Genome resources for three modern cotton lines guide future breeding efforts.

Cotton (Gossypium hirsutum L.) is the key renewable fibre crop worldwide, yet its yield and fibre quality show high variability due to genotype-specific traits and complex interactions among cultivars, management practices and environmental factors. Modern breeding practices may limit future yield gains due to a narrow founding gene pool. Precision breeding and biotechnological approaches offer potential solutions, contingent on accurate cultivar-specific data. Here we address this need by generating high-quality reference genomes for three modern cotton cultivars ('UGA230', 'UA48' and 'CSX8308') and updating the 'TM-1' cotton genetic standard reference. Despite hypothesized genetic uniformity, considerable sequence and structural variation was observed among the four genomes, which overlap with ancient and ongoing genomic introgressions from 'Pima' cotton, gene regulatory mechanisms and phenotypic trait divergence. Differentially expressed genes across fibre development correlate with fibre production, potentially contributing to the distinctive fibre quality traits observed in modern cotton cultivars. These genomes and comparative analyses provide a valuable foundation for future genetic endeavours to enhance global cotton yield and sustainability.

Leaf cuticular wax composition of a genetically diverse collection of lettuce (Lactuca sativa L.) cultivars evaluated under field conditions.

Cuticular waxes of plants impart tolerance to many forms of environmental stress and help shed dangerous human pathogens on edible plant parts. Although the chemical composition of waxes on a wide variety of important crops has been described, a detailed wax compositional analysis has yet to be reported for lettuce (Lactuca sativa L.), one of the most widely consumed vegetables. We present herein the leaf wax content and composition of 12 genetically diverse lettuce cultivars sampled across five time points during their vegetative growth phase in the field. Mean total leaf wax amounts across all cultivars varied little over 28 days of vegetative growth, except for a notable decrease in total waxes following a major precipitation event, presumably due to wax degradation from wind and rain. All lettuce cultivars were found to contain a unique wax composition highly enriched in 22- and 24-carbon length 1-alcohols (docosanol and tetracosanol, respectively). In our report, the dominance of these shorter chain length 1-alcohols as wax constituents represents a relatively rare phenotype in plants. The ecological significance of these dominant and relatively short 1-alcohols is still unknown. Although waxes have been a target for improvement of various crops, no such work has been reported for lettuce. This study lays the groundwork for future research that aims to integrate cuticular wax characteristics of field grown plants into the larger context of lettuce breeding and cultivar development.

PhytoOracle: Scalable, modular phenomics data processing pipelines.

As phenomics data volume and dimensionality increase due to advancements in sensor technology, there is an urgent need to develop and implement scalable data processing pipelines. Current phenomics data processing pipelines lack modularity, extensibility, and processing distribution across sensor modalities and phenotyping platforms. To address these challenges, we developed PhytoOracle (PO), a suite of modular, scalable pipelines for processing large volumes of field phenomics RGB, thermal, PSII chlorophyll fluorescence 2D images, and 3D point clouds. PhytoOracle aims to (i) improve data processing efficiency; (ii) provide an extensible, reproducible computing framework; and (iii) enable data fusion of multi-modal phenomics data. PhytoOracle integrates open-source distributed computing frameworks for parallel processing on high-performance computing, cloud, and local computing environments. Each pipeline component is available as a standalone container, providing transferability, extensibility, and reproducibility. The PO pipeline extracts and associates individual plant traits across sensor modalities and collection time points, representing a unique multi-system approach to addressing the genotype-phenotype gap. To date, PO supports lettuce and sorghum phenotypic trait extraction, with a goal of widening the range of supported species in the future. At the maximum number of cores tested in this study (1,024 cores), PO processing times were: 235 minutes for 9,270 RGB images (140.7 GB), 235 minutes for 9,270 thermal images (5.4 GB), and 13 minutes for 39,678 PSII images (86.2 GB). These processing times represent end-to-end processing, from raw data to fully processed numerical phenotypic trait data. Repeatability values of 0.39-0.95 (bounding area), 0.81-0.95 (axis-aligned bounding volume), 0.79-0.94 (oriented bounding volume), 0.83-0.95 (plant height), and 0.81-0.95 (number of points) were observed in Field Scanalyzer data. We also show the ability of PO to process drone data with a repeatability of 0.55-0.95 (bounding area).

Selection of favorable alleles of genes controlling flowering and senescence improves malt barley quality.

