Genotype X Environment Research Articles

Genetic Analysis of Embryo, Cytoplasm and Maternal Effects and Their Environment Interactions for Isoflavone Content in Soybean [ Glycine max (L.) Merr.

Abstract Soybean seed products contain isoflavones (genistein, daidzein, and glycitein) that display biological effects when ingested by humans and animals. These effects are species, dose and age dependent. Therefore, the content and quality of isoflavones in soybeans is a key factor to the biological effect. Our objective was to identify the genetic effects that underlie the isoflavone content in soybean seeds. A genetic model for quantitative traits of seeds in diploid plants was applied to estimate the genetic main effects and genotype x environment ( GE) interaction effects for the isoflavone content ( IC) of soybean seeds by using two years experimental data with an incomplete diallel mating design of six parents. Results showed that the IC of soybean seeds was simultaneously controlled by the genetic effects of maternal, embryo, and cytoplasm, of which maternal genetic effects were most important, followed by embryo and cytoplasmic genetic effects. The main effects of different genetic systems on IC trait were more important than environment interaction effects. The strong dominance effects on isoflavone from residual was made easily by environment conditions. Therefore, the improvement of the IC of soybean seeds would be more efficient when selection is based on maternal plants than that on the single seed. Maternal heritability (65.73%) was most important for IC, followed by embryo heritability (25.87%) and cytoplasmic heritability (8.39%). Based on predicated genetic effects, Yudou 29 and Zheng 90007 were better than other parents for increasing IC in the progeny and improving the quality of soybean. The significant effects of maternal and embryo dominance effects in variance show that the embryo heterosis and maternal heterosis are existent and uninfluenced by environment interaction effects.

Genotype × Adiposity Interaction Linkage Analyses Reveal a Locus on Chromosome 1 for Lipoprotein-Associated Phospholipase A 2, a Marker of Inflammation and Oxidative Stress

Because obesity leads to a state of chronic, low-grade inflammation and oxidative stress, we hypothesized that the contribution of genes to variation in a biomarker of these two processes may be influenced by the degree of adiposity. We tested this hypothesis using samples from the San Antonio Family Heart Study that were assayed for activity of lipoprotein-associated phospholipase A(2) (Lp-PLA(2)), a marker of inflammation and oxidative stress. Using an approach to model discrete genotypexenvironment (GxE) interaction, we assigned individuals to one of two discrete diagnostic states (or "adiposity environments"): nonobese or obese, according to criteria suggested by the World Health Organization. We found a genomewide maximum LOD of 3.39 at 153 cM on chromosome 1 for Lp-PLA(2). Significant GxE interaction for Lp-PLA(2) at the genomewide maximum (P=1.16 x 10(-4)) was also found. Microarray gene-expression data were analyzed within the 1-LOD interval of the linkage signal on chromosome 1. We found two transcripts--namely, for Fc gamma receptor IIA and heat-shock protein (70 kDa)--that were significantly associated with Lp-PLA(2) (P<.001 for both) and showed evidence of cis-regulation with nominal LOD scores of 2.75 and 13.82, respectively. It would seem that there is a significant genetic response to the adiposity environment in this marker of inflammation and oxidative stress. Additionally, we conclude that GxE interaction analyses can improve our ability to identify and localize quantitative-trait loci.

The dynamic gene expression from different genetic systems for protein and lysine contents of indica rice

The dynamic expression of genes for protein and lysine contents of rice grain under different environments was carried out with time-dependent measures by using the developmental genetic models for quantitative traits of triploid endosperm in cereal crops. The results showed that the genetic effects, especially genotype x environment (GE) interaction effects from the genes expression of different genetic systems including triploid endosperm, cytoplasm and diploid maternal plant were important for the performance of both nutrient quality traits at all developmental times/stages of rice grain. The conditional genetic variance analysis found that the activation of quantitative genes especially from endosperm and maternal plant genetic systems for protein and lysine contents was gradually carried through the developmental process of rice grain. The net genetic effects showed that the new expression of quantitative genes for protein and lysine contents was more active at late filling stage (15-21 days after flowering) and maturity stage (22-28 days) of rice grain. Also the sequential expression of cytoplasmic genes cannot be ignorable for the development of nutrient quality traits. The phenomena that some genes could continuously express for several developmental stages or the genes expression could be interrupted among developmental stages of rice grain was detected especially for net endosperm additive main effects or maternal additive main effects. The differences of genetic relationships from different genetic systems were found for protein and lysine contents among developmental times of rice grain.

