A Study on Genotype-by-Environment Interaction Analysis for Agronomic Traits of Maize Genotypes Across Huang-Huai-Hai Region in China

Facing the trend of increasing population, how to increase maize grain yield is a very important issue to ensure food security. In this study, 28 nationally approved maize hybrids were evaluated across 24 different climatic conditions for two consecutive years (2018–2019). The purpose of this study was to select high-yield with stable genotypes and identify important agronomic traits for maize breeding program improvement. The results of this study showed that the genotype ╳ environment interaction effects of the 12 evaluated agronomic traits was highly significant (P < 0.001). We introduced a novel multi-trait genotype-ideotype distance index (MGIDI) to select genotypes based on multiple agronomic traits. The selection process exhibited by this method is unique and easy to understand, so the MGIDI index will have more and more important applications in future multi-environment trials (METs) research. The genotypes selected by the MGIDI index were G22, G10, G12 and G1 as the high yielding and stable genotypes. The parents of these selected genotypes have the ability to play a greater role as the basic germplasm in the breeding process. A new form of genotype (G) main effects and genotype (G) -by-environment (E) interaction (GGE) technician, genotype*yield*trait (GYT) biplot, based on multiple traits for genotypes selection was also applied in this study. The GYT biplot ranked genotypes by combining grain yield with other evaluated agronomic traits, and displayed the distribution of their traits, namely strengths and weaknesses.     

燕麦种质资源重要农艺性状适应性和稳定性评价

为客观评价燕麦种质资源重要农艺性状的适应性和稳定性,本研究利用加权隶属函数法分析了81份燕麦种质材料在7个试验点的株高等7个重要农艺性状的遗传差异,以加权隶属函数值(D值)构建基因型×环境的GGE双标图,分析裸燕麦、皮燕麦在不同试验点的适应性和稳定性。结果表明:主穗粒重是裸燕麦材料在所有试验点中变异程度最大的性状,有效分蘖数是皮燕麦中变异程度最大的性状,其余5个性状的变异程度与皮裸性几乎无关;加权隶属函数法结合GGE双标图在对燕麦农艺性状进行综合分析时具有很好的应用价值;坝莜三号、73014-336、二莜麦、Bauntebue、坝燕一号等材料可用于实际生产,其中的坝莜三号、坝燕一号已是当下河北等地区的主栽品种;晋8609-1、LY03-02、二秋莜麦、64燕麦、品16、Banner、LY01-12等可作为杂交育种的亲本材料。     

Genotypes and their interaction effects on reproduction and mating‐induced immune activation in Drosophila melanogaster

Mating causes considerable alterations in female physiology and behaviour, and immune gene expression, partly due to proteins transferred from males to females during copulation. The magnitude of these phenotypic changes could be driven by the genotypes of males and females, as well as their interaction. To test this, we carried out a series of genotype‐by‐genotype (G × G) experiments using Drosophila melanogaster populations from two distant geographical locations. We expected lines to have diverged in male reproductive traits and females to differ in their responses to these traits. We examined female physiological and behavioural post‐mating responses to male mating traits, that is behaviour and ejaculate composition, in the short to mid‐term (48 hr) following mating. We then explored whether a sexually transferred molecule, sex peptide (SP), is the mechanism behind our observed female post‐mating responses. Our results show that the genotypes of both sexes as well as the interaction between male and female genotypes affect mating and post‐mating reproductive traits. Immune gene expression of three candidate genes increased in response to mating and was genotype‐dependent but did not show a G × G signature. Males showed genotype‐dependent SP expression in the 7 days following eclosion, but female genotypes showed no differential sensitivity to the receipt of SP. The two genotypes demonstrated clear divergence in physiological traits in short‐ to mid‐term responses to mating, but the longer‐term consequences of these initial dynamics remain to be uncovered.     

