Genome-wide association identifies a missing hydrolase for tocopherol synthesis in plants.

The tocopherol biosynthetic pathway, encoded by VTE genes 1 through 6, is highly conserved in plants but most large effect quantitative trait loci for seed total tocopherols (totalT) lack VTE genes, indicating other activities are involved. A genome-wide association study of Arabidopsis seed tocopherols showed five of seven significant intervals lacked VTE genes, including the most significant, which mapped to an uncharacterized, seed-specific, envelope-localized, alpha/beta hydrolase with esterase activity, designated AtVTE7. Atvte7 null mutants decreased seed totalT 55% while a leaky allele of the maize ortholog, ZmVTE7, decreased kernel and leaf totalT 38% and 49%, respectively. Overexpressing AtVTE7 or ZmVTE7 partially or fully complemented the Atvte7 seed phenotype and increased leaf totalT by 3.6- and 6.9-fold, respectively. VTE7 has the characteristics of an esterase postulated to provide phytol from chlorophyll degradation for tocopherol synthesis, but bulk chlorophyll levels were unaffected in vte7 mutants and overexpressing lines. Instead, levels of specific chlorophyll biosynthetic intermediates containing partially reduced side chains were impacted and strongly correlated with totalT. These intermediates are generated by a membrane-associated biosynthetic complex containing protochlorophyllide reductase, chlorophyll synthase, geranylgeranyl reductase (GGR) and light harvesting-like 3 protein, all of which are required for both chlorophyll and tocopherol biosynthesis. We propose a model where VTE7 releases prenyl alcohols from chlorophyll biosynthetic intermediates, which are then converted to the corresponding diphosphates for tocopherol biosynthesis.

Eleven biosynthetic genes explain the majority of natural variation in carotenoid levels in maize grain.

Vitamin A deficiency remains prevalent in parts of Asia, Latin America, and sub-Saharan Africa where maize (Zea mays) is a food staple. Extensive natural variation exists for carotenoids in maize grain. Here, to understand its genetic basis, we conducted a joint linkage and genome-wide association study of the US maize nested association mapping panel. Eleven of the 44 detected quantitative trait loci (QTL) were resolved to individual genes. Six of these were correlated expression and effect QTL (ceeQTL), showing strong correlations between RNA-seq expression abundances and QTL allelic effect estimates across six stages of grain development. These six ceeQTL also had the largest percentage of phenotypic variance explained, and in major part comprised the three to five loci capturing the bulk of genetic variation for each trait. Most of these ceeQTL had strongly correlated QTL allelic effect estimates across multiple traits. These findings provide an in-depth genome-level understanding of the genetic and molecular control of carotenoids in plants. In addition, these findings provide a roadmap to accelerate breeding for provitamin A and other priority carotenoid traits in maize grain that should be readily extendable to other cereals.

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.

Integrating GWAS and TWAS to elucidate the genetic architecture of maize leaf cuticular conductance.

The cuticle, a hydrophobic layer of cutin and waxes synthesized by plant epidermal cells, is the major barrier to water loss when stomata are closed. Dissecting the genetic architecture of natural variation for maize (Zea mays L.) leaf cuticular conductance (gc) is important for identifying genes relevant to improving crop productivity in drought-prone environments. To this end, we performed an integrated genome- and transcriptome-wide association studies (GWAS and TWAS) to identify candidate genes putatively regulating variation in leaf gc. Of the 22 plausible candidate genes identified, 4 were predicted to be involved in cuticle precursor biosynthesis and export, 2 in cell wall modification, 9 in intracellular membrane trafficking, and 7 in the regulation of cuticle development. A gene encoding an INCREASED SALT TOLERANCE1-LIKE1 (ISTL1) protein putatively involved in intracellular protein and membrane trafficking was identified in GWAS and TWAS as the strongest candidate causal gene. A set of maize nested near-isogenic lines that harbor the ISTL1 genomic region from eight donor parents were evaluated for gc, confirming the association between gc and ISTL1 in a haplotype-based association analysis. The findings of this study provide insights into the role of regulatory variation in the development of the maize leaf cuticle and will ultimately assist breeders to develop drought-tolerant maize for target environments.

