Exome-wide comparative analyses revealed differentiating genomic regions for performance traits in Indian native buffaloes

In India, 20 breeds of buffalo have been identified and registered, yet limited studies have been conducted to explore the performance potential of these breeds, especially in the Indian native breeds. This study is a maiden attempt to delineate the important variants and unique genes through exome sequencing for milk yield, milk composition, fertility, and adaptation traits in Indian local breeds of buffalo. In the present study, whole exome sequencing was performed on Chhattisgarhi (n = 3), Chilika (n = 4), Gojri (n = 3), and Murrah (n = 4) buffalo breeds and after stringent quality control, 4333, 6829, 4130, and 4854 InDels were revealed, respectively. Exome-wide FST along 100-kb sliding windows detected 27, 98, 38, and 35 outlier windows in Chhattisgarhi, Chilika, Gojri, and Murrah, respectively. The comparative exome analysis of InDels and subsequent gene ontology revealed unique breed specific genes for milk yield (CAMSAP3), milk composition (CLCN1, NUDT3), fertility (PTGER3) and adaptation (KCNA3, TH) traits. Study provides insight into mechanism of how these breeds have evolved under natural selection, the impact of these events on their respective genomes, and their importance in maintaining purity of these breeds for the traits under study. Additionally, this result will underwrite to the genetic acquaintance of these breeds for breeding application, and in understanding of evolution of these Indian local breeds.

Diversity assessment of a lesser known buffalo population from Central India and its comparative evaluation reveals presence of sufficient genetic variation and absence of selection

Planned breeding and conservation strategies for a lesser-known population require an assessment of complete genetic diversity and population structure analysis in addition to its morphometric characteristics. In the present study, a comparative analysis of the genetic structure of a rare buffalo population, namely Chhattisgarhi, was extensively studied using a panel of FAO-recommended microsatellite markers along with well-established breeds namely Murrah, Nili-Ravi, Gojri, Kalahandi, and Nagpuri. Mode shift analysis indicated the absence of genetic bottleneck in the recent past. Assessment of genetic diversity indices across all loci indicated the presence of sufficient genetic variation within and between populations. Analysis of molecular variance between the six different buffalo populations attributed 19.05% of the variations to between-population differentiation. Cluster analyses using DAPC and Bayesian approach along with the phylogenetic tree based on UPGMA grouped six populations into three groups. The Chhattisgarhi population was revealed to be genetically closer to Nagpuri and Kalahandi populations. The study reveals the presence of sufficient genetic diversity within the Chhattisgarhi population and indicates the absence of a systematic selection program. We suggest improvement and conservation programs should be planned for this breed in the near future through short-term selection.

TWAS revealed significant causal loci for milk production and its composition in Murrah buffaloes

Milk yield is the most complex trait in dairy animals, and mapping all causal variants even with smallest effect sizes has been difficult with the genome-wide association study (GWAS) sample sizes available in geographical regions with small livestock holdings such as Indian sub-continent. However, Transcriptome-wide association studies (TWAS) could serve as an alternate for fine mapping of expression quantitative trait loci (eQTLs). This is a maiden attempt to identify milk production and its composition related genes using TWAS in Murrah buffaloes (Bubalus bubalis). TWAS was conducted on a test (N = 136) set of Murrah buffaloes genotyped through ddRAD sequencing. Their gene expression level was predicted using reference (N = 8) animals having both genotype and mammary epithelial cell (MEC) transcriptome information. Gene expression prediction was performed using Elastic-Net and Dirichlet Process Regression (DPR) model with fivefold cross-validation and without any cross-validation. DPR model without cross-validation predicted 80.92% of the total genes in the test group of Murrah buffaloes which was highest compared to other methods. TWAS in test individuals based on predicted gene expression, identified a significant association of one unique gene for Fat%, and two for SNF% at Bonferroni corrected threshold. The false discovery rates (FDR) corrected P-values of the top ten SNPs identified through GWAS were comparatively higher than TWAS. Gene ontology of TWAS-identified genes was performed to understand the function of these genes, it was revealed that milk production and composition genes were mainly involved in Relaxin, AMPK, and JAK-STAT signaling pathway, along with CCRI, and several key metabolic processes. The present study indicates that TWAS offers a lower false discovery rate and higher significant hits than GWAS for milk production and its composition traits. Hence, it is concluded that TWAS can be effectively used to identify genes and cis-SNPs in a population, which can be used for fabricating a low-density genomic chip for predicting milk production in Murrah buffaloes.

