Characterization of a foxtail mosaic virus vector for gene silencing and analysis of innate immune responses in Sorghum bicolor.

Sorghum is vulnerable to many biotic and abiotic stresses, which cause considerable yield losses globally. Efforts to genetically characterize beneficial sorghum traits, including disease resistance, plant architecture, and tolerance to abiotic stresses, are ongoing. One challenge faced by sorghum researchers is its recalcitrance to transformation, which has slowed gene validation efforts and utilization for cultivar development. Here, we characterize the use of a foxtail mosaic virus (FoMV) vector for virus-induced gene silencing (VIGS) by targeting two previously tested marker genes: phytoene desaturase (PDS) and ubiquitin (Ub). We additionally demonstrate VIGS of a subgroup of receptor-like cytoplasmic kinases (RLCKs) and report the role of these genes as positive regulators of early defence signalling. Silencing of subgroup 8 RLCKs also resulted in higher susceptibility to the bacterial pathogens Pseudomonas syringae pv. syringae (B728a) and Xanthomonas vasicola pv. holcicola, demonstrating the role of these genes in host defence against bacterial pathogens. Together, this work highlights the utility of FoMV-induced gene silencing in the characterization of genes mediating defence responses in sorghum. Moreover, FoMV was able to systemically infect six diverse sorghum genotypes with high efficiency at optimal temperatures for sorghum growth and therefore could be extrapolated to study additional traits of economic importance.

Dissection of canopy layer-specific genetic control of leaf angle in Sorghum bicolor by RNA sequencing.

BACKGROUND: Leaf angle is an important plant architecture trait, affecting plant density, light interception efficiency, photosynthetic rate, and yield. The "smart canopy" model proposes more vertical leaves in the top plant layers and more horizontal leaves in the lower canopy, maximizing conversion efficiency and photosynthesis. Sorghum leaf arrangement is opposite to that proposed in the "smart canopy" model, indicating the need for improvement. Although leaf angle quantitative trait loci (QTL) have been previously reported, only the Dwarf3 (Dw3) auxin transporter gene, colocalizing with a major-effect QTL on chromosome 7, has been validated. Additionally, the genetic architecture of leaf angle across canopy layers remains to be elucidated. RESULTS: This study characterized the canopy-layer specific transcriptome of five sorghum genotypes using RNA sequencing. A set of 284 differentially expressed genes for at least one layer comparison (FDR < 0.05) co-localized with 69 leaf angle QTL and were consistently identified across genotypes. These genes are involved in transmembrane transport, hormone regulation, oxidation-reduction process, response to stimuli, lipid metabolism, and photosynthesis. The most relevant eleven candidate genes for layer-specific angle modification include those homologous to genes controlling leaf angle in rice and maize or genes associated with cell size/expansion, shape, and cell number. CONCLUSIONS: Considering the predicted functions of candidate genes, their potential undesirable pleiotropic effects should be further investigated across tissues and developmental stages. Future validation of proposed candidates and exploitation through genetic engineering or gene editing strategies targeted to collar cells will bring researchers closer to the realization of a "smart canopy" sorghum.

Dissecting the genetic control of natural variation in sorghum photosynthetic response to drought stress.

Drought stress causes crop yield losses worldwide. Sorghum is a C4 species tolerant to moderate drought stress, and its extensive natural variation for photosynthetic traits under water-limiting conditions can be exploited for developing cultivars with enhanced stress tolerance. The objective of this study was to discover genes/genomic regions that control the sorghum photosynthetic capacity under pre-anthesis water-limiting conditions. We performed a genome-wide association study for seven photosynthetic gas exchange and chlorophyll fluorescence traits during three periods of contrasting soil volumetric water content (VWC): control (30% VWC), drought (15% VWC), and recovery (30% VWC). Water stress was imposed with an automated irrigation system that generated a controlled dry-down period for all plants, to perform an unbiased genotypic comparison. A total of 60 genomic regions were associated with natural variation in one or more photosynthetic traits in a particular treatment or with derived variables. We identified 33 promising candidate genes with predicted functions related to stress signaling, oxidative stress protection, hormonal response to stress, and dehydration protection. Our results provide new knowledge about the natural variation and genetic control of sorghum photosynthetic response to drought with the ultimate goal of improving its adaptation and productivity under water stress scenarios.

