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Genome-Wide Detection of Spontaneous Chromosomal Rearrangements in Bacteria

Overview of attention for article published in PLOS ONE, August 2012
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Title
Genome-Wide Detection of Spontaneous Chromosomal Rearrangements in Bacteria
Published in
PLOS ONE, August 2012
DOI 10.1371/journal.pone.0042639
Pubmed ID
Authors

Song Sun, Rongqin Ke, Diarmaid Hughes, Mats Nilsson, Dan I. Andersson

Abstract

Genome rearrangements have important effects on bacterial phenotypes and influence the evolution of bacterial genomes. Conventional strategies for characterizing rearrangements in bacterial genomes rely on comparisons of sequenced genomes from related species. However, the spectra of spontaneous rearrangements in supposedly homogenous and clonal bacterial populations are still poorly characterized. Here we used 454 pyrosequencing technology and a 'split mapping' computational method to identify unique junction sequences caused by spontaneous genome rearrangements in chemostat cultures of Salmonella enterica Var. Typhimurium LT2. We confirmed 22 unique junction sequences with a junction microhomology more than 10 bp and this led to an estimation of 51 true junction sequences, of which 28, 12 and 11 were likely to be formed by deletion, duplication and inversion events, respectively. All experimentally confirmed rearrangements had short inverted (inversions) or direct (deletions and duplications) homologous repeat sequences at the endpoints. This study demonstrates the feasibility of genome wide characterization of spontaneous genome rearrangements in bacteria and the very high steady-state frequency (20-40%) of rearrangements in bacterial populations.

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The data shown below were compiled from readership statistics for 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
France 1 1%
Australia 1 1%
Sweden 1 1%
Russia 1 1%
United States 1 1%
Unknown 84 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 27%
Researcher 24 27%
Student > Master 9 10%
Student > Bachelor 5 6%
Professor 4 4%
Other 12 13%
Unknown 12 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 49%
Biochemistry, Genetics and Molecular Biology 20 22%
Veterinary Science and Veterinary Medicine 2 2%
Mathematics 2 2%
Immunology and Microbiology 2 2%
Other 5 6%
Unknown 15 17%