Functional transcriptome analysis revealed upregulation of MAPK-SMAD signalling pathways in chronic heat stress in crossbred cattle.

Animal geneticists and breeders have the impending challenge of enhancing the resilience of Indian livestock to heat stress through better selection strategies. Climate change's impact on livestock is more intense in tropical countries like India where dairy cattle crossbreeds are more sensitive to heat stress. The main reason for this study was to find the missing relative changes in transcript levels in thermo-neutral and heat stress conditions in crossbred cattle through whole-transcriptome analysis of RNA-Seq data. Differentially expressed genes (DEGs) identified based on the minimum log twofold change value and false discovery rate 0.05 revealed 468 up-regulated genes and 2273 down-regulated significant genes. Functional annotation and pathway analysis of these significant DEGs were compared based on Gene Ontology (Biological process), Kyoto Encyclopedia of Genes and Genome (KEGG), and Reactome pathways using g: Profiler, ShinyGO v0.76, and iDEP.951 web tools. On finding network visualization, the most over-represented and correlated pathways were neuronal and sensory organ development, calcium signalling pathway, Mitogen-activated protein kinase (MAPK) and Smad signalling pathway, Ras-proximate-1, or Ras-related protein 1 (Rap 1) signalling pathway, apoptosis, and oxidative stress. Similarly, down-regulated genes were most expressed in mRNA processing, immune system, B-cell receptor signalling pathway, Nucleotide oligomerization domain (NOD)-like receptors (NLRs) signalling pathway and nonsense-mediated decay (NMD) pathway. The heat stress-responsive genes identified in this study will facilitate our understanding of the molecular basis for climate resilience and heat tolerance in Indian dairy crossbreeds.

Weighted single step GWAS reveals genomic regions associated with economic traits in Murrah buffaloes.

The objective of the present study was to identify genomic regions influencing economic traits in Murrah buffaloes using weighted single step Genome Wide Association Analysis (WssGWAS). Data on 2000 animals, out of which 120 were genotyped using a double digest Restriction site Associated DNA (ddRAD) sequencing approach. The phenotypic data were collected from NDRI, India, on growth traits, viz., body weight at 6M (month), 12M, 18M and 24M, production traits like 305D (day) milk yield, lactation length (LL) and dry period (DP) and reproduction traits like age at first calving (AFC), calving interval (CI) and first service period (FSP). The biallelic genotypic data consisted of 49353 markers post-quality check. The heritability estimates were moderate to high, low to moderate, low for growth, production, reproduction traits, respectively. Important genomic regions explaining more than 0.5% of the total additive genetic variance explained by 30 adjacent SNPs were selected for further analysis of candidate genes. In this study, 105 genomic regions were associated with growth, 35 genomic regions with production and 42 window regions with reproduction traits. Different candidate genes were identified in these genomic regions, of which important are OSBPL8, NAP1L1 for growth, CNTNAP2 for production and ILDR2, TADA1 and POGK for reproduction traits.

Modelling the lactation curve in Alpine × Beetal crossbred dairy goats using random regression models fitted with Legendre polynomial and B-spline functions.

