Hexi cattle are a local cattle population endemic to the Hexi Corridor in Gansu Province, China, and exhibit strong adaptability to the region’s arid continental environment. However, comprehensive genomic investigations of this population are still lacking. In the present study, we integrated population genomic analyses with a genome-wide association study (GWAS) to dissect the genetic architecture of Hexi cattle. Whole-genome resequencing data were generated for 264 Hexi cattle, and public genomic datasets from six representative cattle breeds were obtained from the NCBI database for comparative analysis. Multiple analytical approaches—including principal component analysis (PCA), linkage disequilibrium (LD) decay analysis, neighbor-joining (NJ) phylogenetic tree construction, and ADMIXTURE analysis—were adopted to evaluate population structure and evolutionary relationships. A mixed linear model was then used to identify significant SNPs associated with five major body conformation traits in six-month-old cattle: body weight (BW), withers height (WH), hip height (HH), heart girth (HG), and abdominal girth (AG). Our results confirm the admixed nature of Hexi cattle, whose genome is derived primarily from Simmental cattle and secondarily from Mongolian cattle. A total of 69 trait-associated significant SNPs were identified and functionally annotated. Specifically, TBC1D31, DERL1 and MCPH1 were linked to BW; FSCN3 and PLBD1 to WH; MCPH1 to HH; NPAS3, TBC1D31, DERL1 and MCPH1 to HG; and SOX5, NTAQ1, FAM83A, TBC1D31, DERL1, CDH11, CPLX4 and ADAM18 to AG. This study deepens our understanding of the genetic basis of growth traits in Hexi cattle and offers valuable molecular resources for future selective breeding, genetic improvement, and long-term conservation of this indigenous cattle population.

Average daily gain (ADG) is a core quantitative trait determining the economic benefits of Ashidan yak, a polled new breed adapted to cold barn feeding on the Qinghai–Tibet Plateau. Unraveling its complex genetic architecture is crucial for early molecular breeding selection. In this study, high-depth whole-genome resequencing (WGS) data from 474 Ashidan yaks were used to conduct combined evaluation of genome-wide association study (GWAS) and genomic selection (GS). During GWAS analysis, sex and measurement batch were included as fixed effects, while birth weight and principal components (PC1–PC3) were incorporated as covariates. Multi-model association analysis using GLM, MLM, and FarmCPU was performed on 3.36 million LD-pruned SNPs. The genomic inflation factors (λ ≈ 1.0) for MLM and FarmCPU confirmed effective elimination of population stratification. A total of 11 genome-wide significant SNP loci and 7 key candidate genes including PDE10A, RAD51B, BCAS3 and KCNH8 were identified via the FarmCPU model. Functional enrichment analysis indicated that these gene clusters are significantly involved in cAMP signaling pathway, regulation of ion channel activity, as well as extracellular matrix remodeling of blood vessels and skeletal muscle cells. For genomic selection, a single-trait GBLUP model was constructed using 22.87 million high-density raw SNPs to fully capture polygenic minor effects. Moderately high narrow-sense genomic heritability of ADG was estimated at h² = 0.3233 (p < 0.05). The average independent prediction accuracy across the 10-fold cross-validation reached an average of R = 0.14 ± 0.07. To evaluate marker prioritized genomic evaluation without data leakage, a strict 10-fold cross-validation scheme was implemented, where the top 1% high-priority variant set (~228,000 SNPs) was screened independently within each training fold. The resulting unbiased prediction accuracy reached R = 0.1328 ± 0.1566 (with an average RMSE of 0.3793 ± 0.0066 and a regression slope of 0.4183 ± 0.5055). Comparing this with the unselected whole-genome baseline (R = 0.14 ± 0.07) indicates that naive marker selection based solely on GBLUP effect size in small reference cohorts is influenced by sampling variance, highlighting the need to integrate multi-omics functional annotations for future custom breeding array development. This study provides quantitative insights into the polygenic architecture of ADG in yaks, offering baseline data for genomic selection and custom array development for indigenous livestock on the Qinghai–Tibet Plateau.