Genotype by environment interaction for litter size in pigs as quantified by reaction norms analysis

A Bayesian procedure was used to estimate linear reaction norms (i.e. individual G × E plots) on 297 518 litter size records of 121 104 sows, daughters of 2040 sires, recorded on 144 farms in North and Latin America, Europe, Asia and Australia. The method allowed for simultaneous estimation of all parameters involved. The analysis was carried out on three subsets, comprising (i) parity 1 records of 33 641 sows of line B, (ii) all parity records of 52 120 sows of line B and (iii) all parity records of 121 104 sows of lines A, B and A × B. Estimated heritabilities ranged from 0.09 to 0.10 (smallest to largest subset) for the intercept of the reaction norms, and were 0.15, 0.08 and 0.02 (ditto) for the slope. Estimated genetic correlations between intercept and slope were -0.09, +0.26 and +0.69 (ditto). The three subsets therefore showed a progressively lower genetic component to environmental sensitivity, and progressively less re-ranking of genotypes across the environmental (herd-year-season) range. In a genetic evaluation that does not include reaction norms in the statistical model, part of the G × E effect remains confounded with the additive genetic effect, which may lead to errors in the estimates of the additive genetic effect; the reaction norms model removes this confounding. The intercept estimates from the largest data subset show correlations with litter size estimated breeding values (EBV) from routine genetic evaluation (without reaction norms included) of 0.78 to 0.85 for sows with one to seven litter records, and 0.75 for sires. Hence, including reaction norms in genetic evaluation would increase the reliability of the EBV of young selection candidates without own performance or progeny data by considerably more than 100 × (1/0.75-1) = 33%. Reaction norm slope estimates turn out to be very demanding statistics; environmental sensitivity must therefore be classified as a 'hard-to-measure' trait.     

Effects of data structure on the estimation of covariance functions to describe genotype by environment interactions in a reaction norm model

Covariance functions have been proposed to predict breeding values and genetic (co)variances as a function of phenotypic within herd-year averages (environmental parameters) to include genotype by environment interaction. The objective of this paper was to investigate the influence of definition of environmental parameters and non-random use of sires on expected breeding values and estimated genetic variances across environments. Breeding values were simulated as a linear function of simulated herd effects. The definition of environmental parameters hardly influenced the results. In situations with random use of sires, estimated genetic correlations between the trait expressed in different environments were 0.93, 0.93 and 0.97 while simulated at 0.89 and estimated genetic variances deviated up to 30% from the simulated values. Non random use of sires, poor genetic connectedness and small herd size had a large impact on the estimated covariance functions, expected breeding values and calculated environmental parameters. Estimated genetic correlations between a trait expressed in different environments were biased upwards and breeding values were more biased when genetic connectedness became poorer and herd composition more diverse. The best possible solution at this stage is to use environmental parameters combining large numbers of animals per herd, while losing some information on genotype by environment interaction in the data.     

Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models

Genotype by environment interactions (GEI) have attracted increasing attention in tropical breeding programs because of the variety of production systems involved. In this work, we assessed GEI in 450-day adjusted weight (W450) Nelore cattle from 366 Brazilian herds by comparing traditional univariate single-environment model analysis (UM) and random regression first order reaction norm models for six environmental variables: standard deviations of herd-year (RRMw) and herd-year-season-management (RRMw-m) groups for mean W450, standard deviations of herd-year (RRMg) and herd-year-season-management (RRMg-m) groups adjusted for 365-450 days weight gain (G450) averages, and two iterative algorithms using herd-year-season-management group solution estimates from a first RRMw-m and RRMg-m analysis (RRMITw-m and RRMITg-m, respectively). The RRM results showed similar tendencies in the variance components and heritability estimates along environmental gradient. Some of the variation among RRM estimates may have been related to the precision of the predictor and to correlations between environmental variables and the likely components of the weight trait. GEI, which was assessed by estimating the genetic correlation surfaces, had values < 0.5 between extreme environments in all models. Regression analyses showed that the correlation between the expected progeny differences for UM and the corresponding differences estimated by RRM was higher in intermediate and favorable environments than in unfavorable environments (p < 0.0001).     

