Genotype by environment interactions in relation to growth traits in slow growing chickens

Since feed conversion ratio (FCR) is higher in slow-growing "Label Rouge" chickens than in broiler chickens, it is important to work on its improvement in this breed. However, this involves rearing animals in cages (C), an environment very different from that used for selection (in floor pens, S) and production (outdoor, E). The aim of this study was to evaluate the importance of genotype by environment (G × E) interactions between S, C, and E environments, to find the best way to select for FCR, using 2002 related animals. Growth curve parameters were estimated and body composition measured. Individual feed conversion ratios (FCR) were recorded between 8 and 10 weeks in C. The presence of G × E interactions was assessed by the genetic correlations between the same trait recorded in different environments. Moderate but significant G × E interactions were detected for carcass traits, a significant one was observed between E and S or C for growth curve parameters but none between C and S. If G × E interactions are set aside, i.e. selecting on traits recorded in C, abdominal fatness is the best indirect selection criterion for FCR but if they are taken in account then leg yield or growth curve parameters in S and growth curve parameters in E are better.     

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.     

The role of maternal effects on offspring performance in familiar and novel environments

Maternal effects are an important evolutionary force that may either facilitate adaptation to a new environment or buffer against unfavourable conditions. The degree of variation in traits expressed by siblings from different mothers is often sensitive to environmental conditions. This could generate a Maternal-by-Environment interaction (M × E) that inflates estimates of Genotype-by-Environment effects (G × E). We aimed to test for environment-specific maternal effects (M × E) using a paternal full-sib/half-sib breeding design in the seed beetle Callosobruchus maculatus, where we split and reared offspring from the same mother on two different bean host types—original and novel. Our quantitative genetic analysis indicated that maternal effects were very small on both host types for all the measured life-history traits. There was also little evidence that maternal oviposition preference for a particular host type predicted her offspring’s performance on that host. Further, additive genetic variance for most traits was relatively high on both hosts. While there was higher heritability for offspring reared in the novel host, there was no evidence for G × Es, and most cross-host genetic correlations were positive. This suggests that offspring from the same family ranked similarly for performance on both host types. Our results point to a genetic basis of host adaptation in the seed beetle, rather than maternal effects. Even so, we encourage researchers to test for potential M × Es because, due to a lack of testing, it remains unclear how often they arise.Subject terms: Evolutionary genetics, Quantitative trait     

Physiological responses of groundnut (Arachis hypogea L.) to drought stress and its amelioration: a critical review

Groundnut (Arachis hypogea L.), is an important legume cash crop for the tropical farmers and its seeds contain high amounts of edible oil (43–55%) and protein (25–28%). Even though it is a fairly drought-tolerant, production fluctuates considerably as a result of rainfall variability. To develop a water stress response function in groundnut, research works have been done to improve the performance under varying degrees of stress at various physiological stages of crop growth. This review summarizes recent information on drought resistance characteristics of groundnut with a view toward developing appropriate genetic enhancement strategies for water-limited environments. It is suggested that there are considerable gains to be made in increasing yield and stabilizing the yield in environments characterized by terminal drought stress and by shortening crop duration. Many traits conferring dehydration avoidance and dehydration tolerance are available, but integrated traits, expressing at a high level of organization are suggested to be more useful in crop improvement programs. Possible genetic improvement strategies are outlined, ranging from empirical selection for yield in drought environments to a physiological–genetic approach. It was also suggested that in view of recent advances in understanding drought resistance mechanisms, the later strategy is becoming more feasible. It is summarized that application of knowledge into practice in a systematic manner can lead to significant gains in yield and yield stability of the worlds groundnuts production. Research is needed to develop transferable technology to help farmers of arid and semi-arid regions. Increasing soil moisture storage by soil profile management and nutrient management for quick recovery from drought are some of the areas that need to be explored further.     

