Assessing genetic parameters for first parity reproductive traits for early selection in Saanen × Beetal goats of India.

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.

Functional transcriptome analysis revealed major changes in pathways affecting systems biology of Tharparkar cattle under seasonal heat stress.

Heat stress significantly disturbs the production, reproduction, and systems biology of dairy cattle. A complex interaction among biological systems helps to combat and overcome heat stress. Indicine cattle breed Tharparkar has been well known for its thermal adaptability. Therefore, present investigation considered RNA-seq technology to explore the functional transcriptomics of Tharparkar cattle with the help of samples collected in spring and summer season. Among differentially expressed genes, about 3280 genes were highly dysregulated, in which 1207 gene were upregulated and 2073 genes were downregulated (|log2fold change|≥ 1 and p ≤ 0.05). Upregulated genes were related to insulin activation, interferons, and potassium ion transport. In contrast, downregulated genes were related to RNA processing, translation, and ubiquitination. Functional annotation revealed that the pathways associated with nervous system (NPFFR1, ROBO3) and metal ion transport (KCNG2, ATP1A2) were highly activated while mRNA processing and translation (EIF4A, EIF4B) and protein processing pathway (VPS4B, PEX13) were highly downregulated. Protein-protein interactions identified hub genes such as ATP13A3, IFNGR2, UBXN7, EIF4A2, SLC12A8 found to play an important role in immune, ubiquitination, translation and transport function. Co-expression network includes LYZ, PNRC1, SQSTM1, EIF4AB and DDX17 genes which are involved in lysosomal activity, tumor inhibition, ubiquitination, and translation initiation. Chemokine signaling pathway associated with immune response was highly upregulated in cluster analysis. The findings of this study provide insights into transcriptome expression and regulation which may better explain complex thermal resilience mechanism of Tharparkar cattle in heat stress under natural conditions. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-024-04018-2.

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.

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.

Genetic variation in promoter region of the bovine LAP3 gene associated with estimated breeding values of milk production traits and clinical mastitis in dairy cattle.

The purpose of this study was to identify genetic variants in the promoter and 5'UTR regions of bovine leucine amino peptidase three (LAP3) gene and analysed their associations with estimated breeding values (EBVs) of milk production traits and clinical mastitis in Sahiwal and Karan Fries cattle. Eleven SNPs were identified within the region under study of the LAP3 gene, including seven promoter variants (rs717156555: C>G, rs720373055: T>C, rs715189731: A>G, rs516876447: A>G, rs461857269: C>T, rs136548163: C>T, and rs720349928: G>A) and four 5'UTR variants (rs717884982: C>T, rs722359733: C>T, rs481631804: C>T and rs462932574: T>G). Out of them, 10 SNPs variants were found in both Sahiwal and Karan Fries cattle, with one SNP variant (rs481631804: C>T) being unique to Karan Fries cattle. Seven of these identified SNPs were chosen for association analyses. Individual SNP based association analysis revealed that two SNPs (rs720373055: T>C and rs720349928: G>A) were significantly associated with EBVs of lactation milk yield (LMY), 305-day milk yield (305dMY), and one significant association of SNP rs722359733: C>T with lactation length (LL) was observed. Haplotype based association analysis indicated that diplotypes are significantly associated with EBVs of LMY, 305dMY, and LL, individuals with H1H3 (CTACGCT/GCGTACG) being linked to higher lactation performance than other diplotypes. Further logistic regression analysis revealed that, animals with diplotype H1H3 was less susceptible to the incidence of clinical mastitis than other cows, as the odds ratio for the non-incidence of clinical mastitis was found to be low. Altogether, variations in the LAP3 gene promoter could be used as a genetic marker, most notably diplotype H1H3, may greatly benefit the simultaneous improvement of mastitis resistance and milk yield traits in dairy cattle. Moreover, bioinformatics analysis predicted that the SNPs rs720373055: T>C, rs715189731:A>G and rs720349928: G>A is located in the core promoter region and in TFBs, play key role in regulation of studied phenotypes.

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.

Sustainable multi-trait selection index based on production, reproduction, and health traits for genetic improvement of Murrah buffaloes.

Selection of Murrah buffaloes based on production, reproduction, and health traits play an important role in sustainable genetic improvement. With the aim to construct an index comprising of production, reproduction and health traits of Murrah buffaloes, the production and reproduction data during a 50-year span (1971-2020) and for health traits data of 27 years (1994-2020) were analyzed. Various three, four, five, and six trait combinations of production, reproduction, and health traits were explored for construction of performance indices. The income and expenditure method was used to calculate relative economic values (REV) for traits under consideration. A total of 37 performance indices were constructed using a multi-trait combination of production, reproduction, and health traits. Out of 37 indices, the (ADMY-PY-DO-AFC-FF) based index was identified as the best, with 78%, 2%, and 20% weightage given to production, reproduction, and female fertility, respectively. Furthermore, when REVs of traits were increased by 25% and 50%, there was no change observed in the relative importance of traits in the best index, indicating that the index was robust to substantial increases in economic values. Therefore, it is recommended that the above constructed composite selection index can be employed in selection of female buffaloes to achieve sustainable genetic gain.

