Network analysis identifies ELF3 as a QTL for the shade avoidance response in Arabidopsis

Natural variants of ELF3 affect thermomorphogenesis by transcriptionally modulating PIF4-dependent auxin response genes

BACKGROUND

Perception and transduction of temperature changes result in altered growth enabling plants to adapt to increased ambient temperature. While PHYTOCHROME-INTERACTING FACTOR4 (PIF4) has been identified as a major ambient temperature signaling hub, its upstream regulation seems complex and is poorly understood. Here, we exploited natural variation for thermo-responsive growth in Arabidopsis thaliana using quantitative trait locus (QTL) analysis.

RESULTS

We identified GIRAFFE2.1, a major QTL explaining ~18 % of the phenotypic variation for temperature-induced hypocotyl elongation in the Bay-0 x Sha recombinant inbred line population. Transgenic complementation demonstrated that allelic variation in the circadian clock regulator EARLY FLOWERING3 (ELF3) is underlying this QTL. The source of variation could be allocated to a single nucleotide polymorphism in the ELF3 coding region, resulting in differential expression of PIF4 and its target genes, likely causing the observed natural variation in thermo-responsive growth.

CONCLUSIONS

In combination with other recent studies, this work establishes the role of ELF3 in the ambient temperature signaling network. Natural variation of ELF3-mediated gating of PIF4 expression during nightly growing periods seems to be affected by a coding sequence quantitative trait nucleotide that confers a selective advantage in certain environments. In addition, natural ELF3 alleles seem to differentially integrate temperature and photoperiod information to induce architectural changes. Thus, ELF3 emerges as an essential coordinator of growth and development in response to diverse environmental cues and implicates ELF3 as an important target of adaptation.

Circadian Clock Genes Universally Control Key Agricultural Traits

Circadian clocks are endogenous timers that enable plants to synchronize biological processes with daily and seasonal environmental conditions in order to allocate resources during the most beneficial times of day and year. The circadian clock regulates a number of central plant activities, including growth, development, and reproduction, primarily through controlling a substantial proportion of transcriptional activity and protein function. This review examines the roles that alleles of circadian clock genes have played in domestication and improvement of crop plants. The focus here is on three groups of circadian clock genes essential to clock function in Arabidopsis thaliana: PSEUDO-RESPONSE REGULATORs, GIGANTEA, and the evening complex genes early flowering 3, early flowering 4, and lux arrhythmo. homologous genes from each group underlie quantitative trait loci that have beneficial influences on key agricultural traits, especially flowering time but also yield, biomass, and biennial growth habit. Emerging insights into circadian clock regulation of other fundamental plant processes, including responses to abiotic and biotic stresses, are discussed to highlight promising avenues for further crop improvement.

Quantitative Variation in Responses to Root Spatial Constraint within Arabidopsis thaliana

Among the myriad of environmental stimuli that plants utilize to regulate growth and development to optimize fitness are signals obtained from various sources in the rhizosphere that give an indication of the nutrient status and volume of media available. These signals include chemical signals from other plants, nutrient signals, and thigmotropic interactions that reveal the presence of obstacles to growth. Little is known about the genetics underlying the response of plants to physical constraints present within the rhizosphere. In this study, we show that there is natural variation among Arabidopsis thaliana accessions in their growth response to physical rhizosphere constraints and competition. We mapped growth quantitative trait loci that regulate a positive response of foliar growth to short physical constraints surrounding the root. This is a highly polygenic trait and, using quantitative validation studies, we showed that natural variation in EARLY FLOWERING3 (ELF3) controls the link between root constraint and altered shoot growth. This provides an entry point to study how root and shoot growth are integrated to respond to environmental stimuli.

Plasticity to simulated shade is associated with altitude in structured populations of Arabidopsis thaliana

Plants compete for photosynthesis light and induce a shade avoidance syndrome (SAS) that confers an important advantage in asymmetric competition for light at high canopy densities. Shade plasticity was studied in a greenhouse experiment cultivating Arabidopsis thaliana plants from 15 populations spread across an altitudinal gradient in the northeast area of Spain that contain a high genetic variation into a reduced geographical range. Plants were exposed to sunlight or simulated shade to identify the range of shade plasticity. Fourteen vegetative, flowering and reproductive traits were measured throughout the life cycle. Shade plasticity in flowering time and dry mass was significantly associated with the altitude of population origin. Plants from coastal populations showed higher shade plasticity indexes than those from mountains. The altitudinal variation in flowering leaf plasticity adjusted negatively with average and minimum temperatures, whereas dry mass plasticity was better explained by negative regressions with the average, maximum and minimum temperatures, and by a positive regression with average precipitation of the population origin. The lack of an altitudinal gradient for the widest number of traits suggests that shade light could be a driver explaining the distribution pattern of individuals in smaller geographical scales than those explored here.

Shade avoidance components and pathways in adult plants revealed by phenotypic profiling

Shade from neighboring plants limits light for photosynthesis; as a consequence, plants have a variety of strategies to avoid canopy shade and compete with their neighbors for light. Collectively the response to foliar shade is called the shade avoidance syndrome (SAS). The SAS includes elongation of a variety of organs, acceleration of flowering time, and additional physiological responses, which are seen throughout the plant life cycle. However, current mechanistic knowledge is mainly limited to shade-induced elongation of seedlings. Here we use phenotypic profiling of seedling, leaf, and flowering time traits to untangle complex SAS networks. We used over-representation analysis (ORA) of shade-responsive genes, combined with previous annotation, to logically select 59 known and candidate novel mutants for phenotyping. Our analysis reveals shared and separate pathways for each shade avoidance response. In particular, auxin pathway components were required for shade avoidance responses in hypocotyl, petiole, and flowering time, whereas jasmonic acid pathway components were only required for petiole and flowering time responses. Our phenotypic profiling allowed discovery of seventeen novel shade avoidance mutants. Our results demonstrate that logical selection of mutants increased success of phenotypic profiling to dissect complex traits and discover novel components.