Population-wide genetic analysis of Ovar-DQA1 and DQA2 loci across sheep breeds in India revealed their evolutionary importance and fitness of sheep in a tropical climate

Genetic variability at the major histocompatibility complex (MHC) is important in any species due to significant role played by MHC for antigen presentation. DQA locus has not been studied for its genetic variability across sheep population in India. In the present study, MHC of sheep at DQA1 and DQA2 loci were evaluated across 17 Indian sheep breeds. Results revealed high degree of heterozygosity (10.34% to 100% for DQA1 and 37.39 to 100% for DQA2). 18 DQA1 alleles and 22 DQA2 alleles were isolated in different breeds. Nucleotide content for DQA region revealed richness of AT content (54.85% for DQA1 and 53.89% for DQA2). DQA1 and DQA2 sequences clustered independently. We could see evidence of divergence of DQA as DQA1 and DQA2 across sheep breeds. Wu-Kabat variability index revealed vast genetic variation across DQA1 and DQA2, specifically at peptide binding sites (PBS) that consisted 21 residues for DQA1 and 17 residues for DQA2. Evolutionary analysis revealed the presence of positive and balancing selection for DQA1 locus, however DQA2 was under purifying selection across sheep breeds. Higher heterozygosity and large diversity at both loci especially at PBS indicated the fitness of the sheep population for evading pathogens and adapt to the harsh tropical climate.

Cross-population genetic analysis revealed genetic variation and selection in the Ovar-DRB1 gene of Indian sheep breeds

In sheep, MHC variability is studied widely to explore disease association. The aim of the current study was to explore the genetic diversity of Ovar-DRB diversity across sheep breeds of India. Here, Ovar-DRB1 locus was studied across 20 sheep breeds. DRB1 was amplified (301 bp) and sequenced using a PCR-sequence-based typing approach. Results revealed a high degree of heterozygosity across breeds (mean: 73.99%). Overall mean distance for DRB1 was highest in Sangamneri (0.18) and lowest in Madgyal sheep (0.10). There was a higher rate of transition, across breeds. Further, 39 alleles were isolated in different breeds, out of which 10 were new. To allow easy access and use of the immune-polymorphic database, an online database management system was launched (http://www.mhcdbms.in/). Nucleotide content across breeds for the DRB1 region revealed the richness of GC content (59.26%). Wu-Kabat index revealed vast genetic variation across peptide binding sites (PBS) of DRB1. Residues 6, 66, 69, 52, and 81, were polymorphic showing utility for antigen presentation. All breeds were under positive selection for DRB1 locus (dN > dS). Study revealed the importance of DRB locus diversity for beta chain specifically at PBS across sheep breeds of the Indian subcontinent and presented evidence of positive selection for DRB owing to its evolutionary significance.

Genomic insights into the conservation of wild and domestic animal diversity: A review

Due to environmental change and anthropogenic activities, global biodiversity has suffered an unprecedented loss, and the world is now heading toward the sixth mass extinction event. This urges the need to step up our efforts to promote the sustainable use of animal genetic resources and plan effective strategies for their conservation. Although habitat preservation and restoration are the primary means of conserving biodiversity, genomic technologies offer a variety of novel tools for identifying biodiversity hotspots and thus, support conservation efforts. Conservation genomics is a broad area of science that encompasses the application of genomic data from thousands or tens of thousands of genome-wide markers to address important conservation biology concerns. Genomic approaches have revolutionized the way we understand and manage animal populations, providing tools to identify and preserve unique genetic variants and alleles responsible for adaptive genetic variation, reducing the deleterious consequences of inbreeding, and increasing the adaptive potential of threatened species. The advancement of genomic technologies, particularly comparative genomic approaches, and the increased accessibility of genomic resources in the form of genome-enabled taxa for non-model organisms, provides a distinct advantage in defining conservation units over traditional genetics approaches. The objective of this review is to provide an exhaustive overview of the concept of conservation genomics, discuss the rationale behind the transition from conservation genetics to genomic approaches, and emphasize the potential applications of genomic techniques for conservation purposes. We also highlight interesting case studies in both livestock and wildlife species where genomic techniques have been used to accomplish conservation goals. Finally, we address some challenges and future perspectives in this field.

Host-specific probiotics feeding influence growth, gut microbiota, and fecal biomarkers in buffalo calves

The current study is aimed to evaluate the effect of host-specific probiotics on the gut microbiome, performance, and select fecal biomarkers of gut health in preruminant buffalo calves. Eight Murrah buffalo calves (3–5 days old; 32.52 ± 0.43 kg average body weight (BW)) were randomly allocated into two groups as follows; 1) Group I (n = 4) fed basal diet alone (CON); 2) Group II (n = 4) supplemented with a lyophilized probiotic formulation at a dose rate of 1 g/day/head (1 × 10⁹ CFU/g) having Limosilactobacillus reuteri BF-E7 and Ligilactobacillus salivarius BF-17 along with basal diet (PF) for 30 days. Results revealed that final BW (kg), average daily gain (g/day), average dry matter intake (g/day), and structural growth measurements were significantly (P < 0.05) increased in the probiotics supplemented group (PF) compared to the control (CON). Fecal pH, fecal moisture, and fecal score were reduced (P < 0.05) in PF than in CON. Moreover, levels of fecal propionate, lactate, and ammonia altered positively in PF compared with CON. The relative abundance of Firmicutes tended to be higher (P = 0.10) in the probiotics fed group than CON. However, the relative abundance of Proteobacteria was significantly lower (P = 0.03) for calves fed probiotics on day 15. A trend was observed in Bacteroides (P = 0.07) and Lactobacillus (P = 0.08) abundances in the feces of the PF than in CON. Overall, it can be concluded that the administration of probiotic formulations significantly improved the performance and gut health of buffalo calves via modulating the gut microbiota composition.

