Genome-wide patterns of genetic variation in worldwide Arabidopsis thaliana accessions from the RegMap panel

Population-genomic analysis identifies a low rate of global adaptive fixation in the proteins of the cyclical parthenogen Daphnia magna

Daphnia are well-established ecological and evolutionary models, and the interaction between D. magna and its microparasites is widely considered a paragon of the host-parasite coevolutionary process. Like other well-studied arthropods such as Drosophila melanogaster and Anopheles gambiae, D. magna is a small, widespread, and abundant species that is therefore expected to display a large long-term population size and high rates of adaptive protein evolution. However, unlike these other species, D. magna is cyclically asexual and lives in a highly structured environment (ponds and lakes) with moderate levels of dispersal, both of which are predicted to impact upon long-term effective population size and adaptive protein evolution. To investigate patterns of adaptive protein fixation, we produced the complete coding genomes of 36 D. magna clones sampled from across the European range (Western Palaearctic), along with draft sequences for the close relatives D. similis and D. lumholtzi, used as outgroups. We analyzed genome-wide patterns of adaptive fixation, with a particular focus on genes that have an a priori expectation of high rates, such as those likely to mediate immune responses, RNA interference against viruses and transposable elements, and those with a strongly male-biased expression pattern. We find that, as expected, D. magna displays high levels of diversity and that this is highly structured among populations. However, compared with Drosophila, we find that D. magna proteins appear to have a high proportion of weakly deleterious variants and do not show evidence of pervasive adaptive fixation across its entire range. This is true of the genome as a whole, and also of putative ‘arms race’ genes that often show elevated levels of adaptive substitution in other species. In addition to the likely impact of extensive, and previously documented, local adaptation, we speculate that these findings may reflect reduced efficacy of selection associated with cyclical asexual reproduction.

Study of natural diversity in response to a key pathogenicity regulator of Ralstonia solanacearum reveals new susceptibility genes in Arabidopsis thaliana

Ralstonia solanacearum gram-negative phytopathogenic bacterium exerts its virulence through a type III secretion system (T3SS) that translocates type III effectors (T3Es) directly into the host cells. T3E secretion is finely controlled at the posttranslational level by helper proteins, T3SS control proteins, and type III chaperones. The HpaP protein, one of the type III secretion substrate specificity switch (T3S4) proteins, was previously highlighted as a virulence factor on Arabidopsis thaliana Col-0 accession. In this study, we set up a genome-wide association analysis to explore the natural diversity of response to the hpaP mutant of two A. thaliana mapping populations: a worldwide collection and a local population. Quantitative genetic variation revealed different genetic architectures in both mapping populations, with a global delayed response to the hpaP mutant compared to the GMI1000 wild-type strain. We have identified several quantitative trait loci (QTLs) associated with the hpaP mutant inoculation. The genes underlying these QTLs are involved in different and specific biological processes, some of which were demonstrated important for R. solanacearum virulence. We focused our study on four candidate genes, RKL1, IRE3, RACK1B, and PEX3, identified using the worldwide collection, and validated three of them as susceptibility factors. Our findings demonstrate that the study of the natural diversity of plant response to a R. solanacearum mutant in a key regulator of virulence is an original and powerful strategy to identify genes directly or indirectly targeted by the pathogen.

Species-specific partial gene duplication in Arabidopsis thaliana evolved novel phenotypic effects on morphological traits under strong positive selection

Gene duplication is increasingly recognized as an important mechanism for the origination of new genes, as revealed by comparative genomic analysis. However, how new duplicate genes contribute to phenotypic evolution remains largely unknown, especially in plants. Here, we identified the new gene EXOV, derived from a partial gene duplication of its parental gene EXOVL in Arabidopsis thaliana. EXOV is a species-specific gene that originated within the last 3.5 million years and shows strong signals of positive selection. Unexpectedly, RNA-sequencing analyses revealed that, despite its young age, EXOV has acquired many novel direct and indirect interactions in which the parental gene does not engage. This observation is consistent with the high, selection-driven substitution rate of its encoded protein, in contrast to the slowly evolving EXOVL, suggesting an important role for EXOV in phenotypic evolution. We observed significant differentiation of morphological changes for all phenotypes assessed in genome-edited and T-DNA insertional single mutants and in double T-DNA insertion mutants in EXOV and EXOVL. We discovered a substantial divergence of phenotypic effects by principal component analyses, suggesting neofunctionalization of the new gene. These results reveal a young gene that plays critical roles in biological processes that underlie morphological evolution in A. thaliana.

cis-prenyltransferase 3 and α/β-hydrolase are new determinants of dolichol accumulation in Arabidopsis

Dolichols (Dols), ubiquitous components of living organisms, are indispensable for cell survival. In plants, as well as other eukaryotes, Dols are crucial for post-translational protein glycosylation, aberration of which leads to fatal metabolic disorders in humans and male sterility in plants. Until now, the mechanisms underlying Dol accumulation remain elusive. In this study, we have analysed the natural variation of the accumulation of Dols and six other isoprenoids among more than 120 Arabidopsis thaliana accessions. Subsequently, by combining QTL and GWAS approaches, we have identified several candidate genes involved in the accumulation of Dols, polyprenols, plastoquinone and phytosterols. The role of two genes implicated in the accumulation of major Dols in Arabidopsis-the AT2G17570 gene encoding a long searched for cis-prenyltransferase (CPT3) and the AT1G52460 gene encoding an α/β-hydrolase-is experimentally confirmed. These data will help to generate Dol-enriched plants which might serve as a remedy for Dol-deficiency in humans.

Entailing the Next-Generation Sequencing and Metabolome for Sustainable Agriculture by Improving Plant Tolerance

Crop production is a serious challenge to provide food for the 10 billion individuals forecasted to live across the globe in 2050. The scientists' emphasize establishing an equilibrium among diversity and quality of crops by enhancing yield to fulfill the increasing demand for food supply sustainably. The exploitation of genetic resources using genomics and metabolomics strategies can help generate resilient plants against stressors in the future. The innovation of the next-generation sequencing (NGS) strategies laid the foundation to unveil various plants' genetic potential and help us to understand the domestication process to unmask the genetic potential among wild-type plants to utilize for crop improvement. Nowadays, NGS is generating massive genomic resources using wild-type and domesticated plants grown under normal and harsh environments to explore the stress regulatory factors and determine the key metabolites. Improved food nutritional value is also the key to eradicating malnutrition problems around the globe, which could be attained by employing the knowledge gained through NGS and metabolomics to achieve suitability in crop yield. Advanced technologies can further enhance our understanding in defining the strategy to obtain a specific phenotype of a crop. Integration among bioinformatic tools and molecular techniques, such as marker-assisted, QTLs mapping, creation of reference genome, de novo genome assembly, pan- and/or super-pan-genomes, etc., will boost breeding programs. The current article provides sequential progress in NGS technologies, a broad application of NGS, enhancement of genetic manipulation resources, and understanding the crop response to stress by producing plant metabolites. The NGS and metabolomics utilization in generating stress-tolerant plants/crops without deteriorating a natural ecosystem is considered a sustainable way to improve agriculture production. This highlighted knowledge also provides useful research that explores the suitable resources for agriculture sustainability.

Expression GWAS of PGIP1 Identifies STOP1-Dependent and STOP1-Independent Regulation of PGIP1 in Aluminum Stress Signaling in Arabidopsis

To elucidate the unknown regulatory mechanisms involved in aluminum (Al)-induced expression of POLYGALACTURONASE-INHIBITING PROTEIN 1 (PGIP1), which is one of the downstream genes of SENSITIVE TO PROTON RHIZOTOXICITY 1 (STOP1) regulating Al-tolerance genes, we conducted a genome-wide association analysis of gene expression levels (eGWAS) of PGIP1 in the shoots under Al stress using 83 Arabidopsis thaliana accessions. The eGWAS, conducted through a mixed linear model, revealed 17 suggestive SNPs across the genome having the association with the expression level variation in PGIP1. The GWAS-detected SNPs were directly located inside transcription factors and other genes involved in stress signaling, which were expressed in response to Al. These candidate genes carried different expression level and amino acid polymorphisms. Among them, three genes encoding NAC domain-containing protein 27 (NAC027), TRX superfamily protein, and R-R-type MYB protein were associated with the suppression of PGIP1 expression in their mutants, and accordingly, the system affected Al tolerance. We also found the involvement of Al-induced endogenous nitric oxide (NO) signaling, which induces NAC027 and R-R-type MYB genes to regulate PGIP1 expression. In this study, we provide genetic evidence that STOP1-independent NO signaling pathway and STOP1-dependent regulation in phosphoinositide (PI) signaling pathway are involved in the regulation of PGIP1 expression under Al stress.