Transcriptomic network analyses shed light on the regulation of cuticle development in maize leaves.

Plant cuticles are composed of wax and cutin and evolved in the land plants as a hydrophobic boundary that reduces water loss from the plant epidermis. The expanding maize adult leaf displays a dynamic, proximodistal gradient of cuticle development, from the leaf base to the tip. Laser microdissection RNA Sequencing (LM-RNAseq) was performed along this proximodistal gradient, and complementary network analyses identified potential regulators of cuticle biosynthesis and deposition. A weighted gene coexpression network (WGCN) analysis suggested a previously undescribed function for PHYTOCHROME-mediated light signaling during the regulation of cuticular wax deposition. Genetic analyses reveal that phyB1 phyB2 double mutants of maize exhibit abnormal cuticle composition, supporting the predictions of our coexpression analysis. Reverse genetic analyses also show that phy mutants of the moss Physcomitrella patens exhibit abnormal cuticle composition, suggesting an ancestral role for PHYTOCHROME-mediated, light-stimulated regulation of cuticle development during plant evolution.

Quantitative Genetic Analysis of Interactions in the Pepper-Phytophthora capsici Pathosystem.

The development of pepper cultivars with durable resistance to the oomycete Phytophthora capsici has been challenging due to differential interactions between the species that allow certain pathogen isolates to cause disease on otherwise resistant host genotypes. Currently, little is known about the pathogen genes involved in these interactions. To investigate the genetic basis of P. capsici virulence on individual pepper genotypes, we inoculated sixteen pepper accessions, representing commercial varieties, sources of resistance, and host differentials, with 117 isolates of P. capsici, for a total of 1,864 host-pathogen combinations. Analysis of disease outcomes revealed a significant effect of inter-species genotype-by-genotype interactions, although these interactions were quantitative rather than qualitative in scale. Isolates were classified into five pathogen subpopulations, as determined by their genotypes at over 60,000 single-nucleotide polymorphisms (SNPs). While absolute virulence levels on certain pepper accessions significantly differed between subpopulations, a multivariate phenotype reflecting relative virulence levels on certain pepper genotypes compared with others showed the strongest association with pathogen subpopulation. A genome-wide association study (GWAS) identified four pathogen loci significantly associated with virulence, two of which colocalized with putative RXLR effector genes and another with a polygalacturonase gene cluster. All four loci appeared to represent broad-spectrum virulence genes, as significant SNPs demonstrated consistent effects regardless of the host genotype tested. Host genotype-specific virulence variants in P. capsici may be difficult to map via GWAS with all but excessively large sample sizes, perhaps controlled by genes of small effect or by multiple allelic variants that have arisen independently. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Acylsugars protect Nicotiana benthamiana against insect herbivory and desiccation.

KEY MESSAGE: Nicotiana benthamiana acylsugar acyltransferase (ASAT) is required for protection against desiccation and insect herbivory. Knockout mutations provide a new resource for investigation of plant-aphid and plant-whitefly interactions. Nicotiana benthamiana is used extensively as a transient expression platform for functional analysis of genes from other species. Acylsugars, which are produced in the trichomes, are a hypothesized cause of the relatively high insect resistance that is observed in N. benthamiana. We characterized the N. benthamiana acylsugar profile, bioinformatically identified two acylsugar acyltransferase genes, ASAT1 and ASAT2, and used CRISPR/Cas9 mutagenesis to produce acylsugar-deficient plants for investigation of insect resistance and foliar water loss. Whereas asat1 mutations reduced accumulation, asat2 mutations caused almost complete depletion of foliar acylsucroses. Three hemipteran and three lepidopteran herbivores survived, gained weight, and/or reproduced significantly better on asat2 mutants than on wildtype N. benthamiana. Both asat1 and asat2 mutations reduced the water content and increased leaf temperature. Our results demonstrate the specific function of two ASAT proteins in N. benthamiana acylsugar biosynthesis, insect resistance, and desiccation tolerance. The improved growth of aphids and whiteflies on asat2 mutants will facilitate the use of N. benthamiana as a transient expression platform for the functional analysis of insect effectors and resistance genes from other plant species. Similarly, the absence of acylsugars in asat2 mutants will enable analysis of acylsugar biosynthesis genes from other Solanaceae by transient expression.