The current study sought to genetically assess the lactation curve of Alpine × Beetal crossbred goats through the application of random regression models (RRM). The objective was to estimate genetic parameters of the first lactation test-day milk yield (TDMY) for devising a practical breeding strategy within the nucleus breeding programme. In order to model variations in lactation curves, 25,998 TDMY records were used in this study. For the purpose of estimating genetic parameters, orthogonal Legendre polynomials (LEG) and B-splines (BS) were examined in order to generate suitable and parsimonious models. A single-trait RRM technique was used for the analysis. The average first lactation TDMY was 1.22 ± 0.03 kg and peak yield (1.35 ± 0.02 kg) was achieved around the 7th test day (TD). The present investigation has demonstrated the superiority of the B-spline model for the genetic evaluation of Alpine × Beetal dairy goats. The optimal random regression model was identified as a quadratic B-spline function, characterized by six knots to represent the central trend. This model effectively captured the patterns of additive genetic influences, animal-specific permanent environmental effects (c2 ) and 22 distinct classes of (heterogeneous) residual variance. Additive variances and heritability (h2 ) estimates were lower in the early lactation, however, moderate across most parts of the lactation studied, ranging from 0.09 ± 0.04 to 0.33 ± 0.06. The moderate heritability estimates indicate the potential for selection using favourable combinations of test days throughout the lactation period. It was also observed that a high proportion of total variance was attributed to the animal's permanent environment. Positive genetic correlations were observed for adjacent TDMY values, while the correlations became less pronounced for more distant TDMY values. Considering better fitting of the lactation curve, the use of B-spline functions for genetic evaluation of Alpine × Beetal goats using RRM is recommended.

Optimizing selection strategy for enhancing reproduction efficiency in Indian crossbred goats using milk productivity as a selection criterion.

The present study was aimed at optimizing the selection strategy for enhancing reproductive efficiency and milk productivity of Alpine × Beetal crossbred goats. The data set included 2949 milk trait records across parities and 1389 milk records from first parity and corresponding reproductive traits. The traits included for analysis were 150-day milk yield (150DMY), days in milk (DIM), peak yield (PY) and total milk yield (TMY). The litter size (LS) and litter weight (LW) were used for specifically formulating selection plan using indirect selection. The least squares mean for lactation traits during the first parity were 150DMY: 195.32 ± 2.09 kg, DIM: 236.42 ± 3.04 days, PY: 1.82 ± 0.02 kg, TMY: 269.62 ± 4.52 kg. Notably, Alpine × Beetal goats demonstrated genetic superiority pan India for milk productivity as compared to other native goat breeds. The least squares mean for 150DMY across all parities was 236 ± 3.13 kg. An animal model employing average information restricted maximum likelihood was used for (co)variance component estimation to get the genetic parameters. The analysis revealed total heritability estimates for 150DMY, DIM, PY and TMY as 0.18 ± 0.06, 0.04 ± 0.04, 0.12 ± 0.06 and 0.08 ± 0.05, respectively. Repeatability estimates for 150DMY, DIM, and TMY were 0.28 ± 0.04, 0.21 ± 0.03 and 0.37 ± 0.03, respectively. Bivariate analysis of 150DMY with reproductive traits revealed heritability for LS and LW as 0.05 ± 0.01 and 0.10 ± 0.01, respectively using Gibbs sampling. Strong and positive genetic correlations of 150DMY with other production and reproduction traits was observed, such as DIM (0.72), PY (0.98), TMY (0.88), LS (0.57) and LW (0.33). Moderate heritability and repeatability estimate of 150DMY, along with its positive correlation with production and reproductive traits suggested it as a suitable selection criterion for early selection and overall genetic progress of lactation traits. The genetic trend analysis showed an overall improvement in all these traits, with observed gain of 98.4 g per year for 150DMY, 0.04 days per year for DIM, 0.5 g per year for PY and 220.5 g per year for TMY. We observed that selecting based on 150DMY would lead to a favourable indirect improvement for LW as 79 g and LS 0.04 units per generation. We, therefore, recommend employing 150DMY as the single trait selection criteria to enhance both milk productivity and reproductive potential of Alpine × Beetal goats.

Explicating the genetic diversity and population structure of Saanen × Beetal goats using pedigree analysis.