Genotype-by-Environment Interactions for Female Mate Choice of Male Cuticular Hydrocarbons in Drosophila simulans

Recent research has highlighted the potential importance of environmental and genotype-by-environment (G×E) variation in sexual selection, but most studies have focussed on the expression of male sexual traits. Consequently, our understanding of genetic variation for plasticity in female mate choice is extremely poor. In this study we examine the genetics of female mate choice in Drosophila simulans using isolines reared across two post-eclosion temperatures. There was evidence for G×Es in female choosiness and preference, which suggests that the evolution of female mate choice behaviour could differ across environments. However, the ranked order of preferred males was consistent across females and environments, so the same males are favoured by mate choice in spite of G×Es. Our study highlights the importance of taking cross-environment perspectives in order to gain a more comprehensive understanding of the operation of sexual selection.     

Vulnerability to cavitation,hydraulic efficiency,growth and survival in an insular pine (Pinus canariensis)

Background and Aims

It is widely accepted that hydraulic failure due to xylem embolism is a key factor contributing to drought-induced mortality in trees. In the present study, an attempt is made to disentangle phenotypic plasticity from genetic variation in hydraulic traits across the entire distribution area of a tree species to detect adaptation to local environments.

Methods

A series of traits related to hydraulics (vulnerability to cavitation and hydraulic conductivity in branches), growth performance and leaf mass per area were assessed in eight Pinus canariensis populations growing in two common gardens under contrasting environments. In addition, the neutral genetic variability (F_ST) and the genetic differentiation of phenotypic variation (Q_ST) were compared in order to identify the evolutionary forces acting on these traits.

Key Results

The variability for hydraulic traits was largely due to phenotypic plasticity. Nevertheless, the vulnerability to cavitation displayed a significant genetic variability (approx. 5 % of the explained variation), and a significant genetic × environment interaction (between 5 and 19 % of the explained variation). The strong correlation between vulnerability to cavitation and survival in the xeric common garden (r = –0·81; P < 0·05) suggests a role for the former in the adaptation to xeric environments. Populations from drier sites and higher temperature seasonality were less vulnerable to cavitation than those growing at mesic sites. No trade-off between xylem safety and efficiency was detected. Q_ST of parameters of the vulnerability curve (0·365 for P₅₀ and the slope of the vulnerability curve and 0·452 for P₈₈) differed substantially from F_ST (0·091), indicating divergent selection. In contrast, genetic drift alone was found to be sufficient to explain patterns of differentiation for xylem efficiency and growth.

Conclusions

The ability of P. canariensis to inhabit a wide range of ecosystems seemed to be associated with high phenotypic plasticity and some degree of local adaptations of xylem and leaf traits. Resistance to cavitation conferred adaptive potential for this species to adapt successfully to xeric conditions.     

Meta-analysis of Correlated Traits via Summary Statistics from GWASs with an Application in Hypertension

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple—even distinct—traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10⁻⁸) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10⁻⁷) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes.     

Genome-Wide Association Analysis for Blood Lipid Traits Measured in Three Pig Populations Reveals a Substantial Level of Genetic Heterogeneity

Serum lipids are associated with myocardial infarction and cardiovascular disease in humans. Here we dissected the genetic architecture of blood lipid traits by applying genome-wide association studies (GWAS) in 1,256 pigs from Laiwu, Erhualian and Duroc × (Landrace × Yorkshire) populations, and a meta-analysis of GWAS in more than 2,400 pigs from five diverse populations. A total of 22 genomic loci surpassing the suggestive significance level were detected on 11 pig chromosomes (SSC) for six blood lipid traits. Meta-analysis of GWAS identified 5 novel loci associated with blood lipid traits. Comparison of GWAS loci across the tested populations revealed a substantial level of genetic heterogeneity for porcine blood lipid levels. We further evaluated the causality of nine polymorphisms nearby or within the APOB gene on SSC3 for serum LDL-C and TC levels. Of the 9 polymorphisms, an indel showed the most significant association with LDL-C and TC in Laiwu pigs. But the significant association was not identified in the White Duroc × Erhualian F₂ resource population, in which the QTL for LDL-C and TC was also detected on SSC3. This indicates that population-specific signals may exist for the SSC3 QTL. Further investigations are warranted to validate this assumption.     

