Selection in action: dissecting the molecular underpinnings of the increasing muscle mass of Belgian Blue Cattle

Abstract

BackgroundBelgian Blue cattle are famous for their exceptional muscular development or “double-muscling”. This defining feature emerged following the fixation of a loss-of-function variant in the myostatin gene in the eighties. Since then, sustained selection has further increased muscle mass of Belgian Blue animals to a comparable extent. In the present paper, we study the genetic determinants of this second wave of muscle growth.ResultsA scan for selective sweeps did not reveal the recent fixation of another allele with major effect on muscularity. However, a genome-wide association study identified two genome-wide significant and three suggestive quantitative trait loci (QTL) affecting specific muscle groups and jointly explaining 8-21% of the heritability. The top two QTL are caused by presumably recent mutations on unique haplotypes that have rapidly risen in frequency in the population. While one appears on its way to fixation, the ascent of the other is compromised as the likely underlying MRC2 mutation causes crooked tail syndrome in homozygotes. Genomic prediction models indicate that the residual additive variance is largely polygenic.ConclusionsContrary to complex traits in humans which have a near-exclusive polygenic architecture, muscle mass in beef cattle (as other production traits under directional selection), appears to be controlled by (i) a handful of recent mutations with large effect that rapidly sweep through the population, and (ii) a large number of presumably older variants with very small effects that rise slowly in the population (polygenic adaptation).Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-796) contains supplementary material, which is available to authorized users.

Coding and noncoding variants in HFM1, MLH3, MSH4, MSH5, RNF212, and RNF212B affect recombination rate in cattle

“…These findings are at odds with the now prevalent view that most complex traits, including morphometric and physiological traits (e.g., height and reproductive aging), as well as common diseases in humans (Finucane et al 2015) and phenotypic variation in domestic animals (Andersson 2008) are highly polygenic and primarily determined by large numbers of common variants that individually explain <1% of the genetic variance and only contain a minority of missense variants (hence, most bound to be regulatory variants) (Flint and Mackay 2009;Yang et al 2010). In agreement with Kemper and Goddard (2012), we have previously shown that at least some production traits under intense directional selection (e.g., muscularity) involve a handful of young alleles with large effects that are sweeping through the population, in addition to a tail of many small "polygenic" effects (Druet et al 2014). Directional selection is unlikely to be the explanation for the segregation of variants with large effects on GRR, as the effects of the derived allele are equally balanced between positive and negative effects (Table 2).…”

The Valdostana goat: a genome-wide investigation of the distinctiveness of its selective sweep regions

“…Several approaches have been used to detect these regions, such as run of homozygosity (ROH;Zhao et al 2012;Fleming et al 2016), fixation index analysis (Fst; Kijas et al 2012;Porto-Neto et al 2013), and haplotypebased analyses (e.g., de Simoni Gouveia et al 2014). Other approaches, such as Bayesian methods, have also been successfully used on some occasions to detect selective sweeps as well (e.g., Druet et al 2014).…”

How old are quantitative trait loci and how widely do they segregate?

“…Our conclusion is that the variants detected here are younger than SNPs on commercial assays, many of which segregate in B. indicus as well as in B. taurus, but older than mutations causing monogenic disorders. For example, double-muscling mutations typically segregate only within one breed or closely related breeds and are relatively young (approximately 50 generations) (O'Rourke et al 2012;Druet et al 2014).…”