Local adaptation in four Iris species tested in a common-garden experiment

Local adaptation is a commonly observed result of natural selection acting in heterogeneous environment. Common-garden experiments are a method of detecting local adaptation, as well as studying phenotypic plasticity and gradients of traits. The present study aimed to analyse reaction norms of four closely-related Iris species of section Oncocyclus and to identify a role of environmentally-specific natural selection in their plastic responses. The plant vegetative and phenological, as well as performance traits were measured in a full factorial common-garden experiment with three levels of water amount and three soil types. We found a significant effect of species identity on all traits measured. Water amount and soil type affected many of the traits, but soil type did not affect the performance. There was no significant difference in the effect of water amount and soil type on performance as reflected by rhizome growth; in other words, there was no significant genotype × environment interaction for performance. Plasticity levels and directions of response were also similar among the species. We conclude that phenotypic differences among species are of genetic origin, although no adaptive value was demonstrated for them at the time and life-stages 'frame' of this experiment.  © 2009 The Linnean Society of London, Biological Journal of the Linnean Society 2009, 98 , 267–277.     

Genotype by environment interaction for livability of dairy calves from first parity cows

Death of calves around parturition is a matter of concern for dairy farmers. Relatively high stillbirth rates and unfavourable trends have been reported for Holstein heifers in the Netherlands and several other countries. In our study, we investigated herd differences, genetic parameters and genotype by environment interaction for heifer calf livability. A large dataset with data from calvings between 1993 and 2012 of Dutch dairy farms was used. There were considerable differences between herds in livability of calves from heifers, with averages ranging from 74% to 95%. Both herds with relatively high and low averages showed the same negative trend between 1993 and 2012, with largest declines in herds with the lowest averages. We found that heritability and genetic variation of first parity livability were substantially larger in herd environments where the likelihood of stillbirth was high v. environments where stillbirth was at a low level. The genetic correlations between herd environment levels were all very close to unity, indicating that ranking of sires was similar for all environments. However, for herds with a relatively high stillbirth incidence selecting sires with favourable breeding values is expected to be twice as profitable as in herds with a relatively low stillbirth incidence.     

Genotype by environment interaction for adult body weights of shrimp Penaeus vannamei when grown at low and high densitie

Shrimp is one of few marine species cultured worldwide for which several selective breeding programs are being conducted. One environmental factor that can affect the response to selection in breeding programs is the density at which the shrimp are cultured (low-medium-high). Phenotypic plasticity in the growth response to different densities might be accompanied by a significant genotype by environment interaction, evidenced by a change in heritabilities between environments and by a genetic correlation less than one for a unique trait between environments. Our goal was to understand whether different growth densities affect estimates of those genetic parameters for adult body weight (BW) in the Pacific white shrimp (Penaeus vannamei). BW heritabilities were significantly different between environments, with the largest at high density. These differences resulted from both an increased additive genetic variance and a decreased environmental variance when grown at high density. The genetic correlation between BWs at the two environmental conditions was significantly less than one. Whereas these results might be suggestive for carrying out shrimp selective breeding for BW under high density conditions, further understanding of genetic correlations between growth and reproductive traits within a given environment is necessary, as there are indications of reduced reproductive fitness for shrimp grown at high densities.     

Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle

The objectives of the present study were: (1) to evaluate the importance of genotype×production environment interaction for the genetic evaluation of birth weight (BW) and weaning weight (WW) in a population of composite beef cattle in Brazil, and (2) to investigate the importance of sire×contemporary group interaction (S×CG) to model G×E and improve the accuracy of prediction in routine genetic evaluations of this population. Analyses were performed with one, two (favorable and unfavorable) or three (favorable, intermediate, unfavorable) different definitions of production environments. Thus, BW and WW records of animals in a favorable environment were assigned to either trait 1, in an intermediate environment to trait 2 or in an unfavorable environment to trait 3. The (co)variance components were estimated using Gibbs sampling in single-, bi- or three-trait animal models according to the definition of number of production environments. In general, the estimates of genetic parameters for BW and WW were similar between environments. The additive genetic correlations between production environments were close to unity for BW; however, when examining the highest posterior density intervals, the correlation between favorable and unfavorable environments reached a value of only 0.70, a fact that may lead to changes in the ranking of sires across environments. The posterior mean genetic correlation between direct effects was 0.63 in favorable and unfavorable environments for WW. When S×CG was included in two- or three-trait analyses, all direct genetic correlations were close to unity, suggesting that there was no evidence of a genotype×production environment interaction. Furthermore, the model including S×CG contributed to prevent overestimation of the accuracy of breeding values of sires, provided a lower error of prediction for both direct and maternal breeding values, lower squared bias, residual variance and deviance information criterion than the model omitting S×CG. Thus, the model that included S×CG can therefore be considered the best model on the basis of these criteria. The genotype×production environment interaction should not be neglected in the genetic evaluation of BW and WW in the present population of beef cattle. The inclusion of S×CG in the model is a feasible and plausible alternative to model the effects of G×E in the genetic evaluations.     

