The benefits of permutation-based genome-wide association studies.

Linear mixed models (LMMs) are a commonly used method for genome-wide association studies (GWAS) that aim to detect associations between genetic markers and phenotypic measurements in a population of individuals while accounting for population structure and cryptic relatedness. In a standard GWAS, hundreds of thousands to millions of statistical tests are performed, requiring control for multiple hypothesis testing. Typically, static corrections that penalize the number of tests performed are used to control for the family-wise error rate, which is the probability of making at least one false positive. However, it has been shown that in practice this threshold is too conservative for normally distributed phenotypes and not stringent enough for non-normally distributed phenotypes. Therefore, permutation-based LMM approaches have recently been proposed to provide a more realistic threshold that takes phenotypic distributions into account. In this work, we discuss the advantages of permutation-based GWAS approaches, including new simulations and results from a re-analysis of all publicly available Arabidopsis phenotypes from the AraPheno database.

Efficient permutation-based genome-wide association studies for normal and skewed phenotypic distributions.

MOTIVATION: Genome-wide association studies (GWAS) are an integral tool for studying the architecture of complex genotype and phenotype relationships. Linear mixed models (LMMs) are commonly used to detect associations between genetic markers and a trait of interest, while at the same time allowing to account for population structure and cryptic relatedness. Assumptions of LMMs include a normal distribution of the residuals and that the genetic markers are independent and identically distributed-both assumptions are often violated in real data. Permutation-based methods can help to overcome some of these limitations and provide more realistic thresholds for the discovery of true associations. Still, in practice, they are rarely implemented due to the high computational complexity. RESULTS: We propose permGWAS, an efficient LMM reformulation based on 4D tensors that can provide permutation-based significance thresholds. We show that our method outperforms current state-of-the-art LMMs with respect to runtime and that permutation-based thresholds have lower false discovery rates for skewed phenotypes compared to the commonly used Bonferroni threshold. Furthermore, using permGWAS we re-analyzed more than 500 Arabidopsis thaliana phenotypes with 100 permutations each in less than 8 days on a single GPU. Our re-analyses suggest that applying a permutation-based threshold can improve and refine the interpretation of GWAS results. AVAILABILITY AND IMPLEMENTATION: permGWAS is open-source and publicly available on GitHub for download: https://github.com/grimmlab/permGWAS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Natural variation of warm temperature-induced raffinose accumulation identifies TREHALOSE-6-PHOSPHATE SYNTHASE 1 as a modulator of thermotolerance.

High-temperature stress limits plant growth and reproduction. Exposure to high temperature, however, also elicits a physiological response, which protects plants from the damage evoked by heat. This response involves a partial reconfiguration of the metabolome including the accumulation of the trisaccharide raffinose. In this study, we explored the intraspecific variation of warm temperature-induced raffinose accumulation as a metabolic marker for temperature responsiveness with the aim to identify genes that contribute to thermotolerance. By combining raffinose measurements in 250 Arabidopsis thaliana accessions following a mild heat treatment with genome-wide association studies, we identified five genomic regions that were associated with the observed trait variation. Subsequent functional analyses confirmed a causal relationship between TREHALOSE-6-PHOSPHATE SYNTHASE 1 (TPS1) and warm temperature-dependent raffinose synthesis. Moreover, complementation of the tps1-1 null mutant with functionally distinct TPS1 isoforms differentially affected carbohydrate metabolism under more severe heat stress. While higher TPS1 activity was associated with reduced endogenous sucrose levels and thermotolerance, disruption of trehalose 6-phosphate signalling resulted in higher accumulation of transitory starch and sucrose and was associated with enhanced heat resistance. Taken together, our findings suggest a role of trehalose 6-phosphate in thermotolerance, most likely through its regulatory function in carbon partitioning and sucrose homoeostasis.

Functional variation in the non-coding genome: molecular implications for food security.