Diverse phosphate and auxin transport loci distinguish phosphate tolerant from sensitive Arabidopsis accessions

Phosphorus (P) is an essential element for plant growth often limiting agroecosystems. To identify genetic determinants of performance under variable phosphate (Pi) supply, we conducted genome-wide association studies on five highly predictive Pi starvation response traits in 200 Arabidopsis (Arabidopsis thaliana) accessions. Pi concentration in Pi-limited organs had the strongest, and primary root length had the weakest genetic component. Of 70 trait-associated candidate genes, 17 responded to Pi withdrawal. The PHOSPHATE TRANSPORTER1 gene cluster on chromosome 5 comprises PHT1;1, PHT1;2, and PHT1;3 with known impact on P status. A second locus featured uncharacterized endomembrane-associated auxin efflux carrier encoding PIN-LIKES7 (PILS7) which was more strongly suppressed in Pi-limited roots of Pi-starvation sensitive accessions. In the Col-0 background, Pi uptake and organ growth were impaired in both Pi-limited pht1;1 and two pils7 T-DNA insertion mutants, while Pi -limited pht1;2 had higher biomass and pht1;3 was indistinguishable from wild-type. Copy number variation at the PHT1 locus with loss of the PHT1;3 gene and smaller scale deletions in PHT1;1 and PHT1;2 predicted to alter both protein structure and function suggest diversification of PHT1 is a key driver for adaptation to P limitation. Haplogroup analysis revealed a phosphorylation site in the protein encoded by the PILS7 allele from stress-sensitive accessions as well as additional auxin-responsive elements in the promoter of the "stress tolerant" allele. The former allele's inability to complement the pils7-1 mutant in the Col-0 background implies the presence of a kinase signaling loop controlling PILS7 activity in accessions from P-rich environments, while survival in P-poor environments requires fine-tuning of stress-responsive root auxin signaling.

Transgenerational effects of temperature fluctuations in Arabidopsis thaliana

Plant stress responses can extend into the following generations, a phenomenon called transgenerational effects. Heat stress, in particular, is known to affect plant offspring, but we do not know to what extent these effects depend on the temporal patterns of the stress, and whether transgenerational responses are adaptive and genetically variable within species. To address these questions, we carried out a two-generation experiment with nine Arabidopsis thaliana genotypes. We subjected the plants to heat stress regimes that varied in timing and frequency, but not in mean temperature, and we then grew the offspring of these plants under controlled conditions as well as under renewed heat stress. The stress treatments significantly carried over to the offspring generation, with timing having stronger effects on plant phenotypes than stress frequency. However, there was no evidence that transgenerational effects were adaptive. The magnitudes of transgenerational effects differed substantially among genotypes, and for some traits the strength of plant responses was significantly associated with the climatic variability at the sites of origin. In summary, timing of heat stress not only directly affects plants, but it can also cause transgenerational effects on offspring phenotypes. Genetic variation in transgenerational effects, as well as correlations between transgenerational effects and climatic variability, indicates that transgenerational effects can evolve, and have probably already done so in the past.

The Genomic Architecture of Competitive Response of Arabidopsis thaliana Is Highly Flexible Among Plurispecific Neighborhoods

Plants are daily challenged by multiple abiotic and biotic stresses. A major biotic constraint corresponds to competition with other plant species. Although plants simultaneously interact with multiple neighboring species throughout their life cycle, there is still very limited information about the genetics of the competitive response in the context of plurispecific interactions. Using a local mapping population of Arabidopsis thaliana, we set up a genome wide association study (GWAS) to estimate the extent of genetic variation of competitive response in 12 plant species assemblages, based on three competitor species (Poa annua, Stellaria media, and Veronica arvensis). Based on five phenotypic traits, we detected strong crossing reaction norms not only between the three bispecific neighborhoods but also among the plurispecific neighborhoods. The genetic architecture of competitive response was highly dependent on the identity and the relative abundance of the neighboring species. In addition, most of the enriched biological processes underlying competitive responses largely differ among neighborhoods. While the RNA related processes might confer a broad range response toolkit for multiple traits in diverse neighborhoods, some processes, such as signaling and transport, might play a specific role in particular assemblages. Altogether, our results suggest that plants can integrate and respond to different species assemblages depending on the identity and number of each neighboring species, through a large range of candidate genes associated with diverse and unexpected processes leading to developmental and stress responses.

Plasticity of rosette size in response to nitrogen availability is controlled by an RCC1-family protein

Nitrogen (N) is fundamental to plant growth, development and yield. Genes underlying N utilization and assimilation are well-characterized, but mechanisms underpinning plasticity of different phenotypes in response to N remain elusive. Here, using Arabidopsis thaliana accessions, we dissected the genetic architecture of plasticity in early and late rosette diameter, flowering time and yield, in response to three levels of N in the soil. Furthermore, we found that the plasticity in levels of primary metabolites were related with the plasticities of the studied traits. Genome-wide association analysis identified three significant associations for phenotypic plasticity, one for early rosette diameter and two for flowering time. We confirmed that the gene At1g19880, hereafter named as PLASTICITY OF ROSETTE TO NITROGEN 1 (PROTON1), encoding for a regulator of chromatin condensation 1 (RCC1) family protein, conferred plasticity of rosette diameter in response to N. Treatment of PROTON1 T-DNA line with salt implied that the reduced plasticity of early rosette diameter was not a general growth response to stress. We further showed that plasticities of growth and flowering-related traits differed between environmental cues, indicating decoupled genetic programs regulating these traits. Our findings provide a prospective to identify genes that stabilize performance under fluctuating environments.

Local auxin biosynthesis acts downstream of brassinosteroids to trigger root foraging for nitrogen

Lateral roots (LRs) dominate the overall root surface of adult plants and are crucial for soil exploration and nutrient acquisition. When grown under mild nitrogen (N) deficiency, flowering plants develop longer LRs to enhance nutrient acquisition. This response is partly mediated by brassinosteroids (BR) and yet unknown mechanisms. Here, we show that local auxin biosynthesis modulates LR elongation while allelic coding variants of YUCCA8 determine the extent of elongation under N deficiency. By up-regulating the expression of YUCCA8/3/5/7 and of Tryptophan Aminotransferase of Arabidopsis 1 (TAA1) under mild N deficiency auxin accumulation increases in LR tips. We further demonstrate that N-dependent auxin biosynthesis in LRs acts epistatic to and downstream of a canonical BR signaling cascade. The uncovered BR-auxin hormonal module and its allelic variants emphasize the importance of fine-tuning hormonal crosstalk to boost adaptive root responses to N availability and offer a path to improve soil exploration by expanded root systems in plants.

Revisiting a GWAS peak in Arabidopsis thaliana reveals possible confounding by genetic heterogeneity

Genome-wide association studies (GWAS) have become a standard approach for exploring the genetic basis of phenotypic variation. However, correlation is not causation, and only a tiny fraction of all associations have been experimentally confirmed. One practical problem is that a peak of association does not always pinpoint a causal gene, but may instead be tagging multiple causal variants. In this study, we reanalyze a previously reported peak associated with flowering time traits in Swedish Arabidopsis thaliana population. The peak appeared to pinpoint the AOP2/AOP3 cluster of glucosinolate biosynthesis genes, which is known to be responsible for natural variation in herbivore resistance. Here we propose an alternative hypothesis, by demonstrating that the AOP2/AOP3 flowering association can be wholly accounted for by allelic variation in two flanking genes with clear roles in regulating flowering: NDX1, a regulator of the main flowering time controller FLC, and GA1, which plays a central role in gibberellin synthesis and is required for flowering under some conditions. In other words, we propose that the AOP2/AOP3 flowering-time association may be yet another example of a spurious, "synthetic" association, arising from trying to fit a single-locus model in the presence of two statistically associated causative loci. We conclude that caution is needed when using GWAS for fine-mapping.