Ideotype Population Exploration: Growth,Photosynthesis, and Yield Components at Different Planting Densities in Winter Oilseed Rape (Brassica napus L.)

Rapeseed is one of the most important edible oil crops in the world and the seed yield has lagged behind the increasing demand driven by population growth. Winter oilseed rape (Brassica napus L.) is widely cultivated with relatively low yield in China, so it is necessary to find the strategies to improve the expression of yield potential. Planting density has great effects on seed yield of crops. Hence, field experiments were conducted in Wuhan in the Yangtze River basin with one conventional variety (Zhongshuang 11, ZS11) and one hybrid variety (Huayouza 9, HYZ9) at five planting densities (27.0×10⁴, 37.5×10⁴, 48.0×10⁴, 58.5×10⁴, 69.0×10⁴ plants ha^–1) during 2010–2012 to investigate the yield components. The physiological traits for high-yield and normal-yield populations were measured during 2011–2013. Our results indicated that planting densities of 58.5×10⁴ plants ha^–1 in ZS11 and 48.0×10⁴ plants ha^–1 in HYZ9 have significantly higher yield compared with the density of 27.0×10⁴ plants ha^–1for both varieties. The ideal silique numbers for ZS11 and HYZ9 were ∼0.9×10⁴ (n m^–2) and ∼1×10⁴ (n m^-2), respectively, and ideal primary branches for ZS11 and HYZ9 were ∼250 (n m^–2) and ∼300 (n m^–2), respectively. The highest leaf area index (LAI) and silique wall area index (SAI) was ∼5.0 and 7.0, respectively. Moreover, higher leaf net photosynthetic rate (Pn) and water use efficiency (WUE) were observed in the high-yield populations. A significantly higher level of silique wall photosynthesis and rapid dry matter accumulation were supposed to result in the maximum seed yield. Our results suggest that increasing the planting density within certain range is a feasible approach for higher seed yield in winter rapeseed in China.     

Plasticity in Vegetative Growth over Contrasted Growing Sites of an F1 Olive Tree Progeny during Its Juvenile Phase

Climatic changes impact fruit tree growth and severely limit their production. Investigating the tree ability to cope with environmental variations is thus necessary to adapt breeding and management strategies in order to ensure sustainable production. In this study, we assessed the genetic parameters and genotype by environment interaction (GxE) during the early tree growth. One hundred and twenty olive seedlings derived from the cross ‘Olivière’ x ‘Arbequina’ were examined across two sites with contrasted environments, accounting for ontogenetic trends over three years. Models including the year of growth, branching order, environment, genotype effects, and their interactions were built with variance function and covariance structure of residuals when necessary. After selection of a model, broad sense heritabilities were estimated. Despite strong environmental effect on most traits, no GxE was found. Moreover, the internal structure of traits co-variation was similar in both sites. Ontogenetic growth variation, related to (i) the overall tree form and (ii) the growth and branching habit at growth unit scale, was not altered by the environment. Finally, a moderate to strong genetic control was identified for traits at the whole tree scale and at internode scale. Among all studied traits, the maximal internode length exhibited the highest heritability (H² = 0.74). Considering the determinant role of this trait in tree architecture and its stability across environments, this study consolidates its relevance for breeding.     

High-throughput root phenotyping screens identify genetic loci associated with root architectural traits in Brassica napus under contrasting phosphate availabilities

Background and Aims

Phosphate (Pi) deficiency in soils is a major limiting factor for crop growth worldwide. Plant growth under low Pi conditions correlates with root architectural traits and it may therefore be possible to select these traits for crop improvement. The aim of this study was to characterize root architectural traits, and to test quantitative trait loci (QTL) associated with these traits, under low Pi (LP) and high Pi (HP) availability in Brassica napus.

Methods

Root architectural traits were characterized in seedlings of a double haploid (DH) mapping population (n = 190) of B. napus [‘Tapidor’ × ‘Ningyou 7’ (TNDH)] using high-throughput phenotyping methods. Primary root length (PRL), lateral root length (LRL), lateral root number (LRN), lateral root density (LRD) and biomass traits were measured 12 d post-germination in agar at LP and HP.