Pedigree analysis is required to assess the genetic diversity and population structure of a close breeding population in order to effectively manage the breeding program and keep inbreeding under acceptable limits. Saanen × Beetal is a crossbred population of goats, reared at the National Dairy Research Institute (NDRI), Karnal, for the last five decades. This germplasm has been acclimated to a tropical climate and has a higher milk potential and prolificacy. The objective of this study was to elucidate the genetic diversity, population structure, and inbreeding in the flock of the Saanen × Beetal goats. The data were collected from the Animal Genetics and Breeding Division of ICAR-NDRI, Karnal, for 2603 animals from the year 1971 to 2021. Animals born between 2014 and 2017 were considered as a reference cohort. Results revealed that the average generation interval was 3.44 years for the complete pedigree. The average inbreeding coefficient and the average relatedness were 4.20% and 6.87%, respectively, for the complete pedigree and 10.78% and 10.80% for the reference population. Higher inbreeding coefficient and average relatedness in the reference cohort demonstrated the impact of the enclosed gene pool and demands immediate intervention for managing diversity in the closed nucleus under study. Ancestors contributing 50% of the gene pool were 8 and 3 for the complete pedigree and reference cohort, respectively, which illustrates the fact that very few ancestors were responsible for genetic diversity in the flock, which results in the decline of effective population size. Effective numbers of founders (fe), ancestors (fa), and founder genome equivalents (fg) were 15, 7, and 3.11, respectively. The (fe/fa) ratio in the reference population was 2.14, indicating the occurrence of the bottleneck effect in the flock. We observed that inbreeding was non-significant for all reproductive traits except for age at first service and age at first kidding. To lessen inbreeding and augment genetic diversity in the flock, the stratified breeding plan needs to be followed, where mate selection would be based on relatedness. Furthermore, the introduction of unrelated Saanen and Beetal crosses will help alleviate the inbreeding accumulation.

Genome-wide identification and annotation of SNPs for economically important traits in Frieswal™, newly evolved crossbred cattle of India.

The Frieswal™ is a crossbred cattle evolved by ICAR-Central Institute for Research on Cattle utilizing more than 15,000 cattle maintained at more than 37 military farms spread all over the agro-climatic regions of the country. The ddRAD sequencing method was used to identify and annotate the SNPs and INDELs. The results of variant calling revealed 1,487,851 SNPs and 128,175 INDELs at a read depth of 10. A total of 3,775,079 effects were identified, and majority (66.41%) of the effects were in the intron region of the genome followed by intergenic (21.87%). Majority (99.18%) of the variants had the modifier effect. The results revealed a higher magnitude of transitions as compared to the transversion. The classification of SNPs by functional class revealed a majority of missense (43%) and silent (56%) effects. Out of 26,278 genes identified, 1841 SNPs were annotated in 207 candidate genes responsible for various milk production and reproduction traits. The observed heterozygosity was 0.2804 against the expected heterozygosity value of 0.2978. The overall average inbreeding coefficient (FIS) was 0.0604. The pathway analysis revealed that the prolactin signaling pathway (GO:0038161) was significant biological process complete for both milk production and reproduction traits. The SNP variations can be effectively used as markers for early and accurate identification of the QTLs and for formulating an efficient and effective breed improvement program in Frieswal™ cattle. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03701-0.

Estimation of genetic parameters and genetic change of first parity reproductive traits in Alpine × Beetal goats.

