Identification of important genomic footprints using eight different selection signature statistics in domestic cattle breeds.

• We merged extracted datasets of 11 cattle breeds with our own generated Tharparkar genotypic data to obtain a final dataset of 284 animals. • The PCA indicates the partitioning between Exotic and Indigenous cattle breeds on the two PC axis. • We used several statistical tools (eight) to find out and verify more genomic footprints. • More number of short ROHs in Tharparkar shows a more historical relationship. • Combined analysis of all the methods may provide refined information about selective sweep regions in different methods. • We extracted out various candidate genes associated with economically important traits. In the present study, the population genomic data of different cattle breeds were explored to decipher the genomic regions affected due to selective events and reflected in the productive, reproductive, thermo-tolerance, and health-related traits. To find out these genomic deviations due to selective sweeps, we used eight different statistical tools (Tajima's D, Fu & Li's D*, CLR, ROH, iHS, F ST , FLK, and hapFLK) on seven indigenous and five exotic cattle breeds. We further performed composite analysis by comparing their covariance matrix. Several candidate genes were found to be related to milk production (ADARB, WDR70, and CA8), reproductive (PARN, FAM134B2, and ZBTB20), and health-related traits (SP110, CXCL2, CLXCL3 , CXCL5 , IRF8, and MYOM1). The outcome of this investigation provides a basis for detecting selective sweeps that explain the genetic variation of traits. They may possess functional importance for multiple cattle breeds in different subcontinents. However, further studies are required to improve the findings using high-density arrays or whole-genome sequencing with higher resolution and greater sample sizes. [ABSTRACT FROM AUTHOR]