Genome-Wide Association Study Reveals Key Genes for Differential Lead Accumulation and Tolerance in Natural Arabidopsis thaliana Accessions

Soil contamination by lead (Pb) has become one of the major ecological threats to the environment. Understanding the mechanisms of Pb transport and deposition in plants is of great importance to achieve a global Pb reduction. We exposed a collection of 360 Arabidopsis thaliana natural accessions to a Pb-polluted soil. Germination rates, growth, and leaf Pb concentrations showed extensive variation among accessions. These phenotypic data were subjected to genome wide association studies (GWAs) and we found a significant association on chromosome 1 for low leaf Pb accumulation. Genes associated with significant SNP markers were evaluated and we selected EXTENSIN18 (EXT18) and TLC (TRAM-LAG1-CLN8) as candidates for having a role in Pb homeostasis. Six Pb-tolerant accessions, three of them exhibiting low leaf Pb content, and three of them with high leaf Pb content; two Pb-sensitive accessions; two knockout T-DNA lines of GWAs candidate genes (ext18, tlc); and Col-0 were screened under control and high-Pb conditions. The relative expression of EXT18, TLC, and other genes described for being involved in Pb tolerance was also evaluated. Analysis of Darwinian fitness, root and leaf ionome, and TEM images revealed that Pb-tolerant accessions employ two opposing strategies: (1) low translocation of Pb and its accumulation into root cell walls and vacuoles, or (2) high translocation of Pb and its efflux to inactive organelles or intracellular spaces. Plants using the first strategy exhibited higher expression of EXT18 and HMA3, thicker root cell walls and Pb vacuolar sequestration, suggesting that these genes may contribute to the deposition of Pb in the roots. On the other hand, plants translocating high amounts of Pb showed upregulation of TLC and ABC transporters, indicating that these plants were able to properly efflux Pb in the aerial tissues. We conclude that EXT18 and TLC upregulation enhances Pb tolerance promoting its sequestration: EXT18 favors the thickening of the cell walls improving Pb accumulation in roots and decreasing its toxicity, while TLC facilitates the formation of dictyosome vesicles and the Pb encapsulation in leaves. These findings are relevant for the design of phytoremediation strategies and environment restoration.

Genomic analysis of field pennycress (Thlaspi arvense) provides insights into mechanisms of adaptation to high elevation

Background

Understanding how organisms evolve and adapt to extreme habitats is of crucial importance in evolutionary ecology. Altitude gradients are an important determinant of the distribution pattern and range of organisms due to distinct climate conditions at different altitudes. High-altitude regions often provide extreme environments including low temperature and oxygen concentration, poor soil, and strong levels of ultraviolet radiation, leading to very few plant species being able to populate elevation ranges greater than 4000 m. Field pennycress (Thlaspi arvense) is a valuable oilseed crop and emerging model plant distributed across an elevation range of nearly 4500 m. Here, we generate an improved genome assembly to understand how this species adapts to such different environments.

Results

We sequenced and assembled de novo the chromosome-level pennycress genome of 527.3 Mb encoding 31,596 genes. Phylogenomic analyses based on 2495 single-copy genes revealed that pennycress is closely related to Eutrema salsugineum (estimated divergence 14.32–18.58 Mya), and both species form a sister clade to Schrenkiella parvula and genus Brassica. Field pennycress contains the highest percentage (70.19%) of transposable elements in all reported genomes of Brassicaceae, with the retrotransposon proliferation in the Middle Pleistocene being likely responsible for the expansion of genome size. Moreover, our analysis of 40 field pennycress samples in two high- and two low-elevation populations detected 1,256,971 high-quality single nucleotide polymorphisms. Using three complementary selection tests, we detected 130 candidate naturally selected genes in the Qinghai-Tibet Plateau (QTP) populations, some of which are involved in DNA repair and the ubiquitin system and potential candidates involved in high-altitude adaptation. Notably, we detected a single base mutation causing loss-of-function of the FLOWERING LOCUS C protein, responsible for the transition to early flowering in high-elevation populations.

Conclusions

Our results provide a genome-wide perspective of how plants adapt to distinct environmental conditions across extreme elevation differences and the potential for further follow-up research with extensive data from additional populations and species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01079-0.

Genome-wide association studies: assessing trait characteristics in model and crop plants

GWAS involves testing genetic variants across the genomes of many individuals of a population to identify genotype–phenotype association. It was initially developed and has proven highly successful in human disease genetics. In plants genome-wide association studies (GWAS) initially focused on single feature polymorphism and recombination and linkage disequilibrium but has now been embraced by a plethora of different disciplines with several thousand studies being published in model and crop species within the last decade or so. Here we will provide a comprehensive review of these studies providing cases studies on biotic resistance, abiotic tolerance, yield associated traits, and metabolic composition. We also detail current strategies of candidate gene validation as well as the functional study of haplotypes. Furthermore, we provide a critical evaluation of the GWAS strategy and its alternatives as well as future perspectives that are emerging with the emergence of pan-genomic datasets.

Plant NLR diversity: the known unknowns of pan-NLRomes

Plants and pathogens constantly adapt to each other. As a consequence, many members of the plant immune system, and especially the intracellular nucleotide-binding site leucine-rich repeat receptors, also known as NOD-like receptors (NLRs), are highly diversified, both among family members in the same genome, and between individuals in the same species. While this diversity has long been appreciated, its true extent has remained unknown. With pan-genome and pan-NLRome studies becoming more and more comprehensive, our knowledge of NLR sequence diversity is growing rapidly, and pan-NLRomes provide powerful platforms for assigning function to NLRs. These efforts are an important step toward the goal of comprehensively predicting from sequence alone whether an NLR provides disease resistance, and if so, to which pathogens.

Improving Genomic Prediction Using High-Dimensional Secondary Phenotypes

In the past decades, genomic prediction has had a large impact on plant breeding. Given the current advances of high-throughput phenotyping and sequencing technologies, it is increasingly common to observe a large number of traits, in addition to the target trait of interest. This raises the important question whether these additional or “secondary” traits can be used to improve genomic prediction for the target trait. With only a small number of secondary traits, this is known to be the case, given sufficiently high heritabilities and genetic correlations. Here we focus on the more challenging situation with a large number of secondary traits, which is increasingly common since the arrival of high-throughput phenotyping. In this case, secondary traits are usually incorporated through additional relatedness matrices. This approach is however infeasible when secondary traits are not measured on the test set, and cannot distinguish between genetic and non-genetic correlations. An alternative direction is to extend the classical selection indices using penalized regression. So far, penalized selection indices have not been applied in a genomic prediction setting, and require plot-level data in order to reliably estimate genetic correlations. Here we aim to overcome these limitations, using two novel approaches. Our first approach relies on a dimension reduction of the secondary traits, using either penalized regression or random forests (LS-BLUP/RF-BLUP). We then compute the bivariate GBLUP with the dimension reduction as secondary trait. For simulated data (with available plot-level data), we also use bivariate GBLUP with the penalized selection index as secondary trait (SI-BLUP). In our second approach (GM-BLUP), we follow existing multi-kernel methods but replace secondary traits by their genomic predictions, with the advantage that genomic prediction is also possible when secondary traits are only measured on the training set. For most of our simulated data, SI-BLUP was most accurate, often closely followed by RF-BLUP or LS-BLUP. In real datasets, involving metabolites in Arabidopsis and transcriptomics in maize, no method could substantially improve over univariate prediction when secondary traits were only available on the training set. LS-BLUP and RF-BLUP were most accurate when secondary traits were available also for the test set.

