The genomic standards consortium: bringing standards to life for microbial ecology.

COMMENTARY
The genomic standards consortium: bringing
standards to life for microbial ecology
Pelin Yilmaz, Jack A Gilbert, Rob Knight, Linda Amaral-Zettler, Ilene Karsch-Mizrachi,
Guy Cochrane, Yasukazu Nakamura, Susanna-Assunta Sansone, Frank Oliver Glo¨ckner
and Dawn Field
The ISME Journal (2011) 5, 1565–1567; doi:10.1038/
ismej.2011.39; published online 7 April 2011
Adoption of easy-to-follow standards will
vastly improve our ability to interpret data
from genomes, metagenomes and marker
studies
Interest in sampling of diverse environments,
combined with advances in high-throughput
sequencing, vastly accelerates the pace at which
new genomes and metagenomes are generated. For
example, as of January 2011, 12 500 user-generated
metagenomes have been submitted to the public
MG-RAST Annotation server (http://metagenomics.
nmpdr.org; Meyer et al., 2008), 490% of which
were produced using high-throughput sequencing
methodologies. We have entered into an era
of ‘mega-sequencing projects’ that include the
Genomic Encyclopaedia of Bacteria and Archaea
project (http://www.jgi.doe.gov/programs/GEBA),
the Microbial Earth Project (http://genome.jgi-psf.
org/programs/bacteria-archaea/MEP/index.jsf), the
Human Microbiome Project (http://nihroadmap.nih.
gov/hmp), the Metagenomics of the Human Intest-
inal Tract consortium (http://www.metahit.eu), the
Terragenome Initiative (http://www.terragenome.
org), the Tara Oceans Expedition (http://oceans.
taraexpeditions.org), the National Ecological Obser-
vatory Network (NEON-http://www.neoninc.org),
the International Census of Marine Microbes
(ICoMM-http://icomm.mbl.edu), Microbial Inven-
tory Research Across Diverse Aquatic Long-Term
Ecological Research Sites (http://amarallab.mbl.
edu/mirada/mirada.html), the Earth Microbiome
Project (http://www.earthmicrobiome.org) and other
funded and unfunded projects, with many more
visionary projects on the horizon.
Additionally, studies of emerging metatrans-
criptomes (community transcript profiles), meta-
proteomes (community protein profiles) and
metametabolomes (community metabolite profiles)
now complement genomes and metagenomes. Com-
parative studies of multi-omic data sets from the
same community hold the promise of unparalleled
insights into fundamental questions across a range of
fields including evolution, ecology, environmental
science, physiology and medicine. Advances stem
from improvements in the annotation and quantifica-
tion of genes, pathways, organisms and consortia
within these communities. We are just starting to
exploit these technologies to understand the
microbial world, and have only scratched the surface
in terms of sampling microbial diversity across
temporal and spatial scales (Delmotte et al., 2009;
Gilbert et al., 2010a). To fully exploit the promise
of these data, we need both scientific innovation
and community agreement on how to provide
appropriate stewardship of these resources for the
benefit of all.
Although we have collected billions of nucleic-
acid sequences from thousands of ecosystems,
illuminating uncharacterized microbial lifestyles
remains far from trivial. For example, in each
analysed genome or metagenome, about 40% of
the putative protein-coding genes cannot be
assigned to any known function or taxon. Only
42% of the 61 known bacterial phyla have even a
single cultured representative (Hugenholtz and
Kyrpides, 2009), with the remainder being known
only from 16S rRNA gene environmental surveys.
Surprisingly, only 14% of cultured bacterial taxa
have a single complete genome sequenced. Holistic
approaches that will centralize (meta) omics data
are needed, which will allow investigators to
analyze these data within the context of space, time,
habitat and characteristics of the environment.
Networks of information arising from these studies
will allow us to describe and predict ecological
patterns of organisms, genes, transcripts and
proteins.
One key insight into the function of a gene or
organism is the environment where it occurs.
Collection of contextual (meta) data, which deline-
ates the source of a sequence in terms of the space,
time, habitat and characteristics of the environment,
is thus essential in interpreting these unknown
genes and species, as well as gaining new insights
into the known fraction. Although early comparative
studies of metagenomes (Tringe et al., 2005) relied
on a few, deeply sequenced samples, the experience
The ISME Journal (2011) 5, 1565–1567
& 2011 International Society for Microbial Ecology All rights reserved 1751-7362/11
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from 16S rRNA gene surveys suggests that
additional insight is gained from observing spatial
and temporal variation across hundreds of samples,
whether examining the distribution of bacteria in
soils across a continent (Lauber et al., 2009) or
various skin sites from many subjects (Grice et al.,
2009).
At present, the valuable contextual data halo is
often missing for sequences deposited in the Inter-
national Nucleotide Sequence Database Collabora-
tion (INSDC; GenBank, European Nucleotide
Archive (ENA, including EMBL-Bank) and the
DNA Databank of Japan (DDBJ)). This leaves
researchers in the position of searching in electronic
resources, literature or contacting the authors for
even the most basic contextual data, such as
geographic location, date and time of sampling or
the habitat where the sample was obtained. Mole-
cular ecologists should immediately recognize the
inherent value of these data to the community,
because without them their own sequence data sets
will have extremely limited comparability with the
wealth of other data available. Sequences without
contextual data are like unlabeled cans in a super-
market—you do not know what you are purchasing
until you open it and examine the contents. The
present inability to automatically retrieve rich con-
textual data hampers comparative research, and
constitutes a considerable misuse of the vast global
resources currently being applied to microbial ecology.
Just as food-safety laws emphasize clear and accurate
labeling based on the product, process and producer,
so should sequence data be properly annotated.
