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The Obstetrician & Gynaecologist 10.1576/toag.13.3.189.27672 http://onlinetog.org 2011;13:189–195 SAC review

SAC review ‘Omic’ technologies:

genomics, transcriptomics,
proteomics and metabolomics
Authors Richard P Horgan / Louise C Kenny
Key content:
• ‘Omic’ technologies are primarily aimed at the universal detection of genes (genomics),
mRNA (transcriptomics), proteins (proteomics) and metabolites (metabolomics) in a specific
biological sample.
• Omic technologies have a broad range of applications.
• Genomic and transcriptomic research has progressed due to advances in microarray technology.
• Mass spectrometry is the most common method used for the detection of analytes in
proteomic and metabolomic research.
• Data analysis is complex as a huge amount of data is generated and statistician and
bioinformatician involvement in the process is essential.
• Much of the omic research in obstetrics and gynaecology has concentrated on using the
technology to develop screening tests for gynaecological cancers and obstetric complications.
Learning objectives:
• To learn about the omic disciplines and to be clear about the terminology in use.
• To appreciate that the omic experiment is a complex process requiring thorough study design and
sample preparation, involving a number of technologies and requiring extensive data analysis.
• To gain a brief overview of the application of these approaches to obstetrics and gynaecology.

Ethical issues:
• The use of genetic testing, particularly in the area of predisposition genes.
• Ethical issues surrounding the storage and use of samples in biobanks and the associated clinical data.
• The limited access to the technology involved in these techniques.
Keywords genomics / metabolomics / proteomics / technology / systems biology /
transcriptomics
Please cite this article as: Horgan RP, Kenny LC. ‘Omic’ technologies: genomics, transcriptomics, proteomics and metabolomics. The Obstetrician & Gynaecologist 2011;13:189–195.

Author details
Richard P Horgan MRCOG MRCPI College Cork, Cork University Maternity Louise C Kenny MRCOG PhD University College Cork, Cork,
Clinical Research Fellow and Specialist Hospital, Cork, Republic of Ireland Consultant Obstetrician Gynaecologist Republic of Ireland
Registrar in Obstetrics and Gynaecology Email: Richard.horgan@ucc.ie and Professor of Obstetrics
The Anu Research Centre, Department of (corresponding author) The Anu Research Centre,
Obstetrics and Gynaecology, University Department of Obstetrics and Gynaecology,

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This article was commissioned

Introduction as they investigate multiple molecules
‘Omic’ technologies adopt a holistic view of the simultaneously. Omic investigation is increasingly
by the Scientific Advisory
Committee (SAC) molecules that make up a cell, tissue or organism. being used in drug discovery and assessment of
They are aimed primarily at the universal detection their toxicity and efficacy.4,5 Pharmacogenomics —
of genes (genomics), mRNA (transcriptomics), the intersection of genomics and pharmacology —
proteins (proteomics) and metabolites is the study of the role of inheritance in individual
(metabolomics) in a specific biological sample in a variation in drug response which can potentially
non-targeted and non-biased manner. This can also be used to individualise and optimise drug
be referred to as high-dimensional biology; the therapy.6 Pharmacogenomics is especially
integration of these techniques is called systems important for oncology, as severe systemic toxicity
biology (Figure 1) (see Box 1 for a list of and unpredictable efficacy are hallmarks of cancer
definitions).1,2 The basic aspect of these approaches therapies.7 Systems approaches to conditions such
is that a complex system can be understood more as cancer, cardiovascular disease and obesity give
thoroughly if considered as a whole. Systems the opportunity to facilitate greatly the success of
biology and omics experiments differ from selecting novel targets for treatments and drug
traditional studies, which are largely hypothesis- development. In the future, systems biology may
driven or reductionist. By contrast, systems biology enable us to develop new approaches that will be
experiments are hypothesis-generating, using predictive, preventive and personalised.
holistic approaches where no hypothesis is known
or prescribed but all data are acquired and analysed Research in obstetrics and gynaecology is currently
to define a hypothesis that can be further tested.3 taking advantage of these possibilities. The aim of
this review is to provide an overview of the omic
These strategies have many applications and much experiment and technologies and their potential
potential. Omic technology can be applied not application to women’s health research.
only for the greater understanding of normal
physiological processes but also in disease High-dimensional biology
processes where they play a role in screening, Genomics is the systematic study of an organism’s
diagnosis and prognosis as well as aiding our genome. The genome is the total DNA of a cell or
understanding of the aetiology of diseases. Omic organism. The human genome contains 3.2 billion
strategies lend themselves to biomarker discovery bases8 and an estimated 30 000–40 000 protein-
coding genes. Traditionally, genes have been
analysed individually but microarray technology
Figure 1
Omic sciences and their
has advanced substantially in recent years. DNA
interaction. The flow of biological microarrays measure differences in DNA sequence
information is bidirectional. The
numbers are the approximate
between individuals and the expression of
quantity at each functional level thousands of genes can be analysed simultaneously.
They can reveal abnormalities such as chromosomal
insertions and deletions or abnormal chromosomal
numbers in a process called comparative genomic
hybridisation. The most common variations in DNA
sequences between people are single nucleotide
polymorphisms (SNPs), in which one nucleotide is
substituted for another; this may have functional
significance if the change results in a codon for a
different amino acid. They are of particular interest
when linked with diseases with a genetic
determination. Single nucleotide polymorphism
profiling also has a role in pharmacogenomics in
exploring individual patient responses to drugs.