Advancing crop genomics from lab to field

Crop genomics remains a key element in ensuring scientific progress to secure global food security. It has been two decades since the sequence of the first plant genome, that of Arabidopsis thaliana, was released, and soon after that the draft sequencing of the rice genome was completed. Since then, the genomes of more than 100 crops have been sequenced, plant genome research has expanded across multiple fronts and the next few years promise to bring further advances spurred by the advent of new technologies and approaches. We are likely to see continued innovations in crop genome sequencing, genetic mapping and the acquisition of multiple levels of biological data. There will be exciting opportunities to integrate genome-scale information across multiple scales of biological organization, leading to advances in our mechanistic understanding of crop biological processes, which will, in turn, provide greater impetus for translation of laboratory results to the field.

Metabolic source isotopic pair labeling and genome-wide association are complementary tools for the identification of metabolite-gene associations in plants

The optimal extraction of information from untargeted metabolomics analyses is a continuing challenge. Here, we describe an approach that combines stable isotope labeling, liquid chromatography- mass spectrometry (LC-MS), and a computational pipeline to automatically identify metabolites produced from a selected metabolic precursor. We identified the subset of the soluble metabolome generated from phenylalanine (Phe) in Arabidopsis thaliana, which we refer to as the Phe-derived metabolome (FDM) In addition to identifying Phe-derived metabolites present in a single wild-type reference accession, the FDM was established in nine enzymatic and regulatory mutants in the phenylpropanoid pathway. To identify genes associated with variation in Phe-derived metabolites in Arabidopsis, MS features collected by untargeted metabolite profiling of an Arabidopsis diversity panel were retrospectively annotated to the FDM and natural genetic variants responsible for differences in accumulation of FDM features were identified by genome-wide association. Large differences in Phe-derived metabolite accumulation and presence/absence variation of abundant metabolites were observed in the nine mutants as well as between accessions from the diversity panel. Many Phe-derived metabolites that accumulated in mutants also accumulated in non-Col-0 accessions and was associated to genes with known or suspected functions in the phenylpropanoid pathway as well as genes with no known functions. Overall, we show that cataloguing a biochemical pathway's products through isotopic labeling across genetic variants can substantially contribute to the identification of metabolites and genes associated with their biosynthesis.

Metabolic Profile Discriminates and Predicts Arabidopsis Susceptibility to Virus under Field Conditions

As obligatory parasites, plant viruses alter host cellular metabolism. There is a lack of information on the variability of virus-induced metabolic responses among genetically diverse plants in a natural context with daily changing conditions. To decipher the metabolic landscape of plant-virus interactions in a natural setting, twenty-six and ten accessions of Arabidopsis thaliana were inoculated with Turnip mosaic virus (TuMV), in two field experiments over 2 years. The accessions were measured for viral accumulation, above-ground biomass, targeted and untargeted metabolic profiles. The phenotypes of the accessions ranged from susceptibility to resistance. Susceptible and resistant accessions were shown to have different metabolic routes after inoculation. Susceptible genotypes accumulate primary and secondary metabolites upon infection, at the cost of hindered growth. Twenty-one metabolic signatures significantly accumulated in resistant accessions whereas they maintained their growth as mock-inoculated plants without biomass penalty. Metabolic content was demonstrated to discriminate and be highly predictive of the susceptibility of inoculated Arabidopsis. This study is the first to describe the metabolic landscape of plant-virus interactions in a natural setting and its predictive link to susceptibility. It provides new insights on plant-virus interactions. In this undomesticated species and in ecologically realistic conditions, growth and resistance are in a permanent conversation.

Neighbor GWAS: incorporating neighbor genotypic identity into genome-wide association studies of field herbivory

An increasing number of field studies have shown that the phenotype of an individual plant depends not only on its genotype but also on those of neighboring plants; however, this fact is not taken into consideration in genome-wide association studies (GWAS). Based on the Ising model of ferromagnetism, we incorporated neighbor genotypic identity into a regression model, named "Neighbor GWAS". Our simulations showed that the effective range of neighbor effects could be estimated using an observed phenotype when the proportion of phenotypic variation explained (PVE) by neighbor effects peaked. The spatial scale of the first nearest neighbors gave the maximum power to detect the causal variants responsible for neighbor effects, unless their effective range was too broad. However, if the effective range of the neighbor effects was broad and minor allele frequencies were low, there was collinearity between the self and neighbor effects. To suppress the false positive detection of neighbor effects, the fixed effect and variance components involved in the neighbor effects should be tested in comparison with a standard GWAS model. We applied neighbor GWAS to field herbivory data from 199 accessions of Arabidopsis thaliana and found that neighbor effects explained 8% more of the PVE of the observed damage than standard GWAS. The neighbor GWAS method provides a novel tool that could facilitate the analysis of complex traits in spatially structured environments and is available as an R package at CRAN ( https://cran.rproject.org/package=rNeighborGWAS ).

A genome-wide association study reveals cytokinin as a major component in the root defense responses against Ralstonia solanacearum

Bacterial wilt caused by the soil-borne pathogen Ralstonia solancearum is economically devastating, with no effective methods to fight the disease. This pathogen invades plants through their roots and colonizes their xylem, clogging the vasculature and causing rapid wilting. Key to preventing colonization are the early defense responses triggered in the host's root upon infection, which remain mostly unknown. Here, we have taken advantage of a high-throughput in vitro infection system to screen natural variability associated with the root growth inhibition phenotype caused by R. solanacearum in Arabidopsis during the first hours of infection. To analyze the genetic determinants of this trait, we have performed a genome-wide association study, identifying allelic variation at several loci related to cytokinin metabolism, including genes responsible for biosynthesis and degradation of cytokinin. Further, our data clearly demonstrate that cytokinin signaling is induced early during the infection process and cytokinin contributes to immunity against R. solanacearum. This study highlights a new role for cytokinin in root immunity, paving the way for future research that will help in understanding the mechanisms underpinning root defenses.

L2,1-norm regularized multivariate regression model with applications to genomic prediction

MOTIVATION

Genomic selection (GS) is currently deemed the most effective approach to speed up breeding of agricultural varieties. It has been recognized that consideration of multiple traits in GS can improve accuracy of prediction for traits of low heritability. However, since GS forgoes statistical testing with the idea of improving predictions, it does not facilitate mechanistic understanding of the contribution of particular single nucleotide polymorphisms (SNP).

RESULTS

Here, we propose a L2,1-norm regularized multivariate regression model and devise a fast and efficient iterative optimization algorithm, called L2,1-joint, applicable in multi-trait GS. The usage of the L2,1-norm facilitates variable selection in a penalized multivariate regression that considers the relation between individuals, when the number of SNPs is much larger than the number of individuals. The capacity for variable selection allows us to define master regulators that can be used in a multi-trait GS setting to dissect the genetic architecture of the analyzed traits. Our comparative analyses demonstrate that the proposed model is a favorable candidate compared to existing state-of-the-art approaches. Prediction and variable selection with datasets from Brassica napus, wheat and Arabidopsis thaliana diversity panels are conducted to further showcase the performance of the proposed model.

AVAILABILITY AND IMPLEMENTATION

: The model is implemented using R programming language and the code is freely available from https://github.com/alainmbebi/L21-norm-GS.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

EigenGWAS: An online visualizing and interactive application for detecting genomic signatures of natural selection

Detecting genetic regions under selection in structured populations is of great importance in ecology, evolutionary biology and breeding programmes. We recently proposed EigenGWAS, an unsupervised genomic scanning approach that is similar to F ST but does not require grouping information of the population, for detection of genomic regions under selection. The original EigenGWAS is designed for the random mating population, and here we extend its use to inbred populations. We also show in theory and simulation that eigenvalues, the previous corrector for genetic drift in EigenGWAS, are overcorrected for genetic drift, and the genomic inflation factor is a better option for this adjustment. Applying the updated algorithm, we introduce the new EigenGWAS online platform with highly efficient core implementation. Our online computational tool accepts plink data in a standard binary format that can be easily converted from the original sequencing data, provides the users with graphical results via the R-Shiny user-friendly interface. We applied the proposed method and tool to various data sets, and biologically interpretable results as well as caveats that may lead to an unsatisfactory outcome are given. The EigenGWAS online platform is available at www.eigengwas.com, and can be localized and scaled up via R (recommended) or docker.