Partitioning genetic effects due to embryo, cytoplasm and maternal parent for oil content in oilseed rape (Brassica napus L.)

Analysis of genetic main effects and genotype x environment (GE) interaction effects on the oil content of oilseed rape (Brassica napus L.) was conducted by using a genetic model for the quantitative traits of seeds in diploid plants. The experiments were carried out over two years with 8 parents and a diallel mating design, which produced F1 and F2 generations. We found that the oil content of rape was simultaneously controlled by embryo genetic effect, cytoplasmic effects and maternal genetic effect as well as GE interaction effects, with the cytoplasmic and maternal effects playing the main role. The results indicate that selection of maternal plants for high oil content would be more efficient than selection based on single seeds. Since the GE interaction effects accounted for 73.69% of the total genetic effects and were more important than the genetic main effects it seems that selection might be influenced by environmental conditions. The estimate of narrow-sense heritability for oil content was 73.52% with the interaction heritability being larger than the general heritability, indicating that the early generations can be used for selection for high oil content. The prediction of genetic effects suggested that the parent cultivars Youcai 601 and Gaoyou 605 were better than the other cultivars for increasing oil content during the breeding of B. napus. The implications for the quantitative trait loci mapping of seed traits interfered by these three genetic systems is also discussed.

Genotype × environment interaction effects on carcass traits in Japanese Black cattle1

The importance of genotype x environment (region or management system) interactions for carcass traits in Japanese Black cattle was investigated using both univariate and multivariate animal models. The univariate approach was used mainly to test the significance of interaction effects. The multivariate approach was used to estimate genetic correlations, which indicated the magnitude of genotype x environment (GE) interactions. The more a genetic correlation deviates from 1, the larger the interaction. From the univariate approach, the addition of genotype x environment (region or management system) interaction (co)variance components resulted in an improved fit of the model for all traits in both cases (P < 0.001). However, estimates of genetic correlation between regions obtained from the multivariate approach for hot carcass weight, LM area, rib thickness, s.c. fat thickness, and marbling score were 0.97, 0.95, 0.93, 0.97, and 0.93, respectively. The corresponding estimates between management systems were 0.84, 0.92, 0.84, 0.90, and 0.97, respectively. These results indicate that GE interaction effects on carcass traits of Japanese Black cattle may be biologically unimportant. Therefore, breeding values obtained using the multivariate method would rank sires similarly in all environments. Consequently, carcass traits measured in these two different regions or management systems can be treated as the same traits.

Genetic analysis of endosperm, cytoplasmic and maternal effects for histidine and arginine in indica rice (Oryza sativa L.) across environments

Genetic main effects and genotype x environment (GE) interaction effects for amino acids histidine (His) and arginine (Arg) in milled rice were analyzed by using the genetic models for quantitative traits of triploid endosperm. Nine cytoplasmic male sterile lines as females and five restoring lines as males were included in an incomplete diallel cross in two environments. Results indicated that the His content and Arg content were mainly controlled by genetic main effects, whereas the ratios of His content to protein content (RHP) or Arg content to protein content (RAP) were mainly affected by GE effects. Since genetic variances involved were found significantly for all traits, the genetic controlling of these two amino acids could be simultaneously affected by the endosperm, cytoplasm and maternal genetic effects. For genetic main effects, the cytoplasm and maternal additive effects for these two amino acids possessed high percentage of 60.2-70.9%, which indicated that selection for these amino acids based on maternal performance could be more effective than that based on single seed. The total narrow-sense heritabilities were high for Arg and RAP with 82.4% and 82.3%, and low for His and RHP with 46.4% and 18.2%, respectively. Since general heritabilities for these two amino acids were found to be much larger than GE interaction heritability, the selection advance for these traits could be expected at different environments. Most cytoplasmic and maternal additive correlations were significantly positive and dominance interaction correlations were also important among all the pairwise traits. Indirect selection of these two amino acids applied in rice breeding was discussed.

