Presence Of Genotype-environment Interaction Research Articles

Study of different parametric stability measures when the basic data/variables are non-normal

The presence of genotype-environment interactions (GEI) necessitates the developments of varieties or breeds suited for different agro-environments based on their stability and adaptability characteristics. In many situations, the assumptions about the normality and independence of observations as well as homogeneity of error variances are not fulfilled. Therefore, there is a need to investigate the performance of different parametric methods for stability measures when the basic data is not normally distributed. This important aspect is taken up in the present investigation. Using simulation technique,power of the test has been computed for different sample sizes when the underlying dataset is normal as well as non-normal like gamma, beta, t, weibull, log normal etc. In most of the cases it is found that Eberhart and Russell parametric stability measure gives better performance.

GENOTYPE-ENVIRONMENT INTERACTIONS ON THE WEIGHT OF TABAPUA CATTLE IN THE NORTHEAST OF BRAZIL

ABSTRACT: The objective of this work was to verify the presence of genotype-environment interactions (GEI) on the weight adjusted to 365 days of age (W365) for Tabapua cattle in the Northeast of Brazil, using reaction norm (RN) models. The reaction norm model with homogeneous residual variance and 1-step provided the best fit to the data by the criteria information of deviance, deviance based on the conditional predictive ordinate and deviance based on the Bayes factors. Direct and maternal heritability estimates for the animal model were 0.17±0.04 and 0.07±0.03, respectively. The direct heritability for model reaction norm in the low and high management environment were 0.21±0.06 and 0,70±0.04, respectively. The correlations between the slope and intercept of the reaction norm were 0.68±0.10 and 0.96±0.06 for the direct and maternal effect, indicating that the animals with high genetic values respond positively to environment improvements, especially for the maternal effect. The Spearman correlations between the sire classifications ranged from 0.14 to 0.94 in the different environments and models. Genetic values of most animals were robust to environmental variation, however, considering the sires with the highest number of progeny, there is the presence of GEI.

Effects of age and rearing environment on genetic parameters of growth and body weight and heritability of skin pigmentation in Arctic charr (Salvelinus alpinus L.)

The Swedish breeding programme for Arctic charr aims to improve traits that are important for farming. Selection has been ongoing since the 1980s, and the aim of this study was to re-estimate the genetic parameters in the selected population. In addition, the genetics of skin pigmentation was studied, as previous work indicated a relationship between pigmentation and the ability to cope with stress.One hundred twenty-five full sib families of Arctic charr were hatched and reared separately until they were individually tagged (n=12,266). In connection with the tagging, three replicates were formed, which were subsequently reared at different sites. The genetic relationships were known from a seven-generation pedigree. Body weight and length were at one site measured at six occasions until 27months old, and these measurements were used to estimate the DGC (daily growth coefficient) and condition factor. At a second site fish were measured at 21 and 27months age and at a third site at 27months age.Skin pigmentation was measured using image analysis. The final weight at 27months of age varied widely between rearing sites, ranging from 529g to 1443g. Weight heritability differed among the sites, at 0.45, 0.11, and 0.07. At one of the sites, where growth was followed closely, weight heritability varied among growth periods, ranging from 0.01 to 0.25, and similar results were obtained for the DGC. In contrast, condition factor heritability did not show such pronounced variations within and among sites. The magnitude of the differences in heritability of weight and growth among different sites that was observed here was not observed previously with this charr population. In particular, the low heritability among the fastest growing fish is unprecedented.Skin pigmentation showed a high heritability of 0.76, indicating a strong additive genetic component. At most ages, pigmentation showed a weak positive genetic correlation with growth. The genotype environment interaction (GEI) was estimated using genetic correlations among sites. For the final weight, genetic correlations were high, indicating weak GEI, although the presence of GEI was suggested from the DGC data. Statement of relevanceThe ms will impact charr breeding for commercial farming.