Standardization of the required information will
greatly facilitate the annotation of sequence data. To
achieve this, we must first have community colla-
boration and participation. Second, as a result of
this collaboration, a contextual data set must be
standardized in terms of content, syntax and
terminology to which the community can adhere.
In 2005, members of the community came together
to form the Genomic Standards Consortium (GSC),
an open-membership working body with the stated
mission of working towards better descriptions of
our genomes, metagenomes and related data (http://
www.gensc.org). Supported by the expertize of the
members involved in many of the aforementioned
mega-sequencing projects, the GSC has formalized
contextual data requirements for genomes and
metagenomes as the Minimum Information about a
Genome/Metagenome Sequence checklist (MIGS/
MIMS) (Field et al., 2008). Furthermore, to cover
the description of phylogenetic and functional
marker genes an extended standard, the Minimum
Information about a MARKer gene Sequence (MI-
MARKS) checklist (http://gensc.org/gc_wiki/index.
php/MIMARKS) has been developed (Yilmaz et al.,
2011). This family of minimum information check-
lists provides researchers with a condensed set of
contextual data requirements, which range from
description of the environment to sampling and
sequencing procedures. The GSC is also driving the
evolution of omics data sharing in a broader context
through participation in the BioSharing (http://
biosharing.org) portal. This forum aims to enable a
broader dialog among funders, journals, standards
and technology developers, and researchers on the
critical issue of data sharing within the meta-
genomics community and beyond (Field et al., 2009).
It provides an example of what an infrastructure to
support standards-compliant reporting of contextual
data might look like; as well as encouraging and
enabling curation at community level (Rocca-Serra
et al., 2010; http://isatab.sourceforge.net).
The primary sequence databases’ adoption of
these standards is integral to their success. The
INSDC partners have recognized this support for
submission of compliant data sets with the adoption
of an official keyword for the family of minimum
standards reserved for compliant INSDC sequence
records. Additionally, the development of a number
of tools and formats to aid in data exchange
(Kottmann et al., 2008) and compliance during
sequence submissions with these standards is
ongoing within specialized genomics and meta-
genomics resources.
The application of high-throughput sequencing
technologies has transformed the way microbial
ecologists approach questions in their field (Gilbert
et al., 2010b). The shift of sequencing capacity
to individual labs is creating a data bonanza.
With appropriate contextual information, these data
sets could herald a new era of discovery for
microbial ecology. This will only be possible, if
each study, from each environment, and from each
lab maintains, at the very least, a minimum
contextual data standard to facilitate cross-
comparison and meta-analysis of global microbial
communities. Inadequate implementation of these
standards threatens progress in our field of research,
as we will lose the best opportunity to produce a
complete mechanistic understanding of microbial
life. Every investigator will benefit immensely by
being able to obtain a rapid, comprehensive answer
to the question ‘Have my microbes been seen before,
and, if so, where, with whom, and what were they
doing? Only by accepting the relatively small
responsibility of entering their own contextual data
into a global system will they realize this dream.
Just as standardized deposition of sequence data
contributed an immensely valuable resource,
standardization of contextual data will allow us to
reap vast dividends for decades to come and enable
us to finally escape the burden of ‘my sequence
matches 1500 uncultured environmental isolates—
now what’?
To provide a better understanding of the require-
ments, we included three examples for MIGS, MIMS
and MIMARKS compliant data sets in the Supple-
mentary Table 1. Supplementary File 2 provides
links to detailed submission and compliance
guidelines.
Commentary
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With this open letter to the ISME community,
we not only hope to advertise the existence of
the GSC and invite more microbial ecologists
investigating marker genes and doing ‘omics’ work
to join us, but also make a call for compliance with
current and future GSC standards. To learn how to
describe your data according to MIGS/MIMS/
MIMARKS (MIxS) standards, please visit the GSC
website for details and options for submitting
compliant data sets into public domain databases
(http://gensc.org/gc_wiki/index.php/MIGS/MIMS/
MIMARKS).
P Yilmaz is at Microbial Genomics
and Bioinformatics Group,
Max Planck Institute for Marine Microbiology,
Bremen, Germany
P Yilmaz is at Jacobs University Bremen
gGmbH, Bremen, Germany;
JA Gilbert is at Mathematics and Computer Science
Division, Argonne National Laboratory,
Argonne, IL, USA
JA Gilbert is at Department of Ecology and
Evolution, University of Chicago, Chicago, IL, USA;
R Knight is at Howard Hughes Medical Institute
and Department of Chemistry & Biochemistry,
University of Colorado at Boulder,
Boulder, CO, USA;
L Amaral-Zettler is at Josephine Bay Paul Center for
Comparative Molecular Biology and Evolution,
Marine Biological Laboratory, Woods Hole, MA, USA;
I Karsch-Mizrachi is at National Center for
Biotechnology Information, National Library of
Medicine, National Institutes of Health,
Bethesda, MD, USA;
G Cochrane is at EMBL Outstation, The European
Bioinformatics Institute (EBI), Wellcome Trust
Genome Campus, Hinxton, Cambridge, UK;
Y Nakamura is at Center for Information Biology and
DNA Data Bank of Japan, National Institute of
Genetics, Research Organization for Information and
Systems, Yata, Mishima, Japan;
S-A Sansone is at Oxford e-Research Centre,
University of Oxford, Oxford, UK;
FO Glo¨ckner is at Microbial Genomics
and Bioinformatics Group,
Max Planck Institute for Marine Microbiology,
Bremen, Germany
FO Glo¨ckner is at Jacobs University Bremen
gGmbH, Bremen, Germany and
D Field is at NERC Centre for Ecology and Hydrology,
Oxford, UK
E-mail: fog@mpi-bremen.de
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Supplementary Information accompanies the paper on The ISME Journal website (http://www.nature.com/ismej)
Commentary
1567
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