Unraveling genetic admixture in the Indian crossbred cattle by different approaches using Bovine 50K BeadChip

Whole-genome resequencing deciphers patterns of genetic diversity, phylogeny, and evolutionary dynamics in Kashmir cattle

Kashmir cattle, which were kept by local pastoralists for centuries, are exceptionally resilient and adaptive to harsh environments. Despite its significance, the genomic characteristics of this cattle breed remain elusive. This study utilized whole genome sequences of Kashmir cattle (n = 20; newly sequenced) alongside published whole genomes of 32 distinct breeds and seven core cattle populations (n = 135). The analysis identified ~25.87 million biallelic single nucleotide polymorphisms in Kashmir cattle, predominantly in intergenic and intron regions. Population structure analyses revealed distinct clustering patterns of Kashmir cattle with proximity to the South Asian, African and Chinese indicine cattle populations. Genetic diversity analysis of Kashmir cattle demonstrated lower inbreeding and greater nucleotide diversity than analyzed global breeds. Homozygosity runs indicated less consanguineous mating in Kashmir cattle compared with European taurine breeds. Furthermore, six selection sweep detection methods were used within Kashmir cattle and other cattle populations to identify genes associated with vital traits, including immunity (BOLA-DQA5, BOLA-DQB, TNFAIP8L, FCRL4, AOAH, HIF1AN, FBXL3, MPEG1, CDC40, etc.), reproduction (GOLGA4, BRWD1, OSBP2, LEO1 ADCY5, etc.), growth (ADPRHL1, NRG2, TCF12, TMOD4, GBP4, IGF2, RSPO3, SCD, etc.), milk composition (MRPS30 and CSF1) and high-altitude adaptation (EDNRA, ITPR2, AGBL4 and SCG3). These findings provide essential genetic insights into the characteristics and establish the foundation for the scientific conservation and utilization of Kashmir cattle breed.

Deciphering climate resilience in Indian cattle breeds by selection signature analyses

The signature of selection is a crucial concept in evolutionary biology that refers to the pattern of genetic variation which arises in a population due to natural selection. In the context of climate adaptation, the signature of selection can reveal the genetic basis of adaptive traits that enable organisms to survive and thrive in changing environmental conditions. Breeds living in diverse agroecological zones exhibit genetic "footprints" within their genomes that mirror the influence of climate-induced selective pressures, subsequently impacting phenotypic variance. It is assumed that the genomes of animals residing in these regions have been altered through selection for various climatic adaptations. These regions are known as signatures of selection and can be identified using various summary statistics. We examined genotypic data from eight different cattle breeds (Gir, Hariana, Kankrej, Nelore, Ongole, Red Sindhi, Sahiwal, and Tharparkar) that are adapted to diverse regional climates. To identify selection signature regions in this investigation, we used four intra-population statistics: Tajima's D, CLR, iHS, and ROH. In this study, we utilized Bovine 50 K chip data and four genome scan techniques to assess the genetic regions of positive selection for high-temperature adaptation. We have also performed a genome-wide investigation of genetic diversity, inbreeding, and effective population size in our target dataset. We identified potential regions for selection that are likely to be caused by adverse climatic conditions. We observed many adaptation genes in several potential selection signature areas. These include genes like HSPB2, HSPB3, HSP20, HSP90AB1, HSF4, HSPA1B, CLPB, GAP43, MITF, and MCHR1 which have been reported in the cattle populations that live in varied climatic regions. The findings demonstrated that genes involved in disease resistance and thermotolerance were subjected to intense selection. The findings have implications for marker-assisted breeding, understanding the genetic landscape of climate-induced adaptation, putting breeding and conservation programs into action.

Detection of genome-wide copy number variation in Murrah buffaloes

Riverine Buffaloes, especially the Murrah breed because of their adaptability to harsh climatic conditions, is farmed in many countries to convert low-quality feed into valuable dairy products and meat. Here, we investigated the copy number variations (CNVs) in 296 Murrah buffalo using the Axiom® Buffalo Genotyping Array 90K (Affymetrix, Santa Clara, CA, USA). The CNVs were detected on the autosomes, using the Copy Number Analysis Module (CNAM) using the univariate analysis. 7937 CNVs were detected in 279 Buffaloes, the average length of the CNVs was 119,048.87 bp that ranged between 7800 and 4,561,030 bp. These CNVs were accounting for 10.33% of the buffalo genome, which was comparable to cattle, sheep, and goat CNV analyses. Further, CNVs were merged and 1541 CNVRs were detected using the Bedtools-mergeBed command. 485 genes were annotated within 196 CNVRs that were identified in at least 10 animals of Murrah population. Out of these, 40 CNVRs contained 59 different genes that were associated with 69 different traits. Overall, the study identified a significant number of CNVs and CNVRs in the Murrah breed of buffalo, with a wide range of lengths and frequencies across the autosomes. The identified CNVRs contained genes associated with important traits related to production and reproduction, making them potentially important targets for future breeding and genetic improvement efforts.

