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Prediction of effective genome size in metagenomic samples

Jeroen Raes1, Jan O Korbel12, Martin J Lercher1, Christian von Mering13 and Peer Bork1*

  • * Corresponding author: Peer Bork

  • † Equal contributors

Author Affiliations

1 European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69117 Heidelberg, Germany

2 Molecular Biophysics & Biochemistry Department, Yale University, Whitney Avenue, New Haven, Connecticut, USA

3 Institute of Molecular Biology, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland

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Genome Biology 2007, 8:R10  doi:10.1186/gb-2007-8-1-r10

Published: 15 January 2007


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.