Quantitative trait loci and candidate genes underlying genotype by environment interaction in the response of Arabidopsis thaliana to drought

Drought stress was imposed on two sets of Arabidopsis thaliana genotypes grown in sand under short-day conditions and analysed for several shoot and root growth traits. The response to drought was assessed for quantitative trait locus (QTL) mapping in a genetically diverse set of Arabidopsis accessions using genome-wide association (GWA) mapping, and conventional linkage analysis of a recombinant inbred line (RIL) population. Results showed significant genotype by environment interaction (G×E) for all traits in response to different watering regimes. For the RIL population, the observed G×E was reflected in 17 QTL by environment interactions (Q×E), while 17 additional QTLs were mapped not showing Q×E. GWA mapping identified 58 single nucleotide polymorphism (SNPs) associated with loci displaying Q×E and an additional 16 SNPs associated with loci not showing Q×E. Many candidate genes potentially underlying these loci were suggested. The genes for RPS3C and YLS7 were found to contain conserved amino acid differences when comparing Arabidopsis accessions with strongly contrasting drought response phenotypes, further supporting their candidacy. One of these candidate genes co-located with a QTL mapped in the RIL population.

ELF3 controls thermoresponsive growth in Arabidopsis

Plant development is highly responsive to ambient temperature, and this trait has been linked to the ability of plants to adapt to climate change. The mechanisms by which natural populations modulate their thermoresponsiveness are not known. To address this, we surveyed Arabidopsis accessions for variation in thermal responsiveness of elongation growth and mapped the corresponding loci. We find that the transcriptional regulator EARLY FLOWERING3 (ELF3) controls elongation growth in response to temperature. Through a combination of modeling and experiments, we show that high temperature relieves the gating of growth at night, highlighting the importance of temperature-dependent repressors of growth. ELF3 gating of transcriptional targets responds rapidly and reversibly to changes in temperature. We show that the binding of ELF3 to target promoters is temperature dependent, suggesting a mechanism where temperature directly controls ELF3 activity.

Variation in sulfur and selenium accumulation is controlled by naturally occurring isoforms of the key sulfur assimilation enzyme ADENOSINE 5'-PHOSPHOSULFATE REDUCTASE2 across the Arabidopsis species range

Natural variation allows the investigation of both the fundamental functions of genes and their role in local adaptation. As one of the essential macronutrients, sulfur is vital for plant growth and development and also for crop yield and quality. Selenium and sulfur are assimilated by the same process, and although plants do not require selenium, plant-based selenium is an important source of this essential element for animals. Here, we report the use of linkage mapping in synthetic F2 populations and complementation to investigate the genetic architecture of variation in total leaf sulfur and selenium concentrations in a diverse set of Arabidopsis (Arabidopsis thaliana) accessions. We identify in accessions collected from Sweden and the Czech Republic two variants of the enzyme ADENOSINE 5'-PHOSPHOSULFATE REDUCTASE2 (APR2) with strongly diminished catalytic capacity. APR2 is a key enzyme in both sulfate and selenate reduction, and its reduced activity in the loss-of-function allele apr2-1 and the two Arabidopsis accessions Hodonín and Shahdara leads to a lowering of sulfur flux from sulfate into the reduced sulfur compounds, cysteine and glutathione, and into proteins, concomitant with an increase in the accumulation of sulfate in leaves. We conclude from our observation, and the previously identified weak allele of APR2 from the Shahdara accession collected in Tadjikistan, that the catalytic capacity of APR2 varies by 4 orders of magnitude across the Arabidopsis species range, driving significant differences in sulfur and selenium metabolism. The selective benefit, if any, of this large variation remains to be explored.

Extensive cis-regulatory variation robust to environmental perturbation in Arabidopsis

cis- and trans-acting factors affect gene expression and responses to environmental conditions. However, for most plant systems, we lack a comprehensive map of these factors and their interaction with environmental variation. Here, we examined allele-specific expression (ASE) in an F1 hybrid to study how alleles from two Arabidopsis thaliana accessions affect gene expression. To investigate the effect of the environment, we used drought stress and developed a variance component model to estimate the combined genetic contributions of cis- and trans-regulatory polymorphisms, environmental factors, and their interactions. We quantified ASE for 11,003 genes, identifying 3318 genes with consistent ASE in control and stress conditions, demonstrating that cis-acting genetic effects are essentially robust to changes in the environment. Moreover, we found 1618 genes with genotype x environment (GxE) interactions, mostly cis x E interactions with magnitude changes in ASE. We found fewer trans x E interactions, but these effects were relatively less robust across conditions, showing more changes in the direction of the effect between environments; this confirms that trans-regulation plays an important role in the response to environmental conditions. Our data provide a detailed map of cis- and trans-regulation and GxE interactions in A. thaliana, laying the ground for mechanistic investigations and studies in other plants and environments.

