ArticleBMC genetics2013
Reconstructing past changes in locus-specific recombination rates.
Article in BMC genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Genome-based prediction of recombination within and between plant species: insights from Brassica oleracea recombinant populations and an interspecific tomato cross (Solanum lycopersicum × S. pimpinellifolium).BMC plant biology · 2026Article
- Last hope for the doomed? Thoughts on the importance of a parasexual cycle for the yeast Candida albicans.Current genetics · 2016Review
- Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundRecombination 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.
resultsWe 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%.
conclusionsWhile 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.
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