Meta-analysis identifies pleiotropic loci controlling phenotypic trade-offs in sorghum.

Community association populations are composed of phenotypically and genetically diverse accessions. Once these populations are genotyped, the resulting marker data can be reused by different groups investigating the genetic basis of different traits. Because the same genotypes are observed and scored for a wide range of traits in different environments, these populations represent a unique resource to investigate pleiotropy. Here, we assembled a set of 234 separate trait datasets for the Sorghum Association Panel, a group of 406 sorghum genotypes widely employed by the sorghum genetics community. Comparison of genome-wide association studies (GWAS) conducted with two independently generated marker sets for this population demonstrate that existing genetic marker sets do not saturate the genome and likely capture only 35-43% of potentially detectable loci controlling variation for traits scored in this population. While limited evidence for pleiotropy was apparent in cross-GWAS comparisons, a multivariate adaptive shrinkage approach recovered both known pleiotropic effects of existing loci and new pleiotropic effects, particularly significant impacts of known dwarfing genes on root architecture. In addition, we identified new loci with pleiotropic effects consistent with known trade-offs in sorghum development. These results demonstrate the potential for mining existing trait datasets from widely used community association populations to enable new discoveries from existing trait datasets as new, denser genetic marker datasets are generated for existing community association populations.

Identification and utilization of genetic determinants of trait measurement errors in image-based, high-throughput phenotyping.

The accuracy of trait measurements greatly affects the quality of genetic analyses. During automated phenotyping, trait measurement errors, i.e. differences between automatically extracted trait values and ground truth, are often treated as random effects that can be controlled by increasing population sizes and/or replication number. In contrast, there is some evidence that trait measurement errors may be partially under genetic control. Consistent with this hypothesis, we observed substantial nonrandom, genetic contributions to trait measurement errors for five maize (Zea mays) tassel traits collected using an image-based phenotyping platform. The phenotyping accuracy varied according to whether a tassel exhibited "open" versus. "closed" branching architecture, which is itself under genetic control. Trait-associated SNPs (TASs) identified via genome-wide association studies (GWASs) conducted on five tassel traits that had been phenotyped both manually (i.e. ground truth) and via feature extraction from images exhibit little overlap. Furthermore, identification of TASs from GWASs conducted on the differences between the two values indicated that a fraction of measurement error is under genetic control. Similar results were obtained in a sorghum (Sorghum bicolor) plant height dataset, demonstrating that trait measurement error is genetically determined in multiple species and traits. Trait measurement bias cannot be controlled by increasing population size and/or replication number.

Toward "Smart Canopy" Sorghum: Discovery of the Genetic Control of Leaf Angle Across Layers.

A "smart canopy" ideotype has been proposed with leaves being upright at the top and more horizontal toward the bottom of the plant to maximize light interception and conversion efficiencies, and thus increasing yield. The genetic control of leaf angle has, to date, been studied on one or two leaves, or data have been merged from multiple leaves to generate average values. This approach has limited our understanding of the diversity of leaf angles across layers and their genetic control. Genome-wide association studies and quantitative trait loci mapping studies in sorghum (Sorghum bicolor) were performed using layer-specific angle data collected manually and via high-throughput phenotyping strategies. The observed distribution of angles in indoor and field settings is opposite to the ideotype. Several genomic regions were associated with leaf angle within layers or across the canopy. The expression of the brassinosteroid-related transcription factor BZR1/BES1 and the auxin-transporter Dwarf3 were found to be highly correlated with the distribution of angles at different layers. The application of a brassinosteroid biosynthesis inhibitor could not revert the undesirable overall angle distribution. These discoveries demonstrate that the exploitation of layer-specific quantitative trait loci/genes will be instrumental to reversing the natural angle distribution in sorghum according to the "smart canopy" ideotype.

Semiautomated Feature Extraction from RGB Images for Sorghum Panicle Architecture GWAS.

