Genome-wide association mapping of time-dependent growth responses to moderate drought stress in Arabidopsis

Genome-wide association study of drought tolerance in wheat (Triticum aestivum L.) identifies SNP markers and candidate genes

Drought stress poses a severe threat to global wheat production, necessitating an in-depth exploration of the genetic basis for drought tolerance associated traits. This study employed a 90 K SNP array to conduct a genome-wide association analysis, unravelling genetic determinants of key traits related to drought tolerance in wheat, namely plant height, root length, and root and shoot dry weight. Using the mixed linear model (MLM) method on 125 wheat accessions subjected to both well-watered and drought stress treatments, we identified 53 SNPs significantly associated with stress susceptibility (SSI) and tolerance indices (STI) for the targeted traits. Notably, chromosomes 2A and 3B stood out with ten and nine associated markers, respectively. Across 17 chromosomes, 44 unique candidate genes were pinpointed, predominantly located on the distal ends of 1A, 1B, 1D, 2A, 3A, 3B, 4A, 6A, 6B, 7A, 7B, and 7D chromosomes. These genes, implicated in diverse functions related to plant growth, development, and stress responses, offer a rich resource for future investigation. A clustering pattern emerged, notably with seven genes associated with SSI for plant height and four genes linked to both STI of plant height and shoot dry weight, converging on specific regions of chromosome arms of 2AS and 3BL. Additionally, shared genes encoding polygalacturonase, auxilin-related protein 1, peptide deformylase, and receptor-like kinase underscored the interconnectedness between plant height and shoot dry weight. In conclusion, our findings provide insights into the molecular mechanisms governing wheat drought tolerance, identifying promising genomic loci for further exploration and crop improvement strategies.

Natural variation in Brachypodium distachyon responses to combined abiotic stresses

The demand for agricultural production is becoming more challenging as climate change increases global temperature and the frequency of extreme weather events. This study examines the phenotypic variation of 149 accessions of Brachypodium distachyon under drought, heat, and the combination of stresses. Heat alone causes the largest amounts of tissue damage while the combination of stresses causes the largest decrease in biomass compared to other treatments. Notably, Bd21-0, the reference line for B. distachyon, did not have robust growth under stress conditions, especially the heat and combined drought and heat treatments. The climate of origin was significantly associated with B. distachyon responses to the assessed stress conditions. Additionally, a GWAS found loci associated with changes in plant height and the amount of damaged tissue under stress. Some of these SNPs were closely located to genes known to be involved in responses to abiotic stresses and point to potential causative loci in plant stress response. However, SNPs found to be significantly associated with a response to heat or drought individually are not also significantly associated with the combination of stresses. This, with the phenotypic data, suggests that the effects of these abiotic stresses are not simply additive, and the responses to the combined stresses differ from drought and heat alone.

Genome-wide association analysis reveals genes controlling an antagonistic effect of biotic and osmotic stress on Arabidopsis thaliana growth

While the response of Arabidopsis thaliana to drought, herbivory or fungal infection has been well-examined, the consequences of exposure to a series of such (a)biotic stresses are not well studied. This work reports on the genetic mechanisms underlying the Arabidopsis response to single osmotic stress, and to combinatorial stress, either fungal infection using Botrytis cinerea or herbivory using Pieris rapae caterpillars followed by an osmotic stress treatment. Several small-effect genetic loci associated with rosette dry weight (DW), rosette water content (WC), and the projected rosette leaf area in response to combinatorial stress were mapped using univariate and multi-environment genome-wide association approaches. A single-nucleotide polymorphism (SNP) associated with DROUGHT-INDUCED 19 (DI19) was identified by both approaches, supporting its potential involvement in the response to combinatorial stress. Several SNPs were found to be in linkage disequilibrium with known stress-responsive genes such as PEROXIDASE 34 (PRX34), BASIC LEUCINE ZIPPER 25 (bZIP25), RESISTANCE METHYLATED GENE 1 (RMG1) and WHITE RUST RESISTANCE 4 (WRR4). An antagonistic effect between biotic and osmotic stress was found for prx34 and arf4 mutants, which suggests PRX34 and ARF4 play an important role in the response to the combinatorial stress.

Dynamic growth QTL action in diverse light environments: characterization of light regime-specific and stable QTL in Arabidopsis

Plant growth is a complex process affected by a multitude of genetic and environmental factors and their interactions. To identify genetic factors influencing plant performance under different environmental conditions, vegetative growth was assessed in Arabidopsis thaliana cultivated under constant or fluctuating light intensities, using high-throughput phenotyping and genome-wide association studies. Daily automated non-invasive phenotyping of a collection of 382 Arabidopsis accessions provided growth data during developmental progression under different light regimes at high temporal resolution. Quantitative trait loci (QTL) for projected leaf area, relative growth rate, and PSII operating efficiency detected under the two light regimes were predominantly condition-specific and displayed distinct temporal activity patterns, with active phases ranging from 2 d to 9 d. Eighteen protein-coding genes and one miRNA gene were identified as potential candidate genes at 10 QTL regions consistently found under both light regimes. Expression patterns of three candidate genes affecting projected leaf area were analysed in time-series experiments in accessions with contrasting vegetative leaf growth. These observations highlight the importance of considering both environmental and temporal patterns of QTL/allele actions and emphasize the need for detailed time-resolved analyses under diverse well-defined environmental conditions to effectively unravel the complex and stage-specific contributions of genes affecting plant growth processes.

Genome-wide association study of multiyear dynamic growth traits in hybrid Liriodendron identifies robust genetic loci associated with growth trajectories

The genetic factors underlying growth traits differ over time points or stages. However, most current studies of phenotypes at single time points do not capture all loci or explain the genetic differences underlying growth trajectories. Hybrid Liriodendron exhibits obvious heterosis and is widely cultivated, although its complex genetic mechanism underlying growth traits remains unknown. A genome-wide association study (GWAS) is an effective method for elucidating the genetic architecture by identifying genetic loci underlying complex quantitative traits. In the present study, using a GWAS, we identified robust loci associated with growth trajectories in hybrid Liriodendron populations. We selected 233 hybrid progenies derived from 25 crosses for resequencing, and measured their tree height (H) and diameter at breast height (DBH) for 11 consecutive years; 192 972 high-quality single nucleotide polymorphisms (SNPs) were obtained. The dynamics of the multiyear single-trait GWAS showed that year-specific SNPs predominated, and only five robust SNPs for DBH were identified in at least three different years. Multitrait GWAS analysis with model parameters as latent variables also revealed 62 SNPs for H and 52 for DBH associated with the growth trajectory, displaying different biomass accumulation patterns, among which four SNPs exerted pleiotropic effects. All identified SNPs also exhibited temporal variations in effect sizes and inheritance patterns potentially related to different growth and developmental stages. The haplotypes resulting from these significant SNPs might pyramid favorable loci, benefitting the selection of superior genotypes. The present study provides insights into the genetic architecture of dynamic growth traits and lays a basis for future molecular-assisted breeding.

