Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP, 243122, India.
Division of Pharmacology & Toxicology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, UP, 243122, India.
Mamm Genome. 2024 Sep;35(3):377-389. doi: 10.1007/s00335-024-10047-2. Epub 2024 Jul 16.
This study seeks a comprehensive exploration of genome-wide selective processes impacting morphometric traits across diverse cattle breeds, utilizing an array of statistical methods. Morphometric traits, encompassing both qualitative and quantitative variables, play a pivotal role in characterizing and selecting livestock breeds based on their external appearance, size, and physical attributes. While qualitative traits, such as color, horn structure, and coat type, contribute to adaptive features and breed identification, quantitative traits like body weight and conformation measurements bear a closer correlation with production characteristics. This study employs advanced genotyping technologies, including the Illumina BovineSNP50 Bead Chip and next-generation sequencing methods like Reduced Representation sequencing, to identify genomic signatures associated with these traits. We applied four intra-population methods to find evidence of selection, such as Tajima's D, CLR, iHS, and ROH. We found a total of 40 genes under the selection signature, that were associated with morphometric traits in five cattle breeds (Kankrej, Tharparkar, Nelore, Sahiwal, and Gir). Crucial genes such as ADIPDQ, DPP6, INSIG1, SLC35D2 in Kankrej, LPL, ATP6V1B2, CDC14B in Tharparkar, HPSE2, PLAG1 in Nelore, PCSK1, PRKD1 in Sahiwal, and GNAQ, HPCAL1 in Gir were identified in our study. This approach provides valuable insights into the genetic basis of variations in body weight and conformation traits, facilitating informed selection processes and offering a deeper understanding of the evolutionary and domestication processes in diverse cattle breeds.
本研究旨在利用一系列统计方法,全面探索影响不同牛种形态特征的全基因组选择过程。形态特征包括定性和定量变量,在根据外部形态、大小和身体特征对家畜品种进行描述和选择方面发挥着关键作用。虽然定性特征,如颜色、角结构和毛色类型,有助于适应特征和品种识别,但定量特征,如体重和体型测量,与生产特征更密切相关。本研究采用先进的基因分型技术,包括 Illumina BovineSNP50 Bead Chip 和下一代测序方法,如简化代表性测序,来识别与这些特征相关的基因组特征。我们应用了四种群体内方法来寻找选择的证据,如 Tajima 的 D、CLR、iHS 和 ROH。我们总共在五个牛种(Kankrej、Tharparkar、Nelore、Sahiwal 和 Gir)中发现了 40 个与形态特征相关的受选择基因。在 Kankrej 中,ADIPDQ、DPP6、INSIG1、SLC35D2 等关键基因,在 Tharparkar 中,LPL、ATP6V1B2、CDC14B 等基因,在 Nelore 中,HPSE2、PLAG1 等基因,在 Sahiwal 中,PCSK1、PRKD1 等基因,在 Gir 中,GNAQ、HPCAL1 等基因都被鉴定出来。这种方法为体重和体型特征变异的遗传基础提供了有价值的见解,有助于知情选择过程,并深入了解不同牛种的进化和驯化过程。