Reaction norms for the study of genotype-environment interaction for growth and indicator traits of sexual precocity in Nellore cattle

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.

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.

Weak genotype x environment interaction suggests that measuring scrotal circumference at 12 and 18 months of age is helpful to select precocious Brahman cattle

The aim of this study was to evaluate the genotype x environment interaction (GxE) for scrotal circumference (SC) measured at different ages using pedigree-based (A -1) and pedigree and genomic-based (H -1) relationship matrices. Data from 1,515 Brahman bulls, from the Cooperative Research Centre for Beef Genetic Technologies (Beef CRC) experimental dataset were used in this study. SC was adjusted to age and body weight measured at 6 months (SC6), 12 months (SC12), 18 months (SC18) and 24 months of age (SC24). Body weight (BW) measured at 6 months (BW6), 12 months (BW12), 18 months (BW18) and 24 months of age (BW24) were used as criteria to describe the environment for SC in each age. All the animals measured were genotyped using medium-density SNP chips ("50k" or "70k" SNP) and their genotype were imputed using a reference panel with 729,068 SNP. The environment gradient (EG) was obtained by standardizing the solutions of the contemporary groups obtained by Animal Model with BW as the dependent variable. Then, the reaction norms (RN) were determined through a Random Regression Model. The breeding values (EBV) were estimated using either A -1 or H -1. The rank correlation was obtained using Spearman's correlation among the EBV estimated for the traits in analysis. For SC6 and SC24, higher estimates of heritability (h²) were obtained using A -1, when compared to those observed with H -1. In those ages, the improvement of the environment decreases the h² coefficient. On the other hand, the h² for SC12 and SC18 increased as the environment became more favorable, regardless of the matrix used. The RN for SC6 and SC24 estimated using A -1 and H -1 showed a decrease of variance from the worst to the best environment, an indication of existence of GxE. On the other hand, for SC12 and SC18, there were no significant differences between the EBV estimated in the lower and in the higher environments, regardless of the kinship matrix used, suggesting absence of GxE on those ages. Spearman's correlation among EBV estimated using A -1 and H -1 in different EG were practically equal to unity for all traits evaluated. In our study, there was weak evidence of GxE effect on SC in ages suitable for selection for sexual precocity. So, the absence of GxE at 12 and 18 months means these ages are advantageous for measuring SC to selection for sexual precocity. The advantage is that no changes in classification were observed when the sires were evaluated in different environments.

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.

Effect of the X chromosome in genomic evaluations of reproductive traits in beef cattle

The aim of this study was to evaluate whether there are predictive advantages for breeding values with inclusion of X chromosome genomic markers for reproductive (occurrence of early pregnancy - P16 and age at first calving - AFC) and andrological (scrotal circumference -SC) variables in beef cattle. There were 3263 genotypes of females and males evaluated. There were breeding value estimates for SC, AFC and P16 considering two scenarios: 1) only autosomal markers or 2) autosomal and X chromosome markers. To evaluate effects of inclusion of X chromosome markers on selection, responses to selection were compared including or not including genomic marker information from the X chromosome. There were greater heritability estimates for SC (0.40 and 0.31), AFC (0.11 and 0.09) and P16 (0.43 and 0.38) when analyses included, compared with not including, genomic marker information from the X chromosome. When selection is based on results from analyses that did not include information for the X chromosome, there was about a 7 % lesser mean genomic breeding value for the SC traits for selected animals. For P16, there was an approximate 4% lesser breeding value without inclusion of genomic marker information from the X chromosome, while this inclusion did not have as great an effect on the breeding value for AFC. There was an average predictive correlation of 0.79, 0.98 and 0.84 for SC, AFC and P16, respectively. These estimates indicate inclusion of the X chromosome genomic marker information in the analysis can improve prediction of genomic breeding values, especially for SC.

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.

Genotype x Environment Interaction for reproductive traits in brazilian Nellore breed cattle

SUMMARY The objective of this study was to evaluate the effect of the genotype-environment interaction (GEI) for scrotal circumference traits measured at different ages, 365 (SC365), 450 (SC450) and 550 (SC550) days of age, and age at first calving (AFC) for Nellore animals raised in different regions of Brazil. For the evaluation, the herds were grouped in the following regions of the country: North, Southeast and Central-west, using information from 26,619, 28,730, 14,476, 15,397 for the traits SC365, SC450, SC550 and AFC respectively. Genetic parameters, as well as the assessment of GEI were performed using Bayesian inference, using the programs of the BLUPF90. The estimated heritabilities were: 0.465 ± 0.021, 0.500 ± 0.022, 0.492 ± 0.026, 0.117 ± 0.017 for SC365, SC450, SC550 and AFC respectively. The results obtained in the analysis, indicated that this interaction was not significant for SC at different ages (genetic correlation, rg> 0.8). For AFC, significant effect of GEI was observed for combinations involving the Northern region (rg<0.8), indicating that this interaction should be considered by the genetic evaluation programs in this region.