Naturally occurring circadian rhythm variation associated with clock gene loci in Swedish Arabidopsis accessions

Circadian clocks have evolved to resonate with external day and night cycles. However, these entrainment signals are not consistent everywhere and vary with latitude, climate and seasonality. This leads to divergent selection for clocks which are locally adapted. To investigate the genetic basis for this circadian variation, we used a delayed fluorescence imaging assay to screen 191 naturally occurring Swedish Arabidopsis accessions for their circadian phenotypes. We demonstrate that the period length co-varies with both geography and population sub-structure. Several candidate loci linked to period, phase and relative amplitude error (RAE) were revealed by genome-wide association mapping and candidate genes were investigated using TDNA mutants. We show that natural variation in a single non-synonymous substitution within COR28 is associated with a long-period and late-flowering phenotype similar to that seen in TDNA knock-out mutants. COR28 is a known coordinator of flowering time, freezing tolerance and the circadian clock; all of which may form selective pressure gradients across Sweden. We demonstrate the effect of the COR28-58S SNP in increasing period length through a co-segregation analysis. Finally, we show that period phenotypic tails remain diverged under lower temperatures and follow a distinctive "arrow-shaped" trend indicative of selection for a cold-biased temperature compensation response.

Arabidopsis natural variation in insect egg-induced cell death reveals a role for LECTIN RECEPTOR KINASE-I.1

In Arabidopsis (Arabidopsis thaliana), a hypersensitive-like response (HR-like response) is triggered underneath the eggs of the large white butterfly Pieris brassicae (P. brassicae), and this response is dependent on salicylic acid (SA) accumulation and signaling. Previous reports indicate that the clade I L-type LECTIN RECEPTOR KINASE-I.8 (LecRK-I.8) is involved in early steps of egg recognition. A genome-wide association study was used to better characterize the genetic structure of the HR-like response and discover loci that contribute to this response. We report here the identification of LecRK-I.1, a close homolog of LecRK-I.8, and show that two main haplotypes that explain part of the variation in HR-like response segregate among natural Arabidopsis accessions. Besides, signatures of balancing selection at this locus suggest that it may be ecologically important. Disruption of LecRK-I.1 results in decreased HR-like response and SA signaling, indicating that this protein is important for the observed responses. Furthermore, we provide evidence that LecRK-I.1 functions in the same signaling pathway as LecRK-I.8. Altogether, our results show that the response to eggs of P. brassicae is controlled by multiple LecRKs.

Temporal dynamics of QTL effects on vegetative growth in Arabidopsis thaliana

We assessed early vegetative growth in a population of 382 accessions of Arabidopsis thaliana using automated non-invasive high-throughput phenotyping. All accessions were imaged daily from 7 d to 18 d after sowing in three independent experiments and genotyped using the Affymetrix 250k SNP array. Projected leaf area (PLA) was derived from image analysis and used to calculate relative growth rates (RGRs). In addition, initial seed size was determined. The generated datasets were used jointly for a genome-wide association study that identified 238 marker-trait associations (MTAs) individually explaining up to 8% of the total phenotypic variation. Co-localization of MTAs occurred at 33 genomic positions. At 21 of these positions, sequential co-localization of MTAs for 2-9 consecutive days was observed. The detected MTAs for PLA and RGR could be grouped according to their temporal expression patterns, emphasizing that temporal variation of MTA action can be observed even during the vegetative growth phase, a period of continuous formation and enlargement of seemingly similar rosette leaves. This indicates that causal genes may be differentially expressed in successive periods. Analyses of the temporal dynamics of biological processes are needed to gain important insight into the molecular mechanisms of growth-controlling processes in plants.

AtMAD: Arabidopsis thaliana multi-omics association database

Integration analysis of multi-omics data provides a comprehensive landscape for understanding biological systems and mechanisms. The abundance of high-quality multi-omics data (genomics, transcriptomics, methylomics and phenomics) for the model organism Arabidopsis thaliana enables scientists to study the genetic mechanism of many biological processes. However, no resource is available to provide comprehensive and systematic multi-omics associations for Arabidopsis. Here, we developed an Arabidopsis thaliana Multi-omics Association Database (AtMAD, http://www.megabionet.org/atmad), a public repository for large-scale measurements of associations between genome, transcriptome, methylome, pathway and phenotype in Arabidopsis, designed for facilitating identification of eQTL, emQTL, Pathway-mQTL, Phenotype-pathway, GWAS, TWAS and EWAS. Candidate variants/methylations/genes were identified in AtMAD for specific phenotypes or biological processes, many of them are supported by experimental evidence. Based on the multi-omics association strategy, we have identified 11 796 cis-eQTLs and 10 119 trans-eQTLs. Among them, 68 837 environment-eQTL associations and 149 622 GWAS-eQTL associations were identified and stored in AtMAD. For expression–methylation quantitative trait loci (emQTL), we identified 265 776 emQTLs and 122 344 pathway-mQTLs. For TWAS and EWAS, we obtained 62 754 significant phenotype-gene associations and 3 993 379 significant phenotype-methylation associations, respectively. Overall, the multi-omics associated network in AtMAD will provide new insights into exploring biological mechanisms of plants at multi-omics levels.

Natural variation in temperature-modulated immunity uncovers transcription factor bHLH059 as a thermoresponsive regulator in Arabidopsis thaliana

Temperature impacts plant immunity and growth but how temperature intersects with endogenous pathways to shape natural variation remains unclear. Here we uncover variation between Arabidopsis thaliana natural accessions in response to two non-stress temperatures (22°C and 16°C) affecting accumulation of the thermoresponsive stress hormone salicylic acid (SA) and plant growth. Analysis of differentially responding A. thaliana accessions shows that pre-existing SA provides a benefit in limiting infection by Pseudomonas syringae pathovar tomato DC3000 bacteria at both temperatures. Several A. thaliana genotypes display a capacity to mitigate negative effects of high SA on growth, indicating within-species plasticity in SA—growth tradeoffs. An association study of temperature x SA variation, followed by physiological and immunity phenotyping of mutant and over-expression lines, identifies the transcription factor bHLH059 as a temperature-responsive SA immunity regulator. Here we reveal previously untapped diversity in plant responses to temperature and a way forward in understanding the genetic architecture of plant adaptation to changing environments.

Temperature has a profound effect on plant innate immune responses but little is known about the mechanisms underlying natural variation in transmission of temperature signals to defence pathways. Much of our understanding of temperature effects on plant immunity and tradeoffs between activated defences and growth has come from analysis of the common Arabidopsis thaliana genetic accession, Col-0. Here we examine A. thaliana genetic variation in response to temperature (within the non-stress range—22 ^oC and 16 ^oC) at the level of accumulation of the thermoresponsive biotic stress hormone salicylic acid (SA), bacterial pathogen resistance, and plant biomass. From analysis of 105 genetically diverse A. thaliana accessions we uncover plasticity in temperature-modulated SA homeostasis and in the relationship between SA levels and plant growth. We find that high SA amounts prior to infection provide a robust benefit of enhancing bacterial resistance. In some accessions this benefit comes without compromised plant growth, suggestive of altered defence–growth tradeoffs. Based on a temperature x SA association study we identify the transcription factor gene, bHLH059, and show that it has features of a temperature-sensitive immunity regulator that are unrelated to PIF4, a known thermosensitive coordinator of immunity and growth.