Rank correlation among different statistical models in ranking of winter wheat genotypes

Several statistical methods have been developed for analyzing genotype×environment (GE) interactions in crop breeding programs to identify genotypes with high yield and stability performances. Four statistical methods, including joint regression analysis (JRA), additive mean effects and multiplicative interaction (AMMI) analysis, genotype plus GE interaction (GGE) biplot analysis, and yield–stability (YSi) statistic were used to evaluate GE interaction in 20 winter wheat genotypes grown in 24 environments in Iran. The main objective was to evaluate the rank correlations among the four statistical methods in genotype rankings for yield, stability and yield–stability. Three kinds of genotypic ranks (yield ranks, stability ranks, and yield–stability ranks) were determined with each method. The results indicated the presence of GE interaction, suggesting the need for stability analysis. With respect to yield, the genotype rankings by the GGE biplot and AMMI analysis were significantly correlated (P<0.01). For stability ranking, the rank correlations ranged from 0.53 (GGE–YSi; P<0.05) to 0.97 (JRA–YSi; P<0.01). AMMI distance (AMMID) was highly correlated (P<0.01) with variance of regression deviation (S2di) in JRA (r=0.83) and Shukla stability variance (σ2) in YSi (r=0.86), indicating that these stability indices can be used interchangeably. No correlation was found between yield ranks and stability ranks (AMMID, S2di, σ2, and GGE stability index), indicating that they measure static stability and accordingly could be used if selection is based primarily on stability. For yield–stability, rank correlation coefficients among the statistical methods varied from 0.64 (JRA–YSi; P<0.01) to 0.89 (AMMI–YSi; P<0.01), indicating that AMMI and YSi were closely associated in the genotype ranking for integrating yield with stability performance. Based on the results, it can be concluded that YSi was closely correlated with (i) JRA in ranking genotypes for stability and (ii) AMMI for integrating yield and stability.

ANALISIS INTERAKSI GENOTIP x LINGKUNGAN MENGGUNAKAN STRUCTURAL EQUATION MODELING

Additive Main Effect and Multiplicative Model (AMMI Model) nowadays is used to asses in plant breeding, especially to asses the Genotype Environment Interaction (GEI) on multi-environment trial. The presence of genotype environment interaction (GEI) creates difficulties in modeling complex trait that involve sequence biological process. Coupling Structural equation modeling with AMMI was developed to analyzed genotype environment interaction (GEI). Structural equation modeling allows us to account for underlying sequential process in plant development by incorporating intermediate variables associated with those processes in the model. With this method we can incorporating genotypic and environmental covariate in the model and explain how those covariates influence grain yield. SEM-AMMI useful when both environments and genotype are fixed and the purpose of the multi-environment trials (MET) is to assess the combined effect genotypic and environmental covariate on yield and yield componentsKeywords : AMMI Model, Structural equation modeling

Use safety first rule in selecting stable barley cultivars

The presence of genotype environment interaction is of major concern to plant breeders, since large interactions can reduce gains from selection and complicate identification of superior cultivars. In order to attain sustainability in barley productivity, the Safety First Rule was used in 10 barley cultivars tested in two locations for four years (1984-1987). An Index that incorporated mean yield and stability was developed for each of the four different definitions of stability. B3072 was identified as a superior cultivar with the highest mean yield of 2.95 t ha-1 and ranked first by all the four selection indices. The line B3072 was released as Kibo in 1991 and the usefulness of the Safety First selection rule in situations where poor yields have severe adverse consequences has been realized.

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&lt;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.

