Multivariate analyses of genotype x environment interaction of popcorn

The objectives of this work were to evaluate the genotype x environment (GxE) interaction for popcorn and to compare two multivariate analyses methods. Nine popcorn cultivars were sown on four dates one month apart during each of the agricultural years 1998/1999 and 1999/2000. The experiments were carried out using randomized block designs, with four replicates. The cv. Zélia contributed the least to the GxE interaction. The cv. Viçosa performed similarly to cv. Rosa-claro. Optimization of GxE was obtained for cv. CMS 42 for a favorable mega-environment, and for cv. CMS 43 for an unfavorable environment. Multivariate analysis supported the results from the method of Eberhart & Russell. The graphic analysis of the Additive Main effects and Multiplicative Interaction (AMMI) model was simple, allowing conclusions to be made about stability, genotypic performance, genetic divergence between cultivars, and the environments that optimize cultivar performance. The graphic analysis of the Genotype main effects and Genotype x Environment interaction (GGE) method added to AMMI information on environmental stratification, defining mega-environments and the cultivars that optimized performance in those mega-environments. Both methods are adequate to explain the genotype x environment interactions.

Genotype x environment interaction in the uptake of Cs and Sr from soils by plants

The soil-plant transfer factors for Cs and Sr were analyzed in relationship to soil properties, crops, and varieties of crops. Two crops and two varieties of each crop: lettuce (Lactuca sativa L.), cv. Salad Bowl Green and cv. Lobjoits Green Cos, and radish (Raphanus sativus L.), cv. French Breakfast 3 and cv. Scarlet Globe, were grown on five different soils amended with Cs and Sr to give concentrations of 1 mg kg(-1) and 50 mg kg(-1) of each element. Soil-plant transfer coefficients ranged between 0.12-19.10 (Cs) and 1.48-146.10 (Sr) for lettuce and 0.09-13.24 (Cs) and 2.99-93.00 (Sr) for radish. Uptake of Cs and Sr by plants depended on both plant and soil properties. There were significant (P less than or equal to 0.05) differences between soil-plant transfer factors for each plant type at the two soil concentrations. At each soil concentration about 60% of the variance in the uptake of the Cs and Sr was due to soil properties. For a given concentration of Cs or Sr in soil, the most important factor effecting soil-plant transfer of these elements was the soil properties rather than the crops or varieties of crops. Therefore, for the varieties considered here, soil-plant transfer of Cs and Sr would be best regulated through the management of soil properties. At each concentration of Cs and Sr, the main soil properties effecting the uptake of Cs and Sr by lettuce and radish were the concentrations of K and Ca, pH and CEC. Together with the concentrations of contaminants in soils, they explained about 80% of total data variance, and were the best predictors for soil-plant transfer. The different varieties of lettuce and radish gave different responses in soil-plant transfer of Cs and Sr in different soil conditions, i.e. genotype x environment interaction caused about 30% of the variability in the uptake of Cs and Sr by plants. This means that a plant variety with a low soil-plant transfer of Cs and Sr in one soil could have an increased soil-plant transfer factor in other soils. The broad implications of this work are that in contaminated agricultural lands still used for plant growing, contaminant-excluding crop varieties may not be a reliable method for decreasing contaminant transfer to foodstuffs. Modification of soil properties would be a more reliable technique. This is particularly relevant to agricultural soils in the former USSR still affected by fallout from the Chernobyl disaster.