Metabolomic Analysis of Natural Variation in Arabidopsis

Methodological advances in coupled-mass spectrometry (gas chromatography and liquid chromatography; GC-MS and LC-MS) have rendered the profiling of highly complex plant extracts relatively facile and allowed that their high-throughput use aids the investigation of a range of biological questions. Among these is the elucidation of the genetic factors underlying metabolite abundance. For this purpose genome-wide association studies (GWAS) are being widely adopted in Arabidopsis with the resultant quantitative trait loci being subjected to cross-validation by the use of recombinant inbred lines, introgression lines, and T-DNA insertional knockout lines.

Expression genome-wide association study identifies that phosphatidylinositol-derived signalling regulates ALUMINIUM SENSITIVE3 expression under aluminium stress in the shoots of Arabidopsis thaliana

To identify unknown regulatory mechanisms leading to aluminium (Al)-induction of the Al tolerance gene ALS3, we conducted an expression genome-wide association study (eGWAS) for ALS3 in the shoots of 95 Arabidopsis thaliana accessions in the presence of Al. The eGWAS was conducted using a mixed linear model with 145,940 genome-wide single nucleotide polymorphisms (SNPs) and the association results were validated using reverse genetics. We found that many SNPs from the eGWAS were associated with genes related to phosphatidylinositol metabolism as well as stress signal transduction, including Ca²⁺signals, inter-connected in a co-expression network. Of these, PLC9, CDPK32, ANAC071, DIR1, and a hypothetical protein (AT4G10470) possessed amino acid sequence/ gene expression level polymorphisms that were significantly associated with ALS3 expression level variation. Furthermore, T-DNA insertion mutants of PLC9, CDPK32, and ANAC071 suppressed shoot ALS3 expression in the presence of Al. This study clarified the regulatory mechanisms of ALS3 expression in the shoot and provided genetic evidence of the involvement of phosphatidylinositol-derived signal transduction under Al stress.

Genome-Wide Association Studies and Transcriptome Changes during Acclimation and Deacclimation in Divergent Brassica napus Varieties

Information concerning genes and signals regulating cold acclimation processes in plants is abundant; however, less is known about genes and signals regulating the deacclimation process. A population of primarily winter B. napus varieties was used to conduct a genome-wide association study and to compare the transcriptomes from two winter B. napus varieties showing time-dependent differences in response to cold acclimation and deacclimation treatments. These studies helped to identify loci, candidate genes, and signaling processes impacting deacclimation in B. napus. GWAS identified polymorphisms at five different loci associated with freezing tolerance following deacclimation. Local linkage decay rates near these polymorphisms identified 38 possible candidate genes. Several of these genes have been reported as differentially regulated by cold stress in arabidopsis (Arabidopsis thaliana), including a calcium-binding EF-hand family protein (encoded by BnaCnng10250D) that was also differentially expressed during deacclimation in this study. Thousands of other genes differentially expressed during the acclimation and deacclimation treatments implicated processes involving oxidative stress, photosynthesis, light-regulated diurnal responses, and growth regulation. Generally, responses observed during acclimation were reversed within one week of deacclimation. The primary differences between the two winter B. napus varieties with differential deacclimation responses involved protection from oxidative stress and the ability to maintain photosynthesis.

Molecular variation in a functionally divergent homolog of FCA regulates flowering time in Arabidopsis thaliana

The identification and functional characterization of natural variants in plants are essential for understanding phenotypic adaptation. Here we identify a molecular variation in At2g47310 that contributes to the natural variation in flowering time in Arabidopsis thaliana accessions. This gene, which we term SISTER of FCA (SSF), functions in an antagonistic manner to its close homolog FCA. Genome-wide association analysis screens two major haplotypes of SSF associated with the natural variation in FLC expression, and a single polymorphism, SSF-N414D, is identified as a main contributor. The SSF414N protein variant interacts more strongly with CUL1, a component of the E3 ubiquitination complex, than the SSF414D form, mediating differences in SSF protein degradation and FLC expression. FCA and SSF appear to have arisen through gene duplication after dicot-monocot divergence, with the SSF-N414D polymorphism emerging relatively recently within A. thaliana. This work provides a good example for deciphering the functional importance of natural polymorphisms in different organisms.

Natural variation represents valuable source for gene discovery. Here, the authors show that a homolog of Flowering Control Locus A (FCA) functions in an antagonistic manner to FCA in regulating Arabidopsis flowering time through interacting with CUL1-E3 and modulating FLC expression.

Genome-Wide Association Studies in Arabidopsis thaliana: Statistical Analysis and Network-Based Augmentation of Signals

Genome-wide association studies (GWAS) have proven effective at identifying genetic variants and genes that are associated with phenotypes in humans, animals, and plants. Since most phenotypes of plant species are complex traits regulated by many genes and their functional interactions, GWAS are increasing in popularity for genetic dissections of plant phenotypes. For the reference plant, Arabidopsis thaliana, detailed information on genetic variations became available with the completion of the 1001 Genomes Project, enabling highly resolved association mapping between chromosomal loci and complex traits. Improvements have been made in the statistical analysis methods for testing the significance of genotype-to-phenotype associations, thereby substantially reducing the confounding effects of population structures. Furthermore, there have been large efforts toward post-GWAS augmentation of signals via integration with other types of information to overcome the limited statistical power of GWAS. This chapter describes the stepwise procedure of GWAS in Arabidopsis, focusing on data analysis processes including preprocessing of genotype and phenotype data, statistical analysis to identify phenotype-associated chromosomal loci, identification of phenotype-associated genes based on the phenotype-associated loci, and finally network-based augmentation of GWAS signals to identify additional candidate genes for the phenotype.

Probing natural variation of IRE1 expression and endoplasmic reticulum stress responses in Arabidopsis accessions

The environmental effects shape genetic changes in the individuals within plant populations, which in turn contribute to the enhanced genetic diversity of the population as a whole. Thus, individuals within the same species can acquire and accumulate genetic differences in their genomes depending on their local environment and evolutionary history. IRE1 is a universal endoplasmic reticulum (ER) stress sensor that activates an evolutionarily conserved signalling cascade in response to biotic and abiotic stresses. Here, we selected nine different Arabidopsis accessions along with the reference ecotype Columbia-0, based on their geographical origins and differential endogenous IRE1 expression under steady-state conditions to investigate the natural variation of ER stress responses. We cloned and analysed selected upstream regulatory regions of IRE1a and IRE1b, which revealed differential levels of their inducibility. We also subjected these accessions to an array of biotic and abiotic stresses including heat, ER stress-inducing chemical tunicamycin, phytohormone salicylic acid, and pathogen infection. We measured IRE1-mediated splicing of its evolutionarily conserved downstream client as well as transcript accumulation of ER-resident chaperones and co-chaperones. Collectively, our results illustrate the expression polymorphism of a major plant stress receptor and its relationship with molecular and physiological ER stress sensitivity.

A Nested Association Mapping Panel in Arabidopsis thaliana for Mapping and Characterizing Genetic Architecture

Linkage and association mapping populations are crucial public resources that facilitate the characterization of trait genetic architecture in natural and agricultural systems. We define a large nested association mapping panel (NAM) from 14 publicly available recombinant inbred line populations (RILs) of Arabidopsis thaliana, which share a common recurrent parent (Col-0). Using a genotype-by-sequencing approach (GBS), we identified single nucleotide polymorphisms (SNPs; range 563-1525 per population) and subsequently built updated linkage maps in each of the 14 RIL sets. Simulations in individual RIL populations indicate that our GBS markers have improved power to detect small effect QTL and enhanced resolution of QTL support intervals in comparison to original linkage maps. Using these robust linkage maps, we imputed a common set of publicly available parental SNPs into each RIL linkage map, generating overlapping markers across all populations. Though ultimately depending on allele frequencies at causal loci, simulations of the NAM panel suggest that surveying between 4 to 7 of the 14 RIL populations provides high resolution of the genetic architecture of complex traits, relative to a single mapping population.