The growing world population, in combination with the anticipated effects of climate change, is pressuring food security. Plants display an impressive arsenal of cellular mechanisms conferring resilience to adverse environmental conditions, and humans rely on these mechanisms for stable food production. The elucidation of the molecular basis of the mechanisms used by plants to achieve resilience promises knowledge-based approaches to enhance food security. DNA sequence polymorphisms can reveal genomic regions that are linked to beneficial traits of plants. However, our ability to interpret how a given DNA sequence polymorphism confers a fitness advantage at the molecular level often remains poor. A key factor is that these polymorphisms largely localize to the enigmatic non-coding genome. Here, we review the functional impact of sequence variations in the non-coding genome on plant biology in the context of crop breeding and agricultural traits. We focus on examples of non-coding with particularly convincing functional support. Our survey combines findings that are consistent with the view that the non-coding genome contributes to cellular mechanisms assisting many plant traits. Understanding how DNA sequence polymorphisms in the non-coding genome shape plant traits at the molecular level offers a largely unexplored reservoir of solutions to address future challenges in plant growth and resilience.

Genetic mapping of the early responses to salt stress in Arabidopsis thaliana.

Salt stress decreases plant growth prior to significant ion accumulation in the shoot. However, the processes underlying this rapid reduction in growth are still unknown. To understand the changes in salt stress responses through time and at multiple physiological levels, examining different plant processes within a single set-up is required. Recent advances in phenotyping has allowed the image-based estimation of plant growth, morphology, colour and photosynthetic activity. In this study, we examined the salt stress-induced responses of 191 Arabidopsis accessions from 1 h to 7 days after treatment using high-throughput phenotyping. Multivariate analyses and machine learning algorithms identified that quantum yield measured in the light-adapted state (Fv' /Fm' ) greatly affected growth maintenance in the early phase of salt stress, whereas the maximum quantum yield (QYmax ) was crucial at a later stage. In addition, our genome-wide association study (GWAS) identified 770 loci that were specific to salt stress, in which two loci associated with QYmax and Fv' /Fm' were selected for validation using T-DNA insertion lines. We characterized an unknown protein kinase found in the QYmax locus that reduced photosynthetic efficiency and growth maintenance under salt stress. Understanding the molecular context of the candidate genes identified will provide valuable insights into the early plant responses to salt stress. Furthermore, our work incorporates high-throughput phenotyping, multivariate analyses and GWAS, uncovering details of temporal stress responses and identifying associations across different traits and time points, which are likely to constitute the genetic components of salinity tolerance.

Global Genetic Heterogeneity in Adaptive Traits.

Understanding the genetic architecture of complex traits is a major objective in biology. The standard approach for doing so is genome-wide association studies (GWAS), which aim to identify genetic polymorphisms responsible for variation in traits of interest. In human genetics, consistency across studies is commonly used as an indicator of reliability. However, if traits are involved in adaptation to the local environment, we do not necessarily expect reproducibility. On the contrary, results may depend on where you sample, and sampling across a wide range of environments may decrease the power of GWAS because of increased genetic heterogeneity. In this study, we examine how sampling affects GWAS in the model plant species Arabidopsis thaliana. We show that traits like flowering time are indeed influenced by distinct genetic effects in local populations. Furthermore, using gene expression as a molecular phenotype, we show that some genes are globally affected by shared variants, whereas others are affected by variants specific to subpopulations. Remarkably, the former are essentially all cis-regulated, whereas the latter are predominately affected by trans-acting variants. Our result illustrate that conclusions about genetic architecture can be extremely sensitive to sampling and population structure.

cis-prenyltransferase 3 and α/ß-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/ß-hydrolase-is experimentally confirmed. These data will help to generate Dol-enriched plants which might serve as a remedy for Dol-deficiency in humans.

AraPheno and the AraGWAS Catalog 2020: a major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana.

