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.     

Grain of environment explains variation in the strength of genotype × environment interaction

Theory predicts that genetic variation in phenotypic plasticity (genotype × environment interaction or G × E) should be eroded by selection acting across environments. However, it appears that G × E is often maintained under selection, although not universally. This variation in the presence and strength of G × E requires explanation. Here I ask whether the explanation may lie in the grain of the environment at which G × E is expressed. The grain (or grain size) of the environment refers to the scale of environmental heterogeneity relative to generation time – that is, relative to the window of operation of selection – with higher rates of heterogeneity occurring in finer‐grained environments. The hypothesis that the grain of the environment explains variation in the expression of G × E encapsulates variation in the power of selection to shape reaction norms: selection should be able to erode G × E in fine‐grained environments but lose its power as the grain becomes coarser. I survey studies of G × E in sexual traits and demonstrate that the strength of G × E varies with the grain of the environment across which it is expressed, with G × E being stronger in coarser‐grained environments. This result elucidates when G × E is most likely to be sustained in the reaction norms of fitness‐related traits and when its evolutionary consequences will be most pronounced.     

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.     

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     

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.     

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 × 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.     

Use of genotype × environment interactions to understand rooting depth and the ability of wheat to penetrate hard soils

Background

Root systems are well-recognized as complex and a variety of traits have been identified as contributing to plant adaptation to the environment. A significant proportion of soil in south-western Australia is prone to the formation of hardpans of compacted soil that limit root exploration and thus access to nutrients and water for plant growth. Genotypic variation has been reported for root-penetration ability of wheat in controlled conditions, which has been related to field performance in these environments. However, research on root traits in field soil is recognized as difficult and labour intensive. Pattern analysis of genotype × environment (G × E) interactions is one approach that enables interpretation of these complex relationships, particularly when undertaken with probe genotypes with well-documented traits, in this case, for the ability to penetrate a wax layer. While the analytical approach is well-established in the scientific literature, there are very few examples of pattern analysis for G × E interactions applied to root traits of cereal crops.

Scope

In this viewpoint, we aim to review the approach of pattern analysis for G × E interaction and the importance of environment and genotype characterization, with a focus on root traits. We draw on our research on G × E interaction for root depth and related studies on genotypic evaluation for root-penetration ability. In doing so, we wish to explore how pattern analysis can aid in the interpretation of complex root traits and their interaction with the environment and how this may explain patterns of adaptation and inform future research.

Conclusions

With appropriate characterization of environments and genotypes, the G × E approach can be used to aid in the interpretation of the complex interactions of root systems with the environment, inform future research and therefore provide supporting evidence for selecting specific root traits for target environments in a crop breeding programme.     

Mapping QTL associated with photoperiod sensitivity and assessing the importance of QTL×environment interaction for flowering time in maize

Background

An understanding of the genetic determinism of photoperiod response of flowering is a prerequisite for the successful exchange of germplasm across different latitudes. In order to contribute to resolve the genetic basis of photoperiod sensitivity in maize, a set of 201 recombinant inbred lines (RIL), derived from a temperate and tropical inbred line cross were evaluated in 5 field trials spread in short- and long-day environments.

Methodology/Principal Findings

Firstly, QTL analyses for flowering time and photoperiod sensitivity in maize were conducted in individual photoperiod environments separately, and then, the total genetic effect was partitioned into additive effect (A) and additive-by-environment interaction effect (AE) by using a mixed-model-based composite interval mapping (MCIM) method.

Conclusions/Significance

Seven putative QTL were found associated with DPS thermal time based on the data estimated in individual environments. Nine putative QTL were found associated with DPS thermal time across environments and six of them showed significant QTL×enviroment (QE) interactions. Three QTL for photoperiod sensitivity were identified on chromosome 4, 9 and 10, which had the similar position to QTL for DPS thermal time in the two long-day environment. The major photoperiod sensitive loci qDPS10 responded to both short and long-day photoperiod environments and had opposite effects in different photoperiod environment. The QTL qDPS3, which had the greatest additive effect exclusively in the short-day environment, were photoperiod independent and should be classified in autonomous promotion pathway.     