The study of reproductive traits is crucial for improving genetic potential of goats because of their significant utility in meat production. Hence, genetic analysis was conducted for reproductive traits on Alpine × Beetal goats using animal model for first parity data. Information on 1462 reproductive records were collected over five decades from ICAR-National Dairy Research Institute, Karnal, Haryana (1971-2021). Single-trait and multi-trait animal models were used for genetic analysis. Estimates of (co)variance components and genetic parameters were obtained using Gibbs Sampler for Animal Model due to non-normal distribution of data. Six single-trait animal models (including or excluding maternal and environmental effects) were fitted and best models were determined based on Deviance Convergence Criterion values. The prolificacy for the A × B goats for first parity data was 32%, having 68% single births, 31% twins and 1% triplets/quadruplets. The least squares mean for age at first service (AFS), age at first kidding (AFK), service period (SP), dry period (DP), gestation length (GL), kidding interval (KI), litter weight (LW), number of kids born (NKB) and number of females kids born (NFKB) in first parity were 546.15 ± 4.10 days, 679.05 ± 4.07 days, 226.51 ± 4.02 days, 67.96 ± 2.76 days, 150.74 ± 0.13 days, 362.53 ± 3.35 days, 3.99 ± 0.04 kg, 1.32 ± 0.02 and 0.64 ± 0.02, respectively. The heritability estimates obtained from best model for AFS, AFK, GL, KI, SP, and DP were 0.12 ± 0.00, 0.10 ± 0.00, 0.09 ± 0.01, 0.03 ± 0.00, 0.04 ± 0.00, and 0.05 ± 0.00, respectively. For NKB, NFKB and LW, heritability estimates were 0.16 ± 0.01, 0.03 ± 0.03, and 0.04 ± 0.00, respectively. These results imply lower heritability estimates for reproductive traits, and hence meagre scope for selection for further improvement. Maternal effects contributed significantly for traits such as GL, NKB and NFKB. Genetic correlation for number of female kids born was negative with SP and DP which is favourable. Furthermore, genetic correlation was negative for dry period and litter weight which is favourable as number of kids born and litter weight are traits of direct economic importance. Results reveal high genetic potential of this breed for meat industry owing to high prolificacy, provided consistent efforts are made for the genetic improvement of this germplasm.

Genetic improvement of economic traits in Murrah buffalo using significant SNPs from genome-wide association study.

GWAS helps to identify QTL and candidate genes of specific traits. Buffalo breeding has primarily focused on milk production, but its negative correlation with reproduction traits resulted in unfavorable decline of reproductive performance among buffaloes. A genome wide scan was performed on a total of 120 Murrah buffaloes genotyped by ddRAD sequencing for 13 traits related to female fertility, production, and growth. The identified 25 significant single nucleotide polymorphisms (SNPs) (P <1×106) are associated with age at first calving (AFC), age at first service (AFS), period from calving to 1st Artifical Insemination (AI), service period (SP) and 6 month body weight (6M). Fifteen genetic variants overlapped with different QTL regions of reported studies. Among the associated loci, outstanding candidate genes for fertility, including AQP1, TRNAE-CUC, NRIP1, CPNE4, and VOPP1, have effect in different fertility traits. AQP1 gene is expressed in ovulatory phase and various stages of pregnancy. TRNAE-CUC gene is associated with AFC and number . of calvings after 4 years of age. Glycogen content-associated gene CPNE4 regulates muscle glycogen and is upregulated during early pregnancy. NRIP1 generegulates ovulation, corpus luteum at pregnancy, and mammary gland development. The objective is to identify potential genomic regions and genetic variants associated with economic traits and to select the most significant SNP which have positive effect on all the traits.

Genome wide mining of SNPs and INDELs through ddRAD sequencing in Sahiwal cattle.

The study was conducted in Sahiwal cattle for genome wide identification and annotation of single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs) in Sahiwal cattle. The double digest restriction-site associated DNA (ddRAD) sequencing, a reduced representation method was used for the identification of variants at nucleotide level. A total of 1,615,211 variants were identified at RD10 and Q30 consisting of 1,480,930 SNPs and 134,281 INDELs with respect to the Bos taurus reference genome. The SNPs were annotated for their location, impact and functional class. The SNPs identified in Sahiwal cattle were found to be associated with a total of 26,229 genes. A total of 1819 SNPs were annotated for 209 candidate genes associated with different production and reproduction traits. The variants identified in the present study may be useful to strengthen the existing bovine SNP chips for reducing the biasness over the taurine cattle breeds. The diversity analysis provides the insight of the genetic architecture of the Sahiwal population Studied. The large genetic variations identified at the nucleotide level provide ample scope for implementing an effective and efficient breed improvement programme for increasing the productivity of Sahiwal cattle.

