Work

Genome-wide association analysis of growth traits in Tianzhu White Yak

Year: 2026

Type: article

Abstract: Background Identifying key markers or genes associated with growth traits in Tianzhu White Yak is crucial for breeding. Precisely locating genetic factors related to body conformation and growth can improve breeding efficiency and economic value. In this study, low-coverage sequencing was used to resequencing 536 Tianzhu White Yak individuals at different growth stages (1 year, 2.5 years, and 4 years or older) for four growth trait indices: body weight (BW), body height (BH), body oblique length (BOL), and chest circumference (CC). Genome-wide association studies (GWAS) were conducted to identify candidate genes associated with these four body measurements, thereby laying the foundation for subsequent studies on the biological functions of these genes. Results After genotype imputation and quality control, a total of 24,383,269 SNPs were retained for subsequent analysis. A total of 366 significant SNP loci were identified, which were annotated to 32 candidate genes associated with body conformation traits, such as PLCB1 , SAR1B , and SRSF6 for body weight; BRPF3 , MAPK13 , and ZNF76 for body height; ABCD3 and NTM for body oblique length; and LMNTD1 and ACVR1 for chest circumference. Functional analysis revealed that multiple candidate genes are involved in key biological processes, including negative regulation of the G1/S transition of the mitotic cell cycle and fatty acid beta-oxidation. Notably, TEAD3 , ZNF76 , and RBL1 were significantly enriched in the transcription regulator complex, a cellular component that may influence cell proliferation, differentiation, and tissue formation. Conclusion This study identified candidate loci and genes associated with growth traits in Tianzhu White Yak through low-coverage sequencing combined with GWAS analysis. These findings provide valuable genetic markers for genomic selection in Tianzhu White Yak, thereby offering resources to advance precision breeding programs.

Source: BMC Genomics

DOI: 10.1186/s12864-026-13444-w