Seroprevalence and risk factors associated with Toxoplasma gondii in pigs in Haryana, India.

AIMS: Toxoplasmosis is one of the most common food-borne parasitic zoonosis, caused by Toxoplasma gondii, an obligate intracellular protozoan parasite. A cross-sectional study was carried out to determine the seroprevalence of T. gondii and associated risk factors in pigs in Haryana, India. METHODS AND RESULTS: Serum samples were collected from 429 pigs from three agroclimatic zones (I-III) of Haryana and analysed for the presence of antibodies against T. gondii using a commercial indirect enzyme-linked immunosorbent assay (ELISA). Anti-T. gondii antibodies were detected in 106 animals (24.7%), with the highest seropositivity in zone II (31.3%) followed by zone III (24.4%) and zone I (18.3%). Risk factors associated with higher seropositivity in pigs were farm size (higher in large-sized farms), age (higher in pigs >1 year of age), sex (higher in males), type of feeding (higher in combination of homemade and hotel waste) and housing (higher in free-ranging pigs). CONCLUSIONS: The findings of the study testify to the exposure of pigs (of all agro-climatic zones) to T. gondii. Hence, the observations are of significant medical and veterinary importance for devising and implementing control measures to check the dissemination of toxoplasmosis to pigs and eventually to humans.

Modelling the growth curve and estimation of associated genetic parameters in Munjal sheep.

The study of growth curves in sheep is an effective approach to monitor the animal development for predicting the growth rate and improving overall flock performance. The purpose of the present work was to study the growth curve traits of Munjal sheep using different non-linear models and to estimate the genetic parameters of those traits for the possibility of inclusion of them under selection strategy. Total 2285 weight records at birth, 3, 6 and 12 months of age of 706 lambs born to 48 sires and 149 dams were collected from the registers maintained from 2004 to 2019. Various non-linear growth models viz., Brody, Gompertz, logistic, Bertalanffy and negative exponential were fitted to targeted growth curve traits and then evaluated using goodness of fit criteria such as adjusted R2, root means square error (RMSE), Akaike's information criterion (AIC) and Bayesian information criterion (BIC). The genetic parameters of growth curve traits were estimated using animal model. The results suggested that Brody model was best fitted to the data than other models. The growth curve estimates for mature weight (A), inflexion point (B) and rate of maturation (k) under Brody model were 25.82 ± 1.72, 0.84 ± 0.04, and 0.21 ± 0.04, respectively for female lambs, and 29.55 ± 2.04, 0.86 ± 0.03 and 0.19 ± 0.04, respectively for male lambs. The males showed superiority for mature weights whereas female lambs had higher maturation rates. The estimates of direct heritability for A, B and k were 0.33, 0.41 and 0.10, respectively. The moderate estimate of direct heritability of A and its negative genetic correlation with k indicated the scope of genetic improvement through selection based on mature weights. Therefore, it was concluded from the present findings that Brody model was the one that best describes the growth curve in the Munjal sheep and the selection based on mature weights can be employed for genetic improvement of Munjal flock.

Evaluation of physiological and morphological parameters for early prediction of prenatal litter size in goats.

The aim of the present study was to evaluate the physiological and morphological parameters of pregnant does for early prediction of prenatal litter size. In total, 33 does were screened using ultrasonography and further categorized into three groups based on does bearing twins (n = 12), a single fetus (n = 12), or non-pregnant does (n = 9). The rectal temperature °F (RT) and respiration rate (RR) as physiological parameters, while abdominal girth in cm (AG) and udder circumference in cm (UC) as morphological parameters were recorded at different gestation times, i.e. 118, 125, 132 and 140 days. In addition to this, age (years) and weight at service (kg) were also used. The statistical analyses included analysis of variance (ANOVA) and linear discriminant analysis (LDA). The results indicated that groups had significant (P < 0.05) differences among morphological parameters at each gestation time, with higher AG and UC in does bearing twins followed by a single fetus and non-pregnant does. However, both physiological parameters were non-significantly (P > 0.05) associated with litter size groups. It was also revealed that the studied parameters showed increasing trends over gestation time in single and twin fetus categories, but they were on par among non-pregnant does. The results of the LDA revealed that estimated function based on age, weight at service, RR, RT, AG and UC had greater (ranging from 75.00 to 91.70%) accuracy, sensitivity and specificity at different gestation times. It was concluded that using an estimated function, future pregnant does may be identified in advance for single or twin litter size, with greater accuracy.