The transcriptome is the total mRNA in a cell or

organism and the template for protein synthesis in
a process called translation. The transcriptome
reflects the genes that are actively expressed at any
given moment. Gene expression microarrays
measure packaged mRNA (mRNA with the introns
spliced out) as a summary of gene activity.

While advances in microarray technology have

resulted in progress in genomics and transcriptomics
(and the resultant literature), it is important to

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highlight some limitations. Specifically, gene Systems biology Box 1

expression microarrays measure changes in Omics-related definitions
Biological research focusing on the systematic study of
mRNA abundance, not protein, and thus there is a complex interactions in biological systems using integration
models. The ultimate aim is to understand whole systems, e.g.
lack of consensus around the interpretation of complex cellular pathways, by studying the effect of altered
microarray data. external factors on the genome, transcriptome, proteome and
metabolome simultaneously
Genomics
The proteome is defined as the set of all expressed
The study of the structure, function and expression of all the
proteins in a cell, tissue or organism.9 Proteomics genes in an organism
aims to characterise information flow within the Genome
cell and the organism, through protein pathways The total DNA of a cell or organism
and networks,10 with the eventual aim of Polymorphism
understanding the functional relevance of Variations in DNA at a specific site
proteins.11 While we can gain much information Transcriptomics
from proteomic investigation, it is complicated by The study of the mRNA within a cell or organism
its domain size (>100 000 proteins) and the Transcriptome
inability to detect accurately low-abundance The total mRNA in a cell or organism
proteins. The proteome is a dynamic reflection of Proteomics
both genes and the environment and is thought to The large-scale study of proteins, including their structure and
hold special promise for biomarker discovery function, within a cell/system/organism. A name coined as an
analogy with the genome
because proteins are most likely to be ubiquitously
Proteome
affected in disease and disease response.12 This is
The set of all expressed proteins in a cell, tissue or organism
reflected in the many protein disease biomarkers
Metabolomics
already available (e.g. CA125 and alpha-fetoprotein).
The study of global metabolite profiles in a system (cell, tissue
or organism) under a given set of conditions
Metabolomics can generally be defined as the study Metabolome
of global metabolite profiles in a system (cell, tissue The total quantitative collection of low molecular weight
or organism) under a given set of conditions.13 compounds (metabolites) present in a cell or organism that
participate in metabolic reactions. It also includes those
Metabolomics has a number of theoretical metabolites taken in from external environments or symbiotic
advantages over the other omic approaches. The relationships
metabolome is the final downstream product of Metabonomics
gene transcription and, therefore, changes in the A measure of the fingerprint of biochemical perturbations
caused by disease, drugs and toxins; some would say that
metabolome are amplified relative to changes in the metabonomics and metabolomics are the same and the
transcriptome and the proteome.14 Additionally, as terms are occasionally used interchangeably
the downstream product, the metabolome is closest Mass spectrometry
to the phenotype of the biological system studied. An analytical technique measuring the mass-to-charge (m/z)
ratio of charged particles
Although the metabolome contains the smallest
domain (~5000 metabolites), it is more diverse,
containing many different biological molecules, required to generate the greatest predictive power,
making it more physically and chemically complex therefore, the collection of clinical data and
than the other ‘omes’. biological samples in large biobanks is essential. The
SCOPE (SCreening fOr Pregnancy Endpoints)
The omic experiment study is an example of such a pregnancy-related
Experimental design biobank (see below and Websites section).
Areas that require careful thought include:
The purpose of the investigation governs what type
• the use of suitable biological samples: the choice of sample should be used. In terms of biomarker
of the sample type to investigate is dependent on discovery, plasma is the obvious candidate, as the
the objectives of the experiment and the ultimate goal is usually a blood test.15 However,
availability of the sample biomarkers are likely to occur in low relative
• the technical/analytical variation: this is the relative abundance and be massively diluted in the
standard deviation of a specific experimental circulation.15 Rigorous reproducible standard
technique and this needs to be validated operating procedures are essential to ensure that
• the biological variation: in humans this can be samples are collected, stored and transported in an
very large, therefore it is important to collect identical manner.
meta-data and, in certain study designs, to match
comparison groups strongly, to ensure that Analytical techniques
changes are not due to confounding factors. Sample preparation for omic experiments is imperative
and should be standardised and reproducible.
A number of factors determine the sample size, but
it has to be such that valid statistical conclusions can DNA microarrays have many modes of use, of
be made. Large numbers of biological specimens are which expression profiling is the dominant mode.