The Evolutionary History of Wild, Domesticated, and Feral Brassica oleracea (Brassicaceae).

Understanding the evolutionary history of crops, including identifying wild relatives, helps to provide insight for conservation and crop breeding efforts. Cultivated Brassica oleracea has intrigued researchers for centuries due to its wide diversity in forms, which include cabbage, broccoli, cauliflower, kale, kohlrabi, and Brussels sprouts. Yet, the evolutionary history of this species remains understudied. With such different vegetables produced from a single species, B. oleracea is a model organism for understanding the power of artificial selection. Persistent challenges in the study of B. oleracea include conflicting hypotheses regarding domestication and the identity of the closest living wild relative. Using newly generated RNA-seq data for a diversity panel of 224 accessions, which represents 14 different B. oleracea crop types and nine potential wild progenitor species, we integrate phylogenetic and population genetic techniques with ecological niche modeling, archaeological, and literary evidence to examine relationships among cultivars and wild relatives to clarify the origin of this horticulturally important species. Our analyses point to the Aegean endemic B. cretica as the closest living relative of cultivated B. oleracea, supporting an origin of cultivation in the Eastern Mediterranean region. Additionally, we identify several feral lineages, suggesting that cultivated plants of this species can revert to a wild-like state with relative ease. By expanding our understanding of the evolutionary history in B. oleracea, these results contribute to a growing body of knowledge on crop domestication that will facilitate continued breeding efforts including adaptation to changing environmental conditions.

Phenotyping stomatal closure by thermal imaging for GWAS and TWAS of water use efficiency-related genes.

Stomata allow CO2 uptake by leaves for photosynthetic assimilation at the cost of water vapor loss to the atmosphere. The opening and closing of stomata in response to fluctuations in light intensity regulate CO2 and water fluxes and are essential for maintaining water-use efficiency (WUE). However, a little is known about the genetic basis for natural variation in stomatal movement, especially in C4 crops. This is partly because the stomatal response to a change in light intensity is difficult to measure at the scale required for association studies. Here, we used high-throughput thermal imaging to bypass the phenotyping bottleneck and assess 10 traits describing stomatal conductance (gs) before, during and after a stepwise decrease in light intensity for a diversity panel of 659 sorghum (Sorghum bicolor) accessions. Results from thermal imaging significantly correlated with photosynthetic gas exchange measurements. gs traits varied substantially across the population and were moderately heritable (h2 up to 0.72). An integrated genome-wide and transcriptome-wide association study identified candidate genes putatively driving variation in stomatal conductance traits. Of the 239 unique candidate genes identified with the greatest confidence, 77 were putative orthologs of Arabidopsis (Arabidopsis thaliana) genes related to functions implicated in WUE, including stomatal opening/closing (24 genes), stomatal/epidermal cell development (35 genes), leaf/vasculature development (12 genes), or chlorophyll metabolism/photosynthesis (8 genes). These findings demonstrate an approach to finding genotype-to-phenotype relationships for a challenging trait as well as candidate genes for further investigation of the genetic basis of WUE in a model C4 grass for bioenergy, food, and forage production.

Machine learning-enabled phenotyping for GWAS and TWAS of WUE traits in 869 field-grown sorghum accessions.

