Phylogeographic variation in recombination rates within a global clone of methicillin-resistant Staphylococcus aureus

BACKGROUND: Next-generation sequencing (NGS) is a powerful tool for understanding both patterns of descent over time and space (phylogeography) and the molecular processes underpinning genome divergence in pathogenic bacteria. Here, we describe a synthesis between these perspectives by employing a r...

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Published in:Genome biology 2012-01, Vol.13 (12), p.R126-R126
Main Authors: Castillo-Ramírez, Santiago, Corander, Jukka, Marttinen, Pekka, Aldeljawi, Mona, Hanage, William P, Westh, Henrik, Boye, Kit, Gulay, Zeynep, Bentley, Stephen D, Parkhill, Julian, Holden, Matthew T, Feil, Edward J
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Language:eng
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Summary:BACKGROUND: Next-generation sequencing (NGS) is a powerful tool for understanding both patterns of descent over time and space (phylogeography) and the molecular processes underpinning genome divergence in pathogenic bacteria. Here, we describe a synthesis between these perspectives by employing a recently developed Bayesian approach, BRATNextGen, for detecting recombination on an expanded NGS dataset of the globally disseminated methicillin-resistant Staphylococcus aureus (MRSA) clone ST239. RESULTS: The data confirm strong geographical clustering at continental, national and city scales and demonstrate that the rate of recombination varies significantly between phylogeographic sub-groups representing independent introductions from Europe. These differences are most striking when mobile non-core genes are included, but remain apparent even when only considering the stable core genome. The monophyletic ST239 sub-group corresponding to isolates from South America shows heightened recombination, the sub-group predominantly from Asia shows an intermediate level, and a very low level of recombination is noted in a third sub-group representing a large collection from Turkey. CONCLUSIONS: We show that the rapid global dissemination of a single pathogenic bacterial clone results in local variation in measured recombination rates. Possible explanatory variables include the size and time since emergence of each defined sub-population (as determined by the sampling frame), variation in transmission dynamics due to host movement, and changes in the bacterial genome affecting the propensity for recombination.
ISSN:1465-6906
1465-6914
1474-760X