Identification of candidate genes JcARF19 and JcIAA9 associated with seed size traits in Jatropha

Jatropha curcas is a new promising bioenergy crop due to the high oil content in its seeds that can be converted into biodiesel. Seed size, a major determinant of Jatropha oil yield, is a target trait for Jatropha breeding. Due to the vital roles of phytohormone auxin in controlling seed and fruit development, we screened key genes in auxin pathway including ARF and IAA families and downstream effectors to identify candidate genes controlling seed size in Jatropha. As a result, JcARF19 was mapped in the major quantitative trait locus (QTL) region and significantly associated with seed length. By using expression QTL (eQTL) analysis to link variants with functional candidate genes, we provided evidences that seed traits were affected by the interaction of JcARF19 and JcIAA9. ARF19 and IAA9, involved in auxin signal transduction, were conserved in higher plants. These data including the single-nucleotide polymorphisms (SNPs) in the two genes could lead to utilization of the genes by integrating favored alleles into elite varieties through marker-assisted selection.

Natural variation reveals that intracellular distribution of ELF3 protein is associated with function in the circadian clock

Natural selection of variants within the Arabidopsis thaliana circadian clock can be attributed to adaptation to varying environments. To define a basis for such variation, we examined clock speed in a reporter-modified Bay-0 x Shakdara recombinant inbred line and localized heritable variation. Extensive variation led us to identify EARLY FLOWERING3 (ELF3) as a major quantitative trait locus (QTL). The causal nucleotide polymorphism caused a short-period phenotype under light and severely dampened rhythm generation in darkness, and entrainment alterations resulted. We found that ELF3-Sha protein failed to properly localize to the nucleus, and its ability to accumulate in darkness was compromised. Evidence was provided that the ELF3-Sha allele originated in Central Asia. Collectively, we showed that ELF3 protein plays a vital role in defining its light-repressor action in the circadian clock and that its functional abilities are largely dependent on its cellular localization.

DOI:http://dx.doi.org/10.7554/eLife.02206.001

Life on Earth tends to follow a daily rhythm: some animals are awake during the day and asleep at night, whilst others are more active at night, or during the twilight around dawn and dusk. For many living things, these cycles of activity are driven by an internal body clock that helps the organism to adapt to the daily cycle of light and dark—and similar internal clocks also exist in plants.

These internal clocks define daily—or circadian—cycles whereby multiple genes are switched ‘on’ or ‘off’ at different time points in every 24-hr period. And, because light and ambient temperatures also vary with time of the day, many organisms use these external signals as cues to reset their own internal clocks. Moreover, the hours of daylight and temperature vary around the world, and also with the seasons, so plants and animals must be able to change how these external signals influence their internal clocks so that they stay in tune with the day/night cycle. However, it is not clear how they do this.

To explore this question, Anwer et al. grew plants that were from a cross between two types of the model plant Arabidopsis thaliana from different environments: one from Germany, and the other from Tajikistan in Central Asia. These offspring were also genetically engineered so that an enzyme that could give off light was produced under the control of the internal clock. Anwer et al. found that the plants continued to glow and fade with an almost daily rhythm even after external cues, such as changes in temperature or light, had been removed.

Different offspring plants consistently glowed and faded with different rhythms such that some had, for example, a 21-hr day and others a 28-hr day. These differences were caused by many genes that differed from the original German and Tajikistan parent plants, and Anwer et al. ‘mapped’ one of these genetic differences to a single gene. Offspring that inherited a version of a gene called ELF3 from the Tajikistan parent had internal clocks that ran faster when the plant was under the light. These plants also gradually stopped glowing as brightly as the German parent when they were kept in the dark, suggesting that their internal clocks were ‘ticking more softly’. It was already known that the ELF3 gene affected the circadian clock in plants, and Anwer et al. thus concluded that the plants with Tajikistan version of this gene, called ELF3-Sha, were also less able to reset their internal clocks to synchronize in response to external cues.

Anwer et al. also showed that the normal ELF3 protein is more likely to be found in the nucleus of a plant cell than the ELF3-Sha version, which might suggest that this protein is involved in switching genes off. Further research is now needed to uncover exactly how the ELF3 protein does this to keep the plant's internal clock ‘ticking’ correctly.

DOI:http://dx.doi.org/10.7554/eLife.02206.002

Network types and their application in natural variation studies in plants

We are in the age of data-driven biology. Not even a decade after the invention of high-throughput sequencing technologies, there are methods that accurately monitor DNA polymorphisms, transcription profiles, methylation states, transcription factor binding sites, chromatin compactness, nucleosome positions, dynamic histone marks, and so on. We are starting to generate comparable amounts of protein or metabolite data. A key issue is how are we going to make sense of all this information. Network analysis is the most promising method to integrate, query and display large amounts of data for human interpretation. This review shortly summarizes the basic types of networks, their properties and limitations. In addition, I introduce the application of networks to the study of the molecular mechanisms behind natural phenotypic variation.

Inference of allele-specific expression from RNA-seq data

The differential abundance of transcripts from alternative alleles of a gene, for example in a hybrid plant or an outbred natural population, can provide information about the nature of interindividual or interstrain variation in gene expression. Allele-specific expression (ASE) can result from epigenetic phenomena, such as imprinting (when the overexpressed allele is inherited consistently from one parent) or allele-specific chromatin modifications. Alternatively, DNA sequence variants in the promoter or within the transcribed region of a gene can affect the rate of transcription or the rate of decay of the transcript, respectively. The existence of this allelic variation and the insights it provides into the nature of the gene regulation are of significant interest. With the recent widespread availability of sequencing based transcriptomics, the power to detect ASE has increased; however, inference of ASE from transcriptome sequencing data is subject to several caveats and potential biases and the results need to be interpreted with care.

