Enhanced recombination empowers the detection and mapping of Quantitative Trait Loci.

Modern plant breeding, such as genomic selection and gene editing, is based on the knowledge of the genetic architecture of desired traits. Quantitative trait loci (QTL) analysis, which combines high throughput phenotyping and genotyping of segregating populations, is a powerful tool to identify these genetic determinants and to decipher the underlying mechanisms. However, meiotic recombination, which shuffles genetic information between generations, is limited: Typically only one to two exchange points, called crossovers, occur between a pair of homologous chromosomes. Here we test the effect on QTL analysis of boosting recombination, by mutating the anti-crossover factors RECQ4 and FIGL1 in Arabidopsis thaliana full hybrids and lines in which a single chromosome is hybrid. We show that increasing recombination ~6-fold empowers the detection and resolution of QTLs, reaching the gene scale with only a few hundred plants. Further, enhanced recombination unmasks some secondary QTLs undetected under normal recombination. These results show the benefits of enhanced recombination to decipher the genetic bases of traits.

Natural variation in response to combined water and nitrogen deficiencies in Arabidopsis.

Understanding plant responses to individual stresses does not mean that we understand real world situations, where stresses usually combine and interact. These interactions arise at different levels, from stress exposure to the molecular networks of the stress response. Here, we built an in-depth multi-omics description of plant responses to mild water (W) and nitrogen (N) limitations, either individually or combined, among five genetically different Arabidopsis (Arabidopsis thaliana) accessions. We highlight the different dynamics in stress response through integrative traits such as rosette growth and the physiological status of the plants. We also used transcriptomics and metabolomics profiling during a stage when the plant response was stabilized to determine the wide diversity in stress-induced changes among accessions, highlighting the limited reality of a 'universal' stress response. The main effect of the WxN interaction was an attenuation of the N-deficiency syndrome when combined with mild drought, but to a variable extent depending on the accession. Other traits subject to WxN interactions are often accession-specific. Multi-omics analyses identified a subset of transcript-metabolite clusters that are critical to stress responses but essentially variable according to the genotype factor. Including intra-specific diversity in our descriptions of plant stress response places our findings in perspective.

Resource allocation modeling for autonomous prediction of plant cell phenotypes.

Predicting the plant cell response in complex environmental conditions is a challenge in plant biology. Here we developed a resource allocation model of cellular and molecular scale for the leaf photosynthetic cell of Arabidopsis thaliana, based on the Resource Balance Analysis (RBA) constraint-based modeling framework. The RBA model contains the metabolic network and the major macromolecular processes involved in the plant cell growth and survival and localized in cellular compartments. We simulated the model for varying environmental conditions of temperature, irradiance, partial pressure of CO2 and O2, and compared RBA predictions to known resource distributions and quantitative phenotypic traits such as the relative growth rate, the C:N ratio, and finally to the empirical characteristics of CO2 fixation given by the well-established Farquhar model. In comparison to other standard constraint-based modeling methods like Flux Balance Analysis, the RBA model makes accurate quantitative predictions without the need for empirical constraints. Altogether, we show that RBA significantly improves the autonomous prediction of plant cell phenotypes in complex environmental conditions, and provides mechanistic links between the genotype and the phenotype of the plant cell.

Protein kinase SnRK2.4 is a key regulator of aquaporins and root hydraulics in Arabidopsis.

Soil water uptake by roots is a key component of plant water homeostasis contributing to plant growth and survival under ever-changing environmental conditions. The water transport capacity of roots (root hydraulic conductivity; Lpr ) is mostly contributed by finely regulated Plasma membrane Intrinsic Protein (PIP) aquaporins. In this study, we used natural variation of Arabidopsis for the identification of quantitative trait loci (QTLs) contributing to Lpr . Using recombinant lines from a biparental cross (Cvi-0 x Col-0), we show that the gene encoding class 2 Sucrose-Non-Fermenting Protein kinase 2.4 (SnRK2.4) in Col-0 contributes to >30% of Lpr by enhancing aquaporin-dependent water transport. At variance with the inactive and possibly unstable Cvi-0 SnRK2.4 form, the Col-0 form interacts with and phosphorylates the prototypal PIP2;1 aquaporin at Ser121 and stimulates its water transport activity upon coexpression in Xenopus oocytes and yeast cells. Activation of PIP2;1 by Col-0 SnRK2.4 in yeast also requires its protein kinase activity and can be counteracted by clade A Protein Phosphatases 2C. SnRK2.4 shows all hallmarks to be part of core abscisic acid (ABA) signaling modules. Yet, long-term (>3 h) inhibition of Lpr by ABA possibly involves a SnRK2.4-independent inhibition of PIP2;1. SnRK2.4 also promotes stomatal aperture and ABA-induced inhibition of primary root growth. The study identifies a key component of Lpr and sheds new light on the functional overlap and specificity of SnRK2.4 with respect to other ABA-dependent or independent SnRK2s.

