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Prediction of effective genome size in metagenomic samples.


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.

SUBMITTER: Raes J 

PROVIDER: S-EPMC1839125 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature

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Prediction of effective genome size in metagenomic samples.

Raes Jeroen J   Korbel Jan O JO   Lercher Martin J MJ   von Mering Christian C   Bork Peer P  

Genome biology 20070101 1


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-dens  ...[more]

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