Copy Number Variants in Two Northernmost Cattle Breeds Are Related to Their Adaptive Phenotypes

Leveraging Whole-Genome Resequencing to Uncover Genetic Diversity and Promote Conservation Strategies for Ruminants in Asia

Whole-genome resequencing (WGRS) is a critical branch of whole-genome sequencing (WGS), primarily targeting species with existing reference genomes. By aligning sequencing data to the reference genome, WGRS enables precise detection of genetic variations in individuals or populations. As a core technology in genomic research, WGS holds profound significance in ruminant studies. It not only reveals the intricate structure of ruminant genomes but also provides essential data for deciphering gene function, variation patterns, and evolutionary processes, thereby advancing the exploration of ruminant genetic mechanisms. However, WGS still faces several challenges, such as incomplete and inaccurate genome assembly, as well as the incomplete annotation of numerous unknown genes or gene functions. Although WGS can identify a vast number of genomic variations, the specific relationships between these variations and phenotypes often remain unclear, which limits its potential in functional studies and breeding applications. By performing WGRS on multiple samples, these assembly challenges can be effectively addressed, particularly in regions with high repeat content or complex structural variations. WGRS can accurately identify subtle variations among different individuals or populations and further elucidate their associations with specific traits, thereby overcoming the limitations of WGS and providing more precise genetic information for functional research and breeding applications. This review systematically summarizes the latest applications of WGRS in the analysis of ruminant genetic structures, genetic diversity, economic traits, and adaptive traits, while also discussing the challenges faced by this technology. It aims to provide a scientific foundation for the improvement and conservation of ruminant genetic resources.

Applications of Next-Generation Sequencing Technologies and Statistical Tools in Identifying Pathways and Biomarkers for Heat Tolerance in Livestock

The climate change-associated abnormal weather patterns negatively influences the productivity and performance of farm animals. Heat stress is the major detrimental factor hampering production, causing substantial economic loss to the livestock industry. Therefore, it is important to identify heat-tolerant breeds that can survive and produce optimally in any given environment. To achieve this goal, a clearer understanding of the genetic differences and the underlying molecular mechanisms associated with climate change impacts and heat tolerance are a prerequisite. Adopting next-generation biotechnological and statistical tools like whole transcriptome analysis, whole metagenome sequencing, bisulphite sequencing, genome-wide association studies (GWAS), and selection signatures provides an opportunity to achieve this goal. Through these techniques, it is possible to identify permanent genetic markers for heat tolerance, and by incorporating those markers in marker-assisted breeding selection, it is possible to achieve the target of breeding for heat tolerance in livestock. This review gives an overview of the recent advancements in assessing heat tolerance in livestock using such 'omics' approaches and statistical models. The salient findings from this research highlighted several candidate biomarkers that have the potential to be incorporated into future heat-tolerance studies. Such approaches could revolutionise livestock production in the changing climate scenario and support the food demands of the growing human population.

Genome-Wide Scan for Copy Number Variations in Chinese Merino Sheep Based on Ovine High-Density 600K SNP Arrays

Sheep are a vital species in the global agricultural economy, providing essential resources such as meat, milk, and wool. Merino sheep (Junken type) are a key breed of fine wool sheep in China. However, research on fine wool traits has largely overlooked the role of SNPs and their association with phenotypes. Copy number variations (CNVs) have emerged as one of the most important sources of genetic variation, influencing phenotypic traits by altering gene expression and dosage. To generate a comprehensive CNVR map of the ovine genome, we conducted genome-wide CNV detection using genotyping data from 285 fine wool sheep. This analysis revealed 656 CNVRs, including 628 on autosomes and 28 on the X chromosome, covering a total of 43.9 Mbs of the sheep genome. The proportion of CNVRs varied across chromosomes, from 0.45% on chromosome 26 to 3.72% on chromosome 10. Functional annotation through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses highlighted significantly enriched GO terms, including odorant binding, ATP binding, and sulfuric ester hydrolase activity. The KEGG analysis identified involvement in pathways such as neuroactive ligand-receptor interaction, axon guidance, ECM-receptor interaction, the one-carbon pool by folate, and focal adhesion (p < 0.05). To validate these CNVRs, we performed quantitative real-time PCR experiments to verify copy number predictions made by PennCNV software (v1.0.5). Out of 11 selected CNVRs with predicted gain, loss, or gain-loss statuses, 8 (IDs 68, 156, 201, 284, 307, 352, 411, 601) were successfully confirmed. This study marks a significant step forward in mapping CNVs in the ovine genome and offers a valuable resource for future research on genetic variation in sheep.

Identification of the genetic characteristics of copy number variations in experimental specific pathogen-free ducks using whole-genome resequencing

BACKGROUND

Specific pathogen-free ducks are a valuable laboratory resource for waterfowl disease research and poultry vaccine development. High throughput sequencing allows the systematic identification of structural variants in genomes. Copy number variation (CNV) can explain the variation of important duck genetic traits. Herein, the genome-wide CNVs of the three experimental duck species in China (Jinding ducks (JD), Shaoxing ducks (SX), and Fujian Shanma ducks (SM)) were characterized using resequencing to determine their genetic characteristics and selection signatures.

RESULTS

We obtained 4,810 CNV regions (CNVRs) by merging 73,012 CNVs, covering 4.2% of the duck genome. Functional analysis revealed that the shared CNVR-harbored genes were significantly enriched for 31 gene ontology terms and 16 Kyoto Encyclopedia of Genes and Genomes pathways (e.g., olfactory transduction and immune system). Based on the genome-wide fixation index for each CNVR, growth (SPAG17 and PTH1R), disease resistance (CATHL3 and DMBT1), and thermoregulation (TRPC4 and SLIT3) candidate genes were identified in strongly selected signatures specific to JD, SM, and SX, respectively.

CONCLUSIONS

In conclusion, we investigated the genome-wide distribution of experimental duck CNVs, providing a reference to establish the genetic basis of different phenotypic traits, thus contributing to the management of experimental animal genetic resources.

Genetic Structure Analysis of 155 Transboundary and Local Populations of Cattle (Bos taurus, Bos indicus and Bos grunniens) Based on STR Markers

Every week, 1-2 breeds of farm animals, including local cattle, disappear in the world. As the keepers of rare allelic variants, native breeds potentially expand the range of genetic solutions to possible problems of the future, which means that the study of the genetic structure of these breeds is an urgent task. Providing nomadic herders with valuable resources necessary for life, domestic yaks have also become an important object of study. In order to determine the population genetic characteristics, and clarify the phylogenetic relationships of modern representatives of 155 cattle populations from different regions of the world, we collected a large set of STR data (10,250 individuals), including unique native cattle, 12 yak populations from Russia, Mongolia and Kyrgyzstan, as well as zebu breeds. Estimation of main population genetic parameters, phylogenetic analysis, principal component analysis and Bayesian cluster analysis allowed us to refine genetic structure and provided insights in relationships of native populations, transboundary breeds and populations of domestic yak. Our results can find practical application in conservation programs of endangered breeds, as well as become the basis for future fundamental research.