Malt barley (Hordeum vulgare L.) is an important cash crop with stringent grain quality standards. Timing of the switch from vegetative to reproductive growth and timing of whole-plant senescence and nutrient remobilization are critical for cereal grain yield and quality. Understanding the genetic variation in genes associated with these developmental traits can streamline genotypic selection of superior malt barley germplasm. Here, we determined the effects of allelic variation in three genes encoding a glycine-rich RNA-binding protein (HvGR-RBP1) and two NAC transcription factors (HvNAM1 and HvNAM2) on malt barley agronomics and quality using previously developed markers for HvGR-RBP1 and HvNAM1 and a novel marker for HvNAM2. Based on a single-nucleotide polymorphism (SNP) in the first intron, the utilized marker differentiates NAM2 alleles of low-grain protein variety 'Karl' and of higher protein variety 'Lewis'. We demonstrate that the selection of favorable alleles for each gene impacts heading date, senescence timing, grain size, grain protein concentration, and malt quality. Specifically, combining 'Karl' alleles for the two NAC genes with the 'Lewis' HvGR-RBP1 allele extends grain fill duration, increases the percentage of plump kernels, decreases grain protein, and provides malt quality stability. Molecular markers for these genes are therefore highly useful tools in malt barley breeding. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-022-01331-7.

Assessing Drought and Heat Stress-Induced Changes in the Cotton Leaf Metabolome and Their Relationship With Hyperspectral Reflectance.

The study of phenotypes that reveal mechanisms of adaptation to drought and heat stress is crucial for the development of climate resilient crops in the face of climate uncertainty. The leaf metabolome effectively summarizes stress-driven perturbations of the plant physiological status and represents an intermediate phenotype that bridges the plant genome and phenome. The objective of this study was to analyze the effect of water deficit and heat stress on the leaf metabolome of 22 genetically diverse accessions of upland cotton grown in the Arizona low desert over two consecutive years. Results revealed that membrane lipid remodeling was the main leaf mechanism of adaptation to drought. The magnitude of metabolic adaptations to drought, which had an impact on fiber traits, was found to be quantitatively and qualitatively associated with different stress severity levels during the two years of the field trial. Leaf-level hyperspectral reflectance data were also used to predict the leaf metabolite profiles of the cotton accessions. Multivariate statistical models using hyperspectral data accurately estimated (R 2 > 0.7 in ∼34% of the metabolites) and predicted (Q 2 > 0.5 in 15-25% of the metabolites) many leaf metabolites. Predicted values of metabolites could efficiently discriminate stressed and non-stressed samples and reveal which regions of the reflectance spectrum were the most informative for predictions. Combined together, these findings suggest that hyperspectral sensors can be used for the rapid, non-destructive estimation of leaf metabolites, which can summarize the plant physiological status.

A minimally disruptive method for measuring water potential in planta using hydrogel nanoreporters.

Leaf water potential is a critical indicator of plant water status, integrating soil moisture status, plant physiology, and environmental conditions. There are few tools for measuring plant water status (water potential) in situ, presenting a critical barrier for developing appropriate phenotyping (measurement) methods for crop development and modeling efforts aimed at understanding water transport in plants. Here, we present the development of an in situ, minimally disruptive hydrogel nanoreporter (AquaDust) for measuring leaf water potential. The gel matrix responds to changes in water potential in its local environment by swelling; the distance between covalently linked dyes changes with the reconfiguration of the polymer, leading to changes in the emission spectrum via Förster Resonance Energy Transfer (FRET). Upon infiltration into leaves, the nanoparticles localize within the apoplastic space in the mesophyll; they do not enter the cytoplasm or the xylem. We characterize the physical basis for AquaDust's response and demonstrate its function in intact maize (Zea mays L.) leaves as a reporter of leaf water potential. We use AquaDust to measure gradients of water potential along intact, actively transpiring leaves as a function of water status; the localized nature of the reporters allows us to define a hydraulic model that distinguishes resistances inside and outside the xylem. We also present field measurements with AquaDust through a full diurnal cycle to confirm the robustness of the technique and of our model. We conclude that AquaDust offers potential opportunities for high-throughput field measurements and spatially resolved studies of water relations within plant tissues.

Combined effects of a glycine-rich RNA-binding protein and a NAC transcription factor extend grain fill duration and improve malt barley agronomic performance.