甘蔗品种主要性状的基因型与环境及其互作效应分析

用AMMI模型双标图对国家第六轮甘蔗品种区域试验5个试点的12个甘蔗品种试验数据进行分析,研究甘蔗区试中不同品种的产量稳定性问题。结果表明,参试品种的6个产量性状在品种间和地点间差异显著,品种与地点的互作效应差异显著;FN30、YG16蔗茎产量和含糖量高,稳定性强,属于高产、稳产性较好的品种。AMMI模型很好地解释了甘蔗品种产量性状的基因型效应、环境效应和GE互作效应。     

Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application

Genotype by environment interaction (G×E) refers to the comparative performances of genotypes differing among environments, representing differences in genotype rankings or differences in the level of expression of genetic differences among environments. G×E can reduce heritability and overall genetic gain, unless breeding programmes are structured to address different categories of environments. Understanding the impact of G×E, the role of environments in generating G×E and the problems and opportunities is vital to efficient breeding programme design and deployment of genetic material. We review the current main analytical methods for identifying G×E: factor analytic models, biplot analysis and reaction norm. We also review biological and statistical evidence of G×E for growth, form and wood properties in forest species of global economic importance, including some pines, eucalypts, Douglas-fir, spruces and some poplars. Among these species, high levels of G×E tend to be reported for growth traits, with low levels of G×E for form traits and wood properties. Finally, we discuss possible ways of exploiting G×E to maximise genetic gain in forest tree breeding. Characterising the role of environments in generating interactions is seen as the basic platform, allowing efficient testing of candidate genotypes. We discuss the importance of level-of-expression interaction, relative to rank-change interaction, as being greater than in many past reports, especially for deployment decisions. We examine the impacts of G×E on tree breeding, some environmental factors that cause G×E and the strategies for dealing with G×E in tree breeding, and the future role of genomics.     

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.     

Genetic by environment interactions affect plant–soil linkages

The role of plant intraspecific variation in plant–soil linkages is poorly understood, especially in the context of natural environmental variation, but has important implications in evolutionary ecology. We utilized three 18‐ to 21‐year‐old common gardens across an elevational gradient, planted with replicates of five Populus angustifolia genotypes each, to address the hypothesis that tree genotype (G), environment (E), and G × E interactions would affect soil carbon and nitrogen dynamics beneath individual trees. We found that soil nitrogen and carbon varied by over 50% and 62%, respectively, across all common garden environments. We found that plant leaf litter (but not root) traits vary by genotype and environment while soil nutrient pools demonstrated genotype, environment, and sometimes G × E interactions, while process rates (net N mineralization and net nitrification) demonstrated G × E interactions. Plasticity in tree growth and litter chemistry was significantly related to the variation in soil nutrient pools and processes across environments, reflecting tight plant–soil linkages. These data overall suggest that plant genetic variation can have differential affects on carbon storage and nitrogen cycling, with implications for understanding the role of genetic variation in plant–soil feedback as well as management plans for conservation and restoration of forest habitats with a changing climate.     

Why does the magnitude of genotype‐by‐environment interaction vary?

Genotype‐by‐environment interaction (G × E), that is, genetic variation in phenotypic plasticity, is a central concept in ecology and evolutionary biology. G×E has wide‐ranging implications for trait development and for understanding how organisms will respond to environmental change. Although G × E has been extensively documented, its presence and magnitude vary dramatically across populations and traits. Despite this, we still know little about why G × E is so evident in some traits and populations, but minimal or absent in others. To encourage synthetic research in this area, we review diverse hypotheses for the underlying biological causes of variation in G × E. We extract common themes from these hypotheses to develop a more synthetic understanding of variation in G × E and suggest some important next steps.     

Breeding for robustness: investigating the genotype‐by‐environment interaction and micro‐environmental sensitivity of Genetically Improved Farmed Tilapia (Oreochromis niloticus)

Robustness has become a highly desirable breeding goal in the globalized agricultural market. Both genotype‐by‐environment interaction (G × E) and micro‐environmental sensitivity are important robustness components of aquaculture production, in which breeding stock is often disseminated to different environments. The objectives of this study were (i) to quantify the degree of G × E by assessing the growth performance of Genetically Improved Farmed Tilapia (GIFT) across three countries (Malaysia, India and China) and (ii) to quantify the genetic heterogeneity of environmental variance for body weight at harvest (BW) in GIFT as a measure of micro‐environmental sensitivity. Selection for BW was carried out for 13 generations in Malaysia. Subsets of 60 full‐sib families from Malaysia were sent to China and India after five and nine generations respectively. First, a multi‐trait animal model was used to analyse the BW in different countries as different traits. The results indicate a strong G × E. Second, a genetically structured environmental variance model, implemented using Bayesian inference, was used to analyse micro‐environmental sensitivity of BW in each country. The analysis revealed the presence of genetic heterogeneity of both BW and its environmental variance in all environments. The presence of genetic variation in residual variance of BW implies that the residual variance can be modified by selection. Incorporating both G × E and micro‐environmental sensitivity information may help in selecting robust genotypes with high performance across environments and resilience to environmental fluctuations.     

