Genome-wide runs of homozygosity signatures in diverse Indian goat breeds

Genomic advancements in goat breeding: enhancing productivity, disease resistance, and sustainability in India's rural economy

Goats are vital to the rural economy of India, contributing significantly to livelihoods, nutrition, and agricultural sustainability. With a population of 148.88 million, India holds the world's largest goat population, comprising 41 recognized indigenous breeds. These goats provide milk, meat, and fiber, particularly in marginal environments. The genomic advancements in goat research have revolutionized the understanding of genetic diversity, adaptation, and trait improvement. Whole-genome sequencing (WGS), single nucleotide polymorphism (SNP) arrays and transcriptomics have unveiled genetic markers associated with production, disease resistance, and reproductive traits. Genomic tools such as the Illumina Goat SNP50K BeadChip and high-throughput sequencing technologies have facilitated the identification of selection signatures and quantitative trait loci (QTL), influencing economically important traits like milk yield, meat quality, and prolificacy. Notably, genes such as DGAT1, GHR, BMPR1B, and HSP70 have been linked to production efficiency, reproductive performance, and climate resilience. Genome-wide association studies (GWAS) and genomic selection (GS) have enabled precision breeding, enhancing genetic gains and reducing inbreeding risks. The application of RNA sequencing has provided insights into gene expression patterns governing lactation, growth, and reproductive efficiency. Epigenomic studies, focusing on DNA methylation and histone modifications, have highlighted regulatory mechanisms underpinning prolificacy and muscle development. Conservation genomics has played a pivotal role in safeguarding native breeds by assessing genetic diversity and mitigating inbreeding depression. Indicine goat breeds, such as Jamunapari, Beetal, Barbari, and Black Bengal, exhibit unique genetic adaptations to diverse agro-climatic conditions, emphasizing the need for their conservation. Emerging technologies, including CRISPR-Cas9 gene editing, hold promise for precision breeding to enhance productivity and disease resistance. Integrating genomics with artificial intelligence (AI) and big data analytics is poised to revolutionize goat breeding and management. Future efforts should focus on expanding genomic databases, developing breed-specific reference genomes, and promoting genomic literacy among farmers to ensure sustainable goat production and improve rural livelihoods in India.

Cataloging copy number variation regions and allied diversity in goat breeds spanning pan India

Huge genetic diversity is evident among the diverse goat breeds in terms of production, reproduction, adaptability, growth, disease resistance and thermo-tolerance. This diversity is an outcome of both natural and artificial selection acting on the caprine genome over the years. A fine characterization of whole genome variation is now possible by employing Next Generation Sequencing (NGS) technologies. To explore underlying genetics, genome-wide analysis of genetic markers is the best resolution. The study strived to capture variation in terms of CNV/CNVRs among 11 Indian goat breeds. In this study, the first ever resequencing-based CNV/CNVR distribution of Indigenous goat breeds was delineated, providing a sizable addition to the prior caprine CNVRs reported. Different diversity metrics were analyzed using identified CNVR. Principal component analysis (PCA) showed separate clustering of Kanniadu (KAN) and Jharkhand Black (JB) from other breeds under the study, indicating their unique genetic profile as the former breeds were sampled from institutional farms. The admixture analysis and introgression revealed by f3 statistics suggested distinct genetic structuring of JB, KAN and TEL(Tellicherry) as compared to the rest of the studied populations. Apart from this, we also identified 32 selection signatures through VST (Variance-stabilizing transformation) method and key genes such as ZBTB7C, BHLHE22, AGT were found elucidating the genetic architecture of hot and cold adaptation in Indian goats. Information generated hereby in the form of 32,711 autosomal CNVRs and the custom scripts ( https://github.com/kkokay07/Climate-Variables-Analysis.git , https://github.com/chau-mau/SelectCNVR.git and https://github.com/chau-mau/CNVrecaller.git ) will be of relevance in further studies on copy number based genetics.

Runs of homozygosity assessment using reduced representation sequencing highlight the evidence of random mating in emu (Dromaius novaehollandiae)

The domestication of emu (Dromaius novaehollandiae) began in the 1970s, but their productive characteristics have not undergone significant genetic enhancement. This study investigated the inbreeding and genetic diversity of 50 emus from various farms in Japan using Double digest restriction-site associated DNA sequencing (ddRAD-seq) markers. Single nucleotide polymorphism (SNP) calling revealed 171 975 high-quality SNPs while runs of homozygosity (ROH) analysis identified 1843 homozygous segments, with an average of 36.86 ROH per individual and a mean genome length of 27 Mb under ROH. The majority (86%) of ROH were short (0.5-1 Mb), indicating ancient or remote inbreeding. The average genomic inbreeding coefficient (FROH) was 0.0228, suggesting nearly no inbreeding. Overlapping ROH regions were identified, with top consensus regions found on chromosomes 8 and Z. Seven candidate genes related to egg production, feather development, and energy metabolism were annotated in these regions. The findings highlight the prevalence of genetic diversity and low inbreeding levels in the studied emu population. This research highlights the potentiality of random mating in genetic management and conservation of emus. Further studies should focus on enhancing productive traits through selective breeding while preserving genetic diversity to ensure the sustainable growth of the emu farming.