Effect of BsaA I genotyped intronic SNP of leptin gene on production and reproduction traits in Indian dairy cattle.

In the present study, candidate single nucleotide polymorphism (SNP) g.92450765 G > A of leptin gene was explored for Bos indicus cattle with an aim to explore its possible effect on production and reproduction traits. The genotypic and allelic frequencies of BsaA 1 genotyped SNP g.92450765 G > A indicated the predominance of AG (0.65) genotyped Sahiwal cows in our studied population. The least-squares analysis showed a significant association (p < 0.05) of identified genetic variants with total milk yield (TMY) and 305 days milk yield (MY) (p < 0.05). The GG genotyped cows were found to be associated with higher milk yields. However, for reproduction traits under study AA genotype was found to be more favorable with respect to service period and calving interval (p < 0.05). Computational analysis was also performed to predict changes if any in the transcription factor binding sites (TFBS) caused due to the identified SNP in the intronic region of the leptin gene. TFBS analysis predicted that the targeted SNP at g.92450765G > A may lead to the disappearance of TFBS such as Hypermethylated in cancer 2 protein (HIC2), Max-binding protein MNT (MNT), Cyclic AMP-dependent transcription factor -3 (ATF3), Myc-associated factor X (MAX) and Microphthalmia-associated transcription factor (MITF). It may lead to changes in transcriptional regulation.

Candidate K232A mutation of DGAT1 gene associated with production and reproduction traits in Indian Dairy cattle.

The present study was conducted on Hardhenu and Sahiwal cows to evaluate the genetic diversity and the effect of candidate K232A mutation of diacylglycerol O-acyltransferase (DGAT1) gene on performance traits. PCR product of 413 bp size targeting K232A mutation of DGAT 1 gene was genotyped by Eae1 restriction enzyme and further confirmed by sequencing. The PCR-RFLP analysis for K232A showed that the frequencies of alleles K and A were 0.80 and 0.20 in Hardhenu and 0.98 and 0.02 in Sahiwal cattle, respectively. The frequencies of genotypes for KK and KA genotype were estimated as 0.60 and 0.40 in Hardhenu and 0.96 and 0.04 in Sahiwal cattle, respectively. Chi-square test showed that K232A SNP did not meet with the Hardy-Weinberg equilibrium (p < .01) in Hardhenu cattle. Association analysis revealed that KA genotype was significantly associated with total milk yield (p < .01) and 305 days milk yield (p < .01)in Hardhenu cattle. Hardhenu cows having KA genotype comparatively revealed favorable mean values for AFS (880.31 ± 26.65), AFC (1166.36 ± 19.94), SP (157.46 ± 22.80), CI (441.41 ± 44.28) and AI/Conception (1.80 ± 0.17), indicating that KA genotype can be used as a candidate marker for simultaneous improvement of both production and reproduction traits.

Neural network and Bayesian-based prediction of breeding values in Beetal goat.

The estimation of breeding values is prime concern for animal breeders in order to achieve desired genetic progress of farm animals. However, current methods for estimating BV involve simultaneous selection of animal model which are computationally intensive and time-consuming. The present attempt was made to predict breeding values of weaning trait under artificial neural networks (ANN), Bayesian technique (BT), and multiple regression (MR) methods. The data records comprising year of birth, sex, type of birth, dam's weight at kidding, birth weight, weaning weight, and estimated breeding values (BV) for weaning weight (under animal model) pertaining to 849 kids born to 37 sires and 237 dams between 2004 and 2019 were used in this study. All three methods, viz., ANN under multilayer perceptron (2 hidden layers), BT under Markov chain Monte Carlo (MCMC) approach, and MR under full model, were used for 75% training dataset initially and prediction model developed was applied on 25% test dataset. The initial analysis showed positive and significant (P < 0.01) relationship of BV with other variables which hinted that BV may be predicted with accuracy. Then, it was revealed from the results indicated that ANN, BT, and MR methods have similar accuracy (r = 0.86 to 0.87) for prediction of BV. However, ANN showed slightly higher but negligible model adequacy than BT and MR method. The prediction error under three methods was almost equal. The results indicated that these methods could be used as potential alternative for recurrent prediction of BV based on phenotypic data in order to optimize selection plans at young age in resourced population of Beetal goat.

