Method

Prediction of effective genome size in metagenomic samples

Jeroen Raes^{* 1} , Jan O Korbel^{* 1,2} , Martin J Lercher¹ , Christian von Mering^1,3 and Peer Bork¹

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

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

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

author email corresponding author email* Contributed equally

Genome Biology 2007, 8:R10doi:10.1186/gb-2007-8-1-r10

Published:	15 January 2007

Subject areas: Genome studies, Bioinformatics, Microbiology and parasitology

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.