Optimization of test day for milk yield recording and sire evaluation in Murrah buffaloes.

In the present study, random regression models (RRM) were used to estimate genetic parameters for test-day milk yield in Murrah buffaloes using Legendre polynomial function (LP), with the objective to find the best combination of "minimum test-day model," which would be essential and sufficient to evaluate the trait successfully. Data included for analysis were 10,615 first lactation monthly test-day milk yield records (5th, 35th, 65th, …, 305th) from 965 Murrah buffaloes for the period 1975-2018. Cubic to octic-order orthogonal polynomials with homogeneous residual variances were used for the estimation of genetic parameters. Random regression models with sixth-order were selected based on goodness of fit criteria like lower AIC, BIC and residual variance. Heritability estimates ranged from 0.079 (TD6) to 0.21(TD10). For both ends of lactation, the additive genetic and environmental variances were higher and ranged from 0.21 ± 0.12 (TD6) to 0.85 ± 0.35 kg2 (TD1) and 3.74 ± 0.36 (TD11) to 1.36 ± 0.14 kg2 (TD9), respectively. Between adjacent test-day records, genetic correlation estimates ranged from 0.09 ± 0.31 (TD1 and TD2) to 0.97 ± 0.03 (TD3 and TD4; TD4 and TD5), but values gradually declined as the distance between test days increased. Negative genetic correlations were also obtained between TD1 with TD3 to TD9, TD2 with TD9 and TD10, and TD3 with TD10. On the basis of genetic correlations, models with 5 and/or 6 test-days combination were able to account for 86.1%-98.7% of variation along the lactation. Models with fourth and fifth-order LP functions were considered to account for variance with combinations of 5 and/or 6 test-day milk yields. The model with 6 test-day combinations had a higher rank correlation (0.93) with model using 11 monthly test-day milk yield records. On the basis of relative efficiency, the model with 6 monthly test day combinations with fifth-order was more efficient (maximum 99%) than the model using 11 monthly test-day milk yield records. Looking into the similar accuracy with the 11TD model, and the low resources requirement, we recommend the use of the "6 test-day combination model" for sire evaluation. These models may help in reducing the cost and time for data recording of milk yield.

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.

Genomic clues of association between clinical mastitis and SNPs identified by ddRAD sequencing in Murrah buffaloes.

The total milk production of India is 209.96 MT out of which 45% is contributed by the indigenous buffalo and due to their high producing virtue, the prevalence of mastitis is 5-20%. Despite the increasing level of technological advancement, mastitis is still an issue of concern for dairy industry in India as well as across the world. Therefore, the present study aimed to identify the SNPs and associate them with the incidence of clinical mastitis in Murrah buffalo using the ddRAD sequencing approach taking mastitis incidence data of 96 Murrah buffaloes. A total of 246 million quality controlled reads were obtained with an average alignment rate of 99.01% and at a read depth of 10, quality controlled SNPs obtained were 18,056. The logistic regression model was used and a total of seven SNPs were found significantly associated (p < 0.001) with mastitis incidence and seven genes were identified viz., NCBP1, FOXN3, TPK1, XYLT2, CPXM2, HERC1, and OPCML. The majority of them were having tumor suppressing action, related to immunogenetics or glycolytic and energy production. Conclusively, the SNPs identified in this study may be useful for future studies on mastitis incidence in Murrah buffalo and the SNP associations can be further validated.

Genetic variants in 5'UTR and exonic region of NPY gene alter the reproduction performance in Indian cattle breeds.

