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The detection of selection signatures assists in understanding domestication, evolution, and the identification of genomic regions related to adaptation and production traits in buffaloes. The emergence of high-throughput technologies like Next Generation Sequencing and SNP genotyping had expanded our ability to detect these signatures of selection. In this study, we sought to identify signatures of selection in five buffalo populations (Brazilian Murrah, Bulgarian Murrah, Indian Murrah, Nili-Ravi, and Kundi) using Axiom Buffalo 90 K Genotyping Array data. Using seven different methodologies (Tajima's D, CLR, ROH, iHS, FST, FLK and hapFLK), we identified selection signatures in 374 genomic regions, spanning a total of 381 genes and 350 quantitative trait loci (QTLs). Among these, several candidate genes were associated with QTLs for milk production, reproduction, growth and carcass traits. The genes and QTLs reported in this study provide insight into selection signals shaping the genome of buffalo breeds. Our findings can aid in further genomic association studies, genomic prediction, and the implementation of breeding programmes in Indian buffaloes. [ABSTRACT FROM AUTHOR]

• Combination of MAF-LD with Delta, F ST & FIFS methods enabled the selection of SNPs for breed purity. • 582 SNPs accurately assigned individuals to their respective breeds. • 63 Tharparkar-specific SNPs annotate to candidate genes of important phenotypic traits. Tharparkar cattle breed is widely known for its superior milch quality and hardiness attributes. This study aimed to develop an ultra-low density breed-specific single nucleotide polymorphism (SNP) genotype panel to accurately quantify Tharparkar populations in biological samples. In this study, we selected and genotyped 72 Tharparkar animals randomly from Cattle & Buffalo Farm of IVRI, India. This Bovine SNP50 BeadChip genotypic datum was merged with the online data from six indigenous cattle breeds and five taurine breeds. Here, we used a combination of pre-selection statistics and the MAF-LD method developed in our laboratory to analyze the genotypic data obtained from 317 individuals of 12 distinct breeds to identify breed-informative SNPs for the selection of Tharparkar cattle. This methodology identified 63 unique Tharparkar-specific SNPs near intermediate gene frequencies. We report several informative SNPs in genes/QTL regions affecting phenotypes or production traits that might differentiate the Tharparkar breed. [ABSTRACT FROM AUTHOR]