Sensitivity of different flax (Linum usitatissimum L.) genotypes to salinity determined by GE biplot

Plants respond differently to salt stress depending on their genetic structure and the severity of the stress. Salinity reduces seed germination, delays plant emergence, and inhibits seedling growth. The selection of the tolerant genotypes, however, plays a vital role in increasing agricultural output since various genotypes greatly vary for their tolerance to salinity. Therefore, this study determined the impact of five different NaCl levels (i.e., 0, 50, 100, 150 and 200 mM) on seed germination and growth attributes of 10 flax (Linum usitatissimum L.) genotypes. The germination and growth characteristics of the genotypes under study were examined using the biplot approach at varied salt levels. The results indicated that individual and interactive effects of genotypes and salinity levels significantly (p ≤ 0.01 or p ≤ 0.05) affected several seed germination traits. The relations of genotype × germination traits indicated that ‘G4′ and ‘G6′ were the most stable genotypes with the highest performance regarding seed germination characteristics. The genotype ‘G2′ was associated with shoot length, while ‘G7′ was linked with salinity tolerance index. The biplot divided the germination characteristics into five different groups according to sector analysis. Most of the germination parameters had higher values under 100 mM, while some of the parameters had better values under 0, 50 and 200 mM NaCl levels. The tested genotypes varied for their seed germination and growth response depending on the NaCl levels. The genotypes ‘G4′, ‘G5′ and ‘G6′ proved more tolerant to high NaCl levels. Therefore, these genotypes can be used to improve flax productivity under saline soils.     

Within‐host interactions shape virulence‐related traits of trematode genotypes

Within‐host interactions between co‐infecting parasites can significantly influence the evolution of key parasite traits, such as virulence (pathogenicity of infection). The type of interaction is expected to predict the direction of selection, with antagonistic interactions favouring more virulent genotypes and synergistic interactions less virulent genotypes. Recently, it has been suggested that virulence can further be affected by the genetic identity of co‐infecting partners (G × G interactions), complicating predictions on disease dynamics. Here, we used a natural host–parasite system including a fish host and a trematode parasite to study the effects of G × G interactions on infection virulence. We exposed rainbow trout (Oncorhynchus mykiss) either to single genotypes or to mixtures of two genotypes of the eye fluke Diplostomum pseudospathaceum and estimated parasite infectivity (linearly related to pathogenicity of infection, measured as coverage of eye cataracts) and relative cataract coverage (controlled for infectivity). We found that both traits were associated with complex G × G interactions, including both increases and decreases from single infection to co‐infection, depending on the genotype combination. In particular, combinations where both genotypes had low average infectivity and relative cataract coverage in single infections benefited from co‐infection, while the pattern was opposite for genotypes with higher performance. Together, our results show that infection outcomes vary considerably between single and co‐infections and with the genetic identity of the co‐infecting parasites. This can result in variation in parasite fitness and consequently impact evolutionary dynamics of host–parasite interactions.     

Genotype‐by‐genotype specificity remains robust to average temperature variation in an aphid/endosymbiont/parasitoid system

Genotype‐by‐genotype interactions demonstrate the existence of variation upon which selection acts in host–parasite systems at respective resistance and infection loci. These interactions can potentially be modified by environmental factors, which would entail that different genotypes are selected under different environmental conditions. In the current study, we checked for a G × G × E interaction in the context of average temperature and the genotypes of asexual lines of the endoparasitoid wasp Lysiphlebus fabarum and isolates of Hamiltonella defensa, a protective secondary endosymbiont of the wasp's host, the black bean aphid Aphis fabae. We exposed genetically identical aphids harbouring different isolates of H. defensa to three asexual lines of the parasitoid and measured parasitism success under three different temperatures (15, 22 and 29 °C). Although there was clear evidence for increased susceptibility to parasitoids at the highest average temperature and a strong G × G interaction between the host's symbionts and the parasitoids, no modifying effect of temperature, that is, no significant G × G × E interaction, was detected. This robustness of the observed specificity suggests that the relative fitness of different parasitoid genotypes on hosts protected by particular symbionts remains uncomplicated by spatial or temporal variation in temperature, which should facilitate biological control strategies.     

