Department of Animal Biosciences, University of Guelph, Guelph, ON, N1G 2W1, Canada; Department of Animal Sciences, Universidade Federal de Viçosa, Viçosa, Minas Gerais, 36570-000, Brazil.
Department of Animal and Dairy Science, University of Georgia, Athens 30602.
J Dairy Sci. 2019 Nov;102(11):9995-10011. doi: 10.3168/jds.2019-16821. Epub 2019 Aug 30.
Estimating single nucleotide polymorphism (SNP) effects over time is essential to identify and validate candidate genes (or quantitative trait loci) associated with time-dependent variation of economically important traits and to better understand the underlying mechanisms of lactation biology. Therefore, in this study, we aimed to estimate time-dependent effects of SNP and identifying candidate genes associated with milk (MY), fat (FY), and protein (PY) yields, and somatic cell score (SCS) in the first 3 lactations of Canadian Ayrshire, Holstein, and Jersey breeds, as well as suggest their potential pattern of phenotypic effect over time. Random regression coefficients for the additive direct genetic effect were estimated for each animal using single-step genomic BLUP, based on 2 random regression models: one considering MY, FY, and PY in the first 3 lactations and the other considering SCS in the first 3 lactations. Thereafter, SNP solutions were obtained for random regression coefficients, which were used to estimate the SNP effects over time (from 5 to 305 d in lactation). The top 1% of SNP that showed a high magnitude of SNP effect in at least 1 d in lactation were selected as relevant SNP for further analyses of candidate genes, and clustered according to the trajectory of their SNP effects over time. The majority of SNP selected for MY, FY, and PY increased the magnitude of their effects over time, for all breeds. In contrast, for SCS, most selected SNP decreased the magnitude of their effects over time, especially for the Holstein and Jersey breeds. In general, we identified a different set of candidate genes for each breed, and similar genes were found across different lactations for the same trait in the same breed. For some of the candidate genes, the suggested pattern of phenotypic effect changed among lactations. Among the lactations, candidate genes (and their suggested phenotypic effect over time) identified for the second and third lactations were more similar to each other than for the first lactation. Well-known candidate genes with major effects on milk production traits presented different suggested patterns of phenotypic effect across breeds, traits, and lactations in which they were identified. The candidate genes identified in this study can be used as target genes in studies of gene expression.
估计单核苷酸多态性(SNP)随时间的效应对于鉴定和验证与经济重要性状随时间变化相关的候选基因(或数量性状位点)以及更好地理解泌乳生物学的潜在机制至关重要。因此,本研究旨在估计 SNP 的时间效应,并鉴定与加拿大爱尔夏牛、荷斯坦牛和泽西牛品种第 1 至 3 泌乳期的牛奶(MY)、脂肪(FY)和蛋白质(PY)产量以及体细胞评分(SCS)相关的候选基因,并提出其随时间变化的潜在表型效应模式。使用单步基因组 BLUP 为每头动物估计加性直接遗传效应的随机回归系数,基于 2 个随机回归模型:一个考虑第 1 至 3 泌乳期的 MY、FY 和 PY,另一个考虑第 1 至 3 泌乳期的 SCS。然后,为随机回归系数获得 SNP 解决方案,用于估计随时间变化的 SNP 效应(泌乳期的 5 至 305 d)。选择至少在泌乳期的 1 天中具有较大 SNP 效应的 SNP 的前 1%作为候选基因进一步分析的相关 SNP,并根据其随时间变化的 SNP 效应轨迹进行聚类。选择用于 MY、FY 和 PY 的大多数 SNP 随着时间的推移增加了其效应的幅度,所有品种均如此。相比之下,对于 SCS,大多数选择的 SNP 随着时间的推移降低了其效应的幅度,特别是对于荷斯坦牛和泽西牛。一般来说,我们为每个品种确定了一组不同的候选基因,并且在同一品种的同一性状的不同泌乳期中发现了相似的基因。对于一些候选基因,建议的表型效应模式在泌乳期之间发生了变化。在泌乳期中,为第二和第三泌乳期确定的候选基因(及其随时间变化的建议表型效应)彼此之间比为第一泌乳期更相似。在鉴定它们的不同品种、性状和泌乳期中,对产奶性状有重大影响的知名候选基因呈现出不同的建议表型效应模式。本研究中鉴定的候选基因可以用作基因表达研究的靶基因。