Because structural variation in the inflorescence architecture of cereal crops can influence yield, it is of interest to identify the genes responsible for this variation. However, the manual collection of inflorescence phenotypes can be time consuming for the large populations needed to conduct genome-wide association studies (GWAS) and is difficult for multidimensional traits such as volume. A semiautomated phenotyping pipeline, TIM (Toolkit for Inflorescence Measurement), was developed and used to extract unidimensional and multidimensional features from images of 1,064 sorghum (Sorghum bicolor) panicles from 272 genotypes comprising a subset of the Sorghum Association Panel. GWAS detected 35 unique single-nucleotide polymorphisms associated with variation in inflorescence architecture. The accuracy of the TIM pipeline is supported by the fact that several of these trait-associated single-nucleotide polymorphisms (TASs) are located within chromosomal regions associated with similar traits in previously published quantitative trait locus and GWAS analyses of sorghum. Additionally, sorghum homologs of maize (Zea mays) and rice (Oryza sativa) genes known to affect inflorescence architecture are enriched in the vicinities of TASs. Finally, our TASs are enriched within genomic regions that exhibit high levels of divergence between converted tropical lines and cultivars, consistent with the hypothesis that these chromosomal intervals were targets of selection during modern breeding.

A cost-effective and customizable automated irrigation system for precise high-throughput phenotyping in drought stress studies.

The development of high-yielding crops with drought tolerance is necessary to increase food, feed, fiber and fuel production. Methods that create similar environmental conditions for a large number of genotypes are essential to investigate plant responses to drought in gene discovery studies. Modern facilities that control water availability for each plant remain cost-prohibited to some sections of the research community. We present an alternative cost-effective automated irrigation system scalable for a high-throughput and controlled dry-down treatment of plants. This system was tested in sorghum using two experiments. First, four genotypes were subjected to ten days of dry-down to achieve three final Volumetric Water Content (VWC) levels: drought (0.10 and 0.20 m3 m-3) and control (0.30 m3 m-3). The final average VWC was 0.11, 0.22, and 0.31 m3 m-3, respectively, and significant differences in biomass accumulation were observed between control and drought treatments. Second, 42 diverse sorghum genotypes were subjected to a seven-day dry-down treatment for a final drought stress of 0.15 m3 m-3 VWC. The final average VWC was 0.17 m3 m-3, and plants presented significant differences in photosynthetic rate during the drought period. These results demonstrate that cost-effective automation systems can successfully control substrate water content for each plant, to accurately compare their phenotypic responses to drought, and be scaled up for high-throughput phenotyping studies.

Differential manipulation of leaf angle throughout the canopy: current status and prospects.

Leaf angle is defined as the inclination between the midrib of the leaf blade and the vertical stem of a plant. This trait has been identified as a key component in the development of high-yielding varieties of cereal species, particularly maize, rice, wheat, and sorghum. The effect of leaf angle on light interception efficiency, photosynthetic rate, and yield has been investigated since the 1960s, yet, significant knowledge gaps remain in understanding the genetic control of this complex trait. Recent advances in physiology and modeling have proposed a plant ideotype with varying leaf angles throughout the canopy. In this context, we present historical and recent evidence of: (i) the effect of leaf angle on photosynthetic efficiency and yield; (ii) the hormonal regulation of this trait; (iii) the current knowledge on its quantitative genetic control; and (iv) the opportunity to utilize high-throughput phenotyping methods to characterize leaf angle at multiple canopy levels. We focus on research conducted on grass species of economic importance, with similar plant architecture and growth patterns. Finally, we present the challenges and strategies plant breeders will need to embrace in order to manipulate leaf angle differentially throughout the canopy and develop superior crops for food, feed, and fuel production.

Genetic architecture of photosynthesis in Sorghum bicolor under non-stress and cold stress conditions.

Sorghum (Sorghum bicolor L. Moench) is a C4 species sensitive to the cold spring conditions that occur at northern latitudes, especially when coupled with excessive light, and that greatly affect the photosynthetic rate. The objective of this study was to discover genes/genomic regions that control the capacity to cope with excessive energy under low temperature conditions during the vegetative growth period. A genome-wide association study (GWAS) was conducted for seven photosynthetic gas exchange and chlorophyll fluorescence traits under three consecutive temperature treatments: control (28 °C/24 °C), cold (15 °C/15 °C), and recovery (28 °C/24 °C). Cold stress significantly reduced the rate of photosynthetic CO2 uptake of sorghum plants, and a total of 143 unique genomic regions were discovered associated with at least one trait in a particular treatment or with derived variables. Ten regions on chromosomes 3, 4, 6, 7, and 8 that harbor multiple significant markers in linkage disequilibrium (LD) were consistently identified in gas exchange and chlorophyll fluorescence traits. Several candidate genes within those intervals have predicted functions related to carotenoids, phytohormones, thioredoxin, components of PSI, and antioxidants. These regions represent the most promising results for future validation and with potential application for the improvement of crop productivity under cold stress.

