longest sequence as the representative sequence for each cluster. We will use also this step to remove sequences shorter than 500 bp. You will use these representative sequences for your initial alignment/tree.

usearch -sortbylength NAME.fasta -fastaout NAME.sorted.fasta -minseqlength 500 -notrunclabels

usearch -cluster_smallmem NAME.sorted.fasta -id 0.97 -centroids NAME.clustered.fasta -uc NAME.clusters -notrunclabels

Step 3. Build initial alignment

3a - Assemble a set of close outgroup sequences.

Outgroup sequences must be full-length. You should include outgroups from all of the clades that are neighbors to your group of interest, 5-10 sequences per group. These should be chosen based on your knowledge (ask for help if needed). You can get outgroup sequences from GenBank, SILVA or PR2. See step 2 for details. Add your outgroup sequences to clustered starting sequences (NAME.clustered.fasta file)

3b Align using MAFFT.

Use the default MAFFT algorithm (command below) unless there is a specific reason to use a different algorithm or approach. (Experience users can use different preferred alignment program)

mafft --reorder --auto NAME.clustered.fasta > NAME_aligned.fasta

or use INFERNAL

cmalign --outformat AFA -o NAME_aligned_infernal.fasta SSUref.cmm NAME.clustered.fasta

sed 's/\./-/g' NAME_aligned_infernal.fasta > NAME_aligned.fasta

or use SINA*

./sina -i NAME.clustered.fasta -o NAME_aligned.fasta --outtype fasta --ptdb REFERENCE_ALN.ARB

3c - Trim the alignment using trimal.

trimal -in NAME_aligned.fasta -out NAME.trimal.fasta -gt 0.3 -st 0.001

Step 4. Build an initial tree

4a - Build a phylogenetic tree using RAxML.

raxmlHPC-PTHREADS-SSE3 -T 4 -m GTRCAT -c 25 -e 0.001 -p 31415 -f a -N 100 -x 02938 -n NAME -s NAME.trimal.fasta -w /full/path/to/output_directory

Constraint trees: You can use a constraint tree in RAxML (-g option), which will allow you to “dictate” how some part of the tree should look like based on previously published relationships for your clade, for example, based on morphology and/or multigene phylogeny. Constraint trees should be used with caution and should ONLY constrain robust relationships (those observed in multiple studies) since it is desirable to avoid fitting the tree into your personal favorite topology. All taxa in the constraint tree must be in the alignment and names in the alignment an in the constraint tree must match exactly. Moreover, constraint tree cannot contain taxa not present in the alignment. Constrained trees can be edited in Mesquite.

Alternatively, you can use FastTree, which is very easy to install and gives you “quick and dirty” tree, in case you don’t want to or can’t wait for RAxML tree or in cases when the number of taxa is too high (more than several thousand).

fasttreeMP -gtr -nt NAME.trimal.fasta > NAME.tre

4b - Visualize tree using FigTree.

Identify errant sequences to be removed. Go back to step 3 to refine alignment, remove errant sequences and repeat as necessary until you have a high quality starting initial alignment and tree. If your tree does not reflect known relationships you may wish to use a constraint tree in step 4a. Proceed to step 5 once you are happy with your tree/alignment. You will need the unaligned set of sequences (without outgroups) as input for step 5 (initial_DS.fas).

Step 5. Download databases

5a - databases.tar.gz

Download and unpack databases.tar.gz

tar -xvf databases.tar.gz

Inside the unpacked “databases” directory you will find three files: Reference_DB.fas and gb203_pr2_all_10_28_97p_noorg.fasta, and tax_d.bin. These files are used for filtering results within eukref_gbretrieve.py. All three files must be in the current working directory where you run the eukref_gbrtrieve.py script in Step 6.

5b - Locate a copy of GenBank nt database in use at your institution or on your server.

At the EukRef workshop there is a copy on the Amazon server. GenBank NT should ideally be downloaded to a server. There will be more than 40 files totaling more than 30 GB. Downloading can take several hours. You may wish to install and use a tool like wget. In a workshop setting download one time and allow access for all participants.

Make a new folder called DATABASEFOLDER. From ftp://ftp.ncbi.nlm.nih.gov/blast/db/ download taxdb.tar.gz and all nt.tar.gz files. Also, download all nt_.tar.gz.md5 files.

Unpack with the following command:

for i in nt*; do tar -xvf $i ; done

Run md5 checksum to ensure all files are fully downloaded.

5c - Before running the pipeline run the following commands

export BLASTDB=/path/to/DATABASE_FOLDER

(you can also add BLASTDB to your PATH permanently)

Step 6. Retrieve all sequences that belong to your clade

6a - Run eukref_gbretrieve.py

Run eukref_gbretrieve.py script. This script will run in a loop until no new sequences are retrieved. This may take several hours for large groups.

Inputs:

-i Unaligned fasta file of your clustered starting set of sequences (the output of Step 2, NAME.clustered.fasta). Should be refined version, with any errant sequences detected in tree inspection during Step 4 removed. Should NOT include outgroups. Fasta headers must either be in standard GenBank format (>gi|ginumber|gb|accession| ), or have the accession number followed by a space (>accession )
-dbnt (/path/to/DATABASE_FOLDER/nt)GenBank NT file from Step 5c . -dbsi (Reference_DB.udb)PR2 SSU reference database plus representative bacteria, used for filtering results. Must be in current working directory.
-n Number of sequences retrieved from GenBank per blasted sequence. recommended: 100
-p Number of CPUs.
-g Name of the most inclusive group you are working with from PR2 taxonomy. Find in the PR2 taxonomy file (ReferenceDB.fas) by grep.
-m Blast method. recommended: megablast
-idsi PR2 Blast cut-off (nothing less than 70% similar will be retrieved).
-idnt GenBank Blast cut-off (average similarity to everything on the original database).

Example command, update with your information.

python eukref_gbretrieve.py -i current_DB.fasta -dbnt /scratch/NCBI_NT/nt -dbsi ../../Reference_DB.fas -n 100 -p 8 -g NAME -m megablast -idsi 75 -idnt 90 -td tax_d.bin

Outputs:

Reference set of sequences (current_DB.fas).
Reference sequences with only accessions in header for downstream use (current_DB_final.fas).
List of accession numbers (accessions_current_DB.txt).
A fasta file of short reads (<500 bp), and of chimeras will also be generated.

6b - Format sequences and metadata

Run the eukref_gbmetadata.py script to pull taxonomy and environmental information from GenBank records to 1) generate your initial reference database, and 2) reformat the fasta headers for easier annotation in a tree.

First, download the GenBank format for all sequences retrieved in step 6a from NCBI batch entrez. Upload accessions ( accessions_current_DB.txt). Click the retrieve records link. Click “send to” then download as GenBank(full) file (.gb extension). This will download the gb file for all of your accessions. Save as gb_metadata.gb

Inputs:

-gb Genbank flat file
-i fasta file output from step 6a (current_DB_final.fasta)
–outgroup outgroup fasta file
-t reference taxonomy file (pr2_4.11_full.txt)

python eukref_gbmetadata.py -gb gb_metadata.gb -i current_DB_final.fasta -o annotated_DB_for_tree.fasta -m metadata.txt -t /path/to/pr2_4.11_full.txt --outgroup outgroup_filtered.fasta

Outputs:

metadata.txt: metadata file (tab delimited format) that includes taxonomy from GenBank, reference taxonomy, environmental data available in the GenBank record, and the publication associated with an accession.
annotated_DB_for_tree.fasta: fasta file with headers labeled for easier curation. We will use the PR2 taxonomic strings or alternatively the GenBank taxonomic string if the sequence is not in PR2. The outgroup_filtered.fasta will be added as well to this fasta file.

Step 7. Build an alignment with the reference sequences

7a - Cluster sequences using usearch

usearch -sortbylength annotated_DB_for_tree.fasta -fastaout current_DB.sorted.fasta -minseqlength 64 -notrunclabels

If the FASTA file to be clustered contains long (e.g. genomic) sequences, it is likely that the clustering step will run out of memory. Check the screen output of this “usearch -sortbylength” step, which indicates the length of the longest sequence found within the file; this should not exceed 5,000 (the hard limit imposed in Step 5).[/su_note]

NOTE: you should choose the -id (similarity threshold for clustering) that is appropriate for your group.

usearch -cluster_smallmem current_DB.sorted.fasta -id 0.97 -centroids current_DB.clustered.fasta -uc current_DB.clusters.uc -notrunclabels

7b - Align using MAFFT

If there is not a specific reason to use a different approach to use the default mafft algorithm. See instructions below for alignments with groups known to be difficult.

mafft --reorder --auto current_DB.clustered.fasta > current_DB_aligned.fasta

or use INFERNAL:

cmalign --outformat AFA -o current_DB_aligned_infernal.fasta SSUref.cmm current_DB.clustered.fasta

sed 's/\./-/g' current_DB_aligned_infernal.fasta > current_DB_aligned.fasta

or use SINA*:

./sina -i NAME.clustered.fasta -o NAME_aligned.fasta --outtype fasta --ptdb REFERENCE_ALN.ARB

It is critical to open and check your alignment in Aliview software (or similar) to see if there are misaligned blocks or sequences. Make sure you look at the entire length of the alignment. If the alignment is not good you will not produce a good tree. If you have a poor alignment you can 1) align according to a template (seed) alignment, the command below, or 2) modify your alignment by hand.

If you already have a curated alignment for your group you can use it as a template (seed) to align your new sequences with the following command.

mafft --reorder --genafpair --maxiterate 1000 --retree --anysymbol --seed template_curated_alignment.fasta current_DB.OUTGROUP.clustered.fasta > current_DB_aligned.fasta

Remember to open your alignment file and check before proceeding.

7c - Trim the alignment using trimal

trimal -in current_DB_aligned.fasta -out current_DB_trim.fasta -gt 0.3 -st 0.001

Step 8. Build RaxML trees and clean up

8a - Build a phylogenetic tree using RAxML

NOTE: do not use more threads (-T option) than available processors. Typically no more than 4 on a laptop and potentially many more on a cluster. NOTE: you can add a backbone constraint tree with the option -g. This should be done if clades within your group are always monophyletic in the literature (e.g. in phylogenomic or multigene analyses), but are not monophyletic in 18S trees. The sequences (tips) in this constraint tree must be in your alignment (they should be a subset of your sequences), and the names must match exactly.

raxmlHPC-PTHREADS-SSE3 -T 4 -m GTRCAT -c 25 -p 31415 -x 20398 -d -f a -N 100 -n NAME -s current_DB.trim.fasta –w /full/path/to/output_directory

Alternatively, you can use FastTree (is a faster algorithm in case you don’t want or can’t wait for the RAxML results, it will give you a “quick and dirty” tree).

fasttreeMP -gtr -nt current_DB.trim.fasta > NAME_fasttree.tre

Step 9. Visualize your tree, identify errant sequences that should be removed

Download your tree e.g. “RAxML_bestTree.clade”. Open tree in FigTree and annotate taxa with either “remove” for taxa you wish to remove, or you can modify/add to the existing name. You can only annotate taxa, NOT nodes or clades. You can select entire clades to annotate all taxa at once. Annotated nodes cannot be collapsed (annotations within the collapsed node will not be reported). “Save as” the tree with annotations for example “RAxML_bestTree.clade_annotated.tre”, which is a nexus file.

Inputs:

-t RAxML_bestTree.clade_annotated.tre
-m metadata.txt

python eukref_treeparse.py -t RAxML_bestTree.clade_annotated.tre -m metadata.txt

Output:

metadata_out.txt

The “metadata_out.txt” will be your tab-delimited metadata file with “remove” in the last column for the sequences you want to remove. You can sort your metadata_out.txt file in excel to get all of the accessions of sequences that should be removed from your tree. Save these accessions to be removed in a file called accessions_remove.txt.

Inputs:

-i current_DB.clustered.fasta
-s accessions_remove.txt

python eukref_filter_fasta.py -i current_DB.clustered.fasta -s accessions_remove.txt -o current_DB.cleaned.fasta

Output:

current_DB.cleaned.fasta

Go back to Step 7 to align and build a new tree, repeat until you are happy with your current set of sequences.

Step 10. Build Reference Tree

Once you are happy with the set of sequences in your tree and your alignment you are ready to build your final reference tree. Your final, trimmed alignment is in input into RAxML. NOTE: you can add a backbone constraint tree with the option -g. The sequences (tips) in this constraint tree must be in your alignment (they should be a subset of your sequences), and the names must match exactly.

raxmlHPC-PTHREADS-SSE3 -T 4 -m GTRCAT -c 25 -p 31415 -x 20398 -d -f a -N 100 -n NAME -s final_DB.trim.fasta –w /full/path/to/output_directory

Step 11. Moving from tree to annotations. Expanding annotations to all sequences

11a - Trim your metadata

Use the script eukref_metatrim.py Trim your metadata file to include only representative sequences of clusters – these are the sequences in your tree.

Inputs:

-i current_DB.cleaned.fasta is the fasta file with your clustered sequences containing only the sequences used in your reference tree. -m metadata.txt is your metadata file from eukref_gbmetadata.py.

python eukref_metatrim.py -i current_DB.cleaned.fasta -m metadata.txt -o metadata_ref.txt

Outputs:

-o metadata_ref.txt, which only has the accessions in your reference tree. This will make annotating easier.

11b - Annotate classification

You need to annotate classification your metadata_ref.txt. Note that you should have GenBank taxonomy and SILVA taxonomy in your metadata_ref.txt file so you know the starting point. In many cases, it will be easiest to annotate clades directly on your reference tree. You can annotate the tree and then export annotations to your metadata_ref.txt file using the instructions below.

Download your reference tree e.g. “RAxML_bestTree.clade”. Open tree in FigTree and annotate taxa with the name of the taxon. You can only annotate the taxa, NOT nodes or clades. You can select entire clades to annotate all taxa at once. Annotated nodes cannot be collapsed (annotations within the collapsed node will not be reported). “Save as” the tree with annotations for example “RAxML_bestTree.clade_annotated.tre”, which is a nexus file.

Run script eukref_treeparse.py to add annotations in your tree to your metadata_ref.txt file.

Inputs:

-t RAxML_bestTree.clade_annotated.tre
-m metadata_ref.txt

python eukref_treeparse.py -t RAxML_bestTree.clade_annotated.tre -m metadata_ref.txt

Outputs:

The “metadata_ref_out.txt” will be your tab-delimited metadata file that includes the Accession Number of representative for your clusters and the annotations that you made on the tree in the last column.

11c - Expand your curation

Use the script eukref_metaexpand.py to expand your curation to all sequences within the clusters.

Inputs:

-i metadata.txt is the initial metadata file you got
-r metadata_ref_out.txt is the reference metadata you just added annotations to
-c current_DB.clusters.uc is the cluster file (.uc) from usearch. Use the most recent version if you clustered multiple times.

python eukref_metaexpand.py -i metadata.txt -r metadata_ref_out.txt -c current_DB.clusters.uc -o metadata_ref_expanded.txt

Outputs:

-o metadata_ref_expanded.txt is the expanded annotated metadata file

Step 12. Create a reference database

Now the taxonomy and metadata curation fun begin! See Building your database page for details.

If you have any question or suggestion please feel free to add it to the comment section below, visit our forum or send us an e-mail

RAxML tips

MPI vs. PTHREADS: If you’re running RAxML on your laptop, use PTHREADS. If you’re running RAxML on a server/cluster with a lot of cores (4), please consider using MPI (or HYBRID) version as it allows for better parallelization. In both cases, make absolutely sure that the number of threads/MPI processes you use is equal to the number of CPU cores you have.
GTRCAT vs. GTRGAMMA: GTRCAT model is faster to compute compared to the standard GAMMA model, and might better account for among-site heterogeneity as it has more rate categories (default: 25). However, it shouldn’t be used on alignments with few taxa (<50-100) because of the risk of overparametrization.
+I models: we generally do not recommend using GTRCATI/GTRGAMMAI, since the use two orthogonal approaches to model rate heterogeneity, which might lead to problems in numerical optimization.
Please refer to RAxML manual for further details: http://sco.h-its.org/exelixis/resource/download/NewManual.pdf

Short read annotation

Thu, 08 Aug 2019 00:00:00 +0000

Software needed

Tools necessary to install to run the pipeline are listed below. You should install each of these programs on your computer. Links to software for installations and description can be found at http://eukref.org/tools

QIIME
RaxML (version 8 or newer).
Use TextWrangler, TextEdit or equivalent text editor for taking notes about the curation process, modifying scripts, and viewing files. DO NOT use Word or equivalent.

Note that these are rough guidelines for the moment.

Steps

Align short reads against your reference alignment using QIIME align_seqs.py, then use RAxML-EPA to place short reads in your tree. Input files:

fasta file of unaligned HTES sequences. This can be all eukaryotes or something specific to your group [unaligned_HTESreads.fas]
Curated alignment for your group in fasta format. Must have gaps included – this is your template. [curated_alignment_clade.fas]
Phylogenetic tree based on your curated alignment in newick format. You will need to export your tree as newick from FigTree. [RAxML_bestTreeNAME.tre]

Percent identity threshold – how similar should environmental sequences be to your curated sequences to be kept. We recommend setting this threshold to 90% or 95% initially to only pull out sequences from your clade. However, this should be tested empirically, it will vary by group.

1) Run the align_seqs.py script within QIIME.

align_seqs.py -i unaligned_HTESreads.fas -t curated_alignment_clade.fas -o HTESreads_aligned.fas –p 90

2) Concatenate aligned HTES reads to your curated alignment. The alignment will be used to build the tree.

cat HTESreads_aligned.fas curated_alignment_clade.fas > HTESreads_aligned_plus_curated.fas

3) Now the alignment needs to be filtered to remove gaps and possible to remove hypervariable positions. This can be done in QIIME with the command below, or with another program.

filter_alignment.py -i HTESreads_aligned_plus_curated.fas -g 0.99 -s -e 0.0001 –o HTESreads_aligned_plus_curated_filtered.fas

4) Place short reads in your reference tree using RaxML-EPA. The –f v option is the EPA placement. Learn more about it here. Use your reference tree here.

raxmlHPC-PTHREADS-SSE3 -f v -G 0.2 -m GTRCAT -n EPARUN -s HTESreads_aligned_plus_curated_filtered.fas -t RAxML_bestTreeNAME.tre -T 4

5) clean the tree so that you can view it in FigTree

sed 's/QUERY___//g' RAxML_labelledTree.EPARUN | sed 's/\[I[0-9]*\]//g' > RAxML_placement_tree_NAME.tre

If you have any question or suggestion please feel free to add it to the comment section below, visit our forum or send us an e-mail

Taxonomy classification guidelines

Thu, 08 Aug 2019 00:00:00 +0000

General guidelines

EukRef follows PR2 and uses a 9 level taxonomy (domain, supergroup, division, subdivision, class, order, family, genus, species).
You can navigate the existing taxonomy on the PR2 web interface.
Please make yourself familiar with the PR2 rules:
- Taxonomic names cannot appear twice at different levels. For example “Stramenopiles” cannot appear at both the supergroup and Division levels.
- Taxa names should only contain letters, numbers (to remove ambiguities) and underscore.
- The key linking sequences to taxonomy is the species level. So the species level should always be annotated.
Be conservative in your taxonomic annotation (e.g. clades that are being annotated should normally be backed up by other analyses).
Use names that have been previously applied to groups in other publications. You can also consult other databases such as WoRMS, AlgaeBase). In particular try to stick to the taxonomic conventions for your community (for example for algae taxa ending by phyceae correspond to classes).
Novel environmental clades identified here may be an exception, but must follow the Novel Environmental Clades guidelines below.
In the case of empty levels, propagate from a high hierarchical level down to fill in blanks. Use the PR2 convention, i.e. if a level is unknown you use the level above with an _X appended and the propagate down with _XX, _XXX etc…
If you have a genus that is paraphyletic, keep the binomial for the least inclusive column (species name) and annotate corrected genus name in genus column.You can create several genera on the model genus_1, genus_2 etc…

In case you run into problems, several options are available.

Search the literature for other publications (phylogenies or classification or taxonomic descriptions) that can guide your decision. You should assemble literature for your clade prior to annotating to guide your work overall, and search again when you become stuck.
Ask yourself, are you really annotating at the right level? (e.g. if 18S is not informative for the for the genus level for your group you should not add genus level annotations).
Describe your question in a post to the element.io EukRef discussion group.
Send your question to a taxonomic expert for your group (perhaps another PR2 curator, your adviser, or an author of publications on your group). E-mail us if you need help finding an expert.

Specific cases

Important clades that have no taxonomic name

Clades that have formal taxon names but the larger clade does not have a name. Options:

If a name has been applied to a group previously, use this name.
If an informal name exists. Treat these like environmental sequence rules.
If the existing informal name is generic (e.g. clade A or clade 1), a prefix should be added to the existing informal name based on the higher taxonomy. This name should be distinguishable from any other environmental clades. Use long names rather than short names. As an exemple use “Haptophyta_clade3” and NOT “HAP3”.
If no informal name exists but the group is important and warrants a name you can apply a new informal name consisting of a prefix based on the next higher level that has a name and a clade name. Hopefully these cases will be very rare.

Naming Environmental clades

Only name lineages that are:

Well-supported by bootstrap / posterior probabilities or possibly by clear 18S sequence signatures.
Composed of two or more clearly distinct sequence types, ideally from two or more different studies.
If they are composed from only one study, make sure that the sequences are from different samples.
Do NOT create clades from isolated sequences, especially long-branches.

For the name, use the rules above plus:

Number related lineages in some arbitrary order (for instance chronological order of their first appearance in a paper).
Even if a lineage later disappears, never re-use the same number again to avoid confusion (e.g. MAST5 no longer exists and the name should not be re-used).

Isolated sequences

Isolated sequences must be treated with caution, as they are likely to be chimeric or bad-quality sequence:

Rigorously check isolated sequences and remove any that are chimeric or poor-quality from your reference alignment.
When isolated sequences look genuine (are not chimeras), they can be kept in the reference alignment because they may carry useful environmental information;
Single-sequence 18S types that do not seem problematic should be identified by the lowest group to which they can be assigned (for example, Dinophyceae_XXX_sp.). This annotation should be done at the species level.

If you have any question or suggestion, please post it to the element.io EukRef discussion group.

Workshop Barcelona 2016

Thu, 08 Aug 2019 00:00:00 +0000

Our second workshop took place at the Institute of Marine Sciences in Barcelona, Spain from November 28 to December 2 2016. This effort brought together taxonomists with expertise in individual lineages that span the eukaryotic tree of life to curate reference 18S rDNA sequences of these lineages by incorporating knowledge of phylogenetic, morphological, and/or environmental contextual data. This second edition was particularly (but not exclusively) focused on Amoebozoa and Rhizaria. During the workshop, the working group integrated the curation efforts on individual eukaryotic groups into a biological data warehouse consisting of curated sequences, flexible taxonomy, and phylogenetic trees and their underlying sequence alignments. We will further use this 18S rDNA reference database to investigate the environmental distribution of eukaryotic microbes from large-scale HTES datasets. Each curator was encouraged to use their curated data to address research questions of interest. We discussed how to tackle such projects and encourage participants to publish their results. The workshop was made possible thanks to the generous contribution of the Moore Foundation.

Participants

Participants	Affiliation
Clément Duckert	Université de Neuchâtel
Kenneth Dumack	University of Cologne
Anna Maria Fiore-Donno	University of Cologne
Thais Garcia da Silva	Universidade Federal de São Carlos
Aaron Heiss	American Museum of Natural History
Konstantina Mitsi	Institut de Biologia Evolutiva CSIC-UPF
Raphael Morard	University of Bremen
Albert Reñé	Institut de Ciències del Mar - CSIC
Lucia Safi	Virginia Institute of Marine Science
Alicia Sánchez-Arroyo	Institut de Biologia Evolutiva CSIC-UPF
Magali Schweizer	Université d’Angers
Samuel Starko	University of British Columbia
Alexander Tice	Mississippi State University
Tomas Tyml	University of South Bohemia in České Budějovice
Ivan Voltski	Ben-Gurion University of the Negev
Lu Wang	Xiamen University

Scientifics Advisors

Adviser	Affiliation
David Bass	Cefas and Natural History Museum
Cedric Berney	Station Biologique Roscoff - CNRS
Matt Brown	Mississippi State University
Javier del Campo	University of British Columbia
Alexey Kozlov	Heidelberg Institute for Theoretical Studies
Ramon Massana	Institut de Ciències del Mar - CSIC
Laura Parfrey	University of British Columbia

Technical Advisors

Adviser	Affiliation
Martin Kolisko	University of British Columbia
Evan Morien	University of British Columbia

Schedule

Workshop Roscoff 2018

Thu, 08 Aug 2019 00:00:00 +0000

Our third workshop took place at the Station Biologique Roscoff in Roscoff, France from November 5 to 9 2018. This effort brought together taxonomists with expertise in individual lineages that span the eukaryotic tree of life to curate reference 18S rDNA sequences of these lineages by incorporating knowledge of phylogenetic, morphological, and/or environmental contextual data. This third edition was particularly (but not exclusively) focused on Diatoms, Dinoflagellates, and Green Algae. During the workshop, the working group integrated the curation efforts on individual eukaryotic groups into a biological data warehouse consisting of curated sequences, flexible taxonomy, and phylogenetic trees and their underlying sequence alignments. We will further use this 18S rDNA reference database to investigate the environmental distribution of eukaryotic microbes from large-scale HTES datasets. Each curator was encouraged to use their curated data to address research questions of interest. We discussed how to tackle such projects and encourage participants to publish their results. The workshop was made possible thanks to the generous contribution of the Moore Foundation, and it has been endorsed by GlobalHAB.