KEY MESSAGE: Two key barley genes independently control anthesis and senescence timing, enabling the manipulation of grain fill duration, grain size/plumpness, and grain protein concentration. Plant developmental processes such as flowering and senescence have direct effects on cereal yield and quality. Previous work highlighted the importance of two tightly linked genes encoding a glycine-rich RNA-binding protein (HvGR-RBP1) and a NAC transcription factor (HvNAM1), controlling barley anthesis timing, senescence, and percent grain protein. Varieties that differ in HvGR-RBP1 expression, 'Karl'(low) and 'Lewis'(high), also differ in sequence 1 KB upstream of translation start site, including an ~ 400 bp G rich insertion in the 5'-flanking region of the 'Karl' allele, which could disrupt gene expression. To improve malt quality, the (low-grain protein, delayed-senescence) 'Karl' HvNAM1 allele was introgressed into Montana germplasm. After several seasons of selection, the resulting germplasm was screened for the allelic combinations of HvGR-RBP1 and HvNAM1, finding lines combining 'Karl' alleles for both genes (-/-), lines combining 'Lewis' (functional, expressed) HvGR-RBP1 with 'Karl' HvNAM1 alleles ( ±), and lines combining 'Lewis' alleles for both genes (+ / +). Field experiments indicate that the functional ('Lewis,' +) HvGR-RBP1 allele is associated with earlier anthesis and with slightly shorter plants, while the 'Karl' (-) HvNAM1 allele delays maturation. Genotypes carrying the ± allele combination therefore had a significantly (3 days) extended grain fill duration, leading to a higher percentage of plump kernels, slightly enhanced test weight, and lower grain protein concentration when compared to the other allele combinations. Overall, our data suggest an important function for HvGR-RBP1 in the control of barley reproductive development and set the stage for a more detailed functional analysis of this gene.

Chlorophyll fluorescence imaging captures photochemical efficiency of grain sorghum (Sorghum bicolor) in a field setting.

BACKGROUND: Photosynthesis is one of the most important biological reactions and forms the basis of crop productivity and yield on which a growing global population relies. However, to develop improved plant cultivars that are capable of increased productivity, methods that can accurately and quickly quantify photosynthetic efficiency in large numbers of genotypes under field conditions are needed. Chlorophyll fluorescence imaging is a rapid, non-destructive measurement that can provide insight into the efficiency of the light-dependent reactions of photosynthesis. RESULTS: To test and validate a field-deployed fluorescence imaging system on the TERRA-REF field scanalyzer, leaves of potted sorghum plants were treated with a photosystem II inhibitor, DCMU, to reduce photochemical efficiency (FV/FM). The ability of the fluorescence imaging system to detect changes in fluorescence was determined by comparing the image-derived values with a handheld fluorometer. This study demonstrated that the imaging system was able to accurately measure photochemical efficiency (FV/FM) and was highly correlated (r = 0.92) with the handheld fluorometer values. Additionally, the fluorescence imaging system was able to track the decrease in photochemical efficiency due to treatment of DCMU over a 7 day period. CONCLUSIONS: The system's ability to capture the temporal dynamics of the plants' response to this induced stress, which has comparable dynamics to abiotic and biotic stressors found in field environments, indicates the system is operating correctly. With the validation of the fluorescence imaging system, physiological and genetic studies can be undertaken that leverage the fluorescence imaging capabilities and throughput of the field scanalyzer.

Use of hydraulic traits for modeling genotype-specific acclimation in cotton under drought.

Understanding the genetic and physiological basis of abiotic stress tolerance under field conditions is key to varietal crop improvement in the face of climate variability. Here, we investigate dynamic physiological responses to water stress in silico and their relationships to genotypic variation in hydraulic traits of cotton (Gossypium hirsutum), an economically important species for renewable textile fiber production. In conjunction with an ecophysiological process-based model, heterogeneous data (plant hydraulic traits, spatially-distributed soil texture, soil water content and canopy temperature) were used to examine hydraulic characteristics of cotton, evaluate their consequences on whole plant performance under drought, and explore potential genotype × environment effects. Cotton was found to have R-shaped hydraulic vulnerability curves (VCs), which were consistent under drought stress initiated at flowering. Stem VCs, expressed as percent loss of conductivity, differed across genotypes, whereas root VCs did not. Simulation results demonstrated how plant physiological stress can depend on the interaction between soil properties and irrigation management, which in turn affect genotypic rankings of transpiration in a time-dependent manner. Our study shows how a process-based modeling framework can be used to link genotypic variation in hydraulic traits to differential acclimating behaviors under drought.

Transcriptomic and evolutionary analysis of the mechanisms by which P. argentatum, a rubber producing perennial, responds to drought.

