ArticleGenetics, selection, evolution : GSE2026
A comparative study on recombination activity in cattle.
Article in Genetics, selection, evolution : GSE, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
backgroundGenetic diversity among cattle breeds exists due to their demographic history and different breeding objectives for meat, dairy or dual purpose. Taking this into account, targeted breeding strategies can be further enhanced by employing breed-specific genetic maps. The aim of this study was to derive genetic maps (also known as linkage maps) for a selection of commercial breeds.
resultsWe analysed genotype data from six cattle breeds with sample size ranging from 4,181 to 76,875. Several different assays were used for genotyping, resulting in a high proportion of systematically missing data. Thus, we streamlined the data preparation and analysed the data with three different approaches. We investigated the frequency of paternal and maternal recombination events and derived genetic-map coordinates of about 50K SNP markers. Estimates of male map length varied from 26.97 to 29.83 M between breeds, whereas length of female maps ranged from 23.32 to 26.08 M. Female recombination activity and female genetic maps were clearly distinct from the outcome in males. In particular, male maps of Brown Swiss, Simmental and Angus clustered separately from other male maps and female maps of dairy breeds were distinct from female maps of dual-purpose breeds. Furthermore, a genomewide association study on mean autosomal crossover count and intra-chromosomal allelic shuffling per parent revealed two chromosomal regions on BTA6 and BTA10 with strong evidence found in Brown Swiss and Swiss Holstein; another suggestive signal was detected on BTA10. These regions were in close proximity to genes with known impact on recombination activity.
conclusionBreed-specific female maps could be clearly differentiated from male maps. Though female maps clustered together depending on breed purpose, this was not the case for male maps. All results on empirical data were implemented in the updated version of the R Shiny app CLARITY v3.0.0. This resource can contribute to several instances of genomic evaluations - from improving haplotype phasing to implementing novel breeding strategies.
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