Genome-wide association studies (GWAS) are integral for studying genotype-phenotype relationships and gaining a deeper understanding of the genetic architecture underlying trait variation. A plethora of genetic associations between distinct loci and various traits have been successfully discovered and published for the model plant Arabidopsis thaliana. This success and the free availability of full genomes and phenotypic data for more than 1,000 different natural inbred lines led to the development of several data repositories. AraPheno (https://arapheno.1001genomes.org) serves as a central repository of population-scale phenotypes in A. thaliana, while the AraGWAS Catalog (https://aragwas.1001genomes.org) provides a publicly available, manually curated and standardized collection of marker-trait associations for all available phenotypes from AraPheno. In this major update, we introduce the next generation of both platforms, including new data, features and tools. We included novel results on associations between knockout-mutations and all AraPheno traits. Furthermore, AraPheno has been extended to display RNA-Seq data for hundreds of accessions, providing expression information for over 28 000 genes for these accessions. All data, including the imputed genotype matrix used for GWAS, are easily downloadable via the respective databases.

Systems genomics approaches provide new insights into Arabidopsis thaliana root growth regulation under combinatorial mineral nutrient limitation.

The molecular mechanisms by which plants modulate their root growth rate (RGR) in response to nutrient deficiency are largely unknown. Using Arabidopsis thaliana accessions, we analyzed RGR variation under combinatorial mineral nutrient deficiencies involving phosphorus (P), iron (Fe), and zinc (Zn). While -P stimulated early RGR of most accessions, -Fe or -Zn reduced it. The combination of either -P-Fe or -P-Zn led to suppression of the growth inhibition exerted by -Fe or -Zn alone. Surprisingly, root growth responses of the reference accession Columbia (Col-0) were not representative of the species under -P nor -Zn. Using a systems approach that combines GWAS, network-based candidate identification, and reverse genetic screen, we identified new genes that regulate root growth in -P-Fe: VIM1, FH6, and VDAC3. Our findings provide a framework to systematically identifying favorable allelic variations to improve root growth, and to better understand how plants sense and respond to multiple environmental cues.

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.

Natural allelic variation of the AZI1 gene controls root growth under zinc-limiting condition.

Zinc is an essential micronutrient for all living organisms and is involved in a plethora of processes including growth and development, and immunity. However, it is unknown if there is a common genetic and molecular basis underlying multiple facets of zinc function. Here we used natural variation in Arabidopsis thaliana to study the role of zinc in regulating growth. We identify allelic variation of the systemic immunity gene AZI1 as a key for determining root growth responses to low zinc conditions. We further demonstrate that this gene is important for modulating primary root length depending on the zinc and defence status. Finally, we show that the interaction of the immunity signal azelaic acid and zinc level to regulate root growth is conserved in rice. This work demonstrates that there is a common genetic and molecular basis for multiple zinc dependent processes and that nutrient cues can determine the balance of growth and immune responses in plants.

Genetic Components of Root Architecture Remodeling in Response to Salt Stress.

Salinity of the soil is highly detrimental to plant growth. Plants respond by a redistribution of root mass between main and lateral roots, yet the genetic machinery underlying this process is still largely unknown. Here, we describe the natural variation among 347 Arabidopsis thaliana accessions in root system architecture (RSA) and identify the traits with highest natural variation in their response to salt. Salt-induced changes in RSA were associated with 100 genetic loci using genome-wide association studies. Two candidate loci associated with lateral root development were validated and further investigated. Changes in CYP79B2 expression in salt stress positively correlated with lateral root development in accessions, and cyp79b2 cyp79b3 double mutants developed fewer and shorter lateral roots under salt stress, but not in control conditions. By contrast, high HKT1 expression in the root repressed lateral root development, which could be partially rescued by addition of potassium. The collected data and multivariate analysis of multiple RSA traits, available through the Salt_NV_Root App, capture root responses to salinity. Together, our results provide a better understanding of effective RSA remodeling responses, and the genetic components involved, for plant performance in stress conditions.

The AraGWAS Catalog: a curated and standardized Arabidopsis thaliana GWAS catalog.