Participants

Participants	Affiliation
Charles Bachy	Station Biologique Roscoff - CNRS
Vincent Billy	University of British Columbia
Tatyana Darienko	University of Göttingen
Andrea de Oliveira da Rocha Franco	Federal University of Rio Grande
Évelyne Derelle	Station Biologique Roscoff - CNRS
Hiroshi Funaki	Ehime University
María García Portela	Spanish Institute of Oceanography
Clara Maria Hereu	Centro de Investigación Científica y de Educación Superior de Ensenada
Katarina Kajan	Ruđer Bošković Institute
Alexander Kudryavtsev	Saint Petersburg University
Becca Lensing	University of Hawaiʻi
Inga Martinek	Institute of Parasitology Biology Centre - ASCR
Sebastian Metz	Universidad Nacional de San Martín
Luis Demetrio Mora Hernandez	Freie Universität Berlin
Thomas Proeschold	University of Innsbruck
Teng Sing Tung	Universiti Malaysia Sarawak
Denis Tikhonenkov	Papanin Institute for Biology of Inland Waters - RAS
Guifré Torruella	Université Paris-Sud
Anh Tu Van	Universität Rostock
Vasily Zlatogursky	Saint Petersburg University

Scientific Advisors

Adviser	Affiliation
Cedric Berney	Station Biologique Roscoff - CNRS
Javier del Campo	Institut de Ciències del Mar - CSIC
Frederik Leliaert	Botanic Garden Meise
David G. Mann	Royal Botanic Garden Edinburgh
Marina Montresor	Stazione Zoologica Anton Dohrn
Solenn Mordret	Stazione Zoologica Anton Dohrn
Raffaele Siano	Institut Français de Recherche pour l’Exploitation de la Mer
Daniel Vaulot	Station Biologique Roscoff - CNRS

Technical Advisors

Adviser	Affiliation
Martin Kolisko	Institute of Parasitology Biology Centre - ASCR
Evan Morien	University of British Columbia
Serafim Nenarokov	Institute of Parasitology Biology Centre - ASCR

Workshop Vancouver 2015

Thu, 08 Aug 2019 00:00:00 +0000

Our first workshop that will take place in Vancouver, Canada from July 19 to 25. This effort brings together taxonomists with expertise in individual lineages that span the eukaryotic tree of life to curate reference 18S rDNA sequences of these lineages by incorporating knowledge of phylogenetic, morphological, and/or environmental contextual data. During the workshop, the working group will integrate the curation efforts on individual eukaryotic groups into a biological data warehouse consisting of curated sequences, flexible taxonomy, and phylogenetic trees and their underlying sequence alignments. We will further use this 18S rDNA reference database to investigate the environmental distribution of eukaryotic microbes from large-scale HTES datasets. Each curator is encouraged to use their curated data to address research questions of interest.

Participants

Participants	Affiliation
Anna Karnkowska	Charles University in Prague
Bente Edvardsen	Univeristy of Oslo
Cedric Berney	Station Biologique Roscoff - CNRS
Chang Jae Choi	Monterey Bay Aquarium Research Institute
Elisabeth Hehenberger	University of British Columbia
Eric Salomaki	University of Rhode Island
Gordon Lax	Dalhousie University
Jingwen Pan	University of British Columbia
Julia Maritz	New York University
Laura M. Walker	University of Arkansas
Luciana Santoferrara	University of Connecticut
Markus Majaneva	University of Helskinki
Martin Kolisko	University of British Columbia
Mary Thaler	Universitè Laval
Matt Ashworth	University of Texas Austin
Olga Flegontova	Institute of Parasitology Biology Centre - ASCR
Qianqian Zhang	Yantai Institute of Coastal Zone Research - CAS
Sandra Lindstrom	University of British Columbia
Thierry Heger	University of British Columbia
Tomas Panek	Charles University in Prague
Vasily Zlatogursky	Saint Petersburg University
Vera Tai	University of British Columbia
Vittorio Boscaro	University of British Columbia

Scientific Advisors

Adviser	Affiliation
Sina Adl	University of Saskatchewan
Matt Brown	Mississippi State University
Javier del Campo	University of British Columbia
Colomban de Vargas	Station Biologique Roscoff - CNRS
Laure Guillou	Station Biologique Roscoff - CNRS
Patrick Keeling	University of British Columbia
Ramon Massana	Institut de Ciències del Mar - CSIC
Laura Parfrey	University of British Columbia
Alastair Simpson	Dalhousie University

Technical Advisors

Adviser	Affiliation
Stephane Audic	Station Biologique Roscoff - CNRS
Martin Kolisko	University of British Columbia
Daniel Richter	Station Biologique Roscoff - CNRS

Schedule

Presentations of the PR2 database

Mon, 05 Nov 2018 00:00:00 +0000

2022-06-23 - AFEM meeting Clermont-Ferrand, France

2020-06-24 - Protist.Online Electronic Symposium on Protistology

2018-11-05 - EukRef workshop in Roscoff

Database fields

Mon, 10 Sep 2018 00:00:00 +0000

We are providing as part of the pr2database package two data frames as functions:

pr2_database(): the main PR2 reference database containing both 18S rRNA and plastid 16S rRNA sequences
pr2_taxonomy(): the main PR2 reference database containing both 18S rRNA and plastid 16S rRNA sequences

pr2_database()

The PR2 reference database is provided as a data frame called through the functionpr2database::pr2_database(). This is a join between the following tables:

pr2_main
pr2_taxonomy
pr2_sequence
pr2_metadata
pr2_countries
pr2_traits
pr2_assign_silva
eukribo_v2

The metadata contains several types of fields:

gb_ : originating from the GenBank entry
eukref_ : annotated by the Eukref project
pr2_ : annotated by pr2 such latitude and longitude
eukribo_ : from the EukRibo database
silva_ : from the Silva database

Detailed description of fields

Fields	Comment
pr2_accession	PR2 specific accession number
genbank_accession	Genbank accession number (without the vresion)
start	Start of sequence in Genbank entry
end	End of sequence in Genbank entry
label	Label explaining origin of sequence
	G: genomic sequence containing a described intron (rDNA)
	R: the previous genomic rRNA sequence, without the intron(s)
	U: no intron described, but intron(s) may be present
	UC: introns were detected in silico and removed from the sequence (putative rRNA)
gene	18S_rRNA or 16S_rRNA
organelle	nucleus, plastid, mitochondria, nucleomorph, apicoplast (left empty for cyanobacteria)
reference_sequence	= 1, this is a reference sequence that can be used for example for alignements
added_version	PR2 version when sequence was added
remark	Remark concerning the sequence
domain	rank 1
supergroup	rank 2
division	rank 3
subdivision	rank 4
class	rank 5
order	rank 6
family	rank 7
genus	rank 8
species	Assigned species - rank 9
reference	Reference in the litterature concerning the taxonomy
sequence	Sequence
sequence_length	Length of sequence
ambiguities	Number of ambiguities
sequence_hash	Hash value of sequence
gb_date	Genbank: Date
gb_locus	Genbank: Locus
gb_definition	Genbank: Definition
gb_organism	Genbank: Organism
gb_taxonomy	Genbank: Taxonomy
gb_strain	Genbank: Strain
gb_culture_collection	Genbank: Culture Collection
gb_clone	Genbank: Clone
gb_isolate	Genbank: Isolate
gb_isolation_source	Genbank: Isolation Source
gb_specimen_voucher	Genbank: Voucher
gb_host	Genbank: Host
gb_collection_date	Genbank: Date of Collection
gb_environmental_sample	Genbank: Environmental Sample
gb_country	Genbank: Country
gb_lat_lon	Genbank: lat Lon
gb_collected_by	Genbank: Collected by
gb_note	Genbank: Note
gb_references	Genbank: Full references not parsed
gb_publication	Genbank: Publication
gb_authors	Genbank: Authors
gb_journal	Genbank: Journal
pubmed_id	Genbank: Pubmed ID
eukref_name	Eukref: Name use in EukRef, usually either the species name or the clone name
eukref_source	Eukref: Source of the sequence : Isolate or Environmental
eukref_env_material	Eukref: uses ENVO keywords
eukref_env_biome	Eukref: uses ENVO keywords
eukref_biotic_relationship	Eukref: eg parasite
eukref_specific_host	Eukref: Specific Host annotated
eukref_geo_loc_name	Eukref: Location name annotated
eukref_notes	Eukref: Notes made during Eukref annotation
pr2_sample_type	PR2: e.g. culture, isolate, environmental, unknown
pr2_sample_method	PR2: e.g. filtration, flow cytometry sorting
pr2_latitude	PR2: Parsed from GenBank entry
pr2_longitude	PR2: Parsed from GenBank entry
pr2_ocean	PR2: e.g. Arctic Ocean
pr2_sea	PR2: e.g. North Sea
pr2_sea_lat	PR2: latitude of sea or ocean
pr2_sea_lon	PR2: longitude of sea or ocean
pr2_continent	PR2: e.g. Asia
pr2_country	PR2: e.g. France
pr2_country_geocode	PR2: 2 letter code from genonames - e.g. FR
pr2_country_lat	PR2: latitude of country
pr2_country_lon	PR2: longitude of country
pr2_location	PR2: from gb_country field - e.g. Paris, France
pr2_location_geoname	PR2: e.g. Paris
pr2_location_geotype	PR2: e.g. bay
pr2_location_lat	PR2: latitude of location
pr2_location_lon	PR2: longtitude of location
pr2_sequence_origin	PR2: clone library, metabarcode, PCR
pr2_size_fraction	PR2: Name of size fraction, e.g. pico, nano
pr2_size_fraction_min	PR2: Minimum size filtered, e.g. 0.2 µm
pr2_size_fraction_max	PR2: Maximum size filtered, e.g. 20 µm
mixoplanton	from the Mixoplankton database (MDB)
	* CM - Constitutive Mixoplankton
	* GNCM - Generalist Non-Constitutive Mixoplankton
	* pSNCM - plastidic Specialist Non-Constitutive Mixoplankton
	* eSNCM - endosymbiotic Specialist Non-Constitutive Mixoplankton
metadata_remark	PR2: Any remark on metadata
eukribo_UniEuk_taxonomy_string	Taxonomy assignment from EukRibo database
eukribo_V4	Information about presence and completeness V4 region from EukRibo database
eukribo_V9	Information about presence and completeness V9 region from EukRibo database
silva_taxonomy	taxonomy from Silva version 138

Reference database structure

Mon, 10 Sep 2018 00:00:00 +0000

From version 4.14.0, a single SSU database is provided which contains sequences for:

18S rRNA from nuclear and nucleomorph
16S rRNA from plastid, apicoplast, chromatophore, mitochondrion
16S rRNA from a small selection of bacteria

The rationale is that the database can now be used to detect bacterial sequences that are amplified with either 18S rRNA or “universal” primers. These sequences can be further assigned with Silva or GTDB.

Taxonomy structure

Version 5.0 and above

9 levels : Domain / Supergroup / Division / Subdivision / Class / Order / Family / Genus / Species
- Kingdom is replaced by Domain
- Adding a Subdivision level

Version 4.14.1 and below

8 levels : Kingdom / Supergroup / Division / Class / Order / Family / Genus / Species

Rules for naming taxonomic levels

All taxonomy paths are unique. For example for a given Class, all higher levels are similar (Division -> Supergroup -> Domain)
No taxon can appear at different levels. For example “Stramenopiles” cannot appear at both the Supergroup and Division levels.
No space (use underscore). For example Home_sapiens
If species is not known use “Genus_sp.” (note the . after sp). The Genus level can be a level with Xs (see next rule): e.g. “Stramenopiles_XXXX_sp.“,
If level i is unknown
- if level i-1 is known, use level i-1 followed by “_X” , e.g. “Stramenopiles_X” at Division level
- if level i-1 is unknown, use level i-1 followed by “X” , e.g. “Stramenopiles_XX” at Class level

Organelles

In order to allow correct assignation with software such as DECIPHER (IDTax) for organelle, the taxonomy is appended with 4 letters corresponding to the organelle

Organelle	Taxonomy suffix
nucleus
nucleomorph	:nucl
plastid	:plas
apicoplast	:apic
chromatophore	:chrom
mitochondrion	:mito

e.g. a sequence annotated as Neoceratium_horridum:plas will correspond to a plastid sequence of the species Neoceratium horridum

Rules for sequences

Minimum length = 500 bp (except for some plastid sequences which are shorter)
Maximum number of ambiguities (N) = 20
No consecutive Ns (so sequences such as ..ATGNNAT.. are removed)

Construction of PR2 id (pr2_accession)

Accession.Start.End_X

For example AF530536.1.1695_U

AF530536 : GenBank accession number
1 : Start of the 18S rRNA in the GenBank sequence
1695 : End of the 18S rRNA in the GenBank sequence
X can take any of the following values:
- G: genomic sequence containing a described intron (rDNA)
- R: the previous genomic rRNA sequence, without the intron(s)
- U: no intron described, but intron(s) may be present
- UC: introns were detected in silico and removed from the sequence (putative rRNA)

Database structure (tables and fields)

Table	Fields	Comment
pr2_main	pr2_accession, genbank_accession, species, editing hitory
pr2_sequence	pr2_accession, , sequence	linked to pr2_main by pr2_accession
pr2_metadata	metadata from GenBank and from published references	linked to pr2_main by genbank_accession
pr2_taxonomy	domain -> species, editing history	linked to pr2_main by species
pr2_countries	geo-information	linked to pr2_metadata by pr2_country
pr2_assign_silva	assignment of pr2 sequences according to Silva	linked to pr2_main by pr2_accession
eukribo_V2	Eukribo version 2 data	linked to pr2_main by genbank_accession
pr2_traits	Traits from other databases harboring species traits	linked to pr2_taxonomy by taxonomy level (e.g. species, genus). This table used a long format.
worms_taxonomy	Worms database entries for taxa from PR2

History of database structure changes

PR2 version	Table	Field	Action	Comment
5.0.0	eukribo_V2	A	New table holding Eukribo version 2 data.
	pr2_traits	A	New table for adding traits to PR2 from other databases (e.g. Mixoplankton Database)
	worms_taxonomy	A	New table with Worms database entries for taxa from PR2
4.14.0	pr2_main	quarantined_version	A	quarantined sequences do not appear in the released version but will be re-assigned latter
	pr2_metadata	gb_references	R	empty
		gb_locus	R	empty
		gb_division	A	3-letter code (e.g. PLN, ENV)
4.13.0	pr2_metadata	pr2_depth	A	depth of sample in meter
		gb_id	A	Genbank ID number (big integer)
		gb_project_id	A	Genbank project ID for metagenomes
		gb_sequence	A	original gb_sequence (longtext)
	pr2_countries	A	New table for country information
	pr2_assign_silva	A	New table for Silva assignation of sequences
4.12.0	pr2_main	gene	A	18S_RNA, 16S_RNA
		organelle	A	nucleus, plastid, mitochondria, nucleomorph, apicoplast (left empty for cyanobacteria)
	pr2_metadata	gb_organelle	A	import the corresponding gb field
		pr2_sequence_origin	M	add other possibilities such as genome and metagenome
		pr2_continent, pr2_country, pr2_country_lat, pr2_country_lon	A	geographical origin extracted from gb_country field, gb_isolation_source, eukref_geo_loc_name
		pr2_location, pr2_location_lat, pr2_location_lon	A	geographical origin extracted from gb_country field, gb_isolation_source, eukref_geo_loc_name
		pr2_sea, pr2_sea_lat, pr2_sea_lon	A	geographical origin extracted from gb_country field, gb_isolation_source, eukref_geo_loc_name
	pr2_sequence	sequence_hash	A	hash value of the sequence (using R function digest::sha1
	pr2_taxonomy	taxon_trophic_mode	A	detailed trophic mode (e.g. “C-fixation constitutive; Mixotroph”) - for future use
4.11.1	pr2_metadata	gb_reference	A	Contains the whole REFERENCE field from GenBank
		eukref_publication eukref_authors eukref_journal	M	Merged into gb_publication, gb_authors, gb_journal
4.11.0	pr2_metadata	eukref_publication eukref_authors eukref_journal eukref_notes	A	Added
4.11.0	pr2_metadata	pr2_xxx	M	fields annotated by Eukref renamed back to eukref_xxx
4.11.0	pr2_main	taxo_id	R	not used anymore since linked is done by species (this will be probably reinstated later on a different form using a different format for the taxonomy table).
4.9	pr2_metadata	eukref_xxx	M	renamed to pr2_xxx to reflect the fact that these fields will also be updated independantly of EukRef
4.9	pr2_main	reference_sequence	A	designate sequences that can be used as reference e.g. for alignment
4.8	pr2_main, taxo	xx_date (e.g. edited_date)	R	redundant with xx_version (e.g. edited_version) fields
4.8	pr2_sequence	sequence_length	M	Minimum length is now 500 bp.

Action : A=Added/R=Removed/M=Modified

Subscribe to PR2 mailing list

Tue, 26 Nov 2019 00:00:00 +0000

The 9-levels taxonomy

Fri, 14 Apr 2023 00:00:00 +0000

The eukaryotic tree. From Burki et al. 2020. The New Tree of Eukaryotes. Trends in Ecology & Evolution. DOI: 10.1016/j.tree.2019.08.008.

Release 5.0.0 of PR2 (April 2023) included a major update of the taxonomy to include nine taxonomic ranks instead of eight, in order to better accommodate the most recent eukaryote Tree of Life (Burki et al. 2019, Adl et al. 2019). The nine taxonomic ranks now correspond to Domain (replacing Kingdom), Supergroup, Division, Subdivision (new taxonomic rank added), Class, Order, Family, Genus, and Species.

The inclusion of nine taxonomic ranks allows to better match recent phylogenomic evidence, e.g. the new supergroup TSAR in PR2 version 5 now subsumes four supergroups in previous PR2 versions; namely Alveolata, Rhizaria, Stramenopiles, and Telonemia (Strassert et al. 2019). Similarly, the supergroup Obazoa unites Opisthokonta, Apusomonada, and Breviatea (Brown et al. 2013). Having increased taxonomic ranks also allowed updating the taxonomy to be more informative for groups such as Discoba, where Diplonemea, Euglenida, Kinetoplastea, and Symbiontida could be grouped under the subdivision Euglenozoa (Yubuki et al. 2009, Simpson 1997).

Current supergroups

PR2 version 5 includes nine supergroups. These are:

Amoebozoa
Archaeplastida
CRuMs
Cryptista
Haptista
Excavata
Obazoa
TSAR
Provora (new supergroup added; Tikhonenkov et al. 2022)

The kingdoms of previous PR2 versions and where are they now?

Amoebozoa is still considered as a supergroup in the new version of PR2.
Archaeplastida is also still considered as a supergroup in PR2 version 5, and now includes Picozoa (Schön et al. 2021).
Apusozoa has been shown to be polyphyletic, with Mantamonadidea, Collodictyonidea, and Rigifilida belonging to the supergroup CRuMs (Brown et al. 2018), Ancyromonadida representing a deep branching lineage of unknown phylogenetic affiliation, and the remaining lineages in Apusomonada within Obazoa.
Hacrobia has similarly been shown to be polyphyletic and its members are now split up between Haptista and Cryptista, with the exception of Telonemia which is in TSAR, and Picozoa in Archaeplastida (Yabuki et al. 2014, Cavalier-Smith et al. 2015, Burki et al. 2016, Strassert et al. 2019, Schön et al. 2021).
Excavata is still considered a supergroup.
Opisthokonta is now a division within Obazoa.
Alveolata is now a division within TSAR.
Protalveolata has been renamed to Colponemidia, a subdivision with Alveolata, TSAR.
Rhizaria is now a division with TSAR.
Stramenopiles is also a division within TSAR.

Problems with taxonomy and metazoa and fungi

References

Adl, S. M., Bass, D., Lane, C. E., Lukeš, J., Schoch, C. L., Smirnov, A., … & Zhang, Q. (2019). Revisions to the classification, nomenclature, and diversity of eukaryotes. Journal of Eukaryotic Microbiology, 66(1), 4-119. https://doi.org/10.1111/jeu.12691

Brown, M. W., Sharpe, S. C., Silberman, J. D., Heiss, A. A., Lang, B. F., Simpson, A. G., & Roger, A. J. (2013). Phylogenomics demonstrates that breviate flagellates are related to opisthokonts and apusomonads. Proceedings of the Royal Society B: Biological Sciences, 280(1769), 20131755. https://doi.org/10.1098/rspb.2013.1755

Brown, M. W., Heiss, A. A., Kamikawa, R., Inagaki, Y., Yabuki, A., Tice, A. K., … & Roger, A. J. (2018). Phylogenomics places orphan protistan lineages in a novel eukaryotic super-group. Genome Biology and Evolution, 10(2), 427-433. https://doi.org/10.1093/gbe/evy014

Burki, F., Kaplan, M., Tikhonenkov, D. V., Zlatogursky, V., Minh, B. Q., Radaykina, L. V., … & Keeling, P. J. (2016). Untangling the early diversification of eukaryotes: a phylogenomic study of the evolutionary origins of Centrohelida, Haptophyta and Cryptista. Proceedings of the Royal Society B: Biological Sciences, 283(1823), 20152802. https://doi.org/10.1098/rspb.2015.2802

Burki, F., Roger, A. J., Brown, M. W., & Simpson, A. G. (2020). The New Tree of Eukaryotes. Trends in Ecology & Evolution, 35(1), 43-55. https://doi.org/10.1016/j.tree.2019.08.008

Cavalier-Smith, T., Chao, E. E., & Lewis, R. (2015). Multiple origins of Heliozoa from flagellate ancestors: new cryptist subphylum Corbihelia, superclass Corbistoma, and monophyly of Haptista, Cryptista, Hacrobia and Chromista. Molecular Phylogenetics and Evolution, 93, 331-362. https://doi.org/10.1016/j.ympev.2015.07.004

Schön, M. E., Zlatogursky, V. V., Singh, R. P., Poirier, C., Wilken, S., Mathur, V., … & Burki, F. (2021). Single cell genomics reveals plastid-lacking Picozoa are close relatives of red algae. Nature Communications, 12(1), 6651. https://doi.org/10.1038/s41467-021-26918-0

Simpson, A. G. (1997). The identity and composition of the Euglenozoa. Archiv für Protistenkunde, 148(3), 318-328. https://doi.org/10.1016/S0003-9365(97)80012-7{.uri}

Strassert, J. F., Jamy, M., Mylnikov, A. P., Tikhonenkov, D. V., & Burki, F. (2019). New phylogenomic analysis of the enigmatic phylum Telonemia further resolves the eukaryote tree of life. Molecular Biology and Evolution, 36(4), 757-765. https://doi.org/10.1093/molbev/msz012

Tikhonenkov, D. V., Mikhailov, K. V., Gawryluk, R. M., Belyaev, A. O., Mathur, V., Karpov, S. A., … & Keeling, P. J. (2022). Microbial predators form a new supergroup of eukaryotes. Nature, 1-6. https://doi.org/10.1038/s41586-022-05511-5

Yabuki, A., Kamikawa, R., Ishikawa, S. A., Kolisko, M., Kim, E., Tanabe, A. S., … & Inagki, Y. (2014). Palpitomonas bilix represents a basal cryptist lineage: insight into the character evolution in Cryptista. Scientific Reports, 4(1), 4641. https://doi.org/10.1038/srep04641

Yubuki, N., Edgcomb, V. P., Bernhard, J. M., & Leander, B. S. (2009). Ultrastructure and molecular phylogeny of Calkinsia aureus: cellular identity of a novel clade of deep-sea euglenozoans with epibiotic bacteria. BMC Microbiology, 9(1), 1-22. https://doi.org/10.1186/1471-2180-9-16

SQLite PR2 reference database

Wed, 01 Apr 2020 00:00:00 +0000

File provided

Each version has a 3 number code: version_x.y.z, e.g. 4.12.0

pr2_version_x.y.z.sqlite.gz: compressed version of the PR² database under SQLite.

Database structure

Four tables are provided

pr2_main
pr2_sequence
pr2_metadata
pr2_taxonomy

Please see here for the detailed structure of the database

Using the database

R

You can use the package RSQLite to interact with the database.

DBeaver database interface

We recommend using DBeaver, an open source Universal database interface that can read a variety of database formats (MySQL, MariaSQL, SQlite…)

Using the DBeaver interface to read the PR² SQLite database.

PR2 team

Tue, 15 Jan 2019 00:00:00 +0000

Format of PR2 reference flat files

Mon, 20 Aug 2018 00:00:00 +0000

List of files are provided for each release

Link to files of latest release

Each version has a 3 number code: version_x.y.z, e.g. 5.1.0

Important note : All files are in UNIX format (end of lines are indicated Line Feed-LF only). Please see at the bottom of the file how to converts the files to Windows format (end of lines are CR+LF).

Files to assign metabarcodes

dada2

pr2_version_x.y.z_SSU_dada2.fasta.gz contains a dada2 format compatible training file

Mothur or Qiime

Two files:

pr2_version_x.y.z_SSU_mothur.fasta.gz contains all sequences in fasta format with the accession in the description line
pr2_version_x.y.z_SSU_mothur.tax.gz contains the taxonomy of each sequence separated from the accession number by a tabulation
Note :Qiime only use 7 taxonomical levels by default.

USEARCH or VSEARCH

pr2_version_x.y.z_SSU_UTAX.fasta.gz contains one fasta file with the accession number of the sequence and its full taxonomy on the description line in the UTAX format. It is suitable to use with USEARCH and VSEARCH.

DECIPHER training set

pr2_version_x.y.z_SSU.decipher.trained.rds is a DECIPHER training set using 3 iterations and a maximum of 20 sequences per species (LearnTaxa) that can be used with the DECIPHER IDTaxa function to assign metabarcodes. Use the readRDS() function of R to load the file.

Emu

Emu is a very efficient program to assign reads to a taxonomy database. It is in particular useful for long reads such as provided by Nanopore or PacBio sequencers.

pr2_version_x.y.z_emu.zip .The files provided starting on version 5.1.0 are those used to build the emu database which is done with the following command:

emu build-database pr2_version_5.1.0_emu.db --sequences pr2_version_5.1.0_emu.fasta --seq2tax pr2_version_5.1.0_emu_map.tsv --taxonomy-list pr2_version_5.1.0_emu_taxo.tsv

Other files

Taxonomy structure

pr2_version_x.y.z_taxonomy.xlsx

Fasta file

pr2_version_x.y.z_SSU_taxo_long.fasta.gz: contains accession number, the name of sequence and full taxonomy on the description line. It is suitable to build a local database for BLAST search

Full database as Excel file

pr2_version_x.y.z_merged.xlsx: Includes sequences, taxonomy and metadata.

Sequences annotated as chimeric

pr2_version_x.y.z_chimera.xlsx

Unassigned sequences

pr2_version_x.y.z_unassigned.xlsx
These SSU GenBank sequences are not part yet of the PR2 database. However some of them have been automatically assigned with AssignTaxa and version 4.14 of PR2 (see columns at the end of the xlsx file).
These sequences can be useful to add more sequences to a phylogenetic tree for example or annotate a specific taxonomic group.

