Effect of food supplementation on in vitro embryo production and growth performance in prepubertal Nelore heifers

In vitro embryos production from prepubertal heifers can help contribute to breeding programs; however, strategies are necessary to increase their embryo production. The aim of this study was to investigate the effects of two nutritional plans on oocyte recovery, embryo production and growth performance of prepubertal Nelore heifers. Thirty-four Nelore heifers with age of 6.5 months were divided into two feeding treatments (NP1 and NP2). The NP1 diets served as the control and NP2 diets were formulated to contain an average of 1.22-fold more energy than NP1. After 3 months of supplementation, the animals underwent follicular aspiration (ovum pick-up, OPU) every 21 d for 3 months and embryos were produced in vitro. Wither height, chest depth, body weight and subcutaneous fat of animals were measured. The number of retrieved and viable oocytes per OPU were 1.49-fold and 1.42-fold greater in NP2 heifers (p = 0.018 and p = 0.049, respectively) than those in NP1 heifers. Heifers administered NP2 produced 29.7% blastocysts, a percentage higher than NP1 animals that produced 24.40% embryos (p < 0.05). Consequently, females in the NP2 treatment showed improved body development. These results indicate a positive effect of a higher energy diet on assisted reproduction and body development in prepubertal heifers.

Genetic association between feed efficiency, growth, scrotal circumference, and carcass traits in Guzerat cattle

The objective of this study was to estimate the genetic parameters for feed efficiency-related traits and their genetic correlations with growth, male fertility, and carcass traits using multi-trait analysis in Guzerat cattle. Further, it aimed to predict the direct and correlated responses for feed efficiency traits when selection was applied for growth, male fertility, and carcass traits. The evaluated traits were adjusted weight at 120 (W120), 210 (W210), 365 (W365), and 450 days of age (W450), adjusted scrotal circumference at 365 days of age (SC365) and at 450 days of age (SC450), scrotal circumference, ribeye area (REA), backfat thickness (BFT), rump fat thickness (RFT), residual feed intake (RFI), and dry matter intake (DMI). The genetic parameters were obtained by the restricted maximum likelihood method (REML), using an animal model in multi-trait analyses. The heritability estimates for W120, W210, W365, W450, SC365, and SC450 varied from low to high (0.17 to 0.39). The carcass traits, REA, BFT, and RFT, displayed low to moderate heritability estimates, 0.27, 0.10, and 0.31, respectively. The heritability estimates for RFI (0.15) and DMI (0.23) were low and moderate, respectively. The RFI showed low genetic correlations with growth traits, ranging from - 0.07 to 0.22, from 0.03 to 0.05 for scrotal circumference, and from - 0.35 to 0.16 for carcass, except for DMI, which ranged from 0.42 to 0.46. The RFI and DMI presented enough additive genetic variability to be used as selection criteria in Guzerat breed genetic improvement program. Additionally, the response to selection for RFI would be higher when selection is performed directly for this trait. The selection for residual feed intake would not promote unfavorable correlated responses for scrotal circumference, carcass (yield and finish), and growth traits. Therefore, the selection for more efficient animals would not compromise the productive, reproductive, and carcass performance, contributing to reduce the production costs, increasing the profitability and sustainability of beef cattle production in tropical areas.

Genomic prediction for meat and carcass traits in Nellore cattle using a Markov blanket algorithm

This study was carried out to evaluate the advantage of preselecting SNP markers using Markov blanket algorithm regarding the accuracy of genomic prediction for carcass and meat quality traits in Nellore cattle. This study considered 3675, 3680, 3660 and 524 records of rib eye area (REA), back fat thickness (BF), rump fat (RF), and Warner-Bratzler shear force (WBSF), respectively, from the Nellore Brazil Breeding Program. The animals have been genotyped using low-density SNP panel (30 k), and subsequently imputed for arrays with 777 k SNPs. Four Bayesian specifications of genomic regression models, namely Bayes A, Bayes B, Bayes Cπ and Bayesian Ridge Regression methods were compared in terms of prediction accuracy using a five folds cross-validation. Prediction accuracy for REA, BF and RF was all similar using the Bayesian Alphabet models, ranging from 0.75 to 0.95. For WBSF, the predictive ability was higher using Bayes B (0.47) than other methods (0.39 to 0.42). Although the prediction accuracies using Markov blanket of SNP markers were lower than those using all SNPs, for WBSF the relative gain was lower than 13%. With a subset of informative SNPs markers, identified using Markov blanket, probably, is possible to capture a large proportion of the genetic variance for WBSF. The development of low-density and customized arrays using Markov blanket might be cost-effective to perform a genomic selection for this trait, increasing the number of evaluated animals, improving the management decisions based on genomic information and applying genomic selection on a large scale.