Environment characterisation for the interpretation of environmental effect and genotype × environment interaction

Increasing attention is being paid to environment characterisation as a means of identifying the environmental factors determining grain protein content (GPC) in durum wheat. New insights in crop physiology and agronomy have led to the development of crop simulation models. Those models can reconstruct plant development for past cropping seasons. One major advantage of these models is that they can also indicate the intensity of limiting factors affecting plants during particular developmental stages. The main environmental factors determining GPC in durum wheat can be investigated by introducing the intensity of limiting factors into genotype × environment (G×E) models. In our case, limiting factors corresponding to water deficit and nitrogen availability were calculated for the development period between booting and heading. These variables were then introduced into a clustering model. This model is an extension of factorial regression applied to discrete environment and genotypic variables. This procedure effectively described the environment main effect: around 30.9% of the sum of squares of the environment main effect was accounted for, using less than 33% of the degrees of freedom. It also partially accounted for G×E interaction. Our methodology, coupling the use of crop simulation and G×E analysis models, is of potential value for improving our understanding of the main development stages and identification of environmental limiting factors for the development of GPC.     

Assessing the importance of genotype × environment interaction for root traits in rice using a mapping population II: conventional QTL analysis

Modifying plant root systems is considered a means of crop improvement targeted to low-resource environments, particularly low nutrient and drought-prone agriculture. The identification of quantitative trait loci (QTLs) for root traits has stimulated marker-assisted breeding to this end, but different QTLs have been detected in different populations of the same species, and importantly, in the same population when grown in different experimental environments. The presence of QTL × environment interaction is implicated, and this must be characterised if the utility of the target QTLs is to be realised. Previous attempts to do this suffer from a lack of control over replicate environments and inadequate statistical rigour. The Bala × Azucena mapping population was grown in two replicate experiments of four treatment environments, a control, a low light, a low soil nitrogen and a low soil water treatment. After a 4 weeks growth, maximum root length, maximum root thickness, root mass below 50 cm, total plant dry mass, % root mass and shoot length were measured. A summary of the overall results is presented in an accompanying paper. Here, QTL analysis by composite interval mapping is presented. A total of 145 QTLs were detected, mapping to 37 discrete loci on all chromosomes. Superficial evidence of QTL × E (great difference in LOD score) was tested by single-marker analysis which confirmed QTL × E for five loci representing only five individual trait-loci interactions. Some loci appeared to be stable across environments. Some QTLs were clearly more or less active under low light, low nitrogen or drought. A few notable loci on chromosomes 1, 2, 3, 5, 7 and 9 are briefly discussed. Also discussed are some remaining statistical shortcomings that will be addressed in another companion paper.     

Needle parameter variation of mature black spruce displaying genetic × soil moisture interaction in growth

To examine soil moisture stress, light, and genetic effects on individual needle parameters and investigate total needle contribution to productivity, individual and total needle parameter variation were quantified in 32-year-old black spruce from five crown positions from four full-sib families studied previously for drought tolerance and differential productivity on a dry and a wet site. The wet site had greater average needle length (NL), specific needle area (SNA), and needle N concentration (NN) than the dry site. Site differences in NN were most likely driven by soil moisture stress impairing N uptake as soil N was equal at both sites. Drought-tolerant families had greater average needle area (NA), but also greater needle dry mass (NDM), than drought-intolerant families. From the top to bottom crown position, needle parameters showing a linear or near linear increase were NL, SNA, and NN; needle parameters showing a linear decrease were NW, NA, NDM and C:N ratio. For total tree needle area, the wet and dry sites had 18.7 and 16.0 m² tree^?1 (leaf area index (LAI) 5.6 and 4.8), respectively, whereas total needle C mass was not significantly different between sites. Drought-tolerant and intolerant families had a total NA of 18.8 and16.0 m² tree^?1, respectively. However, the greater total NA of drought-tolerant families was driven by one family. Thus, the role of total foliage area at these high LAI values in genetic differences in productivity is inconsistent and most likely low. Therefore, based on a previous 3-year campaign of gas exchange measurements and confirmed independently with carbon isotope analyses, the rate of net photosynthesis is a more important component of site and genetic growth differential in mature black spruce than total needle area.     