DiffSegR: an RNA-seq data driven method for differential expression analysis using changepoint detection.

To fully understand gene regulation, it is necessary to have a thorough understanding of both the transcriptome and the enzymatic and RNA-binding activities that shape it. While many RNA-Seq-based tools have been developed to analyze the transcriptome, most only consider the abundance of sequencing reads along annotated patterns (such as genes). These annotations are typically incomplete, leading to errors in the differential expression analysis. To address this issue, we present DiffSegR - an R package that enables the discovery of transcriptome-wide expression differences between two biological conditions using RNA-Seq data. DiffSegR does not require prior annotation and uses a multiple changepoints detection algorithm to identify the boundaries of differentially expressed regions in the per-base log2 fold change. In a few minutes of computation, DiffSegR could rightfully predict the role of chloroplast ribonuclease Mini-III in rRNA maturation and chloroplast ribonuclease PNPase in (3'/5')-degradation of rRNA, mRNA and tRNA precursors as well as intron accumulation. We believe DiffSegR will benefit biologists working on transcriptomics as it allows access to information from a layer of the transcriptome overlooked by the classical differential expression analysis pipelines widely used today. DiffSegR is available at https://aliehrmann.github.io/DiffSegR/index.html.

Genomic Basis of Adaptation to a Novel Precipitation Regime.

Energy production and metabolism are intimately linked to ecological and environmental constraints across the tree of life. In plants, which depend on sunlight to produce energy, the link between primary metabolism and the environment is especially strong. By governing CO2 uptake for photosynthesis and transpiration, leaf pores, or stomata, couple energy metabolism to the environment and determine productivity and water-use efficiency (WUE). Although evolution is known to tune physiological traits to the local environment, we lack knowledge of the specific links between molecular and evolutionary mechanisms that shape this process in nature. Here, we investigate the evolution of stomatal conductance and WUE in an Arabidopsis population that colonized an island with a montane cloud scrubland ecosystem characterized by seasonal drought and fog-based precipitation. We find that stomatal conductance increases and WUE decreases in the colonizing population relative to its closest outgroup population from temperate North Africa. Genome-wide association mapping reveals a polygenic basis of trait variation, with a substantial contribution from a nonsynonymous single-nucleotide polymorphism in MAP KINASE 12 (MPK12 G53R), which explains 35% of the phenotypic variance in WUE in the island population. We reconstruct the spatially explicit evolutionary history of MPK12 53R on the island and find that this allele increased in frequency in the population due to positive selection as Arabidopsis expanded into the harsher regions of the island. Overall, these findings show how adaptation shaped quantitative eco-physiological traits in a new precipitation regime defined by low rainfall and high humidity.

Genetic and environmental modulation of transposition shapes the evolutionary potential of Arabidopsis thaliana.

BACKGROUND: How species can adapt to abrupt environmental changes, particularly in the absence of standing genetic variation, is poorly understood and a pressing question in the face of ongoing climate change. Here we leverage publicly available multi-omic and bio-climatic data for more than 1000 wild Arabidopsis thaliana accessions to determine the rate of transposable element (TE) mobilization and its potential to create adaptive variation in natural settings. RESULTS: We demonstrate that TE insertions arise at almost the same rate as base substitutions. Mobilization activity of individual TE families varies greatly between accessions, in association with genetic and environmental factors as well as through complex gene-environment interactions. Although the distribution of TE insertions across the genome is ultimately shaped by purifying selection, reflecting their typically strong deleterious effects when located near or within genes, numerous recent TE-containing alleles show signatures of positive selection. Moreover, high rates of transposition appear positively selected at the edge of the species' ecological niche. Based on these findings, we predict through mathematical modeling higher transposition activity in Mediterranean regions within the next decades in response to global warming, which in turn should accelerate the creation of large-effect alleles. CONCLUSIONS: Our study reveals that TE mobilization is a major generator of genetic variation in A. thaliana that is finely modulated by genetic and environmental factors. These findings and modeling indicate that TEs may be essential genomic players in the demise or rescue of native populations in times of climate crises.

