Allelic heterogeneity and trade-off shape natural variation for response to soil micronutrient

Natural variants of molybdate transporters contribute to yield traits of soybean by affecting auxin synthesis

Soybean (Glycine max) is a crop with high demand for molybdenum (Mo) and typically requires Mo fertilization to achieve maximum yield potential. However, the genetic basis underlying the natural variation of Mo concentration in soybean and its impact on soybean agronomic performance is still poorly understood. Here, we performed a genome-wide association study (GWAS) to identify GmMOT1.1 and GmMOT1.2 that drive the natural variation of soybean Mo concentration and confer agronomic traits by affecting auxin synthesis. The soybean population exhibits five haplotypes of the two genes, with the haplotype 5 demonstrating the highest expression of GmMOT1.1 and GmMOT1.2, as well as the highest transport activities of their proteins. Further studies showed that GmMOT1.1 and GmMOT1.2 improve soybean yield, especially when cultivated in acidic or slightly acidic soil. Surprisingly, these two genes contribute to soybean growth by enhancing the activity of indole-3-acetaldehyde (IAAld) aldehyde oxidase (AO), leading to increased indole-3-acetic acid (IAA) synthesis, rather than being involved in symbiotic nitrogen fixation or nitrogen assimilation. Furthermore, the geographical distribution of five haplotypes in China and their correlation with soil pH suggest the potential significance of GmMOT1.1 and GmMOT1.2 in soybean breeding strategies.

Molybdenum: More than an essential element

Molybdenum (Mo) is an essential element for almost all living organisms. After being taken up into the cells as molybdate, it is incorporated into the molybdenum cofactor, which functions as the active site of several molybdenum-requiring enzymes and thus plays crucial roles in multiple biological processes. The uptake and transport of molybdate is mainly mediated by two types of molybdate transporters. The homeostasis of Mo in plant cells is tightly controlled, and such homeostasis likely plays vital roles in plant adaptation to local environments. Recent evidence suggests that Mo is more than an essential element required for plant growth and development; it is also involved in local adaptation to coastal salinity. In this review, we summarize recent research progress on molybdate uptake and transport, molybdenum homeostasis network in plants, and discuss the potential roles of the molybdate transporter in plant adaptation to their local environment.

Adaptation to coastal soils through pleiotropic boosting of ion and stress hormone concentrations in wild Arabidopsis thaliana

Local adaptation in coastal areas is driven chiefly by tolerance to salinity stress. To survive high salinity, plants have evolved mechanisms to specifically tolerate sodium. However, the pathways that mediate adaptive changes in these conditions reach well beyond Na⁺ . Here we perform a high-resolution genetic, ionomic, and functional study of the natural variation in Molybdenum transporter 1 (MOT1) associated with coastal Arabidopsis thaliana accessions. We quantify the fitness benefits of a specific deletion-harbouring allele (MOT1^DEL ) present in coastal habitats that is associated with lower transcript expression and molybdenum accumulation. Analysis of the leaf ionome revealed that MOT1^DEL  plants accumulate more copper (Cu) and less sodium (Na⁺ ) than plants with the noncoastal MOT1 allele, revealing a complex interdependence in homeostasis of these three elements. Our results indicate that under salinity stress, reduced MOT1 function limits leaf Na⁺  accumulation through abscisic acid (ABA) signalling. Enhanced ABA biosynthesis requires Cu. This demand is met in Cu deficient coastal soils through MOT1^DEL  increasing the expression of SPL7 and the copper transport protein COPT6. MOT1^DEL  is able to deliver a pleiotropic suite of phenotypes that enhance salinity tolerance in coastal soils deficient in Cu. This is achieved by inducing ABA biosynthesis and promoting reduced uptake or better compartmentalization of Na⁺ , leading to coastal adaptation.