Genetic analysis of non-essential amino acid contents in rice (Oryza sativa L.) across environments

Genetic main effects and genotype x environment (GE) interaction effects for 7 non-essential amino acids in milled rice were analyzed for two year data by using the genetic models based on mixed linear model approaches for quantitative traits of triploid endosperm. Nine cytoplasmic, male sterile lines as females and five restoring lines as males were introduced in a diallel cross in two environments. It was found that the content of non-essential amino acids including Asp, Ser, Glu, Gly and Tyr were mainly controlled by genetic main effects, whereas the content of Ala or Pro was mainly affected by GE effects. In genetic main effects, the cytoplasmic and maternal genetic effects were preponderant for all traits of non-essential amino acids, indicating that selection for improving these traits based on the maternal plant would be more effective than on seeds. The total narrow-sense heritabilities for non-essential amino acids were 70.9-85.9%. By predicating the genetic effects of parents, the total genetic effects from Xieqingzao, V20, Zuo 5 and Zhenshan 97 were mainly negative and these parents would decrease the content of most essential amino acids. Since parents of Zhenan 3, Yinchao 1, T49, 26715, 102 and 1391 had possessed a positive value of most total genetic effects, these parents could be chosen as optimal parents for increasing the content of most non-essential amino acids.

Analysis of genetic effects and heritabilities for linoleic and α‐linolenic acid content of Brassica napus L. across Chinese environments

AbstractA genetic model for quantitative traits of seed in diploid plant was applied to analyze the main genetic effects and genotype × environment (GE) interaction effects for linoleic and α‐linolenic acid content of rapeseed (Brassica napus L.) by using two year experimental data with 8 parents and their F1 and F2. Results indicated that the performance of linoleic (C18:2) and α‐linolenic acid content (C18:3) of rapeseed were simultaneously controlled by diploid embryo nuclear genes, cytoplasmic genes and diploid maternal plant nuclear genes, and the GE interaction effects for these two seed quality traits were more important than the genetic main effects. The total narrow‐sense heritability was 69.5% and 41.8% for C18:2 and C18:3, respectively, and the GE interaction heritabilities were found to be larger than the general heritabilities for both quality traits. It was suggested by the predicted genetic effects that Huashuang 3 was better than other parents for improving offspring of C18:2 and Youcai 601, Zhongyou 821, Eyouchangjia and Zhong R‐888 for decreasing C18:3.

Regression analysis of yield stability is strongly affected by companion test varieties and locations — examples from a study of Nordic barley lines

The suitability of regression analysis for studying the phenotypic stability of grain yield was investigated using a collection of 220 Nordic barley lines. Linear regression explained 26-52% of the genotype x environment (GE) interactions in different groupings of the material. The regression coefficient, b i , measures the yield response of the i-th genotype to improved environmental conditions. Deviations from regression, S di (2) , have been used to estimate Tai's stability parameter, λ i , which is a measure of the phenotypic yield stability in the agronomic sense. Repeatability of b i , λ i , and grain yield was studied by means of correlations between estimates obtained in each experimental year. Yield had the highest repeatability, with correlations between years ranging from 0.57 to 0.85. In this study, regression coefficients and λ i -values were not repeatable, i.e. genotypes reacted differentially to the yearly climatic variations. Six-rowed (6r) barleys had higher responsiveness, but lower mean yields, than two-rowed (2r) barleys. This is partly due to the history of selection of 6r-barleys, which mainly originate from regions with low potential yield levels, i.e. Finland and Norway. In general, responsiveness and stability were not correlated with yield. The highest-yielding lines had b i ≈1. The response pattern of the different types of barleys used in this study show that responsiveness can be changed by recombination.