Shape and size variation on the wing of Drosophila mediopunctata: influence of chromosome inversions and genotype-environment interaction

The second chromosome of Drosophila mediopunctata is highly polymorphic for inversions. Previous work reported a significant interaction between these inversions and collecting date on wing size, suggesting the presence of genotype-environment interaction. We performed experiments in the laboratory to test for the joint effects of temperature and chromosome inversions on size and shape of the wing in D. mediopunctata. Size was measured as the centroid size, and shape was analyzed using the generalized least squares Procrustes superimposition followed by discriminant analysis and canonical variates analysis of partial warps and uniform components scores. Our findings show that wing size and shape are influenced by temperature, sex, and karyotype. We also found evidence suggestive of an interaction between the effects of karyotype and temperature on wing shape, indicating the existence of genotype-environment interaction for this trait in D. mediopunctata. In addition, the association between wing size and chromosome inversions is in agreement with previous results indicating that these inversions might be accumulating alleles adapted to different temperatures. However, no significant interaction between temperature and karyotype for size was found--in spite of the significant presence of temperature-genotype (cross) interaction. We suggest that other ecological factors--such as larval crowding--or seasonal variation of genetic content within inversions may explain the previous results.

Impacts of QTL × Environment Interactions on Genetic Response to Marker-Assisted Selection

Genotype × environment ( GE) interaction is a common characteristic for quantitative traits, and has been a subject of great concern for breeding programs. Simulation studies were conducted to investigate the effects of GE interaction on genetic response to marker-assisted selection (MAS). In our study we demonstrated that MAS is generally more efficient than phenotypic selection in the presence of GE interaction, and this trend is more pronounced for developing broadly adaptable varieties. The utilization of different QTL information dramatically influences MAS efficiency. When MAS is based on QTLs evaluated in a single environment, the causal QTL × environment ( QE) interactions usually reduce general response across environments, and the reduction in the cumulative general response is a function of the proportion of QE interactions for the trait studied. However, MAS using QTL information evaluated in multiple environments not only yields higher general response, but the general response obtained is also reasonably robust to QE interactions. The total response achieved by MAS in a specific environment depends largely on the total heritability of traits and is slightly subject to relative changes between general heritability and GE interaction heritability. Two breeding strategies, breeding experiments conducted in one environment throughout and in two environments alternately, were also examined for the implementation of marker-based selection. It was thus concluded that plant breeders should be cautious to utilize QTL information from only one environment and execute breeding studies in another.

Partition of sire effects for international sire evaluation in the presence of genotype×environment interaction

Both simulation and field data were analyzed to compare the current MACE (multiple-trait across-country evaluation) and a proposed partition model (MACE_P) for international sire evaluation in the presence of genotype–environment (GE) interaction. The partition model decomposes the sire effect into two components: constant effect that is stable genetically across countries and interaction effect that varies from country to country. Simulation results indicate that interaction effect was estimated more accurately by MACE_P when GE interaction is strong than when it is weak. The accuracy of estimating sire effects increased as GE interaction and/or heterogeneity of sire variances between countries lessened, indicating the importance of accounting for GE interaction and heterogeneous sire variances in the international genetic evaluation. A joint analysis of Japanese and the US Holstein populations reveals that the estimated interaction correlation ( r I) as a new measure of GE interaction was 0.924, suggesting little evidence of sire by country interaction for milk yield. A general formula was developed to convert the estimates of sire effects from MACE to MACE_P. Although MACE_P demands more computing resources than MACE, the use of this simple conversion formula would greatly reduce the computing requirements by MACE_P. Both constant and interaction effects estimated by MACE_P sums to the sire effect estimated by MACE. Sire (co)variances obtained as a sum of constant and interaction (co)variances estimated by MACE_P were very similar to those estimated by MACE. The partition of sire effect into the constant and interaction effects by MACE_P allows the indexing of these two component traits with different weights to maximize overall response in the presence of GE interaction.