Identification of novel seed longevity genes related to oxidative stress and seed coat by genome-wide association studies and reverse genetics

Seed longevity is a polygenic trait of relevance for agriculture and for understanding the effect of environment on the ageing of biological systems. In order to identify novel longevity genes, we have phenotyped the natural variation of 270 ecotypes of the model plant, Arabidopsis thaliana, for natural ageing and for three accelerated ageing methods. Genome-wide analysis, using publicly available single-nucleotide polymorphisms (SNPs) data sets, identified multiple genomic regions associated with variation in seed longevity. Reverse genetics of 20 candidate genes in Columbia ecotype resulted in seven genes positive for seed longevity (PSAD1, SSLEA, SSTPR, DHAR1, CYP86A8, MYB47 and SPCH) and five negative ones (RBOHD, RBOHE, RBOHF, KNAT7 and SEP3). In this uniform genetic background, natural and accelerated ageing methods provided similar results for seed-longevity in knock-out mutants. The NADPH oxidases (RBOHs), the dehydroascorbate reductase (DHAR1) and the photosystem I subunit (PSAD1) highlight the important role of oxidative stress on seed ageing. The cytochrome P-450 hydroxylase, CYP86A8, and the transcription factors, MYB47, KNAT7 and SEP3, support the protecting role of the seed coat during seed ageing.

Identification of Genes Conferring Plant Salt Tolerance using GWAS: Current Success and Perspectives

An understanding of the molecular mechanisms that underlie plant salt tolerance is important for both economic and scientific interests. Genome-wide association study (GWAS) is a promising approach to pinpoint genes that confer plant salt tolerance. With the advancement of supporting technology and methodology, GWAS has enabled the discovery of genes that play central roles in regulating plant salt tolerance in the past decade. Here, I highlight recent successful GWAS work in unveiling the molecular factors underlying plant salt tolerance and discuss the concerns and opportunities in conducting such experiments. It is anticipated that GWAS will be increasingly successful in the identification of key genes that are useful for crop improvement.

A single-population GWAS identified AtMATE expression level polymorphism caused by promoter variants is associated with variation in aluminum tolerance in a local Arabidopsis population

Organic acids (OA) are released from roots in response to aluminum (Al), conferring an Al tolerance to plants that is regulated by OA transporters such as ALMT (Al-activated malate transporter) and multi-drug and toxic compound extrusion (MATE). We have previously reported that the expression level polymorphism (ELP) of AtALMT1 is strongly associated with variation in Al tolerance among natural accessions of Arabidopsis. However, although AtMATE is also expressed following Al exposure and contributes to Al tolerance, whether AtMATE contributes to the variation of Al tolerance and the molecular mechanisms of ELP remains unclear. Here, we dissected the natural variation in AtMATE expression level in response to Al at the root using diverse natural accessions of Arabidopsis. Phylogenetic analysis revealed that more than half of accessions belonging to the Central Asia (CA) population show markedly low AtMATE expression levels, while the majority of European populations show high expression levels. The accessions of the CA population with low AtMATE expression also show significantly weakened Al tolerance. A single-population genome-wide association study (GWAS) of AtMATE expression in the CA population identified a retrotransposon insertion in the AtMATE promoter region associated with low gene expression levels. This may affect the transcriptional regulation of AtMATE by disrupting the effect of a cis-regulatory element located upstream of the insertion site, which includes AtSTOP1 (sensitive to proton rhizotoxicity 1) transcription factor-binding sites revealed by chromatin immunoprecipitation-qPCR analysis. Furthermore, the GWAS performed without the accessions expressing low levels of AtMATE, excluding the effect of AtMATE promoter polymorphism, identified several candidate genes potentially associated with AtMATE expression.

Natural variation of photosynthetic efficiency in Arabidopsis thaliana accessions under low temperature conditions

Low, but non-freezing, temperatures have negative effects on plant growth and development. Despite some molecular signalling pathways being known, the mechanisms causing different responses among genotypes are still poorly understood. Photosynthesis is one of the processes that are affected by low temperatures. Using an automated phenotyping platform for chlorophyll fluorescence imaging the steady state quantum yield of photosystem II (PSII) electron transport (Φ_PSII ) was measured and used to quantify the effect of moderately low temperature on a population of Arabidopsis thaliana natural accessions. Observations were made over the course of several weeks in standard and low temperature conditions and a strong decrease in Φ_PSII upon the cold treatment was found. A genome wide association study identified several quantitative trait loci (QTLs) that are associated with changes in Φ_PSII in low temperature. One candidate for a cold specific QTL was validated with a mutant analysis to be one of the genes that is likely involved in the PSII response to the cold treatment. The gene encodes the PSII associated protein PSB27 which has already been implicated in the adaptation to fluctuating light.

The Root Foraging Response under Low Nitrogen Depends on DWARF1-Mediated Brassinosteroid Biosynthesis

Root developmental plasticity enables plants to adapt to limiting or fluctuating nutrient conditions in the soil. When grown under nitrogen (N) deficiency, plants develop a more exploratory root system by increasing primary and lateral root length. However, mechanisms underlying this so-called foraging response remain poorly understood. We performed a genome-wide association study in Arabidopsis (Arabidopsis thaliana) and we show here that noncoding variations of the brassinosteroid (BR) biosynthesis gene DWARF1 (DWF1) lead to variation of the DWF1 transcript level that contributes to natural variation of root elongation under low N. In addition to DWF1, other central BR biosynthesis genes upregulated under low N include CONSTITUTIVE PHOTOMORPHOGENIC DWARF, DWF4, and BRASSINOSTEROID-6-OXIDASE 2 Phenotypic characterization of knockout and knockdown mutants of these genes showed significant reduction of their root elongation response to low N, suggesting a systemic stimulation of BR biosynthesis to promote root elongation. Moreover, we show that low N-induced root elongation is associated with aboveground N content and that overexpression of DWF1 significantly improves plant growth and overall N accumulation. Our study reveals that mild N deficiency induces key genes in BR biosynthesis and that natural variation in BR synthesis contributes to the root foraging response, complementing the impact of enhanced BR signaling observed recently. Furthermore, these results suggest a considerable potential of BR biosynthesis to genetically engineer plants with improved N uptake.

Rapid identification of an Arabidopsis NLR gene as a candidate conferring susceptibility to Sclerotinia sclerotiorum using time-resolved automated phenotyping

The broad host range necrotrophic fungus Sclerotinia sclerotiorum is a devastating pathogen of many oil and vegetable crops. Plant genes conferring complete resistance against S. sclerotiorum have not been reported. Instead, plant populations challenged by S. sclerotiorum exhibit a continuum of partial resistance designated as quantitative disease resistance (QDR). Because of their complex interplay and their small phenotypic effect, the functional characterization of QDR genes remains limited. How broad host range necrotrophic fungi manipulate plant programmed cell death is for instance largely unknown. Here, we designed a time-resolved automated disease phenotyping pipeline enabling high-throughput disease lesion measurement with high resolution, low footprint at low cost. We could accurately recover contrasted disease responses in several pathosystems using this system. We used our phenotyping pipeline to assess the kinetics of disease symptoms caused by seven S. sclerotiorum isolates on six A. thaliana natural accessions with unprecedented resolution. Large effect polymorphisms common to the most resistant A. thaliana accessions identified highly divergent alleles of the nucleotide-binding site leucine-rich repeat gene LAZ5 in the resistant accessions Rubezhnoe and Lip-0. We show that impaired LAZ5 expression in laz5.1 mutant lines and in A. thaliana Rub natural accession correlate with enhanced QDR to S. sclerotiorum. These findings illustrate the value of time-resolved image-based phenotyping for unravelling the genetic bases of complex traits such as QDR. Our results suggest that S. sclerotiorum manipulates plant sphingolipid pathways guarded by LAZ5 to trigger programmed cell death and cause disease.

Adaptive reduction of male gamete number in the selfing plant Arabidopsis thaliana

The number of male gametes is critical for reproductive success and varies between and within species. The evolutionary reduction of the number of pollen grains encompassing the male gametes is widespread in selfing plants. Here, we employ genome-wide association study (GWAS) to identify underlying loci and to assess the molecular signatures of selection on pollen number-associated loci in the predominantly selfing plant Arabidopsis thaliana. Regions of strong association with pollen number are enriched for signatures of selection, indicating polygenic selection. We isolate the gene REDUCED POLLEN NUMBER1 (RDP1) at the locus with the strongest association. We validate its effect using a quantitative complementation test with CRISPR/Cas9-generated null mutants in nonstandard wild accessions. In contrast to pleiotropic null mutants, only pollen numbers are significantly affected by natural allelic variants. These data support theoretical predictions that reduced investment in male gametes is advantageous in predominantly selfing species.