Estimation of inbreeding and its effects on growth traits in Beetal goat.

The purpose of the present study was to estimate the inbreeding coefficient and its effects on various growth traits in Beetal goat using pedigree records of 963 kids born to 38 sires and 287 dams over the period of 2004 to 2019. The inbreeding coefficients for each individual were obtained under animal model. The effects of inbreeding along with other fixed effects such as year of birth, sex of kid, type of birth, and dam's weight at kidding on growth traits viz., weight at birth (BWT), 3 (WT3), 6 (WT6), 9 (WT9), and 12 (WT12) months of age were studied using least-squares analysis. Additionally, average daily gain and Kleiber ratio up to weaning age (90 days) were studied under the same model. The overall inbreeding coefficient was low in magnitude (1.42%) and ranged from 0 to 25% over the study period. The significant (P < 0.05) increase in average inbreeding coefficient (%) over the years was observed among the studied population. Although, the effects of various factors had significant (P < 0.05) influence on growth traits under least-squares model, the regression of targeted traits on inbreeding were non-significant (P > 0.05) and the same ranged from - 0.06 to 0.04. The present findings indicated that there was no inbreeding depression among the growth traits of Beetal goat. However, as inbreeding (%) raised in recent years only, the scientific efforts must be taken to avoid inbreeding at resourced population by introducing new germplasms at earliest.

Survival analysis for estimating lamb survival up to weaning in Harnali sheep.

The present study was carried out to estimate lamb survival (in days) from birth to weaning under survival analysis using data records from 2057 Harnali lambs born to 134 sires and 623 dams between the period from 2001 to 2020. The weaning age in resourced population was 90 days from birth. The hazard ratio in terms of risk of death up to weaning was determined using Cox proportional hazards model by subjecting some fixed factors such as year of birth, sex of lamb, birth weight (kg), dam's weight at lambing (kg) and dam's age at lambing (years). The overall survivability up to weaning among lambs was 91.59% and Kaplan-Meier estimates of mean survival time up to weaning was 85.77 days. Cox proportional hazard modelling revealed that the hazards of death up to weaning was higher in male lambs [1.66, 95% confidence interval (CI): 1.22-2.26] compared with female lambs [hazard ratio (HR) = 1.00]. It was also observed that the hazards of death (HR = 0.91, 95% CI: 0.88-0.94) had decreasing trends over years. For birth weight (kg), hazard rate was 0.34 (95% CI: 0.25-0.46), which indicated that the risk of pre-weaning mortality was lower as birth weight increases. The weight and age of dams at lambing did not influence the survival time of studied population. The present findings indicated that survival time increased in studied lambs over the years and it could be increased more by giving more emphasis on better litter weight and general health aspects at farm level.

Investigation of cause-specific pre-weaning mortality in Harnali sheep.

Lamb mortality is an important aspect in sheep production system which affects farm profitability worldwide. The aim of the present study was to investigate the causes of pre-weaning mortality (PWM) in Harnali lambs with respect to various associated factors. The data records of 173 lambs which died before 90 days of age (weaning age) out of 2057 lambs born during 2001-2020 year were collected from various registers, and the respective causes of mortality were taken from the post-mortem reports. The association of various factors such as age, sex, period of birth, birth weight of lamb and causes of death with PWM was assessed using chi-square test and log-linear modelling. The results showed that respiratory and digestive diseases were major causes of PWM. The log-linear modelling showed significant (P < 0.05) association of age, sex and period of birth with PWM. In the first month of age, digestive disease was the predominant cause of death; however, with age of lamb advances, respiratory disease was more prevalent. It was also revealed that male lambs (odds ratio (OR) = 0.48, 95% confidence interval (CI) = 0.24, 0.97) had lesser deaths due to respiratory diseases as compared to digestive disease. The reverse scenario was observed in female lambs. The findings of the present study might be helpful for understanding the risks and common causes of PWM in lambs to implement appropriate management practices in order to reduce economic losses to sheep farmers.

