Local variation in recombination rates of the honey bee (Apis mellifera) genome among samples from six disparate populations
Meiotic recombination is an essential component of eukaryotic sexual reproduction, but its frequency varies within and between genomes. Although it is well established that honey bees have a high recombination rate with about 20 cM/Mbp, the proximate and ultimate causes of this exceptional rate are poorly understood. Here, we describe six linkage maps of the western honey bee Apis mellifera that were produced with consistent methodology from samples from distinct parts of the species near global distribution. We compared the genome-wide rates and distribution of meiotic crossovers among the six maps and found considerable differences. Overall similarity of local recombination rates among our samples was unrelated to geographic or phylogenetic distance of the populations that our samples were derived from. However, the limited sampling constrains the interpretation of our results, because it is unclear how representative these samples were. In contrast to previous studies, we found only in two datasets a significant relation between local recombination rate and GC content. Focusing on regions of particularly increased or decreased recombination in specific maps, we identified several enriched gene ontologies in these regions and speculated about their local adaptive relevance. These data are contributing to an increasing comparative effort to gain an understanding of the intra-specific variability of recombination rates and their evolutionary role in honey bees and other social insects.
KeywordsGenome evolution Genetic diversity Meiotic recombination Intra-specific variability Crossover
We would like to thank all instructors and fellow students of the Math-Bio REU-site at UNCG for their support and collegial working atmosphere. We appreciate the opportunity to sample “Russian” colonies from Steven Coy (then President of the Russian Honey Bee Breeders) in Perkinston, Mississippi. We would like to thank Sharon Furiness and the Genomics Core Lab at TAMU Corpus Christi for performing the ddRAD library preparation, SE sequencing, and SNP extraction. Esmaeil Amiri assisted in the data management. We would also like to thank three anonymous reviewers whose comments on a previous version of this manuscript helped us to improve the presentation of our study. Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R15GM102753. Further financial support was provided by the US National Science Foundation (DMS #1359187) and UNCG.
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