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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The present study aimed to evaluate the genetic parameters of first parity reproductive traits. Information on 762 reproductive records on Saanen × Beetal (S × B) goats reared for approximately five decades was collected from ICAR‐National Dairy Research Institute, Karnal, Haryana (1973–2020). For genetic analysis, single‐trait and multiple‐trait animal models were used. Gibbs sampler for animal model (GSAM) approach was used for estimating (co)variance components of reproductive traits. Six different single‐trait animal models (with or without maternal and environmental effects) were used and the deviance information criterion (DIC) determined the best model. 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 female kids born (NFKB) in first parity were 526.99 ± 4.86, 662.96 ± 5.03, 219.11 ± 6.25, 109.38 ± 6.00, 150.48 ± 0.27, 356.63 ± 4.80 days, 3.87 ± 0.05 kg, 1.27 ± 0.02 and 0.67 ± 0.03, respectively. Lower heritability estimates for these reproductive traits revealed a sparse scope for genetic improvement. Multivariate analysis using Model 1 was carried out to evaluate the genetic and phenotypic correlation of these nine reproductive traits. The genetic correlation of DP and SP was negatively with LW, NKB and NFKB, which is favourable as reduction in SP and DP can improve these economically important traits through indirect selection. Consistent efforts towards genetic improvement of these goat flock poses a promising future for meat industry owing to high prolificacy and good reproductive potential in this flock. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 (). 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. [ABSTRACT FROM AUTHOR]