Genotype multiply environment interactions in progeny from a barley cross. 1. Patterns of response among progeny lines for grain yield and time to anthesis

Barley progeny lines (201) derived from F2 plants of the cross cv. Triumph x cv. Grimmett were evaluated at 7 environments in Queensland. Cluster analysis and principal component analysis were used to examine the variation in response for grain yield. The relationship between days to anthesis and these responses was investigated. The variance component for genotype x environment (GE) interaction for grain yield was of similar magnitude to that for line main effects. Groups of lines formed using cluster analysis exhibited substantial differences in ranking across environments, indicating that selection would be affected by choice of test environments. The components of grain yield, harvest index (HI), and total dry matter (TDM) had large variation for GE interaction. However, for days to anthesis, the variance component for GE interaction was small compared with that for the line main effects. There were significant differences in mean days to anthesis for groups of lines that were classified on the basis of grain yield. Early flowering was associated with high grain yield in some environments but with low grain yield in the 2 irrigated environments. The first component from principal component analysis of grain yield was only weakly related to days to anthesis. This component appeared to be related to performance in favourable environments, suggesting that an important source of variation in grain yield among the progeny lines was associated with their responsiveness to favourable conditions.

The impact of genotype multiply environment interactions for sugar yield on the use of indirect selection in southern Queensland

To develop a strategy to improve the efficiency of selection, indirect selection and pattern analysis were used to examine the magnitude and form of genotype x environment (GE) interactions for sugar yield in sugarcane clones in southern Queensland. Clone x location interactions were the predominant source of clone X environment interactions and were much larger than clone x crop-year and clone x location x crop-year interactions. Both the indirect selection study and the pattern analysis emphasised the relative magnitude of these sources of interactions. Pattern analysis strongly associated crop classes at each location, and indirect selection analysis emphasised an opportunity to exploit correlated genetic advance between crop classes within a location. These suggest that more emphasis should be placed on sampling a greater number of locations than on the testing of clonal ratooning ability within locations. This would improve the chances of obtaining both broadly and specifically adapted sugarcane varieties.

Selection of test locations for regional trials of barley

Three sets of regional six-row barley (Hordeum vulgare L.) trial data, representing cultivar x location x year, were grouped for locations based on the similarity of genotype x environment (GE) interaction. Locations were selected from each group (cluster) so that the structure of the GE interaction generated by the subsets of the locations would be approximately similar to that of the whole set (all locations). The purpose of this paper is to determine the number of locations where the GE interaction structure generated by these selected locations would be fairly consistent over years. Two statistics were used to measure the success of the selected locations: (1) the ratio of GE mean square (MS) associated with the selected location set relative to that associated with the best set (which gives the highest GE interaction MS) and (2) the rank correlation between the cultivar means averaged over the selected locations and those based on the entire data set. The results show that, for eastern Canada, 10-13 locations based on the cluster method can achieve a fairly consistent GE interaction structure over years.

Genetics of nitrate content in lettuce

Adverse effects on human health makes the high nitrate content frequently found in lettuce (Lactuca sativa L.) grown under low light conditions an undesirable trait. Efforts have been made to breed cultivars with a reduced capacity for nitrate accumulation. In this study components of variance for nitrate content were estimated in F2 and F3 generations of ten lettuce crosses. Additive genotypic variances (A) were estimated from F3 variance components and from the covariance between F2 plants and corresponding F3 lines. Estimates of wide sense heritability of the F2 from crosses between a high nitrate genotype and four low nitrate genotypes ranged from 0.44 to 0.74 and the estimates for √A ranged from 0.25 to 0.40 g·l-1. Estimated wide sense heritabilities of F2's from six crosses involving two low nitrate parents ranged from 0.15 to 0.52. The parents of four of the low nitrate crosses showed relatively large effects of genotype x environment (GE) interaction in successive experiments: the nitrate content of the parents reacted differently to environmental changes between experiments. Estimates of √A for crosses between low nitrate genotypes without large effects of GE interaction ranged from 0 to 0.19 g·l-1. The estimated probability of selecting transgressive low nitrate lines in the progeny of a cross between a high and a low nitrate genotype was low (P=0.002−0.039), indicating that large populations should be evaluated to combine the positive traits of modern high nitrate cultivars with low nitrate content from genotypes not adapted to modern cropping practices. In the progenies from crosses between two low nitrate genotypes without important GE effects, only low estimates of the probability of obtaining transgressive low nitrate lines were obtained (P=0.04−0.06). With the growth conditions used in this study, the probability of selecting lines with a nitrate content compatible under all winter conditions with the proposed future maximum permissible level of 2.5 g nitrate per kg fresh matter is low. Therefore the solution of this problem should be found in a combination of low nitrate cultivars and cultural measures that reduce the nitrate content of the crop.