Using genotype × nitrogen interaction variables to evaluate the QTL involved in wheat tolerance to nitrogen constraints

Lower market prices and environmental concerns now orientate wheat (Triticum aestivum L.) breeding programs towards low input agricultural practices, and more particularly low nitrogen (N) input management. Such programs require knowledge of the genetic determination of plant reaction to N deficiency. Our aim was to characterize the genetic basis of N use efficiency and genotype × N interactions. The detection of QTL for grain yield, grain protein yield and their components was performed on a mapping population of 222 doubled haploid lines (DH), obtained from the cross between an N stress tolerant variety and an N stress sensitive variety. Experiments on the population were carried out in seven different environments, and in each case under high (N⁺) and low (N⁻) N supplies. In total, 233 QTL were detected for traits measured in each combination of environment and N supply, for “global” interaction variables (N⁺–N⁻ and N⁻/N⁺), for sensitivity to N stress and for performance under N-limited conditions which were assessed using factorial regression parameters. The 233 QTL were detected on the whole genome and clustered into 82 genome regions. The dwarfing gene (Rht-B1), the photoperiod sensitivity gene (Ppd-D1) and the awns inhibitor gene (B1) coincided with regions that contained the highest numbers of QTL. Non-interactive QTL were detected on linkage groups 3D, 4B, 5A1 and 7B2. Interactive QTL were revealed by interaction or factorial regression variables (2D2, 3D, 5A1, 5D, 6A, 6B, 7B2) or by both variables (1B, 2A1, 2A2, 2D1, 4B, 5A2, 5B). The usefulness of QTL meta-analysis and factorial regression to study QTL × N interactions and the impact of Rht-B1, Ppd-D1 and B1, are discussed. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Use of artificial environments to reproduce and exploit genotype × location interaction for lucerne in northern Italy

Genotype × environment interaction effects can be exploited by breeding for specific adaptation to well-defined subregions within a target region. Previous work showed that genotype × location interaction for dry matter (DM) yield of lucerne (Medicago sativa L. subsp. sativa) cultivars in northern Italy is large and associated with soil type and level of summer drought stress of locations, suggesting the presence of two contrasting subregions. Thirteen farm landraces collected across the region and four control varieties were evaluated for DM yield in four artificial environments created at one site by the factorial combination of soil type (sandy loam or silty clay) and drought stress level (almost nil or high) for: (1) exploring the possibility to reproduce in artificial environments the adaptation patterns occurring across the region; (2) investigating the adaptation pattern of landraces and its relationship with environmental factors at collecting sites; and (3) providing a preliminary comparison of wide- versus specific-adaptation strategies based on yield gains predicted from selection of populations. Different soils filled large (24.0×1.6×0.8-m deep), bottomless containers in concrete. Water amounts were controlled by irrigation under a moving rain shelter. Cultivars varied largely for adaptation pattern across the artificial environments, mainly due to cultivar × stress interaction. Better response to stress conditions of landraces was closely associated with the level of summer drought at collecting sites (r=0.82), highlighting the importance of evolutionary adaptation. The additive main effects and multiplicative interaction-modelled responses of control cultivars successfully reproduced those observed across locations, candidating the artificial environments as a cheaper alternative to more selection locations when breeding for wide or specific adaptation. The latter implied about 40–50% greater estimated gains relative to breeding for wide adaptation.     

