ArticleBMC genomic data2026
Development and validation of high-density SNP array for genomic studies in Indian yak populations.
Article in BMC genomic data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundYaks are multipurpose ruminants crucial for milk, meat, wool, fuel, and high-altitude transportation. Effective management of their genetic resources requires detailed knowledge of their genetic diversity, population structure, and genealogical parameters. SNP arrays offer a reliable and reproducible method for genotyping, overcoming limitations of other approaches. The present study focused on developing and validating a high-density SNP array tailored for Indian yak populations.
resultsIn whole genome resequencing analysis, 31 million variants, including SNPs and InDels, were scored in the Indian yak populations. The identified variants underwent rigorous filtering based on various criteria such as minor allele frequency, removal of insertions and deletions, selection of biallelic SNPs, filtration of adjacent SNPs, and p-convert value. Finally, a total of 627,377 SNPs were selected and tiled using Affymetrix® Axiom® High Density genotyping array technology. Subsequently, the developed SNP array was validated using 338 Indian yak DNA samples using the Affymetrix GeneTitan platform. Further, the SNP array data analysis revealed a greater than 99% SNP call rate with the ability to detect all three genotypes. Furthermore, a total of 465,203 markers were found to be polymorphic or poly high resolution, indicating robustness of the array. The MAF of selected variants across genotyped samples and WGS data was found to be 0.287 and 0.308, respectively. The PCA and admixture analysis confirmed the ability of the SNP panel to differentiate Indian, Chinese, and wild yak populations.
conclusionThe newly developed SNP array (IndiYak) holds significant promise for various applications in yak genetics research, including genome-wide association studies, assessment of genomic diversity, genomic selection, and molecular evolutionary analysis.
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