Neuropeptide Y (NPY) is one of the most potent orexigenic factors which can produce diverse effects on behaviour and other physiological functions and is highly conserved in evolution. The present study was aimed to identify and associate SNPs in the 5' UTR and exon2 region of the NPY gene with reproduction and production traits in Kankrej cattle of Indian origin. Three mutations in the 5'-UTR region and one mutation in the exon2 region of the NPY gene were identified by PCR-SSCP and PCR-RFLP, respectively, followed by sequencing. Further, association studies were conducted with reproduction and production traits in Kankrej cattle. The GACCGA genotyped animals based on the 5'UTR variants indicated better dry period and calving interval, whereas with GGCCGG genotypes showed higher total lactation milk yield and 305-day milk yield in comparison to other genotypes. Also, service period and inter calving period varied significantly among the genotypes of exon2, as the GG genotyped animals had significantly longer calving interval. Other traits like age at first heat, age at first service and age at first calving were not affected by the mutations. So, the present study outlined that the bovine NPY gene may be considered to be one of the candidate gene for improvement of reproductive performance of cattle, after validation on large sample size.

Differentially expressed microRNAs in biochemically characterized FrieswalTM crossbred bull semen.

In addition to the transmission of paternal genome, spermatozoa also carry coding as well as noncoding microRNAs (miRNAs) into the female oocyte during the process of biological fertilization. Based on RNA deep sequencing, a total 28 number of differentially expressed miRNAs were cataloged in categorized FrieswalTM crossbred (Holstein Friesian X Sahiwal) bull semen on the basis of conception rate (CR) in field progeny testing program. Validation of selected miRNAs viz. bta-mir-182, bta-let-7b, bta-mir-34c and bta-mir-20a revealed that, superior bull semen having comparatively (p < .05) lower level of all the miRNAs in contrast to inferior bull semen. Additionally, it was illustrated that, bta-mir-20a and bta-mir-34c miRNAs are negatively (p < .01) correlated with seminal plasma catalase (CAT) activity and glutathione peroxidase (GPx) level. Interactome studies identified that bta-mir-140, bta-mir-342, bta-mir-1306 and bta-mir-217 can target few of the important solute carrier (SLC) proteins viz. SLC30A3, SLC39A9, SLC31A1 and SLC38A2, respectively. Interestingly, it was noticed that all the SLCs were significantly (p < .05) expressed at higher level in superior quality bull semen and they are negatively correlated (p < .01) with their corresponding miRNAs as mentioned. This study may reflect the role of miRNAs in regulating few of the candidate genes and thus may influence the bull semen quality traits.

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.

Impact and utility of shallow pedigree using single-step genomic BLUP for prediction of unbiased genomic breeding values.

In unstructured dairy programs, pedigree is usually shallow, which leads to biased prediction of breeding values using best linear unbiased prediction (BLUP). The objective of this study was to come out with a genomic prediction strategy that can utilize shallow pedigree information and predict unbiased and more accurate GEBV for sex-limited traits in a small population using single-step GBLUP (ssGBLUP). The data and models for a population under selection were simulated. Out of current 10 generations, 10th generation with 1000 candidates served as validation population. For the complete pedigree scenario, pedigree (P)BLUP estimated breeding values (EBV) were unbiased with accuracy (r) of 0.35 ± 0.02 and 0.26 ± 0.01 for 0.3 and 0.1 h2 scenario, respectively. For the shallow pedigree, biased prediction of breeding values and low accuracies were obtained with linear decline in the accuracy of EBV for removal of information on more distant pedigree. Accuracy and bias (ρ) for scenario with removing 4 distant generations from pedigree were 0.30 ± 0.02 and 0.55 ± 0.03, respectively, in moderate h2 scenario. Use of Genomic (G)BLUP, especially with "extreme phenotypic contrast selective genotyping," (TB) resulted in higher accuracy for a small reference of females; however, GEBV were highly biased. We observed that ssGBLUPF, where the numerator relationship matrix is corrected for inbreeding, resulted in more accurate and unbiased estimates of GEBV across shallow pedigree scenario, with TB all female reference (missing 4 distant generations: r = 0.50 ± 0.02; ρ = 0.96 ± 0.02). We recommend use of ssGBLUPF with two tailed selectively genotyped all female reference in shallow pedigree scenarios, to obtain unbiased and accurate GEBV for sex-limited traits, when resources are limited.

