Husien Hosameldeen Mohamed, Saleh Ahmed A, Hassanine Nada N A M, Rashad Amr M A, Sharaby Mahmoud A, Mohamed Asmaa Z, Abdelhalim Heba, Hafez Elsayed E, Essa Mohamed Osman Abdalrahem, Adam Saber Y, Chen Ning, Wang Mengzhi
Laboratory of Metabolic Manipulation of Herbivorous Animal Nutrition, College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China.
College of Veterinary Medicine, Albutana University, Rufaa 22217, Sudan.
Vet Sci. 2024 Dec 6;11(12):627. doi: 10.3390/vetsci11120627.
Distinctive molecular approaches and tools, particularly high-throughput SNP genotyping, have been applied to determine and discover SNPs, potential genes of interest, indicators of evolutionary selection, genetic abnormalities, molecular indicators, and loci associated with quantitative traits (QTLs) in various livestock species. These methods have also been used to obtain whole-genome sequencing (WGS) data, enabling the implementation of genomic selection. Genomic selection allows for selection decisions based on genomic-estimated breeding values (GEBV). The estimation of GEBV relies on the calculation of SNP effects using prediction equations derived from a subset of individuals in the reference population who possess both SNP genotypes and phenotypes for target traits. Compared to traditional methods, modern genomic selection methods offer advantages for sex-limited traits, low heritability traits, late-measured traits, and the potential to increase genetic gain by reducing generation intervals. The current availability of high-density genotyping and next-generation sequencing data allow for genome-wide scans for selection. This investigation provides an overview of the essential role of advanced molecular tools in studying genetic diversity and implementing genomic selection. It also highlights the significance of adaptive selection in light of new high-throughput genomic technologies and the establishment of selective comparisons between different genomes. Moreover, this investigation presents candidate genes and QTLs associated with various traits in different livestock species, such as body conformation, meat production and quality, carcass characteristics and composition, milk yield and composition, fertility, fiber production and characteristics, and disease resistance.
独特的分子方法和工具，特别是高通量单核苷酸多态性（SNP）基因分型，已被应用于确定和发现各种家畜物种中的SNP、潜在的感兴趣基因、进化选择指标、遗传异常、分子指标以及与数量性状（QTL）相关的基因座。这些方法也被用于获取全基因组测序（WGS）数据，从而实现基因组选择。基因组选择允许基于基因组估计育种值（GEBV）做出选择决策。GEBV的估计依赖于使用从参考群体中的一部分个体推导出来的预测方程来计算SNP效应，这些个体同时拥有目标性状的SNP基因型和表型。与传统方法相比，现代基因组选择方法在限性性状、低遗传力性状、晚期测量性状方面具有优势，并且有可能通过缩短世代间隔来增加遗传增益。目前高密度基因分型和下一代测序数据的可用性使得能够进行全基因组扫描以进行选择。本研究概述了先进分子工具在研究遗传多样性和实施基因组选择中的重要作用。它还强调了鉴于新的高通量基因组技术适应性选择的重要性以及不同基因组之间选择性比较的建立。此外，本研究展示了与不同家畜物种的各种性状相关的候选基因和QTL，如体型、肉的产量和品质、胴体特征和组成、牛奶产量和组成、繁殖力、纤维产量和特征以及抗病性。