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

With the upsurge of crossbreeding in India, the admixture levels are highly unpredictable in the composite breeds. Hence, in the present study, 72 Vrindavani animals were assessed for the level of admixture from their known ancestors that are Holstein-Friesian, Jersey, Brown Swiss, and Hariana, through three different software, namely, STRUCTURE, ADMIXTURE, and frappe. The genotype data for ancestral breeds were obtained from a public repository, i.e., DRYAD. The Frieswal crossbred cattle along with ancestral breeds like Holstein-Friesian and Sahiwal were also investigated for the level of admixture with the help of the above-mentioned software. The Frieswal population was found to comprise an average of 62.49, 61.12, and 61.21% of Holstein-Friesian and 37.50, 38.88, and 38.80% of Sahiwal estimated through STRUCTURE, ADMIXTURE, and frappe, respectively. The Vrindavani population was found to consist of on average 39.5, 42.4, and 42.3% of Holstein-Friesian; 22.9, 22.3, and 21.7% of Jersey; 10.7, 10.6, and 11.9% of Brown Swiss; and 26.9, 24.7, and 24.1% of Hariana blood estimated through STRUCTURE, ADMIXTURE, and frappe, respectively. A greater degree of variation was noted in the results from STRUCTURE vs. frappe, STRUCTURE vs. ADMIXTURE than in ADMIXTURE vs. frappe. From this study, we conclude that the admixture analysis based on a single software should be validated through the use of many different approaches for better prediction of admixture levels.

Genome-Wide Association Studies in Indian Buffalo Revealed Genomic Regions for Lactation and Fertility

Murrah breed of buffalo is an excellent dairy germplasm known for its superior milk quality in terms of milk fat and solids-not-fat (SNF); however, it is often reported that Indian buffaloes had lower lactation and fertility potential compared to the non-native cattle of the country. Recent techniques, particularly the genome-wide association studies (GWAS), to identify genomic variations associated with lactation and fertility traits offer prospects for systematic improvement of buffalo. DNA samples were sequenced using the double-digestion restriction-associated DNA (RAD) tag genotyping-by-sequencing. The bioinformatics pipeline was standardized to call the variants, and single-nucleotide polymorphisms (SNPs) qualifying the stringent quality check measures were retained for GWAS. Over 38,000 SNPs were used to perform GWAS on the first two principal components of test-day records of milk yields, fat percentages, and SNF percentages, separately. GWAS was also performed on 305 days’ milk yield; lactation persistency was estimated through the rate of decline after attaining the peak yield method, along with three other standard methods; and breeding efficiency, post-partum breeding interval, and age at sexual maturity were considered fertility traits. Significant association of SNPs was observed for the first principal component, explaining the maximum proportion of variation in milk yield. Furthermore, some potential genomic regions were identified to have a potential role in regulating milk yield and fertility in Murrah. Identification of such genomic regions shall help in carrying out an early selection of high-yielding persistent Murrah buffaloes and, in the long run, would be helpful in shaping their future genetic improvement programs.

Morphometric and microsatellite-based comparative genetic diversity analysis in Bubalus bubalis from North India

To understand the similarities and dissimilarities of a breed structure among different buffalo breeds of North India, it is essential to capture their morphometric variation, genetic diversity, and effective population size. In the present study, diversity among three important breeds, namely, Murrah, Nili-Ravi and Gojri were studied using a parallel approach of morphometric characterization and molecular diversity. Morphology was characterized using 13 biometric traits, and molecular diversity through a panel of 22 microsatellite DNA markers recommended by FAO, Advisory Group on Animal Genetic Diversity, for diversity studies in buffaloes. Canonical discriminate analysis of biometric traits revealed different clusters suggesting distinct genetic entities among the three studied populations. Analysis of molecular variance revealed 81.8% of genetic variance was found within breeds, while 18.2% of the genetic variation was found between breeds. Effective population sizes estimated based on linkage disequilibrium were 142, 75 and 556 in Gojri, Nili-Ravi and Murrah populations, respectively, indicated the presence of sufficient genetic variation and absence of intense selection among three breeds. The Bayesian approach of STRUCTURE analysis (at K = 3) assigned all populations into three clusters with a degree of genetic admixture in the Murrah and Nili-Ravi buffalo populations. Admixture analysis reveals introgression among Murrah and Nili-Ravi breeds while identified the Gojri as unique buffalo germplasm, indicating that there might be a common origin of Murrah and Nili-Ravi buffaloes. The study provides important insights on buffalo breeds of North India that could be utilized in designing an effective breeding strategy, with an appropriate choice of breeds for upgrading local non-descript buffaloes along with conservation of unique germplasm.