Estimation of genetic parameters of growth traits for direct and maternal effects in Murrah buffalo.

An understanding of genetic principles and environmental factors affecting the growth traits is essential to implement optimal breeding and selection programs. Early growth is an indicator of future success in production and reproduction status of dairy animals. In this study, a total of 18,989 records of body weight were used to estimate genetic parameters of body weight at birth (BW), 3 months (3BW), 6 months (6BW), 9 months (9BW),12 months (12BW), 18 months (18BW), 24 months (24 BW), 30 months (3BW), and 36 months (36BW) in Murrah buffalo at ICAR-NDRI Karnal, Haryana, for the period 1974-2019. The genetic parameters were estimated using the average information restricted maximum likelihood (AIREML) procedure by excluding or including maternal effects. Six analytical models were fitted in order to optimize the model for each trait. The most appropriate univariate model was selected based on the log likelihood ratio test (LRT). Influencing factors like calf sex, period of birth, season of birth, and dam's parity were investigated. The results showed that the maternal genetic effects, in addition to direct additive effects, were important for unbiased and accurate genetic parameter estimates of growth traits in Murrah buffaloes. Total heritability estimates h2T1 for BW, 3BW, 6BW, 9BW, 12BW, 18BW, 24BW, 30BW, and 36BW were 0.25, 0.04, 0.14, 0.16, 0.10, 0.15, 0.21, 0.24, and 0.23, respectively. Maternal effect was significant for birth weight and accounted for 13% variation through maternal genetic and 5% variability through maternal permanent environmental effect. Maternal genetic effect was also important for other traits. However, it interfered with the estimates of variance ratios in live weight traits owing to large and negative covariance between direct and maternal genetic effects. Direct genetic correlations between body weight traits were positive and high ranging from 0.10 to 0.94. Results revealed that the Murrah herd has a sizable genetic variability for growth traits and hence, there is sufficient scope for selection for achieving better growth rate if selection in this direction is applied. Owing to higher positive genetic correlation of 6BW with later ages, the scope of indirect selection for optimum growth in later ages can be aimed at by selecting animals for their higher 6-month live weight.

Associations between polymorphisms of LAP3 and SIRT1 genes with clinical mastitis and milk production traits in Sahiwal and Karan Fries dairy cattle.

BACKGROUND: Bovine mastitis continues to remain as the most challenging disease in dairy cattle, as a result improvement of selection methods has great economic relevance while a deeper understanding of the genetic mechanisms regulating milk production traits and mastitis is of general scientific interest. OBJECTIVES: This study aimed to evaluate the association of SNPs of the LAP3 and SIRT1 genes with estimated breeding values (EBVs) of milk production traits and clinical mastitis in dairy cattle of Indian origin. METHODS: DNA samples from 263 animals (Sahiwal and Karan Fries cattle) were genotyped by PCR-RFLP to assess their pattern of genetic variation. EBVs of milk production traits and phenotypic records of incidences of clinical mastitis were used for association analysis. RESULTS: A total of 9 SNPs were identified, including three (rs110932626: A>G, rs716493845: C>T and rs43702363: C>T) in intron 12, four (g.24904G>C, rs110839532: G>T, rs43702361: T>C and rs41255599: C>T) in exon 13 and within 3'UTR of LAP3 gene and two (rs110250233: G>A and rs42140046: C>G) in the promoter region of SIRT1 gene. Eight of these identified SNPs were chosen for subsequent genotyping and association analyses. Association analysis revealed that SNP rs41255599: C>T was significantly associated with lactation milk yield, 305-day milk yield, 305-day fat yield, 305-day solid not fat yield, lactation length and incidence of clinical mastitis (p < 0.05) in Sahiwal cattle. For Karan Fries cattle, two SNPs including rs110932626: A>G and rs43702363: C>T showed significant association with 305-day milk yield. CONCLUSION: Overall, these findings provide evidence for association of the LAP3 gene with milk production traits and clinical mastitis in dairy cattle, indicating the potential role of LAP3 variants in these traits.