The AT-hook motif-encoding gene METABOLIC NETWORK MODULATOR 1 underlies natural variation in Arabidopsis primary metabolism

Regulation of primary metabolism is a central mechanism by which plants coordinate their various responses to biotic and abiotic challenge. To identify genes responsible for natural variation in primary metabolism, we focused on cloning a locus from Arabidopsis thaliana that influences the level of TCA cycle metabolites in planta. We found that the Met.V.67 locus was controlled by natural variation in METABOLIC NETWORK MODULATOR 1 (MNM1), which encoded an AT-hook motif-containing protein that was unique to the Brassicales lineage. MNM1 had wide ranging effects on plant metabolism and displayed a tissue expression pattern that was suggestive of a function in sink tissues. Natural variation within MNM1 had differential effects during a diurnal time course, and this temporal dependency was supported by analysis of T-DNA insertion and over-expression lines for MNM1. Thus, the cloning of a natural variation locus specifically associated with primary metabolism allowed us to identify MNM1 as a lineage-specific modulator of primary metabolism, suggesting that the regulation of primary metabolism can change during evolution.

Genomics and the Evolution of Phenotypic Traits

Evolutionary genetics has entered an unprecedented era of discovery, catalyzed in large part by the development of technologies that provide information about genome sequence and function. An important benefit is the ability to move beyond a handful of model organisms in lab settings to identify the genetic basis for evolutionarily interesting traits in many organisms in natural settings. Other benefits are the abilities to identify causal mutations and validate their phenotypic consequences more readily and in many more species. Genomic technologies have reinvigorated interest in some of the most fundamental and persistent questions in evolutionary genetics, revealed previously unsuspected evolutionary phenomena, and opened the door to a wide range of new questions.

The receptor-like kinase ERECTA contributes to the shade-avoidance syndrome in a background-dependent manner

BACKGROUND AND AIMS

Plants growing at high densities perceive a decrease in the red to far-red (R/FR) ratio of incoming light. These changes in light quality trigger a suite of responses collectively known as the shade-avoidance syndrome (SAS) including hypocotyl and stem elongation, inhibition of branching and acceleration of flowering.

METHODS

Quantitative trait loci (QTLs) were mapped for hypocotyl length to end-of-day far-red (EOD), a simulated shade-avoidance response, in recombinant inbred line (RIL) populations of Arabidopsis thaliana seedlings, derived from Landsberg erecta (Ler) and three accessions (Columbia, Col; Nossen, No-0; and Cape Verde Islands, Cvi-0).

KEY RESULTS

Five loci were identified as being responsible for the EOD response, with a positive contribution of Ler alleles on the phenotype independently of the RIL population. Quantitative complementation analysis and transgenic lines showed that PHYB is the candidate gene for EODRATIO5 in the Ler × Cvi-0 RIL population, but not for two co-localized QTLs, EODRATIO1 and EODRATIO2 mapped in the Ler × No-0 and Ler × Col RIL populations, respectively. The ERECTA gene was also implicated in the SAS in a background-dependent manner. For hypocotyl length EOD response, a positive contribution of erecta alleles was found in Col and Van-0, but not in Ler, Cvi-0, Hir-1 or Ws. Furthermore, pleiotropic effects of ERECTA in the EOD response were also detected for petiole and lamina elongation, hyponastic growth, and flowering time.

CONCLUSIONS

The results show that the analysis of multiple mapping populations leads to a better understanding of the SAS genetic architecture. Moreover, the background- and trait-dependent contribution of ERECTA in the SAS suggest that its function in shaded natural environments may be relevant for some populations in different phases of plant development. It is proposed that ERECTA is involved in canalization processes buffering the genetic variation of the SAS against environmental light fluctuations.

Molecular mechanisms of robustness in plants

Robustness, the ability of organisms to buffer phenotypes against perturbations, has drawn renewed interest among developmental biologists and geneticists. A growing body of research supports an important role of robustness in the genotype to phenotype translation, with far-reaching implications for evolutionary processes and disease susceptibility. Similar to animals and fungi, plant robustness is a function of genetic network architecture. Most perturbations are buffered; however, perturbation of network hubs destabilizes many traits. Here, we review recent advances in identifying molecular robustness mechanisms in plants that have been enabled by a combination of classical genetics and population genetics with genome-scale data.

The flowering repressor SVP underlies a novel Arabidopsis thaliana QTL interacting with the genetic background

The timing of flowering initiation is a fundamental trait for the adaptation of annual plants to different environments. Large amounts of intraspecific quantitative variation have been described for it among natural accessions of many species, but the molecular and evolutionary mechanisms underlying this genetic variation are mainly being determined in the model plant Arabidopsis thaliana. To find novel A. thaliana flowering QTL, we developed introgression lines from the Japanese accession Fuk, which was selected based on the substantial transgression observed in an F₂ population with the reference strain Ler. Analysis of an early flowering line carrying a single Fuk introgression identified Flowering Arabidopsis QTL1 (FAQ1). We fine-mapped FAQ1 in an 11 kb genomic region containing the MADS transcription factor gene SHORT VEGETATIVE PHASE (SVP). Complementation of the early flowering phenotype of FAQ1-Fuk with a SVP-Ler transgen demonstrated that FAQ1 is SVP. We further proved by directed mutagenesis and transgenesis that a single amino acid substitution in SVP causes the loss-of-function and early flowering of Fuk allele. Analysis of a worldwide collection of accessions detected FAQ1/SVP-Fuk allele only in Asia, with the highest frequency appearing in Japan, where we could also detect a potential ancestral genotype of FAQ1/SVP-Fuk. In addition, we evaluated allelic and epistatic interactions of SVP natural alleles by analysing more than one hundred transgenic lines carrying Ler or Fuk SVP alleles in five genetic backgrounds. Quantitative analyses of these lines showed that FAQ1/SVP effects vary from large to small depending on the genetic background. These results support that the flowering repressor SVP has been recently selected in A. thaliana as a target for early flowering, and evidence the relevance of genetic interactions for the intraspecific evolution of FAQ1/SVP and flowering time.