Testing the association of relative growth rate and adaptation to climate across natural ecotypes of Arabidopsis

Ecophysiologists have reported a range of relationships, including intrinsic trade-offs across and within species between plant relative growth rate in high resource conditions (RGR) vs adaptation to tolerate cold or arid climates, arising from trait-based mechanisms. Few studies have considered ecotypes within a species, in which the lack of a trade-off would contribute to a wide species range and resilience to climate change. For 15 ecotypes of Arabidopsis thaliana in a common garden we tested for associations between RGR vs adaptation to cold or dry native climates and assessed hypotheses for its mediation by 15 functional traits. Ecotypes native to warmer, drier climates had higher leaf density, leaf mass per area, root mass fraction, nitrogen per leaf area and carbon isotope ratio, and lower osmotic potential at full turgor. Relative growth rate was statistically independent of the climate of the ecotype native range and of individual functional traits. The decoupling of RGR and cold or drought adaptation in Arabidopsis is consistent with multiple stress resistance and avoidance mechanisms for ecotypic climate adaptation and would contribute to the species' wide geographic range and resilience as the climate changes.

Inter-tissue and inter-organ signaling in drought stress response and phenotyping of drought tolerance

Plant response to drought stress includes systems for intracellular regulation of gene expression and signaling, as well as inter-tissue and inter-organ signaling, which helps entire plants acquire stress resistance. Plants sense water-deficit conditions both via the stomata of leaves and roots, and transfer water-deficit signals from roots to shoots via inter-organ signaling. Abscisic acid is an important phytohormone involved in the drought stress response and adaptation, and is synthesized mainly in vascular tissues and guard cells of leaves. In leaves, stress-induced abscisic acid is distributed to various tissues by transporters, which activates stomatal closure and expression of stress-related genes to acquire drought stress resistance. Moreover, the stepwise stress response at the whole-plant level is important for proper understanding of the physiological response to drought conditions. Drought stress is sensed by multiple types of sensors as molecular patterns of abiotic stress signals, which are transmitted via separate parallel signaling networks to induce downstream responses, including stomatal closure and synthesis of stress-related proteins and metabolites. Peptide molecules play important roles in the inter-organ signaling of dehydration from roots to shoots, as well as signaling of osmotic changes and reactive oxygen species/Ca²⁺ . In this review, we have summarized recent advances in research on complex plant drought stress responses, focusing on inter-tissue signaling in leaves and inter-organ signaling from roots to shoots. We have discussed the mechanisms via which drought stress adaptations and resistance are acquired at the whole-plant level, and have proposed the importance of quantitative phenotyping for measuring plant growth under drought conditions.

New drought-adaptive loci underlying candidate genes on wheat chromosome 4B with improved photosynthesis and yield responses

Flag leaf serves as an essential source of assimilates during grain filling, thereby contributing to grain yield up to 48%. Thus, high-throughput phenotyping of flag leaves is crucial to determine their physiological and genetic basis of yield formation and drought adaptation. Here, we utilized 200 wheat cultivars to identify drought-adaptive loci underlying candidate genes associated with flag leaf biomass and photosynthesis-related traits using a genome-wide association study (GWAS). GWAS revealed 21 significant marker-trait associations for key photosynthetic traits in response to drought stress. Analysis of linkage disequilibrium (LD) in these SNPs intervals discovered 103 significant SNPs that established distinct LD blocks containing a total of 382 candidate genes putatively involved in physiological processes, including photosynthesis and water responses. Further, in silico transcript analysis identified two candidate genes in locus AX-580365925 on chromosome 4B, those were found to be highly expressed under drought and associated with proton-transporting ATP synthase activity and stress response pathways. Accordingly, we identified significant allelic haplotype differences on this same locus. The tolerant haplotype (higher chlorophyll content under drought) representing major allele was more abundant and stably increased photosynthetic efficiency and yield under drought scenarios. Collectively, this study offers new adaptive loci and beneficial alleles to reshape the flag leaf physiological and associated photosynthetic components for better yield and sustainability to water-deficit stress.

Intervessel pit membrane thickness best explains variation in embolism resistance amongst stems of Arabidopsis thaliana accessions

BACKGROUND AND AIMS

The ability to avoid drought-induced embolisms in the xylem is one of the essential traits for plants to survive periods of water shortage. Over the past three decades, hydraulic studies have been focusing on trees, which limits our ability to understand how herbs tolerate drought. Here we investigate the embolism resistance in inflorescence stems of four Arabidopsis thaliana accessions that differ in growth form and drought response. We assess functional traits underlying the variation in embolism resistance amongst the accessions studied using detailed anatomical observations.

METHODS

Vulnerability to xylem embolism was evaluated via vulnerability curves using the centrifuge technique and linked with detailed anatomical observations in stems using light microscopy and transmission electron microscopy.

KEY RESULTS

The data show significant differences in stem P50, varying 2-fold from -1.58 MPa in the Cape Verde Island accession to -3.07 MPa in the woody soc1 ful double mutant. Out of all the anatomical traits measured, intervessel pit membrane thickness (TPM) best explains the differences in P50, as well as P12 and P88. The association between embolism resistance and TPM can be functionally explained by the air-seeding hypothesis. There is no evidence that the correlation between increased woodiness and increased embolism resistance is directly related to functional aspects. However, we found that increased woodiness is strongly linked to other lignification characters, explaining why mechanical stem reinforcement is indirectly related to increased embolism resistance.

CONCLUSIONS

The woodier or more lignified accessions are more resistant to embolism than the herbaceous accessions, confirming the link between increased stem lignification and increased embolism resistance, as also observed in other lineages. Intervessel pit membrane thickness and, to a lesser extent, theoretical vessel implosion resistance and vessel wall thickness are the missing functional links between stem lignification and embolism resistance.