Effects of sex and age on genotype x environment interaction for beef cattle body weight studied using reaction norm models

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Genotype x environment interaction for age at first calving in Brazilian and Colombian Holsteins

The objective was to determine whether there is a genotype x environment interaction for age at first calving (AFC) in Holstein cattle in Brazil and Colombia. Data included 51,239 and 25,569 first-lactation records from Brazil and Colombia, respectively. Of 4230 sires in the data, 530 were North American sires used in both countries. Analyses were done using the REML bi-trait animal model, and AFC was considered as a distinct characteristic in each country. Fixed effects of contemporary group (herd-calving year), sire genetic group, and cow genetic group, and random effects of animal and residual variation were included in the model. Average AFC in Brazil and Colombia were 29.5 ± 4.0 and 32.1 ± 3.5 mo, respectively. Additive and residual genetic components and heritability coefficient for AFC in Brazil were 2.21 mo 2, 9.41 mo 2, and 0.19, respectively, whereas for Colombia, they were 1.02 mo 2, 6.84 mo 2, and 0.13, respectively. The genetic correlation of AFC between Brazil and Colombia was 0.78, indicating differences in ranking of sires consistent with a genotype x environment interaction. Therefore, in countries with differing environments, progeny of Holstein sires may calve at relatively younger or older ages compared with contemporary herdmates in one environment versus another.

Genotype x environment interaction for age at first calving, scrotal circumference, and yearling weight in Nellore cattle using reaction norms in multitrait random regression models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Strategies in identifying individuals in a segregant population of common bean and implications of genotype x environment interaction in the success of selection

The objective of this study was to compare the BLUP selection method with different selection strategies in F-2:4 and assess the efficiency of this method on the early choice of the best common bean (Phaseolus vulgaris) lines. Fifty-one F-2:4 progenies were produced from a cross between the CVIII8511 x RP-26 lines. A randomized block design was used with 20 replications and one-plant field plots. Character data on plant architecture and grain yield were obtained and then the sum of the standardized variables was estimated for simultaneous selection of both traits. Analysis was carried out by mixed models (BLUP) and the least squares method to compare different selection strategies, like mass selection, stratified mass selection and between and within progeny selection. The progenies selected by BLUP were assessed in advanced generations, always selecting the greatest and smallest sum of the standardized variables. Analyses by the least squares method and BLUP procedure ranked the progenies in the same way. The coincidence of the individuals identified by BLUP and between and within progeny selection was high and of the greatest magnitude when BLUP was compared with mass selection. Although BLUP is the best estimator of genotypic value, its efficiency in the response to long term selection is not different from any of the other methods, because it is also unable to predict the future effect of the progenies x environments interaction. It was inferred that selection success will always depend on the most accurate possible progeny assessment and using alternatives to reduce the progenies x environments interaction effect.

Genetic parameters and investigation of genotype x environment interactions in Nellore x Hereford crossbred for resistance to cattle ticks in different regions of Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Prediction of Hevea progeny performance in the presence of genotype-environment interaction

Twenty two open-pollinated Hevea progenies from different parental clones of the Asian origin were tested at five sites in the Northwestern São Paulo State Brazil to investigate the progeny girth growth, rubber yield, bark thickness and plant height. Except for the rubber yield, the analysis of variance indicated highly significant (p<0.01) genotype x environment interaction and heterogeneity of regressions among the progenies. However, the regression stability analysis identified only a few interacting progenies which had regression coefficients significantly different from the expected value of one. The linear regressions of the progeny mean performance at each test on an environmental index (mean of all the progenies in each test) showed the general stability and adaptability of most selected Hevea progenies over the test environments. The few progenies which were responsive and high yielding on different test sites could be used to maximize the rubber cultivars productivity and to obtain the best use of the genetically improved stock under different environmental conditions.

Factors that cause genotype by environment interaction and use of a multiple-trait herd-cluster model for milk yield of Holstein cattle from Brazil and Colombia