Random regression models for detection of gene by environment interaction

Two random regression models, where the effect of a putative QTL was regressed on an environmental gradient, are described. The first model estimates the correlation between intercept and slope of the random regression, while the other model restricts this correlation to 1 or -1, which is expected under a bi-allelic QTL model. The random regression models were compared to a model assuming no gene by environment interactions. The comparison was done with regards to the models ability to detect QTL, to position them accurately and to detect possible QTL by environment interactions. A simulation study based on a granddaughter design was conducted, and QTL were assumed, either by assigning an effect independent of the environment or as a linear function of a simulated environmental gradient. It was concluded that the random regression models were suitable for detection of QTL effects, in the presence and absence of interactions with environmental gradients. Fixing the correlation between intercept and slope of the random regression had a positive effect on power when the QTL effects re-ranked between environments.     

Genotype by environment interactions in winter survival in red deer

1. The extent to which environmental heterogeneity interacts with genetic hetero geneity to affect individual fitness within populations has the potential to affect the dynamics of natural populations and the amount of genetic variation maintained in natural populations, yet is a relatively poorly investigated topic in either ecology or evolutionary biology.
2. Many individual-based studies are precluded from such investigations by the practical problems of measuring heritability of traits affecting fitness and the difficulties of experimental manipulation of the study population. One way of demonstrating how commonly genotype by environmental interactions affect fitness, though not their overall importance in determining fitness, is to investigate fitness in a population subdivided by genotype at one or more marker loci.
3. We analyse data on calf winter survival from a population of red deer from the Isle of Rum, Scotland. Data on individual survival, environmental fluctuations and genotype at 13 loci were collected from 1982 to 1994.
4. We found associations between survival over the first winter of life and calf genotype at two out of three allozyme loci and five out of 10 microsatellite loci. All of the results remained significant under randomization tests. Other genotypes that initially appeared to have an association with survival were rejected when bootstrapped, usually due to insufficient data or anomalies in the data.
5. Our results suggest that associations between fitness and genotype are common. Five out of the seven associations found involved interactions with environmental variables. Four of these showed density-dependent selection with different genotypes showing high survival at high population size compared to low population size and one interacted with autumn rainfall. In a sixth case, genotype interacted with sex.     

Contrasting levels of genotype by environment interaction for life history and morphological traits in invasive populations of Zaprionus indianus (Diptera: Drosophilidae)

It has been demonstrated that phenotypic plasticity and genotype by environment interaction are important for coping with new and heterogeneous environments during invasions. Zaprionus indianus Gupta (Diptera: Drosophilidae) is an Afrotropical invasive fly species introduced to the South American continent in 1999. This species is generalist and polyphagous, since it develops and feeds in several different fruit species. These characteristics of Z. indianus suggest that phenotypic plasticity and genotype by environment interaction may be important in this species invasion process. In this sense, our aim was to investigate the role of genetic variation for phenotypic plasticity (genotype by environment interaction) in Z. indianus invasion of the South American continent. Specifically, we quantified quantitative genetic variation and genotype by environment interactions of morphological and life history traits in different developmental environments, that is, host fruits. This was done in different populations in the invasive range of Z. indianus in Argentina. Results showed that Z. indianus populations have considerable amounts of quantitative genetic variation. Also, genotype by environment interactions was detected for the different traits analyzed in response to the different developmental environments. Interestingly, the amounts and patterns of these parameters differed between populations. We interpreted these results as the existence of differences in evolutionary potential between populations that have an important role in the short‐ and long‐term success of the Z. indianus invasion process.     

Genetic variance of sexually selected traits in waxmoths: maintenance by genotype x environment interaction

