Sequencing-by-synthesis (SBS) technologies have provided new cost efficient ways of obtaining a high quality draft assembly as well as a fully finished genome. The result is also a change in the complex dynamics of shotgun assembly which makes it necessary to re-evaluate the whole process, especially when complete finishing is the goal. As of yet, no single SBS technology has proven itself fully capable of providing all the data necessary for efficient and streamlined finishing, therefore, a combination of SBS and Sanger data is still prefered. JGI currently utilizes both 454/Roche and Solexa/Illumina pyrosequencing in addition to the Sanger big-dye shotgun method. In this study we evaluated how various key assembly features are affected by changes in the levels of sequence from different platforms and attempted to arrive to a combination optimal for cost-efficient finishing. We also looked at how stable and predictable this optimum is in genomes with different GC and repeat composition. The criteria we picked are believed to be the best indicators, available upon the initial draft assembly, of what kind of additional effort, and how much of it, is needed to finish a microbial genome to JGI?s quality standards.

With the onset of new technology JGI has shifted its scope of work for microbes to 454 standard titanium, 454 paired end titanium, and illumina data for gap closer and quality improvement (polishing). Raw reads are assembled by Newbler to create a draft assembly that will be passed to finishers. An in-house developed software tool creates subprojects for each gap. In-silico attempts are made to close gaps using existing unassembled pyrosequence and Illumina data. Any remaining gaps are tackled by PCR based methods. These include standard PCR, bubble PCR, multiplex PCR, combinatorial PCR, and long range PCR. Once products are generated they can be sequenced, cloned or shattered as needed. Currently gap closing data is still generated using sanger. Eventually these gaps may be pooled and sequenced using illumina or 454. Once a genome is closed, illumina data is used to polish the genome. Any areas that are still substandard are subjects for resequencing. We extend this approach to fungal genomes

The Rearray Manager is a web-based software application designed at the Joint Genome Institute for microbial finishing. The Rearray Manager allows us to track primers and reaction plates by name, date, library, or reaction type. One of the most critical functions of the Rearray Manager is its interaction with the Tecan robot. Our Tecan machines have been programmed to cherry pick from multiple source plates into a single destination plate. This is very important to our group because as finishers often we only need a handful of clones from a 384 well plate. The Rearray Manager tells the Tecan which wells to pick from and dispense into and dictates the deck layout. The Rearray Manager is intergraded with consed so primers and reaction lists are automatically generated. Alternatively, such lists can be entered manually. The Rearray Manager organizes clones first by library, then by clone number unless you indicate otherwise. This flexibility in sorting is extremely useful when there are multiple libraries combined in one plate. From the Rearray Manager one can also look up plates (primer plates or reaction plates), check on the status of plates, edit or delete plates, and make sample sheets so plates can be loaded onto an ABI 3730. Finishing plates and their source plates can be visualized in 384 or 96 well format. Rearray Manager also generates a list of source plates which is essential to ordering necessary source plates from production storage.Use of the Rearray Manager allows us to effectively perform lab experiments for a large amount of projects.

The introduction of pyrosequencing-based sequencing platforms such as 454-sequencing along with the Sanger technology for whole-genome shotgun sequencing has provided an alternative way to produce cost-effective sequence data. For microbial genome finishing, the 454/Sanger hybrid approach has made a considerable impact in reducing the time required to close a genome. However, errors within the 454 sequencing data remain to be addressed to make sure that final consensus represents high quality sequence. JGI is working on further cost reduction of sequencing and finishing processes and is planning significant cut of Sanger sequencing. This will increase the portion of the genome covered with pyrosequence only. Thus the analysis of errors produced by this new technology becomes very important. We conducted a study to assess the quality of the 454 sequence data in order to determine its impact on error rate, and to devise a strategy to correct or reduce the errors. The study analyzed 29 microbial genomes containing both Sanger and 454 only assemblies to look for mismatches in the 454 sequence data. We examined both homopolymer tracts and non-homopolymer regions with respect to read depth and quality assignment. An overview of our findings and strategy for reducing the 454 errors will be presented.