The potential of resilient carbon dynamics for stabilizing crop reproductive development and productivity during heat stress

Impaired carbon metabolism and reproductive development constrain crop productivity during heat stress. Reproductive development is energy intensive, and its requirement for respiratory substrates rises as associated metabolism increases with temperature. Understanding how these processes are integrated and the extent to which they contribute to the maintenance of yield during and following periods of elevated temperatures is important for developing climate-resilient crops. Recent studies are beginning to demonstrate links between processes underlying carbon dynamics and reproduction during heat stress, consequently a summation of research that has been reported thus far and an evaluation of purported associations are needed to guide and stimulate future research. To this end, we review recent studies relating to source-sink dynamics, non-foliar photosynthesis and net carbon gain as pivotal in understanding how to improve reproductive development and crop productivity during heat stress. Rapid and precise phenotyping during narrow phenological windows will be important for understanding mechanisms underlying these processes, thus we discuss the development of relevant high-throughput phenotyping approaches that will allow for more informed decision-making regarding future crop improvement.

Distinct cellular strategies determine sensitivity to mild drought of Arabidopsis natural accessions

The worldwide distribution of Arabidopsis (Arabidopsis thaliana) accessions imposes different types of evolutionary pressures, which contributes to various responses of these accessions to environmental stresses. Responses to drought stress have mostly been studied in the Columbia accession, which is predominantly used in plant research. However, the reactions to drought stress are complex and our understanding of the responses that contribute to maintaining plant growth during mild drought (MD) is very limited. Here, we studied the mechanisms with which natural accessions react to MD at a physiological and molecular level during early leaf development. We documented variations in MD responses among natural accessions and used transcriptome sequencing of a drought-sensitive accession, ICE163, and a drought-insensitive accession, Yeg-1, to gain insights into the mechanisms underlying this discrepancy. This revealed that ICE163 preferentially induces jasmonate- and anthocyanin-related pathways, which are beneficial in biotic stress defense, whereas Yeg-1 has a more pronounced activation of abscisic acid signaling, the classical abiotic stress response. Related physiological traits, including the content of proline, anthocyanins, and reactive oxygen species, stomatal closure, and cellular leaf parameters, were investigated and linked to the transcriptional responses. We can conclude that most of these processes constitute general drought response mechanisms that are regulated similarly in drought-insensitive and -sensitive accessions. However, the capacity to close stomata and maintain cell expansion under MD appeared to be major factors that allow to better sustain leaf growth under MD.

Genome wide association study of the whiteness and colour related traits of flour and dough sheets in common wheat

Flour whiteness and colour are important factors that influence the quality of wheat flour and end-use products. In this study, a genome wide association study focusing on flour and dough sheet colour using a high density genetic map constructed with 90K single nucleotide polymorphism arrays in a panel of 205 elite winter wheat accessions was conducted in two different locations in 2 years. Eighty-six significant marker-trait associations (MTAs) were detected for flour whiteness and the brightness index (L* value), the redness index (a* value), and the yellowness index (b* value) of flour and dough sheets (P < 10^-4) on homologous group 1, 2, 5 and 7, and chromosomes 3A, 3B, 4A, 6A and 6B. Four, three, eleven, eleven MTAs for the flour whiteness, L* value, a* value, b* value, and one MTA for the dough sheet L* value were identified in more than one environment. Based on MATs, some important new candidate genes were identified. Of these, two candidate genes, TraesCS5D01G004300 and Gsp-1D, for BS00000020_51 were found in wheat, relating to grain hardness. Other candidate genes were associated with proteins, the fatty acid biosynthetic process, the ketone body biosynthetic process, etc.

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.

DeepPod: a convolutional neural network based quantification of fruit number in Arabidopsis

Background

High-throughput phenotyping based on non-destructive imaging has great potential in plant biology and breeding programs. However, efficient feature extraction and quantification from image data remains a bottleneck that needs to be addressed. Advances in sensor technology have led to the increasing use of imaging to monitor and measure a range of plants including the model Arabidopsis thaliana. These extensive datasets contain diverse trait information, but feature extraction is often still implemented using approaches requiring substantial manual input.

Results

The computational detection and segmentation of individual fruits from images is a challenging task, for which we have developed DeepPod, a patch-based 2-phase deep learning framework. The associated manual annotation task is simple and cost-effective without the need for detailed segmentation or bounding boxes. Convolutional neural networks (CNNs) are used for classifying different parts of the plant inflorescence, including the tip, base, and body of the siliques and the stem inflorescence. In a post-processing step, different parts of the same silique are joined together for silique detection and localization, whilst taking into account possible overlapping among the siliques. The proposed framework is further validated on a separate test dataset of 2,408 images. Comparisons of the CNN-based prediction with manual counting (R² = 0.90) showed the desired capability of methods for estimating silique number.

Conclusions

The DeepPod framework provides a rapid and accurate estimate of fruit number in a model system widely used by biologists to investigate many fundemental processes underlying growth and reproduction

Polygenic adaptation of rosette growth in Arabidopsis thaliana

The rate at which plants grow is a major functional trait in plant ecology. However, little is known about its evolution in natural populations. Here, we investigate evolutionary and environmental factors shaping variation in the growth rate of Arabidopsis thaliana. We used plant diameter as a proxy to monitor plant growth over time in environments that mimicked latitudinal differences in the intensity of natural light radiation, across a set of 278 genotypes sampled within four broad regions, including an outgroup set of genotypes from China. A field experiment conducted under natural conditions confirmed the ecological relevance of the observed variation. All genotypes markedly expanded their rosette diameter when the light supply was decreased, demonstrating that environmental plasticity is a predominant source of variation to adapt plant size to prevailing light conditions. Yet, we detected significant levels of genetic variation both in growth rate and growth plasticity. Genome-wide association studies revealed that only 2 single nucleotide polymorphisms associate with genetic variation for growth above Bonferroni confidence levels. However, marginally associated variants were significantly enriched among genes with an annotated role in growth and stress reactions. Polygenic scores computed from marginally associated variants confirmed the polygenic basis of growth variation. For both light regimes, phenotypic divergence between the most distantly related population (China) and the various regions in Europe is smaller than the variation observed within Europe, indicating that the evolution of growth rate is likely to be constrained by stabilizing selection. We observed that Spanish genotypes, however, reach a significantly larger size than Northern European genotypes. Tests of adaptive divergence and analysis of the individual burden of deleterious mutations reveal that adaptive processes have played a more important role in shaping regional differences in rosette growth than maladaptive evolution.

The rate at which plants grow is a major functional trait in plant ecology. However, little is known about its genetic variation in natural populations. Here, we investigate genetic and environmental factors shaping variation in the growth rate of Arabidopsis thaliana and ask whether genetic variation in plant growth contributes to adaptation to local environmental conditions. We grew plants under two light regimes that mimic latitudinal differences in the intensity of natural light radiation, and measured plant diameter as it grew over time. When the light supply was decreased, plant diameter grew more slowly but reached a markedly larger final size, confirming that plants can adjust their growth to prevailing light conditions. Yet, we also detected significant levels of genetic variation both in growth rate and in how the growth dynamics is adjusted to the light conditions. We show that this variation is encoded by many loci of small effect that are hard to locate in the genome but overall significantly enriched among genes associated with growth and stress reactions. We further observe that Spanish genotypes tended to reach, on average, a significantly larger rosette size than Northern European genotypes. Tests of adaptive divergence indicate that these differences may reflect adaptation to local environmental conditions.

