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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]

Single nucleotide polymorphisms (SNPs) have now replaced microsatellite markers in several species for various genetic investigations like parentage assignment, genetic breed composition, assessment for individuality and, most popularly, as a useful tool in genomic selection. However, such a resource, which can offer to assist breed identification in a cost-effective manner is still not explored in cattle breeding programs. In our study, we have tried to describe methods for reducing the number of SNPs to develop a breed-specific panel. We have used SNP data from Dryad open public access repository. Starting from a global dataset of 178 animals belonging to 10 different breeds, we selected five panels each comprising of similar number of SNPs using different methods i.e., Delta, Pairwise Wright's FST, informativeness for assignment, frequent item feature selection (FIFS) and minor allele frequency–linkage disequilibrium (MAF-LD) based method. MAF-LD based method has been recently developed by us for construction of breed-specific SNP panels. The STRUCTURE software analysis of MAF-LD based method showed appropriate clustering in comparison to other panels. Later, the panel of 591 breed-specific SNPs was called to their respective breeds using Venny 2.1.0 and UGent web tools software. Breed-specific SNPs were later annotated by using various Bioinformatics softwares. [ABSTRACT FROM AUTHOR]

The present study in the 5’ upstream region of TLR4 gene revealed four Single Nucleotide Polymorphisms (SNPs) in Vrindavani and Tharparkar cattle. The polymorphic information content (PIC), heterozygosity and allelic diversity values were low to moderate for these SNPs. In Vrindavani cattle, one SNP was found to be in Hardy-Weinberg Equilibrium (HWE) and the remaining three were found to be in linkage disequilibrium (LD) as indicated statistically (P > 0.05). In Tharparkar cattle, two SNPs were found to be in HWE and were not in LD as indicated statistically (P > 0.05). These SNPs were used for construction of haplotypes. In-silico analysis of these SNPs predicted abolition of eight transcription factor binding sites and creation of eight new sites. The quantitative real time PCR analysis did not show any significant variation of gene expression among haplotypes. However, gene expression between breed was found to be significant (P < 0.05) which suggested that upstream region of bovine TLR4 gene has a crucial role in its expression. These findings in TLR4 gene offer essential evidence that can be useful in future research exploring its role in immunity. TLR4 can be used as a marker for selection for disease resistance in bovines. [ABSTRACT FROM AUTHOR]

A total of 129 crossbred cows were selected to explore the genotypic and expression profiling of partial TNF-α gene and its association with mastitis susceptibility. Two exon spanning region of TNF-α gene (221 bp and 239 bp) were amplified by Polymerase Chain Reaction (PCR). The different genotypic analysis by SSCP revealed that 221 bp fragment was monomorphic, whereas 239 bp was polymorphic. Association studies revealed that AA genotypes of 239 bp were more prevalent in mastitis group and the mRNA expression of TNF-α was significantly (P < 0.05) higher in AA genotypic animals compare to AB and BB. This suggested that genotypes AB and BB may be used as candidate markers for mastitis resistance selection in dairy cattle. [ABSTRACT FROM AUTHOR]