In many plant species, the timing of flowering initiation shows abundant quantitative variation among natural varieties, which reflects the importance of this trait for adaptation to different environments. Currently, a major goal in plant biology is to determine the molecular and evolutionary bases of this natural genetic variation. In this study we demonstrate that the central flowering regulator SHORT VEGETATIVE PHASE (SVP), encoding a MADS transcription factor, is involved in the flowering natural variation of the model organism Arabidopsis thaliana. In particular, we prove that a structural change caused by a single amino acid substitution generates a SVP early flowering allele that is distributed only in Asia. Furthermore, genetic interactions have been shown to be a component of the natural variation for many important adaptive traits. However, very few studies, either in animals or plants, have systematically addressed the extent of genetic interactions among specific alleles responsible for the natural variation of complex traits. Our study shows that the flowering effects of SVP natural alleles depend significantly on the genetic background; and, subsequently, we demonstrate the relevance of epistasis for the evolution of this crucial transcription factor and flowering time.

Genetical Genomics Reveals Large Scale Genotype-By-Environment Interactions in Arabidopsis thaliana

One of the major goals of quantitative genetics is to unravel the complex interactions between molecular genetic factors and the environment. The effects of these genotype-by-environment interactions also affect and cause variation in gene expression. The regulatory loci responsible for this variation can be found by genetical genomics that involves the mapping of quantitative trait loci (QTLs) for gene expression traits also called expression-QTL (eQTLs). Most genetical genomics experiments published so far, are performed in a single environment and hence do not allow investigation of the role of genotype-by-environment interactions. Furthermore, most studies have been done in a steady state environment leading to acclimated expression patterns. However a response to the environment or change therein can be highly plastic and possibly lead to more and larger differences between genotypes. Here we present a genetical genomics study on 120 Arabidopsis thaliana, Landsberg erecta × Cape Verde Islands, recombinant inbred lines (RILs) in active response to the environment by treating them with 3 h of shade. The results of this experiment are compared to a previous study on seedlings of the same RILs from a steady state environment. The combination of two highly different conditions but exactly the same RILs with a fixed genetic variation showed the large role of genotype-by-environment interactions on gene expression levels. We found environment-dependent hotspots of transcript regulation. The major hotspot was confirmed by the expression profile of a near isogenic line. Our combined analysis leads us to propose CSN5A, a COP9 signalosome component, as a candidate regulator for the gene expression response to shade.

LASSO modeling of the Arabidopsis thaliana seed/seedling transcriptome: a model case for detection of novel mucilage and pectin metabolism genes

Whole genome transcript correlation-based approaches have been shown to be enormously useful for candidate gene detection. Consequently, simple Pearson correlation has been widely applied in several web based tools. That said, several more sophisticated methods based on e.g. mutual information or Bayesian network inference have been developed and have been shown to be theoretically superior but are not yet commonly applied. Here, we propose the application of a recently developed statistical regression technique, the LASSO, to detect novel candidates from high throughput transcriptomic datasets. We apply the LASSO to a tissue specific dataset in the model plant Arabidopsis thaliana to identify novel players in Arabidopsis thaliana seed coat mucilage synthesis. We built LASSO models based on a list of genes known to be involved in a sub-pathway of Arabidopsis mucilage synthesis. After identifying a putative transcription factor, we verified its involvement in mucilage synthesis by obtaining knock-out mutants for this gene. We show that a loss of function of this putative transcription factor leads to a significant decrease in mucilage pectin.

A conserved molecular basis for photoperiod adaptation in two temperate legumes

Legumes were among the first plant species to be domesticated, and accompanied cereals in expansion of agriculture from the Fertile Crescent into diverse environments across the Mediterranean basin, Europe, Central Asia, and the Indian subcontinent. Although several recent studies have outlined the molecular basis for domestication and eco-geographic adaptation in the two main cereals from this region, wheat and barley, similar questions remain largely unexplored in their legume counterparts. Here we identify two major loci controlling differences in photoperiod response between wild and domesticated pea, and show that one of these, high response to photoperiod (HR), is an ortholog of early flowering 3 (ELF3), a gene involved in circadian clock function. We found that a significant proportion of flowering time variation in global pea germplasm is controlled by HR, with a single, widespread functional variant conferring altered circadian rhythms and the reduced photoperiod response associated with the spring habit. We also present evidence that ELF3 has a similar role in lentil, another major legume crop, with a distinct functional variant contributing to reduced photoperiod response in cultivars widely deployed in short-season environments. Our results identify the factor likely to have permitted the successful prehistoric expansion of legume cultivation to Northern Europe, and define a conserved genetic basis for major adaptive changes in flowering phenology and growth habit in an important crop group.