When traits experience directional selection, such as that imposed by sexual selection, their genetic variance is expected to diminish. Nonetheless, theory and findings from sexual selection predict and demonstrate that male traits favored by female choice retain substantial amounts of additive genetic variance. We explored this dilemma through an ecological genetic approach and focused on the potential contributions of genotype x environment interaction (GEI) to maintenance of additive genetic variance for male signal characters in the lesser waxmoth, Achroia grisella (Lepidoptera: Pyralidae). We artificially selected genetic variants for two male signal characters, signal rate (SR) and peak amplitude (PA), that influence female attraction and then examined the phenotypic plasticity of these variants (high- and low-SR and high- and low-PA lines) under a range of environmental conditions expected in natural populations. Our split-family breeding experiments indicated that two signal characters, SR and PA, and several developmental characters in both high- and low-SR and high- and low-PA lines displayed considerable phenotypic plasticity among the environments tested. Moreover, strong GEIs leading to crossover between high- and low-SR lines were found for SR and developmental period. Therefore, neither high- nor low-SR genetic variants would achieve maximum attractiveness and fitness in every environment, and those variants producing unattractive signals with low SRs under normal conditions may remain in populations provided that gene flow across environments or generation overlap are sufficiently high. We speculate that the phenotypic plasticity for SR and developmental period is adaptive in A. grisella populations experiencing a range of temperature and density conditions. Females mating with attractive (high-SR) males may be assured of obtaining good genes because these males sire offspring that develop more rapidly and a crossover for developmental period may parallel that for SR. Such parallel crossovers may be expected wherever good-genes sexual selection mechanisms operate.     

Interactions between genotype and sexual conflict environment influence transgenerational fitness in Drosophila melanogaster

Theory predicts that sexual conflict can fuel evolutionary change and generate substantial reproductive costs. This was tested here by measuring the fitness of focal individuals across multiple generations using an experimental framework. We manipulated sexual conflict through high versus low exposure of females to males across a four-generation pedigree of Drosophila melanogaster, and assessed fitness in 1062 females and 639 males. We used the animal model to estimate (1) genotype by sexual conflict environment interactions for female fitness and (2) indirect benefits gained through sons and daughters. Some female genotypes achieved higher fitness under low, in comparison to high, conflict and vice versa. We found a consistent 10% reduction in female fitness under high conflict, regardless of maternal history. Following high exposure, females produced sons with increased, but grandsons with decreased, fitness. This opposing effect suggests no consistent fitness gains through sons for females that mated multiply. We saw no indirect benefits through daughters. Our pedigree was based exclusively on maternal links; however, maternal effects are unlikely to contribute significantly unless expressed across multiple generations. In sum, we quantified a significant sexual conflict load and a female genotype by sexual conflict interaction that could slow the erosion of genetic variation.     

Niche construction and the environmental term of the price equation: How natural selection changes when organisms alter their environments

Organisms construct their own environments and phenotypes through the adaptive processes of habitat choice, habitat construction, and phenotypic plasticity. We examine how these processes affect the dynamics of mean fitness change through the environmental change term of the Price Equation. This tends to be ignored in evolutionary theory, owing to the emphasis on the first term describing the effect of natural selection on mean fitness (the additive genetic variance for fitness of Fisher's Fundamental Theorem). Using population genetic models and the Price Equation, we show how adaptive niche constructing traits favorably alter the distribution of environments that organisms encounter and thereby increase population mean fitness. Because niche-constructing traits increase the frequency of higher-fitness environments, selection favors their evolution. Furthermore, their alteration of the actual or experienced environmental distribution creates selective feedback between niche constructing traits and other traits, especially those with genotype-by-environment interaction for fitness. By altering the distribution of experienced environments, niche constructing traits can increase the additive genetic variance for such traits. This effect accelerates the process of overall adaption to the niche-constructed environmental distribution and can contribute to the rapid refinement of alternative phenotypic adaptations to different environments. Our findings suggest that evolutionary biologists revisit and reevaluate the environmental term of the Price Equation: owing to adaptive niche construction, it contributes directly to positive change in mean fitness; its magnitude can be comparable to that of natural selection; and, when there is fitness G × E, it increases the additive genetic variance for fitness, the much-celebrated first term.     

Unpredictable selection in a structured population leads to local genetic differentiation in evolved reaction norms

Unpredictability during development of the optimum phenotype under future selection leads to a compromise reaction norm with a slope that is shallower than the slope of the optimum reaction norm. Unpredictability of selection can lead to an evolved curved reaction norm when genetic variation for curvature is available even if the optimum reaction norm is linear. This requires asymmetry in the frequency distribution of the habitats of selection; at small population size, stochasticity in the number of individuals per selection habitat is sufficient to generate such asymmetry. Unpredictability of selection in structured populations leads to local genetic differentiation of reaction norms. The mean habitat of a subpopulation is defined as the subpopulation's focal habitat. The evolved mean reaction norm of each subpopulation is anchored at the optimum genotypic value in its focal habitat. Linear reaction norms are parallel if the conditional distribution of adults around the focal habitats is the same for each subpopulation. Adult migration and absence of zygote dispersal represents the ultimate structured population, each habitat playing the role of focal habitat. Absence of zygote dispersal requires that the flow of individuals through the habitats is used instead of the habitats’ frequencies in the prediction of the evolved reaction norm. Adult migration in absence of zygote dispersal leads to an evolved pattern of locally differentiated reaction norms with optimum genotypic value anchored in the focal habitat and, for linear reaction norms, parallel slopes.     

