Whole genome resequencing revealed genomic variants and functional pathways related to adaptation in Indian yak populations.

The present study aims to identify genomic variants through a whole genome sequencing (WGS) approach and uncover biological pathways associated with adaptation and fitness in Indian yak populations. A total of 30 samples (10 from each population) were included from Arunachali, Himachali and Ladakhi yak populations. WGS analysis revealed a total of 32171644, 27260825, and 32632460 SNPs and 4865254, 4429941, and 4847513 Indels in the Arunachali, Himachali, and Ladakhi yaks, respectively. Genes such as RYR2, SYNE2, BOLA, HF1, and the novel transcript ENSBGRG00000011079 were found to have the maximum number of high impact variants in all three yak populations, and might play a major role in local adaptation. Functional enrichment analysis of genes harboring high impact SNPs revealed overrepresented pathways related to response to stress, immune system regulation, and high-altitude adaptation. This study provides comprehensive information about genomic variants and their annotation in Indian yak populations, thus would serve as a data resource for researchers working on the yaks. Furthermore, it could be well exploited for better yak conservation strategies by estimating population genetics parameters viz., effective population size, inbreeding, and observed and expected heterozygosity.

Characterization of a unique Sikkimese yak population of India: a multivariate approach.

Native Sikkimese yak in Sikkim state of India is a pastoral treasure being raised through centuries-old transhumance practices and has evolved in response to natural and man-made selection. Currently, the population of Sikkimese yak is at risk with about five thousand total headcounts. Characterization is essential for taking appropriate decisions for conservation of any endangered population. In an attempt to phenotypically characterize the Sikkimese yaks, this study recorded phenotypic morphometric traits information, viz., body length (LG), height at withers (HT), heart girth (HG), paunch girth (PG), horn length (HL), horn circumference (HC), distance between horns (DbH), ear length (EL), face length (FL), face width (FW), and tail length with switch (TL), on 2154 yaks of both sexes. Multiple correlation estimation highlighted that HG and PG, DbH and FW, and EL and FW were highly correlated. Using principal component analysis, LG, HT, HG, PG, and HL were found to be the most important traits for phenotypic characterization of Sikkimese yak animals. Discriminant analysis based on different locations of Sikkim hinted at the existence of two separate clusters, however, broadly, phenotypic uniformity could be observed. Subsequent genetic characterization can offer greater insights and can pave the way for future breed registration and conservation of the population.

Novel insights into genome-wide associations in Bos indicus reveal genetic linkages between fertility and growth.

Bos indicus breed Sahiwal, famous for its optimum performance, has so far been genetically improved for performance traits based on phenotypic records and the genomic knowhow regarding genes, regions and biological processes underlying the complex quantitative traits is lacking. In this context, a Genome-wide Association Study was performed for fertility and growth traits in Sahiwal cattle to shed light on its genomic profile. A total of 46 SNPs were found associated with the traits at genome-wide suggestive threshold of P ≤ 10-4. USP32, LRPPRC, PLA2G10, RRN3 and ASAP1 were identified as putative candidate genes for body weight at different ages. However, several genes mapped for growth traits like GREB1, PLA2G10, RAD51C, BIRC6, TEX14 and PEBP4 had significant physiological underpinnings in determining fertility of the animals. Moreover, Quantitative trait loci (QTL) identification revealed potential overlaps with the already reported QTLs for both fertility and growth for most of the traits. Further, candidate SNP enrichment analysis revealed an enriched biological process for birth weight with a significant reproductive role. Based on the findings, genetic linkages underlying fertility and growth could be discerned in Sahiwal population and may be utilized for improving fertility traits in future.

Genomic Diversity Profiling and Breed-Specific Evolutionary Signatures of Selection in Arunachali Yak.

Arunachali yak, the only registered yak breed of India, is crucial for the economic sustainability of pastoralist Monpa community. This study intended to determine the genomic diversity and to identify signatures of selection in the breed. Previously available double digest restriction-site associated DNA (ddRAD) sequencing data of Arunachali yak animals was processed and 99,919 SNPs were considered for further analysis. The genomic diversity profiled based on nucleotide diversity, π (π = 0.041 in 200 bp windows), effective population size, Ne (Ne = 83) and Runs of homozygosity (ROH) (predominance of shorter length ROHs) was found to be optimum. Subsequently, 207 regions were identified to be under selective sweeps through de-correlated composite of multiple signals (DCMS) statistic which combined three individual test statistics viz. π, Tajima's D and |iHS| in non-overlapping 100 kb windows. Mapping of these regions revealed 611 protein-coding genes including KIT, KITLG, CDH12, FGG, FGA, FGB, PDGFRA, PEAR1, STXBP3, olfactory receptor genes (OR5K3, OR5H6 and OR1E1) and taste receptor genes (TAS2R1, TAS2R3 and TAS2R4). Functional annotation highlighted that biological processes like platelet aggregation and sensory perception were the most overrepresented and the associated regions could be considered as breed-specific signatures of selection in Arunachali yak. These findings point towards evolutionary role of natural selection in environmental adaptation of Arunachali yak population and provide useful insights for pursuing genome-wide association studies in future.

Understanding the genomic architecture of clinical mastitis in Bos indicus.

This study elucidated potential genetic variants and QTLs associated with clinical mastitis incidence traits in Bos indicus breed, Sahiwal. Estimated breeding values for the traits (calculated using Bayesian inference) were used as pseudo-phenotypes for association with genome-wide SNPs and further QTL regions underlying the traits were identified. In all, 25 SNPs were found to be associated with the traits at the genome-wide suggestive threshold (p ≤ 5 × 10-4) and these SNPs were used to define QTL boundaries based on the linkage disequilibrium structure. A total of 16 QTLs were associated with the trait EBVs including seven each for clinical mastitis incidence (CMI) in first and second lactations and two for CMI in third lactation. Nine out of sixteen QTLs overlapped with the already reported QTLs for mastitis traits, whereas seven were adjudged as novel ones. Important candidates for clinical mastitis in the identified QTL regions included DNAJB9, ELMO1, ARHGAP26, NR3C1, CACNB2, RAB4A, GRB2, NUP85, SUMO2, RBPJ, and RAB33B genes. These findings shed light on the genetic architecture of the disease in Bos indicus, and present potential regions for fine mapping and downstream analysis in future.

Marker-assisted selection vis-à-vis bull fertility: coming full circle-a review.

Bull fertility is considered an indispensable trait, as far as farm economics is concerned since it is the successful conception in a cow that provides calf crop, along with the ensuing lactation. This ensures sustainability of a dairy farm. Traditionally, bull fertility did not receive much attention by the farm managers and breeding animals were solely evaluated based on phenotypic predictors, namely, sire conception rate and seminal parameters in bull. With the advent of the molecular era in animal breeding, attempts were made to unravel the genetic complexity of bull fertility by the identification of genetic markers related to the trait. Marker-Assisted Selection (MAS) is a methodology that aims at utilizing the genetic information at markers and selecting improved populations for important traits. Traditionally, MAS was pursued using a candidate gene approach for identifying markers related to genes that are already known to have a physiological function related to the trait but this approach had certain shortcomings like stringent criteria for significance testing. Now, with the availability of genome-wide data, the number of markers identified and variance explained in relation to bull fertility has gone up. So, this presents a unique opportunity to revisit MAS by selection based on the information of a large number of genome-wide markers and thus, improving the accuracy of selection.