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. 2019 Oct;29(10):1744-1752.
doi: 10.1101/gr.243311.118. Epub 2019 Aug 21.

Exploration of fine-scale recombination rate variation in the domestic horse

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Exploration of fine-scale recombination rate variation in the domestic horse

Samantha K Beeson et al. Genome Res. 2019 Oct.

Abstract

Total genetic map length and local recombination landscapes typically vary within and across populations. As a first step to understanding the recombination landscape in the domestic horse, we calculated population recombination rates and identified likely recombination hotspots using approximately 1.8 million SNP genotypes for 485 horses from 32 distinct breeds. The resulting breed-averaged recombination map spans 2.36 Gb and accounts for 2939.07 cM. Recombination hotspots occur once per 23.8 Mb on average and account for ∼9% of the physical map length. Regions with elevated recombination rates in the entire cohort were enriched for genes in pathways involving interaction with the environment: immune system processes (specifically, MHC class I and class II genes), responses to stimuli, and serotonin receptor pathways. We found significant correlations between differences in local recombination rates and population differentiation quantified by F ST Analysis of breed-specific maps revealed thousands of hotspot regions unique to particular breeds, as well as unique "coldspots," regions where a particular breed showed below-average recombination, whereas all other breeds had evidence of a hotspot. Finally, we identified relative enrichment (P = 5.88 × 10-27) for the in silico-predicted recognition motif for equine PR/SET domain 9 (PRDM9) in recombination hotspots. These results indicate that selective pressures and PRDM9 function contribute to variation in recombination rates across the domestic horse genome.

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Figures

Figure 1.
Figure 1.
Recombination rate distribution. (A) Proportion of total recombination versus proportion of sequence covered, sorted by highest inter-recombination rate estimates. (B) Recombination rate as a function of distance from the nearest start codon in 1-kb bins.
Figure 2.
Figure 2.
Recombination rates across ECA20 with zoom window including predicted hotspots and protein-coding genes located in the region spanning the MHC class I and MHC class II loci.
Figure 3.
Figure 3.
Zinc finger array for the equine reference PRDM9 protein (top) and corresponding in silico–predicted 31-mer DNA recognition sequence (bottom). Each colored box represents a single zinc finger, with distinct zinc fingers represented in different colors. Letters within the boxes signify DNA-contacting amino acids at the −1, 2, 3, and 6 positions. Dotted lines lead to the portion of the DNA sequence motif recognized by each zinc finger.
Figure 4.
Figure 4.
Fine-scale recombination rate variation on ECA7. (A) Recombination rate variation along ECA7 in five breeds. (B) Pairwise FST versus recombination dissimilarity (1 − Spearman's rank correlation coefficient) across ECA7.

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