AthCNV: A Map of DNA Copy Number Variations in the Arabidopsis Genome

Copy number variations (CNVs) greatly contribute to intraspecies genetic polymorphism and phenotypic diversity. Recent analyses of sequencing data for >1000 Arabidopsis (Arabidopsis thaliana) accessions focused on small variations and did not include CNVs. Here, we performed genome-wide analysis and identified large indels (50 to 499 bp) and CNVs (500 bp and larger) in these accessions. The CNVs fully overlap with 18.3% of protein-coding genes, with enrichment for evolutionarily young genes and genes involved in stress and defense. By combining analysis of both genes and transposable elements (TEs) affected by CNVs, we revealed that the variation statuses of genes and TEs are tightly linked and jointly contribute to the unequal distribution of these elements in the genome. We also determined the gene copy numbers in a set of 1060 accessions and experimentally validated the accuracy of our predictions by multiplex ligation-dependent probe amplification assays. We then successfully used the CNVs as markers to analyze population structure and migration patterns. Finally, we examined the impact of gene dosage variation triggered by a CNV spanning the SEC10 gene on SEC10 expression at both the transcript and protein levels. The catalog of CNVs, CNV-overlapping genes, and their genotypes in a top model dicot will stimulate the exploration of the genetic basis of phenotypic variation.

mGWAS Uncovers Gln-Glucosinolate Seed-Specific Interaction and its Role in Metabolic Homeostasis

Gln is a key player in plant metabolism. It is one of the major free amino acids that is transported into the developing seed and is central for nitrogen metabolism. However, Gln natural variation and its regulation and interaction with other metabolic processes in seeds remain poorly understood. To investigate the latter, we performed a metabolic genome-wide association study (mGWAS) of Gln-related traits measured from the dry seeds of the Arabidopsis (Arabidopsis thaliana) diversity panel using all potential ratios between Gln and the other members of the Glu family as traits. This semicombinatorial approach yielded multiple candidate genes that, upon further analysis, revealed an unexpected association between the aliphatic glucosinolates (GLS) and the Gln-related traits. This finding was confirmed by an independent quantitative trait loci mapping and statistical analysis of the relationships between the Gln-related traits and the presence of specific GLS in seeds. Moreover, an analysis of Arabidopsis mutants lacking GLS showed an extensive seed-specific impact on Gln levels and composition that manifested early in seed development. The elimination of GLS in seeds was associated with a large effect on seed nitrogen and sulfur homeostasis, which conceivably led to the Gln response. This finding indicates that both Gln and GLS play key roles in shaping the seed metabolic homeostasis. It also implies that select secondary metabolites might have key functions in primary seed metabolism. Finally, our study shows that an mGWAS performed on dry seeds can uncover key metabolic interactions that occur early in seed development.

Integrating molecular markers into metabolic models improves genomic selection for Arabidopsis growth

The current trends of crop yield improvements are not expected to meet the projected rise in demand. Genomic selection uses molecular markers and machine learning to identify superior genotypes with improved traits, such as growth. Plant growth directly depends on rates of metabolic reactions which transform nutrients into the building blocks of biomass. Here, we predict growth of Arabidopsis thaliana accessions by employing genomic prediction of reaction rates estimated from accession-specific metabolic models. We demonstrate that, comparing to classical genomic selection on the available data sets for 67 accessions, our approach improves the prediction accuracy for growth within and across nitrogen environments by 32.6% and 51.4%, respectively, and from optimal nitrogen to low carbon environment by 50.4%. Therefore, integration of molecular markers into metabolic models offers an approach to predict traits directly related to metabolism, and its usefulness in breeding can be examined by gathering matching datasets in crops.

An increase in genomic selection (GS) accuracy can accelerate genetic gain by shortening the breeding cycles. Here, the authors introduce a network-based GS method that uses metabolic models and improves the prediction accuracy of Arabidopsis growth within and across environments.

Epigenetic Variation at a Genomic Locus Affecting Biomass Accumulation under Low Nitrogen in Arabidopsis thaliana

Nitrogen (N) is a macronutrient determining crop yield. The application of N fertilisers can substantially increase the yield, but excess use also causes the nitrate pollution of water resources and increases production costs. Increasing N use efficiency (NUE) in crop plants is an important step to implement low-input agricultural systems. We used Arabidopsis thaliana as model system to investigate the natural genetic diversity in traits related to NUE. Natural variation was used to study adaptive growth patterns and changes in gene expression associated with limited nitrate availability. A genome-wide association study revealed an association of eight SNP markers on Chromosome 1 with shoot growth under limited N. The identified linkage disequilibrium (LD) interval includes the DNA sequences of three cysteine/histidine-rich C1 domain proteins in tandem orientation. These genes differ in promoter structure, methylation pattern and expression level among accessions, correlating with growth performance under N deficiency. Our results suggest the involvement of epigenetic regulation in the expression of NUE-related traits.

Imputation of 3 million SNPs in the Arabidopsis regional mapping population

Natural variation has become a prime resource to identify genetic variants that contribute to phenotypic variation. The regional mapping (RegMap) population is one of the most important populations for studying natural variation in Arabidopsis thaliana, and has been used in a large number of association studies and in studies on climatic adaptation. However, only 413 RegMap accessions have been completely sequenced, as part of the 1001 Genomes (1001G) Project, while the remaining 894 accessions have only been genotyped with the Affymetrix 250k chip. As a consequence, most association studies involving the RegMap are either restricted to the sequenced accessions, reducing power, or rely on a limited set of SNPs. Here we impute millions of SNPs to the 894 accessions that are exclusive to the RegMap, using the 1135 accessions of the 1001G Project as the reference panel. We assess imputation accuracy using a novel cross-validation scheme, which we show provides a more reliable measure of accuracy than existing methods. After filtering out low accuracy SNPs, we obtain high-quality genotypic information for 2029 accessions and 3 million markers. To illustrate the benefits of these imputed data, we reconducted genome-wide association studies on five stress-related traits and could identify novel candidate genes.

Genome-Wide Association Study and Genomic Prediction Elucidate the Distinct Genetic Architecture of Aluminum and Proton Tolerance in Arabidopsis thaliana

Under acid soil conditions, Al stress and proton stress can occur, reducing root growth and function. However, these stressors are distinct, and tolerance to each is governed by multiple physiological processes. To better understand the genes that underlie these coincidental but experimentally separable stresses, a genome-wide association study (GWAS) and genomic prediction (GP) models were created for approximately 200 diverse Arabidopsis thaliana accessions. GWAS and genomic prediction identified 140/160 SNPs associated with Al and proton tolerance, respectively, which explained approximately 70% of the variance observed. Reverse genetics of the genes in loci identified novel Al and proton tolerance genes, including TON1-RECRUITING MOTIF 28 (AtTRM28) and THIOREDOXIN H-TYPE 1 (AtTRX1), as well as genes known to be associated with tolerance, such as the Al-activated malate transporter, AtALMT1. Additionally, variation in Al tolerance was partially explained by expression level polymorphisms of AtALMT1 and AtTRX1 caused by cis-regulatory allelic variation. These results suggest that we successfully identified the loci that regulate Al and proton tolerance. Furthermore, very small numbers of loci were shared by Al and proton tolerance as determined by the GWAS. There were substantial differences between the phenotype predicted by genomic prediction and the observed phenotype for Al tolerance. This suggested that the GWAS-undetectable genetic factors (e.g., rare-allele mutations) contributing to the variation of tolerance were more important for Al tolerance than for proton tolerance. This study provides important new insights into the genetic architecture that produces variation in the tolerance of acid soil.