Ionomic Approaches for Discovery of Novel Stress-Resilient Genes in Plants

Plants, being sessile, face an array of biotic and abiotic stresses in their lifespan that endanger their survival. Hence, optimized uptake of mineral nutrients creates potential new routes for enhancing plant health and stress resilience. Recently, minerals (both essential and non-essential) have been identified as key players in plant stress biology, owing to their multifaceted functions. However, a realistic understanding of the relationship between different ions and stresses is lacking. In this context, ionomics will provide new platforms for not only understanding the function of the plant ionome during stresses but also identifying the genes and regulatory pathways related to mineral accumulation, transportation, and involvement in different molecular mechanisms under normal or stress conditions. This article provides a general overview of ionomics and the integration of high-throughput ionomic approaches with other "omics" tools. Integrated omics analysis is highly suitable for identification of the genes for various traits that confer biotic and abiotic stress tolerance. Moreover, ionomics advances being used to identify loci using qualitative trait loci and genome-wide association analysis of element uptake and transport within plant tissues, as well as genetic variation within species, are discussed. Furthermore, recent developments in ionomics for the discovery of stress-tolerant genes in plants have also been addressed; these can be used to produce more robust crops with a high nutritional value for sustainable agriculture.

QTL x environment interactions underlie ionome divergence in switchgrass

Ionomics measures elemental concentrations in biological organisms and provides a snapshot of physiology under different conditions. In this study, we evaluate genetic variation of the ionome in outbred, perennial switchgrass in three environments across the species' native range, and explore patterns of genotype-by-environment interactions. We grew 725 clonally replicated genotypes of a large full sib family from a four-way linkage mapping population, created from deeply diverged upland and lowland switchgrass ecotypes, at three common gardens. Concentrations of 18 mineral elements were determined in whole post-anthesis tillers using ion coupled plasma mass spectrometry (ICP-MS). These measurements were used to identify quantitative trait loci (QTL) with and without QTL-by-environment interactions (QTLxE) using a multi-environment QTL mapping approach. We found that element concentrations varied significantly both within and between switchgrass ecotypes, and GxE was present at both the trait and QTL level. Concentrations of 14 of the 18 elements were under some genetic control, and 77 QTL were detected for these elements. 74% of QTL colocalized multiple elements, half of QTL exhibited significant QTLxE, and roughly equal numbers of QTL had significant differences in magnitude and sign of their effects across environments. The switchgrass ionome is under moderate genetic control and by loci with highly variable effects across environments.

1,135 ionomes reveal the global pattern of leaf and seed mineral nutrient and trace element diversity in Arabidopsis thaliana

Soil is a heterogeneous reservoir of essential elements needed for plant growth and development. Plants have evolved mechanisms to balance their nutritional needs based on availability of nutrients. This has led to genetically based variation in the elemental composition, the 'ionome', of plants, both within and between species. We explore this natural variation using a panel of wild-collected, geographically widespread Arabidopsis thaliana accessions from the 1001 Genomes Project including over 1,135 accessions, and the 19 parental accessions of the Multi-parent Advanced Generation Inter-Cross (MAGIC) panel, all with full-genome sequences available. We present an experimental design pipeline for high-throughput ionomic screenings and analyses with improved normalisation procedures to account for errors and variability in conditions often encountered in large-scale, high-throughput data collection. We report quantification of the complete leaf and seed ionome of the entire collection using this pipeline and a digital tool, Ion Explorer, to interact with the dataset. We describe the pattern of natural ionomic variation across the A. thaliana species and identify several accessions with extreme ionomic profiles. It forms a valuable resource for exploratory genetic mapping studies to identify genes underlying natural variation in leaf and seed ionome and genetic adaptation of plants to soil conditions.

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

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

FLOWERING LOCUS M (FLM) is known as a repressor of Arabidopsis flowering. Here, the authors show that a single intronic substitution of FLM modulates leaf color and plant growth strategy along the leaf economics spectrum, as well as plays a role in plant adaptation.