Key Results

In general, root and biomass traits were highly correlated under LP and HP conditions. ‘Ningyou 7’ had greater LRL, LRN and LRD than ‘Tapidor’, at both LP and HP availability, but smaller PRL. A cluster of highly significant QTL for LRN, LRD and biomass traits at LP availability were identified on chromosome A03; QTL for PRL were identified on chromosomes A07 and C06.

Conclusions

High-throughput phenotyping of Brassica can be used to identify root architectural traits which correlate with shoot biomass. It is feasible that these traits could be used in crop improvement strategies. The identification of QTL linked to root traits under LP and HP conditions provides further insights on the genetic basis of plant tolerance to P deficiency, and these QTL warrant further dissection.     

Genetic improvement of peanut (Arachis hypogea L.) genotypes by developing short duration hybrids

Peanut, the only cash crop of rainfed areas of Pakistan, is facing immense challenges due to global warming. Climatic factors particularly the temperature fluctuations and rain pattern shift significantly impact the production and yield of peanut and unavailability of resilient varieties exacerbate this impact. To deal with the cropping pattern change and yield losses, due to climate vagaries, a study was conducted to develop early maturing hybrids using line into tester mating design. The F₁ hybrids from the parental lines were produced in the year 2018 using Line × Tester mating design and then grown in the field in the year 2019 for further evaluation. The hybrids were evaluated based on the early maturity and yield-related attributes in comparison with the parental lines. Based on the general combining ability estimate, line V-3 (Golden), was found as best parent with highly significant values for plant height, days to peg formation, days to maturity, number of pegs per plant, number of pods per plants, number of seeds per plant, 100 pod weight 100 seed weight. Similarly, tester V-7 (PI 635006 01 SD) showed highly significant results of GCA for days to germination, day to 50% flowering, plant height, days to peg formation, days to maturity, number of pegs per plant, number of pods per plants, number of seeds per plant, 100 kernel weight, shelling percentage. All the combinations were evaluated for specific combining ability and significant results were observed for V-3 × V-4 (Golden × PI 619175 01 SD) and V-1 × V-6 (BARI-2000 × PI 564846 01 SD) by developing or maturity and yield-related attributes. The hybrid combinations V-3 × V-5 (Golden × PI 635006 01 SD) followed by V-3 × V-6 showed highly significant results for mid parent heterosis and better parent heterosis for days to 50% flowering, plant height, days to peg formation, number of pegs, days to maturity, number of mature seeds per plant, shelling ratio, 100 pod weight and 100 kernel weight. These parents and hybrid combinations with early maturity genes and high yield attributes can further be used for the development of short duration variety.     

Assessing Gene-Environment Interactions for Common and Rare Variants with Binary Traits Using Gene-Trait Similarity Regression

Accounting for gene–environment (G×E) interactions in complex trait association studies can facilitate our understanding of genetic heterogeneity under different environmental exposures, improve the ability to discover susceptible genes that exhibit little marginal effect, provide insight into the biological mechanisms of complex diseases, help to identify high-risk subgroups in the population, and uncover hidden heritability. However, significant G×E interactions can be difficult to find. The sample sizes required for sufficient power to detect association are much larger than those needed for genetic main effects, and interactions are sensitive to misspecification of the main-effects model. These issues are exacerbated when working with binary phenotypes and rare variants, which bear less information on association. In this work, we present a similarity-based regression method for evaluating G×E interactions for rare variants with binary traits. The proposed model aggregates the genetic and G×E information across markers, using genetic similarity, thus increasing the ability to detect G×E signals. The model has a random effects interpretation, which leads to robustness against main-effect misspecifications when evaluating G×E interactions. We construct score tests to examine G×E interactions and a computationally efficient EM algorithm to estimate the nuisance variance components. Using simulations and data applications, we show that the proposed method is a flexible and powerful tool to study the G×E effect in common or rare variant studies with binary traits.     

