Sequenced-based GWAS for linear classification traits in Belgian Blue beef cattle reveals new coding variants in genes regulating body size in mammals

Abstract

Background Cohorts of individuals that have been genotyped and phenotyped for genomic selection programs offer the opportunity to better understand genetic variation associated with complex traits. Here, we performed an association study for traits related to body size and muscular development in intensively selected beef cattle. We leveraged multiple trait information to refine and interpret the significant associations. Results After a multiple-step genotype imputation to the sequence-level for 14,762 Belgian Blue beef (BBB) cows, we performed a genome-wide association study (GWAS) for 11 traits related to muscular development and body size. The 37 identified genome-wide significant quantitative trait loci (QTL) could be condensed in 11 unique QTL regions based on their position. Evidence for pleiotropic effects was found in most of these regions (e.g., correlated association signals, overlap between credible sets (CS) of candidate variants). Thus, we applied a multiple-trait approach to combine information from different traits to refine the CS. In several QTL regions, we identified strong candidate genes known to be related to growth and height in other species such as LCORL-NCAPG or CCND2. For some of these genes, relevant candidate variants were identified in the CS, including three new missense variants in EZH2, PAPPA2 and ADAM12, possibly two additional coding variants in LCORL, and candidate regulatory variants linked to CCND2 and ARMC12. Strikingly, four other QTL regions associated with dimension or muscular development traits were related to five (recessive) deleterious coding variants previously identified. Conclusions Our study further supports that a set of common genes controls body size across mammalian species. In particular, we added new genes to the list of those associated with height in both humans and cattle. We also identified new strong candidate causal variants in some of these genes, strengthening the evidence of their causality. Several breed-specific recessive deleterious variants were identified in our QTL regions, probably as a result of the extreme selection for muscular development in BBB cattle.

Inbreeding depression is associated with recent homozygous-by-descent segments in Belgian Blue beef cattle

“…We performed our study with the data used by Gualdrón Duarte et al [ 23 ]. Briefly, the data consisted in a cohort of 14,762 Belgian Blue beef cows genotyped for a set of 28,858 single nucleotide polymorphisms (SNPs), after filtering for call rate (> 0.95), Hardy–Weinberg equilibrium (p > 0.001) and MAF (> 0.01).…”

“…To address the second potential issue, we took advantage of the available imputed genotypes for 572,667 SNPs from the Illumina BovineHD array (from the study from Gualdrón Duarte et al [ 23 ]). This represents a 20-fold increase in marker density and should allow more accurate estimation of HBD proportions in different classes, particularly for those with higher rates.…”

GWAS reveals determinants of mobilization rate and dynamics of an active endogenous retrovirus of cattle

“…number of alleles with the ERVK[2-1-LTR] insertion) was added as an extra covariate in the model. Linkage disequilibrium in the Belgian Blue population results in the fact that the ~11 million variants behave as ~ 500,000 independent tests 44 , yielding a genome-wide significance threshold of 0.05/500,000 = 10 −7 .…”

Evaluation of heritability partitioning approaches in livestock populations

“…For the present study we used data from 14,762 Belgian Blue beef cows with imputed genotypes from 11,537,240 SNPs and small indels [ 23 ]. Cows were genotyped with either low-density (9983 to 20,502 SNPs) or medium-density (51,809 to 57,979 SNPs) arrays and genotype imputation to the sequence level was performed in successive steps.…”

“…Variants with low minor allele frequency (MAF) (< 0.01) or with lower imputation accuracy (r 2 < 0.90) were filtered out, resulting in the selection of 11,431,742 variants. More details on the imputation procedure and the data set can be found in Gualdrón Duarte et al [ 23 ]. We used phenotypes for muscularity traits (shoulder muscularity, top muscularity, buttock muscularity rear and side view) and height (with heritabilities of 0.30, 0.31, 0.42, 0.39 and 0.38, respectively).…”