Identifying low-density, ancestry-informative SNP markers through whole genome resequencing in Indian, Chinese, and wild yak

The current investigation was undertaken to elucidate the population-stratifying and ancestry-informative markers in Indian, Chinese, and wild yak populations using whole genome resequencing (WGS) analysis while employing various selection strategies (Delta, Pairwise Wright's Fixation Index-F<sub>ST</sub>, and Informativeness of Assignment) and marker densities (5-25 thousand). The study used WGS data on 105 individuals from three separate yak cohorts i.e., Indian yak (n = 29), Chinese yak (n = 61), and wild yak (n = 15). Variant calling in the GATK program with strict quality control resulted in 1,002,970 high-quality and independent (LD-pruned) SNP markers across the yak autosomes. Analysis was undertaken in toolbox for ranking and evaluation of SNPs (TRES) program wherein three different criteria i.e., Delta, Pairwise Wright's Fixation Index-F<sub>ST</sub>, and Informativeness of Assignment were employed to identify population-stratifying and ancestry-informative markers across various datasets. The top-ranked 5,000 (5K), 10,000 (10K), 15,000 (15K), 20,000 (20K), and 25,000 (25K) SNPs were identified from each dataset while their composition and performance was assessed using different criteria. The average genomic breed clustering of Indian, Chinese, and wild yak cohorts with full density dataset (105 individuals with 1,002,970 markers) was 81.74%, 80.02%, and 83.62%, respectively. Informativeness of Assignment criterion with 10K density emerged as the best combination for three yak cohorts with 86.94%, 96.46%, and 98.20% clustering for Indian, Chinese, and wild yak, respectively. There was an average increase of 7.56%, 22.72%, and 30.35% in genomic breed clustering scores of Indian, Chinese, and wild yak cohorts over the estimates of the original dataset. The selected markers showed overlap multiple protein-coding genes within a 10 kb window including ADGRB3, ANK1, CACNG7, CALN1, CHCHD2, CREBBP, GLI3, KHDRBS2, and OSBPL10. This is the first report ever on elucidating low-density SNP marker sets with population-stratifying and ancestry-informative properties in three yak groups using WGS data. The results gain significance for application of genomic selection using cost-effective low-density SNP panels in global yak species.

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Publication Details

Journal
BMC Genomics
Published
2024-11-05
DOI
https://doi.org/10.1186/s12864-024-10924-9
Citations
6
Primary Topic
Genetic and phenotypic traits in livestock
Type
article
Field-Weighted Citation Impact
3.30

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article

Identifying low-density, ancestry-informative SNP markers through whole genome resequencing in Indian, Chinese, and wild yak

Amit Kumar, Ahmed K. Ali, Triveni Dutt, Sheikh Firdous Ahmad et al.
6 citations
BMC Genomics
Genetic and phenotypic traits in livestock
3.30
article

Identifying low-density, ancestry-informative SNP markers through whole genome resequencing in Indian, Chinese, and wild yak

Amit Kumar, Ahmed K. Ali, Triveni Dutt, Sheikh Firdous Ahmad, Amod Kumar, Munish Gangwar, Gyanendra Kumar Gaur
article en
6 citations

Abstract

The current investigation was undertaken to elucidate the population-stratifying and ancestry-informative markers in Indian, Chinese, and wild yak populations using whole genome resequencing (WGS) analysis while employing various selection strategies (Delta, Pairwise Wright's Fixation Index-F<sub>ST</sub>, and Informativeness of Assignment) and marker densities (5-25 thousand). The study used WGS data on 105 individuals from three separate yak cohorts i.e., Indian yak (n = 29), Chinese yak (n = 61), and wild yak (n = 15). Variant calling in the GATK program with strict quality control resulted in 1,002,970 high-quality and independent (LD-pruned) SNP markers across the yak autosomes. Analysis was undertaken in toolbox for ranking and evaluation of SNPs (TRES) program wherein three different criteria i.e., Delta, Pairwise Wright's Fixation Index-F<sub>ST</sub>, and Informativeness of Assignment were employed to identify population-stratifying and ancestry-informative markers across various datasets. The top-ranked 5,000 (5K), 10,000 (10K), 15,000 (15K), 20,000 (20K), and 25,000 (25K) SNPs were identified from each dataset while their composition and performance was assessed using different criteria. The average genomic breed clustering of Indian, Chinese, and wild yak cohorts with full density dataset (105 individuals with 1,002,970 markers) was 81.74%, 80.02%, and 83.62%, respectively. Informativeness of Assignment criterion with 10K density emerged as the best combination for three yak cohorts with 86.94%, 96.46%, and 98.20% clustering for Indian, Chinese, and wild yak, respectively. There was an average increase of 7.56%, 22.72%, and 30.35% in genomic breed clustering scores of Indian, Chinese, and wild yak cohorts over the estimates of the original dataset. The selected markers showed overlap multiple protein-coding genes within a 10 kb window including ADGRB3, ANK1, CACNG7, CALN1, CHCHD2, CREBBP, GLI3, KHDRBS2, and OSBPL10. This is the first report ever on elucidating low-density SNP marker sets with population-stratifying and ancestry-informative properties in three yak groups using WGS data. The results gain significance for application of genomic selection using cost-effective low-density SNP panels in global yak species.

BMC GenomicsVol. 25(1)
Indian Council of Agricultural Research (IN), Indian Veterinary Research Institute (IN), National Bureau of Animal Genetic Resources (IN)
Indian Council of Agricultural Research, ICAR-Indian Veterinary Research Institute, Centre for Agricultural Bioinformatics
Zero hunger
Openalex Percentile: Top 7%
Genetic and phenotypic traits in livestock
3.30
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