title: 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.
authors.affiliation: European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69117 Heidelberg, Germany. raes@embl.de
authors.forename: Jeroen
authors.initials: J
authors.lastname: Raes
authors.forename: Jan O
authors.initials: JO
authors.lastname: Korbel
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Lercher
authors.forename: Christian
authors.initials: C
authors.lastname: von Mering
authors.forename: Peer
authors.initials: P
authors.lastname: Bork
mesh_terms: D016477:Artifacts; D004777:Environment; D005819:Genetic Markers; D016680:Genome, Bacterial / Q000235:genetics*; D023281:Genomics / Q000379:methods*; D008957:Models, Genetic; D011387:Prokaryotic Cells / Q000378:metabolism; D015203:Reproducibility of Results; D017422:Sequence Analysis, DNA
chemical_list: D005819:Genetic Markers