A High-Throughput, Field-Based Phenotyping Technology for Tall Biomass Crops.

Recent advances in omics technologies have not been accompanied by equally efficient, cost-effective, and accurate phenotyping methods required to dissect the genetic architecture of complex traits. Even though high-throughput phenotyping platforms have been developed for controlled environments, field-based aerial and ground technologies have only been designed and deployed for short-stature crops. Therefore, we developed and tested Phenobot 1.0, an auto-steered and self-propelled field-based high-throughput phenotyping platform for tall dense canopy crops, such as sorghum (Sorghum bicolor). Phenobot 1.0 was equipped with laterally positioned and vertically stacked stereo RGB cameras. Images collected from 307 diverse sorghum lines were reconstructed in 3D for feature extraction. User interfaces were developed, and multiple algorithms were evaluated for their accuracy in estimating plant height and stem diameter. Tested feature extraction methods included the following: (1) User-interactive Individual Plant Height Extraction (UsIn-PHe) based on dense stereo three-dimensional reconstruction; (2) Automatic Hedge-based Plant Height Extraction (Auto-PHe) based on dense stereo 3D reconstruction; (3) User-interactive Dense Stereo Matching Stem Diameter Extraction; and (4) User-interactive Image Patch Stereo Matching Stem Diameter Extraction (IPaS-Di). Comparative genome-wide association analysis and ground-truth validation demonstrated that both UsIn-PHe and Auto-PHe were accurate methods to estimate plant height, while Auto-PHe had the additional advantage of being a completely automated process. For stem diameter, IPaS-Di generated the most accurate estimates of this biomass-related architectural trait. In summary, our technology was proven robust to obtain ground-based high-throughput plant architecture parameters of sorghum, a tall and densely planted crop species.

Genome-Wide Association Study for Nine Plant Architecture Traits in Sorghum.

Sorghum [ (L) Moench], an important grain and forage crop, is receiving significant attention as a lignocellulosic feedstock because of its water-use efficiency and high biomass yield potential. Because of the advancement of genotyping and sequencing technologies, genome-wide association study (GWAS) has become a routinely used method to investigate the genetic mechanisms underlying natural phenotypic variation. In this study, we performed a GWAS for nine grain and biomass-related plant architecture traits to determine their overall genetic architecture and the specific association of allelic variants in gibberellin (GA) biosynthesis and signaling genes with these phenotypes. A total of 101 single-nucleotide polymorphism (SNP) representative regions were associated with at least one of the nine traits, and two of the significant markers correspond to GA candidate genes, () and (), affecting plant height and seed number, respectively. The resolution of a previously reported quantitative trait loci (QTL) for leaf angle on chromosome 7 was increased to a 1.67 Mb region containing seven candidate genes with good prospects for further investigation. This study provides new knowledge of the association of GA genes with plant architecture traits and the genomic regions controlling variation in leaf angle, stem circumference, internode number, tiller number, seed number, panicle exsertion, and panicle length. The GA gene affecting seed number variation () and the genomic region on chromosome 7 associated with variation in leaf angle are also important outcomes of this study and represent the foundation of future validation studies needed to apply this knowledge in breeding programs.

QQS orphan gene regulates carbon and nitrogen partitioning across species via NF-YC interactions.

The allocation of carbon and nitrogen resources to the synthesis of plant proteins, carbohydrates, and lipids is complex and under the control of many genes; much remains to be understood about this process. QQS (Qua-Quine Starch; At3g30720), an orphan gene unique to Arabidopsis thaliana, regulates metabolic processes affecting carbon and nitrogen partitioning among proteins and carbohydrates, modulating leaf and seed composition in Arabidopsis and soybean. Here the universality of QQS function in modulating carbon and nitrogen allocation is exemplified by a series of transgenic experiments. We show that ectopic expression of QQS increases soybean protein independent of the genetic background and original protein content of the cultivar. Furthermore, transgenic QQS expression increases the protein content of maize, a C4 species (a species that uses 4-carbon photosynthesis), and rice, a protein-poor agronomic crop, both highly divergent from Arabidopsis. We determine that QQS protein binds to the transcriptional regulator AtNF-YC4 (Arabidopsis nuclear factor Y, subunit C4). Overexpression of AtNF-YC4 in Arabidopsis mimics the QQS-overexpression phenotype, increasing protein and decreasing starch levels. NF-YC, a component of the NF-Y complex, is conserved across eukaryotes. The NF-YC4 homologs of soybean, rice, and maize also bind to QQS, which provides an explanation of how QQS can act in species where it does not occur endogenously. These findings are, to our knowledge, the first insight into the mechanism of action of QQS in modulating carbon and nitrogen allocation across species. They have major implications for the emergence and function of orphan genes, and identify a nontransgenic strategy for modulating protein levels in crop species, a trait of great agronomic significance.