Multi-Locus Genome-Wide Association Study of Four Yield-Related Traits in Chinese Wheat Landraces

Wheat (Triticum aestivum L.) is one of the most important crops in the world. Here, four yield-related traits, namely, spike length, spikelets number, tillers number, and thousand-kernel weight, were evaluated in 272 Chinese wheat landraces in multiple environments. Five multi-locus genome-wide association studies (FASTmrEMMA, ISIS EN-BLASSO, mrMLM, pKWmEB, and pLARmEB) were performed using 172,711 single-nucleotide polymorphisms (SNPs) to identify yield-related quantitative trait loci (QTL). A total of 27 robust QTL were identified by more than three models. Nine of these QTL were consistent with those in previous studies. The remaining 18 QTL may be novel. We identified a major QTL, QTkw.sicau-4B, with up to 18.78% of phenotypic variation explained. The developed kompetitive allele-specific polymerase chain reaction marker for QTkw.sicau-4B was validated in two recombinant inbred line populations with an average phenotypic difference of 16.07%. After combined homologous function annotation and expression analysis, TraesCS4B01G272300 was the most likely candidate gene for QTkw.sicau-4B. Our findings provide new insights into the genetic basis of yield-related traits and offer valuable QTL to breed wheat cultivars via marker-assisted selection.

Harnessing High-throughput Phenotyping and Genotyping for Enhanced Drought Tolerance in Crop Plants

Development of drought-tolerant cultivars is one of the challenging tasks for the plant breeders due to its complex inheritance and polygenic regulation. Evaluating genetic material for drought tolerance is a complex process due to its spatiotemporal interactions with environmental factors. The conventional breeding approaches are costly, lengthy, and inefficient to achieve the expected gain in drought tolerance. In this regard, genomics-assisted breeding (GAB) offers promise to develop cultivars with improved drought tolerance in a more efficient, quicker, and cost-effective manner. The success of GAB depends upon the precision in marker-trait association and estimation of genomic estimated breeding values (GEBVs), which mostly depends on coverage and precision of genotyping and phenotyping. A wide gap between the discovery and practical use of quantitative trait loci (QTL) for crop improvement has been observed for many important agronomical traits. Such a limitation could be due to the low accuracy in QTL detection, mainly resulting from low marker density and manually collected phenotypes of complex agronomic traits. Increasing marker density using the high-throughput genotyping (HTG), and accurate and precise phenotyping using high-throughput digital phenotyping (HTP) platforms can improve the precision and power of QTL detection. Therefore, both HTG and HTP can enhance the practical utility of GAB along with a faster characterization of germplasm and breeding material. In the present review, we discussed how the recent innovations in HTG and HTP would assist in the breeding of improved drought-tolerant varieties. We have also discussed strategies, tools, and analytical advances made on the HTG and HTP along with their pros and cons.

Leveraging genome-enabled growth models to study shoot growth responses to water deficit in rice

Elucidating genotype-by-environment interactions and partitioning its contribution to phenotypic variation remains a challenge for plant scientists. We propose a framework that utilizes genome-wide markers to model genotype-specific shoot growth trajectories as a function of time and soil water availability. A rice diversity panel was phenotyped daily for 21 d using an automated, high-throughput image-based, phenotyping platform that enabled estimation of daily shoot biomass and soil water content. Using these data, we modeled shoot growth as a function of time and soil water content, and were able to determine the time point where an inflection in the growth trajectory occurred. We found that larger, more vigorous plants exhibited an earlier repression in growth compared with smaller, slow-growing plants, indicating a trade-off between early vigor and tolerance to prolonged water deficits. Genomic inference for model parameters and time of inflection (TOI) identified several candidate genes. This study is the first to utilize a genome-enabled growth model to study drought responses in rice, and presents a new approach to jointly model dynamic morpho-physiological responses and environmental covariates.

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.

Competition × drought interactions change phenotypic plasticity and the direction of selection on Arabidopsis traits

Populations often exhibit genetic diversity in traits involved in responses to abiotic stressors, but what maintains this diversity is unclear. Arabidopsis thaliana exhibits high within-population variation in drought response. One hypothesis is that competition, varying at small scales, promotes diversity in resource use strategies. However, little is known about natural variation in competition effects on Arabidopsis physiology. We imposed drought and competition treatments on diverse genotypes. We measured resource economics traits, physiology, and fitness to characterize plasticity and selection in response to treatments. Plastic responses to competition differed depending on moisture availability. We observed genotype-drought-competition interactions for relative fitness: competition had little effect on relative fitness under well-watered conditions, whereas competition caused rank changes in fitness under drought. Early flowering was always selected. Higher δ¹³ C was selected only in the harshest treatment (drought and competition). Competitive context significantly changed the direction of selection on aboveground biomass and inflorescence height in well-watered environments. Our results highlight how local biotic conditions modify abiotic selection, in some cases promoting diversity in abiotic stress response. The ability of populations to adapt to environmental change may thus depend on small-scale biotic heterogeneity.

Differentially evolved drought stress indices determine the genetic variation of Brassica napus at seedling traits by genome-wide association mapping

Drought seriously curtails growth, physiology and productivity in rapeseed (Brassica napus). Although drought tolerance is a complex trait, efficient phenotyping and genotyping has led to the identification of novel marker-trait associations underlying drought tolerance. A diverse panel of 228 Brassica accessions was phenotyped under normal (without stress) and water-stress conditions, simulated by polyethylene glycol (PEG-6000) (15% PEG stress) at the seedling stage; stress tolerance index (STI) and stress susceptibility index (SSI) values were acquired. Genome-wide association studies (GWAS) using 201 817 high quality SNPs identified 314 marker-trait associations strongly linked with drought indices and distributed across all nineteen chromosomes in both the A and C genomes. None of these quantitative trait loci (QTL) had been previously identified by other studies. We identified 85 genes underlying these QTL (most within 100 kb of associated SNPs) which were orthologous to Arabidopsis genes known to be associated with drought tolerance. Our study provides a novel resource for breeding drought-tolerant Brassica crops.