Arabidopsis COP1 and SPA genes are essential for plant elongation but not for acceleration of flowering time in response to a low red light to far-red light ratio

Plants sense vegetative shade as a reduction in the ratio of red light to far-red light (R:FR). Arabidopsis (Arabidopsis thaliana) responds to a reduced R:FR with increased elongation of the hypocotyl and the leaf petioles as well as with an acceleration of flowering time. The repressor of light signaling, CONSTITUTIVELY PHOTOMORPHOGENIC1 (COP1), has been shown previously to be essential for the shade-avoidance response in seedlings. Here, we have investigated the roles of COP1 and the COP1-interacting SUPPRESSOR OF PHYA-105 (SPA) proteins in seedling and adult facets of the shade-avoidance response. We show that COP1 and the four SPA genes are essential for hypocotyl and leaf petiole elongation in response to low R:FR, in a fashion that involves the COP1/SPA ubiquitination target LONG HYPOCOTYL IN FR LIGHT1 but not ELONGATED HYPOCOTYL5. In contrast, the acceleration of flowering in response to a low R:FR was normal in cop1 and spa mutants, thus demonstrating that the COP1/SPA complex is only required for elongation responses to vegetative shade and not for shade-induced early flowering. We further show that spa mutant seedlings fail to exhibit an increase in the transcript levels of the auxin biosynthesis genes YUCCA2 (YUC2), YUC8, and YUC9 in response to low R:FR, suggesting that an increase in auxin biosynthesis in vegetative shade requires SPA function. Consistent with this finding, expression of the auxin-response marker gene DR5::GUS did not increase in spa mutant seedlings exposed to low R:FR. We propose that COP1/SPA activity, via LONG HYPOCOTYL IN FR LIGHT1, is required for shade-induced modulation of the auxin biosynthesis pathway and thereby enhances cell elongation in low R:FR.

Background-dependent effects of polyglutamine variation in the Arabidopsis thaliana gene ELF3

Tandem repeats (TRs) have extremely high mutation rates and are often considered to be neutrally evolving DNA. However, in coding regions, TR copy number mutations can significantly affect phenotype and may facilitate rapid adaptation to new environments. In several human genes, TR copy number mutations that expand polyglutamine (polyQ) tracts beyond a certain threshold cause incurable neurodegenerative diseases. PolyQ-containing proteins exist at a considerable frequency in eukaryotes, yet the phenotypic consequences of natural variation in polyQ tracts that are not associated with disease remain largely unknown. Here, we use Arabidopsis thaliana to dissect the phenotypic consequences of natural variation in the polyQ tract encoded by EARLY FLOWERING 3 (ELF3), a key developmental gene. Changing ELF3 polyQ tract length affected complex ELF3-dependent phenotypes in a striking and nonlinear manner. Some natural ELF3 polyQ variants phenocopied elf3 loss-of-function mutants in a common reference background, although they are functional in their native genetic backgrounds. To test the existence of background-specific modifiers, we compared the phenotypic effects of ELF3 polyQ variants between two divergent backgrounds, Col and Ws, and found dramatic differences. In fact, the Col-ELF3 allele, encoding the shortest known ELF3 polyQ tract, was haploinsufficient in Ws × Col F(1) hybrids. Our data support a model in which variable polyQ tracts drive adaptation to internal genetic environments.

Towards understanding how molecular networks evolve in plants

Residing beneath the phenotypic landscape of a plant are intricate and dynamic networks of genes and proteins. As evolution operates on phenotypes, we expect its forces to shape somehow these underlying molecular networks. In this review, we discuss progress being made to elucidate the nature of these forces and their impact on the composition and structure of molecular networks. We also outline current limitations and open questions facing the broader field of plant network analysis.

A genome-wide association study identifies variants underlying the Arabidopsis thaliana shade avoidance response

Shade avoidance is an ecologically and molecularly well-understood set of plant developmental responses that occur when the ratio of red to far-red light (R∶FR) is reduced as a result of foliar shade. Here, a genome-wide association study (GWAS) in Arabidopsis thaliana was used to identify variants underlying one of these responses: increased hypocotyl elongation. Four hypocotyl phenotypes were included in the study, including height in high R∶FR conditions (simulated sun), height in low R∶FR conditions (simulated shade), and two different indices of the response of height to low R∶FR. GWAS results showed that variation in these traits is controlled by many loci of small to moderate effect. A known PHYC variant contributing to hypocotyl height variation was identified and lists of significantly associated genes were enriched in a priori candidates, suggesting that this GWAS was capable of generating meaningful results. Using metadata such as expression data, GO terms, and other annotation, we were also able to identify variants in candidate de novo genes. Patterns of significance among our four phenotypes allowed us to categorize associations into three groups: those that affected hypocotyl height without influencing shade avoidance, those that affected shade avoidance in a height-dependent fashion, and those that exerted specific control over shade avoidance. This grouping allowed for the development of explicit hypotheses about the genetics underlying shade avoidance variation. Additionally, the response to shade did not exhibit any marked geographic distribution, suggesting that variation in low R∶FR–induced hypocotyl elongation may represent a response to local conditions.

The goal of this work was to identify genetic variants underlying a well-characterized environmental response, the elongation of Arabidopsis thaliana hypocotyls (seedling stems) in response to shade, otherwise known as shade avoidance. We performed a genome-wide association study with four phenotypes: absolute hypocotyl height of plants grown in both simulated sun and shade and two measures of how height responded to shade. With this study, we confirmed previous findings that variants in two photoreceptors were associated with hypocotyl height variation. We also found associations with genetic variants in previously-identified shade avoidance genes, as well as with variants in genes not typically considered part of the shade avoidance pathway. By examining patterns of which of the four phenotypes were associated with each gene, we were then able to discriminate between genetic variants that have a general role in hypocotyl height variation and variants that are specifically involved in the shade avoidance response. We also found that shade avoidance was not broadly associated with geography, suggesting that variation in this trait may be due to local differences in light quality.