Genetic and genotype × environment interaction effects for the content of seven essential amino acids in<Emphasis Type="Italic">Indica</Emphasis> rice

It is necessary for rice breeders to understand the genetic basis of nutrient quality traits of rice. Essential amino acids are most important in determining the nutrient quality of rice grain and can affect the health of people who depend on rice as a staple food. In view of the paucity of genetic information available on essential amino acids inindica rice, we estimated the genetic main effects and genotype × environment (G × E) interaction effects on the content of essential amino acids. Nine cytoplasmic male sterile lines as females and five restorer lines as males were introduced in a North Carolina II design across environments. Estimates of the content of the essential amino acids valine, methionine, leucine and phenylalanine showed that they were mainly controlled by genetic main effects, while the contents of threonine, cysteine and isoleucine were mainly affected by G × E effects. In the case of genetic main effects, both cytoplasmic and maternal genetic effects were predominant for all essential amino acids, indicating that selection for improving essential amino acid content based on maternal performance would be more effective than that based on seeds. The total narrow-sense heritabilities were high and ranged from 0.72 to 0.83. Since general heritabilities for these essential amino acids (except for cysteine) were found to be much larger than G × E interaction heritability, the improvement of content of most essential amino acids under selection would be expected under various environments. Rice varieties such as Zhenan 3, Yinchao 1, T49, 26715, 102 and 1391 should be selected as optimal parents for increasing the content of most essential amino acids, while the total genetic effects from Zhexie 2, Xieqingzao, Gangchao 1, V20, Zuo 5 and Zhenshan 97 were mainly negative and these parents could decrease the contents of most essential amino acids.     

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.     

Addressing speciation in the effect factor for characterisation of freshwater ecotoxicity—the case of copper

Purpose  

Determination of the ecotoxicity effect factor (EF) in life cycle impact assessment (LCIA) is based on test data reporting the total dissolved concentration of a substance. In spite of the recognised influence of chemical speciation and physico-chemical characteristics of the aquatic systems on toxicity of dissolved metals, these properties are not considered when calculating characterization factors (CFs) for metals. It is hypothesised that the main cause of the variation in reported EC50 values of Cu among published test results lies in different speciation patterns for Cu in the test media, and that the toxicity of Cu is predominantly caused by the free Cu²⁺ ion. Hence, the free Cu²⁺ ion concentration should substitute the total dissolved metal concentration when determining the EF.     

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.     

The consequence of genotype × environment interaction on high essential oil yield and its composition in clove basil (Ocimum gratissimum L.)

Clove basil (Ocimum gratissimum L.) is an aromatic, perennial herb belonging to the family Lamiaceae. The plant is indigenous to tropical areas especially India and West Africa. In Nigeria, it is found in the Savannah and coastal areas. The whole herbs of the plant contain essential oils and it is cultivated for various purposes. The plant is a rich source of eugenol in its essential oil. It is also used in the preparation of tea and infusions. It is also used in the treatment of fungal infections, fever, cold, and cough. Eugenol (4-allyl-2-methoxy phenol) is a phenolic compound from the class of phenylpropanoids. It is used in the food industry as a preservative, mainly due to its antioxidant property, and flavoring agent. The fresh herb × winter season/environment produced the highest essential oil 2.07 mL/plot with essential oil content 0.41% followed by fresh herb × summer season/environment (M1S2) = 1.68 mL. For the eugenol content, the autumn season/environment was found highly favorable = 74.52% (leaves = 69.024, stem = 74.531, and in inflorescence = 80.012) followed winter season/environment 72.30% (leaves = 71.841, stem 69.389, inflorescence 76.042, mean = 72.42%). These seasons are recommended for harvesting to obtain the optimum benefit for the quality essential oil yield.     