The Evolutionary Dynamics of Genetic Incompatibilities Introduced by Duplicated Genes in Arabidopsis thaliana.

Although gene duplications provide genetic backup and allow genomic changes under relaxed selection, they may potentially limit gene flow. When different copies of a duplicated gene are pseudofunctionalized in different genotypes, genetic incompatibilities can arise in their hybrid offspring. Although such cases have been reported after manual crosses, it remains unclear whether they occur in nature and how they affect natural populations. Here, we identified four duplicated-gene based incompatibilities including one previously not reported within an artificial Arabidopsis intercross population. Unexpectedly, however, for each of the genetic incompatibilities we also identified the incompatible alleles in natural populations based on the genomes of 1,135 Arabidopsis accessions published by the 1001 Genomes Project. Using the presence of incompatible allele combinations as phenotypes for GWAS, we mapped genomic regions that included additional gene copies which likely rescue the genetic incompatibility. Reconstructing the geographic origins and evolutionary trajectories of the individual alleles suggested that incompatible alleles frequently coexist, even in geographically closed regions, and that their effects can be overcome by additional gene copies collectively shaping the evolutionary dynamics of duplicated genes during population history.

Natural variation at FLM splicing has pleiotropic effects modulating ecological strategies in Arabidopsis thaliana.

Investigating the evolution of complex phenotypes and the underlying molecular bases of their variation is critical to understand how organisms adapt to their environment. Applying classical quantitative genetics on a segregating population derived from a Can-0xCol-0 cross, we identify the MADS-box transcription factor FLOWERING LOCUS M (FLM) as a player of the phenotypic variation in plant growth and color. We show that allelic variation at FLM modulates plant growth strategy along the leaf economics spectrum, a trade-off between resource acquisition and resource conservation, observable across thousands of plant species. Functional differences at FLM rely on a single intronic substitution, disturbing transcript splicing and leading to the accumulation of non-functional FLM transcripts. Associations between this substitution and phenotypic and climatic data across Arabidopsis natural populations, show how noncoding genetic variation at a single gene might be adaptive through pleiotropic effects.

Mild drought in the vegetative stage induces phenotypic, gene expression, and DNA methylation plasticity in Arabidopsis but no transgenerational effects.

There is renewed interest in whether environmentally induced changes in phenotypes can be heritable. In plants, heritable trait variation can occur without DNA sequence mutations through epigenetic mechanisms involving DNA methylation. However, it remains unknown whether this alternative system of inheritance responds to environmental changes and if it can provide a rapid way for plants to generate adaptive heritable phenotypic variation. To assess potential transgenerational effects induced by the environment, we subjected four natural accessions of Arabidopsis thaliana together with the reference accession Col-0 to mild drought in a multi-generational experiment. As expected, plastic responses to drought were observed in each accession, as well as a number of intergenerational effects of the parental environments. However, after an intervening generation without stress, except for a very few trait-based parental effects, descendants of stressed and non-stressed plants were phenotypically indistinguishable irrespective of whether they were grown in control conditions or under water deficit. In addition, genome-wide analysis of DNA methylation and gene expression in Col-0 demonstrated that, while mild drought induced changes in the DNA methylome of exposed plants, these variants were not inherited. We conclude that mild drought stress does not induce transgenerational epigenetic effects.

The complex genetic architecture of shoot growth natural variation in Arabidopsis thaliana.

