Reaction norms in weights at 365 days old in nellore bulls in northern Brazil

Genotype by environment interaction (GxE) studies are of particular interest in Brazil because of the regional diversity of environmental effects and the wide variety of management systems. The present study evaluates GxE effects on 365 d weight (365W) of Nellore cattle raised on pasture in northern Brazil. The analysis utilized random regression techniques to model the reaction norm. Fixed effects consisted of sex, contemporary group, and the covariate of age of cow at calving. The environmental gradient, defined by the concatenation of a bull and the state in which the calf was born, was modeled by second order Legendre polynomials. Direct additive genetic and residual effects were fit as random. Results showed differences in the magnitude of expression of genotype in proportion to decreasing favorability of the environment. As the environment became more unfavorable, the correlation of breeding value to different environments decreased. The correlations between the intercept and the level slope for 365W feature were of moderate magnitude, predominantly indicating the reclassification of sires in different environments. Reaction standard model was coherent from a technical and biological view point and enabled the perception of GxE in the genetic evaluation of Nellore cattle in the states of Maranhão, Pará and Tocantins.

Download Full-text

Reaction norms in weights at 365 days old in nellore bulls in northern Brazil

Semina Ciências Agrárias ◽

10.5433/1679-0359.2015v36n6supl2p4613 ◽

2015 ◽

Vol 36 (6Supl2) ◽

pp. 4613 ◽

Cited By ~ 1

Author(s):

Jorge Luís Ferreira ◽

Alliny Souza de Assis ◽

Fernando Brito Lopes ◽

Thomas Wayne Murphy ◽

Marcelo Corrêa da Silva ◽

...

Keyword(s):

Fixed Effects ◽

Reaction Norm ◽

Genotype By Environment Interaction ◽

Random Regression ◽

Residual Effects ◽

Breeding Value ◽

Environment Interaction ◽

Nellore Cattle ◽

Regression Techniques ◽

Northern Brazil

<p>Genotype by environment interaction (GxE) studies are of particular interest in Brazil because of the regional diversity of environmental effects and the wide variety of management systems. The present study evaluates GxE effects on 365 d weight (365W) of Nellore cattle raised on pasture in northern Brazil. The analysis utilized random regression techniques to model the reaction norm. Fixed effects consisted of sex, contemporary group, and the covariate of age of cow at calving. The environmental gradient, defined by the concatenation of a bull and the state in which the calf was born, was modeled by second order Legendre polynomials. Direct additive genetic and residual effects were fit as random. Results showed differences in the magnitude of expression of genotype in proportion to decreasing favorability of the environment. As the environment became more unfavorable, the correlation of breeding value to different environments decreased. The correlations between the intercept and the level slope for 365W feature were of moderate magnitude, predominantly indicating the reclassification of sires in different environments. Reaction standard model was coherent from a technical and biological view point and enabled the perception of GxE in the genetic evaluation of Nellore cattle in the states of Maranhão, Pará and Tocantins.</p><p> </p>

Download Full-text

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

Animal Production Science ◽

10.1071/an17048 ◽

2018 ◽

Vol 58 (11) ◽

pp. 1996

Author(s):

S. Ribeiro ◽

J. P. Eler ◽

V. B. Pedrosa ◽

G. J. M. Rosa ◽

J. B. S. Ferraz ◽

...

Keyword(s):

Genetic Correlation ◽

Environmental Gradient ◽

Genotype By Environment Interaction ◽

Reaction Norms ◽

Breeding Value ◽

Environment Interaction ◽

Genotype By Environment ◽

Genotype Environment Interaction ◽

Nellore Cattle ◽

Gradient Variation

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.

Download Full-text

Adaptability and stability analyses of plants using random regression models

PLoS ONE ◽

10.1371/journal.pone.0233200 ◽

2020 ◽

Vol 15 (12) ◽

pp. e0233200

Author(s):

Michel Henriques de Souza ◽

José Domingos Pereira Júnior ◽

Skarlet De Marco Steckling ◽

Jussara Mencalha ◽

Fabíola dos Santos Dias ◽

...