AtSK11 and AtSK12 Mediate the Mild Osmotic Stress-Induced Root Growth Response in Arabidopsis

Although most osmotic stresses are harmful to plant growth and development, certain drought- or polyethylene glycol (PEG)-induced mild osmotic stresses promote plant root growth. The underlying regulatory mechanisms of this response remain elusive. Here, we report that the GLYCOGEN SYNTHASE KINASE 3 (GSK3) genes ARABIDOPSIS THALIANA SHAGGY-RELATED KINASE 11 (AtSK11) (AT5G26751) and AtSK12 (AT3G05840) are involved in the mild osmotic stress (−0.4 MPa) response in Arabidopsis thaliana. When grown on plant medium infused with different concentrations of PEG to mimic osmotic stress, both wild-type (WT) and atsk11atsk12 plants showed stimulated root growth under mild osmotic stress (−0.4 MPa) but repressed root growth under relatively strong osmotic stress (−0.5, −0.6, −0.7 MPa) as compared to the mock condition (−0.25 MPa). The root growth stimulation of atsk11atsk12 was more sensitive to −0.4 MPa treatment than was that of WT, indicating that AtSK11 and AtSK12 inhibit the mild stress-induced root growth response. RNA-seq analysis of WT and atsk11atsk12 plants under three water potentials (−0.25 MPa, −0.4 MPa, −0.6 MPa) revealed 10 differentially expressed candidate genes mainly involved in cell wall homeostasis, which were regulated by AtSK11 and AtSK12 to regulate root growth in response to the mild stress condition (−0.4 MPa). Promoter motif and transcription factor binding analyses suggested that the basic helix-loop-helix (bHLH) transcription factor bHLH69/LJRHL1-LIKE 2 (LRL2) may directly regulate the expression of most −0.4 MPa-responsive genes. These findings indicate that mild osmotic stress (−0.4 MPa) promotes plant growth and that the GSK3 family kinase genes AtSK11 and AtSK12 play a negative role in the induction of root growth in response to mild osmotic stress.

Fine mapping and gene cloning in the post-NGS era: advances and prospects

Improvement in traits of agronomic importance is the top breeding priority of crop improvement programs. Majority of these agronomic traits show complex quantitative inheritance. Identification of quantitative trait loci (QTLs) followed by fine mapping QTLs and cloning of candidate genes/QTLs is central to trait analysis. Advances in genomic technologies revolutionized our understanding of genetics of complex traits, and genomic regions associated with traits were employed in marker-assisted breeding or cloning of QTLs/genes. Next-generation sequencing (NGS) technologies have enabled genome-wide methodologies for the development of ultra-high-density genetic linkage maps in different crops, thus allowing placement of candidate loci within few kbs in genomes. In this review, we compare the marker systems used for fine mapping and QTL cloning in the pre- and post-NGS era. We then discuss how different NGS platforms in combination with advanced experimental designs have improved trait analysis and fine mapping. We opine that efficient genotyping/sequencing assays may circumvent the need for cumbersome procedures that were earlier used for fine mapping. A deeper understanding of the trait architectures of agricultural significance will be crucial to accelerate crop improvement.

Genome-Wide Association Study to Identify Candidate Loci for Biomass Formation Under Water Deficit in Perennial Ryegrass

Global warming is predicted to impact many agricultural areas, which will suffer from reduced water availability. Due to precipitation changes, mild summer droughts are expected to become more frequent, even in temperate regions. For perennial ryegrass (Lolium perenne L.), an important forage grass of the Poaceae family, leaf growth is a crucial factor determining biomass accumulation and hence forage yield. Although leaf elongation has been shown to be temperature-dependent under normal conditions, the genetic regulation of leaf growth under water deficit in perennial ryegrass is poorly understood. Herein, we evaluated the response to water deprivation in a diverse panel of perennial ryegrass genotypes, employing a high-precision phenotyping platform. The study revealed phenotypic variation for growth-related traits and significant (P < 0.05) differences in leaf growth under normal conditions within the subgroups of turf and forage type cultivars. The phenotypic data was combined with genotypic variants identified using genotyping-by-sequencing to conduct a genome-wide association study (GWAS). Using GWAS, we identified DNA polymorphisms significantly associated with leaf growth reduction under water deprivation. These polymorphisms were adjacent to genes predicted to encode for phytochrome B and a MYB41 transcription factor. The result obtained in the present study will increase our understanding on the complex molecular mechanisms involved in plant growth under water deficit. Moreover, the single nucleotide polymorphism (SNP) markers identified will serve as a valuable resource in future breeding programs to select for enhanced biomass formation under mild summer drought conditions.

Dissection of Phenotypic and Genetic Variation of Drought-Related Traits in Diverse Chinese Wheat Landraces

Variations in 16 seedling traits under normal and drought conditions were investigated. Extremely resistant and sensitive accessions were identified for future analyses. Under normal and drought conditions, 57 and 29 QTL were identified, respectively. A total of 77 candidate genes were identified, and four were validated by qRT-PCR. Drought is one of the most important abiotic stressors affecting wheat (Triticum aestivum L.) production. To improve wheat yield, a better understanding of the genetic control of traits governing drought resistance is paramount. Here, using 645 wheat landraces, we evaluated 16 seedling traits related to root and shoot growth and water content under normal and drought (induced by polyethylene glycol) conditions. Extremely resistant and sensitive accessions were identified for future drought-resistance breeding and further genetic analyses. A genome-wide association study was performed for the 16 traits using 52,118 diversity arrays technology sequencing (DArT-seq) markers. A total of 57 quantitative trait loci (QTL) were detected for seven traits under normal conditions, whereas 29 QTL were detected for eight traits under drought conditions. On the basis of these markers, we identified 56 candidate genes for six seedling traits under normal conditions, and 21 candidate genes for seven seedling traits under drought conditions. Four candidate genes were validated under normal and drought conditions using quantitative reverse transcription polymerase chain reaction (qRT-PCR) data. The co-localization of the flowering date and drought-related traits indicates that the regulatory networks of flowering may also respond to drought stress or are associated with the correlated responses of these traits. The phenotypic and genetic elucidation of drought-related traits will assist future gene discovery efforts and provide a basis for breeding drought-resistant wheat cultivars.

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

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

Genome-wide association of barley plant growth under drought stress using a nested association mapping population

BACKGROUND

Barley (Hordeum vulgare L.) is the fourth most important cereal crop worldwide. Barley production is compromised by many abiotic stresses including drought. Wild barley is a valuable source of alleles that can improve adaptation of cultivated barley to drought stress.