Genes Contributing to Pain Sensitivity in the Normal Population: An Exome Sequencing Study

Sensitivity to pain varies considerably between individuals and is known to be heritable. Increased sensitivity to experimental pain is a risk factor for developing chronic pain, a common and debilitating but poorly understood symptom. To understand mechanisms underlying pain sensitivity and to search for rare gene variants (MAF<5%) influencing pain sensitivity, we explored the genetic variation in individuals'' responses to experimental pain. Quantitative sensory testing to heat pain was performed in 2,500 volunteers from TwinsUK (TUK): exome sequencing to a depth of 70× was carried out on DNA from singletons at the high and low ends of the heat pain sensitivity distribution in two separate subsamples. Thus in TUK1, 101 pain-sensitive and 102 pain-insensitive were examined, while in TUK2 there were 114 and 96 individuals respectively. A combination of methods was used to test the association between rare variants and pain sensitivity, and the function of the genes identified was explored using network analysis. Using causal reasoning analysis on the genes with different patterns of SNVs by pain sensitivity status, we observed a significant enrichment of variants in genes of the angiotensin pathway (Bonferroni corrected p = 3.8×10⁻⁴). This pathway is already implicated in animal models and human studies of pain, supporting the notion that it may provide fruitful new targets in pain management. The approach of sequencing extreme exome variation in normal individuals has provided important insights into gene networks mediating pain sensitivity in humans and will be applicable to other common complex traits.     

Response to mass selection when the genotype by environment interaction is modelled as a linear reaction norm

A breeding goal accounting for the effects of genotype by environment interaction (G × E) has to define not only traits but also the environment in which those traits are to be improved. The aim of this study was to predict the selection response in the coefficients of a linear reaction norm, and response in average phenotypic value in any environment, when mass selection is applied to a trait where G × E is modelled as a linear reaction norm. The optimum environment in which to test the selection candidates for a given breeding objective was derived. Optimisation of the selection environment can be used as a means to either maximise genetic progress in a certain response environment, to keep the change in environmental sensitivity at a desired rate, or to reduce the proportion of animals performing below an acceptance level. The results showed that the optimum selection environment is not always equal to the environment in which the response is to be realised, but depends on the degree of G × E (determined by the ratio of variances in slope and level of a linear reaction norm), the correlation between level and slope, and the heritability of the trait.     

Phenotypic evaluation of genetic variability and selection of yield contributing traits in chickpea recombinant inbred line population under high temperature stress

Heat is a major abiotic stress that drastically reduces chickpea yield. This study aimed to identify heat-responsive traits to sustain crop productivity by screening a recombinant inbred line (RILs) population at two locations in India (Ludhiana and Faridkot). The RIL population was derived from an inter-specific cross between heat-tolerant genotype GPF 2 (C. arietinum L.) and heat sensitive accession ILWC 292 (C. reticulatum). The pooled analysis of variance showed highly significant differences for all the traits in RILs and most of the traits were significantly affected by heat stress at both locations. High values of genotypic coefficient of variation (19.52–38.53%), phenotypic coefficient of variation (20.29–39.85%), heritability (92.50–93.90%), and genetic advance as a percentage of mean (38.68–76.74%) have been observed for plant height, number of pods per plant, biomass, yield, and hundred seed weight across the heat stress environments. Association studies and principal component analysis showed a significant positive correlation of plant height, number of pods per plant, biomass, hundred seed weight, harvest index, relative leaf water content, and pollen viability with yield under both timely-sown and late-sown conditions. Path analysis revealed that biomass followed by harvest index was the major contributor to yield among the environments. Both step-wise and multiple regression analyses concluded that number of pods per plant, biomass and harvest index consistently showed high level of contribution to the total variation in yield under both timely-sown and late-sown conditions. Thus, the holistic approach of these analyses illustrated that the promising traits provide a framework for developing heat-tolerant cultivars in chickpea.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12298-021-00977-5.     

