Fathoni Akhmad, Boonkum Wuttigrai, Chankitisakul Vibuntita, Buaban Sayan, Duangjinda Monchai
Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen 40002, Thailand.
Department of Animal Breeding and Reproduction, Faculty of Animal Science, Universitas Gadjah Mada, Yogyakarta 55281, Indonesia.
Animals (Basel). 2024 Dec 27;15(1):43. doi: 10.3390/ani15010043.
Days open (DO) is a critical economic and reproductive trait that is commonly employed in genetic selection. Making improvements using conventional genetic techniques is exceedingly challenging. Therefore, new techniques are required to improve the accuracy of genetic selection using genomic data. This study examined the genetic approaches of traditional AIREML and single-step genomic AIREML (ssGAIREML) to assess genetic parameters and the accuracy of estimated breeding values while also investigating SNP regions associated with DO and identifying candidate genes through a genome-wide association study (GWAS). The dataset included 59415 DO records from 36368 Thai-Holstein crossbred cows and 882 genotyped animals. The cows were classified according to their Holstein genetic proportion (breed group, BG) as follows: BG1 (>93.7% Holstein genetics), BG2 (87.5% to 93.6% Holstein genetics), and BG3 (<87.5% Holstein genetics). AIREML was utilized to estimate genetic parameters and variance components. The results of this study reveal that the average DO values for BG1, BG2, and BG3 were 97.64, 97.25, and 96.23 days, respectively. The heritability values were estimated to be 0.02 and 0.03 for the traditional AIREML and ssGAIREML approaches, respectively. Depending on the dataset, the ssGAIREML method produced more accurate estimated breeding values than the traditional AIREML method, ranging from 40.5 to 45.6%. The highest values were found in the top 20% of the dam dataset. For the GWAS, we found 12 potential candidate genes (, , , , , , , , , , , and ) that are believed to have a significant influence on days open. In summary, the ssGAIREML method has the potential to enhance the accuracy and heritability of reproductive values compared to those obtained using conventional AIREML. Consequently, it is a viable alternative for transitioning from conventional methodologies to the ssGAIREML method in the breeding program for dairy cattle in Thailand. Moreover, the 12 identified potential candidate genes can be utilized in future studies to select markers for days open in regard to dairy cattle.
产犊间隔天数（DO）是遗传选择中常用的一个关键经济和繁殖性状。使用传统遗传技术进行改进极具挑战性。因此，需要新技术来提高利用基因组数据进行遗传选择的准确性。本研究考察了传统的动物模型约束极大似然法（AIREML）和单步基因组AIREML（ssGAIREML）的遗传方法，以评估遗传参数和估计育种值的准确性，同时研究与产犊间隔天数相关的单核苷酸多态性（SNP）区域，并通过全基因组关联研究（GWAS）鉴定候选基因。数据集包括来自36368头泰国-荷斯坦杂交奶牛的59415条产犊间隔天数记录以及882头基因分型动物的数据。根据荷斯坦遗传比例（品种组，BG）将奶牛分类如下：BG1（荷斯坦遗传比例>93.7%）、BG2（荷斯坦遗传比例87.5%至93.6%）和BG3（荷斯坦遗传比例<87.5%）。利用AIREML估计遗传参数和方差组分。本研究结果表明，BG1、BG2和BG3的平均产犊间隔天数分别为97.64天、97.25天和96.23天。传统AIREML方法和ssGAIREML方法估计的遗传力值分别为0.02和0.03。根据数据集的不同，ssGAIREML方法产生的估计育种值比传统AIREML方法更准确，范围为40.5%至45.6%。在母本数据集中前20%的数据中发现了最高值。对于全基因组关联研究，我们发现了12个潜在的候选基因（……此处原文未完整列出基因名称），据信它们对产犊间隔天数有显著影响。总之，与使用传统AIREML获得的结果相比，ssGAIREML方法有可能提高繁殖值的准确性和遗传力。因此，在泰国奶牛育种计划中，从传统方法过渡到ssGAIREML方法是一种可行的选择。此外，这12个已鉴定的潜在候选基因可用于未来关于奶牛产犊间隔天数选择标记的研究。