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Figure 2 chips. The amount of the two dyes is representative

Analytical techniques
(a) Process flow for gene
of the gene expression in the different samples. An
expression microarray experiment ultraviolet laser is used to scan the slide which
(b) Simplified schematic workflow
for proteomics experiments
detects the amount of fluorescent signal for each
(c) Simplified schematic workflow gene. This image is then analysed (Figure 2a).
for metabolomics experiments
PCR ⴝ polymerase chain reaction;
RNA ⴝ ribonucleic acid The principal considerations in a proteomic
experiment are protein concentration, sample
purification and protein digestion, plus affinity
capture and sample fractionation (using gel-based
or chromatography techniques) to reduce the
complexity of the target fluid. These steps require
different emphasis, depending on the biological
sample being used (Figure 2b). For example, urine
provides different analytical challenges to plasma,
including the need for preparation techniques such
as ultrafiltration and precipitation, which are
necessary to remove salts and concentrate urinary
proteins. Different problems can arise for each fluid,
such as inter-individual variation in urinary protein
concentration in diseases such as pre-eclampsia.

The degree of sample preparation required for

metabolomic experiments depends on the type of
sample. Metabolomic samples also require
fractionation (usually chromatography or
electrophoresis) prior to analysis. These
fractionation techniques use the different
chemical/physical properties of molecules and
enable the separation of proteins/peptides/
metabolites in liquid or gas phase (Figure 2c).

Mass spectrometry is the most commonly used

method for the investigation/identification of
analytes in both proteomics and metabolomics. Ions
are created from neutral proteins, peptides or
metabolites, which are then separated according to
In gene expression microarray, the probe used to their mass-to-charge ratio (m/z) and detected to
assess the amount of mRNA can be either create a mass spectrum, which is characteristic of the
complementary DNA (cDNA) or an molecular mass and/or structure. Figure 3 shows a
oligonucleotide. The probe is amplified by general flow chart for mass spectrometry. Each
polymerase chain reaction (PCR) and spotted onto analytical technique offers different advantages and
an array which is then immobilised on a solid limitations in terms of instrument sensitivity,
support (glass slide).16 In the experiment RNA is resolution, mass accuracy, dynamic range and
extracted from the samples and, by the process of throughput: a number of techniques are needed to
reverse transcription and addition of fluorescent analyse the entire proteome or metabolome. In
dyes, labelled cDNA is formed (both proteomics, several ionisation techniques have
normal/control and diseased/case) which is then improved the way proteins are characterised and
combined and hybridised with the microarray sequenced, in particular, electrospray ionisation
slide. These microarray glass slides are often called (ESI) and matrix-assisted laser desorption/