Sorghum (Sorghum bicolor) is a model C4 crop made experimentally tractable by extensive genomic and genetic resources. Biomass sorghum is studied as a feedstock for biofuel and forage. Mechanistic modeling suggests that reducing stomatal conductance (gs) could improve sorghum intrinsic water use efficiency (iWUE) and biomass production. Phenotyping to discover genotype-to-phenotype associations remains a bottleneck in understanding the mechanistic basis for natural variation in gs and iWUE. This study addressed multiple methodological limitations. Optical tomography and a machine learning tool were combined to measure stomatal density (SD). This was combined with rapid measurements of leaf photosynthetic gas exchange and specific leaf area (SLA). These traits were the subject of genome-wide association study and transcriptome-wide association study across 869 field-grown biomass sorghum accessions. The ratio of intracellular to ambient CO2 was genetically correlated with SD, SLA, gs, and biomass production. Plasticity in SD and SLA was interrelated with each other and with productivity across wet and dry growing seasons. Moderate-to-high heritability of traits studied across the large mapping population validated associations between DNA sequence variation or RNA transcript abundance and trait variation. A total of 394 unique genes underpinning variation in WUE-related traits are described with higher confidence because they were identified in multiple independent tests. This list was enriched in genes whose Arabidopsis (Arabidopsis thaliana) putative orthologs have functions related to stomatal or leaf development and leaf gas exchange, as well as genes with nonsynonymous/missense variants. These advances in methodology and knowledge will facilitate improving C4 crop WUE.

A combined BSA-Seq and linkage mapping approach identifies genomic regions associated with Phytophthora root and crown rot resistance in squash.

KEY MESSAGE: Two QTL mapping approaches were used to identify a total of six QTL associated with Phytophthora root and crown rot resistance in a biparental squash population. Phytophthora root and crown rot, caused by the soilborne oomycete pathogen Phytophthora capsici, leads to severe yield losses in squash (Cucurbita pepo). To identify quantitative trait loci (QTL) involved in resistance to this disease, we crossed a partially resistant squash breeding line with a susceptible zucchini cultivar and evaluated over 13,000 F2 seedlings in a greenhouse screen. Bulked segregant analysis with whole genome resequencing (BSA-Seq) resulted in the identification of five genomic regions-on chromosomes 4, 5, 8, 12, and 16-featuring significant allele frequency differentiation between susceptible and resistant bulks in each of two independent replicates. In addition, we conducted linkage mapping using a population of 176 F3 families derived from individually genotyped F2 individuals. Variation in disease severity among these families was best explained by a four-QTL model, comprising the same loci identified via BSA-Seq on chromosomes 4, 5, and 8 as well as an additional locus on chromosome 19, for a combined total of six QTL identified between both methods. Loci, whether those identified by BSA-Seq or linkage mapping, were of small-to-moderate effect, collectively accounting for 28-35% and individually for 2-10% of the phenotypic variance explained. However, a multiple linear regression model using one marker in each BSA-Seq QTL could predict F2:3 disease severity with only a slight drop in cross-validation accuracy compared to genomic prediction models using genome-wide markers. These results suggest that marker-assisted selection could be a suitable approach for improving Phytophthora crown and root rot resistance in squash.

Multi-omics prediction of oat agronomic and seed nutritional traits across environments and in distantly related populations.