Assessing the impact of natural service bulls and genotype by environment interactions on genetic gain and inbreeding in organic dairy cattle genomic breeding programs

The objective of the present study was to compare genetic gain and inbreeding coefficients of dairy cattle in organic breeding program designs by applying stochastic simulations. Evaluated breeding strategies were: (i) selecting bulls from conventional breeding programs, and taking into account genotype by environment (G×E) interactions, (ii) selecting genotyped bulls within the organic environment for artificial insemination (AI) programs and (iii) selecting genotyped natural service bulls within organic herds. The simulated conventional population comprised 148 800 cows from 2976 herds with an average herd size of 50 cows per herd, and 1200 cows were assigned to 60 organic herds. In a young bull program, selection criteria of young bulls in both production systems (conventional and organic) were either ‘conventional’ estimated breeding values (EBV) or genomic estimated breeding values (GEBV) for two traits with low (h²=0.05) and moderate heritability (h²=0.30). GEBV were calculated for different accuracies (r_mg), and G×E interactions were considered by modifying originally simulated true breeding values in the range from r_g=0.5 to 1.0. For both traits (h²=0.05 and 0.30) and r_mg⩾0.8, genomic selection of bulls directly in the organic population and using selected bulls via AI revealed higher genetic gain than selecting young bulls in the larger conventional population based on EBV; also without the existence of G×E interactions. Only for pronounced G×E interactions (r_g=0.5), and for highly accurate GEBV for natural service bulls (r_mg>0.9), results suggests the use of genotyped organic natural service bulls instead of implementing an AI program. Inbreeding coefficients of selected bulls and their offspring were generally lower when basing selection decisions for young bulls on GEBV compared with selection strategies based on pedigree indices.     

Genotype by environment interaction in response to cold stress in a composite beef cattle breed

Extreme weather conditions such as cold stress influence the productivity and survivability of beef cattle raised on pasture. The objective of this study was to identify and evaluate the extent of the impact of genotype by environment interaction due to cold stress on birth weight (BW) and weaning weight (WW) in a composite beef cattle population. The effect of cold stress was modelled as the accumulation of total cold load (TCL) calculated using the Comprehensive Climate Index units, considering three TCL classes defined based on temperature: less than −5°C (TCL5), −15°C (TCL15) and −25°C (TCL25). A total of 4221 and 4217 records for BW and WW, respectively, were used from a composite beef cattle population (50% Red Angus, 25% Charolais and 25% Tarentaise) between 2002 and 2015. For both BW and WW, a univariate model (ignoring cold stress) and a reaction norm model were implemented. As cold load increased, the direct heritability slightly increased in both BW and WW for TCL5 class; however, this heritability remained consistent across the cold load of TCL25 class. In contrast, the maternal heritability of BW was constant with cold load increase in all TCL classes, although a slight increase of maternal heritability was observed for TCL5 and TCL15. The direct and maternal genetic correlation for BW and maternal genetic correlation for WW across different cold loads between all TCL classes were high (r > 0.99), whereas the lowest direct genetic correlations observed for WW were 0.88 for TCL5 and 0.85 for TCL15. The Spearman rank correlation between the estimated breeding value of top bulls (n = 79) using univariate and reaction norm models across TCL classes showed some re-ranking in direct and maternal effects for both BW and WW particularly for TCL5 and TCL15. In general, cold stress did not have a big impact on direct and maternal genetic effects of BW and WW.     

Adaptation to an extraordinary environment by evolution of phenotypic plasticity and genetic assimilation

Adaptation to a sudden extreme change in environment, beyond the usual range of background environmental fluctuations, is analysed using a quantitative genetic model of phenotypic plasticity. Generations are discrete, with time lag τ between a critical period for environmental influence on individual development and natural selection on adult phenotypes. The optimum phenotype, and genotypic norms of reaction, are linear functions of the environment. Reaction norm elevation and slope (plasticity) vary among genotypes. Initially, in the average background environment, the character is canalized with minimum genetic and phenotypic variance, and no correlation between reaction norm elevation and slope. The optimal plasticity is proportional to the predictability of environmental fluctuations over time lag τ. During the first generation in the new environment the mean fitness suddenly drops and the mean phenotype jumps towards the new optimum phenotype by plasticity. Subsequent adaptation occurs in two phases. Rapid evolution of increased plasticity allows the mean phenotype to closely approach the new optimum. The new phenotype then undergoes slow genetic assimilation, with reduction in plasticity compensated by genetic evolution of reaction norm elevation in the original environment.     