Keyword(s):

Plant Breeding ◽

Regression Models ◽

Real Data ◽

Reaction Norm ◽

Good Alternative ◽

Genotype By Environment Interaction ◽

Repeated Measurements ◽

Random Regression ◽

Environment Interaction ◽

Genetic Covariance

The evaluation of cultivars using multi-environment trials (MET) is an important step in plant breeding programs. One of the objectives of these evaluations is to understand the genotype by environment interaction (GEI). A method of determining the effect of GEI on the performance of cultivars is based on studies of adaptability and stability. Initial studies were based on linear regression; however, these methodologies have limitations, mainly in trials with genetic or statistical unbalanced, heterogeneity of residual variances, and genetic covariance. An alternative would be the use of random regression models (RRM), in which the behavior of the genotypes is characterized as a reaction norm using longitudinal data or repeated measurements and information regarding a covariance function. The objective of this work was the application of RRM in the study of the behavior of common bean cultivars using a MET, based on Legendre polynomials and genotype-ideotype distances. We used a set of 13 trials, which were classified as unfavorable or favorable environments. The results revealed that RRM enables the prediction of the genotypic values of cultivars in environments where they were not evaluated with high accuracy values, thereby circumventing the unbalanced of the experiments. From these values, it was possible to measure the genotypic adaptability according to ideotypes, according to their reaction norms. In addition, the stability of the cultivars can be interpreted as variation in the behavior of the ideotype. The use of ideotypes based on real data allowed a better comparison of the performance of cultivars across environments. The use of RRM in plant breeding is a good alternative to understand the behavior of cultivars in a MET, especially when we want to quantify the adaptability and stability of genotypes.

Download Full-text

Covariance function of Legendre polynomials for the modeling of Polled Nellore cattle growth in northern Brazil

Semina Ciências Agrárias ◽

10.5433/1679-0359.2019v40n2p781 ◽

2019 ◽

Vol 40 (2) ◽

pp. 781

Author(s):

Diego Helcias Cavalcante ◽

Severino Cavalcante Sousa Júnior ◽

Luciano Pinheiro Silva ◽

Carlos Henrique Mendes Malhado ◽

Raimundo Martins Filho ◽

...

Keyword(s):

Fixed Effects ◽

Growth Parameters ◽

Random Effect ◽

Growth Curves ◽

Random Regression ◽

Analytical Models ◽

Residual Variance ◽

Age Related ◽

Nellore Cattle ◽

Northern Brazil

This study aimed to compare random regression models fitted by Legendre orthogonal polynomials and determine which best fits changes in Nellore cattle growth parameters. Age polynomial functions of different orders were evaluated using a random-effect modeling associated with a genetic study of cattle growth curves. For this purpose, weight records (15,148) were performed in Polled Nellore bovines (3,115), aged between 1 and 660 days, reared in northern Brazil and born between 1995 and 2010. The fixed effects of analytical models comprised age-matched groups, heifer calving age (linear and quadratic), and fourth-order Legendre age polynomial (cubic), depicting the mean growth curve. Besides, different order functions were considered for random effects, so that (co) variance associated with genetic effects (direct and maternal) and permanent environmental effects (animal and maternal) could be modeled. Residual variance was fitted by six heterogeneous classes throughout the analyzed period. According to AIC and BIC criteria, the model 6333 allowed the fitting of changes in variance and covariance over time (genetic and environmental). Thus, this model can be used to describe age-related changes in Polled Nellore cattle reared in northern Brazil.

Download Full-text

Assessment of Genotype by Environment Interaction Via Reaction Norms for Milk Yield in Holstein Cattle of Southern Brazil

Annals of Animal Science ◽

10.2478/aoas-2020-0032 ◽

2020 ◽

Vol 20 (3) ◽

pp. 1101-1112

Author(s):

Henrique Alberto Mulim ◽

Luis Fernando Batista Pinto ◽

Aline Zampar ◽

Gerson Barreto Mourão ◽

Altair Antônio Valloto ◽

...

