Study of the effect of genotype-environment interaction on age at first calving and production traits in Nellore cattle using multi-trait reaction norms and Bayesian inference

Genomic analysis of genotype-environment interaction in age at first calving of Murrah buffaloes

Age at first calving (AFC) is a measure of sexual maturity associated with the start of productive life of dairy animals. Additionally, a lower AFC reduces the generation interval and early culling of females. However, AFC has low heritability, making it a trait highly influenced by environmental factors. In this scenario, one way to improve the reproductive performance of buffalo cows is to select robust animals according to estimated breeding value (EBV) using models that include genotype-environment interaction (GEI) with the application of reaction norm models (RNMs). This can be achieved by understanding the genomic basis related to GEI of AFC. Thus, in this study, we aimed to predict EBV considering GEI via the RNM and identify candidate genes related to this component in dairy buffaloes through genome-wide association studies (GWAS). We used 1795 AFC records from three Murrah buffalo herds and formed environmental gradients (EGs) from contemporary group solutions obtained from genetic analysis of 270-day cumulative milk yield. Heritability estimates ranged from 0.15 to 0.39 along the EG. GWAS of the RNM slope parameter identified important genomic regions. The genomic window that explained the highest percentage of genetic variance of the slope (0.67%) was located on BBU1. After functional analysis, five candidate genes were detected, involved in two biological processes. The results suggested the existence of a GEI for AFC in Murrah buffaloes, with reclassification of animals when different environmental conditions were considered. The inclusion of genomic information increased the accuracy of breeding values for the intercept and slope of the reaction norm. GWAS analysis suggested that important genes associated with the AFC reaction norm slope were possibly also involved in biological processes related to lipid metabolism and immunity.

Genetic and phenotypic parameters for sexual precocity and parasite resistance traits in Nellore cattle

Indicator traits of sexual precocity are widely used as selection criteria for the genetic improvement of beef cattle; however, the impact of selection for these traits on resistance to endoparasites and ectoparasites is unknown. Therefore, this study aimed to estimate the genetic and phenotypic parameters for indicator traits of sexual precocity and parasite resistance in Nellore cattle. The sexual precocity traits evaluated were probability of first calving (PFC) and scrotal circumference at 12 and 18 months of age (SC12 and SC18). The resistance-related traits included tick (TC), gastrointestinal nematode egg (NEC), and Eimeria spp. oocyst (EOC) counts. (Co)variance components were estimated by Bayesian inference using multitrait animal models. The mean heritabilities for PFC, SC12, SC18, TC, NEC, and EOC were 0.23, 0.38, 0.42, 0.14, 0.16, and 0.06, respectively, and suggest that selection will change the mean values of these traits over time. The genetic and phenotypic correlations for most pairs formed by a precocity and a resistance trait were not different from zero, suggesting that selection for sexual precocity traits will not result in changes in resistance traits. Thus, selection for indicator traits of sexual precocity does not elicit unfavorable correlated responses in resistance to endoparasites and ectoparasites, and joint selection aimed at improving these traits can be performed using multitrait selection methods, when necessary.

Genetic parameters for mouth size and their influence on growth traits in pasture-raised Nelore cattle

Evaluating traits that allow breeders to increase production efficiency in beef production systems is important. The mouth size (MS) score is a trait easily measured and implemented by breeders. Bite size is related to MS in beef cattle and is a determinant of daily feed intake of pasture-raised animals, influencing their growth. The aim of this study was to estimate genetic parameters for MS, weaning weight (WW) and postweaning weight gain (PWG) of Nelore cattle and to evaluate the influence of the interaction between MS and WW on PWG. Phenotypic records of 134,282 Nelore animals born between 1995 and 2019 were used. Variance components were estimated using multitrait animal model with the Bayesian method. The model included the contemporary group as fixed effect, age at measurement of the trait as linear covariate, and direct additive genetic and residual effects as random effects. For WW, random maternal and maternal permanent environmental effects were added to the model. A Bayesian approach was used to analyze the interaction between WW clusters and MS. The heritability estimates were 0.24, 0.15, and 0.23 for MS, WW, and PWG, respectively. The genetic correlation between variables studied ranged from 0.24 to 0.46. The results suggest that animals with a larger mouth tend to have greater PWG, demonstrating the positive influence of MS score on the postweaning performance of cattle. The direct heritability estimates confirm the possibility of selecting animals for the traits studied.

