Genetic Features of Reproductive Traits in Bovine and Buffalo: Lessons From Bovine to Buffalo - Shao, Baoshun; Sun, Hui; Ahmad, Muhammad Jamil; Ghanem, Nasser; Abdel-Shafy, Hamdy; Du, Chao; Deng, Tingxian; Mansoor, Shahid; Zhou, Yang; Yang, Yifen; Zhang, Shujun; Yang, Liguo; et al. (Frontiers in Genetics, 2021)
Bovine and buffalo are important livestock species contributing to human living for thousands of years. To improve fertility is a critical way to reduce the cost of production. Based on physiological process, we classified numerous reproduction traits into three categories, such as ovulation, breeding and calving related traits. We systematically summarized the heritability estimates, molecular markers, and genomic selection (GS) for reproductive traits of bovine and buffalo. This review aimed to compile the heritability and genome-wide association studies (GWAS) related to reproductive traits for both bovine and buffalos and try to explore the possible disciplines which should benefit buffalo breeding. The estimates of heritability of reproductive traits ranged from 0-0.57 and there were wide differences between the populations. For some specific traits, such as age of puberty (AOP) and calving difficulty (CD), the majority beef population presents relatively higher heritability than dairy cattle. Compared with bovine, the genetic studies for buffalo reproductive traits are limited on age at first calving and calving interval traits. Several QTLs, candidate genes, SNPs associated with bovine reproductive traits were screened and identified by candidate gene methods and/or GWAS. The IGF1 and LEP pathways in addition to non-coding RNAs are highlighted due to their crucial relevance with these traits. The distribution of QTLs related to various traits showed a great difference. Few GWAS were performed so far on buffalo age at first calving, calving interval and days open traits. Besides, we summarized the GS studies on bovine and buffalo reproductive traits and compared the accuracy between different reports. Taken together, GWAS and candidate gene methods can help to understand the molecular genetic mechanisms of complex traits. Recently GS has been used extensively and can be performed on multiple traits to improve the accuracy of prediction even for traits with low heritability, and can be combined with multi-omics for further analysis.