Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta, Canada.
Hendrix Genetics Research, Technology & Services B.V., Boxmeer, the Netherlands.
J Anim Breed Genet. 2023 Jul;140(4):413-430. doi: 10.1111/jbg.12768. Epub 2023 Mar 7.
Fat depth (FD) and muscle depth (MD) are economically important traits and used to estimate carcass lean content (LMP), which is one of the main breeding objectives in pig breeding programmes. We assessed the genetic architectures of body composition traits for additive and dominance effects in commercial crossbred Piétrain pigs using both 50 K array and sequence genotypes. We first performed a genome-wide association study (GWAS) using single-marker association analysis with a false discovery rate of 0.1. Then, we estimated the additive and dominance effects of the most significant variant in the quantitative trait loci (QTL) regions. It was investigated whether the use of whole-genome sequence (WGS) will improve the QTL detection (both additive and dominance) with a higher power compared with lower density SNP arrays. Our results showed that more QTL regions were detected by WGS compared with 50 K array (n = 54 vs. n = 17). Of the novel associated regions associated with FD and LMP and detected by WGS, the most pronounced peak was on SSC13, situated at ~116-118, 121-127 and 129-134 Mbp. Additionally, we found that only additive effects contributed to the genetic architecture of the analysed traits and no significant dominance effects were found for the tested SNPs at QTL regions, regardless of panel density. The associated SNPs are located in or near several relevant candidate genes. Of these genes, GABRR2, GALR1, RNGTT, CDH20 and MC4R have been previously reported as being associated with fat deposition traits. However, the genes on SSC1 (ZNF292, ORC3, CNR1, SRSF12, MDN1, TSHZ1, RELCH and RNF152) and SSC18 (TTC26 and KIAA1549) have not been reported previously to our best knowledge. Our current findings provide insights into the genomic regions influencing composition traits in Piétrain pigs.
脂肪厚度(FD)和肌肉深度(MD)是经济上重要的性状,用于估计瘦肉含量(LMP),这是猪育种计划的主要育种目标之一。我们使用 50K 阵列和序列基因型评估了商业杂交皮特兰猪的体组成性状的加性和显性遗传结构。我们首先使用单标记关联分析进行了全基因组关联研究(GWAS),假发现率为 0.1。然后,我们估计了数量性状位点(QTL)区域中最显著变异的加性和显性效应。研究了使用全基因组序列(WGS)是否会提高 QTL 检测(加性和显性)的功效,与较低密度的 SNP 阵列相比。我们的结果表明,与 50K 阵列相比,WGS 检测到更多的 QTL 区域(n=54 对 n=17)。在 WGS 检测到的与 FD 和 LMP 相关的新关联区域中,最显著的峰位于 SSC13,位于约 116-118、121-127 和 129-134 Mbp。此外,我们发现,只有加性效应对分析性状的遗传结构有贡献,并且在 QTL 区域中,无论面板密度如何,测试 SNP 都没有发现显著的显性效应。关联 SNP 位于或靠近几个相关候选基因。在这些基因中,GABRR2、GALR1、RNGTT、CDH20 和 MC4R 先前已被报道与脂肪沉积性状有关。然而,在 SSC1(ZNF292、ORC3、CNR1、SRSF12、MDN1、TSHZ1、RELCH 和 RNF152)和 SSC18(TTC26 和 KIAA1549)上的基因以前没有报道过。根据我们目前的研究结果,提供了有关影响皮特兰猪组成性状的基因组区域的见解。