Potential status of A1 and A2 variants of bovine beta-casein gene in milk samples of Indian cattle breeds

This study aimed to determine the polymorphism in 7th exon of beta-casein gene (CSN2) gene in seven domestic (Kosali, Tharparkar, Gangatiri, Sahiwal, Gir, Khariar, Motu) and two exotic cattle breeds (Jersey and Holstein-Friesian). Genomic DNA was extracted from 1000 milk samples, and the C > A polymorphism in CSN2 was determined using the tetra-primer amplification refractory mutation system-polymerase chain reaction method. In all Indigenous cattle breeds, the mean frequency of A1A2 and A2A2 genotypes was 0.19 and 0.80, respectively. The A1A1 genotype was absent in all seven domestic cattle breeds. The frequency of the A2A2 genotype was highest in the Gir breed (0.93). However, the Sahiwal, Tharparkar, and Motu breeds also had a higher frequency of A2A2 genotype compared to other breeds. In contrast, Gangatiri breed of India showed lowest frequency of A2A2 genotype. The mean A1 and A2 allele frequency was 0.09 and 0.91, respectively. In exotic breeds, the mean frequencies of the A1A1, A1A2, and A2A2 genotypes were 0.42, 0.55, and 0.03, respectively. Similarly, the mean A1 and A2 allele frequency was 0.69 and 0.31, respectively. This study suggests the high potential of Gir, Sahiwal, Tharparkar, and Motu cattle for A2 milk production since they carry a favorable A2 genotype.

Signatures of selection in riverine buffalo populations revealed by genome-wide SNP data

The detection of selection signatures assists in understanding domestication, evolution, and the identification of genomic regions related to adaptation and production traits in buffaloes. The emergence of high-throughput technologies like Next Generation Sequencing and SNP genotyping had expanded our ability to detect these signatures of selection. In this study, we sought to identify signatures of selection in five buffalo populations (Brazilian Murrah, Bulgarian Murrah, Indian Murrah, Nili-Ravi, and Kundi) using Axiom Buffalo 90 K Genotyping Array data. Using seven different methodologies (Tajima's D, CLR, ROH, iHS, FST, FLK and hapFLK), we identified selection signatures in 374 genomic regions, spanning a total of 381 genes and 350 quantitative trait loci (QTLs). Among these, several candidate genes were associated with QTLs for milk production, reproduction, growth and carcass traits. The genes and QTLs reported in this study provide insight into selection signals shaping the genome of buffalo breeds. Our findings can aid in further genomic association studies, genomic prediction, and the implementation of breeding programmes in Indian buffaloes.

Uncovering genes underlying coat color variation in indigenous cattle breeds through genome-wide positive selection

The identification of candidate genes related to pigmentation and under selective sweep provides insights into the genetic basis of pigmentation and the evolutionary forces that have shaped this variation. The selective sweep events in the genes responsible for normal coat color in Indian cattle groups are still unknown. To find coat color genes displaying signs of selective sweeps in the indigenous cattle, we compiled a list of candidate genes previously investigated for their association with coat color and pigmentation. After that, we performed a genome-wide scan of positive selection signatures using the BovineSNP50K Bead Chip in 187 individuals of seven indigenous breeds. We applied a wide range of methods to find evidence of selection, such as Tajima's D, CLR, iHS, varLD, ROH, and FST. We found a total of sixteen genes under selective sweep, that were involved in coat color and pigmentation physiology. These genes are CRIM1 in Gir, MC1R in Sahiwal, MYO5A, PMEL and POMC in Tharparkar, TYRP1, ERBB2, and ASIP in Red Sindhi, MITF, LOC789175, PAX3 and TYR in Ongole, and IRF2, SDR165 and, KIT in Nelore, ADAMTS19 in Hariana. These genes are related to melanin synthesis, the biology of melanocytes and melanosomes, and the migration and survival of melanocytes during development.

Trajectory of livestock genomics in South Asia: A comprehensive review

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.