scholarly journals Genotype by Environment Interaction in Pinus sylvestris L. in Southern Sweden

2008 ◽  
Vol 57 (1-6) ◽  
pp. 306-311 ◽  
Author(s):  
B. Hannrup ◽  
G. Jansson ◽  
Ö. Danell
Keyword(s):  
Pinus Sylvestris ◽  
Genetic Correlation ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Site Index ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Height Increment ◽  
Southern Sweden ◽  
Genotype By Environment

Abstract To estimate the amount of genotype by environment interaction (G x E) data was obtained within the Swedish breeding program of Pinus sylvestris L. The calculations were based on estimates of G x E expressed by the genetic correlations across trials. In total, 66 progeny trials were included coming from 17 different test series. The number of parents tested per progeny trial was in average 52. Some parents were tested in several series and in total 812 parents were represented in the study. The results of our study showed that the amount of G x E for growth traits in Pinus sylvestris in southern Sweden was low. The median genetic correlation across trials for height, height increment and diameter were in the range 0.75-0.80 and the pattern of interaction was largely unpredictable from site differences in site index, latitude, longitude and altitude.

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

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.

The genetic variation in the timing of heteroblastic transition in Eucalyptus globulus is stable across environments

2011 ◽  
Vol 59 (2) ◽  
pp. 170 ◽  
Author(s):  
M. G. Hamilton ◽  
P. A. Tilyard ◽  
D. R. Williams ◽  
R. E. Vaillancourt ◽  
T. J. Wardlaw ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Phase Change ◽  
Eucalyptus Globulus ◽  
Developmental Change ◽  
Genetic Correlations ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Narrow Sense Heritability ◽  
Genotype By Environment ◽  
Analyse Data

Eucalyptus globulus is one of the best known examples of a heteroblastic plant. It exhibits a dramatic phase change from distinctive juvenile to adult leaves, but the timing of this transition varies markedly. We examined the genetic variation in the timing of heteroblastic transition using five large open-pollinated progeny trials established in north-western Tasmania. We used univariate and multi-variate mixed models to analyse data on the presence/absence of adult or intermediate foliage at age 2 years from a total of 14 860 trees across five trials, as well as height to heteroblastic phase change from one trial. Up to 566 families and 15 geographic subraces of E. globulus were represented in the trials. The timing of the heteroblastic transition was genetically variable and under strong genetic control at the subrace and within-subrace level, with single-trial narrow-sense heritability estimates for the binary trait averaging 0.50 (range 0.44–0.65). The degree of quantitative trait differentiation in the timing of heteroblastic transition among subraces, as measured by QST, exceeded the published level of neutral molecular marker (FST) differentiation in all cases, arguing that diversifying selection has contributed to shaping broad-scale patterns of genetic differentiation. Most inter-trial genetic correlations were close to one at the subrace and additive genetic levels, indicating that the genetic variation in this important developmental change is expressed in a stable manner and that genotype-by-environment interaction is minimal across the environments studied.

scholarly journals Genetic Parameters and Genotype by Environment Interaction in Radiata Pine for Growth and Wood Quality Traits in Australia

2010 ◽  
Vol 59 (1-6) ◽  
pp. 113-124 ◽  
Author(s):  
Brian. S. Baltunis ◽  
W. J. Gapare ◽  
H. X. Wu
Keyword(s):  
Genetic Correlation ◽  
Genetic Parameters ◽  
Radiata Pine ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Tree Diameter ◽  
Genotype By Environment ◽  
Branch Angle ◽  
Stem Straightness ◽  
Branch Size