Heteroscedastic Reaction Norm Models Improve the Assessment of Genotype by Environment Interaction for Growth, Reproductive, and Visual Score Traits in Nellore Cattle

The assessment of the presence of genotype by environment interaction (GxE) in beef cattle is very important in tropical countries with diverse climatic conditions and production systems. The present study aimed to assess the presence of GxE by using different reaction norm models for eleven traits related to growth, reproduction, and visual score in Nellore cattle. We studied five reaction norm models (RNM), fitting a linear model considering homoscedastic residual variance (RNM_homo), and four models considering heteroskedasticity, being linear (RNM_hete), quadratic (RNM_quad), linear spline (RNM_l-l), and quadratic spline (RNM_q-q). There was the presence of GxE for age at first calving (AFC), scrotal circumference (SC), weaning to yearling weight gain (WYG), and yearling weight (YW). The best models were RNM_l-l for YW and RNM_q-q for AFC, SC, and WYG. The heritability estimates for RNM_l-l ranged from 0.07 to 0.20, 0.42 to 0.61, 0.24 to 0.42, and 0.47 to 0.63 for AFC, SC, WYG, and YW, respectively. The heteroskedasticity in reaction norm models improves the assessment of the presence of GxE for YW, WYG, AFC, and SC. Additionally, the trajectories of reaction norms for these traits seem to be affected by a non-linear component, and selecting robust animals for these traits is an alternative to increase production and reduce environmental sensitivity.

Different selection practices affect the environmental sensitivity of beef cattle

The objective of the present study was to evaluate the effects of different selection practices on the environmental sensitivity of reproductive and growth traits in males and females of three Nellore selection lines [control (NeC), selection (NeS), and traditional (NeT) lines]. Moreover, genetic trends for the intercept and slope were estimated for each line, and the possible reranking of sires was examined. A total of 8,757 records of selection weight (SW), 3,331 records of scrotal circumference (SC), and 2,311 records of days to first calving (DFC) from Nellore cattle born between 1981 and 2017 were analyzed. (Co)variance components and genetic parameters of all traits were estimated using a reaction norm model with Gibbs sampler. In all cattle lines, the mean heritability of the studied traits ranged from 0.39 to 0.75 for SW in both males and females, from 0.46 to 0.68 for SC, and from 0.06 to 0.57 for DFC along with the environmental descriptor. In all cattle lines, the genetic correlation coefficients between the intercept and slope ranged from 0.03 to 0.81 for SW, from -0.14 to 0.39 for SC, and from -0.87 to -0.42 for DFC. Genetic trends for the slope and proportion of plastic genotypes indicated that the NeS line was more responsive to environmental changes, whereas the NeC and NeT lines tended to respond more modestly. Reranking of sires was observed for all traits, specifically in the NeC and NeT lines, because of the weak correlation between the opposite extreme environments. In the NeS line, reranking of sires was observed for DFC alone. Our results indicate that the effects of genotype-environment interaction are important and should be considered in genetic evaluations of Nellore cattle. Moreover, different selection practices affected the environmental sensitivity of the Nellore selection lines tested in this study.

Genomic reaction norm models exploiting genotype × environment interaction on sexual precocity indicator traits in Nellore cattle