Selection on purebred and crossbred Performance for litter size in pigs*

Abstract. The present study deals with estimation of genetic parameter for purebred and crossbred Performance of live born piglets, in order to choose the optimal selection method. Data sets of two pure breeds, line L03 and L04, with 5,422 sows, a two line crossbred, L303, with 3,553 sows and a three line crossbred, L350, with 3,609 sows of a North-German breeding Company were recorded. Estimated genetic correlation between purebred and crossbred Performance were rg = 0.59 and 0.40 for reciprocal crosses L03xL04 and L04xL03, respectively. Further investigations showed that the genetic correlation is influenced by genotype-environment interactions between a nucleus farm and a farm on production level. Full-sib effects showed a proportion of FS = 0.06 on the phenotypic variance of litter size. They were confounded with additive genetic variance and permanent environment variance, when full-sib effects were neglected. The percentage of equal selected purebred sires of line L03 were 80% when 30% of the sires selected on purebred or crossbred breeding values. Accuracy of estimated breeding values of purebred sires increased when crossbred Information were considered additionally from 0.32 to 0.38 for line L03 and 0.46 to 0.47 for line L04. Genetic correlation between purebred and crossbred Performance, the genetic connectedness between nucleus and production and the presence of genotype-environment interactions were analysed to have high influence on the value of additionally considered crossbred Performance.

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

Twenty recombinant inbred line (RIL) populations of European two-row spring barley and their parents were tested in six environments in the Netherlands to investigate the prediction of progeny yield level, yield variance, stability level and stability variance, based on parent information. Progeny yield level is positively correlated with midparent value for average yield. Progeny yield variance is more difficult to predict, but there does appear to be a promising negative correlation between progeny yield variance and Habgood's (1977) parental similarity measure. To quantify yield stability, three statistics were calculated: Finlay and Wilkinson's (1963) regression coefficient bi, Shukla's (1972) stability variance i2 and Eberhart and Russell's (1966) mean squared deviation di2. The first stability statistic describes a different aspect of the response pattern to change in environment from the last two. Parents with high bi values appear to have a better average yield, i.e. they react more positively to an improvement in the environment than the other genotypes. The average bi value of the progeny is positively correlated with the midparent value, indicating its heritable nature. There are also indications that di2 and i2 are heritable but their repeatability is poor. Therefore, it is concluded that only prediction of bi is useful in practical plant breeding. There is a positive correlation between progeny yield variance and progeny variance for bi but we conclude that the inaccuracy of the stability variance estimates is too high for good predictors for progeny stability variance to be found.

Interacción genotipo-ambiente en avena sativa l: utilizando los modelos AMMI y factorial de correspondencias

El objetivo fue (i) determinar la presencia de interacción genotipo-ambiente (IGA) en la producción forrajera de avena (Avena sativa L.) de genotipos tolerantes y no tolerantes a Schizaphis graminum empleando un número bajo de ambientes en la provincia de Buenos Aires (Argentina) mediante los modelos de efectos principales aditivos e interacción multiplicativa (AMMI) y análisis factorial de correspondencias (AFC) y (ii) comparar los resultados obtenidos por ambos métodos. Los ensayos se condujeron en La Dulce (Argentina) y La Plata (Argentina) (1993, 1994 y 1995). Se evaluaron 12 genotipos (comerciales y líneas avanzadas) en 12 ambientes (combinación de localidad, años y cortes). Los factores ambiente, genotipo e interacción explicaron un 41,15% (p&lt;0,001), 7,88% (p&lt;0,05) y 36,36% (p&lt;0,001) de la suma de cuadrados del total respectivamente. El modelo AMMI mostró los tres primeros ejes del análisis de componentes principales (ACP) altamente significativos (p&lt;0,001), explicando un 57,99%, 29,03% y 6,27% de la suma de cuadrados de la interacción respectivamente. Las tres primeros ejes del AFC explicaron un 58,98%, 29,58% y 5,60% de dicha suma de cuadrados, respectivamente. El uso conjunto de ambos métodos surge como una herramienta muy útil para reflejar y caracterizar la existencia de interacción genotipo-ambiente en avena.

Application of a generalized Grubbs' model in the analysis of genotype-environment interaction

The presence of genotype-environment interaction is a common feature of yield trial data. Estimating variance components attributable to the interactions of single cultivars is a useful means of assessing phenotypic stability. The stability variance is one such measure. In this paper it is argued that the stability variance is appropriate only if the error variances are homogeneous across genotypes and the number of replicates is the same in each environment. An alternative is suggested for the case that either of these two assumptions is violated.

