Genetic analysis of first lactation and lifetime performance traits in composite Vrindavani cattle: important considerations for higher milk production.

The present study was aimed to evaluate the influence of non-genetic factors on several first lactation and lifetime performance traits and elucidate their genetic parameters in an organized Vrindavani cattle population. Data on eight first-lactation and thirteen lifetime traits were collected on 2400 cows with pedigree records that were reared during 33-year period (1989-2021). The first-lactation traits included age at first calving (AFC), total milk yield (FTMY), standard milk yield (FSMY305), peak yield (FPY), lactation length (FLL), dry period (FDP), service period (FSP) and calving interval (FCI). Whereas, the lifetime traits mainly included total lifetime milk yield (TLMY), total standard milk yield (TSMY), number of lactations completed (NL), total lactation length (TLL), herd life (HL), productive life (PL), average milk yield per day of herd life (TLMY/HL), average milk yield per day of productive life (TLMY/PL), average milk yield per day of productive life (TLMY/TLL). Other lifetime production traits included average service period (ASP), average dry period (ADP), average calving interval (ACI) and unproductive days (UD). The heritability estimates of first-lactation traits ranged between 0.026 and 0.228 and were found to be low for AFC (0.180 ± 0.042), FCI (0.191 ± 0.125), FSMY305 (0.145 ± 0.061), FTMY (0.165 ± 0.048), FDP (0.052 ± 0.049) and FSP (0.026 ± 0.033); however, FLL (0.229 ± 0.044) and FPY (0.202 ± 0.046) showed moderate heritability. Positive phenotypic correlation (p < 0.001) was revealed among FTMY, TLMY, TLL, HL and PL. The AFC produced a significant effect (p < 0.05) on several traits i,e, TLL, TLMY/HL, FSMY305, FPY, TLMY, HL and TLMY/PL. Lower AFC was associated with higher TLMY, TLL and TLMY/HL; while FSMY305, FPY, HL and TLMY/PL were higher in heifers that calved late in their life. The results revealed that AFC may be optimized with first lactation and lifetime traits for this population.

Genome wide copy number variations using Porcine 60K SNP Beadchip in Landlly pigs.

In the present study, Porcine 60K SNP genotype data from 69 Landlly pigs were used to explore Copy Number Variations (CNVs) across the autosomes. A total of 386 CNVs were identified using Hidden Markov Model (HMM) in PennCNV software, which were subsequently aggregated to 115 CNV regions (CNVRs). Among the total detected CNVRs, 58 gain, 49 were loss type while remaining 8 events were both gain and loss types. Identified CNVRs covered 12.5 Mb (0.55%) of Sus scrofa reference 11.1 genome. Comparison of our results with previous investigations on pigs revealed that approximately 75% CNVRs were novel, which may be due to differences in genetic background, environment and implementation of artificial selection in Landlly pigs. Functional annotation and pathway analysis showed the significant enrichment of 267 well-annotated Sus scrofa genes in CNVRs. These genes were involved in different biological functions like sensory perception, meat quality traits, back fat thickness and immunity. Additionally, KIT and FUT1 were two major genes detected on CNVR in our population. This investigation provided a comprehensive overview of CNV distribution in the Indian porcine genome for the first time, which may be useful for further investigating the association of important quantitative traits in Landlly pigs.Highlights115 CNVRs were identified in 69 Landlly pig population.Approximately 75% detected CNVRs were novel for Landlly population.Significant enrichment of 267 well-annotated Sus scrofa genes observed in these CNVRs.These genes were involved in different biological functions like sensory perception, meat quality traits, back fat thickness and immunity.Comprehensive CNV map in the Indian porcine genome developed for the first time.

Bayesian analysis reveals the influence of maternal effect on pre-weaning body weights in Landlly piglets.