Meta-analysis of MspI derived variants of growth hormone gene associated with milk yield in dairy cattle.

OBJECTIVE: The present work aimed to obtain common effect sizes for the gene frequency and association of MspI derived variants of growth hormone (GH) gene with milk yield in dairy cows. METHODS: We performed a systematic review and meta-analysis of 35 published studies identified in literature search from 2000 to 2020 (n = 4164). These studies were specific to fragment size (329) for genotypes viz., CC (224, 105 bp), CD (329, 224, 105 bp) and DD (329 bp). Pooled standard mean differences (SMDs) as effect sizes between allele pairs were derived using different genetic models. The heterogeneity between effects sizes across studies was estimated using I2 Index (%). RESULTS: The common effect size for gene frequency of allele C (224, 105 bp) was significantly (P < 0.05) higher in 2881 Bos taurus/cross cows (0.82; 95% CI: 0.74, 0.89; I2 = 97.81%) than 1283 Bos indicus cows (0.15; 95% CI: 0.12, 0.18; I2 = 71.90%), with overall gene frequency was 0.33 (95% CI: 0.21, 0.46; I2 = 99.29%). Additive (CC vs. DD) and dominant (CC + CD vs. DD) did not revealed significant (P > 0.05) association with milk yield. However, completely over dominant (CC + DD vs. CD) and recessive (CC vs. CD + DD) models showed significant (P < 0.05) and positive SMDs with milk yield specially at early lactations. There was no evidence of heterogeneity (I2 = 0.00%) between SMDs across studies. CONCLUSIONS: This meta-analysis suggested potential association of C allele for enhancing milk production of dairy cows.

Evaluation of candidate genotype of GH gene associated with growth, production and reproduction traits in Dairy Cows.

Growth hormone (GH) is a major regulator of postnatal growth and metabolism in mammals and plays a critical role in growth, production and fertility in cattle. The present study was conducted in dairy cattle to find the association of g.48769565 C > T mutation with growth, production and reproduction traits in Sahiwal and Hardhenu cattle. PCR-RFLP was performed to genotype g.48769565 C > T mutation using the MspI restriction enzyme in our resource cattle population. In Hardhenu cattle, the frequencies of C and T alleles were 0.59 and 0.41, respectively, while genotypic frequencies were 0.33, 0.53 and 0.14 for CC, CT and TT respectively. The frequencies of the C and T alleles were 0.24 and 0.76, respectively, in Sahiwal cattle and it was observed that the highest frequency was for the TT genotype (0.58) and the lowest was for the CC genotype (0.06). Chi-square analysis showed that g.48769565C>T SNP loci meet with the Hardy-Weinberg equilibrium in Sahiwal and Hardhenu cattle. From the least-squares analysis, it was observed that CC genotype was significantly associated with total milk yield (TMY), 300 days milk yield (300D MY), lactation length (LL), dry period (DP) and artificial insemination (AI)/conception (p < .05). We also observed a significant association (p < .05) of genotype CT with 3-month calves body weight. Cows with TT genotype revealed comparatively favourable service period (SP) and calving interval (CI) in our resource population. These observed differences in their allelic and genotypic frequencies in association with the traits underlying production and fertility can be utilized for genetic improvement in dairy cattle.

Impact of mother genetic and resource environment on her offspring's growth features in Munjal sheep.

The present study evaluated maternal and additive influences that contribute to phenotypic variation in various growth traits in Munjal sheep. The targeted traits that pertained to 2278 records of 706 lambs were birth weight (BWT), weaning weight (WT3), 6-month body weight (WT6), 12-month body weight (WT12), average daily gain (ADG1: 0-3 months; ADG2: 3-6 months, ADG3: 6-12 months of age) and their corresponding Kleiber ratios designated as KR1, KR2 and KR3. The direct heritability estimates for BWT, WT3, WT6, WT12, ADG1, ADG2, ADG3, KR1, KR2 and KR3 under animal models were 0.20 ± 0.08, 0.28 ± 0.08, 0.17 ± 0.07, 0.47 ± 0.09, 0.33 ± 0.08, 0.09 ± 0.06, 0.36 ± 0.10, 0.33 ± 0.08, 0.09 ± 0.06 and 0.32 ± 0.10, respectively. The estimates of maternal genetic effects contributed significantly and were 8% and 7% for BWT and WT3 traits, respectively, which highlighted the considerable role of maternal effects on early growth traits. Genetic and phenotypic correlations ranged from moderate to high between weaning and post-weaning traits. It was concluded that early selection that considered additive as well as maternal effects at weaning age may be delivered to the desired genetic progress in Munjal sheep.