Application of a stability statistic to international maize yield trials

Genotype x environment (GE) interaction encountered in experiments complicates genotype selection and varietal recommendation. The integration of yield and stability of genotypes into a single parameter may make selection and recommendation easier. Kang developed a rank-sum method that allows selection for both yield and the stability variance statistics (σ i (2) or s i (2) ) of Shukla. The objective of this research was to compare the rank-sum selection method to selection based on yield alone in five international maize (Zea mays L.) yield trials. Ranks were assigned for yield (the highest mean yield received a rank of 1) and for σ i (2) and s i (2) (the lowest value received a rank of 1). The yield and σ i (2) ranks and/or the yield and s i (2) ranks for each genotype were summed. Each trial contained two reference entries (REs). Yield rank or rank-sum of each genotype was compared to yield rank or rank-sum of the best RE (BRE). GE interaction was significant for all trials. Heterogeneity in the GE interaction due to the linear effect of a covariate (differences in fertility and/or cultural practices) was significant in Trials 1, 2, and 5. Overall, in all trials, 29 genotypes were selected on the basis of yield alone. On the basis of σ i (2) and yield rank-sum, 32 genotypes were identified, with 11 being lower yielding than the 29 yield-based selections. On the basis of s i (2) and yield rank-sum, 31 genotypes were selected, with 11 being lower yielding than the yield-bases selections. Obviously, yield is sacrificed when the rank-sum method is used in the selection process. However, selection based on yield alone may not be adequate when GE interaction is significant because of testing in diverse environments.

Genetic properties of four types of stability parameter

The genetic properties of four types of stability parameter for individual genotypes were investigated using a set of diallel cross data (28 genotypes x four locations x 3 years). The specific parameters studied were: the variance of a genotype across environments (T1); the genotype x environment (GE) interaction effect for a genotype, squared and summed across all environments (T2); the residual mean square (MS) of deviations from the regression of a genotype on an environmental index (T3); and years within locations MS for a genotype, averaged over all locations (T4). Each stability statistic was fitted to the additive model, based on the assumption that if the stability parameter is heritable, stability of F1 is most likely to be the average stability of its parents. The results showed that T1 and T4 were additive, but T2 and T3 were not. A study of the consistency of stability rankings between two seeding rates over the same set of environments showed a similar pattern. It appears that stability parameters of types 1 and 4 are heritable, and thus useful for selection, while those of types 2 and 3 are nonheritable, and thus not useful.

Statistical Analysis of a Yield Trial

AbstractYield trials frequently have both significant main effects and a significant genotype X environment (GE) interaction. Traditional statistical analyses are not always effective with this data structure: the usual analysis of variance (ANOVA), having a merely additive model, identifies the GE interaction as a source but does not analyze it; principal components analysis (PCA), on the other hand is a multiplicative model and hence contains no sources for additive genotype or environment main effects; and linear regression (LR) analysis is able to effectively analyze interaction terms only where the pattern fits a specific regression model. The consequence of fitting inappropriate statistical models to yield trial data is that the interaction may be declared nonsignificant, although a more appropriate analysis would find agronomically important and statistically significant patterns in the interaction. Therefore, agronomists and plant breeders may fail to perceive important interaction effects. This paper compares the above three traditional models with the additive main effects and multiplicative interaction (AMMI) Model, in an analysis of a soybean [Glycine max (L.) Merr.] yield trial. ANOVA fails to detect a significant interaction component, PCA fails to identify and separate the significant genotype and environment main effects, and LR accounts for only a small portion of the interaction sum of squares. On the other hand, AMMI analysis reveals a highly significant interaction component that has clear agronomic meaning. Since ANOVA, PCA, and LR are sub‐cases of the more complete AMMI model, AMMI offers a more appropriate first statistical analysis of yield trials that may have a genotype X environment interaction. AMMI analysis can then be used to diagnose whether or not a specific sub‐case provides a more appropriate analysis. AMMI has no specific experimental design requirements, except for a two‐way data structure.

Analysis of Cultivar X Environment Interactions for Kansas Growing Wheat Using Regression, Variance Component, and Clustering Methods

Analysis of Cultivar X Environment Interactions for Kansas Growing Wheat Using Regression, Variance Component, and Clustering Methods