Influences of maternal factors on the estimate of genetic parameters for goat feed efficiency traits.

The objective of the present study was to estimate the genetic parameters for the feed efficiency traits in Barbari goats. The data records of 9332 progenies born to 413 sires and 2580 dams were collected with respect to the average daily weight gain (ADG), i.e., ADG1 (birth to weaning), ADG2 (weaning to 6 months), ADG3 (6 to 12 months), as well as derived trait Kleiber ratio (KR), i.e., KR1 (ADG1/3MW0.75), KR2 (ADG2/6MW0.75), and KR3 (ADG3/12MW0.75). The data were corrected for fixed covariates like period of kidding, the season of birth, sex, type of birth, and parity. Univariate and multivariate animal models with an average information function of restricted maximum likelihood (REML) were used to estimate genetic factors for these traits. The best model was evaluated based on the likelihood ratio test. The direct heritability estimates were 0.21 ± 0.03, 0.17 ± 0.03, 0.23 ± 0.04, 0.22 ± 0.04, 0.16 ± 0.04, and 0.26 ± 0.04 for ADG1, ADG2, ADG3, KR1, KR2, and KR3, respectively. However, they were inflated due to high and negative estimates of covariance between direct animal and maternal genetic effects. Moderate estimates of heritability augur the scope for improvement for feed efficiency traits. The maternal genetic effects (m2) significantly contributed to 3-12% of the total phenotypic variance. The realized heritability of mass selection, which takes into account direct and maternal genetic variance together, shows a low to moderate estimate of genetic variance for ADG and KR. The genetic correlation ranged from - 0.48 ± 0.11 (ADG1-KR3) to 0.95 ± 0.00 (ADG1-KR1), phenotypic correlation ranged from - 0.28 ± 0.01 (ADG2-KR3) to 0.94 ± 0.01 (ADG1-KR1), maternal genetic correlation ranged from - 0.22 (KR2-KR3) to 0.96 (ADG1-KR1) and - 0.69 (ADG1-KR3) to 0.95 (ADG1-KR1) for the maternal permanent environment, respectively. Kids can be indirectly chosen for higher feed efficiency since ADG and their associated KR have substantial genetic correlations. It is suggested that the KR should be used as a selection criterion for Barbari goats for improving feed efficiency.

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.

Fitting random regression models with Legendre polynomial and B-spline to model the lactation curve for Indian dairy goat of semi-arid tropic.

The present investigation aimed at genetic evaluation of tropical Indian dairy Jamunapari goat using random regression models (RRM) for the estimation of genetic parameters in the first three lactations across test days (TD) and also to come out with a pragmatic breeding plan in the nucleus. Variations in the lactation curves were modelled using 67,172 TD milk yield (TDMY) records. To obtain adequate and parsimonious models for the estimation of genetic parameters, orthogonal Legendre Polynomials (LP) and B-splines (BS) were compared. The analysis was carried out using a single-trait RRM approach. Average TDMY was 0.72, 0.81 and 0.79 kg in 1st to 3rd parities that also had 4th TD peak yield in common. BS function resulted in robust genetic parameters and a smoother curve for lactation as compared to LP. Maternal effects were evaluated and then dropped from the final model, owing to no significant contribution to the genetic variance. The best RRM was a quadratic BS function with six knots for the mean trend, curves of additive genetic, animal permanent environmental (c2 ) and 22 classes of residual variance. Additive variances and heritability (h2 ) estimates were higher in the early lactation. For first parity, the estimates of h2 varied between 0.19 to 0.35 across TD. Moderate h2 estimate suggests further scope for selection using desirable combinations of TD over the lactation. We observed a very high variance due to c2 across TD in three lactations. Genetic correlations were positive and larger between adjacent TDMY and weakened for distant TDMY. Looking into the robust estimates of genetic parameters and better fitting of lactation curve, we suggest the use of B-spline function for regular genetic evaluation of Jamunapari goat.

Estimates of genetic parameters for linear body measurements and prediction of body weight in goat.