Inputs for optimizing selection platform for milk production traits of dairy Sahiwal cattle.

The premises for the potential success of molecular breeding is the ability to identify major genes associated with important dairy related traits. The present study was taken up with the objectives to identify single nucleotide polymorphism (SNP) of bovine MASP2 and SIRT1 genes and its effect on estimated breeding values (EBVs) and to estimate genetic parameters for lactation milk yield (LMY), 305-day milk yield (305dMY), 305-day fat yield (305dFY), 305-day solid not fat yield (305dSNFY) and lactation length (LL) in Sahiwal dairy cattle to devise a promising improvement strategy. Genetic parameters and breeding values of milk production traits were estimated from 935 Sahiwal cattle population (1979-2019) reared at National Dairy Research Institute at Karnal, India. A total of 7 SNPs, where one SNP (g.499C>T) in exon 2 and four SNPs (g.576G>A, g.609T>C, g.684G>T and g.845A>G) in exon 3 region of MASP2 gene and 2 SNPs (g.-306T>C and g.-274G>C) in the promoter region of SIRT1 gene were identified in Sahiwal cattle population. Five of these identified SNPs were chosen for further genotyping by PCR-RFLP and association analysis. Association analysis was performed using estimated breeding values (n = 150) to test the effect of SNPs on LMY, 305dMY, 305dFY, 305dSNFY and LL. Association analysis revealed that, three SNP markers (g.499C>T, g.609T>C and g.-306T>C) were significantly associated with all milk yield traits. The estimates for heritability using repeatability model for LMY, 305dMY, 305dFY, 305dSNFY and LL were low, however the corresponding estimates from first parity were 0.20±0.08, 0.17±0.08, 0.13±0.09, 0.13±0.09 and 0.24, respectively. The repeatability estimates were moderate to high indicating consistency of performance over the parities and hence reliability of first lactation traits. Genetic correlations among the traits of first parity were high (0.55 to 0.99). From the results we could conclude that optimum strategy to improve the Sahiwal cattle further would be selecting the animals based on their first lactation 305dMY. Option top include the significant SNP in selection criteria can be explored. Taken together, a 2-stage selection approach, select Sahiwal animals early for the SNP and then on the basis of first lactation 305dMY will help to save resources.

In silico modeling revealed new insights into the mechanism of action of enzyme 2'-5'-oligoadenylate synthetase in cattle.

The innate immune system has an important role in developing the initial resistance to virus infection, and the ability of oligoadenylate synthetase to overcome viral evasion and enhance innate immunity is already established in humans. In the present study, we have tried to explore the molecular and structural variations present in Sahiwal (indigenous) and crossbred (Frieswal) cattle to identify the molecular mechanism of action of OAS1 gene in activation of innate immune response. The significant changes in structural alignment in terms of orientation of loops, shortening of ß-sheets and formation of 3-10 α-helix was noticed in Sahiwal and Frieswal cattle. Further, it has been observed that OAS1 from Sahiwal had better binding with APC and DTP ligand than Frieswal OAS1. A remarkable change was seen in orientation at the nucleoside base region of both the ligands, which are bound with OAS1 protein from Frieswal and Sahiwal cattle. The Molecular Dynamic study of apo and ligand complex structures was provided more insight towards the stability of OAS1 from both cattle. This analysis displayed that the Sahiwal cattle protein has more steady nature throughout the simulation and has better binding towards Frieswal in terms of APC and DTP binding. Thus, OAS1 protein is the potential target for explaining the innate immune response in Sahiwal than Frieswal.Communicated by Ramaswamy H. Sarma.