The abundance of high-quality genotype and phenotype data for the model organism Arabidopsis thaliana enables scientists to study the genetic architecture of many complex traits at an unprecedented level of detail using genome-wide association studies (GWAS). GWAS have been a great success in A. thaliana and many SNP-trait associations have been published. With the AraGWAS Catalog (https://aragwas.1001genomes.org) we provide a publicly available, manually curated and standardized GWAS catalog for all publicly available phenotypes from the central A. thaliana phenotype repository, AraPheno. All GWAS have been recomputed on the latest imputed genotype release of the 1001 Genomes Consortium using a standardized GWAS pipeline to ensure comparability between results. The catalog includes currently 167 phenotypes and more than 222 000 SNP-trait associations with P < 10-4, of which 3887 are significantly associated using permutation-based thresholds. The AraGWAS Catalog can be accessed via a modern web-interface and provides various features to easily access, download and visualize the results and summary statistics across GWAS.

Leaf Growth Response to Mild Drought: Natural Variation in Arabidopsis Sheds Light on Trait Architecture.

Plant growth and crop yield are negatively affected by a reduction in water availability. However, a clear understanding of how growth is regulated under nonlethal drought conditions is lacking. Recent advances in genomics, phenomics, and transcriptomics allow in-depth analysis of natural variation. In this study, we conducted a detailed screening of leaf growth responses to mild drought in a worldwide collection of Arabidopsis thaliana accessions. The genetic architecture of the growth responses upon mild drought was investigated by subjecting the different leaf growth phenotypes to genome-wide association mapping and by characterizing the transcriptome of young developing leaves. Although no major effect locus was found to be associated with growth in mild drought, the transcriptome analysis delivered further insight into the natural variation of transcriptional responses to mild drought in a specific tissue. Coexpression analysis indicated the presence of gene clusters that co-vary over different genetic backgrounds, among others a cluster of genes with important regulatory functions in the growth response to osmotic stress. It was found that the occurrence of a mild drought stress response in leaves can be inferred with high accuracy across accessions based on the expression profile of 283 genes. A genome-wide association study on the expression data revealed that trans regulation seems to be more important than cis regulation in the transcriptional response to environmental perturbations.

AraPheno: a public database for Arabidopsis thaliana phenotypes.

Natural genetic variation makes it possible to discover evolutionary changes that have been maintained in a population because they are advantageous. To understand genotype-phenotype relationships and to investigate trait architecture, the existence of both high-resolution genotypic and phenotypic data is necessary. Arabidopsis thaliana is a prime model for these purposes. This herb naturally occurs across much of the Eurasian continent and North America. Thus, it is exposed to a wide range of environmental factors and has been subject to natural selection under distinct conditions. Full genome sequencing data for more than 1000 different natural inbred lines are available, and this has encouraged the distributed generation of many types of phenotypic data. To leverage these data for meta analyses, AraPheno (https://arapheno.1001genomes.org) provide a central repository of population-scale phenotypes for A. thaliana inbred lines. AraPheno includes various features to easily access, download and visualize the phenotypic data. This will facilitate a comparative analysis of the many different types of phenotypic data, which is the base to further enhance our understanding of the genotype-phenotype map.

Natural variation in stomata size contributes to the local adaptation of water-use efficiency in Arabidopsis thaliana.

Stomata control gas exchanges between the plant and the atmosphere. How natural variation in stomata size and density contributes to resolve trade-offs between carbon uptake and water loss in response to local climatic variation is not yet understood. We developed an automated confocal microscopy approach to characterize natural genetic variation in stomatal patterning in 330 fully sequenced Arabidopsis thaliana accessions collected throughout the European range of the species. We compared this to variation in water-use efficiency, measured as carbon isotope discrimination (δ13 C). We detect substantial genetic variation for stomata size and density segregating within Arabidopsis thaliana. A positive correlation between stomata size and δ13 C further suggests that this variation has consequences on water-use efficiency. Genome wide association analyses indicate a complex genetic architecture underlying not only variation in stomatal patterning but also to its covariation with carbon uptake parameters. Yet, we report two novel QTL affecting δ13 C independently of stomatal patterning. This suggests that, in A. thaliana, both morphological and physiological variants contribute to genetic variance in water-use efficiency. Patterns of regional differentiation and covariation with climatic parameters indicate that natural selection has contributed to shape some of this variation, especially in Southern Sweden, where water availability is more limited in spring relative to summer. These conditions are expected to favour the evolution of drought avoidance mechanisms over drought escape strategies.

