Rafter Pierce, Gormley Isobel Claire, Parnell Andrew C, Naderi Saeid, Berry Donagh P
Animal & Grassland Research and Innovation Centre, Fermoy, Ireland.
School of Mathematics and Statistics, University College Dublin, Dublin, Ireland.
Front Genet. 2021 Nov 2;12:761503. doi: 10.3389/fgene.2021.761503. eCollection 2021.
The relative contributions of both copy number variants (CNVs) and single nucleotide polymorphisms (SNPs) to the additive genetic variance of carcass traits in cattle is not well understood. A detailed understanding of the relative importance of CNVs in cattle may have implications for study design of both genomic predictions and genome-wide association studies. The first objective of the present study was to quantify the relative contributions of CNV data and SNP genotype data to the additive genetic variance of carcass weight, fat, and conformation for 945 Charolais, 923 Holstein-Friesian, and 974 Limousin sires. The second objective was to jointly consider SNP and CNV data in a least absolute selection and shrinkage operator (LASSO) regression model to identify genomic regions associated with carcass weight, fat, and conformation within each of the three breeds separately. A genomic relationship matrix (GRM) based on just CNV data did not capture any variance in the three carcass traits when jointly evaluated with a SNP-derived GRM. In the LASSO regression analysis, a total of 987 SNPs and 18 CNVs were associated with at least one of the three carcass traits in at least one of the three breeds. The quantitative trait loci (QTLs) corresponding to the associated SNPs and CNVs overlapped with several candidate genes including previously reported candidate genes such as and several potential novel candidate genes such as and . The results of the LASSO regression analysis demonstrated that CNVs can be used to detect associations with carcass traits which were not detected using the set of SNPs available in the present study. Therefore, the CNVs and SNPs available in the present study were not redundant forms of genomic data.
拷贝数变异(CNV)和单核苷酸多态性(SNP)对牛胴体性状加性遗传方差的相对贡献尚未得到充分了解。深入了解CNV在牛中的相对重要性可能会对基因组预测和全基因组关联研究的研究设计产生影响。本研究的第一个目标是量化CNV数据和SNP基因型数据对945头夏洛来牛、923头荷斯坦-弗里生牛和974头利木赞牛种公牛的胴体重、脂肪和体型加性遗传方差的相对贡献。第二个目标是在最小绝对收缩选择算子(LASSO)回归模型中联合考虑SNP和CNV数据,以分别识别三个品种中与胴体重、脂肪和体型相关的基因组区域。当与基于SNP的基因组关系矩阵(GRM)联合评估时,仅基于CNV数据的GRM未捕获三个胴体性状中的任何方差。在LASSO回归分析中,共有987个SNP和18个CNV与三个品种中至少一个品种的至少一个胴体性状相关。与相关SNP和CNV对应的数量性状位点(QTL)与几个候选基因重叠,包括先前报道的候选基因如 以及几个潜在的新候选基因如 和 。LASSO回归分析结果表明,CNV可用于检测与本研究中可用SNP集未检测到的胴体性状的关联。因此,本研究中可用的CNV和SNP不是基因组数据的冗余形式。