title: Bayesian inference of shared recombination hotspots between humans and chimpanzees.
abstract: Recombination generates variation and facilitates evolution. Recombination (or lack thereof) also contributes to human genetic disease. Methods for mapping genes influencing complex genetic diseases via association rely on linkage disequilibrium (LD) in human populations, which is influenced by rates of recombination across the genome. Comparative population genomic analyses of recombination using related primate species can identify factors influencing rates of recombination in humans. Such studies can indicate how variable hotspots for recombination may be both among individuals (or populations) and over evolutionary timescales. Previous studies have suggested that locations of recombination hotspots are not conserved between humans and chimpanzees. We made use of the data sets from recent resequencing projects and applied a Bayesian method for identifying hotspots and estimating recombination rates. We also reanalyzed SNP data sets for regions with known hotspots in humans using samples from the human and chimpanzee. The Bayes factors (BF) of shared recombination hotspots between human and chimpanzee across regions were obtained. Based on the analysis of the aligned regions of human chromosome 21, locations where the two species show evidence of shared recombination hotspots (with high BFs) were identified. Interestingly, previous comparative studies of human and chimpanzee that focused on the known human recombination hotspots within the β-globin and HLA regions did not find overlapping of hotspots. Our results show high BFs of shared hotspots at locations within both regions, and the estimated locations of shared hotspots overlap with the locations of human recombination hotspots obtained from sperm-typing studies.
authors.affiliation: Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Department of Evolution and Ecology, University of California, Davis, California 95616 brannala@ucdavis.edu.
authors.forename: Bruce
authors.identifier: http://orcid.org/0000-0002-8355-9955
authors.initials: B
authors.lastname: Rannala
mesh_terms: D000465:Algorithms; D000818:Animals; D001499:Bayes Theorem; D002891:Chromosomes, Human, Pair 21; D019295:Computational Biology; D003198:Computer Simulation; D005828:Genetics, Population; D016678:Genome; D015894:Genome, Human; D023281:Genomics; D006649:Histocompatibility Antigens / Q000235:genetics; D006801:Humans; D008957:Models, Genetic; D002679:Pan troglodytes / Q000235:genetics*; D011110:Polymorphism, Genetic; D011995:Recombination, Genetic; D055544:beta-Globins / Q000235:genetics
chemical_list: D006649:Histocompatibility Antigens; D055544:beta-Globins
keywords: Bayes factor; Markov chain Monte Carlo; comparative genomics; recombination hotspots