Multivariate analysis reveals environmental and genetic determinants of element covariation in the maize grain ionome

The integrated responses of biological systems to genetic and environmental variation result in substantial covariance in multiple phenotypes. The resultant pleiotropy, environmental effects, and genotype-by-environmental interactions (GxE) are foundational to our understanding of biology and genetics. Yet, the treatment of correlated characters, and the identification of the genes encoding functions that generate this covariance, has lagged. As a test case for analyzing the genetic basis underlying multiple correlated traits, we analyzed maize kernel ionomes from Intermated B73 x Mo17 (IBM) recombinant inbred populations grown in 10 environments. Plants obtain elements from the soil through genetic and biochemical pathways responsive to physiological state and environment. Most perturbations affect multiple elements which leads the ionome, the full complement of mineral nutrients in an organism, to vary as an integrated network rather than a set of distinct single elements. We compared quantitative trait loci (QTL) determining single-element variation to QTL that predict variation in principal components (PCs) of multiple-element covariance. Single-element and multivariate approaches detected partially overlapping sets of loci. QTL influencing trait covariation were detected at loci that were not found by mapping single-element traits. Moreover, this approach permitted testing environmental components of trait covariance, and identified multi-element traits that were determined by both genetic and environmental factors as well as genotype-by-environment interactions. Growth environment had a profound effect on the elemental profiles and multi-element phenotypes were significantly correlated with specific environmental variables.

Natural variation in a molybdate transporter controls grain molybdenum concentration in rice

Molybdenum (Mo) is an essential micronutrient for most living organisms, including humans. Cereals such as rice (Oryza sativa) are the major dietary source of Mo. However, little is known about the genetic basis of the variation in Mo content in rice grain. We mapped a quantitative trait locus (QTL) qGMo8 that controls Mo accumulation in rice grain by using a recombinant inbred line population and a backcross introgression line population. We identified a molybdate transporter, OsMOT1;1, as the causal gene for this QTL. OsMOT1;1 exhibits transport activity for molybdate, but not sulfate, when heterogeneously expressed in yeast cells. OsMOT1;1 is mainly expressed in roots and is involved in the uptake and translocation of molybdate under molybdate-limited condition. Knockdown of OsMOT1;1 results in less Mo being translocated to shoots, lower Mo concentration in grains and higher sensitivity to Mo deficiency. We reveal that the natural variation of Mo concentration in rice grains is attributed to the variable expression of OsMOT1;1 due to sequence variation in its promoter. Identification of natural allelic variation in OsMOT1;1 may facilitate the development of rice varieties with Mo-enriched grain for dietary needs and improve Mo nutrition of rice on Mo-deficient soils.

AtHMA4 Drives Natural Variation in Leaf Zn Concentration of Arabidopsis thaliana

Zinc (Zn) is an essential element for plant growth and development, and Zn derived from crop plants in the diet is also important for human health. Here, we report that genetic variation in Heavy Metal-ATPase 4 (HMA4) controls natural variation in leaf Zn content. Investigation of the natural variation in leaf Zn content in a world-wide collection of 349 Arabidopsis thaliana wild collected accessions identified two accessions, Van-0 and Fab-2, which accumulate significantly lower Zn when compared with Col-0. Both quantitative trait loci (QTL) analysis and bulked segregant analysis (BSA) identified HMA4 as a strong candidate accounting for this variation in leaf Zn concentration. Genetic complementation experiments confirmed this hypothesis. Sequence analysis revealed that a 1-bp deletion in the third exon of HMA4 from Fab-2 is responsible for the lose of function of HMA4 driving the low Zn observed in Fab-2. Unlike in Fab-2 polymorphisms in the promoter region were found to be responsible for the weak function of HMA4 in Van-0. This is supported by both an expression analysis of HMA4 in Van-0 and through a series of T-DNA insertion mutants which generate truncated HMA4 promoters in the Col-0 background. In addition, we also observed that Fab-2, Van-0 and the hma4-2 null mutant in the Col-0 background show enhanced resistance to a combination of high Zn and high Cd in the growth medium, raising the possibility that variation at HMA4 may play a role in environmental adaptation.