Abstract The phenotypic response of genotypes across different environments can be quantified by estimating the genotype by environment interaction (GxE). In a practical sense, GxE means that the relative performance of genotypes does not remain constant under all test conditions. Genetic parameters and genotype by environment interactions for wood density, growth, branching characteristics and stem straightness were investigated in eight radiata pine progeny trials derived from a second generation breeding population in Australia. Five trials were on the mainland, while three trials were in Tasmania. Generally, ĥ2 for density > branch angle > stem straightness > tree diameter > branch size; and significant ĥ2 was observed for all traits and at all trials with only two exceptions. Genetic correlations were estimated among the five traits, and a large negative genetic correlation observed between wood density and tree diameter indicated that a selection strategy should be developed in dealing with this adverse genetic correlation in advanced generations of breeding for radiata pine. Interactions for density, branch angle, and stem straightness were small within the two regions. Overall, branch angle had the least GxE, followed by density and stem straightness. Growth traits (tree diameter and branch size) tended to be the most interactive with substantial GxE present. Genotype by regional interactions (Mainland versus Tasmania) revealed that density and branch angle had the least interactions (ȓB = 0.98 and ȓB = 0.95, respectively). Branch size and tree diameter had the highest interactions among the two regions (ȓB = 0.55 and ȓB = 0.63, respectively). Within Tasmania, only branch size and tree diameter had a sizable interaction within the three sites. In contrast, there was little interaction for tree diameter among the Mainland trials. Branch size in the Mainland trials had a similar size of interaction as in Tasmania. Further research is recommended in identifying the cause of GxE for tree diameter and branch size in radiata pine across the entire radiata pine estate in Australia.

scholarly journals Analysis of genotype by environment interactions in a maize mapping population

2021 ◽  
Author(s):  
Asher I Hudson ◽  
Sarah G Odell ◽  
Pierre Dubreuil ◽  
Marie-Helene Tixier ◽  
Sebastien Praud ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Genetic Correlations ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Crop Breeding ◽  
Genotype By Environment Interactions ◽  
Genotype By Environment ◽  
Genome Wide ◽  
A Genome ◽  
Genetic Covariances

Genotype by environment interactions are a significant challenge for crop breeding as well as being important for understanding the genetic basis of environmental adaptation. In this study, we analyzed genotype by environment interaction in a maize multi-parent advanced generation intercross population grown across five environments. We found that genotype by environment interactions contributed as much as genotypic effects to the variation in some agronomically important traits. In order to understand how genetic correlations between traits change across environments, we estimated the genetic variance-covariance matrix in each environment. Changes in genetic covariances between traits across environments were common, even among traits that show low genotype by environment variance. We also performed a genome-wide association study to identify markers associated with genotype by environment interactions but found only a small number of significantly associated markers, possibly due to the highly polygenic nature of genotype by environment interactions in this population.

Estimation of genetic correlation between milk production and fat yield in different climates of Iran

2007 ◽  
Vol 2007 ◽  
pp. 70-70
Author(s):  
Sima Savar Sofla
Keyword(s):  
Genetic Correlation ◽  
Milk Production ◽  
Genetic Parameters ◽  
Genetic Difference ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Heterogeneous Variances ◽  
Fat Yield ◽  
Different Climates

Performance of one genotype in similar climates is approximately the same but if this genotype is introduced into a different climate, its performance will be affected, based on Nizamani and Berger (1996). The function that relates phenotype to environment is unique for each genotype. Hence, the response to changes in environment may vary from one genotype to the other, based on Mulder et al. (2004). Different selection responses between environments are generally attributed to two types of genotype by environment interaction. The first type occurs when the genetic correlation between performances in two environments is substantially less than 1.0, indicating a genetic difference basis for the trait in the two environments. The second type of genotype by environment interaction results from heterogeneous variances, based on Ojango and Pollott (2002). The goal of this study was to estimate genetic (co)variances, environmental variances, and genetic parameters of milk production and fat yield among different environments in Iran to determine variables that are useful indicators of genotype by environment interaction.

Sensitivity of genotypes to feeding systems for production, weight and feed intake in dairy cattle

2000 ◽  
Vol 2000 ◽  
pp. 112-112 ◽  
Author(s):  
J.E. Pryce ◽  
R.F. Veerkamp
Keyword(s):  
Dry Matter ◽  
Genetic Parameter ◽  
Genetic Correlations ◽  
Genotype By Environment Interaction ◽  
Parameter Estimates ◽  
Environment Interaction ◽  
Combine Data ◽  
Genotype By Environment ◽  
University Of Edinburgh ◽  
Feeding Systems

Getting reliable genetic parameter estimates for dry matter intake is difficult because recording it is expensive, hence it is tempting to combine data from research herds. However, there are large differences in feeding and management systems, which causes differences in means across herds. Furthermore, variances or heritabilities may differ and genetic correlations may be less than one between herds. This is one of the reasons why it is important to investigate effects of genotype by environment interaction (GxE). Another reason is that it is important to understand how high genetic merit cows perform in different feeding systems. The objective of this study was to estimate the effect of GxE for three feeding systems at two research herds belonging to ID-Lelystad (ID) and to SAC/University of Edinburgh (Langhill).