Association mapping of brassinosteroid candidate genes and plant architecture in a diverse panel of Sorghum bicolor.

KEY MESSAGE: This first association analysis between plant architecture and BR candidate genes in sorghum suggests that natural allelic variation has significant and pleiotropic effects on plant architecture phenotypes. Sorghum bicolor (L) Moench is a self-pollinated species traditionally used as a staple crop for human consumption and as a forage crop for livestock feed. Recently, sorghum has received attention as a bioenergy crop due to its water use efficiency and biomass yield potential. Breeding for superior bioenergy-type lines requires knowledge of the genetic mechanisms controlling plant architecture. Brassinosteroids (BRs) are a group of hormones that determine plant growth, development, and architecture. Biochemical and genetic information on BRs are available from model species but the application of that knowledge to crop species has been very limited. A candidate gene association mapping approach and a diverse sorghum collection of 315 accessions were used to assess marker-trait associations between BR biosynthesis and signaling genes and six plant architecture traits. A total of 263 single nucleotide polymorphisms (SNPs) from 26 BR genes were tested, 73 SNPs were significantly associated with the phenotypes of interest and 18 of those were associated with more than one trait. An analysis of the phenotypic variation explained by each BR pathway revealed that the signaling pathway had a larger effect for most phenotypes (R (2) = 0.05-0.23). This study constitutes the first association analysis between plant architecture and BR genes in sorghum and the first LD mapping for leaf angle, stem circumference, panicle exsertion and panicle length. Markers on or close to BKI1 associated with all phenotypes and thus, they are the most important outcomes of this study and will be further validated for their future application in breeding programs.

From dwarves to giants? Plant height manipulation for biomass yield.

The increasing demand for lignocellulosic biomass for the production of biofuels provides value to vegetative plant tissue and leads to a paradigm shift for optimizing plant architecture in bioenergy crops. Plant height (PHT) is among the most important biomass yield components and is the focus of this review, with emphasis on the energy grasses maize (Zea mays) and sorghum (Sorghum bicolor). We discuss the scientific advances in the identification of PHT quantitative trait loci (QTLs) and the understanding of pathways and genes controlling PHT, especially gibberellins and brassinosteroids. We consider pleiotropic effects of QTLs or genes affecting PHT on other agronomically important traits and, finally, we discuss strategies for applying this knowledge to the improvement of dual-purpose or dedicated bioenergy crops.

Equilibrium processes cannot explain high levels of short- and medium-range linkage disequilibrium in the domesticated grass Sorghum bicolor.

Patterns of linkage disequilibrium (LD) are of interest because they provide evidence of both equilibrium (e.g., mating system or long-term population structure) and nonequilibrium (e.g., demographic or selective) processes, as well as because of their importance in strategies for identifying the genetic basis of complex phenotypes. We report patterns of short and medium range (up to 100 kb) LD in six unlinked genomic regions in the partially selfing domesticated grass, Sorghum bicolor. The extent of allelic associations in S. bicolor, as assessed by pairwise measures of LD, is higher than in maize but lower than in Arabidopsis, in qualitative agreement with expectations based on mating system. Quantitative analyses of the population recombination parameter, rho, however, based on empirical estimates of rates of recombination, mutation, and self-pollination, show that LD is more extensive than expected under a neutral equilibrium model. The disparity between rho and the population mutation parameter, , is similar to that observed in other species whose population history appears to be complex. From a practical standpoint, these results suggest that S. bicolor is well suited for association studies using reasonable numbers of markers, since LD typically extends at least several kilobases but has largely decayed by 15 kb.