Relationships between soil and leaf mineral composition are element-specific, environment-dependent and geographically structured in the emerging model Arabidopsis halleri

Leaf mineral composition, the leaf ionome, reflects the complex interaction between a plant and its environment including local soil composition, an influential factor that can limit species distribution and plant productivity. Here we addressed within-species variation in plant-soil interactions and edaphic adaptation using Arabidopsis halleri, a well-suited model species as a facultative metallophyte and metal hyperaccumulator. We conducted multi-element analysis of 1972 paired leaf and soil samples from 165 European populations of A. halleri, at individual resolution to accommodate soil heterogeneity. Results were further confirmed under standardized conditions upon cultivation of 105 field-collected genotypes on an artificially metal-contaminated soil in growth chamber experiments. Soil-independent between- and within-population variation set apart leaf accumulation of zinc, cadmium and lead from all other nutrient and nonessential elements, concurring with differential hypothesized ecological roles in either biotic interaction or nutrition. For these metals, soil-leaf relationships were element-specific, differed between metalliferous and nonmetalliferous soils and were geographically structured both in the field and under standardized growth conditions, implicating complex scenarios of recent ecological adaptation. Our study provides an example and a reference for future related work and will serve as a basis for the molecular-genetic dissection and ecological analysis of the observed phenotypic variation.

Multiple alleles at a single locus control seed dormancy in Swedish Arabidopsis

Seed dormancy is a complex life history trait that determines the timing of germination and is crucial for local adaptation. Genetic studies of dormancy are challenging, because the trait is highly plastic and strongly influenced by the maternal environment. Using a combination of statistical and experimental approaches, we show that multiple alleles at the previously identified dormancy locus DELAY OF GERMINATION1 jointly explain as much as 57% of the variation observed in Swedish Arabidopsis thaliana, but give rise to spurious associations that seriously mislead genome-wide association studies unless modeled correctly. Field experiments confirm that the major alleles affect germination as well as survival under natural conditions, and demonstrate that locally adaptive traits can sometimes be dissected genetically.

Plant Ionomics: From Elemental Profiling to Environmental Adaptation

Ionomics is a high-throughput elemental profiling approach to study the molecular mechanistic basis underlying mineral nutrient and trace element composition (also known as the ionome) of living organisms. Since the concept of ionomics was first introduced more than 10 years ago, significant progress has been made in the identification of genes and gene networks that control the ionome. In this update, we summarize the progress made in using the ionomics approach over the last decade, including the identification of genes by forward genetics and the study of natural ionomic variation. We further discuss the potential application of ionomics to the investigation of the ecological functions of ionomic alleles in adaptation to the environment.

Local adaptation to temperature and precipitation in naturally fragmented populations of Cephalotaxus oliveri, an endangered conifer endemic to China

Cephalotaxus oliveri is an endangered tertiary relict conifer endemic to China. The species survives in a wide range from west to east with heterogeneous climatic conditions. Precipitation and temperature are main restrictive factors for distribution of C. oliveri. In order to comprehend the mechanism of adaptive evolution to climate variation, we employed ISSR markers to detect adaptive evolution loci, to identify the association between variation in temperature and precipitation and adaptive loci, and to investigate the genetic structure for 22 C. oliveri natural populations. In total, 14 outlier loci were identified, of which five were associated with temperature and precipitation. Among outlier loci, linkage disequilibrium (LD) was high (42.86%), which also provided strong evidence for selection. In addition, C. oliveri possessed high genetic variation (93.31%) and population differentiation, which may provide raw material to evolution and accelerate local adaptation, respectively. Ecological niche modeling showed that global warming will cause a shift for populations of C. oliveri from south to north with a shrinkage of southern areas. Our results contribute to understand the potential response of conifers to climatic changes, and provide new insights for conifer resource management and conservation strategies.

The Multi-allelic Genetic Architecture of a Variance-Heterogeneity Locus for Molybdenum Concentration in Leaves Acts as a Source of Unexplained Additive Genetic Variance

Genome-wide association (GWA) analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA) signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or “missing heritability”. Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1), and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975) as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.