Genotype by environment interaction and model comparison for growth traits of Santa Ines sheep

2013 ◽  
Vol 130 (5) ◽  
pp. 394-403
Author(s):  
M.L. Santana ◽  
A.B. Bignardi ◽  
J.P. Eler ◽  
F.F. Cardoso ◽  
J.B.S. Ferraz
Keyword(s):  
Model Comparison ◽  
Growth Traits ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
Genotype By Environment ◽  
Santa Inês

Genetic correlation between growth and reproductive performance of beef females depends on environment

2018 ◽  
Vol 58 (7) ◽  
pp. 1201 ◽  
Author(s):  
Mário L. Santana Jr ◽  
Joanir P. Eler ◽  
Annaiza B. Bignardi ◽  
Arione A. Boligon ◽  
José B. S. Ferraz
Keyword(s):  
Beef Cattle ◽  
Genetic Correlation ◽  
Reproductive Performance ◽  
Growth Traits ◽  
Genetic Correlations ◽  
Random Regression ◽  
Tropical Region ◽  
Correlated Response ◽  
Heterogeneous Environments ◽  
Environment Interaction

In tropical production systems, beef cattle are raised in highly heterogeneous environments. Heterogeneity is, therefore, expected to exist in the (co)variance components for traits of economic interest in different production environments. The main objective of the present study was to estimate genetic correlations between growth traits and reproductive performance of beef females, depending on the environment. The present study was conducted in the tropical region of Brazil, applying a multiple-trait random regression animal model to field records of heifer pregnancy (HP), hip height, bodyweight at ~18 months of age (BW18) and postweaning weight gain (PWG) from 20 893 Nelore females. As evidence of genotype by environment interaction (G × E), heterogeneity of genetic variance across environments was observed mainly for HP, PWG and BW18. Moreover, the estimates of genetic correlation within these traits reached values lower than unity on the environmental gradient. The genetic correlation among growth traits tended to be stronger in favourable environments, a fact that should favour correlated responses under these conditions. In contrast, the genetic correlations between growth traits and HP tended to become weaker and even exhibited little evidence of antagonism in more favourable environments. On the basis of these findings, selection for higher growth in extreme favourable environments should result in little or no damage to HP as a correlated response. All these results lead us to believe that the G × E is an important factor to be considered in genetic evaluations of beef cattle raised in tropical environments.

scholarly journals Genotype by environment interaction for growth and survival rate in black tiger shrimp (Penaeus monodon) in generation 4

2019 ◽  
Vol 18 (5) ◽  
pp. 24-32
Author(s):  
Sang V. Nguyen
Keyword(s):  
Growth Rate ◽  
Survival Rate ◽  
Genetic Correlations ◽  
Growth Trait ◽  
Genotype By Environment Interaction ◽  
Environment Interaction ◽  
The South ◽  
Selection Program ◽  
Genotype By Environment ◽  
Testing Environments

Genotype by environment interaction for growth rate in G1 of the same selection program has been published. However, there is no repeated figure in later generations for confirming and well-planning the design of selection program for further improvement. The experiment was conducted using selective population of generation 4 with 97 families tested in 3 environments. Growth (body weight) and survival rate at harvest weight were recorded and evaluated. There was no genotype by environment interaction for both traits with high genetic correlations of the same traits tested between ponds in the Central and in the South of Vietnam of 0.80 and 0.83, respectively. There was also no genotype by environment interaction for growth rate between ponds in the South of Vietnam and bio-security indoor tank with high genetic correlation of 0.91. These results indicated that the number of testing environments would be reduced to save the operation cost for a breeding program. Estimated genetic response was from moderate to high for growth trait corresponding to moderate to high heritabilities (0.20 - 0.45) and high for survival rate corresponding to high heritabilities (0.34 - 0.45).

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