Examples of format

mothur fasta

>AB353770.1.1740_U
ATGCTTGTCTCAAAGATTAAGCCATGCATGTCTCAGTATAAGCTTTTACATGGCGAAACTGCGAATGGCTCATTAAAACA
GTTACAGTTTATTTGAAGGTCATTTTCTACATGGATAACTGTGGTAATTCTAGAGCTAATACATGCGCCCAAACCCGACT
CCGTGGAAGGGTTGTATTTATTAGTTACAGAACCAACCCAGGTTCGCCTGGCCATTTGGTGATTCATAATAAACGAGCGA
ATTGCACAGCCTCAGCTGGCGATGTATCATTCAAGTTTCTGACCTATCAGCTTCCGACGGTAGGGTATTGGCCTACCGTG
GCAATGACGGGTAACGGAGAATTAGGGTTCGATTCCGGAGAGGGAGCCTGAGAAACGGCTACCACATCTAAGGAAGGCAG
CAGGCGCGCAAATTACCCAATCCTGACACAGGGAGGTAGTGACAAGAAATAACAATACAGGGCAACCATGTCTTGTA`

mothur taxonomy

AB353770.1.1740_U
Eukaryota;Alveolata;Dinophyta;Dinophyceae;Dinophyceae_X;Dinophyceae_XX;Peridiniopsis;Peridiniopsis_kevei;
KC672520.1.1801_U
Eukaryota;Opisthokonta;Fungi;Ascomycota;Pezizomycotina;Leotiomycetes;Leotiomycetes_X;Leotiomycetes_X_sp.;

UTAX fasta

>AB353770.1.1740_U;tax=k:Eukaryota,d:Alveolata,p:Dinophyta,c:Dinophyceae,o:Dinophyceae_X,f:Dinophyceae_XX,g:Peridiniopsis,s:Peridiniopsis_kevei
ATGCTTGTCTCAAAGATTAAGCCATGCATGTCTCAGTATAAGCTTTTACATGGCGAAACTGCGAATGGCTCATTAAAACA
GTTACAGTTTATTTGAAGGTCATTTTCTACATGGATAACTGTGGTAATTCTAGAGCTAATACATGCGCCCAAACCCGACT
CCGTGGAAGGGTTGTATTTATTAGTTACAGAACCAACCCAGGTTCGCCTGGCCATTTGGTGATTCATAATAAACGAGCGA
ATTGCACAGCCTCAGCTGGCGATGTATCATTCAAGTTTCTGACCTATCAGCTTCCGACGGTAGGGTATTGGCCTACCGT

dada2 fasta

>Eukaryota;Alveolata;Dinophyta;Dinophyceae;Dinophyceae_X;Dinophyceae_XX;Peridiniopsis;Peridiniopsis_kevei;
ATGCTTGTCTCAAAGATTAAGCCATGCATGTCTCAGTATAAGCTTTTACATGGCGAAACTGCGAATGGCTCATTAAAACA
GTTACAGTTTATTTGAAGGTCATTTTCTACATGGATAACTGTGGTAATTCTAGAGCTAATACATGCGCCCAAACCCGACT

fasta long

>AB353770.1.1740_U||Eukaryota|Alveolata|Dinophyta|Dinophyceae|Dinophyceae_X|Dinophyceae_XX|Peridiniopsis|Peridiniopsis_kevei
ATGCTTGTCTCAAAGATTAAGCCATGCATGTCTCAGTATAAGCTTTTACATGGCGAAACTGCGAATGGCTCATTAAAACA
GTTACAGTTTATTTGAAGGTCATTTTCTACATGGATAACTGTGGTAATTCTAGAGCTAATACATGCGCCCAAACCCGACT
CCGTGGAAGGGTTGTATTTATTAGTTACAGAACCAACCCAGGTTCGCCTGGCCATTTGGTGATTCATAATAAACGAGCGA

merged

pr2_main_id	pr2_accession	genbank_accession	start	end	label	taxo_id.x	species	chimera	chimera_remark	added_date	added_version	removed_date	removed_version	edited_date	edited_version	edited_by	edited_remark	remark	taxo_id.y	kingdom	supergroup	division	class	order	family	genus	taxo_edited_date	taxo_edited_version	taxo_removed_date	taxo_removed_version	taxo_remark	reference	seq_id	sequence	sequence_length	ambiguities	pr2_metadata_id	gb_date	gb_locus	gb_definition	gb_organism	gb_strain	gb_culture_collection	gb_clone	gb_isolate	gb_isolation_source	gb_specimen_voucher	gb_host	gb_collection_date	gb_environmental_sample	gb_country	gb_lat_lon	gb_collected_by	gb_note	pubmed_id	gb_publication	gb_authors	gb_journal	eukref_name	eukref_env_material	eukref_env_biome	eukref_biotic_relationship	eukref_specific_host	eukref_geo_loc_name	pr2_sample_type	p2_sample_method	pr2_ocean	pr2_latitude	pr2_longitude	pr2_sequence_origin	pr2_size_fraction	pr2_size_fraction_min	pr2_size_fraction_max	metadata_remark	metadata_select	sequence_label
AB353770.1.1740_U	AB353770	1	1740	U	2014	Peridiniopsis_kevei												2014	Eukaryota	Alveolata	Dinophyta	Dinophyceae	Dinophyceae_X	Dinophyceae_XX	Peridiniopsis								ATGCTTGTCTCAAAGATTAAGCCATGCATGTCTCAGTATAAGCTTTTACATGGCGAAACTGCGAATGGCTCATTAAAACAGTTACAGTTTATTTGAAGGTCATTTTCTACATGGATAACTGTGGTAATTCTAGAGCTAATACATGCGCCCAAACCCGACTCCGTGGAAGGGTTGTATTTATTAGTTACAGAACCAACCCAGGTTCGCCTGGCCATTTGGTGATTCATAATAAACGAGCGAATTGCACAGCCTCAGCTGGCGATGTATCATTCAAGTTTCTGACCTATCAGCTTCCGACGGTAGGGTATTGGCCTACCGTGGCAATGACGGGTAACGGAGAATTAGGGTTCGATTCCGGAGAGGGAGCCTGAGAAACGGCTACCACATCTAAGGAAGGCAGCAGGCGCGCAAATTACCCAATCCTGACACAGGGAGGTAGTGACAAGAAATAACAATACAGGGCAACCATGTCTTGTAATTGGAATGAGTAGAATTTAAATCCCTTTACGAGTATCCATTGGAGGGCAAGTCTGGTGCCAGCAGCCGCGGTAATTCCAGCTCCAATAGCGTATATTAAAGTTGTTGCGGTTAAAAAGCTCGTAGTTGGATTTCTGTCGAAGGAGACCGGTCCGCCCTCTGGGTGAGTATCTGGATCTCTTTGGACATCTTCTTGGGGAACGTATCTGCACTTCATTGTGCGGTGCGGTACTCAAGACTTTTACTTTGAGGAAATTAGAGTGTTTCAAGCAGGCACACGCCTTGAATACATTAGCATGGAATAATAAGATAGGACCTCGGTTCTATTTTGTTGGTTTCTAGAGCTGAGGTAATGATTAATAGGGATAGTTGGGGGCATTCGTATTTAACTGTCAGAGGTGAAATTCTTGGATTTGTTAAAGACGGACTACTGCGAAAGCATTTGCCAAGGATGTTTTCATTGATCAAGAACGAAAGTTAGGGGATCGAAGACGATCAGATACCGTCGTAGTCTTAACCATAAACCATGCCGACTAGAGATTGGAGGTCGTTATCCGTACGACTCCTTCAGCACCTTATGAGAAATCAAAGTCTTTGGGTTCCGGGGGGAGTATGGTCGCAAGGCTGAAACTTAAAGGAATTGACGGAAGGGCACCACCAGGAGTGGAGCCTGCGGCTTAATTTGACTCAACACGGGGAAACTTACCAGGTCCAGACATAGTAAGGATTGACAGATTGATAGCTCTTTCTTGATTCTATGGGTGGTGGTGCATGGCCGTTCTTAGTTGGTGGAGTGATTTGTCTGGTTAATTCCGTTAACGAACGAGACCTTAACCTGCTAAATAGTGACACATTACCCCGGTAATGTGGGTTACTTCTTAGAGGGACTTTGCGTGTCTAACGCAAGGAAGTTTGAGGCAATAACAGGTCTGTGATGCCCTTAGATGTTCTGGGCTGCACGCGCGCTACACTGATGCGCTCAACGAGTTTATGACCTTGCCCGGAAGGGTTGGGTAATCTTGTTAAAACGCATCGTGATGGGGATAGATTATTGCAATTATTAATCTTCAACGAGGAATTCCTAGTAAGCGCGAGTCATCAGCTCGTGCTGATTAAGTCCCTGCCCTTTGTACACACCGCCCGTCGCTCCTACCGATTGAGTGATCCGGTGAATAATTCGGACCGCAGCATTTGTCAGTTCCTGACTCATGCCGTGGAAAGTCTAGTGAACCTTATCACTTAGAGGAAGGAGAAGTCGTAACA	1740	0	3830		PLN	Peridiniopsis cf. kevei gene for 18S rRNA, partial sequence.									26-juil.-03		Japan: Toyama, Tomi-iwa Canal Park

Converting files from UNIX to Windows format

All files are in UNIX format (end of lines are indicated Line Feed-LF only). File can be converted to Windows format (end of lines are CR+LF):

Install Notepad++
Open the files to convert (e.g. for mothur the .fasta and .tax files)

Convert the end of lines

Now the file should like the image below (red arrow)
Save the file under the same name by clicking on the disk icon (blue arrow)

How to contribute annotations to PR2 reference database

Mon, 20 Aug 2018 00:00:00 +0000

Steps

Contact one member of the Core Team
Explain which group you want to annotate. It can be a genus, a class or any other taxonomic level.
We will send you an Excel file and a fasta file containing all existing PR² sequences for the group you are expert in.
You can alternatively download the data from the web interface
Follow the instructions below to update or add data.
Send back the updated Excel file
Your contribution will be added to the next release of PR² (we are doing 2 to 3 releases per year).
You will be acknowledged as a contributor on the PR² web site and you name will appear as a co-author on the Zenodo entry for the next PR2 update (see for example)

Files provided

Three files will be provided to you

A fasta file with the PR2 accession number
A text file that can be used to annotate trees
An excel file with 2 sheets (taxonomy, metadata)

Please edit the Excel file by marking all your changes in yellow.

pr2_export.fas.gz - FASTA file

Contains the sequence labelled with the PR2 accession number

>JX988758.1.1807_U
TTGATCCTGCCAGTAGTCATATGCTTGTCTCAAAGATTAAGCCATGCATGTCTAAGTATAAGCACCTTATACTGTGAAACTGCGAATGGCTCATTAAATCAGTTATCGTTTATTTGATGATCTCTTGCTACTTGGATACCCGTGGT...
...

pr2_export.txt

Contains information about each sequence that can be uploaded to TreeView or TreeViewer.
Fields are separated by tabulation.
Species that have been assigned automatically by dada2 are labelled with 1 in the column pr2_annotated.
You can generate more complete text files by exporting columns of the metadata sheet from the Excel file pr2_export.xlsx.

pr2_accession   domain  supergroup  division    subdivision class   order   family  genus   species pr2_annotated   gb_strain
AF265331.1.1123_U   Eukaryota   TSAR    Stramenopiles   Bigyra  Sagenista   Labyrinthulomycetes Amphifilaceae   Amphifila   Amphifila_marina    1    
AY082983.1.1879_U   Eukaryota   TSAR    Stramenopiles   Bigyra  Sagenista   Labyrinthulomycetes Amphifilaceae   Amphifila   Amphifila_sp.   1    
EF023442.1.1807_U   Eukaryota   TSAR    Stramenopiles   Bigyra  Sagenista   Labyrinthulomycetes Amphifilaceae   Amphifilaceae_X Amphifilaceae_X_sp. 1    
EF023338.1.1806_U   Eukaryota   TSAR    Stramenopiles   Bigyra  Sagenista   Labyrinthulomycetes Amphifilaceae   Amphifilaceae_X Amphifilaceae_X_sp. 1    
EF023208.1.1805_U   Eukaryota   TSAR    Stramenopiles   Bigyra  Sagenista   Labyrinthulomycetes Amphifilaceae   Amphifilaceae_X Amphifilaceae_X_sp. 1    
EF023658.1.1802_U   Eukaryota   TSAR    Stramenopiles   Bigyra  Sagenista   Labyrinthulomycetes Amphifilaceae   Amphifilaceae_X Amphifilaceae_X_sp. 1    
EF023821.1.1802_U   Eukaryota   TSAR    Stramenopiles   Bigyra  Sagenista   Labyrinthulomycetes Amphifilaceae   Amphifilaceae_X Amphifilaceae_X_sp. 1    

...

pr2_export.xlsx - Excel file

This file contains two sheets:

Taxonomy - DO NOT EDIT

Taxonomy sheet.

This sheet provides a summary of the current taxonomy of the group with the number of sequences for each species (n).
Please do not edit this file directly, this is only for your information.

Excel - Metadata - edit only this file

Metadata sheet.

Each sequence has a unique identifier (pr2_accession) which is based on the GenBank accession (genbank_accession).
For each sequence, the full taxonomic path is provided along with metadata (see here for a full description of the fields).
There are two types of entries (column pr2_annotated):
- If pr2_annotatedis equal to 1, the entry is part of the reference PR2 database and has been previously validated
- If pr2_annotatedis equal to 0, the entry is NOT part of the reference PR2 database. It has been automatically annotated using dada2 AssignTaxonomy. It needs to be validated and you can validate it (change pr2_annotated to 1 and mark in yellow).

Modifying or adding entries

Only change entries in the Metadata table

Update metadata entries.

You can
- modify the taxonomy of a given entry (do not alter the species_old column though).
- add new metadata. If your metadata do not fit the existing columns, just add more columns and we will see how to incorporate them.
You can change the ranks (supergroup to genus) if necessary but you must make sure that:
- you follow exactly the PR2 conventions which are detailed here (see the second paragraph). In particular, any taxonomic name can only appear in a single column (taxonomic level). Use the _X convention to distinguish different levels with the same name.
- you are consistent for all sequences belonging to the same taxon.
You can also add new species as needed.
Please see the figure above for some examples of changes
- 1 - These entries are unchanged
- 2 - These entries have been reassigned to a new species
- 3 - These are new entries. Provide the following information
  - genbank_accession. We will download the sequence and all genbank metadata, so no need for you to do it
  - taxonomy assignation. If the species is already present in the database you can just provide the species name
  - if the sequence is not limited to the 18S, but also contains the ITS, please provide the coordinates on the sequence of the start and end of the 18S rRNA gene.
- 4 - You can also indicate whether the new sequence is a reference sequence. Reference sequences are have a high quality, preferentially full length and are representative a given taxon.

Taxonomic groups annotated in the PR2 reference database

Sun, 01 Jul 2018 00:00:00 +0000

Groups with updated annotations

Level	Class	Group	Who	Date	Version
Eukaryotes			M. Jamy, F. Burki, J. del Campo	2023	5.0
Alveolata	Apicomplexa		J. del Campo	2019	4.12, 4.14
Alveolata	Ciliates		W. Ting, C. Bachy	2017	4.7
Alveolata	Ciliates		V. Boscaro, L. Santoferrara, E. Gentekaki and Q. Zhang	2018	4.11
Alveolata	Ciliates	Spirotrichea	L. Santoferrara, M. Ganser	2023	5.0
Alveolata	Dinoflagellates		S. Mordret, D. Sarno	2018	4.9
Alveolata	Dinoflagellates	Suessiales	J. del Campo	2021	4.13
Alveolata	Dinoflagellates	Suessiaceae, Borghiellaceae, Gonyaucales, Kareniaceae, Warnowiaceae	K. Mertens, H. Gu, SH Jang	2023	5.0
Alveolata	Dinoflagellates	misc	H. Gu, A. Bonacolta	2025	5.1
Alveolata	Perkinsids		S. Metz	2023	5.0
Chlorophyta			M.Tragin, A. Lopes dos Santos	2015	3.0
Chlorophyta	Chloropicophyceae		D. Vaulot	2025	5.1
Chlorophyta	Chloropicophyceae		E. Salomaki	2025	5.1
Picozoa			N. Pohl	2025	5.1
Excavata			J. del Campo	2021	4.14
Haptophyta			B. Edvardsen	2015	4.0
Prasinodermophyta			D. Vaulot	2021	4.13
Rhizaria	Collodaria		T. Biard	2015	2.0
Rhizaria	Foraminifera		R. Morard	2021
Rhizaria	Foraminifera		R. Morard	2025	5.1
Rhizaria	Radiolaria		M. Mendez Sandin.	2021
Stramenopiles			R. Massana	2019	4.12
Stramenopiles		Cafeteria	Alex Schoenle	2021	4.14
Stramenopiles	Labyrinthulomycetes		J. del Campo	2021	4.14
Stramenopiles	Diatoms	Chaetoceros	C. Gaonkar	2019	4.12
Stramenopiles	Diatoms	Thalassiosirales	L. Arsenieff	2021	4.13
Stramenopiles	Diatoms		D. Vaulot	2023	5.0
Stramenopiles	Bolidophyceae		D. Vaulot	2017	4.6
Stramenopiles	Pelagophyceae		A.M. Cabello	2021	4.13
Stramenopiles	Chrysophyceae		D. Vaulot	2021	4.13
Stramenopiles	Chrysophyceae		P. Škaloud	2023	5.0
Fungi	Chytrids		Alexei Seliuk	2023	5.0
Metazoa	Non-bilaterians		J. Arañó Ansola	2025	5.1

List of references used to annotate database

Eukaryotic taxonomy

Adl SM., Bass D., Lane CE., Lukeš J., Schoch CL., Smirnov A., Agatha S., Berney C., Brown MW., Burki F., Cárdenas P., Čepička I., Chistyakova L., del Campo J., Dunthorn M., Edvardsen B., Eglit Y., Guillou L., Hampl V., Heiss AA., Hoppenrath M., James TY., Karpov S., Kim E., Kolisko M., Kudryavtsev A., Lahr DJG., Lara E., Le Gall L., Lynn DH., Mann DG., Massana i Molera R., Mitchell EAD., Morrow C., Park JS., Pawlowski JW., Powell MJ., Richter DJ., Rueckert S., Shadwick L., Shimano S., Spiegel FW., Torruella i Cortes G., Youssef N., Zlatogursky V., Zhang Q. 2019. Revisions to the Classification, Nomenclature, and Diversity of Eukaryotes. Journal of Eukaryotic Microbiology 66:4–119. DOI: 10.1111/jeu.12691.
Berney, Cédric, Nicolas Henry, Frédéric Mahé, Daniel J. Richter, et Colomban de Vargas. 2022. EukRibo: A Manually Curated Eukaryotic 18S RDNA Reference Database to Facilitate Identification of New Diversity. Preprint. BiorXiv. https://doi.org/10.1101/2022.11.03.515105.
Brown, M.W., Heiss, A.A., Kamikawa, R., Inagaki, Y., Yabuki, A., Tice, A.K., Shiratori, T., Ishida, K.I., Hashimoto, T., Simpson, A.G. and Roger, A.J., 2018. Phylogenomics places orphan protistan lineages in a novel eukaryotic super-group. Genome biology and evolution, 10(2), pp.427-433.
Burki, Fabien, Andrew J. Roger, Matthew W. Brown, et Alastair G.B. Simpson. 2020. The New Tree of Eukaryotes. Trends in Ecology and Evolution 35 (1): 43‑55. https://doi.org/10.1016/j.tree.2019.08.008.
Gawryluk, R.M., Tikhonenkov, D.V., Hehenberger, E., Husnik, F., Mylnikov, A.P. and Keeling, P.J., 2019. Non-photosynthetic predators are sister to red algae. Nature, 572(7768), pp.240-243.
Strassert, J.F., Jamy, M., Mylnikov, A.P., Tikhonenkov, D.V. and Burki, F., 2019. New phylogenomic analysis of the enigmatic phylum Telonemia further resolves the eukaryote tree of life. Molecular biology and evolution, 36(4), pp.757-765.
Krabberød, A.K., Stokke, E., Thoen, E., Skrede, I. & Kauserud, H. 2025. The Ribosomal Operon Database: A Full-Length rDNA Operon Database Derived From Genome Assemblies. Molecular Ecology Resources. 25:e14031.

Chlorophyta

Tragin, M., Lopes dos Santos, A., Christen, R., and Vaulot, D. (2016). Diversity and ecology of green microalgae in marine systems: an overview based on 18S rRNA gene sequences. Perspect. Phycol. 3, 141–154. doi:10.1127/pip/2016/0059.
Lopes dos Santos A., Pollina T., Gourvil P., Corre E., Marie D., Garrido JL., Rodríguez F., Noël M-H., Vaulot D., Eikrem W. 2017. Chloropicophyceae, a new class of picophytoplanktonic prasinophytes. Scientific Reports 7:14019. DOI: 10.1038/s41598-017-12412-5.
Daugbjerg N., Fassel NMD., Moestrup Ø. 2019. Microscopy and phylogeny of Pyramimonas tatianae sp. nov. (Pyramimonadales, Chlorophyta), a scaly quadriflagellate from Golden Horn Bay (eastern Russia) and formal description of Pyramimonadophyceae classis nova . European Journal of Phycology 0:1–15. DOI: 10.¹⁰⁸⁰⁄_09670262.2019.1638524
Crépeault, O., Otis, C., Pombert, J.-F., Turmel, M. & Lemieux, C. 2024. Comparative plastome and mitogenome analyses indicate that the marine prasinophyte green algae Pycnococcus provasolii and Pseudoscourfieldia marina (Pseudoscourfieldiophyceae class nov., Chlorophyta) represent morphotypes of the same species. Journal of Phycology. 60:1021–7.

Ochrophyta/Stramenopiles

Adl, S.M., Bass, D., Lane, C.E., Lukeš, J., Schoch, C.L., Smirnov, A., Agatha, S. et al. 2019. Revisions to the Classification, Nomenclature, and Diversity of Eukaryotes. J. Eukaryot. Microbiol. 66:4–119.
Andersen RA., Graf L., Malakhov Y., Yoon HS. 2017. Rediscovery of the Ochromonas type species Ochromonas triangulata (Chrysophyceae) from its type locality (Lake Veysove, Donetsk region, Ukraine). Phycologia 56:591–604. DOI: 10.²²¹⁶⁄₁₇-15.1.
Arsenieff L., Le Gall F., Rigaut-Jalabert F., Mahé F., Sarno D., Gouhier L., Baudoux A-C., Simon N. 2020. Diversity and dynamics of relevant nanoplanktonic diatoms in the Western English Channel. The ISME Journal. DOI: 10.1038/s41396-020-0659-6.
Barcytė, D., Eikrem, W., Engesmo, A., Seoane, S., Wohlmann, J., Horák, A., Yurchenko, T., & Eliáš, M. (2021). Olisthodiscus represents a new class of Ochrophyta. Journal of Phycology, 57(4), 1094‑1118. https://doi.org/10.1111/jpy.13155
Charvet, Sophie, Warwick F. Vincent, et Connie Lovejoy. 2012. « Chrysophytes and Other Protists in High Arctic Lakes: Molecular Gene Surveys, Pigment Signatures and Microscopy ». Polar Biology 35 (5): 733‑48. https://doi.org/10.1007/s00300-011-1118-7.
Derelle, R., López-García, P., Timpano, H. & Moreira, D. 2016. A Phylogenomic Framework to Study the Diversity and Evolution of Stramenopiles (= Heterokonts). Mol. Biol. Evol. 33:2890–8.
Gaonkar, C.C., Piredda, R., Minucci, C., Mann, D.G., Montresor, M., Sarno, D. & Kooistra, W.H.C.F. 2018. Annotated 18S and 28S rDNA reference sequences of taxa in the planktonic diatom family Chaetocerotaceae. PLoS One. 13:e0208929.
Han KY., Graf L., Reyes CP., Melkonian B., Andersen RA., Yoon HS., Melkonian M. 2018. A Re-investigation of Sarcinochrysis marina (Sarcinochrysidales, Pelagophyceae) from its Type Locality and the Descriptions of Arachnochrysis, Pelagospilus, Sargassococcus and Sungminbooa genera nov. Protist 169:79–106. DOI: 10.1016/j.protis.2017.12.004.
Ichinomiya, M., dos Santos, A. L., Gourvil, P., Yoshikawa, S., Kamiya, M., Ohki, K., et al. (2016). Diversity and oceanic distribution of the Parmales (Bolidophyceae), a picoplanktonic group closely related to diatoms. ISME J. 10, 2419–2434. doi:10.1038/ismej.2016.38.
Jirsová, D., Füssy, Z., Richtová, J., Gruber, A., & Oborník, M. (2019). Morphology, ultrastructure, and mitochondrial genome of the marine non-photosynthetic bicosoecid Cafileria marina gen. Et sp. Nov. Microorganisms, 7(8), 240. https://doi.org/10.3390/microorganisms7080240
Massana, R., del Campo, J., Sieracki, M.E., Audic, S. & Logares, R. 2014. Exploring the uncultured microeukaryote majority in the oceans: reevaluation of ribogroups within stramenopiles. ISME J. 8:854–66.
Pan, J., del Campo, J., & Keeling, P. J. (2017). Reference Tree and Environmental Sequence Diversity of Labyrinthulomycetes. Journal of Eukaryotic Microbiology, 64(1), 88–96. https://doi.org/10.1111/jeu.12342
Schoenle, A., Hohlfeld, M., Rosse, M., Filz, P., Wylezich, C., Nitsche, F., & Arndt, H. (2020). Global comparison of bicosoecid Cafeteria-like flagellates from the deep ocean and surface waters, with reorganization of the family Cafeteriaceae. European Journal of Protistology, 73, 125665. https://doi.org/10.1016/j.ejop.2019.125665.
Scoble, Josephine Margaret, et Thomas Cavalier-Smith. 2014. « Scale Evolution in Paraphysomonadida (Chrysophyceae): Sequence Phylogeny and Revised Taxonomy of Paraphysomonas, New Genus Clathromonas, and 25 New Species ». European Journal of Protistology 50 (5): 551‑92. https://doi.org/10.1016/j.ejop.2014.08.001.