Most biological traits vary in natural populations, and understanding the genetic basis of this variation remains an important challenge. Genome-wide association (GWA) studies have emerged as a powerful tool to address this challenge by dissecting the genetic architecture of trait variation into the contribution of individual genes. This contribution has traditionally been measured as the difference in the phenotypic means between groups of individuals with alternative genotypes at one, or multiple loci. However, instead of altering the trait mean, certain loci alter the variability of the trait. Here, we describe the genetic dissection of one such variance-controlling locus that drives variation in leaf molybdenum concentrations amongst natural accessions of Arabidopsis thaliana. The variance-controlling locus was found to result from the contributions of multiple alleles at multiple loci that are closely linked on the chromosome and is a major contributor to the “missing heritability” for this trait identified in previous studies. This illustrates that multi-allelic genetic architectures can hide large amounts of additive genetic variation, and that it is possible to uncover this hidden variation using the appropriate experimental designs and statistical methods described here.

Population Genomics for Understanding Adaptation in Wild Plant Species

Darwin's theory of evolution by natural selection is the foundation of modern biology. However, it has proven remarkably difficult to demonstrate at the genetic, genomic, and population level exactly how wild species adapt to their natural environments. We discuss how one can use large sets of multiple genome sequences from wild populations to understand adaptation, with an emphasis on the small herbaceous plant Arabidopsis thaliana. We present motivation for such studies; summarize progress in describing whole-genome, species-wide sequence variation; and then discuss what insights have emerged from these resources, either based on sequence information alone or in combination with phenotypic data. We conclude with thoughts on opportunities with other plant species and the impact of expected progress in sequencing technology and genome engineering for studying adaptation in nature.

Salinity Is an Agent of Divergent Selection Driving Local Adaptation of Arabidopsis to Coastal Habitats

Understanding the molecular mechanism of adaptive evolution in plants provides insights into the selective forces driving adaptation and the genetic basis of adaptive traits with agricultural value. The genomic resources available for Arabidopsis (Arabidopsis thaliana) make it well suited to the rapid molecular dissection of adaptive processes. Although numerous potentially adaptive loci have been identified in Arabidopsis, the consequences of divergent selection and migration (both important aspects of the process of local adaptation) for Arabidopsis are not well understood. Here, we use a multiyear field-based reciprocal transplant experiment to detect local populations of Arabidopsis composed of multiple small stands of plants (demes) that are locally adapted to the coast and adjacent inland habitats in northeastern Spain. We identify fitness tradeoffs between plants from these different habitats when grown together in inland and coastal common gardens and also, under controlled conditions in soil excavated from coastal and inland sites. Plants from the coastal habitat also outperform those from inland when grown under high salinity, indicating local adaptation to soil salinity. Sodium can be toxic to plants, and we find its concentration to be elevated in soil and plants sampled at the coast. We conclude that the local adaptation that we observe between adjacent coastal and inland populations is caused by ongoing divergent selection driven by the differential salinity between coastal and inland soils.

Planting molecular functions in an ecological context with Arabidopsis thaliana

The vascular plant Arabidopsis thaliana is a central genetic model and universal reference organism in plant and crop science. The successful integration of different fields of research in the study of A. thaliana has made a large contribution to our molecular understanding of key concepts in biology. The availability and active development of experimental tools and resources, in combination with the accessibility of a wealth of cumulatively acquired knowledge about this plant, support the most advanced systems biology approaches among all land plants. Research in molecular ecology and evolution has also brought the natural history of A. thaliana into the limelight. This article showcases our current knowledge of the natural history of A. thaliana from the perspective of the most closely related plant species, providing an evolutionary framework for interpreting novel findings and for developing new hypotheses based on our knowledge of this plant.

Genetic architecture of naturally occurring quantitative traits in plants: an updated synthesis

Deciphering the genetic and molecular bases of quantitative variation is a long-standing challenge in plant biology because it is essential for understanding evolution and for accelerating plant breeding. Recent multi-trait analyses at different phenotypic levels are uncovering the pleiotropy and the genetic regulation underlying high-level complex traits. Thus, the number of known causal loci, genes and nucleotide polymorphisms is expanding. Current plant causal catalogs contain ∼400 genes and natural polymorphisms revealing several dysfunctional allelic series that involve multiple mutations. In addition, repeated evolution of quantitative traits mediated by large effect alleles is found across plant phylogeny. Finally, systematic analyses of genetic and environmental interactions are beginning to elucidate the molecular mechanisms of relevant interactions.

