Discriminatory Analysis of Principal Components (DAPC) is a powerful method used in population genetics to estimate the ancestry and genetic structure of various populations. In this research paper, we applied DAPC to analyze Indian sheep populations using different SNP densities and four distinct methods: Combine, Delta, Information, and FST. The central focus was to evaluate the variation in "a" score values, a crucial parameter in DAPC, across different SNP densities and method. Our results reveal significant variations in the "a" score values across different SNP densities and methods, indicating the efficiency of DAPC in estimating ancestry and discerning genetic structure in Indian sheep populations. The 20K marker panel consistently demonstrated superior performance, closely resembling the original dataset. Comparative insights from previous studies on sheep populations are also discussed to put our findings in context.

SNP, FST, Marker, PCA, Population, Ancestry

Discriminatory Analysis of Principal Components (DAPC) is a valuable tool for estimating ancestry and assessing population structure in Indian sheep populations. The 20K marker panel consistently produced the best results, demonstrating its efficiency in capturing the genetic diversity of Indian sheep breeds. Our findings provide important insights into the genetic structure of Indian sheep populations and contribute to the broader field of population genetics. Future research can further explore the genetic diversity of Indian sheep populations using advanced genomic techniques and larger datasets. Additionally, investigating the functional implications of genetic diversity and ancestry in these populations can offer valuable insights for sheep breeding and conservation efforts.

Priyanka Swami, Jaswant Singh, Mahender Miland Lakeshar, Radha Rani Swami, M.K. Verma, Nidhi Verma and Sunil Kumar Meena (2024). Discriminatory Analysis of Principal Components (DAPC) for Ancestry Estimation in Indian Sheep Populations. Biological Forum – An International Journal, 16(1): 41-43.