Haptophyta

Edvardsen, B., Egge, E. S., and Vaulot, D. (2016). Diversity and distribution of haptophytes revealed by environmental sequencing and metabarcoding – a review. Perspect. Phycol. 3, 77–91. doi:10.1127/pip/2016/0052.
Kawachi, M., Nakayama, T., Kayama, M., Nomura, M., Miyashita, H., Bojo, O., Rhodes, L., Sym, S., Pienaar, R. N., Probert, I., Inouye, I., & Kamikawa, R. (2021). Rappemonads are haptophyte phytoplankton. Current Biology. https://doi.org/10.1016/j.cub.2021.03.012
Bendif, E.M., Probert, I., Archontikis, O.A., Young, J.R., Beaufort, L., Rickaby, R.E. & Filatov, D. 2023. Rapid diversification underlying the global dominance of a cosmopolitan phytoplankton. ISME J. 1–11.

Ciliates

Agatha, S. and Strüder-Kypke, M.C. (2014) What Morphology and Molecules Tell Us about the Evolution of Oligotrichea (Alveolata, Ciliophora). Acta Protozool. 2014: 7790.
Bachy, C., Gómez, F., López-García, P., Dolan, J.R., and Moreira, D. (2012) Molecular Phylogeny of Tintinnid Ciliates (Tintinnida, Ciliophora). Protist 163: 873–887.
Boscaro V., Santoferrara L., Zhang Q., Gentekaki E., Syberg-Olsen M., del Campo J., Keeling P., 2018. EukRef–Ciliophora: A manually curated, phylogeny‐based database of small subunit rRNA gene sequences of ciliates. Environmental Microbiology, 20: 2218-2230.
Ganser, Maximilian H., Luciana F. Santoferrara, et Sabine Agatha. 2022. « Molecular Signature Characters Complement Taxonomic Diagnoses: A Bioinformatic Approach Exemplified by Ciliated Protists (Ciliophora, Oligotrichea) ». Molecular Phylogenetics and Evolution 170 (mai): 107433. https://doi.org/10.1016/j.ympev.2022.107433.
Santoferrara, L.F., Alder, V.V., and McManus, G.B. (2017) Phylogeny, classification and diversity of Choreotrichia and Oligotrichia (Ciliophora, Spirotrichea). Mol. Phylogenet. Evol. 112: 12–22.
Zhang, Q., Agatha, S., Zhang, W., Dong, J., Yu, Y., Jiao, N., and Gong, J. (2017) Three rDNA Loci-Based Phylogenies of Tintinnid Ciliates (Ciliophora, Spirotrichea, Choreotrichida). J. Eukaryot. Microbiol. 64: 226–241.

Dinoflagellates

Janouškovec, Jan, Gregory S. Gavelis, Fabien Burki, Donna Dinh, Tsvetan R. Bachvaroff, Sebastian G. Gornik, Kelley J. Bright, et al. 2017. Major Transitions in Dinoflagellate Evolution Unveiled by Phylotranscriptomics. Proceedings of the National Academy of Sciences 114 (2): E171–80. https://doi.org/10.1073/pnas.1614842114.
LaJeunesse, Todd C., John Everett Parkinson, Paul W. Gabrielson, Hae Jin Jeong, James Davis Reimer, Christian R. Voolstra, and Scott R. Santos. 2018. Systematic Revision of Symbiodiniaceae Highlights the Antiquity and Diversity of Coral Endosymbionts. Current Biology 28 (16): 2570-2580.e6. https://doi.org/10.1016/j.cub.2018.07.008.
Mordret, S., Piredda, R., Vaulot, D., Montresor, M., Kooistra, W.H.C.F. & Sarno, D. 2018. dinoref : A curated dinoflagellate (Dinophyceae) reference database for the 18S rRNA gene. Mol. Ecol. Resour. in press.

Apicomplexa

del Campo J., Heger TJ., Rodríguez-Martínez R., Worden AZ., Richards TA., Massana R., Keeling PJ. 2019. Assessing the Diversity and Distribution of Apicomplexans in Host and Free-Living Environments Using High-Throughput Amplicon Data and a Phylogenetically Informed Reference Framework. Frontiers in Microbiology 10:1–15. DOI: 10.3389/fmicb.2019.02373.

Plastids

Decelle, J., Romac, S., Stern, R.F., Bendif, E.M., Zingone, A., Audic, S., Guiry, M.D. et al. 2015. PhytoREF: a reference database of the plastidial 16S rRNA gene of photosynthetic eukaryotes with curated taxonomy. Mol. Ecol. Resour. 15:1435–144

Radiolaria

Biard, T., Bigeard, E., Audic, S., Poulain, J., Stemmann, L., Not, F., 2017. Biogeography and diversity of Collodaria (Radiolaria) in the global ocean. Nat. Publ. Gr. 1–42. doi:10.1038/ismej.2017.12
Capella-Gutiérrez, S., Silla-Martínez, J.M., Gabaldón, T., 2009. trimAl: A tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973. doi:10.1093/bioinformatics/btp348
Cavalier-Smith, T., Chao, E.E., Lewis, R., 2018. Multigene phylogeny and cell evolution of chromist infrakingdom Rhizaria: contrasting cell organisation of sister phyla Cercozoa and Retaria. Protoplasma 255, 1517–1574. doi:10.1007/s00709-018-1241-1
Decelle, J., Suzuki, N., Mahé, F., Vargas, C. De, Not, F., 2012b. Molecular Phylogeny and Morphological Evolution of the Acantharea (Radiolaria). Protist 163, 435–450. doi:10.1016/j.protis.2011.10.002
Gouy, M., Guindon, S., Gascuel, O., 2010. SeaView Version 4: A Multiplatform Graphical User Interface for Sequence Alignment and Phylogenetic Tree Building. Mol. Biol. Evol. 27, 221–224. doi:10.1093/molbev/msp259
Katoh, K., Standley, D.M., 2013. MAFFT multiple sequence alignment software version 7: Improvements in performance and usability. Mol. Biol. Evol. 30, 772–780. doi:10.1093/molbev/mst010
Larsson, A. (2014). AliView: a fast and lightweight alignment viewer and editor for large data sets. Bioinformatics30(22): 3276-3278. http://dx.doi.org/10.1093/bioinformatics/btu531
Nakamura, Y., Sandin, M.M., Suzuki N., Somiya R., Tuji A., Not, F, 2020. Phylogenetic revision of the order Entactinaria - Paleozoic relict Radiolaria (Rhizaria, SAR). Protist 171. doi:10.1016/j.protis.2019.125712
Rambaut A (2016) FigTree version 1.4.3. http://tree.bio.ed.ac.uk/software/figtree/
Sandin M.M., Biard T., Romac S., O’Dogherty L., Suzuki N., Not F., 2020. Morpho-molecular diversity and evolutionary analyses suggest hidden life styles in Spumellaria (Radiolaria) bioRxiv 2020.06.29.176917; doi: https://doi.org/10.¹¹⁰¹⁄₂₀₂₀.06.29.176917
Sandin, M.M., Pillet, L., Biard, T., Poirier, C., Bigeard, E., Romac, S., Suzuki, N., Not, F., 2019. Time Calibrated Morpho-molecular Classification of Nassellaria (Radiolaria). Protist 170, 187–208. doi:10.1016/j.protis.2019.02.002
Schloss, P.D., Westcott, S.L., Ryabin, T., Hall, J.R., Hartmann, M., Hollister, E.B., Lesniewski, R.A., Oakley, B.B., Parks, D.H., Robinson, C.J., Sahl, J.W., Stres, B., Thallinger, G.G., Van Horn, D.J., Weber, C.F., 2009. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541.doi:10.1128/AEM.01541-09
Stamatakis, A., 2014. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313. doi:10.1093/bioinformatics/btu033 Rognes, T., Flouri, T., Nichols, B., Quince, C., Mahé, F., 2016. VSEARCH: a versatile open source tool for metagenomics. PeerJ 4, e2584.doi:10.7717/peerj.2584

Excavata

Hohlfeld, Manon, Claudia Meyer, Alexandra Schoenle, Frank Nitsche, et Hartmut Arndt. 2023. « Biogeography, Autecology, and Phylogeny of Percolomonads Based on Newly Described Species ». Journal of Eukaryotic Microbiology 70 (1): e12930. https://doi.org/10.1111/jeu.12930.

Provora

Tikhonenkov, Denis V., Kirill V. Mikhailov, Ryan M. R. Gawryluk, Artem O. Belyaev, Varsha Mathur, Sergey A. Karpov, Dmitry G. Zagumyonnyi, et al. 2022. « Microbial Predators Form a New Supergroup of Eukaryotes ». Nature 612 (7941): 714‑19. https://doi.org/10.1038/s41586-022-05511-5.

Fungi

Galindo, L.J., López-García, P., Torruella, G. et al. Phylogenomics of a new fungal phylum reveals multiple waves of reductive evolution across Holomycota. Nat Commun 12, 4973 (2021). doi/ 10.1038/s41467-021-25308-w

PfR2

Wed, 27 Apr 2016 00:00:00 +0000

PhytoRef

Wed, 27 Apr 2016 00:00:00 +0000

PR2 primers

Wed, 27 Apr 2016 00:00:00 +0000

The pr2-primers database hosts a list of 18S rRNA primers and of primer-sets. It provides in silico analysis of these primer-sets against the PR² database.

Mon, 01 Jan 0001 00:00:00 +0000

Papers citing EukRef

del Campo J., Kolisko M., Boscaro V., Santoferrara LF., Nenarokov S., Massana R., Guillou L., Simpson A., Berney C., de Vargas C., Brown MW., Keeling PJ., Wegener Parfrey L. 2018. EukRef: Phylogenetic curation of ribosomal RNA to enhance understanding of eukaryotic diversity and distribution. PLOS Biology 16:e2005849. DOI: 10.1371/journal.pbio.2005849.

Number of papers citing EukRef: 95

2025

Mills, D. B., A. Vuillemin, K. Muschler, et al. (2025). “The Rise of Algae promoted eukaryote predation in the Neoproterozoic benthos”. In: Science Advances 11.8. Cited by: 0; All Open Access, Gold Open Access, Green Open Access. DOI: 10.1126/sciadv.adt2147.

Packer, J. A., D. Zavadska, E. J. Weston, et al. (2025). “Characterization of Allobodo yubaba sp. nov. and Novijibodo darinka gen. et sp. nov., cultivable free-living species of the phylogenetically enigmatic kinetoplastid taxon Allobodonidae”. In: Journal of Eukaryotic Microbiology 72.1. Cited by: 0; All Open Access, Hybrid Gold Open Access. DOI: 10.1111/jeu.13072.

Piwosz, K., A. Ameryk, K. Wdówka, et al. (2025). “Vertical distribution of heterotrophic nanoflagellates in the Baltic Proper”. In: Oceanologia 67.1. Cited by: 0. DOI: 10.5697/JMZS3739.

2024

Cho, A., D. V. Tikhonenkov, G. Lax, et al. (2024). “Phylogenomic position of genetically diverse phagotrophic stramenopile flagellates in the sediment-associated MAST-6 lineage and a potentially halotolerant placididean”. In: Molecular Phylogenetics and Evolution 190. Cited by: 7. DOI: 10.1016/j.ympev.2023.107964.

Cristi, A., C. S. Law, M. Pinkerton, et al. (2024). “Environmental driving forces and phytoplankton diversity across the Ross Sea region during a summer–autumn transition”. In: Limnology and Oceanography 69.4. Cited by: 1; All Open Access, Hybrid Gold Open Access, p. 772 – 788. DOI: 10.1002/lno.12526.

Debjit, D., T. Nayak, G. Das, et al. (2024). Metagenomics and bioinformatics in microbial ecology: current status and beyond. Cited by: 1 , p. 359 – 385. DOI: 10.1016/B978-0-323-98394-5.00009-2.

Huang, X., Y. Li, H. Du, et al. (2024). “Comparative assessment of the intragenomic variations of dinoflagellate Tripos species through single-cell sequencing”. In: Marine Pollution Bulletin 206. Cited by: 2. DOI: 10.1016/j.marpolbul.2024.116690.

Kang, Z., Z. Lei, W. Fei, et al. (2024). “Dynamics in eukaryotic algal communities regulate bacterial and fungal communities as biocrusts develop in a temperate desert in Central Asia”. In: Functional Ecology 38.3. Cited by: 2, p. 531 – 545. DOI: 10.1111/1365-2435.14496.

Knoll, L. B., B. Fry, N. M. Hayes, et al. (2024). “Reduced snow and increased nutrients show enhanced ice-associated photoautotrophic growth using a modified experimental under-ice design”. In: Limnology and Oceanography 69.1. Cited by: 5; All Open Access, Hybrid Gold Open Access, p. 203 – 216. DOI: 10.1002/lno.12469.

Krinos, A., R. Bowers, R. Rohwer, et al. (2024). “Time-series metagenomics reveals changing protistan ecology of a temperate dimictic lake”. In: Microbiome 12.1. Cited by: 3; All Open Access, Gold Open Access, Green Open Access. DOI: 10.1186/s40168-024-01831-y.

López-Rodríguez, M. R., C. G. Ribeiro, S. Rodríguez-Marconi, et al. (2024). “Stable dominance of parasitic dinoflagellates in Antarctic sponges”. In: PeerJ 12.11. Cited by: 0; All Open Access, Gold Open Access, Green Open Access. DOI: 10.7717/peerj.18365.

Maggard, I. J., K. B. Deel, T. W. Etoll, et al. (2024). “Freshwater mussels prefer a diet of stramenopiles and fungi over bacteria”. In: Scientific Reports 14.1. Cited by: 3; All Open Access, Gold Open Access, Green Open Access. DOI: 10.1038/s41598-024-62245-2.

Mazurkiewicz, M., J. Pawłowska, I. Barrenechea Angeles, et al. (2024). “Sediment DNA metabarcoding and morphology provide complementary insight into macrofauna and meiobenthos response to environmental gradients in an Arctic glacial fjord”. In: Marine Environmental Research 198. Cited by: 2; All Open Access, Green Open Access, Hybrid Gold Open Access. DOI: 10.1016/j.marenvres.2024.106552.

Renner, S. S., M. D. Scherz, C. L. Schoch, et al. (2024). “Improving the gold standard in NCBI GenBank and related databases: DNA sequences from type specimens and type strains”. In: Systematic Biology 73.2. Cited by: 4; All Open Access, Green Open Access, Hybrid Gold Open Access, p. 486 – 494. DOI: 10.1093/sysbio/syad068.

Wiśniewska, M. M., E. D. Salomaki, J. D. Silberman, et al. (2024). “Expanded gene and taxon sampling of diplomonads shows multiple switches to parasitic and free-living lifestyle”. In: BMC Biology 22.1. Cited by: 1; All Open Access, Gold Open Access. DOI: 10.1186/s12915-024-02013-w.

Wright, L., J. Garbarino, and C. Marizzi (2024). “Engaging Students and Teachers as Community Scientists in DNA Barcoding Initiatives”. In: Methods in Molecular Biology 2744. Cited by: 0, p. 525 – 535. DOI: 10.1007/978-1-0716-3581-0_32.

2023

Baltoumas, F. A., E. Karatzas, D. Paez-Espino, et al. (2023). “Exploring microbial functional biodiversity at the protein family level—From metagenomic sequence reads to annotated protein clusters”. In: Frontiers in Bioinformatics 3. Cited by: 3; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3389/fbinf.2023.1157956.

Belair, M., F. Pensec, J. Jany, et al. (2023). “Profiling Walnut Fungal Pathobiome Associated with Walnut Dieback Using Community-Targeted DNA Metabarcoding”. In: Plants 12.12. Cited by: 8; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3390/plants12122383.

Canino, A., C. Lemonnier, B. Alric, et al. (2023). “Which barcode to decipher freshwater microalgal assemblages? Tests on mock communities”. In: International Journal of Limnology 59. Cited by: 2; All Open Access, Green Open Access, Hybrid Gold Open Access. DOI: 10.1051/limn/2023008.

Cepon-Robins, T. J., E. K. Mallott, I. C. Recca, et al. (2023). “Exploring biocultural determinants of intestinal health: Do resource access and parasite exposure contribute to intestinal inflammation among a preliminary sample of children in rural Mississippi?” In: American Journal of Biological Anthropology 182.4. Cited by: 8, p. 606 – 619. DOI: 10.1002/ajpa.24574.

Dacks, J. B. and M. L. Ginger (2023). “Two decades taken at speed: genomics, cell biology, ecology, and evolution of protists”. In: BMC Biology 21.1. Cited by: 2; All Open Access, Gold Open Access, Green Open Access. DOI: 10.1186/s12915-023-01787-9.

Gaonkar, C. C. and L. Campbell (2023). “Metabarcoding reveals high genetic diversity of harmful algae in the coastal waters of Texas, Gulf of Mexico”. In: Harmful Algae 121. Cited by: 11; All Open Access, Bronze Open Access. DOI: 10.1016/j.hal.2022.102368.

González-Miguéns, R., E. Cano, A. Guillén-Oterino, et al. (2023). “A needle in a haystack: A new metabarcoding approach to survey diversity at the species level of Arcellinida (Amoebozoa: Tubulinea)”. In: Molecular Ecology Resources 23.5. Cited by: 7; All Open Access, Green Open Access, Hybrid Gold Open Access, p. 1034 – 1049. DOI: 10.1111/1755-0998.13771.

Groussman, R., S. Blaskowski, S. Coesel, et al. (2023). “MarFERReT, an open-source, version-controlled reference library of marine microbial eukaryote functional genes”. In: Scientific Data 10.1. Cited by: 6; All Open Access, Gold Open Access. DOI: 10.1038/s41597-023-02842-4.

Ikenoue, T., K. R. Bjørklund, A. K. Krabberød, et al. (2023). “Radiolaria and Phaeodaria (siliceous Rhizaria) in south-western and northern Norwegian fjords during late summer 2016: dominant species and biomass in shallow-water assemblages”. In: Polar Research 42. Cited by: 0; All Open Access, Gold Open Access, Green Open Access. DOI: 10.33265/polar.v42.9584.

Lefler, F. W., D. E. Berthold, and H. D. Laughinghouse (2023). “Cyanoseq: A database of cyanobacterial 16S rRNA gene sequences with curated taxonomy”. In: Journal of Phycology 59.3. Cited by: 29; All Open Access, Bronze Open Access, p. 470 – 480. DOI: 10.1111/jpy.13335.

Panova, M. A. Z., M. A. Varfolomeeva, E. R. Gafarova, et al. (2023). “First insights into the gut microbiomes and the diet of the Littorina snail ecotypes, a recently emerged marine evolutionary model”. In: Evolutionary Applications 16.2. Cited by: 8; All Open Access, Gold Open Access, Green Open Access, p. 365 – 378. DOI: 10.1111/eva.13447.

Petersen, H. C., R. Sapkota, A. Hiillos, et al. (2023). “Spatial and temporal dynamics of coastal benthic microbial communities along a salinity gradient”. In: Aquatic Microbial Ecology 89. Cited by: 0; All Open Access, Green Open Access, p. 127 – 142. DOI: 10.3354/ame02002.

Wang, L., M. Zhao, X. Du, et al. (2023). “Fungi and cercozoa regulate methane-associated prokaryotes in wetland methane emissions”. In: Frontiers in Microbiology 13. Cited by: 6; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3389/fmicb.2022.1076610.

Yadav, B. N. S., P. Sharma, S. Maurya, et al. (2023). “Metagenomics and metatranscriptomics as potential driving forces for the exploration of diversity and functions of micro-eukaryotes in soil”. In: 3 Biotech 13.12. Cited by: 2; All Open Access, Green Open Access. DOI: 10.1007/s13205-023-03841-3.

2022

Cahoon, A. B. and R. D. VanGundy (2022). “Alveolates (dinoflagellates, ciliates and apicomplexans) and Rhizarians are the most common microbial eukaryotes in temperate Appalachian karst caves”. In: Environmental Microbiology Reports 14.4. Cited by: 7; All Open Access, Green Open Access, p. 538 – 548. DOI: 10.1111/1758-2229.13060.

Caracciolo, M., F. Rigaut-Jalabert, S. Romac, et al. (2022). “Seasonal dynamics of marine protist communities in tidally mixed coastal waters”. In: Molecular Ecology 31.14. Cited by: 18; All Open Access, Green Open Access, Hybrid Gold Open Access, p. 3761 – 3783. DOI: 10.1111/mec.16539.

Cho, A., D. V. Tikhonenkov, E. Hehenberger, et al. (2022). “Monophyly of diverse Bigyromonadea and their impact on phylogenomic relationships within stramenopiles”. In: Molecular Phylogenetics and Evolution 171. Cited by: 13; All Open Access, Green Open Access. DOI: 10.1016/j.ympev.2022.107468.

Czech, L., A. Stamatakis, M. Dunthorn, et al. (2022). “Metagenomic Analysis Using Phylogenetic Placement—A Review of the First Decade”. In: Frontiers in Bioinformatics 2. Cited by: 23; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3389/fbinf.2022.871393.

De Assis Leite, D. C. and N. C. Gabiatti (2022). Advances in Microbial Molecular Biology: The Potential of the Tool for Agrobiotechnology. Cited by: 0 , p. 35 – 76. DOI: 10.1201/9781003110477-2.

Duerschlag, J., W. Mohr, T. G. Ferdelman, et al. (2022). “Niche partitioning by photosynthetic plankton as a driver of CO2-fixation across the oligotrophic South Pacific Subtropical Ocean”. In: ISME Journal 16.2. Cited by: 14; All Open Access, Green Open Access, Hybrid Gold Open Access, p. 465 – 476. DOI: 10.1038/s41396-021-01072-z.

Eshghi Sahraei, S., B. Furneaux, K. Kluting, et al. (2022). “Effects of operational taxonomic unit inference methods on soil microeukaryote community analysis using long-read metabarcoding”. In: Ecology and Evolution 12.3. Cited by: 5; All Open Access, Gold Open Access, Green Open Access. DOI: 10.1002/ece3.8676.

Frantal, D., S. Agatha, D. Beisser, et al. (2022). “Molecular Data Reveal a Cryptic Diversity in the Genus Urotricha (Alveolata, Ciliophora, Prostomatida), a Key Player in Freshwater Lakes, With Remarks on Morphology, Food Preferences, and Distribution”. In: Frontiers in Microbiology 12. Cited by: 18; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3389/fmicb.2021.787290.

Hammond, S. W., L. Lodolo, S. K. Hu, et al. (2022). “Methodological ‘lenses’ influence the characterization of phytoplankton dynamics in a coastal upwelling ecosystem”. In: Environmental Microbiology Reports 14.6. Cited by: 3, p. 897 – 906. DOI: 10.1111/1758-2229.13116.

Igai, K., O. Kitade, J. Fu, et al. (2022). “Fine-scale genetic diversity and putative ecotypes of oxymonad protists coinhabiting the hindgut of Reticulitermes speratus”. In: Molecular Ecology 31.4. Cited by: 4, p. 1317 – 1331. DOI: 10.1111/mec.16309.

Kanjer, L., K. Filek, M. Mucko, et al. (2022). “Surface microbiota of Mediterranean loggerhead sea turtles unraveled by 16S and 18S amplicon sequencing”. In: Frontiers in Ecology and Evolution 10. Cited by: 9; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3389/fevo.2022.907368.

Martins, S. J., S. J. Taerum, L. Triplett, et al. (2022). “Predators of Soil Bacteria in Plant and Human Health”. In: Phytobiomes Journal 6.3. Cited by: 22; All Open Access, Gold Open Access, p. 184 – 200. DOI: 10.1094/PBIOMES-11-21-0073-RVW.

Metz, S., P. Huber, V. Accattatis, et al. (2022). “Freshwater protists: unveiling the unexplored in a large floodplain system”. In: Environmental Microbiology 24.4. Cited by: 12, p. 1731 – 1745. DOI: 10.1111/1462-2920.15838.

Reid, B. N., J. A. Servis, M. Timmers, et al. (2022). “18S rDNA amplicon sequence data (V1-V3) of the Palmyra Atoll National Wildlife Refuge, Central Pacific”. In: Metabarcoding and Metagenomics 6. Cited by: 1; All Open Access, Gold Open Access, Green Open Access, p. 89 – 99. DOI: 10.3897/mbmg.6.78762.

Sandin, M. M., S. Romac, and F. Not (2022). “Intra-genomic rRNA gene variability of Nassellaria and Spumellaria (Rhizaria, Radiolaria) assessed by Sanger, MinION and Illumina sequencing”. In: Environmental Microbiology 24.7. Cited by: 10; All Open Access, Green Open Access, Hybrid Gold Open Access, p. 2979 – 2993. DOI: 10.1111/1462-2920.16081.

Sterling, A. R., L. Z. Holland, R. M. Bundy, et al. (2022). “Potential interactions between diatoms and bacteria are shaped by trace element gradients in the Southern Ocean”. In: Frontiers in Marine Science 9. Cited by: 4; All Open Access, Gold Open Access. DOI: 10.3389/fmars.2022.876830.

Tikhonenkov, D. V., M. Jamy, A. S. Borodina, et al. (2022). “On the origin of TSAR: Morphology, diversity and phylogeny of Telonemia”. In: Open Biology 12.3. Cited by: 11; All Open Access, Gold Open Access, Green Open Access. DOI: 10.1098/rsob.210325.

Zafeiropoulos, H., S. Paragkamian, S. Ninidakis, et al. (2022). “PREGO: A Literature and Data-Mining Resource to Associate Microorganisms, Biological Processes, and Environment Types”. In: Microorganisms 10.2. Cited by: 14; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3390/microorganisms10020293.

Zhao, Y. and G. A. Langlois (2022). “Ciliate Morpho-Taxonomy and Practical Considerations before Deploying Metabarcoding to Ciliate Community Diversity Surveys in Urban Receiving Waters”. In: Microorganisms 10.12. Cited by: 1; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3390/microorganisms10122512.

2021

Burki, F., M. M. Sandin, and M. Jamy (2021). “Diversity and ecology of protists revealed by metabarcoding”. In: Current Biology 31.19. Cited by: 102; All Open Access, Green Open Access, Hybrid Gold Open Access, p. R1267 – R1280. DOI: 10.1016/j.cub.2021.07.066.

Campbell, L., C. C. Gaonkar, and D. W. Henrichs (2021). Integrating imaging and molecular approaches to assess phytoplankton diversity. Cited by: 5 , p. 159 – 190. DOI: 10.1016/B978-0-12-822861-6.00013-3.

Canino, A., A. Bouchez, C. Laplace-Treyture, et al. (2021). “Phytool, a ShinyApp to homogenise taxonomy of freshwater microalgae from DNA barcodes and microscopic observations”. In: Metabarcoding and Metagenomics 5. Cited by: 7; All Open Access, Gold Open Access, Green Open Access, p. 199 – 205. DOI: 10.3897/mbmg.5.74096.