A pair of receptor-like kinases is responsible for natural variation in shoot growth response to mannitol treatment in Arabidopsis thaliana

Growth is a complex trait that adapts to the prevailing conditions by integrating many internal and external signals. Understanding the molecular origin of this variation remains a challenging issue. In this study, natural variation of shoot growth under mannitol-induced stress was analyzed by standard quantitative trait locus mapping methods in a recombinant inbred line population derived from a cross between the Col-0 and Cvi-0 Arabidopsis thaliana accessions. Cloning of a major QTL specific to mannitol-induced stress condition led to identification of EGM1 and EGM2, a pair of tandem-duplicated genes encoding receptor-like kinases that are potentially involved in signaling of mannitol-associated stress responses. Using various genetic approaches, we identified two non-synonymous mutations in the EGM2[Cvi] allele that are shared by at least ten accessions from various origins and are probably responsible for a specific tolerance to mannitol. We have shown that the enhanced shoot growth phenotype contributed by the Cvi allele is not linked to generic osmotic properties but instead to a specific chemical property of mannitol itself. This result raises the question of the function of such a gene in A. thaliana, a species that does not synthesize mannitol. Our findings suggest that the receptor-like kinases encoded by EGM genes may be activated by mannitol produced by pathogens such as fungi, and may contribute to plant defense responses whenever mannitol is present.

ABA control of plant macroelement membrane transport systems in response to water deficit and high salinity

Plant growth and productivity are adversely affected by various abiotic stressors and plants develop a wide range of adaptive mechanisms to cope with these adverse conditions, including adjustment of growth and development brought about by changes in stomatal activity. Membrane ion transport systems are involved in the maintenance of cellular homeostasis during exposure to stress and ion transport activity is regulated by phosphorylation/dephosphorylation networks that respond to stress conditions. The phytohormone abscisic acid (ABA), which is produced rapidly in response to drought and salinity stress, plays a critical role in the regulation of stress responses and induces a series of signaling cascades. ABA signaling involves an ABA receptor complex, consisting of an ABA receptor family, phosphatases and kinases: these proteins play a central role in regulating a variety of diverse responses to drought stress, including the activities of membrane-localized factors, such as ion transporters. In this review, recent research on signal transduction networks that regulate the function ofmembrane transport systems in response to stress, especially water deficit and high salinity, is summarized and discussed. The signal transduction networks covered in this review have central roles in mitigating the effect of stress by maintaining plant homeostasis through the control of membrane transport systems.

Genome wide association mapping of grain arsenic, copper, molybdenum and zinc in rice (Oryza sativa L.) grown at four international field sites

The mineral concentrations in cereals are important for human health, especially for individuals who consume a cereal subsistence diet. A number of elements, such as zinc, are required within the diet, while some elements are toxic to humans, for example arsenic. In this study we carry out genome-wide association (GWA) mapping of grain concentrations of arsenic, copper, molybdenum and zinc in brown rice using an established rice diversity panel of ∼300 accessions and 36.9 k single nucleotide polymorphisms (SNPs). The study was performed across five environments: one field site in Bangladesh, one in China and two in the US, with one of the US sites repeated over two years. GWA mapping on the whole dataset and on separate subpopulations of rice revealed a large number of loci significantly associated with variation in grain arsenic, copper, molybdenum and zinc. Seventeen of these loci were detected in data obtained from grain cultivated in more than one field location, and six co-localise with previously identified quantitative trait loci. Additionally, a number of candidate genes for the uptake or transport of these elements were located near significantly associated SNPs (within 200 kb, the estimated global linkage disequilibrium previously employed in this rice panel). This analysis highlights a number of genomic regions and candidate genes for further analysis as well as the challenges faced when mapping environmentally-variable traits in a highly genetically structured diversity panel.