Predicting Gene Regulatory Interactions Using Natural Genetic Variation.

Genome-wide association studies (GWAS) are a powerful tool to elucidate the genotype-phenotype map. Although GWAS are usually used to assess simple univariate associations between genetic markers and traits of interest, it is also possible to infer the underlying genetic architecture and to predict gene regulatory interactions. In this chapter, we describe the latest methods and tools to perform GWAS by calculating permutation-based significance thresholds. For this purpose, we first provide guidelines on univariate GWAS analyses that are extended in the second part of this chapter to more complex models that enable the inference of gene regulatory networks and how these networks vary.

Closely related receptor complexes differ in their ABA selectivity and sensitivity.

The recent discovery of a variety of receptors has led to new models for hormone perception in plants. In the case of the hormone abscisic acid (ABA), which regulates plant responses to abiotic stress, perception seems to occur both at the plasma membrane and in the cytosol. The cytosolic receptors for ABA have recently been identified as complexes between protein phosphatases 2C (PP2C) and regulatory components (RCAR/PYR/PYL) that bind ABA. Binding of ABA to the receptor complexes inactivates the PP2Cs, thereby activating the large variety of physiological processes regulated by ABA. The Arabidopsis genome encodes 13 homologues of RCAR1 and approximately 80 PP2Cs, of which six in clade A have been identified as negative regulators of ABA responses. In this study we characterize a novel member of the RCAR family, RCAR3. RCAR3 was identified in a screen for interactors of the PP2Cs ABI1 and ABI2, which are key regulators of ABA responses. RCAR3 was shown to repress ABI1 and ABI2 in vitro, and to stimulate ABA signalling in protoplast cells. RCAR3 conferred greater ABA sensitivity to the PP2C regulation than RCAR1, whereas stereo-selectivity for (S)-ABA was less stringent with RCAR3 as compared with RCAR1. In addition, regulation of the protein phosphatase activity by RCAR1 and RCAR3 was more sensitive to ABA for ABI1 than for ABI2. Based on the differences we have observed in transcriptional regulation and biochemical properties, we propose a model whereby differential expression of the co-receptors and combinatorial assembly of the receptor complexes act in concert to modulate and fine-tune ABA responses.

Getting the metabolites right.

A study of almost 800 Arabidopsis thaliana plants from across Europe reveals how the environment and evolutionary pressures shape their metabolites.

Plant roots employ cell-layer-specific programs to respond to pathogenic and beneficial microbes.

Plant roots are built of concentric cell layers that are thought to respond to microbial infections by employing specific, genetically defined programs. Yet, the functional impact of this radial organization remains elusive, particularly due to the lack of genome-wide techniques for monitoring expression at a cell-layer resolution. Here, cell-type-specific expression of tagged ribosomes enabled the isolation of ribosome-bound mRNA to obtain cell-layer translatomes (TRAP-seq, translating ribosome affinity purification and RNA sequencing). After inoculation with the vascular pathogen Verticillium longisporum, pathogenic oomycete Phytophthora parasitica, or mutualistic endophyte Serendipita indica, root cell-layer responses reflected the fundamentally different colonization strategies of these microbes. Notably, V. longisporum specifically suppressed the endodermal barrier, which restricts fungal progression, allowing microbial access to the root central cylinder. Moreover, localized biosynthesis of antimicrobial compounds and ethylene differed in response to pathogens and mutualists. These examples highlight the power of this resource to gain insights into root-microbe interactions and to develop strategies in crop improvement.