Evaluating animal models comprising direct and maternal effects associated with growth rates and the Kleiber ratio in Harnali sheep.

The present work evaluated animal models comprising direct and maternal effects to estimate (co)variance components and genetic parameters of growth rates and Kleiber ratio in Harnali sheep. The information on pedigree and targeted traits of 1862 lambs born to 144 sires and 591 dams was collected for the period from 1998 to 2018. The traits studied were average daily gain from birth to 3 months of age (ADG1), 3 months to 6 months of age (ADG2), and 6 months to 12 months of age (ADG3) and their corresponding Kleiber ratios as KR1, KR2 and KR3, respectively. The statistical methods included the general linear model for analyzing the effects of fixed factors and animal models for deriving variance components for targeted traits. According to best model evaluated on the basis of likelihood ratio test, the estimated direct heritability was low in magnitude and ranged from 0.04 to 0.14. Direct heritability estimates for ADG1, ADG2, ADG3, KR1, KR2 and KR3 were 0.06, 0.14, 0.05, 0.04, 0.11 and 0.05, respectively. The maternal genetic effects contributed (4-7%) significantly for ADG1, KR1 and KR2 traits. The genetic correlations ranged from -0.35 ± 0.11 (ADG1-KR2) to 0.98 ± 0.01 (ADG2-KR2 and ADG3-KR3) and phenotypic correlations ranged from -0.36 ± 0.02 to 0.98 ± 0.01 for ADG1-KR2 and ADG2-KR2, respectively. The significant maternal effects along with low levels of direct effects for average daily gain and Kleiber ratio at different age group should be considered while setting selection and managerial strategies to achieve anticipated growth rates in Harnali sheep.

Estimation of genetic parameters for early reproduction traits in Beetal goat.

The evaluation of early reproduction traits in Beetal goat was performed for possible effects of genetic and non-genetic factors on litter size at birth (LSB), litter size at weaning (LSW), litter weight at birth (LWB), litter weight at weaning (LWW) and age at first kidding (AFK). The data records consisted of information of pedigree and targeted traits pertained to 223 does born to 25 sires and 122 dams between the years 2004 to 2019. A general linear model was used for assessment of non-genetic factors such as period of birth, type of birth and dam's weight at kidding on studied traits. Genetic evaluation of targeted traits was done to estimate variance components and genetic parameters under dyadic mixed modelling. The estimates of least-square means for LSB, LSW, LWB, LWW and AFK were observed as 1.27 ± 0.03, 1.25 ± 0.03, 3.24 ± 0.07 kg, 13.08 ± 0.30 kg and 27.56 ± 0.58 months, respectively. Only the period of birth showed significant (P < 0.05) effects for targeted traits in this study. The estimates of direct heritability for LSB, LSW, LWB, LWW and AFK were low in magnitude as 0.08, 0.03, 0.10, 0.03 and 0.06, respectively. The moderate to high genetic and phenotypic correlations among litter traits indicate simultaneous improvement for these traits. It was concluded that low ranged direct heritability estimates for targeted traits indicated modest scope for genetic improvement of reproductive efficiency in Beetal goat through selection and, therefore, adoption of improved managerial practices is necessary to improve reproductive efficiency of Beetal goat.

Meta-Analysis of Gene Polymorphism of Beta-Lactoglobulin Gene in Indian Dairy Cows.