RESULTS

In the present study, a nested association mapping population named HEB-25, consisting of 1420 BC₁S₃ lines that were developed by crossing 25 different wild barley accessions to the elite barley cultivar 'Barke', was evaluated under both control and drought-stressed conditions in the Australian Plant Phenomics Facility, University of Adelaide. Overall, 14 traits reflecting the performance of individual plants in each treatment were calculated from non-destructive imaging over time and destructive end-of-experiment measurements. For each trait, best linear unbiased estimators (BLUEs) were calculated and used for genome-wide association study (GWAS) analysis. Among the quantitative trait loci (QTL) identified for the 14 traits, many co-localise with known inflorescence and developmental genes. We identified a QTL on chromosome 4H where, under drought and control conditions, wild barley alleles increased biomass by 10 and 17% respectively compared to the Barke allele.

CONCLUSIONS

Across all traits, QTL which increased phenotypic values were identified, providing a wider range of genetic diversity for the improvement of drought tolerance in barley.

A cheminformatics approach to characterize metabolomes in stable-isotope-labeled organisms

We report a computational approach (implemented in MS-DIAL 3.0; http://prime.psc.riken.jp/) for metabolite structure characterization using fully ¹³C-labeled and non-labeled plants and LC-MS/MS. Our approach facilitates carbon number determination and metabolite classification for unknown molecules. Applying our method to 31 tissues from 12 plant species, we assigned 1,092 structures and 344 formulae to 3,604 carbon-determined metabolite ions, 69 of which were found to represent structures currently not listed in metabolome databases.

Linking genes with ecological strategies in Arabidopsis thaliana

Arabidopsis thaliana is the most prominent model system in plant molecular biology and genetics. Although its ecology was initially neglected, collections of various genotypes revealed a complex population structure, with high levels of genetic diversity and substantial levels of phenotypic variation. This helped identify the genes and gene pathways mediating phenotypic change. Population genetics studies further demonstrated that this variation generally contributes to local adaptation. Here, we review evidence showing that traits affecting plant life history, growth rate, and stress reactions are not only locally adapted, they also often co-vary. Co-variation between these traits indicates that they evolve as trait syndromes, and reveals the ecological diversification that took place within A. thaliana. We argue that examining traits and the gene that control them within the context of global summary schemes that describe major ecological strategies will contribute to resolve important questions in both molecular biology and ecology.

Multiple genomic regions influence root morphology and seedling growth in cultivated sunflower (Helianthus annuus L.) under well-watered and water-limited conditions

With climate change and an ever-increasing human population threatening food security, developing a better understanding of the genetic basis of crop performance under stressful conditions has become increasingly important. Here, we used genome-wide association studies to genetically dissect variation in seedling growth traits in cultivated sunflower (Helianthus annuus L.) under well-watered and water-limited (i.e., osmotic stress) conditions, with a particular focus on root morphology. Water limitation reduced seedling size and produced a shift toward deeper rooting. These effects varied across genotypes, and we identified 13 genomic regions that were associated with traits of interest across the two environments. These regions varied in size from a single marker to 186.2 Mbp and harbored numerous genes, some of which are known to be involved in the plant growth/development as well as the response to osmotic stress. In many cases, these associations corresponded to growth traits where the common allele outperformed the rare variant, suggesting that selection for increased vigor during the evolution of cultivated sunflower might be responsible for the relatively high frequency of these alleles. We also found evidence of pleiotropy across multiple traits, as well as numerous environmentally independent genetic effects. Overall, our results indicate the existence of genetic variation in root morphology and allocation and further suggest that the majority of alleles associated with these traits have consistent effects across environments.

Determining the evolutionary forces shaping G × E

Contents Summary 31 I. Introduction 31 II. The maintenance of genetic variation for plasticity 32 III. Why is there environmental variation for genetic effects? 33 IV. Conclusions 35 Acknowledgements 35 References 35 SUMMARY: Phenotypic plasticity is common in nature, yet we lack a comprehensive understanding of the evolutionary forces that shape genetic variation for plasticity. This endeavor is especially important because variation for plasticity will result in genotype-by-environment interactions (G × E), a crucial component of variation in quantitative traits. Here, I review our understanding of the evolutionary forces shaping G × E, focusing specifically on: what evolutionary forces maintain variation for plasticity; and what forces maintain different genetic architectures across environments. My specific goal is to show that genomic data can be leveraged to explain the maintenance of G × E by contrasting patterns of genetic variation for plasticity with neutral expectations.

To defend or to grow: lessons from Arabidopsis C24

The emergence of Arabidopsis as a model species and the availability of genetic and genomic resources have resulted in the identification and detailed characterization of abiotic stress signalling pathways. However, this has led only to limited success in engineering abiotic stress tolerance in crops. This is because there needs to be a deeper understanding of how to combine resistances to a range of stresses with growth and productivity. The natural variation and genomic resources of Arabidopsis thaliana (Arabidopsis) are a great asset to understand the mechanisms of multiple stress tolerances. One natural variant in Arabidopsis is the accession C24, and here we provide an overview of the increasing research interest in this accession. C24 is highlighted as a source of tolerance for multiple abiotic and biotic stresses, and a key accession to understand the basis of basal immunity to infection, high water use efficiency, and water productivity. Multiple biochemical, physiological, and phenological mechanisms have been attributed to these traits in C24, and none of them constrains productivity. Based on the uniqueness of C24, we postulate that the use of variation derived from natural selection in undomesticated species provides opportunities to better understand how complex environmental stress tolerances and resource use efficiency are co-ordinated.

Association analysis of drought tolerance in cut chrysanthemum (Chrysanthemum morifolium Ramat.) at seedling stage

Understanding the genetic architecture is a prerequisite for crop improvement. The current research aimed to characterize the extent of genetic variation of drought tolerance harbored in a global collection of 159 chrysanthemum cultivars over 2 years. An average subordinate function value (ASFV), integrating the wilting index, the fresh weight retention rate, and the survival rate after re-watering under two drought-stressed trials, was used to quantify the level of drought tolerance. The performance of ASFV was generally correlated between the 2 years; and a high magnitude (0.95) of broad-sense heritability, coupled with the moderate genetic advance, was estimated for the ASFV. By applying MLM model with both population structure and kinship matrix as covariates association mapping identified 16 markers linked to drought tolerance, with the proportion of the phenotypic variation explained by an individual marker ranging from 4.4 to 7.6%. Of the eight markers predictive across the 2 years, four (E11M24-9, E3M2-8, E1M5-5, and EST-SSR34-3) were identified as favorable alleles for drought tolerance. Several cultivars that carry at least three of the four favorable alleles were identified as potential donor parents for future improvement of the drought tolerance. The findings provide an insight into the genetic basis of the drought tolerance in chrysanthemum and will, therefore, aid in developing new cultivars with enhanced tolerance against drought stress.