Figure 3
General flow chart for mass
spectrometry. APCI ⴝ atmospheric
pressure chemical ionisation;
CE ⴝ capillary electrophoresis;
CI ⴝ chemical ionisation;
EI ⴝ electron impact ionisation;
ESI ⴝ electrospray ionisation;
FTICR ⴝ Fourier transform ion
cyclotron resonance; GC ⴝ gas
chromatography; LC ⴝ liquid
chromatography; MALDI ⴝ matrix-
assisted laser desorption/
ionisation; MCP ⴝ microchannel
plate; TOF ⴝ time of flight

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ionisation (MALDI), while questions have been producing the model is called the training set.
raised regarding reproducibility, accuracy, mass Models built using the training data can then be
range and dynamic range of another technique, independently validated using the hold-out set. An
surface-enhanced laser desorption/ionisation alternative method of independent model validation
(SELDI). Quantitative analysis has been improved is to use permutation testing.19 More robust methods
by several techniques, including differential image include confirming the observations with a
gel electrophoresis (DIGE), which uses fluorescent complementary technique and replicating the
tags in gel-based techniques, and strategies of experiment in a different sample set.20
isotopically coded affinity tag (ICAT) labelling have
been used along with tandem mass spectrometry. In There are many publications, across all the
metabolomics, other analytical platforms, including biological sciences, pointing out the potential folly
nuclear magnetic resonance (NMR) spectroscopy of using profiling techniques such as metabolomics,
and infra-red spectroscopy, have also been used for proteomics, transcriptomics and genomics in order
metabolite identification but this is still an area that to discover clinically significant biomarkers.21–25
requires significant improvement.17 Nuclear
magnetic resonance spectroscopy is disadvantaged These areas of experimental design, sample
by its poor sensitivity and can only reliably detect preparation, analytical techniques and data analysis
and quantify metabolites present in relatively high are covered in greater detail in a number of review
concentrations. Spectroscopy also has limited articles.13,21,26–30
sensitivity and poor ability to identify metabolites in
complex samples. Omic research in obstetrics
It is important to realise that not all omic techniques and gynaecology
can be interpreted equally and that each analytical While omic studies in the area of obstetrics and
technique offers different advantages and limitations. gynaecology are relatively small in number, with
There often has to be a trade-off between the advancing technology, it is a rapidly expanding field
technique and the experimental objectives. of research. It is not possible in this article to give an
in-depth discussion of all omic research in
obstetrics and gynaecology. As may be anticipated,
Data analysis most of the omic research in gynaecology is centred
Given the enormous amount of data generated in on oncology and cancer screening and much of the
these studies, sophisticated bioinformatics and work in obstetrics on identifying biomarkers for
dedicated statisticians are fundamental. complications of pregnancy such as pre-eclampsia
and preterm birth.
In genomics and transcriptomics microarray data
analysis can prove difficult. Huge numbers of A wide range of biological samples has been used
variables (each gene) in microarray experiments for omic research, including plasma/serum, urine,
complicate the statistics and increase the amniotic fluid, cultured trophoblasts and
likelihood of false positives. Microarray changes cervicovaginal and follicular fluid.
should be validated using real-time PCR. In
proteomics, the properties of many thousands of Pre-eclampsia
ions are recorded in a single experiment and Studies have found gene expression to differ
complex algorithms are used to match these data to between pregnancies with pre-eclampsia and
a theoretical database to enable protein uncomplicated pregnancies in peripheral blood,31
identification and/or quantification. In first-trimester placentas32 and placentas at delivery.33
metabolomics, raw data require transformation to
a suitable format prior to processing. The methods Much of the proteomic research in pregnancy has
available for analysis comprise various statistical been in the area of pre-eclampsia. Studies have
techniques including univariate and multivariate shown differences in women with pre-eclampsia
analysis, supervised and unsupervised learning compared with women with uncomplicated
tools and system-based analyses. The aim of these pregnancies, including differing serum levels of
strategies is to find data patterns that provide clusterin34 and ficolin35 but these were time-of-
useful biological information which can be used to disease samples. One study36 showed differences in
generate further hypotheses for testing. five proteins at 26 weeks of gestation but these
proteins could not be identified. Recently the
Omic strategies generate huge amounts of data and plasma proteome at 20 weeks in women who
multiple testing increases the likelihood of false subsequently developed pre-eclampsia (n = 39) was
positives. Data validation is essential to ensure that compared with that in normal healthy controls
findings are not just random findings. P-values can (n = 57): 39 proteins were identified and two protein
be corrected for multiple testing (false discovery clusters identified as fibrinogen gamma-chain and
rate). Other methods of model validation include alpha-1-antichymotrypsin accurately classified
the use of a ‘hold-out’ or ‘test’ set.18 The set used in women at risk of developing pre-eclampsia.37

