Ancestry informative markers derived from discriminant analysis of principal components provide important insights into the composition of crossbred cattle.

The cost of SNP genotyping to screen different breeds and to estimate the exact proportion of ancestry level is quite high, which can be compensated through deriving a small panel of ancestry informative markers (AIMs). Hence, we carried out the present study to provide an insight into ancestry level inferred from a panel of informative markers in the crossbred Vrindavani population developed at ICAR-IVRI, India. We have performed a new method i.e., discriminant analysis of principal components (DAPC) for the first time on the dataset of Vrindavani cattle. To confirm our method, we had performed DAPC on two other well-known crossbred cattle, i.e., Frieswal and Beefmaster. Three sets of panels (500, 1000 and 2000 markers) were tested for clustering of individuals. Among all the panels, we found the panel (1000 markers) with DAPC based contribution method was of the smallest size and comparatively of the highest accuracy. • The present study was carried out to infer ancestry level from a panel of informative markers in the crossbred population • The 1000 markers panel selected through DAPC based contribution method was the smallest and comparatively accurate • The information generated in our study will pave the way for characterization of other crossbreds available in the country [ABSTRACT FROM AUTHOR]