双用途比利时蓝奶牛乳尿素浓度的全基因组关联。

Hadi Atashi, Yansen Chen, Hélène Wilmot, Sylvie Vanderick, Xavier Hubin, Nicolas Gengler
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引用次数: 2

摘要

本研究旨在估计双用途比利时蓝(DPBB)奶牛的遗传参数并鉴定与乳尿素浓度(MU)相关的基因组区域。数据来源于2014 - 2020年间比利时瓦隆地区49个畜群的2498头一胎奶牛(16,935个试验日记录)和1939头二胎奶牛(12,758个试验日记录)的产奶量(MY)、脂肪产量(FY)、蛋白质产量(PY)、脂肪率(FP)、蛋白质率(PP)和MU的29,693个试验日记录。利用1699只牛(雄性639只,雌性1060只)29条牛常染色体(BTA)的28266个单核苷酸多态性(SNP)数据进行分析。使用随机回归测试日模型,通过贝叶斯吉布斯抽样方法,使用100,000次迭代的单链,在20,000个老化期后估计遗传参数。使用单步基因组最佳线性无偏预测方法估计SNP解决方案。计算25个连续snp(平均大小为~2 Mb)的窗口所解释的遗传变异比例,并使用至少占总加性遗传变异1.0%的区域来搜索候选基因。第一胎和第二胎的平均SD分别为22.89(10.07)和22.35 (10.07)mg/dl。第一次和第二次胎次的平均遗传力分别为0.18(0.01)和0.22(0.02)。首胎日MU与MY、FY、PY、FP和PP的平均遗传相关(SD)分别为-0.05(0.09)、-0.07(0.11)、-0.03(0.13)、-0.05(0.08)和-0.03(0.11)。第二奇偶校验的对应值分别为0.02(0.10)、-0.02(0.09)、0.02(0.08)、-0.08(0.06)和-0.05(0.05)。全基因组关联分析确定了与MU相关的三个基因组区域(BTA2、BTA3和BTA13)。所确定的区域显示出胎次之间和每个胎次内不同阶段之间的对比结果。这表明不同的候选基因组是胎次之间和胎次内不同哺乳期MU表型表达的基础。本研究结果可用于未来实施和使用基因组评估来减少DPBB奶牛的MU。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genome-wide association for milk urea concentration in Dual-Purpose Belgian Blue cows.

The objectives of this study were to estimate genetic parameters and identify genomic regions associated with milk urea concentration (MU) in Dual-Purpose Belgian Blue (DPBB) cows. The data were 29,693 test-day records of milk yield (MY), fat yield (FY), protein yield (PY), fat percentage (FP), protein percentage (PP) and MU collected between 2014 and 2020 on 2498 first parity cows (16,935 test-day records) and 1939 second-parity cows (12,758 test-day records) from 49 herds in the Walloon Region of Belgium. Data of 28,266 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA), on 1699 animals (639 males and 1060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method using a single chain of 100,000 iterations after a burn-in period of 20,000. SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by windows of 25 consecutive SNPs (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. The mean (SD) of MU was 22.89 (10.07) and 22.35 (10.07) mg/dl for first and second parity, respectively. The mean (SD) heritability estimates for daily MU were 0.18 (0.01) and 0.22 (0.02), for first and second parity, respectively. The mean (SD) genetic correlations between daily MU and MY, FY, PY, FP and PP were -0.05 (0.09), -0.07 (0.11), -0.03 (0.13), -0.05 (0.08) and -0.03 (0.11) for first parity, respectively. The corresponding values estimated for second parity were 0.02 (0.10), -0.02 (0.09), 0.02 (0.08), -0.08 (0.06) and -0.05 (0.05). The genome-wide association analyses identified three genomic regions (BTA2, BTA3 and BTA13) associated with MU. The identified regions showed contrasting results between parities and among different stages within each parity. This suggests that different groups of candidate genes underlie the phenotypic expression of MU between parities and among different lactation stages within a parity. The results of this study can be used for future implementation and use of genomic evaluation to reduce MU in DPBB cows.

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