Brazilian beef cattle are raised predominantly on pasture in a wide range of environments. In this scenario, genotype by environment (G×E) interaction is an important source of phenotypic variation in the reproductive traits. Hence, the evaluation of G×E interactions for heifer's early pregnancy (HP) and scrotal circumference (SC) traits in Nellore cattle, belonging to three breeding programs, was carried out to determine the animal's sensitivity to the environmental conditions (EC). The dataset consisted of 85 874 records for HP and 151 553 records for SC, from which 1800 heifers and 3343 young bulls were genotyped with the BovineHD BeadChip. Genotypic information for 826 sires was also used in the analyses. EC levels were based on the contemporary group solutions for yearling body weight. Linear reaction norm models (RNM), using pedigree information (RNM_A) or pedigree and genomic information (RNM_H), were used to infer G×E interactions. Two validation schemes were used to assess the predictive ability, with the following training populations: (a) forward scheme-dataset was split based on year of birth from 2008 for HP and from 2011 for SC; and (b) environment-specific scheme-low EC (-3.0 and -1.5) and high EC (1.5 and 3.0). The inclusion of the H matrix in RNM increased the genetic variance of the intercept and slope by 18.55 and 23.00% on average respectively, and provided genetic parameter estimates that were more accurate than those considering pedigree only. The same trend was observed for heritability estimates, which were 0.28-0.56 for SC and 0.26-0.49 for HP, using RNM_H, and 0.26-0.52 for SC and 0.22-0.45 for HP, using RNM_A. The lowest correlation observed between unfavorable (-3.0) and favorable (3.0) EC levels were 0.30 for HP and -0.12 for SC, indicating the presence of G×E interaction. The G×E interaction effect implied differences in animals' genetic merit and re-ranking of animals on different environmental conditions. SNP marker-environment interaction was detected for Nellore sexual precocity indicator traits with changes in effect and variance across EC levels. The RNM_H captured G×E interaction effects better than RNM_A and improved the predictive ability by around 14.04% for SC and 21.31% for HP. Using the forward scheme increased the overall predictive ability for SC (20.55%) and HP (11.06%) compared with the environment-specific scheme. The results suggest that the inclusion of genomic information combined with the pedigree to assess the G×E interaction leads to more accurate variance components and genetic parameter estimates.

Genotype-environment interaction for age at first calving in buffaloes, using the reaction norm model

The objective of this study was to evaluate the genotype-environment interaction effect on age at first calving in buffaloes. The records were analysed using two approaches: (a) standard animal model and (b) reaction norm model. For the reaction norm analysis, two environmental gradients were formed, using age of first calving or milk yield group contemporary average. The results showed differences in the heritability estimates when using the two approaches. The reaction norm model indicated high heritability in more favourable environments and low magnitude genetic correlations between extreme environments. Based on our findings, we verified the significance of the genotype-environment interaction effect on age at first calving in buffaloes.

CLUSTERS DE ROBUSTEZ COMO CRITÉRIO DE SELEÇÃO NO MELHORAMENTO GENÉTICO PARA MITIGAÇÃO DE IMPACTOS DAS MUDANÇAS CLIMÁTICAS

Mudanças climáticas são previstas para as próximas décadas e, consequentemente, seus impactos na pecuária bovina, sendo a seleção nos rebanhos uma maneira de amenizá-los. Este trabalho teve como objetivo desenvolver um sistema de seleção baseado nos parâmetros genéticos gerados por modelos de norma de reação adaptativa em bovinos da raça Nelore. Foram utilizados dados genealógicos e de crescimento fornecidos pela Associação Brasileira de Criadores de Bovinos. Definiu-se um gradiente ambiental baseado em valores médios de grupos contemporâneos padronizados. Para a predição de coeficientes das normas de reação adaptativas utilizou-se a regressão aleatória com polinômios cúbicos para pesos aos 450 dias com análise de sexos separados. Foram calculados os valores genéticos dos diferentes indivíduos em função de um gradiente ambiental utilizando o software BLUPF90. Os indivíduos foram classificados considerando coeficientes que gerassem normas com valores genéticos elevados e com menor variação ao longo do gradiente ambiental. Compensou-se, então, a elevação do valor genético e a sua robustez, criando clusters de robustez (CRs) com base na comparação direta entre os coeficientes. Os resultados da classificação mostraram que a seleção de indivíduos das classes de maior robustez devem gerar progênies com menor sensibilidade ambiental, visto que os coeficientes são componentes genéticos aditivos. Conclui-se que a seleção por clusters de robustez é uma forma de amenizar os impactos produzidos nos sistemas de produção por alterações nos ambientes de criação.