Host plant and competitor identity matter in genotype × genotype × environment interactions between vetch and pea aphids

1. Selection does not only operate in a genotype (G) × environment (E) context, but can also be modulated by the activities of organisms interacting with their environment (G × G × E). 2. The influences of aphid clonal identity and host plant (Vicia faba) intraspecific genetic variation on the performance of five genotypes of pea aphid (Acyrthosiphon pisum) were investigated – with and without interaction with a competing heterospecific clone of vetch aphid (Megoura viciae) – across three cultivars of V. faba. 3. Pea aphid performance in the presence of a competing vetch aphid clone (G × G × E) compared with the absence of competition (G × E) revealed strong context‐dependent, genotype‐specific shifts in performance, influenced by plant cultivar, competitor presence and their interaction. 4. The performance of vetch aphid in competition with each pea aphid clone was also compared. Here, competitor's genotype and abundance underlay a remarkably varied response by vetch aphid across interactions. 5. The study shows that aphid genotypes exhibit a varying degree of risk spreading, contingent on competitor identity and the patterns of aggregation across three plant cultivars. Owing to feedback loops between species activities and selective forces acting on them, our findings suggest that there are context‐dependent responses by competitors that are shaped via the interplay of the co‐occurring species and their biotic environment. 6. This work highlights the complexity of species interactions and the importance of investigating reciprocity between competition and intraspecific genetic variation. A better understanding of the eco‐evolutionary interactions between phloem‐feeding insects and their host plants can potentially be used to enhance crop protection and pest control.     

Phenotypic integration plasticity in Daphnia magna: an integral facet of G × E interactions

Phenotypic integration can be defined as the network of multivariate relationships among behavioural, physiological and morphological traits that describe the organism. Phenotypic integration plasticity refers to the change in patterns of phenotypic integration across environments or ontogeny. Because studies of phenotypic plasticity have predominantly focussed on single traits, a G × E interaction is typically perceived as differences in the magnitude of trait expression across two or more environments. However, many plastic responses involve coordinated responses in multiple traits, raising the possibility that relative differences in trait expression in different environments are an important, but often overlooked, source of G × E interaction. Here, we use phenotypic change vectors to statistically compare the multivariate life‐history plasticity of six Daphnia magna clones collected from four disparate European populations. Differences in the magnitude of plastic responses were statistically distinguishable for two of the six clones studied. However, differences in phenotypic integration plasticity were statistically distinguishable for all six of the clones studied, suggesting that phenotypic integration plasticity is an important component of G × E interactions that may be missed unless appropriate multivariate analyses are used.     

The potential for arms race and Red Queen coevolution in a protist host–parasite system

The dynamics and consequences of host–parasite coevolution depend on the nature of host genotype‐by‐parasite genotype interactions (G × G) for host and parasite fitness. G × G with crossing reaction norms can yield cyclic dynamics of allele frequencies (“Red Queen” dynamics) while G × G where the variance among host genotypes differs between parasite genotypes results in selective sweeps (“arms race” dynamics). Here, we investigate the relative potential for arms race and Red Queen coevolution in a protist host–parasite system, the dinoflagellate Alexandrium minutum and its parasite Parvilucifera sinerae. We challenged nine different clones of A. minutum with 10 clones of P. sinerae in a fully factorial design and measured infection success and host and parasite fitness. Each host genotype was successfully infected by four to ten of the parasite genotypes. There were strong G × Gs for infection success, as well as both host and parasite fitness. About three quarters of the G × G variance components for host and parasite fitness were due to crossing reaction norms. There were no general costs of resistance or infectivity. We conclude that there is high potential for Red Queen dynamics in this host–parasite system.     