The aim of the present paper was to summarize the gene polymorphisms of beta-lactoglobulin (BLG) gene and its effects on milk yield in 1840 genotyped Indian dairy cows reported in 17 published studies. The meta-analysis was undertaken using gene frequencies of individual studies under random effects model, whereas for association analysis of genotypes with milk yield, standardized mean differences (SMDs) along with 95% confidence interval (CI) were obtained under four genetic models such as additive (AA vs. BB), dominant (AA+AB vs. BB), completely over dominant (AA+BB vs. AB) and recessive (AA vs. AB+BB). The heterogeneity index (I2) was used to determine heterogeneity between studies. The results of meta-analysis suggested that the pooled allelic frequency of allele A was subsidiary as 0.29 (95% CI 0.24, 0.33, I2 = 88.54%) in targeted population, and also, it was non-significantly (P > 0.05) different between Bos indicus (0.28) and Bos taurus/cross cows (0.30). Egger's test indicated no risk of publication bias (P > 0.05). The results also revealed that BLG gene variants have non-significant (P > 0.05) association with milk yield under all genetic models. Although positive effects of SMDs under some models were observed, however, they failed to meet statistical significance (P > 0.05) due to high heterogeneity between studies which lead to conclusion of only uncertain influences of SNP genotypes with milk yield. It was concluded that BLG markers may not be beneficial for improving milk yield in Indian dairy cows. However, it is suggested that the revalidation of the present results should be done by using more number of studies.

Influence of maternal and additive genetic effects on lamb survival in Harnali sheep.

Lamb survival is a critical aspect in the sheep industry as it increases the chances of economic gain in the flock. The objective of the current study was to assess the incidence of lamb mortality in Harnali sheep and to estimate maternal and additive genetic effects of lamb survival using the data of 2057 lambs born to 134 sires and 623 dams for the period of 20 years (2001-2020). The genetic evaluation was carried out using threshold animal models comprising direct and maternal effects using THRGIBBS1F90 and POSTGIBBSF90 programs. Cumulative mortality (95% CI (confidence interval)) for the S1 (lambs which died up to weaning age), S2 (lambs which died from birth to 6 months of age) and S3 (lambs which died from birth to 12 months of birth) groups was 8.41 (7.21-9.61), 14.10 (12.59-15.60) and 17.70 (16.05-19.34) %, respectively. The logistic regression analysis revealed significant (p < 0.05) influences of non-genetic factors and indicated that the female lambs, heavier dam and higher birth weight of lamb were associated with better survival as compared to their counterparts. The estimates of direct additive heritability for S1, S2 and S3 were 0.04 ± 0.01, 0.07 ± 0.03 and 0.11 ± 0.04, respectively. In addition to this, significant influences of the maternal permanent environmental effects were observed for lamb survival up to weaning as well as six months of age. Thus, the present findings suggest that lamb survival could be improved through better management practices but consideration of maternal permanent environmental effects is important for initial survival of the lamb.

Genetic and non-genetic effects associated with ewe productivity in Harnali sheep.

The objective of the current study was to estimate the genetic parameters for ewe productivity traits of Harnali sheep by examining non-genetic effects. The data records of 440 animals born to 85 sires and 259 dams were collected with respect to various traits such as litter size at birth (LSB), litter weight at birth (LWB), litter size at weaning (LSW), litter weight at weaning (LWW) and age at first lambing (AFL) for the period of 2001 to 2020. Genetic parameters were estimated by fitting a series of animal models using an average information restricted maximum likelihood (REML) algorithm in WOMBAT software. Least-squares analysis revealed significant (P < 0.05) influences of period of lambing, age and weight of ewe at lambing on the studied traits. These results indicated that heavier ewes had significantly higher (P < 0.05) values of litter weight traits than their counterparts. On the basis of likelihood ratio test, the estimates of direct heritability under best model for AFL, LSB, LWB, LSW and LWW were 0.06, 0.18, 0.09, 0.07 and 0.16, respectively. Maternal permanent environment effect made a significant contribution to the LSB trait (0.20). The genetic correlation between litter size and LWW was negative, while the remaining correlations were positive. The present results suggest that selection based on ewe productivity traits will result in low genetic progress and therefore the management role is more important for better gains.

Evaluating advanced computing techniques for predicting breeding values in Harnali sheep.