Ancestry informative markers derived from discriminant analysis of principal components provide important insights into the composition of crossbred cattle

The cost of SNP genotyping to screen different breeds and to estimate the exact proportion of ancestry level is quite high, which can be compensated through deriving a small panel of ancestry informative markers (AIMs). Hence, we carried out the present study to provide an insight into ancestry level inferred from a panel of informative markers in the crossbred Vrindavani population developed at ICAR-IVRI, India. We have performed a new method i.e., discriminant analysis of principal components (DAPC) for the first time on the dataset of Vrindavani cattle. To confirm our method, we had performed DAPC on two other well-known crossbred cattle, i.e., Frieswal and Beefmaster. Three sets of panels (500, 1000 and 2000 markers) were tested for clustering of individuals. Among all the panels, we found the panel (1000 markers) with DAPC based contribution method was of the smallest size and comparatively of the highest accuracy.

Revelation of genomic breed composition in a crossbred cattle of India with the help of Bovine50K BeadChip

The aim of the present study was to assess the population structure and admixture levels in the Vrindavani composite population in India by using Bovine50KSNP BeadChip data. Genotypic data were generated for randomly selected animals (n = 72) of Vrindavani population and the data for parental breeds i.e., Hariana (n = 10), Holstein-Friesian (n = 63), Jersey (n = 28) and Brown Swiss (n = 22) were retrieved from a public repository. The indices of population structure were calculated using PLINK software and R-program. The merged dataset was analysed for assessing admixture levels and population stratification using three different approaches i.e., principal component analysis (PCA), multi-dimensional scaling (MDS) approach and the model-based approach in STRUCTURE software. The average minor allele frequency (MAF) value for Vrindavani population was estimated to be 0.235. Vrindavani population was found to possess an average ancestry of 39.5, 22.9, 26.9, and 10.7% inheritance levels from Holstein Friesian, Jersey, Hariana and Brown Swiss cattle breeds, respectively.

Comparative analysis of five different methods to design a breed-specific SNP panel for cattle

Single nucleotide polymorphisms (SNPs) have now replaced microsatellite markers in several species for various genetic investigations like parentage assignment, genetic breed composition, assessment for individuality and, most popularly, as a useful tool in genomic selection. However, such a resource, which can offer to assist breed identification in a cost-effective manner is still not explored in cattle breeding programs. In our study, we have tried to describe methods for reducing the number of SNPs to develop a breed-specific panel. We have used SNP data from Dryad open public access repository. Starting from a global dataset of 178 animals belonging to 10 different breeds, we selected five panels each comprising of similar number of SNPs using different methods i.e., Delta, Pairwise Wright's F_ST, informativeness for assignment, frequent item feature selection (FIFS) and minor allele frequency-linkage disequilibrium (MAF-LD) based method. MAF-LD based method has been recently developed by us for construction of breed-specific SNP panels. The STRUCTURE software analysis of MAF-LD based method showed appropriate clustering in comparison to other panels. Later, the panel of 591 breed-specific SNPs was called to their respective breeds using Venny 2.1.0 and UGent web tools software. Breed-specific SNPs were later annotated by using various Bioinformatics softwares.

Red flour beetle (Tribolium castaneum): From population genetics to functional genomics

Tribolium castaneum is a small and low maintenance beetle that has emerged as a most suitable insect model for studying developmental biology and functional genetic analysis. Diverse population genetic studies have been conducted using Tribolium as the principal model to establish basic facts and principles of inbreeding experiments and response to the selection and other quantitative genetics fundamentals. The advanced molecular genetic studies presently focused on the use of Tribolium as a typical invertebrate model for higher diploid eukaryotes. After a whole genome sequencing of Tribolium, many areas of functional genomics were unraveled, which enabled the use of it in many technical approaches of genomics. The present text reviews the use of Tribolium in techniques such as RNAi, transgenic studies, immune priming, immunohistochemistry, in situ hybridization, gene sequencing for characterization of microRNAs, and gene editing using engineered endonuclease. In contrast to Drosophila, the T. castaneum holds a robust systemic RNAi response, which makes it an excellent model for comparative functional genetic studies.

Copy number variation in livestock: A mini review

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.