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A Novel Computational Method Identifies Intra- and Inter-Species Recombination Events in Staphylococcus aureus and Streptococcus pneumoniae

Overview of attention for article published in PLoS Computational Biology, September 2012
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Title
A Novel Computational Method Identifies Intra- and Inter-Species Recombination Events in Staphylococcus aureus and Streptococcus pneumoniae
Published in
PLoS Computational Biology, September 2012
DOI 10.1371/journal.pcbi.1002668
Pubmed ID
Authors

Lisa Sanguinetti, Simona Toti, Valerio Reguzzi, Fabio Bagnoli, Claudio Donati

Abstract

Advances in high-throughput DNA sequencing technologies have determined an explosion in the number of sequenced bacterial genomes. Comparative sequence analysis frequently reveals evidences of homologous recombination occurring with different mechanisms and rates in different species, but the large-scale use of computational methods to identify recombination events is hampered by their high computational costs. Here, we propose a new method to identify recombination events in large datasets of whole genome sequences. Using a filtering procedure of the gene conservation profiles of a test genome against a panel of strains, this algorithm identifies sets of contiguous genes acquired by homologous recombination. The locations of the recombination breakpoints are determined using a statistical test that is able to account for the differences in the natural rate of evolution between different genes. The algorithm was tested on a dataset of 75 genomes of Staphylococcus aureus and 50 genomes comprising different streptococcal species, and was able to detect intra-species recombination events in S. aureus and in Streptococcus pneumoniae. Furthermore, we found evidences of an inter-species exchange of genetic material between S. pneumoniae and Streptococcus mitis, a closely related commensal species that colonizes the same ecological niche. The method has been implemented in an R package, Reco, which is freely available from supplementary material, and provides a rapid screening tool to investigate recombination on a genome-wide scale from sequence data.

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Geographical breakdown

Country Count As %
United States 3 5%
Sweden 2 3%
Portugal 1 2%
France 1 2%
Kenya 1 2%
Denmark 1 2%
India 1 2%
Unknown 53 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 37%
Student > Ph. D. Student 15 24%
Student > Postgraduate 4 6%
Student > Master 4 6%
Other 3 5%
Other 11 17%
Unknown 3 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 32 51%
Biochemistry, Genetics and Molecular Biology 5 8%
Computer Science 4 6%
Immunology and Microbiology 4 6%
Medicine and Dentistry 3 5%
Other 6 10%
Unknown 9 14%