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Inferring genomic flux in bacteria
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Didelot, Xavier, Darling, Aaron and Falush, Daniel (2009) Inferring genomic flux in bacteria. Genome Research, Vol.19 (No.2). pp. 306-317. doi:10.1101/gr.082263.108 ISSN 1088-9051.
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Official URL: http://dx.doi.org/10.1101/gr.082263.108
Abstract
Acquisition and loss of genetic material are essential forces in bacterial microevolution. They have been repeatedly linked with adaptation of lineages to new lifestyles, and in particular, pathogenicity. Comparative genomics has the potential to elucidate this genetic flux, but there are many methodological challenges involved in inferring evolutionary events from collections of genome sequences. Here we describe a model-based method for using whole-genome sequences to infer the patterns of genome content evolution. A fundamental property of our model is that it allows the rates at which genetic elements are gained or lost to vary in time and from one lineage to another. Our approach is purely sequence based, and does not rely on gene identification. We show how inference can be performed under our model and illustrate its use on three datasets from Francisella tularensis, Streptococcus pyogenes, and Escherichia coli. In all three examples, we found interesting variations in the rates of genetic material gain and loss, which strongly correlate with their lifestyle. The algorithms we describe are implemented in a computer software named GenoPlast.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QD Chemistry T Technology > TP Chemical technology Q Science > QH Natural history > QH426 Genetics |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Journal or Publication Title: | Genome Research | ||||
Publisher: | Cold Spring Harbor Lab Press | ||||
ISSN: | 1088-9051 | ||||
Official Date: | February 2009 | ||||
Dates: |
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Volume: | Vol.19 | ||||
Number: | No.2 | ||||
Number of Pages: | 12 | ||||
Page Range: | pp. 306-317 | ||||
DOI: | 10.1101/gr.082263.108 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Funder: | Wellcome Trust, Centre for Research in Statistical Methodology (CRiSM), NSF, Science Foundation of Ireland | ||||
Grant number: | WT082930MA, DBI-063075, 05/FE1/B882 |
Data sourced from Thomson Reuters' Web of Knowledge
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