Keyword(s):

Milk Production ◽

Milk Yield ◽

Genetic Correlations ◽

Genotype By Environment Interaction ◽

Reaction Norms ◽

Random Regression ◽

Breeding Value ◽

Environment Interaction ◽

Southern Brazil ◽

Genotype By Environment

AbstractThe experiments reported in this research paper were aimed at assessing the genetic responses of a Holstein cow population, as a response to the variations in environmental temperature, through the analysis of the effects resulting from the genotype by environment interaction (GEI), based on reaction norms. Therefore, milk production data was collected from the database of the Paraná Holstein Breeders Association in Brazil for 67,360 primiparous cows born between 1990 and 2015, with the purpose of evaluating the temperature effect, considered as an environmental variable, distinguished under six gradients (17 ºC to 19.5 ºC) over the region. A random regression model was adopted, utilizing the fourth order under the Legendre polynomials, applying the mixed models of analysis by the REML method, and using the WOMBAT software. Additionally, the breeding value of the 15 most representative bulls was assessed, in response to the changes in the temperature gradient. The total milk production on average was estimated at 8,412.83 ± 2,012.08 kg. The heritabilities estimates were found in the low to moderate range, from 0.18 to 0.23, displaying a decline with a rise in the temperature, highlighting the influence it exerted on the heritabilities. Variations in the genetic expression of some bulls were noted to show differences of up to 289 kg of milk in response to the increase in the temperature from 17 ºC to 19.5 ºC. However, all the genetic correlations between the gradients for milk yield were above 0.80, in the range of 0.873 to 0.998, revealing no remarkable interaction between the genotype and environment. This result indicates that the application of the temperature variable in the models of genetic analysis in southern Brazil is not required.

Download Full-text

Genetic Parameters for Tolerance to Heat Stress in Crossbred Swine Carcass Traits

Frontiers in Genetics ◽

10.3389/fgene.2020.612815 ◽

2021 ◽

Vol 11 ◽

Author(s):

Maria Usala ◽

Nicolò Pietro Paolo Macciotta ◽

Matteo Bergamaschi ◽

Christian Maltecca ◽

Justin Fix ◽

...

Keyword(s):

Heat Stress ◽

Environmental Conditions ◽

Extreme Values ◽

Carcass Traits ◽

Genetic Material ◽

Genotype By Environment Interaction ◽

Random Regression ◽

Breeding Value ◽

Environment Interaction ◽

Genotype By Environment

Data for loin and backfat depth, as well as carcass growth of 126,051 three-way crossbred pigs raised between 2015 and 2019, were combined with climate records of air temperature, relative humidity, and temperature–humidity index. Environmental covariates with the largest impact on the studied traits were incorporated in a random regression model that also included genomic information. Genetic control of tolerance to heat stress and the presence of genotype by environment interaction were detected. Its magnitude was more substantial for loin depth and carcass growth, but all the traits studied showed a different impact of heat stress and different magnitude of genotype by environment interaction. For backfat depth, heritability was larger under comfortable conditions (no heat stress), as compared to heat stress conditions. Genetic correlations between extreme values of environmental conditions were lower (∼0.5 to negative) for growth and loin depth. Based on the solutions obtained from the model, sires were ranked on their breeding value for general performance and tolerance to heat stress. Antagonism between overall performance and tolerance to heat stress was moderate. Still, the models tested can provide valuable information to identify genetic material that is resilient and can perform equally when environmental conditions change. Overall, the results obtained from this study suggest the existence of genotype by environment interaction for carcass traits, as a possible genetic contributor to heat tolerance in swine.