One of the main outcomes of quantitative genetics approaches to natural variation is to reveal the genetic architecture underlying the phenotypic space. Complex genetic architectures are described as including numerous loci (or alleles) with small-effect and/or low-frequency in the populations, interactions with the genetic background, environment or age. Linkage or association mapping strategies will be more or less sensitive to this complexity, so that we still have an unclear picture of its extent. By combining high-throughput phenotyping under two environmental conditions with classical QTL mapping approaches in multiple Arabidopsis thaliana segregating populations as well as advanced near isogenic lines construction and survey, we have attempted to improve our understanding of quantitative phenotypic variation. Integrative traits such as those related to vegetative growth used in this work (highlighting either cumulative growth, growth rate or morphology) all showed complex and dynamic genetic architecture with respect to the segregating population and condition. The more resolutive our mapping approach, the more complexity we uncover, with several instances of QTLs visible in near isogenic lines but not detected with the initial QTL mapping, indicating that our phenotyping accuracy was less limiting than the mapping resolution with respect to the underlying genetic architecture. In an ultimate approach to resolve this complexity, we intensified our phenotyping effort to target specifically a 3Mb-region known to segregate for a major quantitative trait gene, using a series of selected lines recombined every 100kb. We discovered that at least 3 other independent QTLs had remained hidden in this region, some with trait- or condition-specific effects, or opposite allelic effects. If we were to extrapolate the figures obtained on this specific region in this particular cross to the genome- and species-scale, we would predict hundreds of causative loci of detectable phenotypic effect controlling these growth-related phenotypes.

Natural variation at XND1 impacts root hydraulics and trade-off for stress responses in Arabidopsis.

Soil water uptake by roots is a key component of plant performance and adaptation to adverse environments. Here, we use a genome-wide association analysis to identify the XYLEM NAC DOMAIN 1 (XND1) transcription factor as a negative regulator of Arabidopsis root hydraulic conductivity (Lpr). The distinct functionalities of a series of natural XND1 variants and a single nucleotide polymorphism that determines XND1 translation efficiency demonstrate the significance of XND1 natural variation at species-wide level. Phenotyping of xnd1 mutants and natural XND1 variants show that XND1 modulates Lpr through action on xylem formation and potential indirect effects on aquaporin function and that it diminishes drought stress tolerance. XND1 also mediates the inhibition of xylem formation by the bacterial elicitor flagellin and counteracts plant infection by the root pathogen Ralstonia solanacearum. Thus, genetic variation at XND1, and xylem differentiation contribute to resolving the major trade-off between abiotic and biotic stress resistance in Arabidopsis.

High contiguity Arabidopsis thaliana genome assembly with a single nanopore flow cell.

The handheld Oxford Nanopore MinION sequencer generates ultra-long reads with minimal cost and time requirements, which makes sequencing genomes at the bench feasible. Here, we sequence the gold standard Arabidopsis thaliana genome (KBS-Mac-74 accession) on the bench with the MinION sequencer, and assemble the genome using typical consumer computing hardware (4 Cores, 16 Gb RAM) into chromosome arms (62 contigs with an N50 length of 12.3 Mb). We validate the contiguity and quality of the assembly with two independent single-molecule technologies, Bionano optical genome maps and Pacific Biosciences Sequel sequencing. The new A. thaliana KBS-Mac-74 genome enables resolution of a quantitative trait locus that had previously been recalcitrant to a Sanger-based BAC sequencing approach. In summary, we demonstrate that even when the purpose is to understand complex structural variation at a single region of the genome, complete genome assembly is becoming the simplest way to achieve this goal.

New Strategies and Tools in Quantitative Genetics: How to Go from the Phenotype to the Genotype.

Quantitative genetics has a long history in plants: It has been used to study specific biological processes, identify the factors important for trait evolution, and breed new crop varieties. These classical approaches to quantitative trait locus mapping have naturally improved with technology. In this review, we show how quantitative genetics has evolved recently in plants and how new developments in phenotyping, population generation, sequencing, gene manipulation, and statistics are rejuvenating both the classical linkage mapping approaches (for example, through nested association mapping) as well as the more recently developed genome-wide association studies. These strategies are complementary in most instances, and indeed, one is often used to confirm the results of the other. Despite significant advances, an emerging trend is that the outcome and efficiency of the different approaches depend greatly on the genetic architecture of the trait in the genetic material under study.

An Arabidopsis Natural Epiallele Maintained by a Feed-Forward Silencing Loop between Histone and DNA.