Dias, R. J. P., P. M. de Souza, M. F. Rossi, et al. (2021). “Ciliates as bioindicators of water quality: A case study in the neotropical region and evidence of phylogenetic signals (18S-rDNA)”. In: Environmental Pollution 268. Cited by: 12. DOI: 10.1016/j.envpol.2020.115760.

Díaz-Torres, O., J. de Anda, O. Y. Lugo-Melchor, et al. (2021). “Rapid Changes in the Phytoplankton Community of a Subtropical, Shallow, Hypereutrophic Lake During the Rainy Season”. In: Frontiers in Microbiology 12. Cited by: 28; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3389/fmicb.2021.617151.

Dumack, K. and M. Bonkowski (2021). “Protists in the plant microbiome: an untapped field of research”. In: Methods in Molecular Biology 2232. Cited by: 5, p. 77 – 84. DOI: 10.1007/978-1-0716-1040-4_8.

Gao, B., L. Chi, Y. Zhu, et al. (2021). “An introduction to next generation sequencing bioinformatic analysis in gut microbiome studies”. In: Biomolecules 11.4. Cited by: 99; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3390/biom11040530.

Greco, M., R. Morard, and M. Kucera (2021). “Single-cell metabarcoding reveals biotic interactions of the Arctic calcifier Neogloboquadrina pachyderma with the eukaryotic pelagic community”. In: Journal of Plankton Research 43.2. Cited by: 16; All Open Access, Bronze Open Access, Green Open Access, p. 113 – 125. DOI: 10.1093/plankt/fbab015.

Lavrinienko, A., T. Jernfors, J. J. Koskimäki, et al. (2021). “Does Intraspecific Variation in rDNA Copy Number Affect Analysis of Microbial Communities?” In: Trends in Microbiology 29.1. Cited by: 79; All Open Access, Green Open Access, Hybrid Gold Open Access, p. 19 – 27. DOI: 10.1016/j.tim.2020.05.019.

Mann, D. G., R. Trobajo, S. Sato, et al. (2021). “Ripe for reassessment: A synthesis of available molecular data for the speciose diatom family Bacillariaceae”. In: Molecular Phylogenetics and Evolution 158. Cited by: 47; All Open Access, Green Open Access. DOI: 10.1016/j.ympev.2020.106985.

Martini, S., F. Larras, A. Boyé, et al. (2021). “Functional trait-based approaches as a common framework for aquatic ecologists”. In: Limnology and Oceanography 66.3. Cited by: 125; All Open Access, Green Open Access, Hybrid Gold Open Access, p. 965 – 994. DOI: 10.1002/lno.11655.

Obertegger, U., M. Pindo, and G. Flaim (2021). “Do inferences about freshwater phytoplankton communities change when based on microscopy or high-throughput sequencing data?” In: Freshwater Biology 66.4. Cited by: 7, p. 640 – 655. DOI: 10.1111/fwb.13667.

Rajter, Ľ., I. Ewers, N. Graupner, et al. (2021). “Colpodean ciliate phylogeny and reference alignments for phylogenetic placements”. In: European Journal of Protistology 77. Cited by: 4. DOI: 10.1016/j.ejop.2020.125747.

Regaldo, L., V. E. Márquez, M. G. Latorre Rapela, et al. (2021). Prokaryotic and Eukaryotic Diversity in Wastewater Treatment: Phenotypic Characterization, Molecular Techniques, and Bioprospecting. Cited by: 0 , p. 343 – 365. DOI: 10.1016/B978-0-12-821881-5.00017-9.

Rimet, F., E. Aylagas, A. Borja, et al. (2021). “Metadata standards and practical guidelines for specimen and DNA curation when building barcode reference libraries for aquatic life”. In: Metabarcoding and Metagenomics 5. Cited by: 30; All Open Access, Gold Open Access, Green Open Access, p. 17 – 33. DOI: 10.3897/mbmg.5.58056.

Schiwitza, S. and F. Nitsche (2021). “A Needle in the Haystack – Mapping Sequences to Morphology Exemplified by the Loricate Choanoflagellate Enibas thessalia sp. nov. (Acanthoecida, Acanthoecidae)”. In: Protist 172.1. Cited by: 6. DOI: 10.1016/j.protis.2020.125782.

Snyder, R. A., J. A. Moss, L. Santoferrara, et al. (2021). “Ciliate microzooplankton from the Northeastern Gulf of Mexico”. In: ICES Journal of Marine Science 78.9. Cited by: 7, p. 3356 – 3371. DOI: 10.1093/icesjms/fsab002.

Tedersoo, L., M. Albertsen, S. Anslan, et al. (2021). “Perspectives and Benefits of High-Throughput Long-Read Sequencing in Microbial Ecology”. In: Applied and Environmental Microbiology 87.17. Cited by: 120; All Open Access, Green Open Access, p. 1 – 19. DOI: 10.1128/AEM.00626-21.

Tonjer, L., E. Thoen, L. Morgado, et al. (2021). “Fungal community dynamics across a forest–alpine ecotone”. In: Molecular Ecology 30.19. Cited by: 18; All Open Access, Green Open Access, p. 4926 – 4938. DOI: 10.1111/mec.16095.

Walker, L. M., T. Hoppe, and M. E. Silliker (2021). Molecular techniques and current research approaches. Cited by: 4 , p. 195 – 229. DOI: 10.1016/B978-0-12-824281-0.00006-3.

Zhou, Y., B. Sun, B. Xie, et al. (2021). “Warming reshaped the microbial hierarchical interactions”. In: Global Change Biology 27.24. Cited by: 142, p. 6331 – 6347. DOI: 10.1111/gcb.15891.

2020

Djemiel, C., D. Plassard, S. Terrat, et al. (2020). “µgreen-db: A reference database for the 23S rRNA gene of eukaryotic plastids and cyanobacteria”. In: Scientific Reports 10.1. Cited by: 24; All Open Access, Gold Open Access, Green Open Access. DOI: 10.1038/s41598-020-62555-1.

Fawley, M. W. and K. P. Fawley (2020). “Identification of eukaryotic microalgal strains”. In: Journal of Applied Phycology 32.5. Cited by: 32; All Open Access, Bronze Open Access, Green Open Access, p. 2699 – 2709. DOI: 10.1007/s10811-020-02190-5.

Fiore-Donno, A. M., T. Richter-Heitmann, and M. Bonkowski (2020). “Contrasting Responses of Protistan Plant Parasites and Phagotrophs to Ecosystems, Land Management and Soil Properties”. In: Frontiers in Microbiology 11. Cited by: 28; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3389/fmicb.2020.01823.

Gottschling, M., J. Chacón, A. Žerdoner Čalasan, et al. (2020). “Phylogenetic placement of environmental sequences using taxonomically reliable databases helps to rigorously assess dinophyte biodiversity in Bavarian lakes (Germany)”. In: Freshwater Biology 65.2. Cited by: 22; All Open Access, Green Open Access, Hybrid Gold Open Access, p. 193 – 208. DOI: 10.1111/fwb.13413.

Irion, S., L. Jardillier, I. Sassenhagen, et al. (2020). “Marked spatiotemporal variations in small phytoplankton structure in contrasted waters of the Southern Ocean (Kerguelen area)”. In: Limnology and Oceanography 65.11. Cited by: 14; All Open Access, Green Open Access, Hybrid Gold Open Access, p. 2835 – 2852. DOI: 10.1002/lno.11555.

Kolisko, M., O. Flegontova, A. Karnkowska, et al. (2020). “EukRef-excavates: Seven curated SSU ribosomal RNA gene databases”. In: Database 2020. Cited by: 17; All Open Access, Gold Open Access, Green Open Access. DOI: 10.1093/database/baaa080.

Lukešová, S., M. Karlicki, L. Tomečková Hadariová, et al. (2020). “Analyses of environmental sequences and two regions of chloroplast genomes revealed the presence of new clades of photosynthetic euglenids in marine environments”. In: Environmental Microbiology Reports 12.1. Cited by: 6, p. 78 – 91. DOI: 10.1111/1758-2229.12817.

Mann, A. E., F. Mazel, M. A. Lemay, et al. (2020). “Biodiversity of protists and nematodes in the wild nonhuman primate gut”. In: ISME Journal 14.2. Cited by: 35; All Open Access, Green Open Access, Hybrid Gold Open Access, p. 609 – 622. DOI: 10.1038/s41396-019-0551-4.

Santoferrara, L. F. and G. B. McManus (2020). Diversity and biogeography as revealed by morphologies and DNA sequences: Tintinnid ciliates as an example. Cited by: 20 , p. 85 – 118.

Santoferrara, L., F. Burki, S. Filker, et al. (2020). “Perspectives from Ten Years of Protist Studies by High-Throughput Metabarcoding”. In: Journal of Eukaryotic Microbiology 67.5. Cited by: 81; All Open Access, Green Open Access, p. 612 – 622. DOI: 10.1111/jeu.12813.

Tůmová, P., E. Nohýnková, A. Klingl, et al. (2020). “A rapid workflow for the characterization of small numbers of unicellular eukaryotes by using correlative light and electron microscopy”. In: Journal of Microbiological Methods 172. Cited by: 5. DOI: 10.1016/j.mimet.2020.105888.

2019

Adl, S. M., D. Bass, C. E. Lane, et al. (2019). “Revisions to the Classification, Nomenclature, and Diversity of Eukaryotes”. In: Journal of Eukaryotic Microbiology 66.1. Cited by: 967; All Open Access, Green Open Access, Hybrid Gold Open Access, p. 4 – 119. DOI: 10.1111/jeu.12691.

Caron, D. A. and S. K. Hu (2019). “Are We Overestimating Protistan Diversity in Nature?” In: Trends in Microbiology 27.3. Cited by: 73; All Open Access, Green Open Access, p. 197 – 205. DOI: 10.1016/j.tim.2018.10.009.

Del Campo, J., T. J. Heger, R. Rodríguez-Martínez, et al. (2019). “Assessing the diversity and distribution of apicomplexans in host and free-living environments using high-throughput amplicon data and a phylogenetically informed reference framework”. In: Frontiers in Microbiology 10.OCT. Cited by: 36; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3389/fmicb.2019.02373.

Ku, C. and A. Sebé-Pedrós (2019). “Using single-cell transcriptomics to understand functional states and interactions in microbial eukaryotes”. In: Philosophical Transactions of the Royal Society B: Biological Sciences 374.1786. Cited by: 24; All Open Access, Bronze Open Access, Green Open Access. DOI: 10.1098/rstb.2019.0098.

Linard, B., K. Swenson, and F. Pardi (2019). “Rapid alignment-free phylogenetic identification of metagenomic sequences”. In: Bioinformatics 35.18. Cited by: 33; All Open Access, Green Open Access, p. 3303 – 3312. DOI: 10.1093/bioinformatics/btz068.

Lutz, S., L. Procházková, L. G. Benning, et al. (2019). “Evaluating amplicon high–throughput sequencing data of microalgae living in melting snow: Improvements and limitations”. In: Fottea 19.2. Cited by: 22; All Open Access, Gold Open Access, Green Open Access, p. 115 – 131. DOI: 10.5507/fot.2019.003.

Metz, S., D. Singer, I. Domaizon, et al. (2019). “Global distribution of Trebouxiophyceae diversity explored by high-throughput sequencing and phylogenetic approaches”. In: Environmental Microbiology 21.10. Cited by: 17; All Open Access, Green Open Access, p. 3885 – 3895. DOI: 10.1111/1462-2920.14738.

Morard, R., N. M. Vollmar, M. Greco, et al. (2019). “Unassigned diversity of planktonic foraminifera from environmental sequencing revealed as known but neglected species”. In: PLoS ONE 14.3. Cited by: 22; All Open Access, Gold Open Access, Green Open Access. DOI: 10.1371/journal.pone.0213936.

PrzyboŚ, E. and S. Tarcz (2019). “Global molecular variation of Paramecium jenningsi complex (Ciliophora, Protista): a starting point for further, detailed biogeography surveys”. In: Systematics and Biodiversity 17.5. Cited by: 8, p. 527 – 539. DOI: 10.1080/14772000.2019.1643424.

Richardson, E. and J. B. Dacks (2019). “Microbial Eukaryotes in oil sands environments: Heterotrophs in the spotlight”. In: Microorganisms 7.6. Cited by: 6; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3390/microorganisms7060178.

Rimet, F., E. Gusev, M. Kahlert, et al. (2019). “Diat.barcode, an open-access curated barcode library for diatoms”. In: Scientific Reports 9.1. Cited by: 117; All Open Access, Gold Open Access, Green Open Access. DOI: 10.1038/s41598-019-51500-6.

Santoferrara, L. F. (2019). “Current practice in plankton metabarcoding: Optimization and error management”. In: Journal of Plankton Research 41.5. Cited by: 61; All Open Access, Bronze Open Access, p. 571 – 582. DOI: 10.1093/plankt/fbz041.

Yu, Z. and N. Chen (2019). “Emerging trends in red tide and major research progresses; [国内外赤潮的发展趋势与研究热点]”. In: Oceanologia et Limnologia Sinica 50.3. Cited by: 38, p. 474 – 486. DOI: 10.11693/hyhz20190200041.

2018

Duarte, S., L. Nunes, P. A. Borges, et al. (2018). “A bridge too far? An integrative framework linking classical protist taxonomy and metabarcoding in lower termites”. In: Frontiers in Microbiology 9.NOV. Cited by: 4; All Open Access, Gold Open Access, Green Open Access. DOI: 10.3389/fmicb.2018.02620.

Mon, 01 Jan 0001 00:00:00 +0000

Papers citing PR2

Guillou, L., Bachar, D., Audic, S., Bass, D., Berney, C., Bittner, L., Boutte, C., Burgaud, G., de Vargas, C., Decelle, J., del Campo, J., Dolan, J. R., Dunthorn, M., Edvardsen, B., Holzmann, M., Kooistra, W. H. C. F., Lara, E., Le Bescot, N., Logares, R., … Christen, R. (2013). The Protist Ribosomal Reference database (PR2): A catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy. Nucleic Acids Research, 41(D1), D597–D604. https://doi.org/10.1093/nar/gks1160

References are available as a Zotero group

2025

Adyari, B., L. Zhang, A. Maravić, et al. (2025). “Urbanization enhances consumer protist-driven ARGs dissemination in riverine ecosystems”. In: Environment International 195. DOI: 10.1016/j.envint.2024.109238.

Alacid, E., A. Reñé, N. Timoneda, et al. (2025). “Macroalgal biofilm harbours a wide diversity of parasitic protists with distinct temporal dynamics”. In: Molecular Ecology 34.5. DOI: 10.1111/mec.17666.

Amacker, N., Z. Gao, A. L. Jousset, et al. (2025). “Identity and timing of protist inoculation affect plant performance largely irrespective of changes in the rhizosphere microbial community”. In: Applied and Environmental Microbiology 91.4. DOI: 10.1128/aem.00240-25.

Badra, M., J. Freudenthal, and K. Dumack (2025). “Sludge retention time in anaerobic digestion affects Archaea by a cascade through microeukaryotes”. In: Water Research 278. DOI: 10.1016/j.watres.2025.123371.

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2024

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2023

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2021

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Suleiman, A. K. A., K. S. Lourenço, C. Clark, et al. (2020). “From toilet to agriculture: Fertilization with microalgal biomass from wastewater impacts the soil and rhizosphere active microbiomes, greenhouse gas emissions and plant growth”. In: Resources, Conservation and Recycling 161. DOI: 10.1016/j.resconrec.2020.104924.

Sun, P., Y. Wang, E. Laws, et al. (2020). “Water mass–driven spatial effects and environmental heterogeneity shape microeukaryote biogeography in a subtropical, hydrographically complex ocean system - A case study of ciliates”. In: Science of the Total Environment 706. DOI: 10.1016/j.scitotenv.2019.135753.

Sunagawa, S., S. G. Acinas, P. Bork, et al. (2020). “Tara Oceans: towards global ocean ecosystems biology”. In: Nature Reviews Microbiology 18.8, pp. 428 - 445. DOI: 10.1038/s41579-020-0364-5.

Taerum, S. J., B. Steven, D. J. Gage, et al. (2020). “Validation of a PNA clamping method for reducing host DNA amplification and increasing eukaryotic diversity in rhizosphere microbiome studies”. In: Phytobiomes Journal 4.4, pp. 291 - 302. DOI: 10.1094/PBIOMES-05-20-0040-TA.

Thompson, A. R., S. Geisen, and B. J. Adams (2020). “Shotgun metagenomics reveal a diverse assemblage of protists in a model Antarctic soil ecosystem”. In: Environmental Microbiology 22.11, pp. 4620 - 4632. DOI: 10.1111/1462-2920.15198.

Tian, H., J. Feng, L. Zhang, et al. (2020). “Ecological drivers of methanotrophic communities in paddy soils around mercury mining areas”. In: Science of the Total Environment 721. DOI: 10.1016/j.scitotenv.2020.137760.

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Velasco-González, I., A. Sanchez-Jimenez, D. Singer, et al. (2020). “Rain-fed granite rock basins accumulate a high diversity of dormant microbial eukaryotes”. In: Microbial Ecology 79.4, pp. 882 - 897. DOI: 10.1007/s00248-019-01463-y.

Wang, W., K. Ren, H. Chen, et al. (2020). “Seven-year dynamics of testate amoeba communities driven more by stochastic than deterministic processes in two subtropical reservoirs”. In: Water Research 185. DOI: 10.1016/j.watres.2020.116232.

Wang, X., J. Long, J. Li, et al. (2020). “Diversity of soil eukaryotic microbes in different succession stages in maolan karst forest of guizhou; [贵州茂兰喀斯特森林不同演替下土壤真核微生物多样性]”. In: Huanjing Kexue/Environmental Science 41.9, pp. 4314 - 4321. DOI: 10.13227/j.hjkx.202001010.

Wang, Y., G. Li, F. Shi, et al. (2020). “Taxonomic diversity of pico-/nanoeukaryotes is related to dissolved oxygen and productivity, but functional composition is shaped by limiting nutrients in eutrophic coastal oceans”. In: Frontiers in Microbiology 11. DOI: 10.3389/fmicb.2020.601037.

Wang, Z., X. Gong, Y. Zheng, et al. (2020). “Soil protist communities in burrowing and casting hotspots of different earthworm species”. In: Soil Biology and Biochemistry 144. DOI: 10.1016/j.soilbio.2020.107774.

Wideman, J. G., A. Monier, R. Rodríguez-Martínez, et al. (2020). “Unexpected mitochondrial genome diversity revealed by targeted single-cell genomics of heterotrophic flagellated protists”. In: Nature Microbiology 5.1, pp. 154 - 165. DOI: 10.1038/s41564-019-0605-4.

Xiong, W., X. Huang, Y. Chen, et al. (2020). “Zooplankton biodiversity monitoring in polluted freshwater ecosystems: A technical review”. In: Environmental Science and Ecotechnology 1. DOI: 10.1016/j.ese.2019.100008.

Xiong, W., Y. Song, K. Yang, et al. (2020). “Rhizosphere protists are key determinants of plant health”. In: Microbiome 8.1. DOI: 10.1186/s40168-020-00799-9.

Xu, D., H. Kong, E. Yang, et al. (2020). “Contrasting community composition of active microbial eukaryotes in melt ponds and sea water of the arctic ocean revealed by high throughput sequencing”. In: Frontiers in Microbiology 11. DOI: 10.3389/fmicb.2020.01170.

Xu, Z., Y. Li, Y. Lu, et al. (2020). “Impacts of the Zhe-Min Coastal Current on the biogeographic pattern of microbial eukaryotic communities”. In: Progress in Oceanography 183. DOI: 10.1016/j.pocean.2020.102309.

Yeh, H. D., J. M. Questel, K. R. Maas, et al. (2020). “Metabarcoding analysis of regional variation in gut contents of the copepod Calanus finmarchicus in the North Atlantic Ocean”. In: Deep-Sea Research Part II: Topical Studies in Oceanography 180. DOI: 10.1016/j.dsr2.2020.104738.

Zaiko, A., S. A. Wood, X. Pochon, et al. (2020). “Elucidating biodiversity shifts in ballast water tanks during a cross-latitudinal transfer: Complementary insights from molecular analyses”. In: Environmental Science and Technology 54.13, pp. 8443 - 8454. DOI: 10.1021/acs.est.0c01931.

Zamora-Terol, S., A. Novotny, and M. Winder (2020). “Reconstructing marine plankton food web interactions using DNA metabarcoding”. In: Molecular Ecology 29.17, pp. 3380 - 3395. DOI: 10.1111/mec.15555.

Zhao, F., S. Filker, K. Xu, et al. (2020). “Microeukaryote communities exhibit phyla-specific distance-decay patterns and an intimate link between seawater and sediment habitats in the Western Pacific Ocean”. In: Deep-Sea Research Part I: Oceanographic Research Papers 160. DOI: 10.1016/j.dsr.2020.103279.

Zhao, F., C. Wang, K. Xu, et al. (2020). “Diversity and connectivity of microeukaryote communities across multiple habitats from intertidal zone to deep-sea floor in the Western Pacific Ocean”. In: Deep-Sea Research Part I: Oceanographic Research Papers 165. DOI: 10.1016/j.dsr.2020.103395.

Zhao, Z., J. He, Z. Quan, et al. (2020). “Fertilization changes soil microbiome functioning, especially phagotrophic protists”. In: Soil Biology and Biochemistry 148. DOI: 10.1016/j.soilbio.2020.107863.

Živaljić, S., A. Scherwass, A. Schoenle, et al. (2020). “A barotolerant ciliate isolated from the abyssal deep sea of the North Atlantic: Euplotes dominicanus sp. n. (Ciliophora, Euplotia)”. In: European Journal of Protistology 73. DOI: 10.1016/j.ejop.2019.125664.

2019

Ahmed, M., M. A. Back, T. Prior, et al. (2019). “Metabarcoding of soil nematodes: The importance of taxonomic coverage and availability of reference sequences in choosing suitable marker(s)”. In: Metabarcoding and Metagenomics 3, pp. 37 - 99. DOI: 10.3897/mbmg.3.36408.

Angelakis, E., D. Bachar, M. Yasir, et al. (2019). “Treponema species enrich the gut microbiota of traditional rural populations but are absent from urban individuals”. In: New Microbes and New Infections 27, pp. 14 - 21. DOI: 10.1016/j.nmni.2018.10.009.

Angelakis, E., D. Bachar, M. Yasir, et al. (2019). “Comparison of the gut microbiota of obese individuals from different geographic origins”. In: New Microbes and New Infections 27, pp. 40 - 47. DOI: 10.1016/j.nmni.2018.11.005.

Angelova, A. G., G. A. Ellis, H. W. Wijesekera, et al. (2019). “Microbial composition and variability of natural marine planktonic and biofouling communities from the bay of bengal”. In: Frontiers in Microbiology 10. DOI: 10.3389/fmicb.2019.02738.

Belilla, J., D. Moreira, L. Jardillier, et al. (2019). “Hyperdiverse archaea near life limits at the polyextreme geothermal Dallol area”. In: Nature Ecology and Evolution 3.11, pp. 1552 - 1561. DOI: 10.1038/s41559-019-1005-0.

Boeuf, D., B. R. Edwards, J. M. Eppley, et al. (2019). “Biological composition and microbial dynamics of sinking particulate organic matter at abyssal depths in the oligotrophic open ocean”. In: Proceedings of the National Academy of Sciences of the United States of America 116.24, pp. 11824 - 11832. DOI: 10.1073/pnas.1903080116.

Boscaro, V., M. J. Syberg-Olsen, N. A. T. Irwin, et al. (2019). “What can environmental sequences tell us about the distribution of low-rank taxa? The case of euplotes (ciliophora, spirotrichea), including a description of euplotes enigma sp. nov.” In: Journal of Eukaryotic Microbiology 66.2, pp. 281 - 293. DOI: 10.1111/jeu.12669.

Buccheri, M. A., E. Salvo, M. Coci, et al. (2019). “Investigating microbial indicators of anthropogenic marine pollution by 16S and 18S High-Throughput Sequencing (HTS) library analysis”. In: FEMS Microbiology Letters 366.14. DOI: 10.1093/femsle/fnz179.

Caron, D. A. and S. K. Hu (2019). “Are we overestimating protistan diversity in nature?” In: Trends in Microbiology 27.3, pp. 197 - 205. DOI: 10.1016/j.tim.2018.10.009.

Chambouvet, A., A. Monier, F. Maguire, et al. (2019). “Intracellular infection of diverse diatoms by an evolutionary distinct relative of the fungi”. In: Current Biology 29.23, pp. 4093 - 4101.e4. DOI: 10.1016/j.cub.2019.09.074.

Chénard, C., W. Wijaya, D. Vaulot, et al. (2019). “Temporal and spatial dynamics of Bacteria, Archaea and protists in equatorial coastal waters”. In: Scientific Reports 9.1. DOI: 10.1038/s41598-019-52648-x.

Cleary, D. F. R. (2019). “A comparison of microeukaryote communities inhabiting sponges and seawater in a Taiwanese coral reef system”. In: Annals of Microbiology 69.8, pp. 861 - 866. DOI: 10.1007/s13213-019-01476-5.

Cleary, D. and N. Gomes (2019). “Baseline information on prokaryotic and microeukaryotic plankton communities inside and outside of Indonesian marine lakes”. In: Journal of Sea Research 148-149, pp. 23 - 32. DOI: 10.1016/j.seares.2019.04.001.

Cordier, T., A. Lanzén, L. Apothéloz-Perret-Gentil, et al. (2019). “Embracing environmental genomics and machine learning for routine biomonitoring”. In: Trends in Microbiology 27.5, pp. 387 - 397. DOI: 10.1016/j.tim.2018.10.012.

Couton, M., T. Comtet, S. Le Cam, et al. (2019). “Metabarcoding on planktonic larval stages: An efficient approach for detecting and investigating life cycle dynamics of benthic aliens”. In: Management of Biological Invasions 10.4, pp. 657 - 689. DOI: 10.3391/mbi.2019.10.4.06.

Cruaud, P., A. Vigneron, M. Fradette, et al. (2019). “Annual protist community dynamics in a freshwater ecosystem undergoing contrasted climatic conditions: The saint-charles river (canada)”. In: Frontiers in Microbiology 10. DOI: 10.3389/fmicb.2019.02359.