The natural variance of the Arabidopsis floral secondary metabolites

Application of mass spectrometry-based metabolomics enables the detection of genotype-related natural variance in metabolism. Differences in secondary metabolite composition of flowers of 64 Arabidopsis thaliana (Arabidopsis) natural accessions, representing a considerable portion of the natural variation in this species are presented. The raw metabolomic data of the accessions and reference extracts derived from flavonoid knockout mutants have been deposited in the MetaboLights database. Additionally, summary tables of floral secondary metabolite data are presented in this article to enable efficient re-use of the dataset either in metabolomics cross-study comparisons or correlation-based integrative analysis of other metabolomic and phenotypic features such as transcripts, proteins and growth and flowering related phenotypes.

Measurement of Arabidopsis thaliana Plant Traits Using the PHENOPSIS Phenotyping Platform

High-throughput phenotyping of plant traits is a powerful tool to further our understanding of plant growth and its underlying physiological, molecular, and genetic determinisms. This protocol describes the methodology of a standard phenotyping experiment in PHENOPSIS automated platform, which was engineered in INRA-LEPSE (https://www6.montpellier.inra.fr/lepse) and custom-made by Optimalog company. The seminal method was published by Granier et al. (2006). The platform is used to explore and test various ecophysiological hypotheses (Tisné et al., 2010; Baerenfaller et al., 2012; Vile et al., 2012; Bac-Molenaar et al., 2015; Rymaszewski et al., 2017). Here, the focus concerns the preparation and management of experiments, as well as measurements of growth-related traits (e.g., projected rosette area, total leaf area and growth rate), water status-related traits (e.g., leaf dry matter content and relative water content), and plant architecture-related traits (e.g., stomatal density and index and lamina/petiole ratio). Briefly, a completely randomized (block) design is set up in the growth chamber. Next, the substrate is prepared, its initial water content is measured and pots are filled. Seeds are sown onto the soil surface and germinated prior to the experiment. After germination, soil watering and image (visible, infra-red, fluorescence) acquisition are planned by the user and performed by the automaton. Destructive measurements may be performed during the experiment. Data extraction from images and estimation of growth-related trait values involves semi-automated procedures and statistical processing.

Genomic basis and evolutionary potential for extreme drought adaptation in Arabidopsis thaliana

As Earth is currently experiencing dramatic climate change, it is of critical interest to understand how species will respond to it. The chance of a species withstanding climate change is likely to depend on the diversity within the species and, particularly, whether there are sub-populations that are already adapted to extreme environments. However, most predictive studies ignore that species comprise genetically diverse individuals. We have identified genetic variants in Arabidopsis thaliana that are associated with survival of an extreme drought event-a major consequence of global warming. Subsequently, we determined how these variants are distributed across the native range of the species. Genetic alleles conferring higher drought survival showed signatures of polygenic adaptation and were more frequently found in Mediterranean and Scandinavian regions. Using geo-environmental models, we predicted that Central European, but not Mediterranean, populations might lag behind in adaptation by the end of the twenty-first century. Further analyses showed that a population decline could nevertheless be compensated by natural selection acting efficiently over standing variation or by migration of adapted individuals from populations at the margins of the species' distribution. These findings highlight the importance of within-species genetic heterogeneity in facilitating an evolutionary response to a changing climate.

Variation in relative water content, proline accumulation and stress gene expression in two cowpea landraces under drought

Many landraces of cowpea [Vigna unguiculata (L.) Walp.] are adapted to particular geographical and climatic conditions. Here we describe two landraces grown respectively in arid and temperate areas of Algeria and assess their physiological and molecular responses to drought stress. As expected, when deprived of water cowpea plants lose water over time with a gradual reduction in transpiration rate. The landraces differed in their relative water content (RWC) and whole plant transpiration rate. The landrace from Menia, an arid area, retained more water in adult leaves. Both landraces responded to drought stress at the molecular level by increasing expression of stress-related genes in aerial parts, including proline metabolism genes. Expression of gene(s) encoding proline synthesis enzyme P5CS was up regulated and gene expression of ProDH, a proline catabolism enzyme, was down regulated. Relatively low amounts of proline accumulated in adult leaves with slight differences between the two landraces. During drought stress the most apical part of plants stayed relatively turgid with a high RWC compared to distal parts that wilted. Expression of key stress genes was higher and more proline accumulated at the apex than in distal leaves indicating that cowpea has a non-uniform stress response at the whole plant level. Our study reveals a developmental control of water stress through preferential proline accumulation in the upper tier of the cowpea plant. We also conclude that cowpea landraces display physiological adaptations to water stress suited to the arid and temperate climates in which they are cultivated.

Natural variation identifies genes affecting drought-induced abscisic acid accumulation in Arabidopsis thaliana

Accumulation of the stress hormone abscisic acid (ABA) in response to drought and low water-potential controls many downstream acclimation mechanisms. However, mechanisms controlling ABA accumulation itself are less known. There was a 10-fold range of variation in ABA levels among nearly 300 Arabidopsis thaliana accessions exposed to the same low water-potential severity. Genome-wide association analysis (GWAS) identified genomic regions containing clusters of ABA-associated SNPs. Candidate genes within these regions included few genes with known stress or ABA-related function. The GWAS data were used to guide reverse genetic analysis, which found effectors of ABA accumulation. These included plasma-membrane-localized signaling proteins such as receptor-like kinases, aspartic protease, a putative lipid-binding START domain protein, and other membrane proteins of unknown function as well as a RING U-box protein and possible effect of tonoplast transport on ABA accumulation. Putative loss-of-function polymorphisms within the START domain protein were associated with climate factors at accession sites of origin, indicating its potential involvement in drought adaptation. Overall, using ABA accumulation as a basis for a combined GWAS-reverse genetic strategy revealed the broad natural variation in low-water-potential-induced ABA accumulation and was successful in identifying genes that affect ABA levels and may act in upstream drought-related sensing and signaling mechanisms. ABA effector loci were identified even when each one was of incremental effect, consistent with control of ABA accumulation being distributed among the many branches of ABA metabolism or mediated by genes with partially redundant function.

Multilevel Regulation of Abiotic Stress Responses in Plants

The sessile lifestyle of plants requires them to cope with stresses in situ. Plants overcome abiotic stresses by altering structure/morphology, and in some extreme conditions, by compressing the life cycle to survive the stresses in the form of seeds. Genetic and molecular studies have uncovered complex regulatory processes that coordinate stress adaptation and tolerance in plants, which are integrated at various levels. Investigating natural variation in stress responses has provided important insights into the evolutionary processes that shape the integrated regulation of adaptation and tolerance. This review primarily focuses on the current understanding of how transcriptional, post-transcriptional, post-translational, and epigenetic processes along with genetic variation orchestrate stress responses in plants. We also discuss the current and future development of computational tools to identify biologically meaningful factors from high dimensional, genome-scale data and construct the signaling networks consisting of these components.