BACKGROUND: Guayule (Parthenium argentatum Gray) is a drought tolerant, rubber producing perennial shrub native to northern Mexico and the US Southwest. Hevea brasiliensis, currently the world's only source of natural rubber, is grown as a monoculture, leaving it vulnerable to both biotic and abiotic stressors. Isolation of rubber from guayule occurs by mechanical harvesting of the entire plant. It has been reported that environmental conditions leading up to harvest have a profound impact on rubber yield. The link between rubber biosynthesis and drought, a common environmental condition in guayule's native habitat, is currently unclear. RESULTS: We took a transcriptomic and comparative genomic approach to determine how drought impacts rubber biosynthesis in guayule. We compared transcriptional profiles of stem tissue, the location of guayule rubber biosynthesis, collected from field-grown plants subjected to water-deficit (drought) and well-watered (control) conditions. Plants subjected to the imposed drought conditions displayed an increase in production of transcripts associated with defense responses and water homeostasis, and a decrease in transcripts associated with rubber biosynthesis. An evolutionary and comparative analysis of stress-response transcripts suggests that more anciently duplicated transcripts shared among the Asteraceae, rather than recently derived duplicates, are contributing to the drought response observed in guayule. In addition, we identified several deeply conserved long non-coding RNAs (lncRNAs) containing microRNA binding motifs. One lncRNA in particular, with origins at the base of Asteraceae, may be regulating the vegetative to reproductive transition observed in water-stressed guayule by acting as a miRNA sponge for miR166. CONCLUSIONS: These data represent the first genomic analyses of how guayule responds to drought like conditions in agricultural production settings. We identified an inverse relationship between stress-responsive transcripts and those associated with precursor pathways to rubber biosynthesis suggesting a physiological trade-off between maintaining homeostasis and plant productivity. We also identify a number of regulators of abiotic responses, including transcription factors and lncRNAs, that are strong candidates for future projects aimed at modulating rubber biosynthesis under water-limiting conditions common to guayules' native production environment.

Mapping of HKT1;5 Gene in Barley Using GWAS Approach and Its Implication in Salt Tolerance Mechanism.

Sodium (Na+) accumulation in the cytosol will result in ion homeostasis imbalance and toxicity of transpiring leaves. Studies of salinity tolerance in the diploid wheat ancestor Triticum monococcum showed that HKT1;5-like gene was a major gene in the QTL for salt tolerance, named Nax2. In the present study, we were interested in investigating the molecular mechanisms underpinning the role of the HKT1;5 gene in salt tolerance in barley (Hordeum vulgare). A USDA mini-core collection of 2,671 barley lines, part of a field trial was screened for salinity tolerance, and a Genome Wide Association Study (GWAS) was performed. Our results showed important SNPs that are correlated with salt tolerance that mapped to a region where HKT1;5 ion transporter located on chromosome four. Furthermore, sodium (Na+) and potassium (K+) content analysis revealed that tolerant lines accumulate more sodium in roots and leaf sheaths, than in the sensitive ones. In contrast, sodium concentration was reduced in leaf blades of the tolerant lines under salt stress. In the absence of NaCl, the concentration of Na+ and K+ were the same in the roots, leaf sheaths and leaf blades between the tolerant and the sensitive lines. In order to study the molecular mechanism behind that, alleles of the HKT1;5 gene from five tolerant and five sensitive barley lines were cloned and sequenced. Sequence analysis did not show the presence of any polymorphism that distinguishes between the tolerant and sensitive alleles. Our real-time RT-PCR experiments, showed that the expression of HKT1;5 gene in roots of the tolerant line was significantly induced after challenging the plants with salt stress. In contrast, in leaf sheaths the expression was decreased after salt treatment. In sensitive lines, there was no difference in the expression of HKT1;5 gene in leaf sheath under control and saline conditions, while a slight increase in the expression was observed in roots after salt treatment. These results provide stronger evidence that HKT1;5 gene in barley play a key role in withdrawing Na+ from the xylem and therefore reducing its transport to leaves. Given all that, these data support the hypothesis that HKT1;5 gene is responsible for Na+ unloading to the xylem and controlling its distribution in the shoots, which provide new insight into the understanding of this QTL for salinity tolerance in barley.

Multivariate Analysis of the Cotton Seed Ionome Reveals a Shared Genetic Architecture.