Czech, L., P. Barbera, and A. Stamatakis (2019). “Methods for automatic reference trees and multilevel phylogenetic placement”. In: Bioinformatics (Oxford, England) 35.7, pp. 1151 - 1158. DOI: 10.1093/bioinformatics/bty767.

Degrune, F., K. Dumack, A. M. Fiore-Donno, et al. (2019). “Distinct communities of Cercozoa at different soil depths in a temperate agricultural field”. In: FEMS Microbiology Ecology 95.4. DOI: 10.1093/femsec/fiz041.

Demory, D., A. Baudoux, A. Monier, et al. (2019). “Picoeukaryotes of the Micromonas genus: sentinels of a warming ocean”. In: ISME Journal 13.1, pp. 132 - 146. DOI: 10.1038/s41396-018-0248-0.

Duarte, L. N., F. J. Coelho, D. F. Cleary, et al. (2019). “Bacterial and microeukaryotic plankton communities in a semi-intensive aquaculture system of sea bass (Dicentrarchus labrax): A seasonal survey”. In: Aquaculture (Amsterdam, Netherlands) 503, pp. 59 - 69. DOI: 10.1016/j.aquaculture.2018.12.066.

Dufresne, Y., F. Lejzerowicz, L. A. Perret-Gentil, et al. (2019). “SLIM: A flexible web application for the reproducible processing of environmental DNA metabarcoding data”. In: BMC Bioinformatics 20.1. DOI: 10.1186/s12859-019-2663-2.

Faure, E., F. Not, A. Benoiston, et al. (2019). “Mixotrophic protists display contrasted biogeographies in the global ocean”. In: ISME Journal 13.4, pp. 1072 - 1083. DOI: 10.1038/s41396-018-0340-5.

Fiore-Donno, A. M., T. Richter-Heitmann, F. Degrune, et al. (2019). “Functional traits and spatio-temporal structure of a major group of soil protists (rhizaria: Cercozoa) in a temperate grassland”. In: Frontiers in Microbiology 10.JUN. DOI: 10.3389/fmicb.2019.01332.

Forster, D., S. Filker, R. Kochems, et al. (2019). “A comparison of different ciliate metabarcode genes as bioindicators for environmental impact assessments of salmon aquaculture”. In: Journal of Eukaryotic Microbiology 66.2, pp. 294 - 308. DOI: 10.1111/jeu.12670.

Gao, Y., Y. Chen, W. Xiong, et al. (2019). “Distribution patterns of dinoflagellate communities along the songhua river”. In: PeerJ 2019.4. DOI: 10.7717/peerj.6733.

Geisen, S., M. J. Briones, H. Gan, et al. (2019). “A methodological framework to embrace soil biodiversity”. In: Soil Biology and Biochemistry 136. DOI: 10.1016/j.soilbio.2019.107536.

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Gołębiewski, M., A. Tarasek, M. Sikora, et al. (2019). “Rapid microbial community changes during initial stages of pine litter decomposition”. In: Microbial Ecology 77.1, pp. 56 - 75. DOI: 10.1007/s00248-018-1209-x.

Gómez-Consarnau, L., D. M. Needham, P. K. Weber, et al. (2019). “Influence of light on particulate organic matter utilization by attached and free-living marine bacteria”. In: Frontiers in Microbiology 10.JUN. DOI: 10.3389/fmicb.2019.01204.

Gran-Stadniczeñko, S., E. Egge, V. Hostyeva, et al. (2019). “Protist diversity and seasonal dynamics in skagerrak plankton communities as revealed by metabarcoding and microscopy”. In: Journal of Eukaryotic Microbiology 66.3, pp. 494 - 513. DOI: 10.1111/jeu.12700.

Gutierrez-Rodriguez, A., M. R. Stukel, A. Lopes dos Santos, et al. (2019). “High contribution of rhizaria (radiolaria) to vertical export in the california current ecosystem revealed by DNA metabarcoding”. In: ISME Journal 13.4, pp. 964 - 976. DOI: 10.1038/s41396-018-0322-7.

Haas, S., D. K. Desai, J. LaRoche, et al. (2019). “Geomicrobiology of the carbon, nitrogen and sulphur cycles in Powell Lake: a permanently stratified water column containing ancient seawater”. In: Environmental Microbiology 21.10, pp. 3927 - 3952. DOI: 10.1111/1462-2920.14743.

Harkes, P., A. K. A. Suleiman, S. J. J. van den Elsen, et al. (2019). “Conventional and organic soil management as divergent drivers of resident and active fractions of major soil food web constituents”. In: Scientific Reports 9.1. DOI: 10.1038/s41598-019-49854-y.

He, X., T. F. Sutherland, J. Pawlowski, et al. (2019). “Responses of foraminifera communities to aquaculture-derived organic enrichment as revealed by environmental DNA metabarcoding”. In: Molecular Ecology 28.5, pp. 1138 - 1153. DOI: 10.1111/mec.15007.

Isabwe, A., K. Ren, Y. Wang, et al. (2019). “Community assembly mechanisms underlying the core and random bacterioplankton and microeukaryotes in a river-reservoir system”. In: Water (Switzerland) 11.6. DOI: 10.3390/w11061127.

Kataoka, T. and R. Kondo (2019a). “Data on taxonomic annotation and diversity of 18S rRNA gene amplicon libraries derived from high throughput sequencing”. In: Data in Brief 25. DOI: 10.1016/j.dib.2019.104213.

Kataoka, T. and R. Kondo (2019b). “Protistan community composition in anoxic sediments from three salinity-disparate Japanese lakes”. In: Estuarine, Coastal and Shelf Science 224, pp. 34 - 42. DOI: 10.1016/j.ecss.2019.04.046.

Kong, J., Y. Wang, A. Warren, et al. (2019). “Diversity distribution and assembly mechanisms of planktonic and benthic microeukaryote communities in intertidal zones of southeast fujian, china”. In: Frontiers in Microbiology 10. DOI: 10.3389/fmicb.2019.02640.

Kulk, G., A. Buist, W. H. van de Poll, et al. (2019). “Size scaling of photophysiology and growth in four freshly isolated diatom species from Ryder Bay, western Antarctic peninsula”. In: Journal of Phycology 55.2, pp. 314 - 328. DOI: 10.1111/jpy.12813.

Lambert, S., M. Tragin, J. Lozano, et al. (2019). “Rhythmicity of coastal marine picoeukaryotes, bacteria and archaea despite irregular environmental perturbations”. In: ISME Journal 13.2, pp. 388 - 401. DOI: 10.1038/s41396-018-0281-z.

Lentendu, G., P. R. B. Buosi, A. F. Cabral, et al. (2019). “Protist biodiversity and biogeography in lakes from four brazilian river–floodplain systems”. In: Journal of Eukaryotic Microbiology 66.4, pp. 592 - 599. DOI: 10.1111/jeu.12703.

Leray, M., N. Knowlton, S. Ho, et al. (2019). “GenBank is a reliable resource for 21st century biodiversity research”. In: Proceedings of the National Academy of Sciences of the United States of America 116.45, pp. 22651 - 22656. DOI: 10.1073/pnas.1911714116.

Li, F., X. Zhang, Y. Xie, et al. (2019). “Sedimentary DNA reveals over 150 years of ecosystem change by human activities in Lake Chao, China”. In: Environment International 133. DOI: 10.1016/j.envint.2019.105214.

Liu, F., X. Zhang, S. Tang, et al. (2019). “Effects of acid mine drainage on eukaryotic community in river sediments; [酸性矿山废水对沉积物真核微生物群落的影响]”. In: Zhongguo Huanjing Kexue/China Environmental Science 39.12, pp. 5285 - 5292.

Liu, L., H. Chen, M. Liu, et al. (2019). “Response of the eukaryotic plankton community to the cyanobacterial biomass cycle over 6 years in two subtropical reservoirs”. In: ISME Journal 13.9, pp. 2196 - 2208. DOI: 10.1038/s41396-019-0417-9.

Liu, M., Y. Xue, and J. Yang (2019). “Rare plankton subcommunities are far more affected by DNA extraction kits than abundant plankton”. In: Frontiers in Microbiology 10.MAR. DOI: 10.3389/fmicb.2019.00454.

Lupatini, M., G. W. Korthals, L. F. Roesch, et al. (2019). “Long-term farming systems modulate multi-trophic responses”. In: Science of the Total Environment 646, pp. 480 - 490. DOI: 10.1016/j.scitotenv.2018.07.323.

Macingo, S. C., K. A. Kormas, A. Oikonomou, et al. (2019). “Taxa-area and distance-decay relationships of unicellular eukaryotes along an elevation gradient of mountainous freshwater ecosystems”. In: Journal of Plankton Research 41.6, pp. 821 - 834. DOI: 10.1093/plankt/fbz066.

Marquardt, M., R. Skogseth, I. Wiedmann, et al. (2019). “Vertical export of marine pelagic protists in an ice-free high-Arctic fjord (Adventfjorden, West Spitsbergen) throughout 2011−2012”. In: Aquatic Microbial Ecology 83.1, pp. 65 - 82. DOI: 10.3354/ame01904.

Metz, S., A. L. Dos Santos, M. C. Berman, et al. (2019). “Diversity of photosynthetic picoeukaryotes in eutrophic shallow lakes as assessed by combining flow cytometry cell-sorting and high throughput sequencing”. In: FEMS Microbiology Ecology 95.5. DOI: 10.1093/femsec/fiz038.

Moore, L. R., T. Huang, M. Ostrowski, et al. (2019). “Unicellular cyanobacteria are important components of phytoplankton communities in Australia’s northern oceanic ecoregions”. In: Frontiers in Microbiology 10.JAN. DOI: 10.3389/fmicb.2018.03356.

Mukherjee, I., Y. Hodoki, Y. Okazaki, et al. (2019). “Widespread dominance of kinetoplastids and unexpected presence of diplonemids in deep freshwater lakes”. In: Frontiers in Microbiology 10. DOI: 10.3389/fmicb.2019.02375.

Murdock, S. A. and S. K. Juniper (2019). “Hydrothermal vent protistan distribution along the Mariana arc suggests vent endemics may be rare and novel”. In: Environmental Microbiology 21.10, pp. 3796 - 3815. DOI: 10.1111/1462-2920.14729.

Nagler, M., K. Kozjek, M. Etemadi, et al. (2019). “Simple yet effective: Microbial and biotechnological benefits of rumen liquid addition to lignocellulose-degrading biogas plants”. In: Journal of Biotechnology 300, pp. 1 - 10. DOI: 10.1016/j.jbiotec.2019.05.004.

Panagiota-Chronopoulou, M., I. Salonen, C. Bird, et al. (2019). “Metabarcoding insights into the trophic behavior and identity of intertidal benthic foraminifera”. In: Frontiers in Microbiology 10.MAY. DOI: 10.3389/fmicb.2019.01169.

Pasulka, A., S. K. Hu, P. D. Countway, et al. (2019). “SSU-rRNA gene sequencing survey of benthic microbial eukaryotes from guaymas basin hydrothermal vent”. In: Journal of Eukaryotic Microbiology 66.4, pp. 637 - 653. DOI: 10.1111/jeu.12711.

Piwosz, K. (2019). “Weekly dynamics of abundance and size structure of specific nanophytoplankton lineages in coastal waters (Baltic Sea)”. In: Limnology and Oceanography 64.5, pp. 2172 - 2186. DOI: 10.1002/lno.11177.

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Wood, S. A., X. Pochon, O. Laroche, et al. (2019). “A comparison of droplet digital polymerase chain reaction (PCR), quantitative PCR and metabarcoding for species-specific detection in environmental DNA”. In: Molecular Ecology Resources 19.6, pp. 1407 - 1419. DOI: 10.1111/1755-0998.13055.

Wu, W., C. Guo, P. Pitta, et al. (2019). “Response of active picoeukaryotes to the deposition of Saharan dust and European aerosols in the eastern Mediterranean Sea”. In: Aquatic Microbial Ecology 82.1, pp. 31 - 42. DOI: 10.3354/ame01881.

Wu, W. and B. Huang (2019). “Protist diversity and community assembly in surface sediments of the South China Sea”. In: MicrobiologyOpen 8.10. DOI: 10.1002/mbo3.891.

Yu, Z. and N. Chen (2019). “Emerging trends in red tide and major research progresses; [国内外赤潮的发展趋势与研究热点]”. In: Oceanologia et Limnologia Sinica 50.3, pp. 474 - 486. DOI: 10.11693/hyhz20190200041.

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2018

Ali, S. R. A., M. N. M. Isa, S. Safari, et al. (2018). “Eukaryotic biodiversity in mixed peat ecosystems in Sarawak, Malaysia”. In: Journal of Oil Palm Research 30.3, pp. 429 - 450. DOI: 10.21894/jopr.2018.0023.

Ammon, U. v., S. A. Wood, O. Laroche, et al. (2018). “Combining morpho-taxonomy and metabarcoding enhances the detection of non-indigenous marine pests in biofouling communities”. In: Scientific Reports 8.1. DOI: 10.1038/s41598-018-34541-1.

Arroyo, A. S., D. López-Escardó, E. Kim, et al. (2018). “Novel diversity of deeply branching holomycota and unicellular holozoans revealed by metabarcoding in Middle Paraná River, Argentina”. In: Frontiers in Ecology and Evolution 6.JUL. DOI: 10.3389/fevo.2018.00099.

Bahram, M., F. Hildebrand, S. K. Forslund, et al. (2018). “Structure and function of the global topsoil microbiome”. In: Nature 560.7717, pp. 233 - 237. DOI: 10.1038/s41586-018-0386-6.

Balzano, S., J. Lattaud, L. Villanueva, et al. (2018). “A quest for the biological sources of long chain alkyl diols in the western tropical North Atlantic Ocean”. In: Biogeosciences (Online) 15.19, pp. 5951 - 5968. DOI: 10.5194/bg-15-5951-2018.

Bass, D., L. Czech, B. A. P. Williams, et al. (2018). “Clarifying the relationships between microsporidia and cryptomycota”. In: Journal of Eukaryotic Microbiology 65.6, pp. 773 - 782. DOI: 10.1111/jeu.12519.

Bensaoud, C., M. Y. Nishiyama, C. Ben Hamda, et al. (2018). “De novo assembly and annotation of Hyalomma dromedarii tick (Acari: Ixodidae) sialotranscriptome with regard to gender differences in gene expression”. In: Parasites and Vectors 11.1. DOI: 10.1186/s13071-018-2874-9.

Berdjeb, L., A. Parada, D. M. Needham, et al. (2018). “Short-term dynamics and interactions of marine protist communities during the spring-summer transition”. In: ISME Journal 12.8, pp. 1907 - 1917. DOI: 10.1038/s41396-018-0097-x.

Boast, A. P., L. S. Weyrich, J. R. Wood, et al. (2018). “Coprolites reveal ecological interactions lost with the extinction of New Zealand birds”. In: Proceedings of the National Academy of Sciences of the United States of America 115.7, pp. 1546 - 1551. DOI: 10.1073/pnas.1712337115.

Boaventura, C., F. Coelho, P. Martins, et al. (2018). “Micro-eukaryotic plankton diversity in an intensive aquaculture system for production of Scophthalmus maximus and Solea senegalensis”. In: Aquaculture (Amsterdam, Netherlands) 490, pp. 321 - 328. DOI: 10.1016/j.aquaculture.2018.02.033.

Bock, C., M. Salcher, M. Jensen, et al. (2018). “Synchrony of eukaryotic and prokaryotic planktonic communities in three seasonally sampled Austrian lakes”. In: Frontiers in Microbiology 9.JUN. DOI: 10.3389/fmicb.2018.01290.

Boscaro, V., L. F. Santoferrara, Q. Zhang, et al. (2018). “EukRef-Ciliophora: a manually curated, phylogeny-based database of small subunit rRNA gene sequences of ciliates”. In: Environmental Microbiology 20.6, pp. 2218 - 2230. DOI: 10.1111/1462-2920.14264.

Briand, J., X. Pochon, S. A. Wood, et al. (2018). “Metabarcoding and metabolomics offer complementarity in deciphering marine eukaryotic biofouling community shifts”. In: Biofouling 34.6, pp. 657 - 672. DOI: 10.1080/08927014.2018.1480757.

Brown, M. V., J. Van De Kamp, M. Ostrowski, et al. (2018). “Data descriptor: Systematic, continental scale temporal monitoring of marine pelagic microbiota by the australian marine microbial biodiversity initiative”. In: Scientific Data 5. DOI: 10.1038/sdata.2018.130.

Cai, J., C. Bai, X. Tang, et al. (2018). “Characterization of bacterial and microbial eukaryotic communities associated with an ephemeral hypoxia event in Taihu Lake, a shallow eutrophic Chinese lake”. In: Environmental Science and Pollution Research 25.31, pp. 31543 - 31557. DOI: 10.1007/s11356-018-2987-x.

Celussi, M., G. M. Quero, L. Zoccarato, et al. (2018). “Planktonic prokaryote and protist communities in a submarine canyon system in the Ligurian Sea (NW Mediterranean)”. In: Progress in Oceanography 168, pp. 210 - 221. DOI: 10.1016/j.pocean.2018.10.002.

Clark, D. R., R. M. W. Ferguson, D. N. Harris, et al. (2018). “Streams of data from drops of water: 21st century molecular microbial ecology”. In: Wiley Interdisciplinary Reviews: Water 5.4. DOI: 10.1002/WAT2.1280.

Clerissi, C., S. Brunet, J. Vidal-Dupiol, et al. (2018). “Protists within corals: The hidden diversity”. In: Frontiers in Microbiology 9.AUG. DOI: 10.3389/fmicb.2018.02043.

Decelle, J., Q. Carradec, X. Pochon, et al. (2018). “Worldwide occurrence and activity of the reef-building coral symbiont symbiodinium in the open ocean”. In: Current Biology 28.22, pp. 3625 - 3633.e3. DOI: 10.1016/j.cub.2018.09.024.

Douglas, G. M., A. M. Comeau, and M. G. I. Langille (2018). “Processing a 16S rRNA sequencing dataset with the microbiome helper workflow”. In: Methods in Molecular Biology 1849, pp. 131 - 141. DOI: 10.1007/978-1-4939-8728-3_9.

Enberg, S., M. Majaneva, R. Autio, et al. (2018). “Phases of microalgal succession in sea ice and the water column in the baltic sea from autumn to spring”. In: Marine Ecology Progress Series 599, pp. 19 - 34. DOI: 10.3354/meps12645.

Engesmo, A., D. Strand, S. Gran-Stadniczeñko, et al. (2018). “Development of a qPCR assay to detect and quantify ichthyotoxic flagellates along the Norwegian coast, and the first Norwegian record of Fibrocapsa japonica (Raphidophyceae)”. In: Harmful Algae 75, pp. 105 - 117. DOI: 10.1016/j.hal.2018.04.007.

Fiore-Donno, A. M., C. Rixen, M. Rippin, et al. (2018). “New barcoded primers for efficient retrieval of cercozoan sequences in high-throughput environmental diversity surveys, with emphasis on worldwide biological soil crusts”. In: Molecular Ecology Resources 18.2, pp. 229 - 239. DOI: 10.1111/1755-0998.12729.

Flegontova, O., P. Flegontov, S. Malviya, et al. (2018). “Neobodonids are dominant kinetoplastids in the global ocean”. In: Environmental Microbiology 20.2, pp. 878 - 889. DOI: 10.1111/1462-2920.14034.

Gaonkar, C. C., R. Piredda, C. Minucci, et al. (2018). “Annotated 18S and 28S rDNA reference sequences of taxa in the planktonic diatom family Chaetocerotaceae”. In: PLoS ONE 13.12. DOI: 10.1371/journal.pone.0208929.

Garvetto, A., E. Nézan, Y. Badis, et al. (2018). “Novel widespread marine oomycetes parasitising diatoms, including the toxic genus pseudo-nitzschia: Genetic, morphological, and ecological characterisation”. In: Frontiers in Microbiology 9. DOI: 10.3389/fmicb.2018.02918.

Gebert, M. J., M. Delgado-Baquerizo, A. M. Oliverio, et al. (2018). “Ecological analyses of mycobacteria in showerhead biofilms and their relevance to human health”. In: mBio 9.5, pp. 1 - 15. DOI: 10.1128/mbio.01614-18.

Geisen, S., E. A. Mitchell, S. Adl, et al. (2018). “Soil protists: A fertile frontier in soil biology research”. In: FEMS Microbiology Reviews 42.3, pp. 293 - 323. DOI: 10.1093/femsre/fuy006.

Geisen, S., L. B. Snoek, F. C. ten Hooven, et al. (2018). “Integrating quantitative morphological and qualitative molecular methods to analyse soil nematode community responses to plant range expansion”. In: Methods in Ecology and Evolution 9.6, pp. 1366 - 1378. DOI: 10.1111/2041-210X.12999.

Guo, S., W. Xiong, H. Xu, et al. (2018). “Continuous application of different fertilizers induces distinct bulk and rhizosphere soil protist communities”. In: European Journal of Soil Biology 88, pp. 8 - 14. DOI: 10.1016/j.ejsobi.2018.05.007.

Hernández-Ruiz, M., E. Barber-Lluch, A. Prieto, et al. (2018). “Seasonal succession of small planktonic eukaryotes inhabiting surface waters of a coastal upwelling system”. In: Environmental Microbiology 20.8, pp. 2955 - 2973. DOI: 10.1111/1462-2920.14313.

Hervé, V., B. Leroy, A. Da Silva Pires, et al. (2018). “Aquatic urban ecology at the scale of a capital: Community structure and interactions in street gutters”. In: ISME Journal 12.1, pp. 253 - 266. DOI: 10.1038/ismej.2017.166.

Hu, S. K., P. E. Connell, L. Y. Mesrop, et al. (2018). “A hard day’s night: Diel shifts in microbial eukaryotic activity in the north pacific subtropical gyre”. In: Frontiers in Marine Science 5.OCT. DOI: 10.3389/fmars.2018.00351.

Hunsucker, K. Z., G. J. Vora, J. T. Hunsucker, et al. (2018). “Biofilm community structure and the associated drag penalties of a groomed fouling release ship hull coating”. In: Biofouling 34.2, pp. 162 - 172. DOI: 10.1080/08927014.2017.1417395.

Jing, H., Y. Zhang, Y. Li, et al. (2018). “Spatial variability of picoeukaryotic communities in the mariana trench”. In: Scientific Reports 8.1. DOI: 10.1038/s41598-018-33790-4.

Kamp, A., C. Petro, H. Røy, et al. (2018). “Intracellular nitrate in sediments of an oxygen-deficient marine basin is linked to pelagic diatoms”. In: FEMS Microbiology Ecology 94.8. DOI: 10.1093/FEMSEC/FIY122.

Kisand, V., L. Talas, A. Kisand, et al. (2018). “From microbial eukaryotes to metazoan vertebrates: Wide spectrum paleo-diversity in sedimentary ancient DNA over the last 14,500 years”. In: Geobiology 16.6, pp. 628 - 639. DOI: 10.1111/gbi.12307.

Kuwata, A., K. Yamada, M. Ichinomiya, et al. (2018). “Bolidophyceae, a sister picoplanktonic group of diatoms - A review”. In: Frontiers in Marine Science 5.OCT. DOI: 10.3389/fmars.2018.00370.

Laroche, O., S. A. Wood, L. A. Tremblay, et al. (2018). “A cross-taxa study using environmental DNA/RNA metabarcoding to measure biological impacts of offshore oil and gas drilling and production operations”. In: Marine Pollution Bulletin 127, pp. 97 - 107. DOI: 10.1016/j.marpolbul.2017.11.042.

Leblanc, K., B. Quéguiner, F. Diaz, et al. (2018). “Nanoplanktonic diatoms are globally overlooked but play a role in spring blooms and carbon export”. In: Nature Communications 9.1. DOI: 10.1038/s41467-018-03376-9.

Leff, J. W., R. D. Bardgett, A. Wilkinson, et al. (2018). “Predicting the structure of soil communities from plant community taxonomy, phylogeny, and traits”. In: ISME Journal 12.7, pp. 1794 - 1805. DOI: 10.1038/s41396-018-0089-x.

Lentendu, G., F. Mahé, D. Bass, et al. (2018). “Consistent patterns of high alpha and low beta diversity in tropical parasitic and free-living protists”. In: Molecular Ecology 27.13, pp. 2846 - 2857. DOI: 10.1111/mec.14731.

Leray, M., S. Ho, I. Lin, et al. (2018). “MIDORI server: a webserver for taxonomic assignment of unknown metazoan mitochondrial-encoded sequences using a curated database”. In: Bioinformatics (Oxford, England) 34.21, pp. 3753 - 3754. DOI: 10.1093/bioinformatics/bty454.

Lewitus, E., L. Bittner, S. Malviya, et al. (2018). “Clade-specific diversification dynamics of marine diatoms since the Jurassic”. In: Nature Ecology and Evolution 2.11, pp. 1715 - 1723. DOI: 10.1038/s41559-018-0691-3.

Li, F., Y. Peng, W. Fang, et al. (2018). “Application of environmental DNA metabarcoding for predicting anthropogenic pollution in rivers”. In: Environmental Science and Technology 52.20, pp. 11708 - 11719. DOI: 10.1021/acs.est.8b03869.

Li, R., N. Jiao, A. Warren, et al. (2018). “Changes in community structure of active protistan assemblages from the lower Pearl River to coastal Waters of the South China Sea”. In: European Journal of Protistology 63, pp. 72 - 82. DOI: 10.1016/j.ejop.2018.01.004.

López-Escardó, D., J. Paps, C. De Vargas, et al. (2018). “Metabarcoding analysis on European coastal samples reveals new molecular metazoan diversity”. In: Scientific Reports 8.1. DOI: 10.1038/s41598-018-27509-8.

Morard, R., M. Garet-Delmas, F. Mahé, et al. (2018). “Surface ocean metabarcoding confirms limited diversity in planktonic foraminifera but reveals unknown hyper-abundant lineages”. In: Scientific Reports 8.1. DOI: 10.1038/s41598-018-20833-z.

Mordret, S., R. Piredda, D. Vaulot, et al. (2018). “dinoref: A curated dinoflagellate (Dinophyceae) reference database for the 18S rRNA gene”. In: Molecular Ecology Resources 18.5, pp. 974 - 987. DOI: 10.1111/1755-0998.12781.