Genotype × prenatal and post-weaning nutritional environment interaction in a composite beef cattle breed using reaction norms and a multi-trait model

Environmental effects have been shown to influence several economically important traits in beef cattle. In this study, genotype × nutritional environment interaction has been evaluated in a composite beef cattle breed (50% Red Angus, 25% Charolais, 25% Tarentaise). Four nutritional environments (marginal-restricted [MARG-RES], marginal-control [MARG-CTRL], adequate-restricted [ADEQ-RES], and adequate-control [ADEQ-CTRL]) were created based on two levels of winter supplement provided to dams grazing winter range during gestation (MARG and ADEQ) and two levels of input to offspring during post-weaning development (RES and CTRL). Genetic parameters of average daily gain (ADG) during the 140-d post-wean trial, yearling weight (YW), and ultrasound measurement of fat depth (FAT) at the 12th rib and intramuscular fat percentage (IMF) of 3,020 individuals in the four environments were estimated. The heritabilities estimated using a single trait mixed linear model were: ADG: 0.21, 0.23, 0.19 and 0.21; YW: 0.27, 0.33, 0.20 and 0.26; FAT: 0.30, 0.29, 0.29, 0.55; IMF: 0.45, 0.51, 0.33, 0.53 for MARG-RES, ADEQ-RES, MARG-CTRL and ADEQ-CTRL, respectively. The extent of genotype × environment interaction was modeled using two separate methods: reaction norms and multi-trait models. The genetic correlations were estimated using a multi-trait model for ADG, YW, FAT and IMF. Growth traits (ADG, YW) and FAT showed correlations less than 0.80 across the four different environments indicating genotype by environment interaction. For example, genetic correlation for ADG between MARG-CTRL and MARG-RES was 0.65 and 0.73 between ADEQ-RES and MARG-RES. In this example, the former genetic correlation corresponds to differences in post-weaning nutritional environment, and the later represents a nutritional difference imposed on dams (i.e., prenatal environment), potentially mediated via fetal programming. The reaction norm model results were in concordance with the multi-trait model, genotype by environment interaction had a higher effect on traits with a lower heritability.

Reaction norm for yearling weight in beef cattle using single-step genomic evaluation

When the environment on which the animals are raised is very diverse, selecting the best sires for different environments may require the use of models that account for genotype by environment interaction (G × E). The main objective of this study was to evaluate the existence of G × E for yearling weight (YW) in Nellore cattle using reaction norm models with only pedigree and pedigree combined with genomic relationships. Additionally, genomic regions associated with each environment gradient were identified. A total of 67,996 YW records were used in reaction norm models to calculate EBV and genomic EBV. The method of choice for genomic evaluations was single-step genomic BLUP (ssGBLUP). Traditional and genomic models were tested on the ability to predict future animal performance. Genetic parameters for YW were obtained with the average information restricted maximum likelihood method, with and without adding genomic information for 5,091 animals. Additive genetic variances explained by windows of 200 adjacent SNP were used to identify genomic regions associated with the environmental gradient. Estimated variance components for the intercept and the slope in traditional and genomic models were similar. In both models, the observed changes in heritabilities and genetic correlations for YW across environments indicate the occurrence of genotype by environment interactions. Both traditional and genomic models were capable of identifying the genotype by environment interaction; however, the inclusion of genomic information in reaction norm models improved the ability to predict animals' future performance by 7.9% on average. The proportion of genetic variance explained by the top SNP window was 0.77% for the regression intercept (BTA5) and 0.82% for the slope (BTA14). Single-step GBLUP seems to be a suitable model to predict genetic values for YW in different production environments.

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.

Genotype by environment interaction for yearling weight in Nellore cattle applying reaction norms models

In the present study, a possible existence of genotype × environment interaction was verified for yearling weight in Nellore cattle, utilising a reaction norms model. Therefore, possible changes in the breeding value were evaluated for 46 032 animals, from three distinct herds, according to the environmental gradient variation of the different contemporary groups. Under a Bayesian approach, analyses were carried out utilising INTERGEN software resulting in solutions of contemporary groups dispersed in the environmental gradient from –90 to +100 kg. The estimates of heritability coefficients ranged from 0.19 to 0.63 through the environmental gradient and the genetic correlation between intercept and slope of the reaction norms was 0.76. The genetic correlation considering all animals of the herds in the environmental gradient ranged from 0.83 to 1.0, and the correlation between breeding values of bulls in different environments ranged from 0.79 to 1.0. The results showed no effect of genotype × environment interaction on yearling weight in the herds of this study. However, it is important to verify a possible influence of the genotype × environment in the genetic evaluation of beef cattle, as different environments might cause interference in gene expression and consequently difference in phenotypic response.