Model Misinterpretation within Biology: Phenotypes, Statistics, Networks, and Inference

Models of myriad forms are rapidly becoming central to biology. These range from statistical models that are fundamental to the interpretation of experimental results to ordinary differential equation models that attempt to describe the results in a mechanistic format. Models will be more and more essential to biologists but this growing importance requires all model users to become more sophisticated about what is in a model and how that limits the usability of the model. This review attempts to relay the potential pitfalls that can lie within a model.

Exploring the shallow end; estimating information content in transcriptomics studies

Transcriptomics is a major platform to study organismal biology. The advent of new parallel sequencing technologies has opened up a new avenue of transcriptomics with ever deeper and deeper sequencing to identify and quantify each and every transcript in a sample. However, this may not be the best usage of the parallel sequencing technology for all transcriptomics experiments. I utilized the Shannon Entropy approach to estimate the information contained within a transcriptomics experiment and tested the ability of shallow RNAseq to capture the majority of this information. This analysis showed that it was possible to capture nearly all of the network or genomic information present in a variety of transcriptomics experiments using a subset of the most abundant 5000 transcripts or less within any given sample. Thus, it appears that it should be possible and affordable to conduct large scale factorial analysis with a high degree of replication using parallel sequencing technologies.

Shade avoidance

The presence of neighboring vegetation modifies the light environment experienced by plants, generating signals that are perceived by phytochromes and cryptochromes. These signals cause large changes in plant body form and function, including enhanced growth of the hypocotyl and petioles, a more erect position of the leaves and early flowering in Arabidopsis thaliana. Collectively, these so-called shade-avoidance responses tend to reduce the degree of current or future shade by neighbors. Shade light signals increase the abundance of PHYTOCHROME INTERACTING FACTOR 4 (PIF4) and PIF5 proteins, promote the synthesis and redirection of auxin, favor the degradation of DELLA proteins and increase the expression of auxin, gibberellins and brassinosteroid-promoted genes, among other events downstream the photoreceptors. Selectively disrupting these events by genetic or pharmacological approaches affects shade-avoidance responses with an intensity that depends on the developmental context and the environment. Shade-avoidance responses provide a model to investigate the signaling networks used by plants to take advantage of the cues provided by the environment to adjust to the challenges imposed by the environment itself.

Next generation quantitative genetics in plants

Most characteristics in living organisms show continuous variation, which suggests that they are controlled by multiple genes. Quantitative trait loci (QTL) analysis can identify the genes underlying continuous traits by establishing associations between genetic markers and observed phenotypic variation in a segregating population. The new high-throughput sequencing (HTS) technologies greatly facilitate QTL analysis by providing genetic markers at genome-wide resolution in any species without previous knowledge of its genome. In addition HTS serves to quantify molecular phenotypes, which aids to identify the loci responsible for QTLs and to understand the mechanisms underlying diversity. The constant improvements in price, experimental protocols, computational pipelines, and statistical frameworks are making feasible the use of HTS for any research group interested in quantitative genetics. In this review I discuss the application of HTS for molecular marker discovery, population genotyping, and expression profiling in QTL analysis.

Genomic analysis of QTLs and genes altering natural variation in stochastic noise

Quantitative genetic analysis has long been used to study how natural variation of genotype can influence an organism's phenotype. While most studies have focused on genetic determinants of phenotypic average, it is rapidly becoming understood that stochastic noise is genetically determined. However, it is not known how many traits display genetic control of stochastic noise nor how broadly these stochastic loci are distributed within the genome. Understanding these questions is critical to our understanding of quantitative traits and how they relate to the underlying causal loci, especially since stochastic noise may be directly influenced by underlying changes in the wiring of regulatory networks. We identified QTLs controlling natural variation in stochastic noise of glucosinolates, plant defense metabolites, as well as QTLs for stochastic noise of related transcripts. These loci included stochastic noise QTLs unique for either transcript or metabolite variation. Validation of these loci showed that genetic polymorphism within the regulatory network alters stochastic noise independent of effects on corresponding average levels. We examined this phenomenon more globally, using transcriptomic datasets, and found that the Arabidopsis transcriptome exhibits significant, heritable differences in stochastic noise. Further analysis allowed us to identify QTLs that control genomic stochastic noise. Some genomic QTL were in common with those altering average transcript abundance, while others were unique to stochastic noise. Using a single isogenic population, we confirmed that natural variation at ELF3 alters stochastic noise in the circadian clock and metabolism. Since polymorphisms controlling stochastic noise in genomic phenotypes exist within wild germplasm for naturally selected phenotypes, this suggests that analysis of Arabidopsis evolution should account for genetic control of stochastic variance and average phenotypes. It remains to be determined if natural genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes.

Plant adaptation to dynamically changing environment: the shade avoidance response

The success of competitive interactions between plants determines the chance of survival of individuals and eventually of whole plant species. Shade-tolerant plants have adapted their photosynthesis to function optimally under low-light conditions. These plants are therefore capable of long-term survival under a canopy shade. In contrast, shade-avoiding plants adapt their growth to perceive maximum sunlight and therefore rapidly dominate gaps in a canopy. Daylight contains roughly equal proportions of red and far-red light, but within vegetation that ratio is lowered as a result of red absorption by photosynthetic pigments. This light quality change is perceived through the phytochrome system as an unambiguous signal of the proximity of neighbors resulting in a suite of developmental responses (termed the shade avoidance response) that, when successful, result in the overgrowth of those neighbors. Shoot elongation induced by low red/far-red light may confer high relative fitness in natural dense communities. However, since elongation is often achieved at the expense of leaf and root growth, shade avoidance may lead to reduction in crop plant productivity. Over the past decade, major progresses have been achieved in the understanding of the molecular basis of shade avoidance. However, uncovering the mechanisms underpinning plant response and adaptation to changes in the ratio of red to far-red light is key to design new strategies to precise modulate shade avoidance in time and space without impairing the overall crop ability to compete for light.