The present study was undertaken to estimate the (co)variance components and genetic parameters of body weights recorded in Landlly piglets from birth to weaning at weekly intervals (w0 to w6). The data pertained to body weights of 2462 piglets, born to 91 sires and 159 dams across different generations during a 7-year period from 2014 to 2020. Five animal models (I-V), differentiated by inclusion or exclusion of maternal effects with or without covariance between maternal and direct genetic effects, were fitted on the data using the Bayesian algorithm. The analyses were implemented by Gibbs sampling in the BLUPF90 program and Markov chain Monte Carlo (MCMC) methodology was used to draw samples of posterior distribution pertaining to (co)variance components. Based on deviance information criteria (DIC), model V with inclusion of direct additive genetic, direct maternal genetic and permanent environmental effect of dam as random factors along with covariance between direct additive and maternal effects best fitted the data on pre-weaning traits (w0 to w5). Whereas, model I incorporating only the direct additive genetic effect best fitted the weaning weight (w6) data in Landlly piglets. The posterior mean estimates of direct heritability under the best models for W0 to W6 were 0.13, 0.19, 0.29, 0.13, 0.26, 0.32 and 0.46, respectively. Inclusion of the maternal component helped in better partitioning of variance for different body weights in Landlly piglets. The maternal heritability ranged from 0.06 to 0.14, while the litter heritability ranged from 0.11 to 0.15 for pre-weaning weights (W0 to W5) under the best-fit models. The influence of maternal environment was greater than maternal genetic effect from birth to 4th week of age. The results implied that variations in body weight of Landlly pigs were genetically controlled to moderate levels (especially w2 and w4) with contributions from direct additive and maternal genotype that can be exploited by designing efficient breeding programmes.

Genome-wide elucidation of CNV regions and their association with production and reproduction traits in composite Vrindavani cattle.

The present study was aimed to analyze the genome-wide copy number variations (CNVs) in Vrindavani composite cattle and concatenate them into CNV regions (CNVRs), and finally test the association of CNVRs with different production and reproduction traits. Genotypic data, generated on BovineSNP50 Beadchip (v3) array for 96 Vrindavani animals, was used to elucidate the CNVs at the genome level. Intensity data covering over 53,218 SNP genotypes on bovine genome was used. Algorithm based on Hidden Markov Model was employed in PennCNV program to detect, normalize and filter CNVs across the genome. 252 putative CNVs, detected via PennCNV program, in different individuals were concatenated into 71 CNV regions (CNVRs) using CNVRuler program. Association of CNVRs with important (re)production traits in Vrindavani animals was assessed using linear regression. Five CNVRs were found to be significantly associated with ten important (re)production traits. The genes harbored in these regions provided useful insights into the association of CNVRs with genes and ultimately the variation at phenotype level. Important genes that overlapped with CNVRs included WASHC4, HS6ST3, MBNL2, TOLLIP, PIDD1 and TSPAN4. Furthermore, the CNVRs were found to overlap with important QTLs available in AnimalQTL database which affect milk yield and composition along with reproduction and immune function traits. The copy number states of three enes were validated using digital droplet PCR technique. The results from the present study significantly enhance the understanding about CNVs in Vrindavani cattle and should help establish its CNV map. The study will also enable further investigation on association of these variants with important traits of economic interest including disease incidence.

Accurate assessment of body weights using morphometric measurements in Landlly pigs.

The aim of the study was to evaluate 16 novel morphometric traits of Landlly piglets at weaning (6 weeks) and post weaning (8 weeks) stage and to predict corresponding body weight from the measurements. A total of 279 Landlly piglets (n = 279, 75% Landrace + 25% Ghurrah crosses) were enrolled in this study. Body length, heart girth, paunch girth, height at wither, height at back, rump width, thigh circumference, neck circumference, and body depth had high correlation coefficients (0.8-0.97) with body weight at both the stages. Stepwise regression showed that body length and heart girth contributed most in prediction of both body weights while height at wither for body weight at 6 weeks and neck circumference for body weight at 8 weeks was the next highest contributing trait. Akaike's information criterion, Bayesian information criteria, adjusted R2, concordance correlation coefficient, bias correction factor, modeling efficiency, and coefficient of model determination were used to determine the most appropriate model for the prediction of body weight. Model containing body length and heart girth was fitted best to data for prediction of body weight at both weaning and post weaning stage with adjusted R2 values of 0.94 and 0.96, respectively. Hence, 2 different models were proposed for accurately predicting body weight in Landlly pigs at 6 and 8 weeks.