Interpreting genotype × environment interaction in tropical maize using linked molecular markers and environmental covariables

An understanding of the genetic and environmental basis of genotype×environment interaction (GEI) is of fundamental importance in plant breeding. In mapping quantitative trait loci (QTLs), suitable genetic populations are grown in different environments causing QTLs×environment interaction (QEI). The main objective of the present study is to show how Partial Least Squares (PLS) regression and Factorial Regression (FR) models using genetic markers and environmental covariables can be used for studying QEI related to GEI. Biomass data were analyzed from a multi-environment trial consisting of 161 lines from a F_3:4 maize segregating population originally created with the purpose of mapping QTLs loci and investigating adaptation differences between highland and lowland tropical maize. PLS and FR methods detected 30 genetic markers (out of 86) that explained a sizeable proportion of the interaction of maize lines over four contrasting environments involving two low-altitude sites, one intermediate-altitude site, and one high-altitude site for biomass production. Based on a previous study, most of the 30 markers were associated with QTLs for biomass and exhibited significant QEI. It was found that marker loci in lines with positive GEI for the highland environments contained more highland alleles, whereas marker loci in lines with positive GEI for intermediate and lowland environments contained more lowland alleles. In addition, PLS and FR models identified maximum temperature as the most-important environmental covariable for GEI. Using a stepwise variable selection procedure, a FR model was constructed for GEI and QEI that exclusively included cross products between genetic markers and environmental covariables. Higher maximum temperature in low- and intermediate-altitude sites affected the expression of some QTLs, while minimum temperature affected the expression of other QTLs. Received: 10 January 1999 / Accepted: 12 March 1999     

Growth and genotype × environment interactions in Betula pendula: can tree genetic variation be maintained by small-scale forest ground heterogeneity?

Forest ground heterogeneity can affect interactions among tree species and control the assembly of local forest communities. Less is known of the effects of spatial heterogeneity on the maintenance of tree genetic variation through small-scale genotype × environment (G × E) interactions. We measured growth variation within and among 17 Betula pendula genotypes, planted in a clear-cut forest site through the summers 2009–2011. We assessed the spatial heterogeneity at two scales: among forest stands having history of the same or different tree species combinations (treated as replicate blocks), and along a gradient of within-block forest density, revealed by the stump density. To add a temporal perspective, we distinguished between old (cut 50 years earlier) and new stumps (cut one year earlier). The broad-sense heritabilities for growth were 0.093–0.055 and the coefficients of genotypic variation 0.37–0.21 in 2009–2011. The growth difference among the genotypes was 3.5–5.5 fold, significant in all years, and the rank of genotype means correlated positively between the years. The most favourable block had 106 % higher growth than the least favourable block and the amount of total variation explained by block increased from 0.4 % in 2009 to 6.9 % in 2011. Genotype × block interaction was marginally significant in 2009, but not later. Similarly, the response of growth to old stump density in sapling vicinity varied among the genotypes in 2009, but not later. In 2010 and 2011, the mean growth increased by 50–91 % along the old stump density gradient. Our results suggest that despite creating significant variation in sapling growth the small-scale forest ground heterogeneity, which reflects the recent forest history, may not significantly contribute to the maintenance of genetic variation in B. pendula populations.     

Detection of QTLs for genotype × environment interactions in tomato seeds and seedlings

Seed quality and seedling establishment are the most important factors affecting successful crop development. They depend on the genetic background and are acquired during seed maturation and therefor, affected by the maternal environment under which the seeds develop. There is little knowledge about the genetic and environmental factors that affect seed quality and seedling establishment. The aim of this study is to identify the loci and possible molecular mechanisms involved in acquisition of seed quality and how these are controlled by adverse maternal conditions. For this, we used a tomato recombinant inbred line (RIL) population consisting of 100 lines which were grown under two different nutritional environmental conditions, high phosphate and low nitrate. Most of the seed germination traits such as maximum germination percentage (G_max), germination rate (t₅₀) and uniformity (U₈₄₁₆) showed ample variation between genotypes and under different germination conditions. This phenotypic variation leads to identification of quantitative trait loci (QTLs) which were dependent on genetic factors, but also on the interaction with the maternal environment (QTL × E). Further studies of these QTLs may ultimately help to predict the effect of different maternal environmental conditions on seed quality and seedling establishment which will be very useful to improve the production of high-performance seeds.     