Mapping QTL, epistasis and genotype?×?environment interaction of antioxidant activity, chlorophyll content and head formation in domesticated lettuce (Lactuca sativa)

Fruits and vegetables are rich sources of antioxidants in human diets and their intake is associated with chronic disease prevention. Lettuce (Lactuca sativa L.) is a common vegetable in diets worldwide, but its nutritional content is relatively low. To elucidate the genetic basis of antioxidant content in lettuce, we measured the oxygen radical absorbance capacity (ORAC) and chlorophyll (Chl) content as a proxy of β-carotene in an F₈ recombinant inbred line (RIL) in multiple production cycles at two different production sites. Plants were phenotyped at the open-leaf stage to measure genetic potential (GP) or at market maturity (MM) to measure the influence of head architecture (‘head’ or ‘open’). Main effect quantitative trait loci (QTL) were identified at MM (three Chl and one ORAC QTL) and GP (two ORAC QTL). No main effect QTL for Chl was detected at GP, but epistatic interaction was identified in one pair of marker intervals for each trait at GP. Interactions with environment were also detected for both main and epistatic effects (two for main effect, and one for epistatic effect). Main effect QTL for plant architecture and nutritional traits at MM colocated to a single genomic region. Chlorophyll contents and ORAC values at MM were significantly higher and Chl a to Chl b ratios were lower in ‘open’ types compared to ‘head’ types. The nutritional traits assessed for GP showed a significant association with plant architecture suggesting pleiotropic effects or closely linked genes. Taken together, the antioxidant and chlorophyll content of lettuce is controlled by complex mechanisms and participating alleles change depending on growth stage and production environment.     

Study of the inhibitory effect of fatty acids on the interaction between DNA and polymerase β

The binding of human DNA polymerase β (pol β) to DNA template-primer duplex and single-stranded DNA in the absence or presence of pol β inhibitors has been studied using a surface plasmon resonance biosensor. Two fatty acids, linoleic acid and nervonic acid, were used as potent pol β inhibitors. In the interaction between pol β and DNA, pol β could bind to ssDNA in a single binding mode, but bound to DNA template-primer duplexes in a parallel mode. Both pol β inhibitors prevented the binding of pol β to the single strand overhang and changed the binding from parallel to single mode. The affinities of pol β to the template-primer duplex region in the presence of nervonic acid or linoleic acid were decreased by 20 and 5 times, respectively. The significant inhibitory effect of nervonic acid on the pol β-duplex interaction was due to both a 2-fold decrease in the association rate and a 9-fold increase in the dissociation rate. In the presence of linoleic acid, no significant change of association rate was observed, and the decrease in binding affinity of pol β to DNA was mainly due to 7-fold increase in the dissociation rate. Published in Russian in Biokhimiya, 2009, Vol. 74, No. 7, pp. 1000–1006. These authors contributed equally.     

Impact of epistasis and QTL×environment interaction on the developmental behavior of plant height in rice (Oryza sativa L.)

QTLs with epistatic effects and environmental interaction effects for the developmental behavior of plant height in rice were studied by conventional and conditional methods for quantitative trait loci (QTLs) by mapping with a doubled-haploid population of 123 lines from IR64/Azucena in three environments. The results showed that epistatic effects were important and most epistasis could be detected only by conditional QTL mapping, while most non–epistatic QTLs could be detected by both conventional and conditional methods. Many modificative QTLs showed only epistatic effects without their own additive effects at some stages. QTL×environment (QE) interaction effects were detected more often than QTL main effects for plant-height behavior, which might indicate that gene expression could be greatly affected by the environment. No QTLs had effects during the whole of ontogeny. Conditional QTL mapping might be a valid way to reveal dynamic gene expression for the development of quantitative traits, especially for epistatic effects. Received: 19 May 2000 / Accepted: 27 October 2000