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The field of genetics has evolved a lot after the emergence of molecular and advanced genomic technologies. The advent of Next Generation Sequencing, SNP genotyping platforms and simultaneous reduction in the cost of sequencing had opened the door to genomic research in farm animals. There are various applications of genomics in livestock, such as the use of genomic data: (i) to investigate genetic diversity and breed composition/population structure (ii) to identify genetic variants and QTLs related to economically important and ecological traits, genome-wide association studies (GWAS) and genomic signatures of selection; (iii) to enhance breeding programs by genomic selection. Compared to traditional methods, genomic selection is expected to improve selection response by increasing selection accuracy and reducing the generation interval due to early selection. Genomic selection (GS) in developed countries has led to rapid genetic gains, especially in dairy cattle, due to a well-established genetic evaluation system. Indian livestock system is still lagging behind developed nations in adopting these technologies. This review discusses the current status, challenges, and future perspectives of livestock genomics in India. [ABSTRACT FROM AUTHOR]

Copy number variations (CNVs) are major forms of genetic variation with an increasing importance in animal genomics. This study used the Illumina BovineSNP 50 K BeadChip to detect the genome-wide CNVs in the Tharparkar cattle. With the aid of PennCNV software, we noticed a total of 447 copy number variation regions (CNVRs) across the autosomal genome, occupying nearly 2.17% of the bovine genome. The average size of detected CNVRs was found to be 122.2 kb, the smallest CNVR being 50.02 kb in size, to the largest being 1,232.87 Kb. Enrichment analyses of the genes in these CNVRs gave significant associations with molecular adaptation-related Gene Ontology (GO) terms. Most CNVR genes were significantly enriched for specific biological functions; signaling pathways, sensory responses to stimuli, and various cellular processes. In addition, QTL analysis of CNVRs described them to be linked with economically essential traits in cattle. The findings here provide crucial information for constructing a more comprehensive CNVR map for the indigenous cattle genome. [ABSTRACT FROM AUTHOR]

The present broad range of sheep phenotypic variation is the consequence of selection for various production characteristics such as wool, milk, meat, and natural adaptability to diverse situations. In the current study, the genomic data of 79 animals from three Indian sheep breeds (Changthangi, Deccani, and Garole) were explored to decipher regions under positive selection for various productive traits using various statistical tools. We found 61, 102 regions using Tajima's D, CLR and 58, 38, and 71 regions using FST, FLK, and hapFLK, respectively, under selective sweep. Significant candidate genes related to various important traits, such as KLHL for fibre diameter and the OMA1 gene for feed-induced thermogenesis in Changthangi, were identified. In addition, the SYCP2 and NAPAS3 genes were found to be associated with seasonal reproductivity, and BMPR1B for fertilization capacity in Garole. In a previous study, the HSPA6 gene (Garole) was found to be associated with thermo-tolerance in the Angus sheep breed. The outcomes discussed here provide a basis for detecting selective sweeps that underlie genetic variations of traits that have functional importance. [ABSTRACT FROM AUTHOR]

Knowledge about genetic diversity is very essential for the management and sustainable utilization of livestock genetic resources. In this study, we presented a comprehensive genome-wide analysis of genetic diversity, ROH, inbreeding, linkage disequilibrium, effective population size and haplotype block structure in Tharparkar cattle of India. A total of 24 Tharparkar animals used in this study were genotyped with Illumina BovineSNP50 array. After quality control, 22,825 biallelic SNPs were retained, which were in HWE, MAF > 0.05 and genotyping rate >90%. The overall mean observed (HO) and expected heterozygosity (HE) were 0.339 ± 0.156 and 0.325 ± 0.129, respectively. The average minor allele frequency was 0.234 with a standard deviation of ± 0.131. We identified a total of 1832 ROH segments and the highest autosomal coverage of 13.87% was observed on chromosome 23. The genomic inbreeding coefficients estimates by FROH, FHOM, FGRM and FUNI were 0.0589, 0.0215, 0.0532 and 0.0160 respectively. The overall mean linkage disequilibrium (LD) for a total of 133,532 pairwise SNPs measured by D' and r2 was 0.6452 and 0.1339, respectively. In addition, we observed a gradual decline in effective population size over the past generations. [ABSTRACT FROM AUTHOR]

The analysis of genetic diversity is very essential to understand the evolution and adaptability of livestock species to different environmental conditions. Genetic variation is the raw material for selection and foundation for breed improvement programmes. The use of high throughput molecular marker technologies, advanced statistical and software tools have revolutionized the precision of animal genetic diversity analysis in a large number of populations with limited time and resources. SNP genotyping is one of the best methods to study genetic variation due to its abundance in livestock species, stability and cost-effectiveness. In this review, some of the most popularly used diversity analysis software programs in livestock genomics are discussed briefly. Microsatellite-based software such as Genepop, Fstat, Genetix, TFPGA, Stackpack, Arlequin and other multipurpose software such as PLINK, PowerMarker, TASSEL, BEAGLE, R software packages (GenABEL, SNPassoc, snpstats, SNP relate), Gemma, SNP Express, SVS, etc. can be utilized for diversity analysis. [ABSTRACT FROM AUTHOR]