Chromosomal inversions associated with environmental adaptation in honeybees.

Christmas MJ, Wallberg A, Bunikis I, Olsson A, Wallerman O, Webster MT

Mol. Ecol. 28 (6) 1358-1374 [2019-03-00; online 2018-12-21]

Chromosomal inversions can facilitate local adaptation in the presence of gene flow by suppressing recombination between well-adapted native haplotypes and poorly adapted migrant haplotypes. East African mountain populations of the honeybee Apis mellifera are highly divergent from neighbouring lowland populations at two extended regions in the genome, despite high similarity in the rest of the genome, suggesting that these genomic regions harbour inversions governing local adaptation. Here, we utilize a new highly contiguous assembly of the honeybee genome to characterize these regions. Using whole-genome sequencing data from 55 highland and lowland bees, we find that the highland haplotypes at both regions are present at high frequencies in three independent highland populations but extremely rare elsewhere. The boundaries of both divergent regions are characterized by regions of high homology with each other positioned in opposite orientations and contain highly repetitive, long inverted repeats with homology to transposable elements. These regions are likely to represent inversion breakpoints that participate in nonallelic homologous recombination. Using long-read data, we confirm that the lowland samples are contiguous across breakpoint regions. We do not find evidence for disruption of functional sequence by these breakpoints, which suggests that the inversions are likely maintained due to their allelic content conferring local adaptation in highland environments. Finally, we identify a third divergent genomic region, which contains highly divergent segregating haplotypes that also may contain inversion variants under selection. The results add to a growing body of evidence indicating the importance of chromosomal inversions in local adaptation.

Bioinformatics Compute and Storage [Service]

NGI Uppsala (Uppsala Genome Center) [Collaborative]

National Genomics Infrastructure [Collaborative]

PubMed 30431193

DOI 10.1111/mec.14944

Crossref 10.1111/mec.14944