Phenotypic plasticity in Crepis tectorum (Asteraceae): genetic correlations across light regimens

Inbred F3 and F4 families from a cross between two contrasting ecotypes of Crepis tectorum were replicated in two regimes in a glasshouse to determine whether genetic tradeoffs within the reaction norm favour genetic differentiation over phenotypic plasticity in this species. There was no tradeoff in reproductive fitness (flower production) across light regimes but genetic cross-environment correlations approached unity for a wide range of characters subject to divergent selection across habitats, suggesting little genetic variation in plasticity and a limited opportunity for selection to favour broadly adapted genotypes capable of attaining the optimum phenotype in every environment. The presence of genotype-environment interaction without large changes in the ranking of genotypes over light regimes indicates a greater potential for evolutionary change in environmental sensitivity although developmental constraints may limit the range of phenotypes that can be expressed in a character. A selection analysis was conducted to determine how the average reaction norm would evolve in this system. Whereas the relationship between each trait and reproductive fitness was environment-specific, there was no change in the direction of selection between light regimes. Given the genetic correlation structure observed, one would expect some of the genetic response in one environment to carry over to the other environment.

Environmental and genotype-by-environment influences on chick size in the Yellow-browed leaf warbler Phylloscopus inornatus.

I investigated genetic and environmental factors affecting fledgling chick size in the Yellow browed leaf warbler Phylloscopus inornatus. The proportion of variation among broods is >45% for both tarsus length and body weight; this can be attributed at least in part to effects of the shared nest environment. A high off-spring-parent regression for weight also appears to be partly due to an environmentally induced correlation and the regression is reduced when effects of laying date are controlled for. A cross-fostering experiment demonstrated a significant nest of origin x nest of rearing interaction. The presence of genotype-environment interaction affecting chick size may be quite general in birds. It is shown how this can account for observed patterns of the dependence of the magnitude of offspringparent regression on prevailing conditions, as has been found in other studies. In P. inornatus the failure to detect significant genetic variance in chick body weight and tarsus length may be due to high standard errors on the estimates, but it may also reflect true low levels of genetic variance in chick size if the genotype-interaction effect described occurs regularly in this species.

A review of biomass quality research relevant to the use of poplar and willow for energy conversion

It has been recognized that the chemical and physical properties of biomass feedstocks can play an important role in the efficiency of most energy conversion processes. These properties include the ratio of bark to wood, moisture content, specific gravity, calorific or heating value, and the relative content of extractives, α-cellulose, hemicellulose, and lignin. A review of the literature dealing with the quality of poplar and willow biomass feedstock for energy conversion revealed that considerable variation existed in many of these traits. This variation may make it possible to improve the quality of feedstock through breeding and selection. Little information exists with respect to heritability (both in the broad sense and narrow sense), the genetic correlation between characters, and the presence of genotype-environment interaction. A better understanding of these parameters is essential if the apparent variability is to be used to improve biomass quality.

XIX.—Sexual Maturity in Brown Leghorns, and the Relationship of Genetic Variance to Differences in Environment

SynopsisThe concept of heritability is discussed in relation to the climatic changes which may affect the variations of age at sexual maturity in the fowl, and it is suggested that genetic and environmental variance, as expressed in the customary statistical formulation, may be largely synonymous terms.Four groups of Brown Leghorn pullets are compared, one subject to no artificial lighting and the sub-optimal conditions of war years, a second to restricted lighting, and a third and fourth to 14-hour day length. The formal estimates of genetic and environmental variance were respectively 910 and 978, 594 and 546, 188 and 295, and 56 and 135. Further reduction of variability is apparent on subdivision into early and late hatches, heritability being apparently zero in the first case but maintained at an average level in the second.Changes in variability substantiate the presence of genotype-environment interactions as previously reported, and similar conclusions follow from heterogeneity of regressions of age at maturity on date of hatch.