Environmental memory from a circadian oscillator: the Arabidopsis thaliana clock differentially integrates perception of photic vs. thermal entrainment

The constraint of a rotating earth has led to the evolution of a circadian clock that drives anticipation of future environmental changes. During this daily rotation, the circadian clock of Arabidopsis thaliana (Arabidopsis) intersects with the diurnal environment to orchestrate virtually all transcriptional processes of the plant cell, presumably by detecting, interpreting, and anticipating the environmental alternations of light and temperature. To comparatively assess differential inputs toward phenotypic and physiological responses on a circadian parameter, we surveyed clock periodicity in a recombinant inbred population modified to allow for robust periodicity measurements after entrainment to respective photic vs. thermal cues, termed zeitgebers. Lines previously thermally entrained generally displayed reduced period length compared to those previously photically entrained. This differential zeitgeber response was also detected in a set of diverse Arabidopsis accessions. Thus, the zeitgebers of the preceding environment direct future behavior of the circadian oscillator. Allelic variation at quantitative trait loci generated significant differences in zeitgeber responses in the segregating population. These were important for periodicity variation dependent on the nature of the subsequent entrainment source. Collectively, our results provide a genetic paradigm for the basis of environmental memory of a preceding environment, which leads to the integrated coordination of circadian periodicity.

Combining genome-wide association mapping and transcriptional networks to identify novel genes controlling glucosinolates in Arabidopsis thaliana

BACKGROUND

Genome-wide association (GWA) is gaining popularity as a means to study the architecture of complex quantitative traits, partially due to the improvement of high-throughput low-cost genotyping and phenotyping technologies. Glucosinolate (GSL) secondary metabolites within Arabidopsis spp. can serve as a model system to understand the genomic architecture of adaptive quantitative traits. GSL are key anti-herbivory defenses that impart adaptive advantages within field trials. While little is known about how variation in the external or internal environment of an organism may influence the efficiency of GWA, GSL variation is known to be highly dependent upon the external stresses and developmental processes of the plant lending it to be an excellent model for studying conditional GWA.

METHODOLOGY/PRINCIPAL FINDINGS

To understand how development and environment can influence GWA, we conducted a study using 96 Arabidopsis thaliana accessions, >40 GSL phenotypes across three conditions (one developmental comparison and one environmental comparison) and ∼230,000 SNPs. Developmental stage had dramatic effects on the outcome of GWA, with each stage identifying different loci associated with GSL traits. Further, while the molecular bases of numerous quantitative trait loci (QTL) controlling GSL traits have been identified, there is currently no estimate of how many additional genes may control natural variation in these traits. We developed a novel co-expression network approach to prioritize the thousands of GWA candidates and successfully validated a large number of these genes as influencing GSL accumulation within A. thaliana using single gene isogenic lines.

CONCLUSIONS/SIGNIFICANCE

Together, these results suggest that complex traits imparting environmentally contingent adaptive advantages are likely influenced by up to thousands of loci that are sensitive to fluctuations in the environment or developmental state of the organism. Additionally, while GWA is highly conditional upon genetics, the use of additional genomic information can rapidly identify causal loci en masse.

Network quantitative trait loci mapping of circadian clock outputs identifies metabolic pathway-to-clock linkages in Arabidopsis

Modern systems biology permits the study of complex networks, such as circadian clocks, and the use of complex methodologies, such as quantitative genetics. However, it is difficult to combine these approaches due to factorial expansion in experiments when networks are examined using complex methods. We developed a genomic quantitative genetic approach to overcome this problem, allowing us to examine the function(s) of the plant circadian clock in different populations derived from natural accessions. Using existing microarray data, we defined 24 circadian time phase groups (i.e., groups of genes with peak phases of expression at particular times of day). These groups were used to examine natural variation in circadian clock function using existing single time point microarray experiments from a recombinant inbred line population. We identified naturally variable loci that altered circadian clock outputs and linked these circadian quantitative trait loci to preexisting metabolomics quantitative trait loci, thereby identifying possible links between clock function and metabolism. Using single-gene isogenic lines, we found that circadian clock output was altered by natural variation in Arabidopsis thaliana secondary metabolism. Specifically, genetic manipulation of a secondary metabolic enzyme led to altered free-running rhythms. This represents a unique and valuable approach to the study of complex networks using quantitative genetics.

Arabidopsis paves the way: genomic and network analyses in crops

Arabidopsis genomic and network analyses have facilitated crop research towards the understanding of many biological processes of fundamental importance for agriculture. Genes that were identified through genomic analyses in Arabidopsis have been used to manipulate crop traits such as pathogen resistance, yield, water-use efficiency, and drought tolerance, with the effects being tested in field conditions. The integration of diverse Arabidopsis genome-wide datasets in probabilistic functional networks has been demonstrated as a feasible strategy to associate novel genes with traits of interest, and novel genomic methods continue to be developed. The combination of genome-wide location studies, using ChIP-Seq, with gene expression profiling data is affording a genome-wide view of regulatory networks previously delineated through genetic and molecular analyses, leading to the identification of novel components and of new connections within these networks.