Functional Partitioning of Genomic Variance and Genome-Wide Association Study for Carcass Traits in Korean Hanwoo Cattle Using Imputed Sequence Level SNP Data

Abstract

Quantitative traits are usually controlled by numerous genomic variants with small individual effects, and variances associated with those traits are explained in a continuous manner. However, the relative contributions of genomic regions to observed genetic variations have not been well explored using sequence level single nucleotide polymorphism (SNP) information. Here, imputed sequence level SNP data (11,278,153 SNPs) of 2109 Hanwoo steers (Korean native cattle) were partitioned according to functional annotation, chromosome, and minor allele frequency (MAF). Genomic relationship matrices (GRMs) were constructed for each classified region and fitted in the model both separately and together for carcass weight (CWT), eye muscle area (EMA), backfat thickness (BFT), and marbling score (MS) traits. A genome-wide association study (GWAS) was performed to identify significantly associated variants in genic and exon regions using a linear mixed model, and the genetic contribution of each exonic SNP was determined using a Bayesian mixture model. Considering all SNPs together, the heritability estimates for CWT, EMA, BFT, and MS were 0.57 ± 0.05, 0.46 ± 0.05, 0.45 ± 0.05, and 0.49 ± 0.05, respectively, which reflected substantial genomic contributions. Joint analysis revealed that the variance explained by each chromosome was proportional to its physical length with weak linear relationships for all traits. Moreover, genomic variances explained by functional category and MAF class differed greatly among the traits studied in joint analysis. For example, exon regions had larger contributions for BFT (0.13 ± 0.08) and MS (0.22 ± 0.08), whereas intron and intergenic regions explained most of the total genomic variances for CWT and EMA (0.22 ± 0.09–0.32 ± 0.11). Considering different functional classes of exon regions and the per SNP contribution revealed the largest proportion of genetic variance was attributable to synonymous variants. GWAS detected 206 and 27 SNPs in genic and exon regions, respectively, on BTA4, BTA6, and BTA14 that were significantly associated with CWT and EMA. These SNPs were harbored by 31 candidate genes, among which TOX, FAM184B, PPARGC1A, PRKDC, LCORL, and COL1A2 were noteworthy. BayesR analysis found that most SNPs (>93%) had very small effects and the 4.02–6.92% that had larger effects (10-4 × σA2, 10-3 × σA2, and 10-2 × σA2) explained most of the total genetic variance, confirming polygenic components of the traits studied.

A Gene-Set Enrichment and Protein–Protein Interaction Network-Based GWAS with Regulatory SNPs Identifies Candidate Genes and Pathways Associated with Carcass Traits in Hanwoo Cattle

“…The significantly associated SNPs for The proportions of genomic variance attributed to the regulatory SNPs were found to be 0.29, 0.25, 0.29, and 0.38 for BFT, CWT, EMA, and MS, respectively (Table 1). This is between 44% and 77% of the heritability estimated in a previous study using 11.2 million SNPs from across the genome of Hanwoo [1], suggesting that the regulatory SNPs might have a large effect on the traits evaluated in this study. This is consistent with previous reports that had reported that the missense variants (non-synonymous variants) are able to capture a large proportion of the genetic variance in beef and dairy cattle [12,57].…”

“…The genotypes were then phased using Eagle v.2.3.2 [30] and then imputed, one chromosome at a time, using Minimac3 [31], to a high-density level, using a reference population consisting of 480 animals genotyped with Bovine HD BeadChip (777,962 SNPs). They were then imputed to the sequence level one chromosome at a time, using whole genome sequence data of a reference population of 311 progeny tested Hanwoo bulls [1], resulting in a total of 27,980,473 SNPs; the imputation pipeline followed for imputing from 770K to the sequence level was the same as the one used for 50K to HD imputation. Following a previous study [32], only SNPs with Minimac3 imputation quality statistic (R 2 ) higher than 0.4 were retained for further analysis, resulting in a total of 12,980,473 SNPs.…”

“…A genome-wide association study (GWAS) was performed using a mixed linear model implemented in GCTA v.1.91.4 beta3 [39]. Farm (1419), birth year (2006-2016), birth month (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12), slaughter year (2008-2018), slaughter month (1-12), age (17-62 months), slaughter place (53), sire (324), and dam (8331) were tested for fixed effects. Fixed effects that were significant for all the traits were fitted in the model; this included farm, birth year, slaughter year, slaughter place, age, and sire.…”

“…Hanwoo (Bos taurus coreanae) is the indigenous premium beef cattle of South Korea. It has been intensively selected for higher meat and carcass quality for the last four decades [1]. It is well known for its extensive marbling, texture, flavor, and juiciness, making it the most economically important species in Korea [2,3].…”

“…GWASs in livestock, including in Hanwoo [8][9][10][11], have resulted in remarkable insights into the genetic architecture of carcass traits. Genetic variation in complex traits such as carcass and meat quality traits are, however, due to the contribution of many mutations with small effects [1,12] (polygenic effect). Though some of these mutations have been successfully identified through GWASs, the high significance thresholds required to correct for the multiple testing problem results in the identification of only SNPs with a large effect size [7,12].…”