Advanced computing techniques have been used by animal researchers to understand the intricate data structures for deriving the most reliable allusions of populations in order to conserve genetically superior animals. The present attempt was made to evaluate the potential of two advanced techniques, artificial neural networks (ANN) and Bayesian technique (BT), for predicting breeding values (BV) of weaning weight (WWT) using data of 498 lambs born to 41 sires and 173 dams in Harnali sheep for the period from 2014 to 2019. The estimated BV for WWT was initially obtained using univariate animal model under restricted maximum likelihood procedure. ANN using multilayer perceptron with two hidden layers was fitted to training set (75%) of estimated BV to predict BV for test set (25%). Similarly, BT using Markov chain Monte Carlo (MCMC) method was also fitted to similar datasets. The high accuracy of prediction, i.e., correlation between BV and predicted BV, was observed as 0.89 and 0.90 under ANN and BT, respectively. Further, similar ranges of goodness of fit criteria, viz., R2, root mean square error (RMSE), mean absolute error (MAE), and bias, indicated that both ANN and BT had similar prediction ability, which was also confirmed by 10-fold cross-validation. The present study indicated high capability and analogous model adequacy for both techniques that can be exploited in selection programs.

Influence of maternal and additive genetic effects on offspring growth traits in Beetal goat.

The purpose of the present study was to obtain estimates of variance components and genetic parameters for direct and maternal effects on various growth traits in Beetal goat by fitting four animal models, attempting to separate direct genetic, maternal genetic and maternal permanent environmental effects under restricted maximum likelihood procedure. The data of 3,308 growth trait records of Beetal kids born during the period from 2004 to 2019 were used in the present study. Based on best fitted models, the direct additive h2 estimates were 0.06, 0.27, 0.37, 0.17 and 0.10 for birth weight (BWT), weight at 3 (WT3), 6 (WT6), 9 (WT9) and 12 (WT12) months of age, respectively. Maternal permanent environmental effects significantly contributed for 10% and 7% of total variance for BWT and WWT, respectively, which reduced direct heritability by 40 and 10% for respective traits from the models without these effects. For average daily gain (ADG1) and Kleiber ratios (KR1) up to weaning period (3 months) traits, maternal permanent environmental effects accounted for 7% and 8% of phenotypic variance, respectively, and resulted in a reduction of 6.6% and 5.4% in direct h2 of respective traits. For post-weaning traits, the maternal effects were non-significant (p > .05) which indicates diminishing influence of mothering ability for these traits. High and positive genetic correlations were obtained among WT3-WT6, WT6-WT9 and WT9-WT12 with correlations of 0.96 ± 0.25, 0.84 ± 0.23 and 0.90 ± 0.13, respectively. Thus, early selection at weaning age can be practised taking into consideration maternal variation for effective response to selection in Beetal goat.

Meta-analysis of SNP in growth hormone gene associated with milk traits in dairy cows.

Previous studies reported varied findings regarding growth hormone polymorphisms and their association with milk traits in dairy cattle. The objective of the present study was to combine the information of Alu1-derived gene polymorphisms of growth hormone in 6571 dairy cows using 51 published studies for obtaining pooled estimate of gene frequency of L allele in dairy cows and for deriving common effect size of association of gene variants with various milk traits (lactation milk yield, fat yield, fat%, protein yield, and protein%) using meta-analysis. The pooled estimate of gene frequency was obtained using proportion as effect size with 95% confidence interval under random effects model. For association analysis, standardized mean difference was employed as effect size under four genetic models comprising additive (LL vs. VV), dominant (LL + LV vs. VV), completely over dominant (LL + VV vs. LV), and recessive (LL vs. LV + VV). The heterogeneity between studies was estimated using Q test and I2 statistic. The results showed that pooled estimate of gene frequency of L allele was 0.81 (95% CI: 0.77, 0.85; I2 = 96.86%). Subgroup analysis revealed that it was significantly higher in Bos indicus cows (0.97, 95% CI 0.89, 1.00; I2 = 95.15%) than Bos taurus/cross cows (0.78, 95% CI 0.73, 0.82; I2 = 96.84%). An association analysis showed that the effects of GH variants on milk-related traits were not significant (P > 0.1) under all genetic models. Substantial range of heterogeneity indicated modest effects of SNP genotypes with milk traits. It was concluded that although allele L is predominant than V allele of GH in dairy cows over large geographical populations, they may not be particularly useful for selection programs for improving milk traits in dairy cows.