Download Full-text

210 Genotype by environment interaction for pre-weaning survival in commercial crossbred pigs

Journal of Animal Science ◽

10.1093/jas/skz258.080 ◽

2019 ◽

Vol 97 (Supplement_3) ◽

pp. 40-41

Author(s):

Francesco Tiezzi ◽

Justin Fix ◽

Clint Schwab

Keyword(s):

Fixed Effects ◽

Genotype By Environment Interaction ◽

Single Step ◽

Random Regression ◽

Residual Variance ◽

Phenotypic Variance ◽

Environment Interaction ◽

Genomic Breeding ◽

Genotype By Environment ◽

The Impact

Abstract Pre-weaning survival (PWS) is a trait of major importance in swine productions systems. Selection is made difficult by the low heritability of the trait(s) and genotype by environment interaction (GxE) could be present. In addition to that, given the binary nature of the trait, phenotypic variance is virtually null in contemporary group where PWS is large. The objective of this study was to assess the impact of heterogeneous phenotypic variance and GxE on PWS. We used survival to day 5 as a trait of interest, available for 574,828 crossbred piglets raised in a commercial environment. Piglets were progeny of 559 sires (450 genotyped with 60k SNP chip) and raised into 242 contemporary groups (CG). In estimating GxE, the E component was represented by fourth-order Legendre polynomials built on the CG solutions. A Single-Step random-regression sire model with heterogeneous residuals (10 classes) was used, once the CG solutions were obtained by a similar model that neglected GxE. Other (fixed) effects in the models were sow parity, litter size, litter transfer of the piglet, gender of the piglet, dam genetic line and litter (random). Results show an increase in phenotypic and residual variance as PWS decreased, which is expected given the nature of the binary trait. Genetic variance increased following the same trend, which made heritability to be constant (~2%). Genomic breeding values for most represented sires were plotted as a function of CG survival. While no variation among the sires can be found in CG with full survival, larger variance is shown as PWS decreases. Re-ranking among the sires is present as CG change. Results suggest that modeling PWS should account for the heterogeneous variance among CG. A moderate GxE in PWS at day 5 is also suggested.

Download Full-text

Genotype×environment interaction for weaning weight in Nellore cattle using reaction norm analysis

Livestock Science ◽

10.1016/j.livsci.2015.03.032 ◽

2015 ◽

Vol 176 ◽

pp. 40-46 ◽

Cited By ~ 5

Author(s):

S. Ribeiro ◽

J.P. Eler ◽

V.B. Pedrosa ◽

G.J.M. Rosa ◽

J.B.S. Ferraz ◽

...

Keyword(s):

Reaction Norm ◽

Environment Interaction ◽

Weaning Weight ◽

Genotype Environment Interaction ◽

Nellore Cattle

Download Full-text

Phenotypic and genetic characteristics of longevity in Lori-Bakhtiari sheep

Biotechnology in Animal Husbandry ◽

10.2298/bah0701323v ◽

2007 ◽

Vol 23 (5-6-1) ◽

pp. 323-329 ◽

Cited By ~ 4

Author(s):

M. Vatankhah ◽

F. Zamani

Keyword(s):

Body Weight ◽

Fixed Effects ◽

Residual Effects ◽

Breeding Value ◽

Weight Estimation ◽

Genetic Characteristics ◽

Breeding Station ◽

Life Traits ◽

Selection For ◽

Genetic Trends

Longevity records of 978 Lori-Bakhtiari ewes were collected from a research flock at the Lori-Bakhtiari sheep breeding station during 1989 to 2006. Single-trait animal model used to analyze trait, included fixed effects of year of production, ewe body weight as covariable and random effects additive genetic of animal and residual effects. Phenotypic and genetic trends were estimated as regression of average phenotypic value and breeding value by birth year of ewe. Results show that, 49.80%, 22.49% and 27.71% of breeding ewes left the flock for illness, low production and oldness respectively. The overall mean (? s.e.) of ewe's longevity was 1779.91 (22.10) days. The effect of year of production and ewe's body weight on longevity were significant (p<0.01), and longevity increased by 41.84 ? 2.80 days with 1 kg of ewe body weight. Estimation of heritability for longevity was 0.33 ? 0.07. The phenotypic and genetic trends of longevity were significant (P<0.01) and estimated as -84.65 and -19.02 days, respectively. Thus, illness is very important reasons to removed ewes from flock. Longevity could be improved by selection, but early life traits is needed to indirect selection for longevity.

Download Full-text