To mitigate the effects of heat and drought stress, a better understanding of the genetic control of physiological responses to these environmental conditions is needed. To this end, we evaluated an upland cotton (Gossypium hirsutum L.) mapping population under water-limited and well-watered conditions in a hot, arid environment. The elemental concentrations (ionome) of seed samples from the population were profiled in addition to those of soil samples taken from throughout the field site to better model environmental variation. The elements profiled in seeds exhibited moderate to high heritabilities, as well as strong phenotypic and genotypic correlations between elements that were not altered by the imposed irrigation regimes. Quantitative trait loci (QTL) mapping results from a Bayesian classification method identified multiple genomic regions where QTL for individual elements colocalized, suggesting that genetic control of the ionome is highly interrelated. To more fully explore this genetic architecture, multivariate QTL mapping was implemented among groups of biochemically related elements. This analysis revealed both additional and pleiotropic QTL responsible for coordinated control of phenotypic variation for elemental accumulation. Machine learning algorithms that utilized only ionomic data predicted the irrigation regime under which genotypes were evaluated with very high accuracy. Taken together, these results demonstrate the extent to which the seed ionome is genetically interrelated and predictive of plant physiological responses to adverse environmental conditions.

Investigation of the Influence of Leaf Thickness on Canopy Reflectance and Physiological Traits in Upland and Pima Cotton Populations.

Many systems for field-based, high-throughput phenotyping (FB-HTP) quantify and characterize the reflected radiation from the crop canopy to derive phenotypes, as well as infer plant function and health status. However, given the technology's nascent status, it remains unknown how biophysical and physiological properties of the plant canopy impact downstream interpretation and application of canopy reflectance data. In that light, we assessed relationships between leaf thickness and several canopy-associated traits, including normalized difference vegetation index (NDVI), which was collected via active reflectance sensors carried on a mobile FB-HTP system, carbon isotope discrimination (CID), and chlorophyll content. To investigate the relationships among traits, two distinct cotton populations, an upland (Gossypium hirsutum L.) recombinant inbred line (RIL) population of 95 lines and a Pima (G. barbadense L.) population composed of 25 diverse cultivars, were evaluated under contrasting irrigation regimes, water-limited (WL) and well-watered (WW) conditions, across 3 years. We detected four quantitative trait loci (QTL) and significant variation in both populations for leaf thickness among genotypes as well as high estimates of broad-sense heritability (on average, above 0.7 for both populations), indicating a strong genetic basis for leaf thickness. Strong phenotypic correlations (maximum r = -0.73) were observed between leaf thickness and NDVI in the Pima population, but not the RIL population. Additionally, estimated genotypic correlations within the RIL population for leaf thickness with CID, chlorophyll content, and nitrogen discrimination ([Formula: see text] = -0.32, 0.48, and 0.40, respectively) were all significant under WW but not WL conditions. Economically important fiber quality traits did not exhibit significant phenotypic or genotypic correlations with canopy traits. Overall, our results support considering variation in leaf thickness as a potential contributing factor to variation in NDVI or other canopy traits measured via proximal sensing, and as a trait that impacts fundamental physiological responses of plants.

Field-Based High-Throughput Plant Phenotyping Reveals the Temporal Patterns of Quantitative Trait Loci Associated with Stress-Responsive Traits in Cotton.

The application of high-throughput plant phenotyping (HTPP) to continuously study plant populations under relevant growing conditions creates the possibility to more efficiently dissect the genetic basis of dynamic adaptive traits. Toward this end, we employed a field-based HTPP system that deployed sets of sensors to simultaneously measure canopy temperature, reflectance, and height on a cotton (Gossypium hirsutum L.) recombinant inbred line mapping population. The evaluation trials were conducted under well-watered and water-limited conditions in a replicated field experiment at a hot, arid location in central Arizona, with trait measurements taken at different times on multiple days across 2010-2012. Canopy temperature, normalized difference vegetation index (NDVI), height, and leaf area index (LAI) displayed moderate-to-high broad-sense heritabilities, as well as varied interactions among genotypes with water regime and time of day. Distinct temporal patterns of quantitative trait loci (QTL) expression were mostly observed for canopy temperature and NDVI, and varied across plant developmental stages. In addition, the strength of correlation between HTPP canopy traits and agronomic traits, such as lint yield, displayed a time-dependent relationship. We also found that the genomic position of some QTL controlling HTPP canopy traits were shared with those of QTL identified for agronomic and physiological traits. This work demonstrates the novel use of a field-based HTPP system to study the genetic basis of stress-adaptive traits in cotton, and these results have the potential to facilitate the development of stress-resilient cotton cultivars.