KEY MESSAGE: Integration of multi-omics data improved prediction accuracies of oat agronomic and seed nutritional traits in multi-environment trials and distantly related populations in addition to the single-environment prediction. Multi-omics prediction has been shown to be superior to genomic prediction with genome-wide DNA-based genetic markers (G) for predicting phenotypes. However, most of the existing studies were based on historical datasets from one environment; therefore, they were unable to evaluate the efficiency of multi-omics prediction in multi-environment trials and distantly related populations. To fill those gaps, we designed a systematic experiment to collect omics data and evaluate 17 traits in two oat breeding populations planted in single and multiple environments. In the single-environment trial, transcriptomic BLUP (T), metabolomic BLUP (M), G + T, G + M, and G + T + M models showed greater prediction accuracy than GBLUP for 5, 10, 11, 17, and 17 traits, respectively, and metabolites generally performed better than transcripts when combined with SNPs. In the multi-environment trial, multi-trait models with omics data outperformed both counterpart multi-trait GBLUP models and single-environment omics models, and the highest prediction accuracy was achieved when modeling genetic covariance as an unstructured covariance model. We also demonstrated that omics data can be used to prioritize loci from one population with omics data to improve genomic prediction in a distantly related population using a two-kernel linear model that accommodated both likely casual loci with large-effect and loci that explain little or no phenotypic variance. We propose that the two-kernel linear model is superior to most genomic prediction models that assume each variant is equally likely to affect the trait and can be used to improve prediction accuracy for any trait with prior knowledge of genetic architecture.

Genome-Wide Association Study in New York Phytophthora capsici Isolates Reveals Loci Involved in Mating Type and Mefenoxam Sensitivity.

Phytophthora capsici is a soilborne oomycete plant pathogen that causes severe vegetable crop losses in New York (NY) state and worldwide. This pathogen is difficult to manage, in part due to its production of long-lasting sexual spores and its tendency to quickly evolve fungicide resistance. We single nucleotide polymorphism (SNP) genotyped 252 P. capsici isolates, predominantly from NY, in order to conduct a genome-wide association study for mating type and mefenoxam sensitivity. The population structure and extent of chromosomal copy number variation in this collection of isolates were also characterized. Population structure analyses showed isolates largely clustered by the field site where they were collected, with values of FST between pairs of fields ranging from 0.10 to 0.31. Thirty-three isolates were putative aneuploids, demonstrating evidence for having up to four linkage groups present in more than two copies, and an additional two isolates appeared to be genome-wide triploids. Mating type was mapped to a region on scaffold 4, consistent with previous findings, and mefenoxam sensitivity was associated with several SNP markers at a novel locus on scaffold 62. We identified several candidate genes for mefenoxam sensitivity, including a homolog of yeast ribosome synthesis factor Rrp5, but failed to locate near the scaffold 62 locus any subunits of RNA polymerase I, the hypothesized target site of phenylamide fungicides in oomycetes. This work expands our knowledge of the population biology of P. capsici and provides a foundation for functional validation of candidate genes associated with epidemiologically important phenotypes.

Heritable temporal gene expression patterns correlate with metabolomic seed content in developing hexaploid oat seed.

Oat ranks sixth in world cereal production and has a higher content of health-promoting compounds compared with other cereals. However, there is neither a robust oat reference genome nor transcriptome. Using deeply sequenced full-length mRNA libraries of oat cultivar Ogle-C, a de novo high-quality and comprehensive oat seed transcriptome was assembled. With this reference transcriptome and QuantSeq 3' mRNA sequencing, gene expression was quantified during seed development from 22 diverse lines across six time points. Transcript expression showed higher correlations between adjacent time points. Based on differentially expressed genes, we identified 22 major temporal co-expression (TCoE) patterns of gene expression and revealed enriched gene ontology biological processes. Within each TCoE set, highly correlated transcripts, putatively commonly affected by genetic background, were clustered and termed genetic co-expression (GCoE) sets. Seventeen of the 22 TCoE sets had GCoE sets with median heritabilities higher than 0.50, and these heritability estimates were much higher than that estimated from permutation analysis, with no divergence observed in cluster sizes between permutation and non-permutation analyses. Linear regression between 634 metabolites from mature seeds and the PC1 score of each of the GCoE sets showed significantly lower p-values than permutation analysis. Temporal expression patterns of oat avenanthramides and lipid biosynthetic genes were concordant with previous studies of avenanthramide biosynthetic enzyme activity and lipid accumulation. This study expands our understanding of physiological processes that occur during oat seed maturation and provides plant breeders the means to change oat seed composition through targeted manipulation of key pathways.