The objective of this study is to estimate genetic parameters for linear body measurements along with their correlation to live weight with a focus on devising a scale to predict live weights from body measurement. A total of 142,564 records on body measures and live weights were collected from 8701 Jamunapari goats. Genetic parameters were obtained for body length (L), height at withers (H) and heart girth (G) from birth to adult stage by univariate and multivariate analysis using the average information restricted maximum likelihood method. The best model for body measures at birth included the additive effect of animal and dam along with their covariance and maternal environment, whereas for traits measured later in life, the maternal environment was not significant. After accounting for the direct maternal correlation (ram ), the total heritability estimates for linear body measurements (L,H and G) at the preweaning and postweaning stages of growth ranged from 0.14 to 0.20. Significant genetic variability implies further scope for selection. The genetic correlations of live weight at birth, 3, 6, 9 and 12 months with corresponding L,H and G were high in magnitude indicating scope to select animals for higher weight using morphometric measurements. When weighing scales are unavailable in the field, prediction of weight using L and G was recommended [live weight = (0.291 × L) + (0.306 × G) - 16.8]. We recommend the use of body measurements in the Jamunapari goat breeding program owing to their high genetic correlation with corresponding live weights.

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.

Farmer's participatory approach for breed improvement in Malpura sheep.

The objective of the study was to propose a model for a community-based breeding programme (CBBP) in Malpura sheep. The study was carried out for nine years (2012-2018) in 31 villages covering 77 flocks. The average flock size was 54.39 ± 0.65. The study revealed that the Malpura sheep is a long-day breeder with 72.1% of lambing during August to January. The higher concentration of lambing in this period is to avoid the stress of harsh summer and scarcity of feed. The disposal pattern of male lambs was stringent due to selection. Only 3.1% of male lambs reach to adult stage. For females, the replacement rate was 34.11%. The live weights (kg) from 8,263 lambs were 3.34 ± 0.01, 14.61 ± 0.04, 20.48 ± 0.07 and 30.01 ± 0.16, for birth, three-, six- and 12-month age, respectively. Non-genetic factors such as sex, season and year of birth and flock significantly influenced growth. The heritability was 0.20 ± 0.03, 0.20 ± 0.008, 0.23 ± 0.004 and 0.17 ± 0.009 for birth, three-, six- and 12-month weight, respectively. This indicated scope for genetic improvement, given a systematic breeding programme, is in place. The present model followed by sheep breeders is highly dependent upon the Government aided Central Sheep and Wool Research Institute (CSWRI) for supply of breeding rams, data collection and health care. Alternate self-sustainable model of CBBP is proposed wherein a breeder's organization leads the way to establish a ram-rearing centre (RRC), teams of experts for ram selection, data collection and market linkage. CSWRI will continue to assist for selection decisions and real-time data entry using a cloud-based "Avimegh" platform. The early selection of 5% male lambs at weaning and rearing them at RRC until final selection at 12-month will provide unbiased selection of rams under CBBP. The surplus rams will be sold by RRC for profit. Several key measures such as micro-finance, co-ordination between stakeholders, market linkage and technical input for data collection and selection have been suggested to make the CBBP self-sustainable.

Effect of selection and selective genotyping for creation of reference on bias and accuracy of genomic prediction.

Reference populations for genomic selection usually involve selected individuals, which may result in biased prediction of estimated genomic breeding values (GEBV). In a simulation study, bias and accuracy of GEBV were explored for various genetic models with individuals selectively genotyped in a typical nucleus breeding program. We compared the performance of three existing methods, that is, Best Linear Unbiased Prediction of breeding values using pedigree-based relationships (PBLUP), genomic relationships for genotyped animals only (GBLUP) and a Single-Step approach (SSGBLUP) using both. For a scenario with no-selection and random mating (RR), prediction was unbiased. However, lower accuracy and bias were observed for scenarios with selection and random mating (SR) or selection and positive assortative mating (SA). As expected, bias disappeared when all individuals were genotyped and used in GBLUP. SSGBLUP showed higher accuracy compared to GBLUP, and bias of prediction was negligible with SR. However, PBLUP and SSGBLUP still showed bias in SA due to high inbreeding. SSGBLUP and PBLUP were unbiased provided that inbreeding was accounted for in the relationship matrices. Selective genotyping based on extreme phenotypic contrasts increased the prediction accuracy, but prediction was biased when using GBLUP. SSGBLUP could correct the biasedness while gaining higher accuracy than GBLUP. In a typical animal breeding program, where it is too expensive to genotype all animals, it would be appropriate to genotype phenotypically contrasting selection candidates and use a Single-Step approach to obtain accurate and unbiased prediction of GEBV.

Challenges and opportunities to livestock breeding programmes in India.