Importance of adaptation and genotype × environment interactions in tropical beef breeding systems

This paper examines the relative importance of productive and adaptive traits in beef breeding systems based on Bos taurus and tropically adapted breeds across temperate and (sub)tropical environments. In the (sub)tropics, differences that exist between breeds in temperate environments are masked by the effects of environmental stressors. Hence in tropical environments, breeds are best categorised into breed types to compare their performance across environments. Because of the presence of environmental stressors, there are more sources of genetic variation in tropical breeding programmes. It is therefore necessary to examine the genetic basis of productive and adaptive traits for breeding programmes in those environments. This paper reviews the heritabilities and genetic relationships between economically important productive and adaptive traits relevant to (sub)tropical breeding programmes. It is concluded that it is possible to simultaneously genetically improve productive and adaptive traits in tropically adapted breeds of beef cattle grazed in tropical environments without serious detrimental consequences for either adaptation or production. However, breed-specific parameters are required for genetic evaluations. The paper also reviews the magnitude of genotype × environment (G × E) interactions impacting on production and adaptation of cattle, where 'genotype' is defined as breed (within a crossbreeding system), sire within breed (in a within-breed selection programme) or associations between economically important traits and single nucleotide polymorphisms (SNPs - within a marker-assisted selection programme). It is concluded that re-ranking of breeds across environments is best managed by the use of the breed type(s) best suited to the particular production environment. Re-ranking of sires across environments is apparent in poorly adapted breed types across extreme tropical and temperate environments or where breeding animals are selected in a temperate environment for use in the (sub)tropics. However, G × E interactions are unlikely to be of major importance in tropically adapted beef cattle grazed in either temperate or (sub)tropical environments, although sex × environment interactions may provide new opportunities for differentially selecting to simultaneously improve steer performance in benign environments and female performance in harsher environments. Early evidence suggests that re-ranking of SNPs occurs across temperate and tropical environments, although their magnitude is still to be confirmed in well-designed experiments. The major limitation to genetic improvement of beef cattle over the next decade is likely to be a deficiency of large numbers of accurately recorded phenotypes for most productive and adaptive traits and, in particular, for difficult-to-measure adaptive traits such as resistance to disease and environmental stressors.     

QTL analysis of the spring wheat “Chapio” identifies stable stripe rust resistance despite inter-continental genotype × environment interactions

Chapio is a spring wheat developed by CIMMYT in Mexico by a breeding program that focused on multigenic resistances to leaf rust and stripe rust. A population consisting of 277 recombinant inbred lines (RILs) was developed by crossing Chapio with Avocet. The RILs were genotyped with DArT markers (137 randomly selected RILs) and bulked segregant analysis conducted to supplement the map with informative SSR markers. The final map consisted of 264 markers. Phenotyping against stripe rust was conducted for three seasons in Toluca, Mexico and at three sites over two seasons (total of four environments) in Sichuan Province, China. Significant loci across the two inter-continental regions included Lr34/Yr18 on 7DS, Sr2/Yr30 on 3BS, and a QTL on 3D. There were significant genotype × environment interactions with resistance gene Yr31 on 2BS being effective in most of the Toluca environments; however, a late incursion of a virulent pathotype in 2009 rendered this gene ineffective. This locus also had no effect in China. Conversely, a 5BL locus was only effective in the Chinese environments. There were also complex additive interactions. In the Mexican environments, Yr31 suppressed the additive effect of Yr30 and the 3D locus, but not of Lr34/Yr18, while in China, the 3D and 5BL loci were generally not additive with each other, but were additive when combined with other loci. These results indicate the importance of maintaining diverse, multi-genic resistances as Chapio had stable inter-continental resistance despite the fact that there were QTLs that were not effective in either one or the other region.     

Genomic models with genotype × environment interaction for predicting hybrid performance: an application in maize hybrids

Key message

A new genomic model that incorporates genotype?×?environment interaction gave increased prediction accuracy of untested hybrid response for traits such as percent starch content, percent dry matter content and silage yield of maize hybrids.

