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• We have identified genes by GWAS which are involved in well-established MAPK and PI3K-AKT signalling pathways, affecting biochemical process of coat colour production. • Due to introduction of exotic blood to continue the process of development of Vrindavani cattle, a very low F ST value was observed suggesting outbreeding of the population. • This work provides a preliminary information to carry forward researches on genomic basis of coat colour patterns in crossbred cattle Coat colour and various patterns are the hallmarked qualitative traits studied in cattle as well as other livestock; however, variation in this trait is resultant of interactions and epistasis of a set of genes rather than being a product of a single gene. In this study, GWAS has been conducted from 50K SNP genotype data, with a stratified approach on Vrindavani cattle (n=48). The study was conducted in two sets of an experiment wherein set I treats all the solid colours (n=18) as controls and rest spotted or patchy types as cases (n=30), and set II treats brown and brown with white spots as controls (n=15), and rest as cases (n=33). After quality check (MAF>0.01, genotyping rate>90%, and H-W equilibrium at p≤ 0.001) of genotype data, 37247 SNPs were further used for accomplishing Genome-Wide Association Study (GWAS) with coat colour. The distinct phenotypes were classified into four different sub-groups that are solid black, black with white patches, solid brown, and brown with white patches along with greyish white. The allele frequency difference was checked in all sub-groups. The GWAS was conducted in PLINK v1.7 and for graphical representation R was used. Two SNPs in set I and 20 in set II were found to be significantly associated with coat colour in Vrindavani cattle. A ±500 Kb genome scan around the significant SNPs revealed gene BDNF for SNP DIAS-217 in set I and FGF18 for SNP ARS-BFGL-NGS-105192, and CACNA2D1 , and HGF for SNP BTB-01885061 in set II, are present around these SNPs. In KEGG-based pathway enrichment analysis, all the above-mentioned genes were found to be involved in well-established MAPK and PI3K-AKT signalling pathways, affecting the biochemical process of coat colour production. Genome-wide F ST values were low to moderate across the genome, however few associated SNPs had moderate to high F ST values indicating their power in differentiating the subgroups according to coat colour phenotype. This study provides a preliminary report of markers and genes involved in coat colour expression and revealed that the reported genes around the associated SNPs are involved in brown with white spotting phenotype. However, further researches in this field are essential for a more conclusive result. [ABSTRACT FROM AUTHOR]

• The natural and artificial selection are expected to impose pressure on specific genomic regions and leave footprints called as "selection signatures" • We identified selective sweep regions based on Runs of Homozygosity (ROH) and Integrated Haplotype Score (iHS) • Highlighted candidate genes related to adaptation and production traits Knowledge about genetic diversity and selection signatures are very essential for the management and sustainable utilization of sheep genetic resources in India. In this study, we performed a comprehensive genome-wide analysis of genetic diversity and selection signatures using SNP data. A total of 79 animals from three Indian sheep breeds: Changthangi (n = 29), Deccani (n = 24), and Garole (n = 26) genotyped with Illumina Ovine SNP50 BeadChip were included in this study. The average minor allele frequency was 0.284 with a standard deviation of 0.129. The overall mean observed (H O) and expected heterozygosity (H E) were 0.369±0.141 and 0.373±0.118, respectively. The proportion of polymorphic SNPs (P N) ranged from 0.84 (Garole) to 0.93 (Changthangi). The average pairwise genetic distance (D) ranged from 0.301 (Garole) to 0.313 (Changthangi). We identified a total of 9244 ROH segments and the genomic inbreeding coefficients ranged from 0.0673 (Deccani) to 0.1779 (Garole). Two different statistical approaches (ROH and iHS) revealed selection signatures in 37 genomic regions mapping to 188 genes across 16 of the 26 autosomes in three sheep breeds. The selective sweeps provide new insights into the local adaptation and production potential of three Indian sheep breeds. Some notable candidate genes include the TRPM8 gene involved in cold adaptation, JADE2, PLEKHB2, SPP2, TSHR, and UBE2B genes associated with meat quality traits, and the PPP3CA gene associated with fecundity. [ABSTRACT FROM AUTHOR]

• Owing to developments in high-throughput technologies, the genome-wide detection of selection signatures has become more common in recent years • Various statistical methods have been developed for the identification of selection signatures based on site frequency spectrum, linkage disequilibrium, reduced local variability, and population differentiation. • In future, the advanced Machine Learning enabled neural networks can also be applied in livestock populations to handle large &complex data sets efficiently and to improve the accuracy of detection of selection signals. • In this review, we have discussed the results of significant studies done in the recent years. Livestock populations have been consistently improving in terms of performance and productivity by selective breeding over the centuries. These selection strategies are expected to leave footprints in the genome that are identified as selection signatures. Due to advances in high-throughput technologies, the genome-wide detection of selection signatures has become more widespread in recent years. Such studies provide insights into the domestication and evolutionary processes that resulted in a huge number of livestock breeds able to live in diverse environments and production systems. Furthermore, these studies facilitate the identification of candidate genes under selection that are associated with economically important traits in livestock populations. Various statistical methods have been developed for the detection of selection signatures based on site frequency spectrum, linkage disequilibrium, reduced local variability, and population differentiation. The objectives of this review are to give a comprehensive overview of the general concept, various methodologies, and bioinformatics tools currently available for the detection of selective sweeps and to summarize the results of recent selection signature studies carried out in various livestock species. [ABSTRACT FROM AUTHOR]

• The Indian Ghurrah pig has a mixture of European and Asian inheritance. • Analysis traced European admixture to the recent past. • Signs of interspecies introgression was detected in admixture analysis. • Ghurrah and Asian pigs show divergence in genomic regions governing teeth development. The evolution and domestication of pigs is a complex and ongoing process. Despite its rich biodiversity and proximity to the geographical origins of Sus scrofa domesticus, the place of Indian pigs in the global phylogeny is unclear. Using microarray-derived (porcine 60K SNP chip) genotypes of 11 Ghurrah pigs from North-Western India and a public dataset comprising 2113 pigs of 146 breeds, we determined the genomic ancestry of Ghurrah pigs and compared their genetic constitution to European and Asian breeds to ascertain signatures of divergent selection. Results showed that Ghurrah pigs contain genes of Asian and European ancestry with signs of inter-species introgression. Using Admixture LD – decay statistics, the European admixture event was dated to the recent past, coinciding with the start of cross-breeding efforts in India. The complex Asian ancestry pattern of the breed resembled that of wild boars of South – Central China and Thailand, possibly suggesting introgression from an Indian wild boar relative. Signatures of selection analysis showed the divergence of Ghurrah pigs from Asian and European breeds in genomic regions associated with odontogenesis, and nervous system processess, respectively. Our results present the first genomic characterization of an Indian pig breed using dense microarray-derived genotypes and highlight the importance of further genomic characterization of Indian domestic and wild pigs. Given the limited sample size available for this study, validation of the findings in a larger population is suggested. [ABSTRACT FROM AUTHOR]