Moreno-Pino, M., B. Krock, R. De la Iglesia, et al. (2018). “Next Generation Sequencing and mass spectrometry reveal high taxonomic diversity and complex phytoplankton-phycotoxins patterns in Southeastern Pacific fjords”. In: Toxicon : official journal of the International Society on Toxinology 151, pp. 5 - 14. DOI: 10.1016/j.toxicon.2018.06.078.

Mucko, M., S. Bosak, R. Casotti, et al. (2018). “Winter picoplankton diversity in an oligotrophic marginal sea”. In: Marine Genomics 42, pp. 14 - 24. DOI: 10.1016/j.margen.2018.09.002.

Oliverio, A. M., J. F. Power, A. Washburne, et al. (2018). “The ecology and diversity of microbial eukaryotes in geothermal springs”. In: ISME Journal 12.8, pp. 1918 - 1928. DOI: 10.1038/s41396-018-0104-2.

Pearman, J. K., F. Afandi, P. Hong, et al. (2018). “Plankton community assessment in anthropogenic-impacted oligotrophic coastal regions”. In: Environmental Science and Pollution Research 25.31, pp. 31017 - 31030. DOI: 10.1007/s11356-018-3072-1.

Pearman, J., M. Leray, R. Villalobos, et al. (2018). “Cross-shelf investigation of coral reef cryptic benthic organisms reveals diversity patterns of the hidden majority”. In: Scientific Reports 8.1. DOI: 10.1038/s41598-018-26332-5.

Piwosz, K., J. Całkiewicz, M. Gołębiewski, et al. (2018). “Diversity and community composition of pico- and nanoplanktonic protists in the Vistula River estuary (Gulf of Gdańsk, Baltic Sea)”. In: Estuarine, Coastal and Shelf Science 207, pp. 242 - 249. DOI: 10.1016/j.ecss.2018.04.013.

Rachik, S., U. Christaki, L. L. Li, et al. (2018). “Diversity and potential activity patterns of planktonic eukaryotic microbes in a mesoeutrophic coastal area (eastern English Channel)”. In: PLoS ONE 13.5. DOI: 10.1371/journal.pone.0196987.

Ren, K., Y. Xue, R. Rønn, et al. (2018). “Dynamics and determinants of amoeba community, occurrence and abundance in subtropical reservoirs and rivers”. In: Water Research 146, pp. 177 - 186. DOI: 10.1016/j.watres.2018.09.011.

Ser-Giacomi, E., L. Zinger, S. Malviya, et al. (2018). “Ubiquitous abundance distribution of non-dominant plankton across the global ocean”. In: Nature Ecology and Evolution 2.8, pp. 1243 - 1249. DOI: 10.1038/s41559-018-0587-2.

Stefanidou, N., S. Genitsaris, J. Lopez-Bautista, et al. (2018). “Unicellular eukaryotic community response to temperature and salinity variation in mesocosm experiments”. In: Frontiers in Microbiology 9.OCT. DOI: 10.3389/fmicb.2018.02444.

Stern, R., A. Kraberg, E. Bresnan, et al. (2018). “Molecular analyses of protists in long-term observation programmes - Current status and future perspectives”. In: Journal of Plankton Research 40.5, pp. 519 - 536. DOI: 10.1093/plankt/fby035.

Stoeck, T., R. Kochems, D. Forster, et al. (2018). “Metabarcoding of benthic ciliate communities shows high potential for environmental monitoring in salmon aquaculture”. In: Ecological Indicators 85, pp. 153 - 164. DOI: 10.1016/j.ecolind.2017.10.041.

Stoeck, T., H. Pan, V. Dully, et al. (2018). “Towards an eDNA metabarcode-based performance indicator for full-scale municipal wastewater treatment plants”. In: Water Research 144, pp. 322 - 331. DOI: 10.1016/j.watres.2018.07.051.

Szelecz, I., S. Lösch, C. V. W. Seppey, et al. (2018). “Comparative analysis of bones, mites, soil chemistry, nematodes and soil micro-eukaryotes from a suspected homicide to estimate the post-mortem interval”. In: Scientific Reports 8.1. DOI: 10.1038/s41598-017-18179-z.

Taberlet, P., A. Bonin, L. Zinger, et al. (2018). Environmental DNA: For biodiversity research and monitoring. DOI: 10.1093/oso/9780198767220.001.0001.

Tan, S. and H. Liu (2018). “Unravel the hidden protistan diversity: application of blocking primers to suppress PCR amplification of metazoan DNA”. In: Applied Microbiology and Biotechnology 102.1, pp. 389 - 401. DOI: 10.1007/s00253-017-8565-1.

Tragin, M. and D. Vaulot (2018). “Green microalgae in marine coastal waters: The Ocean Sampling Day (OSD) dataset”. In: Scientific Reports 8.1. DOI: 10.1038/s41598-018-32338-w.

Tragin, M., A. Zingone, and D. Vaulot (2018). “Comparison of coastal phytoplankton composition estimated from the V4 and V9 regions of the 18S rRNA gene with a focus on photosynthetic groups and especially Chlorophyta”. In: Environmental Microbiology 20.2, pp. 506 - 520. DOI: 10.1111/1462-2920.13952.

Vader, A., H. D. Laughinghouse, C. Griffiths, et al. (2018). “Proton-pumping rhodopsins are abundantly expressed by microbial eukaryotes in a high-Arctic fjord”. In: Environmental Microbiology 20.2, pp. 890 - 902. DOI: 10.1111/1462-2920.14035.

Varkey, D., S. Mazard, T. C. Jeffries, et al. (2018). “Stormwater influences phytoplankton assemblages within the diverse, but impacted Sydney Harbour estuary”. In: PLoS ONE 13.12. DOI: 10.1371/journal.pone.0209857.

Venter, P. C., F. Nitsche, and H. Arndt (2018). “The hidden diversity of flagellated protists in soil”. In: Protist 169.3, pp. 432 - 449. DOI: 10.1016/j.protis.2018.04.007.

Venter, P. C., F. Nitsche, A. Scherwass, et al. (2018). “Discrepancies between molecular and morphological databases of soil ciliates studied for temperate grasslands of central europe”. In: Protist 169.4, pp. 521 - 538. DOI: 10.1016/j.protis.2018.04.001.

Wang, Y., T. Shi, G. Huang, et al. (2018). “Molecular detection of eukaryotic diets and gut mycobiomes in two marine sediment-dwelling worms, sipunculus nudus and urechis unicinctus”. In: Microbes and Environments 33.3, pp. 290 - 300. DOI: 10.1264/jsme2.ME18065.

Wangensteen, O. S., E. Cebrian, and C. Palacín (2018). “Under the canopy: Community-wide effects of invasive algae in Marine Protected Areas revealed by metabarcoding”. In: Marine Pollution Bulletin 127, pp. 54 - 66. DOI: 10.1016/j.marpolbul.2017.11.033.

Ward, G. M., S. Neuhauser, R. Groben, et al. (2018). “Environmental sequencing fills the gap between parasitic haplosporidians and free-living giant amoebae”. In: Journal of Eukaryotic Microbiology 65.5, pp. 574 - 586. DOI: 10.1111/jeu.12501.

Wu, W. and H. Liu (2018). “Disentangling protist communities identified from DNA and RNA surveys in the pearl river–south china sea continuum during the wet and dry seasons”. In: Molecular Ecology 27.22, pp. 4627 - 4640. DOI: 10.1111/mec.14867.

Wu, W., H. Lu, A. Sastri, et al. (2018). “Contrasting the relative importance of species sorting and dispersal limitation in shaping marine bacterial versus protist communities”. In: ISME Journal 12.2, pp. 485 - 494. DOI: 10.1038/ismej.2017.183.

Wylezich, C., D. P. Herlemann, and K. Jürgens (2018). “Improved 18S rDNA amplification protocol for assessing protist diversity in oxygen-deficient marine systems”. In: Aquatic Microbial Ecology 81.1, pp. 83 - 94. DOI: 10.3354/ame01864.

Xie, Y., T. Floehr, X. Zhang, et al. (2018). “In situ microbiota distinguished primary anthropogenic stressor in freshwater sediments”. In: Environmental Pollution 239, pp. 189 - 197. DOI: 10.1016/j.envpol.2018.03.099.

Xie, Y., X. Zhang, J. Yang, et al. (2018). “eDNA-based bioassessment of coastal sediments impacted by an oil spill”. In: Environmental Pollution 238, pp. 739 - 748. DOI: 10.1016/j.envpol.2018.02.081.

Zaiko, A., X. Pochon, E. Garcia-Vazquez, et al. (2018). “Advantages and limitations of environmental DNA/RNA tools for marine biosecurity: Management and surveillance of non-indigenous species”. In: Frontiers in Marine Science 5.SEP. DOI: 10.3389/fmars.2018.00322.

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Zhu, P., Y. Wang, T. Shi, et al. (2018). “Genetic diversity of benthic microbial eukaryotes in response to spatial heterogeneity of sediment geochemistry in a mangrove ecosystem”. In: Estuaries and Coasts 41.3, pp. 751 - 764. DOI: 10.1007/s12237-017-0317-z.

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2017

Alves-De-Souza, C., T. S. Benevides, J. B. O. Santos, et al. (2017). “Does environmental heterogeneity explain temporal β diversity of small eukaryotic phytoplankton? Example from a tropical eutrophic coastal lagoon”. In: Journal of Plankton Research 39.4, pp. 698 - 714. DOI: 10.1093/plankt/fbx026.

Berney, C., A. Ciuprina, S. Bender, et al. (2017). “UniEuk: Time to speak a common language in protistology!” In: Journal of Eukaryotic Microbiology 64.3, pp. 407 - 411. DOI: 10.1111/jeu.12414.

Biard, T., E. Bigeard, S. Audic, et al. (2017). “Biogeography and diversity of Collodaria (Radiolaria) in the global ocean”. In: ISME Journal 11.6, pp. 1331 - 1344. DOI: 10.1038/ismej.2017.12.

Christaki, U., S. Genitsaris, S. Monchy, et al. (2017). “Parasitic eukaryotes in a meso-eutrophic coastal system with marked Phaeocystis globosa blooms”. In: Frontiers in Marine Science 4.DEC. DOI: 10.3389/fmars.2017.00416.

Deiner, K., H. M. Bik, E. Mächler, et al. (2017). “Environmental DNA metabarcoding: Transforming how we survey animal and plant communities”. In: Molecular Ecology 26.21, pp. 5872 - 5895. DOI: 10.1111/mec.14350.

Domaizon, I., A. Winegardner, E. Capo, et al. (2017). “DNA-based methods in paleolimnology: new opportunities for investigating long-term dynamics of lacustrine biodiversity”. In: Journal of Paleolimnology 58.1. DOI: 10.1007/s10933-017-9958-y.

Dunthorn, M., H. Kauserud, D. Bass, et al. (2017). “Yeasts dominate soil fungal communities in three lowland Neotropical rainforests”. In: Environmental Microbiology Reports 9.5, pp. 668 - 675. DOI: 10.1111/1758-2229.12575.

Filker, S., D. Forster, L. Weinisch, et al. (2017). “Transition boundaries for protistan species turnover in hypersaline waters of different biogeographic regions”. In: Environmental Microbiology 19.8, pp. 3186 - 3200. DOI: 10.1111/1462-2920.13805.

Fletcher, L. M., A. Zaiko, J. Atalah, et al. (2017). “Bilge water as a vector for the spread of marine pests: a morphological, metabarcoding and experimental assessment”. In: Biological Invasions 19.10, pp. 2851 - 2867. DOI: 10.1007/s10530-017-1489-y.

Foster, Z. S. L., T. J. Sharpton, and N. J. Grünwald (2017). “Metacoder: An R package for visualization and manipulation of community taxonomic diversity data”. In: PLoS Computational Biology 13.2. DOI: 10.1371/journal.pcbi.1005404.

Frank, N., T. Helge Abuldhauge, and J. R. Daniel (2017). “Bridging the gap between morphological species and molecular barcodes – Exemplified by loricate choanoflagellates”. In: European Journal of Protistology 57, pp. 26 - 37. DOI: 10.1016/j.ejop.2016.10.006.

Gleason, F. H., B. Scholz, T. G. Jephcott, et al. (2017). Key ecological roles for zoosporic true fungi in aquatic habitats. DOI: 10.1128/9781555819583.ch18.

Gołębiewski, M., J. Całkiewicz, S. Creer, et al. (2017). “Tideless estuaries in brackish seas as possible freshwater-marine transition zones for bacteria: the case study of the Vistula river estuary”. In: Environmental Microbiology Reports 9.2, pp. 129 - 143. DOI: 10.1111/1758-2229.12509.

Gran-Stadniczeñko, S., L. Šupraha, E. D. Egge, et al. (2017). “Haptophyte diversity and vertical distribution explored by 18S and 28S ribosomal RNA gene metabarcoding and scanning electron microscopy”. In: Journal of Eukaryotic Microbiology 64.4, pp. 514 - 532. DOI: 10.1111/jeu.12388.

Groendahl, S., M. Kahlert, and P. Fink (2017). “The best of both worlds: A combined approach for analyzing microalgal diversity via metabarcoding and morphology-based methods”. In: PLoS ONE 12.2. DOI: 10.1371/journal.pone.0172808.

Heinz, K. G. H., P. R. S. Zanoni, R. R. Oliveira, et al. (2017). “Recycled paper sludge microbial community as a potential source of cellulase and xylanase enzymes”. In: Waste and Biomass Valorization 8.6, pp. 1907 - 1917. DOI: 10.1007/s12649-016-9792-x.

Hugerth, L. W. and A. F. Andersson (2017). “Analysing microbial community composition through amplicon sequencing: From sampling to hypothesis testing”. In: Frontiers in Microbiology 8.SEP. DOI: 10.3389/fmicb.2017.01561.

Jacob, F., T. T. Melachio, G. R. Njitchouang, et al. (2017). “Intestinal bacterial communities of trypanosome-infected and uninfected Glossina palpalis palpalis from three human African trypanomiasis foci in Cameroon”. In: Frontiers in Microbiology 8.AUG. DOI: 10.3389/fmicb.2017.01464.

Kataoka, T., H. Yamaguchi, M. Sato, et al. (2017). “Seasonal and geographical distribution of near-surface small photosynthetic eukaryotes in the western north pacific determined by pyrosequencing of 18S rDNA”. In: FEMS Microbiology Ecology 93.2. DOI: 10.1093/femsec/fiw229.

Kaysen, A., A. Heintz-Buschart, E. E. Muller, et al. (2017). “Integrated meta-omic analyses of the gastrointestinal tract microbiome in patients undergoing allogeneic hematopoietic stem cell transplantation”. In: Translational Research 186, pp. 79 - 94.e1. DOI: 10.1016/j.trsl.2017.06.008.

Khomich, M., H. Kauserud, R. Logares, et al. (2017). “Planktonic protistan communities in lakes along a large-scale environmental gradient”. In: FEMS Microbiology Ecology 93.4. DOI: 10.1093/femsec/fiw231.

Laroche, O., S. A. Wood, L. A. Tremblay, et al. (2017). “Metabarcoding monitoring analysis: The pros and cons of using co-extracted environmental DNA and RNA data to assess offshore oil production impacts on benthic communities”. In: PeerJ 2017.5. DOI: 10.7717/peerj.3347.

Lee, K. H., L. S. Ab Samad, P. M. Lwin, et al. (2017). “On the rocks: Microbiological quality and microbial diversity of packaged ice in southern California”. In: Journal of Food Protection 80.6, pp. 1041 - 1049. DOI: 10.4315/0362-028X.JFP-16-295.

Leray, M. and N. Knowlton (2017). “Random sampling causes the low reproducibility of rare eukaryotic OTUs in Illumina COI metabarcoding”. In: PeerJ 2017.3. DOI: 10.7717/peerj.3006.

Machida, R. J., M. Leray, S. Ho, et al. (2017). “Data Descriptor: Metazoan mitochondrial gene sequence reference datasets for taxonomic assignment of environmental samples”. In: Scientific Data 4. DOI: 10.1038/sdata.2017.27.

Mahé, F., C. De Vargas, D. Bass, et al. (2017). “Parasites dominate hyperdiverse soil protist communities in Neotropical rainforests”. In: Nature Ecology and Evolution 1.4. DOI: 10.1038/s41559-017-0091.

Marie, D., F. Le Gall, R. Edern, et al. (2017). “Improvement of phytoplankton culture isolation using single cell sorting by flow cytometry”. In: Journal of Phycology 53.2, pp. 271 - 282. DOI: 10.1111/jpy.12495.

Meshram, A. R., A. Vader, S. Kristiansen, et al. (2017). “Microbial eukaryotes in an arctic under-ice spring bloom north of Svalbard”. In: Frontiers in Microbiology 8.JUN. DOI: 10.3389/fmicb.2017.01099.

Morard, R., F. Lejzerowicz, K. F. Darling, et al. (2017). “Planktonic foraminifera-derived environmental DNA extracted from abyssal sediments preserves patterns of plankton macroecology”. In: Biogeosciences (Online) 14.11, pp. 2741 - 2754. DOI: 10.5194/bg-14-2741-2017.

Mukherjee, I., Y. Hodoki, and S. Nakano (2017). “Seasonal dynamics of heterotrophic and plastidic protists in the water column of Lake Biwa, Japan”. In: Aquatic Microbial Ecology 80.2, pp. 123 - 137. DOI: 10.3354/ame01843.

Pan, J., J. del Campo, and P. J. Keeling (2017). “Reference tree and environmental sequence diversity of labyrinthulomycetes”. In: Journal of Eukaryotic Microbiology 64.1, pp. 88 - 96. DOI: 10.1111/jeu.12342.

Pearman, J. K., J. Ellis, X. Irigoien, et al. (2017). “Microbial planktonic communities in the Red Sea: high levels of spatial and temporal variability shaped by nutrient availability and turbulence”. In: Scientific Reports 7.1. DOI: 10.1038/s41598-017-06928-z.

Penna, A., S. Casabianca, A. F. Guerra, et al. (2017). “Analysis of phytoplankton assemblage structure in the Mediterranean Sea based on high-throughput sequencing of partial 18S rRNA sequences”. In: Marine Genomics 36, pp. 49 - 55. DOI: 10.1016/j.margen.2017.06.001.

Piredda, R., D. Sarno, C. B. Lange, et al. (2017). “Diatom resting stages in surface sediments: a pilot study comparing next generation sequencing and serial dilution cultures”. In: Cryptogamie, Algologie 38.1, pp. 31 - 46. DOI: 10.7872/crya/v38.iss1.2017.31.

Piredda, R., M. Tomasino, A. D’Erchia, et al. (2017). “Diversity and temporal patterns of planktonic protist assemblages at a Mediterranean Long Term Ecological Research site”. In: FEMS Microbiology Ecology 93.1. DOI: 10.1093/femsec/fiw200.

Pochon, X., A. Zaiko, L. M. Fletcher, et al. (2017). “Wanted dead or alive? Using metabarcoding of environmental DNA and RNA to distinguish living assemblages for biosecurity applications”. In: PLoS ONE 12.11. DOI: 10.1371/journal.pone.0187636.

Reich, M. and A. Labes (2017). “How to boost marine fungal research: A first step towards a multidisciplinary approach by combining molecular fungal ecology and natural products chemistry”. In: Marine Genomics 36, pp. 57 - 75. DOI: 10.1016/j.margen.2017.09.007.

Saghaï, A., A. Gutiérrez-Preciado, P. Deschamps, et al. (2017). “Unveiling microbial interactions in stratified mat communities from a warm saline shallow pond”. In: Environmental Microbiology 19.6, pp. 2405 - 2421. DOI: 10.1111/1462-2920.13754.

Salvitti, L., S. A. Wood, R. Fairweather, et al. (2017). “In situ accumulation of tetrodotoxin in non-toxic Pleurobranchaea maculata (Opisthobranchia)”. In: Aquatic Sciences 79.2, pp. 335 - 344. DOI: 10.1007/s00027-016-0500-5.

Santos, S. S., I. Nunes, T. K. Nielsen, et al. (2017). “Soil DNA extraction procedure influences protist 18S rRNA gene community profiling outcome”. In: Protist 168.3, pp. 283 - 293. DOI: 10.1016/j.protis.2017.03.002.

Schnittler, M., O. N. Shchepin, N. H. A. Dagamac, et al. (2017). “Barcoding myxomycetes with molecular markers: Challenges and opportunities”. In: Nova Hedwigia 104.1-3, pp. 323 - 341. DOI: 10.1127/nova_hedwigia/2017/0397.

Seppey, C. V., D. Singer, K. Dumack, et al. (2017). “Distribution patterns of soil microbial eukaryotes suggests widespread algivory by phagotrophic protists as an alternative pathway for nutrient cycling”. In: Soil Biology and Biochemistry 112, pp. 68 - 76. DOI: 10.1016/j.soilbio.2017.05.002.

Simon, N., E. Foulon, D. Grulois, et al. (2017). “Revision of the genus micromonas manton et parke (chlorophyta, mamiellophyceae), of the type species M. pusilla (butcher) manton & parke and of the species M. commoda van baren, bachy and worden and description of two new species based on the genetic and phenotypic characterization of cultured isolates”. In: Protist 168.5, pp. 612 - 635. DOI: 10.1016/j.protis.2017.09.002.

Smith, K. F., G. S. Kohli, S. A. Murray, et al. (2017). “Assessment of the metabarcoding approach for community analysis of benthic-epiphytic dinoflagellates using mock communities”. In: New Zealand Journal of Marine and Freshwater Research 51.4, pp. 555 - 576. DOI: 10.1080/00288330.2017.1298632.

Sun, P., L. Huang, D. Xu, et al. (2017). “Marked seasonality and high spatial variation in estuarine ciliates are driven by exchanges between the ‘abundant’ and ‘intermediate’ biospheres”. In: Scientific Reports 7.1. DOI: 10.1038/s41598-017-10308-y.

Tirichine, L., A. Rastogi, and C. Bowler (2017). “Recent progress in diatom genomics and epigenomics”. In: Current Opinion in Plant Biology 36, pp. 46 - 55. DOI: 10.1016/j.pbi.2017.02.001.

Torruella, G., D. Moreira, and P. López-García (2017). “Phylogenetic and ecological diversity of apusomonads, a lineage of deep-branching eukaryotes”. In: Environmental Microbiology Reports 9.2, pp. 113 - 119. DOI: 10.1111/1758-2229.12507.

Venter, P. C., F. Nitsche, A. Domonell, et al. (2017). “The protistan microbiome of grassland soil: Diversity in the mesoscale”. In: Protist 168.5, pp. 546 - 564. DOI: 10.1016/j.protis.2017.03.005.

Wampach, L., A. Heintz-Buschart, A. Hogan, et al. (2017). “Colonization and succession within the human gut microbiome by archaea, bacteria, and microeukaryotes during the first year of life”. In: Frontiers in Microbiology 8.MAY. DOI: 10.3389/fmicb.2017.00738.

Wang, Y., X. Guo, P. Zheng, et al. (2017). “Distinct seasonality of chytrid-dominated benthic fungal communities in the neritic oceans (Bohai Sea and North Yellow Sea)”. In: Fungal Ecology 30, pp. 55 - 66. DOI: 10.1016/j.funeco.2017.08.008.

Weber, F., A. P. Mylnikov, K. Jürgens, et al. (2017). “Culturing heterotrophic protists from the baltic sea: Mostly the “usual suspects” but a few novelties as well”. In: Journal of Eukaryotic Microbiology 64.2, pp. 153 - 163. DOI: 10.1111/jeu.12347.

Wu, W., R. Logares, B. Huang, et al. (2017). “Abundant and rare picoeukaryotic sub-communities present contrasting patterns in the epipelagic waters of marginal seas in the northwestern Pacific Ocean”. In: Environmental Microbiology 19.1, pp. 287 - 300. DOI: 10.1111/1462-2920.13606.

Xie, Y., S. Hong, S. Kim, et al. (2017). “Ecogenomic responses of benthic communities under multiple stressors along the marine and adjacent riverine areas of northern Bohai Sea, China”. In: Chemosphere 172, pp. 166 - 174. DOI: 10.1016/j.chemosphere.2016.12.121.

Xie, Y., J. Wang, J. Yang, et al. (2017). “Environmental DNA metabarcoding reveals primary chemical contaminants in freshwater sediments from different land-use types”. In: Chemosphere 172, pp. 201 - 209. DOI: 10.1016/j.chemosphere.2016.12.117.

Xu, D., N. Jiao, R. Ren, et al. (2017). “Distribution and diversity of microbial eukaryotes in bathypelagic waters of the south china sea”. In: Journal of Eukaryotic Microbiology 64.3, pp. 370 - 382. DOI: 10.1111/jeu.12372.

2016

Aguilar, M., E. Richardson, B. Tan, et al. (2016). “Next-generation sequencing assessment of eukaryotic diversity in oil sands tailings ponds sediments and surface water”. In: Journal of Eukaryotic Microbiology 63.6, pp. 732 - 743. DOI: 10.1111/jeu.12320.

Amato, K. R., J. L. Metcalf, S. J. Song, et al. (2016). “Using the gut microbiota as a novel tool for examining colobine primate GI health”. In: Global Ecology and Conservation 7, pp. 225 - 237. DOI: 10.1016/j.gecco.2016.06.004.

Angelakis, E., M. Yasir, D. Bachar, et al. (2016). “Gut microbiome and dietary patterns in different Saudi populations and monkeys”. In: Scientific Reports 6. DOI: 10.1038/srep32191.

Bass, D. and T. Bell (2016). Protist systematics, ecology and next generation sequencing. DOI: 10.1017/CBO9781139236355.010.

Bass, D., J. D. Silberman, M. W. Brown, et al. (2016). “Coprophilic amoebae and flagellates, including Guttulinopsis, Rosculus and Helkesimastix, characterise a divergent and diverse rhizarian radiation and contribute to a large diversity of faecal-associated protists”. In: Environmental Microbiology 18.5, pp. 1604 - 1619. DOI: 10.1111/1462-2920.13235.

Boyer, F., C. Mercier, A. Bonin, et al. (2016). “obitools: A unix-inspired software package for DNA metabarcoding”. In: Molecular Ecology Resources 16.1, pp. 176 - 182. DOI: 10.1111/1755-0998.12428.

Cleary, A. C. and E. G. Durbin (2016). “Unexpected prevalence of parasite 18S rDNA sequences in winter among Antarctic marine protists”. In: Journal of Plankton Research 38.3, pp. 401 - 417. DOI: 10.1093/plankt/fbw005.

