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Balancing selection is the process of selection that preserves various alleles within a population. Studying the areas undergoing balancing selection is essential, because it preserves genetic diversity in a population. Finding genes that exhibit signs of balancing selection during the domestication of cattle is the goal of this study. To identify regions where polymorphism has persisted in the cattle population for millions of years, we examined the genome of cattle. In this study, we used bovine SNP 50 k data to conduct a detailed genome-wide assessment of selection signatures for balancing selection. We have included the genotyped data from 427 animals, including five taurines, two crossbreds, and eight Indian cattle breeds. For this study, we employed Tajima's D approach to identify signature regions undergoing balancing selection. Using the NCBI database, PANTHER 17.0, and CattleQTL database, the annotation was carried out after finding the relevant areas under balancing selection. The number of genomic regions undergoing balancing selection in Ayrshire, Brown-Swiss, Frieswal, Gir, Guernsey, Hariana, Holstein Friesian, Jersey, Kankrej, Nelore, Ongole, Red Sindhi, Sahiwal, Tharparkar, and Vrindavani was 11, 13, 13, 19, 18, 11, 17, 14, 14, 12, 10, 12, 13, 13, and 11, respectively. We have observed multiple immune system-related genes going through balancing selection, including KIT, NFATC2, GBP4, LRRC32, SYT7, RAG1, RAG2, LOC513659, and ZBTB17. In our study, we found that the majority of the immune-related genes and a few genes associated with growth, reproduction, production, and adaptation are undergoing balancing selection. [ABSTRACT FROM AUTHOR]

Half a century ago, a seminal article on the hitchhiking effect by Smith and Haigh inaugurated the concept of the selection signature. Selective sweeps are characterised by the rapid spread of an advantageous genetic variant through a population and hence play an important role in shaping evolution and research on genetic diversity. The process by which a beneficial allele arises and becomes fixed in a population, leading to a increase in the frequency of other linked alleles, is known as genetic hitchhiking or genetic draft. Kimura's neutral theory and hitchhiking theory are complementary, with Kimura's neutral evolution as the 'null model' and positive selection as the 'signal'. Both are widely accepted in evolution, especially with genomics enabling precise measurements. Significant advances in genomic technologies, such as next‐generation sequencing, high‐density SNP arrays and powerful bioinformatics tools, have made it possible to systematically investigate selection signatures in a variety of species. Although the history of selection signatures is relatively recent, progress has been made in the last two decades, owing to the increasing availability of large‐scale genomic data and the development of computational methods. In this review, we embark on a journey through the history of research on selective sweeps, ranging from early theoretical work to recent empirical studies that utilise genomic data. [ABSTRACT FROM AUTHOR]

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]

The process of building a model or copy of a real-world system and assessing its behaviour under various scenarios is referred to as simulation. Simulation in population genetics is the process of simulating a population's genetic makeup and evolutionary history using mathematical models and computer algorithms. It is important in population genetics for a better understanding of the impact of various evolutionary and demographic scenarios on sequence variation and patterns, it allows investigators to better assess and design analytical methods in the study of disease-associated genetic factors. This is an important tool for studying population genetic diversity and how natural selection, genetic drift, mutation, migration, and other evolutionary forces have influenced the genetic makeup of the population. There are three fundamental frameworks for simulation: coalescent, forward, and resampling methods. Numerous simulators that fit under these frameworks can be compared in terms of their evolutionary and demographic scenarios, computing complexity, and particular applications. Population simulation is becoming increasingly important in evolutionary biology, enabling researchers to explore the effects of various genetic models on genetic diversity and DNA sequence patterns. [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 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]

• The review covers livestock genomics of South Asian cattle, buffalo, sheep, goat, pig, camel, horse, yak, mithun, and poultry. • Advancements in next-generation sequencing (NGS) technologies led to the discovery of numerous SNP arrays for different livestock species. • The application of genomics in animal breeding has had the biggest economic impact on livestock production. Livestock plays a central role in sustaining human livelihood in South Asia. There are numerous and distinct livestock species in South Asian countries. Several of them have experienced genetic development in recent years due to the application of genomic technologies and effective breeding programs. This review discusses genomic studies on cattle, buffalo, sheep, goat, pig, horse, camel, yak, mithun, and poultry. The frontiers covered in this review are genetic diversity, admixture studies, selection signature research, QTL discovery, genome-wide association studies (GWAS), and genomic selection. The review concludes with recommendations for South Asian livestock systems to increasingly leverage genomic technologies, based on the lessons learned from the numerous case studies. This paper aims to present a comprehensive analysis of the dichotomy in the South Asian livestock sector and argues that a realistic approach to genomics in livestock can ensure long-term genetic advancements. [ABSTRACT FROM AUTHOR]

[Display omitted] • The availability of genomic data enables a very rapid global follow-up of COVID-19 progression. • Genomic surveillance integrates epidemiological and genomic data to track SARS-CoV-2 variants and their spread. • Genomics plays a significant role in the development of molecular diagnostics, therapeutics, and vaccine candidates. The coronavirus disease 2019 (COVID-19) quickly swept over the world, becoming one of the most devastating outbreaks in human history. Being the first pandemic in the post-genomic era, advancements in genomics contributed significantly to scientific understanding and public health response to COVID-19. Genomic technologies have been employed by researchers all over the world to better understand the biology of SARS-CoV-2 and its origin, genomic diversity, and evolution. Worldwide genomic resources have greatly aided in the investigation of the COVID-19 pandemic. The pandemic has ushered in a new era of genomic surveillance, wherein scientists are tracking the changes of the SARS-CoV-2 genome in real-time at the international and national levels. Availability of genomic and proteomic information enables the rapid development of molecular diagnostics and therapeutics. The advent of high-throughput sequencing and genome editing technologies led to the development of modern vaccines. We briefly discuss the impact of genomics in the ongoing COVID-19 pandemic in this review. [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]

Copy number variation (CNV) is a phenomenon in which sections of the genome, ranging from one kilo base pair (Kb) to several million base pairs (Mb), are repeated and the number of repeats vary between the individuals in a population. It is an important source of genetic variation in an individual which is now being utilized rather than single nucleotide polymorphisms (SNPs), as it covers the more genomic region. CNVs alter the gene expression and change the phenotype of an individual due to deletion and duplication of genes in the copy number variation regions (CNVRs). Earlier, researchers extensively utilized SNPs as the main source of genetic variation. But now, the focus is on identification of CNVs associated with complex traits. With the recent advances and reduction in the cost of sequencing, arrays are developed for genotyping which cover the maximum number of SNPs at a time that can be used for detection of CNVRs and underlying quantitative trait loci (QTL) for the complex traits to accelerate genetic improvement. CNV studies are also being carried out to understand the evolutionary mechanism in the domestication of livestock and their adaptation to the different environmental conditions. The main aim of the study is to review the available data on CNV and its role in genetic variation among the livestock. [ABSTRACT FROM AUTHOR]