The extent of epigenetic variation is currently well documented, but the number of natural epialleles described so far remains very limited. Determining the relevance of epigenetic changes for natural variation is an important question of research that we investigate by isolating natural epialleles segregating in Arabidopsis recombinant populations. We previously described a genetic incompatibility among Arabidopsis strains based on the silencing of a gene involved in fitness. Here, we isolated a new epiallele resulting from the silencing of a transfer-RNA editing gene in an Arabidopsis accession from the Netherlands (Nok-1). Crosses with the reference accession Col-0 show a complete incompatibility between this epiallele and another locus localized on a different chromosome. We demonstrate that conversion of an unmethylated version of this allele occurs in hybrids, associated with modifications of small RNA populations. These epialleles can also spontaneously revert within the population. Furthermore, we bring evidence that neither METHYLTRANSFERASE 1, maintaining methylation at CGs, nor components of RNA-directed DNA methylation, are key factors for the transmission of the epiallele over generations. This depends only on the self-reinforcing loop between CHROMOMETHYLASE 3 and KRYPTONITE, involving DNA methylated in the CHG context and histone H3 lysine 9 methylation. Our findings reveal a predominant role of this loop in maintaining a natural epiallele.

AraQTL - workbench and archive for systems genetics in Arabidopsis thaliana.

Genetical genomics studies uncover genome-wide genetic interactions between genes and their transcriptional regulators. High-throughput measurement of gene expression in recombinant inbred line populations has enabled investigation of the genetic architecture of variation in gene expression. This has the potential to enrich our understanding of the molecular mechanisms affected by and underlying natural variation. Moreover, it contributes to the systems biology of natural variation, as a substantial number of experiments have resulted in a valuable amount of interconnectable phenotypic, molecular and genotypic data. A number of genetical genomics studies have been published for Arabidopsis thaliana, uncovering many expression quantitative trait loci (eQTLs). However, these complex data are not easily accessible to the plant research community, leaving most of the valuable genetic interactions unexplored as cross-analysis of these studies is a major effort. We address this problem with AraQTL (http://www.bioinformatics.nl/Ara QTL/), an easily accessible workbench and database for comparative analysis and meta-analysis of all published Arabidopsis eQTL datasets. AraQTL provides a workbench for comparing, re-using and extending upon the results of these experiments. For example, one can easily screen a physical region for specific local eQTLs that could harbour candidate genes for phenotypic QTLs, or detect gene-by-environment interactions by comparing eQTLs under different conditions.

A Potassium-Dependent Oxygen Sensing Pathway Regulates Plant Root Hydraulics.

Aerobic organisms survive low oxygen (O2) through activation of diverse molecular, metabolic, and physiological responses. In most plants, root water permeability (in other words, hydraulic conductivity, Lpr) is downregulated under O2 deficiency. Here, we used a quantitative genetics approach in Arabidopsis to clone Hydraulic Conductivity of Root 1 (HCR1), a Raf-like MAPKKK that negatively controls Lpr. HCR1 accumulates and is functional under combined O2 limitation and potassium (K(+)) sufficiency. HCR1 regulates Lpr and hypoxia responsive genes, through the control of RAP2.12, a key transcriptional regulator of the core anaerobic response. A substantial variation of HCR1 in regulating Lpr is observed at the Arabidopsis species level. Thus, by combinatorially integrating two soil signals, K(+) and O2 availability, HCR1 modulates the resilience of plants to multiple flooding scenarios.

Leaf Segmentation and Tracking in Arabidopsis thaliana Combined to an Organ-Scale Plant Model for Genotypic Differentiation.

A promising method for characterizing the phenotype of a plant as an interaction between its genotype and its environment is to use refined organ-scale plant growth models that use the observation of architectural traits, such as leaf area, containing a lot of information on the whole history of the functioning of the plant. The Phenoscope, a high-throughput automated platform, allowed the acquisition of zenithal images of Arabidopsis thaliana over twenty one days for 4 different genotypes. A novel image processing algorithm involving both segmentation and tracking of the plant leaves allows to extract areas of the latter. First, all the images in the series are segmented independently using a watershed-based approach. A second step based on ellipsoid-shaped leaves is then applied on the segments found to refine the segmentation. Taking into account all the segments at every time, the whole history of each leaf is reconstructed by choosing recursively through time the most probable segment achieving the best score, computed using some characteristics of the segment such as its orientation, its distance to the plant mass center and its area. These results are compared to manually extracted segments, showing a very good accordance in leaf rank and that they therefore provide low-biased data in large quantity for leaf areas. Such data can therefore be exploited to design an organ-scale plant model adapted from the existing GreenLab model for A. thaliana and subsequently parameterize it. This calibration of the model parameters should pave the way for differentiation between the Arabidopsis genotypes.

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.