Embrapa Pecuária Sul, Bagé, Brazil.
The Roslin Institute and R(D)SVS, University of Edinburgh, Edinburgh, United Kingdom.
Front Immunol. 2021 Jun 23;12:620847. doi: 10.3389/fimmu.2021.620847. eCollection 2021.
Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV.
蜱虫会给肉牛和奶牛养殖业造成巨大的产量损失。牛对蜱虫的抵抗力是影响蜱虫控制的最重要因素之一，但由于表型分析的挑战，这一因素在很大程度上被忽视了。在这项研究中，我们评估了来自多个国家的肉牛品种的抗蜱参考群体的合并，以评估通过多性状基因组选择提高宿主抗性的可能性。数据包括蜱虫计数或评分，评估至少 4.5 毫米长的雌性蜱虫数量，来自七个群体，其品种、国家、记录数量和基因分型/表型动物分别为：安格斯（AN），巴西，2233 头，921/1156 头，赫里福德（HH），巴西，6615 头，1910/2802 头，布兰格斯（BN），巴西，2441 头，851/851 头，布拉夫多（BO），巴西，9523 头，3062/4095 头，热带复合（TC），澳大利亚，229 头，229/229 头，婆罗门（BR），澳大利亚，675 头，675/675 头，以及 Nguni（NG），南非，490 头，490/490 头。所有群体均使用中等密度的 Illumina SNP BeadChips 进行基因分型，并被内插至 332468 个标记的常见高密度面板。不同群体之间相邻 SNP 的平均连锁不平衡（LD）从 0.24 到 0.37 不等，因此足以进行基因组育种值（GEBV）预测。复合品种与其原始品种之间的 LD 相位相关性（0.81 至 0.95）高于 NG 与其他品种之间的相关性（0.27 至 0.35）。在所研究的群体中，对蜱虫抗性的估计遗传力（0.05 至 0.42）和遗传相关性（-0.01 至 0.87）差异很大，BN 和 BO 之间观察到最大的遗传相关性。与单个性状群体内预测相比，使用多性状方法对七个群体中的三个群体进行旧-幼验证时，预测能力得到了提高，而在所有情况下，整体和部分数据 GEBV 相关性均增加，相对改进幅度从 BO 的 3%到 TC 的 64%不等。此外，多性状分析有助于纠正 GEBV 的典型过度分散。本研究结果表明，可以通过对 GEBV 进行选择，轻松地对 AN、HH、BN、BO 和 BR 进行联合基因组评估，以提高这些群体对蜱虫的抵抗力。对于 NG 和 TC，需要进行额外的表型分析，以获得准确的 GEBV。
