Vol. 8, Issue 1, Part C (2024)
Integrative analysis of common SNPS and imputation accuracy across diverse genomic densities in Asian, exotic, and Indian sheep breeds
Author(s):
Priyanka Swami, Jaswant Singh, Pushkar Sharma and Sunil Kumar Meena
Abstract:
The present study aimed to explore pure SNP densities within Indian, Asian, and exotic sheep breeds using Ovine 50K SNP BeadChip data. This study explored Common Single Nucleotide Polymorphisms (SNPs) in datasets A, B, C, and D, revealing genetic variations among Asian, exotic, and Indian sheep breeds. Venn diagrams identified 13 (0.32%), 201 (1.67%), and 30 (0.15%) common SNPs across all datasets at different genomic densities (1K, 3K, 5K, 10K, and 20K). Using the Frequent item Feature Selection (FIFS) method, unique SNP patterns emphasized genetic differentiation among datasets. Imputation accuracy varied across densities, with dataset A showing the highest average accuracy at 5K (0.6124). Challenges in SNP selection for 10K and 20K densities in datasets A, B, and D indicated difficulties in capturing common SNPs. The study's insights into discriminant SNP loci on specific chromosomes, like ovine chromosomes 17, 6, 4, 15, 19, 12, and 8, offer potential for cost-effective SNP assays in sheep breed assignment. These findings aim to aid in developing low-cost genotyping methods, reducing genotyping expenses in diverse sheep breeds.
Pages: 168-174 | 420 Views 196 Downloads
How to cite this article:
Priyanka Swami, Jaswant Singh, Pushkar Sharma and Sunil Kumar Meena. Integrative analysis of common SNPS and imputation accuracy across diverse genomic densities in Asian, exotic, and Indian sheep breeds. Int. J. Adv. Biochem. Res. 2024;8(1):168-174. DOI: 10.33545/26174693.2024.v8.i1c.330