Welcome to the neighbourhood: interspecific genotype by genotype interactions in Solidago influence above- and belowground biomass and associated communities

Intra- and interspecific plant-plant interactions are fundamental to patterns of community assembly and to the mixture effects observed in biodiversity studies. Although much research has been conducted at the species level, very little is understood about how genetic variation within and among interacting species may drive these processes. Using clones of both Solidago altissima and Solidago gigantea, we found that genotypic variation in a plant's neighbours affected both above- and belowground plant traits, and that genotype by genotype interactions between neighbouring plants impacted associated pollinator communities. The traits for which focal plant genotypic variation explained the most variation varied by plant species, whereas neighbour genotypic variation explained the most variation in coarse root biomass. Our results provide new insight into genotypic and species diversity effects in plant-neighbour interactions, the extended consequences of diversity effects, and the potential for evolution in response to competitive or to facilitative plant-neighbour interactions.     

Environmental origins of sexually selected variation and a critique of the fluctuating asymmetry-sexual selection hypothesis

Identifying sources of phenotypic variability in secondary sexual traits is critical for understanding their signaling properties, role in sexual selection, and for predicting their evolutionary dynamics. The present study tests for the effects of genotype, developmental temperature, and their interaction, on size and fluctuating asymmetry of the male sex comb, a secondary sexual character, in Drosophila bipectinata Duda. Both the size and symmetry of elements of the sex comb have been shown previously to be under sexual selection in a natural population in northeastern Australia. Two independent reciprocal crosses were conducted at 25 degrees and 29 degrees C between genetic lines extracted from this population that differed in the size of the first (TC1) and third (TC3) comb segments. These temperatures are within the documented range experienced by the species in nature. Additive and dominance genetic effects were detected for TC1, whereas additive genetic, and Y-chromosomal effects were detected for TC3. TC2 and TC3 decreased sharply with increasing temperature, by 10% and 22%, respectively. In contrast, positional fluctuating asymmetry (PFA) significantly increased with temperature, by up to 38%. The results (1) document an important source of environmental variance in a sexual ornament expected to reduce trait heritability in field populations, and thus act to attenuate response to sexual selection, (2) suggest that variation in ornament size reflects differences in male condition; and (3) support the general hypothesis that asymmetry in a sexual ornament is indicative of developmental instability arising from environmental stress. The "environmental heterogeneity" (EH) hypothesis is proposed, and supportive evidence for it presented, to explain negative size-FA correlations in natural populations. Data and theory challenge the use of negative size-FA correlations observed in nature to support the FA-sexual selection hypothesis, which posits that such correlations are driven by differences in genetic quality among individuals.     

Environmental and genetic interactions reveal FLOWERING LOCUS C as a modulator of the natural variation for the plasticity of flowering in Arabidopsis

The timing of flowering initiation depends strongly on the environment, a property termed as the plasticity of flowering. Such plasticity determines the adaptive potential of plants because it provides phenotypic buffer against environmental changes, and its natural variation contributes to evolutionary adaptation. We addressed the genetic mechanisms of the natural variation for this plasticity in Arabidopsis thaliana by analysing a population of recombinant inbred lines derived from Don‐0 and Ler accessions collected from distinct climates. Quantitative trait locus (QTL) mapping in four environmental conditions differing in photoperiod, vernalization treatment and ambient temperature detected the folllowing: (i) FLOWERING LOCUS C (FLC) as a large effect QTL affecting flowering time differentially in all environments; (ii) numerous QTL displaying smaller effects specifically in some conditions; and (iii) significant genetic interactions between FLC and other loci. Hence, the variation for the plasticity of flowering is determined by a combination of environmentally sensitive and specific QTL, and epistasis. Analysis of FLC from Don identified a new and more active allele likely caused by a cis‐regulatory deletion covering the non‐coding RNA COLDAIR. Further characterization of four FLC natural alleles showed different environmental and genetic interactions. Thus, FLC appears as a major modulator of the natural variation for the plasticity of flowering to multiple environmental factors.