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Inference of recombination maps from a single pair of genomes and its application to ancient samples

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Barroso,  Gustavo
IMPRS for Evolutionary Biology, Max Planck Institute for Evolutionary Biology, Max Planck Society;
Research Group Molecular Systems Evolution, Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Puzović,  Nataša
Research Group Molecular Systems Evolution, Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Dutheil,  Julien Y.
Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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journal.pgen.1008449.pdf
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Citation

Barroso, G., Puzović, N., & Dutheil, J. Y. (2019). Inference of recombination maps from a single pair of genomes and its application to ancient samples. PLoS Genetics, 15(11): e1008449. doi:10.1371/journal.pgen.1008449.


Cite as: http://hdl.handle.net/21.11116/0000-0006-3E4F-E
Abstract
Author summary In sexually-reproducing species, meiotic recombination causes the genome of each individual to be a mosaic of DNA sequences that existed in its ancestral population. As a result, genealogical ancestry changes along the genome and shapes genetic diversity. The importance of recombination in genome evolution has motivated a surge in the development of statistical tools to infer genome-wide variation in the recombination rate using polymorphism data. For the most part, however, these methods rely on relatively large sample sizes. Here, we introduce iSMC–a new tool that infers recombination maps while simultaneously modelling the demographic history. A critical improvement over existing methods is that iSMC has high accuracy using as little as a single diploid genome. Using experimentally derived recombination maps from fruit-flies and a fungal pathogen, we demonstrate that iSMC compares well to state-of-the-art methods that require larger sample sizes. We further analyse data from ancient hominins, showcasing that our method can extract information in intrinsically limited datasets. These results suggest that iSMC is a valuable tool that can foster studies in non-model organisms. Moreover, its joint-inference approach of demography and the recombination landscape represents a step towards more realistic models in population genomics.