Transcription through the eye of a needle: daily and annual cyclic gene expression variation in Douglas-fir needles

BACKGROUND

Perennial growth in plants is the product of interdependent cycles of daily and annual stimuli that induce cycles of growth and dormancy. In conifers, needles are the key perennial organ that integrates daily and seasonal signals from light, temperature, and water availability. To understand the relationship between seasonal cycles and seasonal gene expression responses in conifers, we examined diurnal and circannual needle mRNA accumulation in Douglas-fir (Pseudotsuga menziesii) needles at diurnal and circannual scales. Using mRNA sequencing, we sampled 6.1 × 10⁹ reads from 19 trees and constructed a de novo pan-transcriptome reference that includes 173,882 tree-derived transcripts. Using this reference, we mapped RNA-Seq reads from 179 samples that capture daily and annual variation.

RESULTS

We identified 12,042 diurnally-cyclic transcripts, 9299 of which showed homology to annotated genes from other plant genomes, including angiosperm core clock genes. Annual analysis revealed 21,225 circannual transcripts, 17,335 of which showed homology to annotated genes from other plant genomes. The timing of maximum gene expression is associated with light intensity at diurnal scales and photoperiod at annual scales, with approximately half of transcripts reaching maximum expression +/- 2 h from sunrise and sunset, and +/- 20 days from winter and summer solstices. Comparisons with published studies from other conifers shows congruent behavior in clock genes with Japanese cedar (Cryptomeria), and a significant preservation of gene expression patterns for 2278 putative orthologs from Douglas-fir during the summer growing season, and 760 putative orthologs from spruce (Picea) during the transition from fall to winter.

CONCLUSIONS

Our study highlight the extensive diurnal and circannual transcriptome variability demonstrated in conifer needles. At these temporal scales, 29% of expressed transcripts show a significant diurnal cycle, and 58.7% show a significant circannual cycle. Remarkably, thousands of genes reach their annual peak activity during winter dormancy. Our study establishes the fine-scale timing of daily and annual maximum gene expression for diverse needle genes in Douglas-fir, and it highlights the potential for using this information for evaluating hypotheses concerning the daily or seasonal timing of gene activity in temperate-zone conifers, and for identifying cyclic transcriptome components in other conifer species.

Genome-Wide Association Study of Developing Leaves' Heat Tolerance during Vegetative Growth Stages in a Sorghum Association Panel

Heat stress reduces grain yield and quality worldwide. Enhancing heat tolerance of crops at all developmental stages is one of the essential strategies required for sustaining agricultural production especially as frequency of temperature extremes escalates in response to climate change. Although heat tolerance mechanisms have been studied extensively in model plant species, little is known about the genetic control underlying heat stress responses of crop plants at the vegetative stage under field conditions. To dissect the genetic basis of heat tolerance in sorghum [ (L.) Moench], we performed a genome-wide association study (GWAS) for traits responsive to heat stress at the vegetative stage in an association panel. Natural variation in leaf firing (LF) and leaf blotching (LB) were evaluated separately for 3 yr in experimental fields at three locations where sporadic heat waves occurred throughout the sorghum growing season. We identified nine single-nucleotide polymorphisms (SNPs) that were significantly associated with LF and five SNPs that were associated with LB. Candidate genes near the SNPs were investigated and 14 were directly linked to biological pathways involved in plant stress responses including heat stress response. The findings of this study provide new knowledge on the genetic control of leaf traits responsive to heat stress in sorghum, which could aid in elucidating the genetic and molecular mechanisms of vegetative stage heat tolerance in crops. The results also provide candidate markers for molecular breeding of enhanced heat tolerance in cereal and bioenergy crops.

Natural variation in life history strategy of Arabidopsis thaliana determines stress responses to drought and insects of different feeding guilds

Plants are sessile organisms and, consequently, are exposed to a plethora of stresses in their local habitat. As a result, different populations of a species are subject to different selection pressures leading to adaptation to local conditions and intraspecific divergence. The annual brassicaceous plant Arabidopsis thaliana is an attractive model for ecologists and evolutionary biologists due to the availability of a large collection of resequenced natural accessions. Accessions of A. thaliana display one of two different life cycle strategies: summer and winter annuals. We exposed a collection of 308 European Arabidopsis accessions, that have been genotyped for 250K SNPs, to a range of stresses: one abiotic stress (drought), four biotic stresses (Pieris rapae caterpillars, Plutella xylostella caterpillars, Frankliniella occidentalis thrips and Myzus persicae aphids) and two combined stresses (drought plus P. rapae and Botrytis cinerea fungus plus P. rapae). We identified heritable genetic variation for responses to the different stresses, estimated by narrow-sense heritability. We found that accessions displaying different life cycle strategies differ in their response to stresses. Winter annuals are more resistant to drought, aphids and thrips and summer annuals are more resistant to P. rapae and P. xylostella caterpillars. Summer annuals are also more resistant to the combined stresses of drought plus P. rapae and infection by the fungus Botryris cinerea plus herbivory by P. rapae. Adaptation to drought displayed a longitudinal gradient. Finally, trade-offs were recorded between the response to drought and responses to herbivory by caterpillars of the specialist herbivore P. rapae.

Association mapping reveals the genetic architecture of tomato response to water deficit: focus on major fruit quality traits

Water scarcity constitutes a crucial constraint for agriculture productivity. High-throughput approaches in model plant species identified hundreds of genes potentially involved in survival under drought, but few having beneficial effects on quality and yield. Nonetheless, controlled water deficit may improve fruit quality through higher concentration of flavor compounds. The underlying genetic determinants are still poorly known. In this study, we phenotyped 141 highly diverse small fruit tomato accessions for 27 traits under two contrasting watering conditions. A subset of 55 accessions exhibited increased metabolite contents and maintained yield under water deficit. Using 6100 single nucleotide polymorphisms (SNPs), association mapping revealed 31, 41, and 44 quantitative trait loci (QTLs) under drought, control, and both conditions, respectively. Twenty-five additional QTLs were interactive between conditions, emphasizing the interest in accounting for QTLs by watering regime interactions in fruit quality improvement. Combining our results with the loci previously identified in a biparental progeny resulted in 11 common QTLs and contributed to a first detailed characterization of the genetic determinants of response to water deficit in tomato. Major QTLs for fruit quality traits were dissected and candidate genes were proposed using expression and polymorphism data. The outcomes provide a basis for fruit quality improvement under deficit irrigation while limiting yield losses.