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.

Divergence of defensive cucurbitacins in independent Cucurbita pepo domestication events leads to differences in specialist herbivore preference.

Crop domestication and improvement often concurrently affect plant resistance to pests and production of secondary metabolites, creating challenges for isolating the ecological implications of selection for specific metabolites. Cucurbitacins are bitter triterpenoids with extreme phenotypic differences between Cucurbitaceae lineages, yet we lack integrated models of herbivore preference, cucurbitacin accumulation, and underlying genetic mechanisms. In Cucurbita pepo, we dissected the effect of cotyledon cucurbitacins on preference of a specialist insect pest (Acalymma vittatum) for multiple tissues, assessed genetic loci underlying cucurbitacin accumulation in diverse germplasm and a biparental F2 population (from a cross between two independent domesticates), and characterized quantitative associations between gene expression and metabolites during seedling development. Acalymma vittatum affinity for cotyledons is mediated by cucurbitacins, but other traits contribute to whole-plant resistance. Cotyledon cucurbitacin accumulation was associated with population structure, and our genetic mapping identified a single locus, Bi-4, containing genes relevant to transport and regulation - not biosynthesis - that diverged between lineages. These candidate genes were expressed during seedling development, most prominently a putative secondary metabolite transporter. Taken together, these findings support the testable hypothesis that breeding for plant resistance to insects involves targeting genes for regulation and transport of defensive metabolites, in addition to core biosynthesis genes.

Novel Loci Underlie Natural Variation in Vitamin E Levels in Maize Grain.

Tocopherols, tocotrienols, and plastochromanols (collectively termed tocochromanols) are lipid-soluble antioxidants synthesized by all plants. Their dietary intake, primarily from seed oils, provides vitamin E and other health benefits. Tocochromanol biosynthesis has been dissected in the dicot Arabidopsis thaliana, which has green, photosynthetic seeds, but our understanding of tocochromanol accumulation in major crops, whose seeds are nonphotosynthetic, remains limited. To understand the genetic control of tocochromanols in grain, we conducted a joint linkage and genome-wide association study in the 5000-line U.S. maize (Zea mays) nested association mapping panel. Fifty-two quantitative trait loci for individual and total tocochromanols were identified, and of the 14 resolved to individual genes, six encode novel activities affecting tocochromanols in plants. These include two chlorophyll biosynthetic enzymes that explain the majority of tocopherol variation, which was not predicted given that, like most major cereal crops, maize grain is nonphotosynthetic. This comprehensive assessment of natural variation in vitamin E levels in maize establishes the foundation for improving tocochromanol and vitamin E content in seeds of maize and other major cereal crops.

Temporal covariance structure of multi-spectral phenotypes and their predictive ability for end-of-season traits in maize.

KEY MESSAGE: Heritable variation in phenotypes extracted from multi-spectral images (MSIs) and strong genetic correlations with end-of-season traits indicates the value of MSIs for crop improvement and modeling of plant growth curve. Vegetation indices (VIs) derived from multi-spectral imaging (MSI) platforms can be used to study properties of crop canopy, providing non-destructive phenotypes that could be used to better understand growth curves throughout the growing season. To investigate the amount of variation present in several VIs and their relationship with important end-of-season traits, genetic and residual (co)variances for VIs, grain yield and moisture were estimated using data collected from maize hybrid trials. The VIs considered were Normalized Difference Vegetation Index (NDVI), Green NDVI, Red Edge NDVI, Soil-Adjusted Vegetation Index, Enhanced Vegetation Index and simple Ratio of Near Infrared to Red (Red) reflectance. Genetic correlations of VIs with grain yield and moisture were used to fit multi-trait models for prediction of end-of-season traits and evaluated using within site/year cross-validation. To explore alternatives to fitting multiple phenotypes from MSI, random regression models with linear splines were fit using data collected in 2016 and 2017. Heritability estimates ranging from (0.10 to 0.82) were observed, indicating that there exists considerable amount of genetic variation in these VIs. Furthermore, strong genetic and residual correlations of the VIs, NDVI and NDRE, with grain yield and moisture were found. Considerable increases in prediction accuracy were observed from the multi-trait model when using NDVI and NDRE as a secondary trait. Finally, random regression with a linear spline function shows potential to be used as an alternative to mixed models to fit VIs from multiple time points.

