Title |
Prediction of effective genome size in metagenomic samples
|
---|---|
Published in |
Genome Biology, January 2007
|
DOI | 10.1186/gb-2007-8-1-r10 |
Pubmed ID | |
Authors |
Jeroen Raes, Jan O Korbel, Martin J Lercher, Christian von Mering, Peer Bork |
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. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 16 | 4% |
France | 6 | 1% |
Germany | 5 | 1% |
Brazil | 4 | <1% |
United Kingdom | 3 | <1% |
Sweden | 3 | <1% |
Netherlands | 2 | <1% |
South Africa | 2 | <1% |
Poland | 2 | <1% |
Other | 14 | 3% |
Unknown | 389 | 87% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 123 | 28% |
Researcher | 110 | 25% |
Student > Master | 47 | 11% |
Student > Doctoral Student | 29 | 7% |
Student > Bachelor | 27 | 6% |
Other | 73 | 16% |
Unknown | 37 | 8% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 249 | 56% |
Biochemistry, Genetics and Molecular Biology | 45 | 10% |
Environmental Science | 32 | 7% |
Computer Science | 21 | 5% |
Immunology and Microbiology | 14 | 3% |
Other | 38 | 9% |
Unknown | 47 | 11% |