Abstract

The prediction of hybrid performance (HP) is very important in agricultural breeding programs. In plant breeding, multi-environment trials play an important role in the selection of important traits, such as stability across environments, grain yield and pest resistance. Environmental conditions modulate gene expression causing genotype?×?environment interaction (G?×?E), such that the estimated genetic correlations of the performance of individual lines across environments summarize the joint action of genes and environmental conditions. This article proposes a genomic statistical model that incorporates G?×?E for general and specific combining ability for predicting the performance of hybrids in environments. The proposed model can also be applied to any other hybrid species with distinct parental pools. In this study, we evaluated the predictive ability of two HP prediction models using a cross-validation approach applied in extensive maize hybrid data, comprising 2724 hybrids derived from 507 dent lines and 24 flint lines, which were evaluated for three traits in 58 environments over 12 years; analyses were performed for each year. On average, genomic models that include the interaction of general and specific combining ability with environments have greater predictive ability than genomic models without interaction with environments (ranging from 12 to 22%, depending on the trait). We concluded that including G?×?E in the prediction of untested maize hybrids increases the accuracy of genomic models.

     

Assessing the importance of genotype x environment interaction for root traits in rice using a mapping population. I: a soil-filled box screen

Altering root system architecture is considered a method of improving crop water and soil nutrient capture. The analysis of quantitative trait loci (QTLs) for root traits has revealed inconsistency in the same population evaluated in different environments. It must be clarified if this is due to genotype × environment interaction or considerations of statistics if the value of QTLs for marker-assisted breeding is to be estimated. A modified split-plot design was used where a main plot corresponded to a separate experiment. The main plot factor had four treatments (environments), which were completely randomized among eight trials, so that each treatment was replicated twice. The sub-plot factor consisted of 168 recombinant inbreed lines of the Bala × Azucena rice mapping population, randomly allocated to the seven soil-filled boxes. The aim of the trial was to quantify QTL × environment interaction. The treatments were chosen to alter partitioning to roots; consisting of a control treatment (high-soil nitrogen, high light and high-water content) and further treatments where light, soil nitrogen or soil water was reduced singly. After 4 weeks growth, maximum root length (MRL), maximum root thickness, root mass below 50 cm, total plant dry mass (%), root mass and shoot length were measured. The treatments affected plant growth as predicted; low nitrogen and drought increased relative root partitioning, low-light decreased it. The parental varieties Bala and Azucena differed significantly for all traits. Broad-sense heritability of most traits was high (57–86%). Variation due to treatment was the most important influence on the variance, while genotype was next. Genotype × environment interaction was detected for all traits except MRL, although the proportion of variation due to this interaction was generally small. It is concluded that genotype × environment interaction is present but less important than genotypic variation. A companion paper presents QTL × environment analysis of data.     

Ethylene and cytokinin interaction in the morphogenesis of Pelargonium × hortorum L.H. Bailey in vitro

Pelargonium × hortorum ‘Grand Prix’ which is susceptible to leaf yellowing and ‘Bergpalais’ which is not susceptible to leaf yellowing were chosen for the experiments. Ethylene production and action as well as the associated morphological response of Pelargonium shoots grown in the presence of a precursor of ethylene biosynthesis 1-aminocyclopropane-1-carboxylic acid (ACC), ethylene inhibitors: α-aminooxyacetic acid (AOA) and silver nitrate (AgNO₃) and different cytokinins: (meta-topolin) (mT) or 6-benzylaminopurine (BAP) were studied. It was found that ‘Grand Prix’ was more sensitive to ethylene than ‘Bergpalais’ and it showed the leaf yellowing in response to 0.1 mg l^?1 ACC. Moreover, it was noted that ACC added separately or together with cytokinin influenced Pelargonium morphogenesis. Depending on the concentration of ACC (0.1–2.0 mg l^?1), it either stimulated or inhibited shoot and root formation as well as the growth of shoots and leaf blades. ACC-induced leaf yellowing in ‘Grand Prix’ was effectively inhibited by mT. In contrast, BAP did not enhance shoot quality. Simultaneously, the presence of mT in the medium resulted in up to a twofold increase in the ethylene production by ‘Grand Prix’ shoots throughout the culture period compared with the shoots growing on the BAP-medium. The inhibitor of ethylene action (AgNO₃) added with cytokinin prevented the yellowing of Pelargonium shoots, but simultaneously influenced the formation of mature shoots with limited long-term multiplication potential. The shoots of P. × hortorum ‘Grand Prix’ treated with AgNO₃ and mT emitted two- and sevenfold more ethylene after 11th and 21st day of culture compared with those treated with AgNO₃ and BAP. It is suggested that mT inhibits the early senescence of Pelargonium in vitro by decreasing its sensitivity to ethylene.     