Genotype‐by‐environment interactions for cuticular hydrocarbon expression in Drosophila simulans

Genotype‐by‐environment interactions (G × Es) describe genetic variation for phenotypic plasticity. Recent interest in the role of these interactions in sexual selection has identified G × Es across a diverse range of species and sexual traits. Additionally, theoretical work predicts that G × Es in sexual traits could help to maintain genetic variation, but could also disrupt the reliability of these traits as signals of mate quality. However, empirical tests of these theoretical predictions are scarce. We reared iso‐female lines of Drosophila simulans across two axes of environmental variation (diet and temperature) in a fully factorial design and tested for G × Es in the expression of cuticular hydrocarbons (CHCs), a multivariate sexual trait in this species. We find sex‐specific environmental, genetic and G × E effects on CHC expression, with G × Es for diet in both male and female CHC profile and a G × E for temperature in females. We also find some evidence for ecological crossover in these G × Es, and by quantifying variance components, genetic correlations and heritabilities, we show the potential for these G × Es to help maintain genetic variation and cause sexual signal unreliability in D. simulans CHC profiles.     

Heterosis and combining ability for floral and yield characters in rice using cytoplasmic male sterility system

Developing high-yielding rice genotypes is decisive to ensure global food security with current population growth and the threat of environmental pressures. Cytoplasmic male sterility (CMS) system provides a valuable approach for commercial exploitation of heterosis and producing high-yielding and quality hybrid rice. Three CMS lines and ten diverse restorers were crossed using line × tester mating design. The obtained thirty F₁ hybrids and their thirteen parents were evaluated. Yield traits as well as certain floral traits characters that influence the efficiency of crossing and hybrid seed production as the duration of floret opening (min), stigma exsertion (mm), stigma length (mm), opening floret angle, and anther length (mm) were assessed. Highly significant variations were detected among parents, crosses, and parents vs. crosses for all the studied traits. The CMS line L2 and the restorer T5 were determined as good combiners for stigma exsertion, stigma length, opining floret angle, and duration of floret opening. Besides, the hybrids L1 × T1, L1 × T3, L2 × T2, L2 × T5, L3 × T4, L3 × T5, and L3 × T9 exhibited positive SCA effects for most floral traits. Moreover, the CMS lines L1 and L3 as well as the restorers T1, T2, T3, T6, and T9 were identified as good general combiners for grain yield and certain related traits. The hybrids L1 × T1, L1 × T5, L1 × T7, L2 × T3, L2 × T4, L2 × T5, L2 × T10, L3 × T1, L3 × T2, and L3 × T6 displayed positive SCA effects for grain yield and one or more of its attributes. Both additive and non-additive gene effects were involved in the governing inheritance of all evaluated traits. The biochemical variations among the certain evaluated genotypes were further studied. The esterase and peroxidase isozymes were applied for verifying the genetic diversity at the protein level among the used CMS lines, restorers, and their crosses. All the applied isozymes displayed polymorphism for the parents and their crosses. The banding pattern and intensity differences provided accurate results on the reliable variability among the tested genotypes.     

Coherent synthesis of genomic associations with phenotypes and home environments

Local adaptation is often studied via (i) multiple common garden experiments comparing performance of genotypes in different environments and (ii) sequencing genotypes from multiple locations and characterizing geographic patterns in allele frequency. Both approaches aim to characterize the same pattern (local adaptation), yet the complementary information from each has not yet been coherently integrated. Here, we develop a genome‐wide association model of genotype interactions with continuous environmental gradients (G × E), that is reaction norms. We present an approach to impute relative fitness, allowing us to coherently synthesize evidence from common garden and genome–environment associations. Our approach identifies loci exhibiting environmental clines where alleles are associated with higher fitness in home environments. Simulations show our approach can increase power to detect loci causing local adaptation. In a case study on Arabidopsis thaliana, most identified SNPs exhibited home allele advantage and fitness trade‐offs along climate gradients, suggesting selective gradients can maintain allelic clines. SNPs exhibiting G × E associations with fitness were enriched in genic regions, putative partial selective sweeps and associations with an adaptive phenotype (flowering time plasticity). We discuss extensions for situations where only adaptive phenotypes other than fitness are available. Many types of data may point towards the loci underlying G × E and local adaptation; coherent models of diverse data provide a principled basis for synthesis.