Li Chenglan, Li Jianye, Wang Haifeng, Zhang Rui, An Xuejiao, Yuan Chao, Guo Tingting, Yue Yaojing
Key Laboratory of Animal Genetics and Breeding on Tibetan Plateau, Ministry of Agriculture and Rural Affairs, Lanzhou Institute of Husbandry and Pharmaceutical Sciences, Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
Sheep Breeding Engineering Technology Research Center of Chinese Academy of Agricultural Sciences, Lanzhou 730050, China.
Animals (Basel). 2023 Nov 14;13(22):3516. doi: 10.3390/ani13223516.
Alpine Merino Sheep is a novel breed reared from Australian Merino Sheep as the father and Gansu Alpine Fine-Wool Sheep as the mother, living all year in cold and arid alpine areas with exceptional wool quality and meat performance. Body weight is an important economic trait of the Alpine Merino Sheep, but there is limited research on identifying the genes associated with live weight in the 14th month for improving the accuracy of the genomic prediction of this trait. Therefore, this study's sample comprised 1310 Alpine Merino Sheep ewes, and the Fine Wool Sheep 50K Panel was used for genome-wide association study (GWAS) analysis to identify candidate genes. Moreover, the trial population (1310 ewes) in this study was randomly divided into two groups. One group was used as the population for GWAS analysis and screened for the most significant top 5%, top 10%, top 15%, and top 20% SNPs to obtain prior marker information. The other group was used to estimate the genetic parameters based on the weight assigned by heritability combined with different prior marker information. The aim of this study was to compare the accuracy of genomic breeding value estimation when combined with prior marker information from GWAS analysis with the optimal linear unbiased prediction method for genome selection (GBLUP) for the breeding value of target traits. Finally, the accuracy was evaluated using the five-fold cross-validation method. This research provides theoretical and technical support to improve the accuracy of sheep genome selection and better guide breeding. The results demonstrated that eight candidate genes were associated with GWAS analysis, and the gene function query and literature search results suggested that , , , , , , , and were candidate genes affecting live weight in the 14th month (WT), which regulated the growth of muscle and bone in sheep. In genome selection analysis, the heritability of GBLUP to calculate the WT was 0.335-0.374, the accuracy after five-fold cross-verification was 0.154-0.190, and after assigning different weights to the top 5%, top 10%, top 15%, and top 20% of the GWAS results in accordance with previous information to construct the G matrix, the accuracy of the WT in the GBLUP model was improved by 2.59-7.79%.
高山美利奴羊是一种以澳洲美利奴羊为父本、甘肃高山细毛羊为母本培育而成的新品种，常年生活在寒冷干旱的高山地区，羊毛品质和肉用性能优异。体重是高山美利奴羊的一项重要经济性状，但关于鉴定与14月龄体重相关基因以提高该性状基因组预测准确性的研究较少。因此，本研究以1310只高山美利奴母羊为样本，采用细毛羊50K芯片进行全基因组关联研究（GWAS）分析以鉴定候选基因。此外，本研究中的试验群体（1310只母羊）被随机分为两组。一组用作GWAS分析群体，筛选出最显著的前5%、前10%、前15%和前20%的单核苷酸多态性（SNP）以获得先验标记信息。另一组用于结合不同先验标记信息，根据遗传力赋予的权重来估计遗传参数。本研究的目的是比较结合GWAS分析的先验标记信息时基因组育种值估计的准确性与基因组选择（GBLUP）的最优线性无偏预测方法对目标性状育种值的准确性。最后，采用五重交叉验证法评估准确性。本研究为提高绵羊基因组选择准确性和更好地指导育种提供了理论和技术支持。结果表明，8个候选基因与GWAS分析相关，基因功能查询和文献检索结果表明， 、 、 、 、 、 、 和 是影响14月龄体重（WT）的候选基因，它们调控绵羊肌肉和骨骼的生长。在基因组选择分析中，GBLUP计算WT的遗传力为0.335 - 0.374，五重交叉验证后的准确性为0.154 - 0.190，根据先前信息对GWAS结果的前5%、前10%、前15%和前20%赋予不同权重构建G矩阵后，GBLUP模型中WT的准确性提高了2.59 - 7.79%。
