Department of Animal Science, College of Agriculture and Natural Resources, University of Tehran, Karaj, 31587-11167, Iran.
Department of Animal Science and Aquaculture, Dalhousie University, Truro, B2N 5E3, Canada.
BMC Genet. 2020 Nov 23;21(1):129. doi: 10.1186/s12863-020-00953-0.
Methane emission by ruminants has contributed considerably to the global warming and understanding the genomic architecture of methane production may help livestock producers to reduce the methane emission from the livestock production system. The goal of our study was to identify genomic regions affecting the predicted methane emission (PME) from volatile fatty acids (VFAs) indicators and VFA traits using imputed whole-genome sequence data in Iranian Holstein cattle.
Based on the significant-association threshold (p < 5 × 10), 33 single nucleotide polymorphisms (SNPs) were detected for PME per kg milk (n = 2), PME per kg fat (n = 14), and valeric acid (n = 17). Besides, 69 genes were identified for valeric acid (n = 18), PME per kg milk (n = 4) and PME per kg fat (n = 47) that were located within 1 Mb of significant SNPs. Based on the gene ontology (GO) term analysis, six promising candidate genes were significantly clustered in organelle organization (GO:0004984, p = 3.9 × 10) for valeric acid, and 17 candidate genes significantly clustered in olfactory receptors activity (GO:0004984, p = 4 × 10) for PME traits. Annotation results revealed 31 quantitative trait loci (QTLs) for milk yield and its components, body weight, and residual feed intake within 1 Mb of significant SNPs.
Our results identified 33 SNPs associated with PME and valeric acid traits, as well as 17 olfactory receptors activity genes for PME traits related to feed intake and preference. Identified SNPs were close to 31 QTLs for milk yield and its components, body weight, and residual feed intake traits. In addition, these traits had high correlations with PME trait. Overall, our findings suggest that marker-assisted and genomic selection could be used to improve the difficult and expensive-to-measure phenotypes such as PME. Moreover, prediction of methane emission by VFA indicators could be useful for increasing the size of reference population required in genome-wide association studies and genomic selection.
反刍动物排放的甲烷对全球变暖有很大影响，了解甲烷生成的基因组结构可以帮助畜牧业生产者减少畜牧业生产系统中的甲烷排放。我们的研究目标是使用伊朗荷斯坦奶牛的全基因组序列数据，鉴定影响挥发性脂肪酸（VFAs）指标和 VFA 性状预测甲烷排放（PME）的基因组区域。
基于显著关联阈值（p<5×10），检测到 33 个单核苷酸多态性（SNP）与 PME/kg 牛奶（n=2）、PME/kg 脂肪（n=14）和缬氨酸（n=17）有关。此外，在 1Mb 范围内发现了 69 个与缬氨酸（n=18）、PME/kg 牛奶（n=4）和 PME/kg 脂肪（n=47）有关的基因。基于基因本体论（GO）术语分析，6 个有前途的候选基因在缬氨酸中显著聚类在细胞器组织（GO：0004984，p=3.9×10），17 个候选基因在 PME 性状中显著聚类在嗅觉受体活性（GO：0004984，p=4×10）。注释结果显示，在显著 SNP 1Mb 范围内，有 31 个与牛奶产量及其成分、体重和剩余饲料摄入量有关的数量性状基因座（QTL）。
我们的结果确定了 33 个与 PME 和缬氨酸性状相关的 SNP，以及 17 个与饲料摄入和偏好相关的 PME 性状嗅觉受体活性基因。确定的 SNP 与牛奶产量及其成分、体重和剩余饲料摄入量性状的 31 个 QTL 接近。此外，这些性状与 PME 性状高度相关。总的来说，我们的研究结果表明，标记辅助和基因组选择可用于改善 PME 等难以测量和昂贵的表型。此外，通过 VFA 指标预测甲烷排放可用于增加全基因组关联研究和基因组选择所需参考群体的规模。