Network-Guided GWAS Improves Identification of Genes Affecting Free Amino Acids.

Amino acids are essential for proper growth and development in plants. Amino acids serve as building blocks for proteins but also are important for responses to stress and the biosynthesis of numerous essential compounds. In seed, the pool of free amino acids (FAAs) also contributes to alternative energy, desiccation, and seed vigor; thus, manipulating FAA levels can significantly impact a seed's nutritional qualities. While genome-wide association studies (GWAS) on branched-chain amino acids have identified some regulatory genes controlling seed FAAs, the genetic regulation of FAA levels, composition, and homeostasis in seeds remains mostly unresolved. Hence, we performed GWAS on 18 FAAs from a 313-ecotype Arabidopsis (Arabidopsis thaliana) association panel. Specifically, GWAS was performed on 98 traits derived from known amino acid metabolic pathways (approach 1) and then on 92 traits generated from an unbiased correlation-based metabolic network analysis (approach 2), and the results were compared. The latter approach facilitated the discovery of additional novel metabolic interactions and single-nucleotide polymorphism-trait associations not identified by the former approach. The most prominent network-guided GWAS signal was for a histidine (His)-related trait in a region containing two genes: a cationic amino acid transporter (CAT4) and a polynucleotide phosphorylase resistant to inhibition with fosmidomycin. A reverse genetics approach confirmed CAT4 to be responsible for the natural variation of His-related traits across the association panel. Given that His is a semiessential amino acid and a potent metal chelator, CAT4 orthologs could be considered as candidate genes for seed quality biofortification in crop plants.

ZEAXANTHIN EPOXIDASE Activity Potentiates Carotenoid Degradation in Maturing Seed.

Elucidation of the carotenoid biosynthetic pathway has enabled altering the composition and content of carotenoids in various plants, but to achieve desired nutritional impacts, the genetic components regulating carotenoid homeostasis in seed, the plant organ consumed in greatest abundance, must be elucidated. We used a combination of linkage mapping, genome-wide association studies (GWAS), and pathway-level analysis to identify nine loci that impact the natural variation of seed carotenoids in Arabidopsis (Arabidopsis thaliana). ZEAXANTHIN EPOXIDASE (ZEP) was the major contributor to carotenoid composition, with mutants lacking ZEP activity showing a remarkable 6-fold increase in total seed carotenoids relative to the wild type. Natural variation in ZEP gene expression during seed development was identified as the underlying mechanism for fine-tuning carotenoid composition, stability, and ultimately content in Arabidopsis seed. We previously showed that two CAROTENOID CLEAVAGE DIOXYGENASE enzymes, CCD1 and CCD4, are the primary mediators of seed carotenoid degradation, and here we demonstrate that ZEP acts as an upstream control point of carotenoid homeostasis, with ZEP-mediated epoxidation targeting carotenoids for degradation by CCD enzymes. Finally, four of the nine loci/enzymatic activities identified as underlying natural variation in Arabidopsis seed carotenoids also were identified in a recent GWAS of maize (Zea mays) kernel carotenoid variation. This first comparison of the natural variation in seed carotenoids in monocots and dicots suggests a surprising overlap in the genetic architecture of these traits between the two lineages and provides a list of likely candidates to target for selecting seed carotenoid variation in other species.