Animal breeding in India has a long and chequered history. High pressure on agricultural land and increasing human population opened a new opportunity for the livestock and poultry sector as a promising food industry. Productivity of livestock in India is low due to less coverage of livestock under structured breeding programmes, inadequate nutrition and its entanglement with several socio-economic issues. A bottom-up approach to breeding policy formulation addressing local needs is required with assured flow of investments. Cattle slaughter is banned in India; hence, a legal policy to curb widespread indiscriminate mating is required which may incur substantial financial and infrastructural burdens for castration of stray males and strengthening of cow rehabilitation centres. Genetic evaluation of indigenous cattle with progeny testing (PT) requires substantial financial support, without affecting the already existing PT for exotic cattle breeds used in the local cross-breeding programmes and PT of new genotypes obtained from crosses of exotic and local breeds of cattle and for purebred buffaloes. Small ruminants need special attention due to their socio-economic importance in rural and often highly disadvantaged communities and because they are the second most important meat-producing species after poultry. Genetic improvement of small ruminants should be accompanied by attention to shrinking grazing resources which would require strong political will together with financial support. The outreach of breeding programmes for small ruminants is currently limited; there is also a lack of linkage between the market and producers that discourages farmers from adopting clear breeding objectives like improvement in growth rate, as animals are seldom sold on weight basis. Apart from government agencies, involvement of private sector, non-government organizations, local co-operatives, self-help groups and self-sustainable community-based breeding programmes can strengthen market linkages. Strengthening of the existing infrastructure along with technical input and skilled manpower is essential for achieving the breeding objectives.

Kinetics of Interferon gamma and Interleukin-21 response following foot and mouth disease virus infection.

Foot and mouth disease (FMD) is one of the most contagious diseases of cloven footed animals causing significant economic impediment in livestock production system. The immune response to FMD virus (FMDV) infection is regulated by a complex interplay between various cells, cytokines and other immune components. Based on the well established role of Interferon-gamma (IFN-γ) and Interleukin-21 (IL-21) in viral infections, this study aimed to determine expression level of these cytokines in clinically infected adults and calves; and the results were compared with those in the subclinically infected animals up to 120 days post outbreak (DPO) in a vaccinated cattle herd. The expression level of IFN-γ and IL-21 was assayed on 0, 7, 14, 28, 60, 90, and 120 DPO by enzyme linked immunosorbent assay (ELISA) with simultaneous assessment of FMDV structural protein-antibody titer against serotype 'O' by liquid phase blocking ELISA (LPBE) and nonstructural protein-antibody, a differential marker of infection, using r3AB3 indirect ELISA (r3AB3 I-ELISA). Although, the peak expression of IFN-γ was observed on 14 DPO across all categories of animals, the clinically infected animals registered a significant increase in IFN-γ level as compared to the subclinically infected population possibly due to the difference in the extent of virus replication and inflammation. The IL-21 level increased significantly during 14-28 DPO and highest expression was noticed on 28 DPO. The increase in the expression level of IFN-γ and IL-21 at 28 DPO correlated with the increase in antibody titer as determined by LPBE suggesting the role of these cytokines in augmenting immune response to FMDV infection.

Genetic analysis for growth traits of prolific Garole × Malpura (GM) sheep.

The FecB gene of Garole sheep was introgressed into non-prolific Malpura sheep to evolve a new prolific sheep strain Garole × Malpura (GM), suitable for semi-arid conditions. The present study was conducted to evaluate the impact of breeding program on production profile of GM sheep and to estimate the genetic parameters for growth traits of GM sheep. Overall prolificacy increased significantly in the new strain as compared to the native Malpura sheep. In the GM flock of F2 and F2 onwards generation 35.31% single, 55.83% twins, 8.16% triplet and 0.70% quadruplets were obtained during lambing. Over the years, prolificacy in the flock has increased significantly. Over all least squares means for birth weight, 3, 6, 9, 12 month weight, pre-weaning gain (ADG1) and post-weaning gain (ADG2) were 1.82 ± 0.03, 9.44 ± 0.18, 14.00 ± 0.24, 16.56 ± 0.33, and 19.32 ± 0.35 kg, and 84.08 ± 1.84 and 35.19 ± 0.99 g, respectively. Majority of the fixed effects had significant influence on the performance traits. The heritability estimates for birth, 3, 6, 9, 12 month weight, ADG1 and ADG2 were 0.30 ± 0.11, 0.22 ± 0.09, 0.23 ± 0.10, 0.27 ± 0.10, 0.30 ± 0.11, 0.17 ± 0.08, and 0.17 ± 0.10, respectively. Modest rate of genetic progress seems possible for these traits under selection. The genetic and phenotypic correlations among different body weights were moderate to high and positive. The genetic correlation of pre and post-weaning daily gains with body weight traits were also high and positive.