QTL analysis of genotype × environment interactions affecting cotton fiber quality

Cotton is unusual among major crops in that large acreages are grown under both irrigated and rainfed conditions, making genotype x environment interactions of even greater importance than usual in designing crop-improvement strategies. We describe the impact of well-watered versus water-limited growth conditions on the genetic control of fiber quality, a complex suite of traits that collectively determine the utility of cotton. Fiber length, length uniformity, elongation, strength, fineness, and color (yellowness) were influenced by 6, 7, 9, 21, 25 and 11 QTLs (respectively) that could be detected in one or more treatments. The genetic control of cotton fiber quality was markedly affected both by general differences between growing seasons ("years") and by specific differences in water management regimes. Seventeen QTLs were detected only in the water-limited treatment while only two were specific to the well-watered treatment, suggesting that improvement of fiber quality under water stress may be even more complicated than improvement of this already complex trait under well-watered conditions. In crops such as cotton with widespread use of both irrigated and rainfed production systems, the need to manipulate larger numbers of genes to confer adequate quality under both sets of conditions will reduce the expected rate of genetic gain. These difficulties may be partly ameliorated by efficiencies gained through identification and use of diagnostic DNA markers, including those identified herein.     

Analysis of QTL×environment interaction for yield components and plant height in rice

 An F₂ and two equivalent F₃ populations of an indica-indica cross of rice, Tesanai 2/CB, were constructed and grown in different environments. The identification of quantitative trait loci (QTL) for yield components and plant height and an analysis of QTL×environment interaction were conducted for three trials. Interval mapping of QTL for eight traits was employed with a threshold of LOD=2 using the computer package MAPMAKER/QTL. A total of 44 QTL were detected in 18 intervals of nine chromosomes, including 3 for the number of panicles (NP), 5 for the number of filled grains (NFG), 6 for total number of spikelets (TNS), 3 for spikelet fertility (SF), 7 for 1000-grain weight (TGWT), 5 for grain weight per plant (GWT), 8 for plant height (PH) and 7 for panicle length (PL). The numbers of QTL detected in two or three trials were 1 for NP, 1 for NFG, 1 for TNS, none for SF, 4 for TGWT, 3 for GWT, 2 for PH and 5 for PL, making a total of 17. When a QTL was detected in more than one trial the direction and magnitude of its additive effect, the dominance effect and the degree of dominance were generally in good agreement. In all three trials, QTL were frequently detected for related traits in the same intervals. The directions of additive effect of QTL for related traits in a given interval were in agreement with few exceptions, no matter whether they were detected in the same trial or not. This result suggested that pleiotropism rather than close linkage of different QTL was the major reason why QTL for different traits were frequently detected in the same intervals. When gene pleiotropism was considered, 23 of the 29 QTL for yield and its components and 9 of the 15 QTL for plant stature were detected in more than one trial. This indicated that the detection of chromosomal segments harboring QTL was hardly affected by environmental factors. Received: 30 January 1997 / Accepted: 21 March 1997     

Genotype × environment interaction, environmental heterogeneity and the lek paradox

