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PMID: 17224063 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't

Prediction of effective genome size in metagenomic samples.

Genome biology ·Vol. 8 ·No. 1 ·2007-00-00 ·Pages R10

Raes J, Korbel JO, Lercher MJ, von Mering C, Bork P

Abstract

We introduce a novel computational approach to predict effective genome size (EGS; a measure that includes multiple plasmid copies, inserted sequences, and associated phages and viruses) from short sequencing reads of environmental genomics (or metagenomics) projects. We observe considerable EGS differences between environments and link this with ecologic complexity as well as species composition (for instance, the presence of eukaryotes). For example, we estimate EGS in a complex, organism-dense farm soil sample at about 6.3 megabases (Mb) whereas that of the bacteria therein is only 4.7 Mb; for bacteria in a nutrient-poor, organism-sparse ocean surface water sample, EGS is as low as 1.6 Mb. The method also permits evaluation of completion status and assembly bias in single-genome sequencing projects.

MeSH Terms
Artifacts Environment Genetic Markers Genome, Bacterial/genetics Genomics/methods Models, Genetic Prokaryotic Cells/metabolism Reproducibility of Results Sequence Analysis, DNA
Chemicals
Genetic Markers
Authors & Affiliations
5 authors, click to expand affiliations / ORCID
Raes Jeroen
European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69117 Heidelberg, Germany. raes@embl.de
Korbel Jan O
Lercher Martin J
von Mering Christian
Bork Peer
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Article Info
Journal
Genome biology
Abbr.
Genome Biol
ISSN
1474-760X
DOI
10.1186/gb-2007-8-1-r10
Email
raes@embl.de
Published
2007-00-00
Pages
R10
Language
English
Region
England
NLM ID
100960660
PMCID
PMC1839125
Subset
IM
External Links
PubMed source DOI: 10.1186/gb-2007-8-1-r10 PMC Full Text View journal details
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