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Most metabolomic research has focused on pre- early detection of epithelial ovarian cancer and one
eclampsia and a number of researchers have found study using three markers (osteopontin, kallikrein
differences between women with pre-eclampsia 10 or MMP-7) in combination with CA125 had
and women with uncomplicated pregnancies using sensitivity and specificity values approaching 100%.52
a number of different analytical techniques,38–42 but
these used time-of-disease blood samples or In gynaecological oncology, proteomic profiling
placentas at delivery and further work needs to was initially applied to human serum to identify
concentrate on early pregnancy if predictive ovarian cancer by Petricoin et al.53 Gadducci et al.54
markers are to be found. give a good overview of the markers associated with
ovarian, endometrial and cervical cancer and the
Not only are omic strategies of value in potential role proteomic profiling has to play. CA125 is the
biomarker discovery, they also help to elucidate the most reliable marker in ovarian cancer. Recently the
molecular mechanisms involved in both normal autoantibody against the S100A7 protein has been
and diseased states. Hypoxia plays a role in the found to be elevated in early and late-stage ovarian
pathophysiology of pre-eclampsia and fetal growth cancer but the clinical usefulness has yet to be
restriction and Hoang et al.43 have detected distinct investigated.55
changes in the protein expression of first-trimester
cytotrophoblasts under hypoxic conditions. Metabolic profiling using gas chromatography–
Metabolomic differences have also been mass spectrometry has also shown differences
demonstrated on placental explants under different between malignant and borderline ovarian
oxygen conditions42 and from women with tumours using fresh-frozen tumour samples.56
pre-eclampsia.44 This demonstrates the systems
biology approach to experimental models. Conclusion
Omic strategies still provide many challenges: the
Preterm birth technology and the software are still evolving and
Romero et al.45 have extensively reviewed the mapping the human proteome and metabolome is
application of high-dimensional biology to the still ongoing. Pregnancy is a unique physiological
preterm parturition syndrome incorporating state and pregnancy conditions can be extremely
spontaneous preterm birth and preterm prelabour heterogeneous. Carefully designed experiments,
rupture of membranes. Numerous genetic accompanied by appropriate analytical techniques
polymorphisms have been reported that confer and statistical analyses, will assist in tackling many
increased risk of preterm birth or preterm of these challenges, with the potential to generate
prelabour rupture of membranes, in particular reliable validated data to answer important
those coding for matrix metalloproteinases biological questions.
(MMPs) and interleukins.
The SCOPE study (see Websites) is actively
In preterm birth, differential expression of proteins recruiting. This is a collaboration of many
has been found in placental membranes,46 international leading obstetricians and scientists
cervicovaginal fluid,47,48 amniotic fluid49 and seeking to develop novel, effective ways for the early
maternal serum.50 prediction of nulliparous women at high risk of the
three major complications of late pregnancy: pre-
The metabolic profiling of amniotic fluid has been eclampsia, spontaneous preterm birth and fetal
reported to identify women at risk of preterm growth restriction. An extensive clinical database
delivery and intra-amniotic infection with a combined with genomic/proteomic/metabolomic
precision of 96%.51 data may provide the means for predictive
screening tests to be developed.
Oncology
Profiling of gynaecological cancers has provided Websites
insight into the origin of these tumours as well as The SCOPE (SCreening fOr Pregnancy Endpoints)
attempting to find diagnostic markers and potential study [www.scopestudy.net/]
therapies and to predict response to treatment.
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