Substantial additive genetic variance (V(A)) often exists for male signalling traits in spite of the directional selection that female choice imposes. One solution to this problem, a conundrum generally termed the 'lek paradox', is that genotype × environment interaction (GEI) occurs and generates a 'crossover' of reaction norms in which no one genotype performs in a superior manner in all environments. Theoretical work indicates that such crossover can sustain genetic variance provided that either (i) spatial heterogeneity in environmental conditions combined with limited migration among populations or (ii) temporal heterogeneity in environmental conditions combined with occasional generation overlap is present. Whereas some recent studies have revealed the intersection of reaction norms for sexually selected traits in laboratory and in natural populations, associated information on environmental heterogeneity, migration and generation overlap has not been investigated. We studied this question in an acoustic pyralid moth, Achroia grisella, in which previous work indicated GEI and crossover of reaction norms for several parameters of the male song evaluated by females. We measured reaction norms for male song as expressed when development was completed under different environmental conditions in four neighbouring, yet isolated, populations during 1 year and in one of these populations during consecutive years. Crossover occurred for the various song parameters in the several populations, but we did not observe a higher incidence of crossover between genotypes taken from two different populations than from the same population. However, for several key song parameters, crossover between genotypes taken from two different years was higher than that between genotypes from the same year. We suggest that temporal heterogeneity in the form of varying selection could potentially conserve V(A) in A. grisella, but we also note other factors that might contribute.     

Indirect genetic effects and the lek paradox: inter-genotypic competition may strengthen genotype × environment interactions and conserve genetic variance

Understanding the evolutionary mechanisms that maintain genetic variation in natural populations is one of the fundamental goals of evolutionary biology. There is growing evidence that genotype-by-environment interaction (G × E) can maintain additive genetic variance (V _A), but we lack information on the relative performance of genotypes under the competitive situations encountered in the field. Competing genotypes may influence each other, and this interaction is also subject to selection through indirect genetic effects (IGE). Here, we explore how genotypes perform when interacting and evaluate IGE in order to understand its influence on V _A for sexually-selected traits in the lesser waxmoth, Achroia grisella. We found that inter-genotype differences and crossover interactions under joint rearing are equal to or greater than values when reared separately. A focal genotype exhibited different performances when jointly reared with various genotypes—suggesting that IGE may be responsible for the increased levels of crossover and differences in performance observed. We suggest that some genotypes are superior competitors for food acquisition in the larval stage, and that these differences influence the development and evolution of other genotypes through IGE. We reaffirm the role of G × E in maintaining V _A and note the general importance of IGE in studies of evolutionary mechanisms.     

Genotype × environment interaction patterns for grain yield of spring barley in different regions of Kazakhstan

Barley plays an important role in agricultural sector of Kazakhstan and it is grown in many different climate zones over 1.5 mln hectares annually. Therefore development of optimal cultivars for specific environments is a major challenge for barley breeding community in Kazakhstan. One of the approaches to address this question is to test large collection of commercial cultivars and advanced lines over a number of environmental sites that reflect major spatial and temporal climate variations in the country. In this work 103 cultivars and advanced lines of spring barley bred in six different breeding stations of Kazakhstan were grown in different testing sites in seven regions over 2009–2011 years. The major tasks of this research were to evaluate genotype × environment interactions and assess grain yield in associations with developmental stages of barley, such as heading date and seed maturation date. The results suggest that (i) heading and seed maturation dates are significantly correlated with grain yield in specific regions and may have opposite correlation indexes in response to environmental conditions; (ii) accessions of different bred origin vary in their ability to exhibit environmentally-dependent plastic responses; (iii) spatial variation was more important than temporal variation in GxE interactions; (iv) biplot analysis is effective approach in identification of best suitable and stable accessions for both broad and narrow environments. The obtained results are further contribution to understanding of complex mechanisms of genotype x environment interactions.     

Genotype × environment interaction of Hevea clones in traditional and non-traditional rubber growing regions of Vietnam

The main objective of this research was to assess genotype?×?environment interactions and the stability status of 24 Hevea clones along with 2 checks in terms of latex yield and girth growth under two different environmental conditions representing for traditional and non-traditional rubber growing regions of Vietnam. Genotype?×?environment interactions were found to be highly significant for both latex yield and girth at opening, indicating that the latex yield and girth growth of the studied rubber clones were significantly affected by the environmental conditions of the location. Stability analyses indicated that LH 94/359, LH 91/579 and LH 94/481 were the best clones for highest latex yield and adaptability to traditional, non-traditional and both rubber growing regions of Vietnam, respectively. In terms of girth at opening, the stability analyses revealed that these clones were also accepted as the average girth growth and adaptability to both rubber growing regions of Vietnam.