Inherited genetic variants associated with glucocorticoid sensitivity in leukaemia cells

Identification of genetic variants associated with glucocorticoids (GC) sensitivity of leukaemia cells may provide insight into potential drug targets and tailored therapy. In the present study, within 72 leukaemic cell lines derived from Japanese patients with B‐cell precursor acute lymphoblastic leukaemia (ALL), we conducted genome‐wide genotyping of single nucleotide polymorphisms (SNP) and attempted to identify genetic variants associated with GC sensitivity and NR3C1 (GC receptor) gene expression. IC50 measures for prednisolone (Pred) and dexamethasone (Dex) were available using an alamarBlue cell viability assay. IC50 values of Pred showed the strongest association with rs904419 (P = 4.34 × 10⁻⁸), located between the FRMD4B and MITF genes. The median IC50 values of prednisolone for cell lines with rs904419 AA (n = 13), AG (n = 31) and GG (n = 28) genotypes were 0.089, 0.139 and 297 µmol/L, respectively. For dexamethasone sensitivity, suggestive association was observed for SNP rs2306888 (P = 1.43 × 10⁻⁶), a synonymous SNP of the TGFBR3 gene. For NR3C1 gene expression, suggestive association was observed for SNP rs11982167 (P = 6.44 × 10⁻⁸), located in the PLEKHA8 gene. These genetic variants may affect GC sensitivity of ALL cells and may give rise to opportunities in personalized medicine for effective and safe chemotherapy in ALL patients.     

Chemical Variation in a Dominant Tree Species: Population Divergence,Selection and Genetic Stability across Environments

Understanding among and within population genetic variation of ecologically important plant traits provides insight into the potential evolutionary processes affecting those traits. The strength and consistency of selection driving variability in traits would be affected by plasticity in differences among genotypes across environments (G×E). We investigated population divergence, selection and environmental plasticity of foliar plant secondary metabolites (PSMs) in a dominant tree species, Eucalyptus globulus. Using two common garden trials we examined variation in PSMs at multiple genetic scales; among 12 populations covering the full geographic range of the species and among up to 60 families within populations. Significant genetic variation in the expression of many PSMs resides both among and within populations of E. globulus with moderate (e.g., sideroxylonal A h²op = 0.24) to high (e.g., macrocarpal G h²op = 0.48) narrow sense heritabilities and high coefficients of additive genetic variation estimated for some compounds. A comparison of Qst and Fst estimates suggest that variability in some of these traits may be due to selection. Importantly, there was no genetic by environment interaction in the expression of any of the quantitative chemical traits despite often significant site effects. These results provide evidence that natural selection has contributed to population divergence in PSMs in E. globulus, and identifies the formylated phloroglucinol compounds (particularly sideroxylonal) and a dominant oil, 1,8-cineole, as candidates for traits whose genetic architecture has been shaped by divergent selection. Additionally, as the genetic differences in these PSMs that influence community phenotypes is stable across environments, the role of plant genotype in structuring communities is strengthened and these genotypic differences may be relatively stable under global environmental changes.     

Plasticity Regulators Modulate Specific Root Traits in Discrete Nitrogen Environments

Plant development is remarkably plastic but how precisely can the plant customize its form to specific environments? When the plant adjusts its development to different environments, related traits can change in a coordinated fashion, such that two traits co-vary across many genotypes. Alternatively, traits can vary independently, such that a change in one trait has little predictive value for the change in a second trait. To characterize such “tunability” in developmental plasticity, we carried out a detailed phenotypic characterization of complex root traits among 96 accessions of the model Arabidopsis thaliana in two nitrogen environments. The results revealed a surprising level of independence in the control of traits to environment – a highly tunable form of plasticity. We mapped genetic architecture of plasticity using genome-wide association studies and further used gene expression analysis to narrow down gene candidates in mapped regions. Mutants in genes implicated by association and expression analysis showed precise defects in the predicted traits in the predicted environment, corroborating the independent control of plasticity traits. The overall results suggest that there is a pool of genetic variability in plants that controls traits in specific environments, with opportunity to tune crop plants to a given environment.