Coelho, F. J. R. C., A. Louvado, P. M. Domingues, et al. (2016). “Integrated analysis of bacterial and microeukaryotic communities from differentially active mud volcanoes in the Gulf of Cadiz”. In: Scientific Reports 6. DOI: 10.1038/srep35272.

Cooper, M. K., D. N. Phalen, S. L. Donahoe, et al. (2016). “The utility of diversity profiling using Illumina 18S rRNA gene amplicon deep sequencing to detect and discriminate Toxoplasma gondii among the cyst-forming coccidia”. In: Veterinary Parasitology 216, pp. 38 - 45. DOI: 10.1016/j.vetpar.2015.12.011.

Cornejo-Castillo, F. M., A. M. Cabello, G. Salazar, et al. (2016). “Cyanobacterial symbionts diverged in the late Cretaceous towards lineage-specific nitrogen fixation factories in single-celled phytoplankton”. In: Nature Communications 7. DOI: 10.1038/ncomms11071.

Dubourg, G., J. Lagier, S. Hüe, et al. (2016). “Gut microbiota associated with HIV infection is significantly enriched in bacteria tolerant to oxygen”. In: BMJ Open Gastroenterology 3.1. DOI: 10.1136/bmjgast-2016-000080.

Ferrera, I., C. R. Giner, A. Reñé, et al. (2016). “Evaluation of alternative high-throughput sequencing methodologies for the monitoring of marine picoplanktonic biodiversity based on rRNA gene amplicons”. In: Frontiers in Marine Science 3.AUG. DOI: 10.3389/fmars.2016.00147.

Forster, D., M. Dunthorn, F. Mahé, et al. (2016). “Benthic protists: The under-charted majority”. In: FEMS Microbiology Ecology 92.8. DOI: 10.1093/femsec/fiw120.

Forster, D., M. Dunthorn, T. Stoeck, et al. (2016). “Comparison of three clustering approaches for detecting novel environmental microbial diversity”. In: PeerJ 2016.2. DOI: 10.7717/peerj.1692.

Genitsaris, S., S. Monchy, E. Breton, et al. (2016). “Small-scale variability of protistan planktonic communities relative to environmental pressures and biotic interactions at two adjacent coastal stations”. In: Marine Ecology Progress Series 548, pp. 61 - 75. DOI: 10.3354/meps11647.

Genitsaris, S., S. Monchy, J. Denonfoux, et al. (2016). “Marine microbial community structure assessed from combined metagenomic analysis and ribosomal amplicon deep-sequencing”. In: Marine Biology Research 12.1, pp. 30 - 42. DOI: 10.1080/17451000.2015.1084425.

Gimmler, A., R. Korn, C. De Vargas, et al. (2016). “The Tara Oceans voyage reveals global diversity and distribution patterns of marine planktonic ciliates”. In: Scientific Reports 6. DOI: 10.1038/srep33555.

Giner, C. R., I. Forn, S. Romac, et al. (2016). “Environmental sequencing provides reasonable estimates of the relative abundance of specific picoeukaryotes”. In: Applied and Environmental Microbiology 82.15, pp. 4757 - 4766. DOI: 10.1128/AEM.00560-16.

Guardiola, M., O. S. Wangensteen, P. Taberlet, et al. (2016). “Spatio-temporal monitoring of deep-sea communities using metabarcoding of sediment DNA and RNA”. In: PeerJ 2016.12. DOI: 10.7717/peerj.2807.

Hu, Y. O., B. Karlson, S. Charvet, et al. (2016). “Diversity of pico- to mesoplankton along the 2000 km salinity gradient of the baltic sea”. In: Frontiers in Microbiology 7.MAY. DOI: 10.3389/fmicb.2016.00679.

Ichinomiya, M., A. L. Dos Santos, P. Gourvil, et al. (2016). “Diversity and oceanic distribution of the Parmales (Bolidophyceae), a picoplanktonic group closely related to diatoms”. In: ISME Journal 10.10, pp. 2419 - 2434. DOI: 10.1038/ismej.2016.38.

Kozlov, A. M., J. Zhang, P. Yilmaz, et al. (2016). “Phylogeny-aware identification and correction of taxonomically mislabeled sequences”. In: Nucleic Acids Research 44.11, pp. 5022 - 5033. DOI: 10.1093/nar/gkw396.

Leray, M. and N. Knowlton (2016). “Censusing marine eukaryotic diversity in the twenty-first century”. In: Philosophical Transactions of the Royal Society B: Biological Sciences 371.1702. DOI: 10.1098/rstb.2015.0331.

Malviya, S., E. Scalco, S. Audic, et al. (2016). “Insights into global diatom distribution and diversity in the world’s ocean”. In: Proceedings of the National Academy of Sciences of the United States of America 113.11, pp. E1516 - E1525. DOI: 10.1073/pnas.1509523113.

Marquardt, M., A. Vader, E. I. Stübner, et al. (2016). “Strong seasonality of marine microbial eukaryotes in a high-Arctic fjord (Isfjorden, in West Spitsbergen, Norway)”. In: Applied and Environmental Microbiology 82.6, pp. 1868 - 1880. DOI: 10.1128/AEM.03208-15.

More, R. P. and H. J. Purohit (2016). “The identification of discriminating patterns from 16S rRNA gene to generate signature for bacillus genus”. In: Journal of Computational Biology 23.8, pp. 651 - 661. DOI: 10.1089/cmb.2016.0002.

Moustaka-Gouni, M., K. A. Kormas, M. Scotti, et al. (2016). “Warming and acidification effects on planktonic heterotrophic pico- and nanoflagellates in a mesocosm experiment”. In: Protist 167.4, pp. 389 - 410. DOI: 10.1016/j.protis.2016.06.004.

Needham, D. M. and J. A. Fuhrman (2016). “Pronounced daily succession of phytoplankton, archaea and bacteria following a spring bloom”. In: Nature Microbiology 1.4. DOI: 10.1038/NMICROBIOL.2016.5.

Nitsche, F. (2016). “A phylogenetic and morphological re-investigation of Diaphanoeca spiralifurca, Didymoeca elongata and Polyoeca dichotoma (Acanthoecida/Choanomonadida) from the Caribbean Sea”. In: European Journal of Protistology 52, pp. 58 - 64. DOI: 10.1016/j.ejop.2015.11.001.

Obbels, D., E. Verleyen, M. Mano, et al. (2016). “Bacterial and eukaryotic biodiversity patterns in terrestrial and aquatic habitats in the sør rondane mountains, dronning maud land, east antarctica”. In: FEMS Microbiology Ecology 92.6, pp. 1 - 13. DOI: 10.1093/femsec/fiw041.

Pawlowski, J., F. Lejzerowicz, L. Apotheloz-Perret-Gentil, et al. (2016). “Protist metabarcoding and environmental biomonitoring: Time for change”. In: European Journal of Protistology 55, pp. 12 - 25. DOI: 10.1016/j.ejop.2016.02.003.

Pearman, J. K., H. Anlauf, X. Irigoien, et al. (2016). “Please mind the gap - Visual census and cryptic biodiversity assessment at central Red Sea coral reefs”. In: Marine Environmental Research 118, pp. 20 - 30. DOI: 10.1016/j.marenvres.2016.04.011.

Pearman, J., S. Kürten, Y. Sarma, et al. (2016). “Biodiversity patterns of plankton assemblages at the extremes of the Red Sea”. In: FEMS Microbiology Ecology 92.3. DOI: 10.1093/femsec/fiw002.

Pernice, M. C., C. R. Giner, R. Logares, et al. (2016). “Large variability of bathypelagic microbial eukaryotic communities across the world’s oceans”. In: ISME Journal 10.4, pp. 945 - 958. DOI: 10.1038/ismej.2015.170.

Ramírez-Sánchez, O., P. Pérez-Rodríguez, L. Delaye, et al. (2016). “Plant proteins are smaller because they are encoded by fewer exons than animal proteins”. In: Genomics, Proteomics and Bioinformatics 14.6, pp. 357 - 370. DOI: 10.1016/j.gpb.2016.06.003.

Rimet, F., P. Chaumeil, F. Keck, et al. (2016). “R-Syst::diatom: An open-access and curated barcode database for diatoms and freshwater monitoring”. In: Database-the Magazine of Electronic Database Reviews 2016. DOI: 10.1093/database/baw016.

Rocke, E., H. Jing, X. Xia, et al. (2016). “Effects of hypoxia on the phylogenetic composition and species distribution of protists in a subtropical harbor”. In: Microbial Ecology 72.1, pp. 96 - 105. DOI: 10.1007/s00248-016-0751-7.

Schiaffino, M. R., E. Lara, L. D. Fernández, et al. (2016). “Microbial eukaryote communities exhibit robust biogeographical patterns along a gradient of Patagonian and Antarctic lakes”. In: Environmental Microbiology 18.12, pp. 5249 - 5264. DOI: 10.1111/1462-2920.13566.

Scholz, B., L. Guillou, A. V. Marano, et al. (2016). “Zoosporic parasites infecting marine diatoms-A black box that needs to be opened”. In: Fungal Ecology 19, pp. 59 - 76. DOI: 10.1016/j.funeco.2015.09.002.

Shazib, S. U. A., P. Vďačný, J. H. Kim, et al. (2016). “Molecular phylogeny and species delimitation within the ciliate genus Spirostomum (Ciliophora, Postciliodesmatophora, Heterotrichea), using the internal transcribed spacer region”. In: Molecular Phylogenetics and Evolution 102, pp. 128 - 144. DOI: 10.1016/j.ympev.2016.05.041.

Simon, M., P. López-García, P. Deschamps, et al. (2016). “Resilience of freshwater communities of small microbial eukaryotes undergoing severe drought events”. In: Frontiers in Microbiology 7.MAY. DOI: 10.3389/fmicb.2016.00812.

Singer, D., E. Lara, M. M. Steciow, et al. (2016). “High-throughput sequencing reveals diverse oomycete communities in oligotrophic peat bog micro-habitat”. In: Fungal Ecology 23, pp. 42 - 47. DOI: 10.1016/j.funeco.2016.05.009.

Sun, P., J. Clamp, D. Xu, et al. (2016). “An integrative approach to phylogeny reveals patterns of environmental distribution and novel evolutionary relationships in a major group of ciliates”. In: Scientific Reports 6. DOI: 10.1038/srep21695.

Volant, A., M. Héry, A. Desoeuvre, et al. (2016). “Spatial distribution of eukaryotic communities using high-throughput sequencing along a pollution gradient in the arsenic-rich creek sediments of carnoulès mine, france”. In: Microbial Ecology 72.3, pp. 608 - 620. DOI: 10.1007/s00248-016-0826-5.

Voudanta, E., K. A. Kormas, S. Monchy, et al. (2016). “Mussel biofiltration effects on attached bacteria and unicellular eukaryotes in fish-rearing seawater”. In: PeerJ 2016.3. DOI: 10.7717/peerj.1829.

Zaiko, A., K. Schimanski, X. Pochon, et al. (2016). “Metabarcoding improves detection of eukaryotes from early biofouling communities: implications for pest monitoring and pathway management”. In: Biofouling 32.6, pp. 671 - 684. DOI: 10.1080/08927014.2016.1186165.

Zoccarato, L., A. Pallavicini, F. Cerino, et al. (2016). “Water mass dynamics shape Ross Sea protist communities in mesopelagic and bathypelagic layers”. In: Progress in Oceanography 149, pp. 16 - 26. DOI: 10.1016/j.pocean.2016.10.003.

2015

Balzano, S., E. Abs, and S. C. Leterme (2015). “Protist diversity along a salinity gradient in a coastal lagoon”. In: Aquatic Microbial Ecology 74.3, pp. 263 - 277. DOI: 10.3354/ame01740.

Bass, D., G. D. Stentiford, D. Littlewood, et al. (2015). “Diverse applications of environmental DNA methods in parasitology”. In: Trends in Parasitology 31.10, pp. 499 - 513. DOI: 10.1016/j.pt.2015.06.013.

Christaki, U., C. Georges, S. Genitsaris, et al. (2015). “Microzooplankton community associated with phytoplankton blooms in the naturally iron-fertilized Kerguelen area (Southern Ocean)”. In: FEMS Microbiology Ecology 91.7. DOI: 10.1093/femsec/fiv068.

Decelle, J., S. Romac, R. F. Stern, et al. (2015). “PhytoREF: A reference database of the plastidial 16S rRNA gene of photosynthetic eukaryotes with curated taxonomy”. In: Molecular Ecology Resources 15.6, pp. 1435 - 1445. DOI: 10.1111/1755-0998.12401.

Egge, E. S., W. Eikrem, and B. Edvardsen (2015). “Deep-branching novel lineages and high diversity of haptophytes in the Skagerrak (Norway) uncovered by 454 pyrosequencing”. In: Journal of Eukaryotic Microbiology 62.1, pp. 121 - 140. DOI: 10.1111/jeu.12157.

Esling, P., F. Lejzerowicz, and J. Pawlowski (2015). “Accurate multiplexing and filtering for high-throughput amplicon-sequencing”. In: Nucleic Acids Research 43.5, pp. 2513 - 2524. DOI: 10.1093/nar/gkv107.

Geisen, S., I. Laros, A. Vizcaíno, et al. (2015). “Not all are free-living: High-throughput DNA metabarcoding reveals a diverse community of protists parasitizing soil metazoa”. In: Molecular Ecology 24.17, pp. 4556 - 4569. DOI: 10.1111/mec.13238.

Genitsaris, S., S. Monchy, E. Viscogliosi, et al. (2015). “Seasonal variations of marine protist community structure based on taxon-specific traits using the eastern English Channel as a model coastal system”. In: FEMS Microbiology Ecology 91.5. DOI: 10.1093/femsec/fiv034.

Goltsman, D. S. A., L. R. Comolli, B. C. Thomas, et al. (2015). “Community transcriptomics reveals unexpected high microbial diversity in acidophilic biofilm communities”. In: ISME Journal 9, pp. 1014 - 1023. DOI: 10.1038/ismej.2014.200.

Gong, J., F. Shi, B. Ma, et al. (2015). “Depth shapes α- and β-diversities of microbial eukaryotes in surficial sediments of coastal ecosystems”. In: Environmental Microbiology 17.10, pp. 3722 - 3737. DOI: 10.1111/1462-2920.12763.

Guardiola, M., M. J. Uriz, P. Taberlet, et al. (2015). “Deep-sea, deep-sequencing: Metabarcoding extracellular DNA from sediments of marine canyons”. In: PLoS ONE 10.10. DOI: 10.1371/journal.pone.0139633.

Jeffries, T. C., M. Ostrowski, R. B. Williams, et al. (2015). “Spatially extensive microbial biogeography of the Indian Ocean provides insights into the unique community structure of a pristine coral atoll”. In: Scientific Reports 5. DOI: 10.1038/srep15383.

Lejzerowicz, F., P. Esling, L. Pillet, et al. (2015). “High-throughput sequencing and morphology perform equally well for benthic monitoring of marine ecosystems”. In: Scientific Reports 5. DOI: 10.1038/srep13932.

Lima-Mendez, G., K. Faust, N. Henry, et al. (2015). “Determinants of community structure in the global plankton interactome”. In: Science 348.6237. DOI: 10.1126/science.1262073.

Mahé, F., J. Mayor, J. Bunge, et al. (2015). “Comparing high-throughput platforms for sequencing the V4 region of SSU-rDNA in environmental microbial eukaryotic diversity surveys”. In: Journal of Eukaryotic Microbiology 62.3, pp. 338 - 345. DOI: 10.1111/jeu.12187.

Mahé, F., T. Rognes, C. Quince, et al. (2015). “Swarmv2: Highly-scalable and high-resolution amplicon clustering”. In: PeerJ 2015.12. DOI: 10.7717/peerj.1420.

Massana, R. (2015). Protistan diversity in environmental molecular surveys. DOI: 10.1007/978-4-431-55130-0_1.

Massana, R., A. Gobet, S. Audic, et al. (2015). “Marine protist diversity in European coastal waters and sediments as revealed by high-throughput sequencing”. In: Environmental Microbiology 17.10, pp. 4035 - 4049. DOI: 10.1111/1462-2920.12955.

Morard, R., K. F. Darling, F. Mahé, et al. (2015). “PFR2: A curated database of planktonic foraminifera 18S ribosomal DNA as a resource for studies of plankton ecology, biogeography and evolution”. In: Molecular Ecology Resources 15.6, pp. 1472 - 1485. DOI: 10.1111/1755-0998.12410.

Pánek, T., P. Táborskỳ, M. G. Pachiadaki, et al. (2015). “Combined culture-based and culture-independent approaches provide insights into diversity of jakobids, an extremely plesiomorphic eukaryotic lineage”. In: Frontiers in Microbiology 6.NOV. DOI: 10.3389/fmicb.2015.01288.

Pochon, X., A. Zaiko, G. A. Hopkins, et al. (2015). “Early detection of eukaryotic communities from marine biofilm using high-throughput sequencing: an assessment of different sampling devices”. In: Biofouling 31.3, pp. 241 - 251. DOI: 10.1080/08927014.2015.1028923.

Pringault, O., J. Aube, O. Bouchez, et al. (2015). “Contrasted effects of natural complex mixtures of PAHs and metals on oxygen cycle in a microbial mat”. In: Chemosphere 135, pp. 189 - 201. DOI: 10.1016/j.chemosphere.2015.04.037.

Richards, T. A., G. Leonard, F. Mahé, et al. (2015). “Molecular diversity and distribution of marine fungi across 130 european environmental samples”. In: Proceedings of the Royal Society B: Biological Sciences 282.1819. DOI: 10.1098/rspb.2015.2243.

Rodríguez-Marconi, S., R. De La Iglesia, B. Díez, et al. (2015). “Characterization of bacterial, archaeal and eukaryote symbionts from antarctic sponges reveals a high diversity at a three-domain level and a particular signature for this ecosystem”. In: PLoS ONE 10.9. DOI: 10.1371/journal.pone.0138837.

Saghaï, A., Y. Zivanovic, N. Zeyen, et al. (2015). “Metagenome-based diversity analyses suggest a significant contribution of non-cyanobacterial lineages to carbonate precipitation in modern microbialites”. In: Frontiers in Microbiology 6.AUG. DOI: 10.3389/fmicb.2015.00797.

Simon, M., P. López-García, P. Deschamps, et al. (2015). “Marked seasonality and high spatial variability of protist communities in shallow freshwater systems”. In: ISME Journal 9.9, pp. 1941 - 1953. DOI: 10.1038/ismej.2015.6.

Wu, W., L. Wang, Y. Liao, et al. (2015). “Microbial eukaryotic diversity and distribution in a river plume and cyclonic eddy-influenced ecosystem in the South China Sea”. In: MicrobiologyOpen 4.5, pp. 826 - 840. DOI: 10.1002/mbo3.282.

2014

Chambouvet, A., C. Berney, S. Romac, et al. (2014). “Diverse molecular signatures for ribosomally ‘active’ Perkinsea in marine sediments”. In: BMC Microbiology 14.1. DOI: 10.1186/1471-2180-14-110.

Christaki, U., K. A. Kormas, S. Genitsaris, et al. (2014). “Winter-summer succession of unicellular eukaryotes in a meso-eutrophic coastal system”. In: Microbial Ecology 67.1, pp. 13 - 23. DOI: 10.1007/s00248-013-0290-4.

Decelle, J., S. Romac, E. Sasaki, et al. (2014). “Intracellular diversity of the V4 and V9 regions of the 18S rRNA in marine protists (radiolarians) assessed by high-throughput sequencing”. In: PLoS ONE 9.8. DOI: 10.1371/journal.pone.0104297.

Georges, C., S. Monchy, S. Genitsaris, et al. (2014). “Protist community composition during early phytoplankton blooms in the naturally iron-fertilized Kerguelen area (Southern Ocean)”. In: Biogeosciences (Online) 11.20, pp. 5847 - 5863. DOI: 10.5194/bg-11-5847-2014.

Heger, T. J., V. P. Edgcomb, E. Kim, et al. (2014). “A resurgence in field research is essential to better understand the diversity, ecology, and evolution of microbial eukaryotes”. In: Journal of Eukaryotic Microbiology 61.2, pp. 214 - 223. DOI: 10.1111/jeu.12095.

Lara, E., C. V. W. Seppey, G. G. Garraza, et al. (2014). “Planktonic eukaryote molecular diversity: Discrimination of minerotrophic and ombrotrophic peatland pools in Tierra del Fuego (Argentina)”. In: Journal of Plankton Research 37.3, pp. 645 - 655. DOI: 10.1093/plankt/fbv016.

Lejzerowicz, F., P. Esling, and J. Pawlowski (2014). “Patchiness of deep-sea benthic foraminifera across the southern ocean: Insights from high-throughput DNA sequencing”. In: Deep-Sea Research Part II: Topical Studies in Oceanography 108, pp. 17 - 26. DOI: 10.1016/j.dsr2.2014.07.018.

Lentendu, G., T. Wubet, A. Chatzinotas, et al. (2014). “Effects of long-term differential fertilization on eukaryotic microbial communities in an arable soil: A multiple barcoding approach”. In: Molecular Ecology 23.13, pp. 3341 - 3355. DOI: 10.1111/mec.12819.

Lie, A. A. Y., Z. Liu, S. K. Hu, et al. (2014). “Investigating microbial eukaryotic diversity from a global census: Insights from a comparison of pyrotag and full-length sequences of 18S rRNA genes”. In: Applied and Environmental Microbiology 80.14, pp. 4363 - 4373. DOI: 10.1128/AEM.00057-14.

Logares, R., S. Audic, D. Bass, et al. (2014). “Patterns of rare and abundant marine microbial eukaryotes”. In: Current Biology 24.8, pp. 813 - 821. DOI: 10.1016/j.cub.2014.02.050.

Massana, R., J. Del Campo, M. E. Sieracki, et al. (2014). “Exploring the uncultured microeukaryote majority in the oceans: Reevaluation of ribogroups within stramenopiles”. In: ISME Journal 8.4, pp. 854 - 866. DOI: 10.1038/ismej.2013.204.

Nanjappa, D., S. Audic, S. Romac, et al. (2014). “Assessment of species diversity and distribution of an ancient diatom lineage using a DNA metabarcoding approach”. In: PLoS ONE 9.8. DOI: 10.1371/journal.pone.0103810.

Parfrey, L. W., W. A. Walters, C. L. Lauber, et al. (2014). “Communities of microbial eukaryotes in the mammalian gut within the context of environmental eukaryotic diversity”. In: Frontiers in Microbiology 5.JUN. DOI: 10.3389/fmicb.2014.00298.

Parris, D. J., S. Ganesh, V. P. Edgcomb, et al. (2014). “Microbial eukaryote diversity in the marine oxygen minimum zone off northern Chile”. In: Frontiers in Microbiology 5.OCT. DOI: 10.3389/fmicb.2014.00543.

Patterson, D. J. (2014). “Helping Protists to find their place in a big data world”. In: Acta Protozoologica 53.1, pp. 115 - 128. DOI: 10.4467/16890027AP.14.011.1448.

Taylor, J. D. and M. Cunliffe (2014). “High-throughput sequencing reveals neustonic and planktonic microbial eukaryote diversity in coastal waters”. In: Journal of Phycology 50.5, pp. 960 - 965. DOI: 10.1111/jpy.12228.

Wu, W., B. Huang, Y. Liao, et al. (2014). “Picoeukaryotic diversity and distribution in the subtropical-tropical south china sea”. In: FEMS Microbiology Ecology 89.3, pp. 563 - 579. DOI: 10.1111/1574-6941.12357.

Xiuhai, L. (2014). “An OpenFlow switch model using kepler GPU”. In: Journal of Software Engineering 8.4, pp. 304 - 313. DOI: 10.3923/jse.2014.304.313.

Xu, Y., T. Vick-Majors, R. Morgan-Kiss, et al. (2014). “Ciliate diversity, community structure, and novel taxa in lakes of the McMurdo dry valleys, antarctica”. In: Biological Bulletin 227.2, pp. 175 - 190. DOI: 10.1086/BBLv227n2p175.

Yilmaz, P., L. W. Parfrey, P. Yarza, et al. (2014). “The SILVA and”all-species living tree project (LTP)” taxonomic frameworks”. In: Nucleic Acids Research 42.D1, pp. D643-D648. DOI: 10.1093/nar/gkt1209.

2013

Adl, S. M., A. Habura, and Y. Eglit (2013). “Amplification primers of SSU rDNA for soil protists”. In: Soil Biology and Biochemistry 69, pp. 328 - 342. DOI: 10.1016/j.soilbio.2013.10.024.

Cheung, M. K., W. Nong, H. S. Kwan, et al. (2013). “Composition of heterotrophic flagellates in coastal waters of different trophic status”. In: Current Microbiology 67.3, pp. 351 - 355. DOI: 10.1007/s00284-013-0374-x.

Decelle, J., P. Martin, K. Paborstava, et al. (2013). “Diversity, ecology and biogeochemistry of cyst-forming acantharia (radiolaria) in the oceans”. In: PLoS ONE 8.1. DOI: 10.1371/journal.pone.0053598.

Egge, E., L. Bittner, T. Andersen, et al. (2013). “454 pyrosequencing to describe microbial eukaryotic community composition, diversity and relative abundance: a test for marine haptophytes”. In: PLoS ONE 8.9. DOI: 10.1371/journal.pone.0074371.

Fernández-Suárez, X. M. and M. Y. Galperin (2013). “The 2013 nucleic acids research database issue and the online molecular biology database collection”. In: Nucleic Acids Research 41.D1, pp. D1-D7. DOI: 10.1093/nar/gks1297.

Risse-Buhl, U., M. Herrmann, P. Lange, et al. (2013). “Phagotrophic protist diversity in the groundwater of a karstified aquifer - Morphological and molecular analysis”. In: Journal of Eukaryotic Microbiology 60.5, pp. 467 - 479. DOI: 10.1111/jeu.12054.

Thaler, M. and C. Lovejoy (2013). “Environmental selection of marine stramenopile clades in the Arctic Ocean and coastal waters”. In: Polar Biology 37.3, pp. 347 - 357. DOI: 10.1007/s00300-013-1435-0.

Vinogradov, S. N., X. Bailly, D. R. Smith, et al. (2013). “Microbial eukaryote globins”. In: Advances in Microbial Physiology 63, pp. 391 - 446. DOI: 10.1016/B978-0-12-407693-8.00009-1.