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Reconstructing past changes in locus-specific recombination rates


Cox, MP and Holland, BR and Wilkins, MC and Schmid, J, Reconstructing past changes in locus-specific recombination rates, BMC Genetics, 14 Article 11. ISSN 1471-2156 (2013) [Refereed Article]


Copyright Statement

Licensed under Creative Commons Attribution 2.0 Generic (CC BY 2.0)

DOI: doi:10.1186/1471-2156-14-11


Background: Recombination rates vary at the level of the species, population and individual. Now recognized as a transient feature of the genome, recombination rates at a given locus can change markedly over time. Existing inferential methods, predominantly based on linkage disequilibrium patterns, return a long-term average estimate of past recombination rates. Such estimates can be misleading, but no analytical framework to infer recombination rates that have changed over time is currently available.

Results: We apply coalescent modeling in conjunction with a suite of summary statistics to show that the recombination history of a locus can be reconstructed from a time series of genetic samples. More usefully, we describe a new method, based on n-tuple dataset subsampling, to infer past changes in recombination rate from DNA sequences taken at a single time point. This subsampling strategy can correctly assign simulated loci to constant, increasing and decreasing recombination models with an accuracy of 84%.

Conclusions: While providing an important stepping-stone to determining past recombination rates, n-tuple subsampling still exhibits a moderate error rate. Theoretical limitations indicated by coalescent theory suggest that highly accurate inference of past recombination rates will remain challenging. Nevertheless, we show for the first time that reconstructing historic recombination rates is possible in principle.

Item Details

Item Type:Refereed Article
Keywords:life sciences, animal genetics and genomics, microbial genetics and genomics, plant genetics and genomics, genetics and population dynamics
Research Division:Mathematical Sciences
Research Group:Applied mathematics
Research Field:Biological mathematics
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the mathematical sciences
UTAS Author:Holland, BR (Professor Barbara Holland)
ID Code:84542
Year Published:2013
Funding Support:Australian Research Council (FT100100031)
Web of Science® Times Cited:4
Deposited By:Mathematics and Physics
Deposited On:2013-05-17
Last Modified:2018-01-31
Downloads:358 View Download Statistics

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