Descriptive herd variables (DVHE) were used to explain genotype by environment interactions (G x E) for milk yield (MY) in Brazilian and Colombian production environments and to develop a herd-cluster model to estimate covariance components and genetic parameters for each herd environment group. Data consisted of 180,522 lactation records of 94,558 Holstein cows from 937 Brazilian and 400 Colombian herds. Herds in both countries were jointly grouped in thirds according to 8 DVHE: production level, phenotypic variability, age at first calving, calving interval, percentage of imported semen, lactation length, and herd size. For each DVHE, REML bivariate animal model analyses were used to estimate genetic correlations for MY between upper and lower thirds of the data. Based on estimates of genetic correlations, weights were assigned to each DVHE to group herds in a cluster analysis using the FASTCLUS procedure in SAS. Three clusters were defined, and genetic and residual variance components were heterogeneous among herd clusters. Estimates of heritability in clusters 1 and 3 were 0.28 and 0.29, respectively, but the estimate was larger (0.39) in Cluster 2. The genetic correlations of MY from different clusters ranged from 0.89 to 0.97. The herd-cluster model based on DVHE properly takes into account G x E by grouping similar environments accordingly and seems to be an alternative to simply considering country borders to distinguish between environments.

Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil

The objectives of the present study were to characterize and define homogenous production environments of composite beef cattle in Brazil in terms of climatic and geographic variables using multivariate exploratory techniques and to use them to assess the presence of G x E for birth weight (BW) and weaning weight (WW). Data from animals born between 1995 and 2008 on 36 farms located in 27 municipalities of the Brazilian states were used. Fifteen years of climate observations (mean minimum and maximum annual temperature and mean annual rainfall) and geographic (latitude, longitude and altitude) data were obtained for each municipality where the farms were located for characterization of the production environments. Hierarchical and nonhierarchical cluster analysis was used to group farms located in regions with similar environmental variables into clusters. Six clusters of farms were formed. The effect of sire-cluster interaction was tested by single-trait analysis using deviance information criterion (DIC). Genetic parameters were estimated by multi-trait analysis considering the same trait to be different in each cluster. According to the values of DIC, the inclusion of sire-cluster effect did not improve the fit of the genetic evaluation model for BW and WW. Estimates of genetic correlations among clusters ranged from -0.02 to 0.92. The low genetic correlation among the most studied regions permits us to suggest that a separate genetic evaluation for some regions should be undertaken. (C) 2012 Elsevier B.V. All rights reserved.

Gene-Environment Interaction Effects on Behavioral Variation and Risk of Complex Disorders: The Example of Alcoholism and Other Psychiatric Disorders

There have been few replicated examples of genotype x environment interaction effects on behavioral variation or risk of psychiatric disorder. We review some of the factors that have made detection of genotype x environment interaction effects difficult, and show how genotype x shared environment interaction (GxSE) effects are commonly confounded with genetic parameters in data from twin pairs reared together. Historic data on twin pairs reared apart can in principle be used to estimate such GxSE effects, but have rarely been used for this purpose. We illustrate this using previously published data from the Swedish Adoption Twin Study of Aging (SATSA), which suggest that GxSE effects could account for as much as 25% of the total variance in risk of becoming a regular smoker. Since few separated twin pairs will be available for study in the future, we also consider methods for modifying variance components linkage analysis to allow for environmental interactions with linked loci.

Using crop simulation to generate genotype by environment interaction effects for sorghum in water-limited environments

Multi-environment trials (METs) used to evaluate breeding lines vary in the number of years that they sample. We used a cropping systems model to simulate the target population of environments (TPE) for 6 locations over 108 years for 54 'near-isolines' of sorghum in north-eastern Australia. For a single reference genotype, each of 547 trials was clustered into 1 of 3 'drought environment types' (DETs) based on a seasonal water stress index. Within sequential METs of 2 years duration, the frequencies of these drought patterns often differed substantially from those derived for the entire TPE. This was reflected in variation in the mean yield of the reference genotype. For the TPE and for 2-year METs, restricted maximum likelihood methods were used to estimate components of genotypic and genotype by environment variance. These also varied substantially, although not in direct correlation with frequency of occurrence of different DETs over a 2-year period. Combined analysis over different numbers of seasons demonstrated the expected improvement in the correlation between MET estimates of genotype performance and the overall genotype averages as the number of seasons in the MET was increased.