Insights from homozygous signatures of cervus nippon revealed genetic architecture for components of fitness

This study investigates the genomic landscape of Sika deer populations, emphasizing the detection and characterization of runs of homozygosity (ROH) and their contribution towards components of fitness. Using 85,001 high-confidence SNPs, the investigation into ROH distribution unveiled nuanced patterns of autozygosity across individuals especially in 2 out of the 8 farms, exhibiting elevated ROH levels and mean genome coverage under ROH segments. The prevalence of shorter ROH segments (0.5-4 Mb) suggests historical relatedness and potential selective pressures within these populations. Intriguingly, despite observed variations in ROH profiles, the overall genomic inbreeding coefficient (FROH) remained relatively low across all farms, indicating a discernible degree of genetic exchange and effective mitigation of inbreeding within the studied Sika deer populations. Consensus ROH (cROH) were found to harbor genes for important functions viz., EGFLAM gene which is involved in the vision function of the eye, SKP2 gene which regulates cell cycle, CAPSL involved in adipogenesis, SPEF2 which is essential for sperm flagellar assembly, DCLK3 involved in the heat stress. This first ever study on ROH in Sika deer, to shed light on the adaptive role of genes in these homozygous regions. The insights garnered from this study have broader implications in the management of genetic diversity in this vulnerable species.

[Runs of Homozygosity Decipher Genetic Diversity in Cattle Breed Dwelling in the Colder Regions of the World]

BACKGROUND

Our study focuses on Yakutian cattle, a Siberian native breed, examining its inbreeding and diversity through genome-wide analysis of runs of homozygosity (ROHs). Yakutian cattle are adapted to Siberia's harsh sub-arctic conditions, enduring temperatures below -70°C. However, the population genetics studies on this breed are scanty, to document the genetic uniqueness in these cattle.

RESULTS

We analyzed 40 Yakutian cattle with strict quality control for ROH detection yielding 683 homozygous segments, averaging 17 per individual with an average length of 9 Mb. ROH regions were found to be involved in important pathways pertaining to cold adaptation. Autozygosity ranged from 1% to 12% of the genome, with a relatively low average inbreeding coefficient (FROH) of 0.057, as compared to other breeds. Also, the different diversity indicators, namely, principal component analysis, heterozygosity, and effective population size analysis, revealed the prevalence of genetic diversity within the breed.

CONCLUSION

Our findings on ROH are the first of its kind in Yakutian cattle that support their adaptability to colder environments, as evidenced by low inbreeding and high genetic diversity.

Genomic Inbreeding and Runs of Homozygosity Analysis of Cashmere Goat

Cashmere goats are valuable genetic resources which are famous worldwide for their high-quality fiber. Runs of homozygosity (ROHs) have been identified as an efficient tool to assess inbreeding level and identify related genes under selection. However, there is limited research on ROHs in cashmere goats. Therefore, we investigated the ROH pattern, assessed genomic inbreeding levels and examined the candidate genes associated with the cashmere trait using whole-genome resequencing data from 123 goats. Herein, the Inner Mongolia cashmere goat presented the lowest inbreeding coefficient of 0.0263. In total, we identified 57,224 ROHs. Seventy-four ROH islands containing 50 genes were detected. Certain identified genes were related to meat, fiber and milk production (FGF1, PTPRM, RERE, GRID2, RARA); fertility (BIRC6, ECE2, CDH23, PAK1); disease or cold resistance and adaptability (PDCD1LG2, SVIL, PRDM16, RFX4, SH3BP2); and body size and growth (TMEM63C, SYN3, SDC1, STRBP, SMG6). 135 consensus ROHs were identified, and we found candidate genes (FGF5, DVL3, NRAS, KIT) were associated with fiber length or color. These findings enhance our comprehension of inbreeding levels in cashmere goats and the genetic foundations of traits influenced by selective breeding. This research contributes significantly to the future breeding, reservation and use of cashmere goats and other goat breeds.