Unveiling the Genomic Signatures for Tropical Adaptation in Kangayam Cattle by De-correlated Composite of Multiple Selection Signals

Abstract

Background: This study aimed to identify genomic regions under selection in Kangayam cattle of Tamil Nadu using a de-correlated composite of multiple signals (DCMS) framework. Methods: BovineHD SNP array data were retrieved from the WIDDE repository and the ICAR Krishi-Kosh portal. After quality control, autosomal SNPs were used for subsequent analyses. Fixation index, integrated haplotype score, modified haplotype homozygosity, Tajima’s D and nucleotide diversity, were calculated and integrated using the DCMS approach. Genomic windows with false discovery rate (FDR) adjusted q less than 0.001 scores were considered for subsequent analysis. Functional annotation, QTL enrichment, protein–protein interaction (PPI) network analysis and hub gene identification were performed to interpret biological relevance. Result: Genomic regions identified after DCMS analysis, harbored genes related to muscle development, metabolism, immunity, thermotolerance, reproduction and milk composition, including MSTN, BMP7, PRKAG3, BoLA-DRB3, IL8R, ABCA1 and members of the SLCO gene family. PPI and hub gene analyses highlighted transport and metabolic pathways, with SLC22A7 and ABCC9 emerging as key nodes. This study presents the first DCMS-based selection signature map for Kangayam cattle, uncovering coordinated selection across interconnected biological pathways.