Genome wide association mapping of grain arsenic, copper, molybdenum and zinc in rice (Oryza sativa L.) grown at four international field sites

The mineral concentrations in cereals are important for human health, especially for individuals who consume a cereal subsistence diet. A number of elements, such as zinc, are required within the diet, while some elements are toxic to humans, for example arsenic. In this study we carry out genome-wide association (GWA) mapping of grain concentrations of arsenic, copper, molybdenum and zinc in brown rice using an established rice diversity panel of ∼ 300 accessions and 36.9 k single nucleotide polymorphisms (SNPs). The study was performed across five environments: one field site in Bangladesh, one in China and two in the US, with one of the US sites repeated over two years. GWA mapping on the whole dataset and on separate subpopulations of rice revealed a large number of loci significantly associated with variation in grain arsenic, copper, molybdenum and zinc. Seventeen of these loci were detected in data obtained from grain cultivated in more than one field location, and six co-localise with previously identified quantitative trait loci. Additionally, a number of candidate genes for the uptake or transport of these elements were located near significantly associated SNPs (within 200 kb, the estimated global linkage disequilibrium previously employed in this rice panel). This analysis highlights a number of genomic regions and candidate genes for further analysis as well as the challenges faced when mapping environmentally-variable traits in a highly genetically structured diversity panel.

Phenoscope: an automated large-scale phenotyping platform offering high spatial homogeneity

Increased phenotyping accuracy and throughput are necessary to improve our understanding of quantitative variation and to be able to deconstruct complex traits such as those involved in growth responses to the environment. Still, only a few facilities are known to handle individual plants of small stature for non-destructive, real-time phenotype acquisition from plants grown in precisely adjusted and variable experimental conditions. Here, we describe Phenoscope, a high-throughput phenotyping platform that has the unique feature of continuously rotating 735 individual pots over a table. It automatically adjusts watering and is equipped with a zenithal imaging system to monitor rosette size and expansion rate during the vegetative stage, with automatic image analysis allowing manual correction. When applied to Arabidopsis thaliana, we show that rotating the pots strongly reduced micro-environmental disparity: heterogeneity in evaporation was cut by a factor of 2.5 and the number of replicates needed to detect a specific mild genotypic effect was reduced by a factor of 3. In addition, by controlling a large proportion of the micro-environmental variance, other tangible sources of variance become noticeable. Overall, Phenoscope makes it possible to perform large-scale experiments that would not be possible or reproducible by hand. When applied to a typical quantitative trait loci (QTL) mapping experiment, we show that mapping power is more limited by genetic complexity than phenotyping accuracy. This will help to draw a more general picture as to how genetic diversity shapes phenotypic variation.

Natural variation of Arabidopsis root architecture reveals complementing adaptive strategies to potassium starvation

Root architecture is a highly plastic and environmentally responsive trait that enables plants to counteract nutrient scarcities with different foraging strategies. In potassium (K) deficiency (low K), seedlings of the Arabidopsis (Arabidopsis thaliana) reference accession Columbia (Col-0) show a strong reduction of lateral root elongation. To date, it is not clear whether this is a direct consequence of the lack of K as an osmoticum or a triggered response to maintain the growth of other organs under limiting conditions. In this study, we made use of natural variation within Arabidopsis to look for novel root architectural responses to low K. A comprehensive set of 14 differentially responding root parameters were quantified in K-starved and K-replete plants. We identified a phenotypic gradient that links two extreme strategies of morphological adaptation to low K arising from a major tradeoff between main root (MR) and lateral root elongation. Accessions adopting strategy I (e.g. Col-0) maintained MR growth but compromised lateral root elongation, whereas strategy II genotypes (e.g. Catania-1) arrested MR elongation in favor of lateral branching. K resupply and histochemical staining resolved the temporal and spatial patterns of these responses. Quantitative trait locus analysis of K-dependent root architectures within a Col-0 × Catania-1 recombinant inbred line population identified several loci each of which determined a particular subset of root architectural parameters. Our results indicate the existence of genomic hubs in the coordinated control of root growth in stress conditions and provide resources to facilitate the identification of the underlying genes.