New candidate loci and marker genes on chromosome 7 for improved chilling tolerance in sorghum

Multi-locus genome-wide association study reveal genomic regions underlying root system architecture traits in Ethiopian sorghum germplasm

The identification of genomic regions underlying the root system architecture (RSA) is vital for improving crop abiotic stress tolerance. To improve sorghum (Sorghum bicolor L. Moench) for environmental stress tolerance, information on genetic variability and genomic regions linked to RSA traits is paramount. The aim of this study was, therefore, to investigate common quantitative trait nucleotides (QTNs) via multiple methodologies and identify genomic regions linked to RSA traits in a panel of 274 Ethiopian sorghum accessions. Multi-locus genome-wide association study was conducted using 265,944 high-quality single nucleotide polymorphism markers. Considering the QTN detected by at least three different methods, a total of 17 reliable QTNs were found to be significantly associated with root angle, number, length, and dry weight. Four QTNs were detected on chromosome SBI-05, followed by SBI-01 and SBI-02 with three QTNs each. Among the 17 QTNs, 11 are colocated with previously identified root traits quantitative trait loci and the remaining six are genome regions with novel genes. A total of 118 genes are colocated with these up- and down-streams of the QTNs. Moreover, five QTNs were found intragenic. These QTNs are S5_8994835 (number of nodal roots), S10_55702393 (number of nodal roots), S1_56872999 (nodal root angle), S9_1212069 (nodal root angle), and S5_5667192 (root dry weight) intragenic regions of Sobic.005G073101, Sobic.010G198000, Sobic.001G273000, Sobic.009G013600, and Sobic.005G054700, respectively. Particularly, Sobic.005G073101, Sobic.010G198000, and Sobic.009G013600 were found responsible for the plant growth hormone-induced RSA. These genes may regulate root development in the seedling stage. Further analysis on these genes might be important to explore the genetic structure of RSA of sorghum.

Precise colocalization of sorghum's major chilling tolerance locus with Tannin1 due to tight linkage drag rather than antagonistic pleiotropy

Chilling tolerance in crops can increase resilience through longer growing seasons, drought escape, and nitrogen use efficiency. In sorghum (Sorghum bicolor [L.] Moench), breeding for chilling tolerance has been stymied by coinheritance of the largest-effect chilling tolerance locus, qSbCT04.62, with the major gene underlying undesirable grain proanthocyanidins, WD40 transcriptional regulator Tannin1. To test if this coinheritance is due to antagonistic pleiotropy of Tannin1, we developed and studied near-isogenic lines (NILs) carrying chilling tolerant haplotypes at qCT04.62. Whole-genome sequencing of the NILs revealed introgressions spanning part of the qCT04.62 confidence interval, including the Tannin1 gene and an ortholog of Arabidopsis cold regulator CBF/DREB1G. Segregation pattern of grain tannin in NILs confirmed the presence of wildtype Tannin1 and the reconstitution of a functional MYB-bHLH-WD40 regulatory complex. Low-temperature germination did not differ between NILs, suggesting that Tannin1 does not modulate this component of chilling tolerance. Similarly, NILs did not differ in seedling growth rate under either of two contrasting controlled environment chilling scenarios. Finally, while the chilling tolerant parent line had notably different photosynthetic responses from the susceptible parent line - including greater non-photochemical quenching before, during, and after chilling - the NIL responses match the susceptible parent. Thus, our findings suggest that tight linkage drag, not pleiotropy, underlies the precise colocalization of Tan1 with qCT04.62 and the qCT04.62 quantitative trait nucleotide lies outside the NIL introgressions. Breaking linkage at this locus should advance chilling tolerance breeding in sorghum and the identification of a novel chilling tolerance regulator.

Time of day and genotype sensitivity adjust molecular responses to temperature stress in sorghum

Sorghum is one of the four major C4 crops that are considered to be tolerant to environmental extremes. Sorghum shows distinct growth responses to temperature stress depending on the sensitivity of the genetic background. About half of the transcripts in sorghum exhibit diurnal rhythmic expressions emphasizing significant coordination with the environment. However, an understanding of how molecular dynamics contribute to genotype-specific stress responses in the context of the time of day is not known. We examined whether temperature stress and the time of day impact the gene expression dynamics in thermo-sensitive and thermo-tolerant sorghum genotypes. We found that time of day is highly influencing the temperature stress responses, which can be explained by the rhythmic expression of most thermo-responsive genes. This effect is more pronounced in thermo-tolerant genotypes, suggesting a stronger regulation of gene expression by the time of day and/or by the circadian clock. Genotypic differences were mostly observed on average gene expression levels, which may be responsible for contrasting sensitivities to temperature stress in tolerant versus susceptible sorghum varieties. We also identified groups of genes altered by temperature stress in a time-of-day and genotype-specific manner. These include transcriptional regulators and several members of the Ca2+ -binding EF-hand protein family. We hypothesize that expression variation of these genes between genotypes along with time-of-day independent regulation may contribute to genotype-specific fine-tuning of thermo-responsive pathways. These findings offer a new opportunity to selectively target specific genes in efforts to develop climate-resilient crops based on their time-of-day and genotype variation responses to temperature stress.

Genetic dissection of root architecture in Ethiopian sorghum landraces

KEY MESSAGE

This study quantified genetic variation in root system architecture (root number, angle, length and dry mass) within a diversity panel of 1771 Ethiopian sorghum landraces and identified 22 genomic regions associated with the root variations. The root system architecture (RSA) of crop plants influences adaptation to water-limited conditions and determines the capacity of a plant to access soil water and nutrients. Four key root traits (number, angle, length and dry mass) were evaluated in a diversity panel of 1771 Ethiopian sorghum landraces using purpose-built root chambers. Significant genetic variation was observed in all studied root traits, with nodal root angle ranging from 16.4° to 26.6°, with a high repeatability of 78.9%. Genome wide association studies identified a total of 22 genomic regions associated with root traits which were distributed on all chromosomes except chromosome SBI-10. Among the 22 root genomic regions, 15 co-located with RSA trait QTL previously identified in sorghum, with the remaining seven representing novel RSA QTL. The majority (85.7%) of identified root angle QTL also co-localized with QTL previously identified for stay-green in sorghum. This suggests that the stay-green phenotype might be associated with root architecture that enhances water extraction during water stress conditions. The results open avenues for manipulating root phenotypes to improve productivity in abiotic stress environments via marker-assisted selection.

Novel QTL for chilling tolerance at germination and early seedling stages in sorghum

Sorghum (Sorghum bicolor L.) a drought tolerant staple crop for half a billion people in Africa and Asia, an important source of animal feed throughout the world and a biofuel feedstock of growing importanceorghum’s originated from tropical regions rendering the crop to be cold sensitive. Low temperature stresses such as chilling and frost greatly affect the agronomic performance of sorghum and limit its geographical distribution, posing a major problem in temperate environments when sorghum is planted early. Understanding the genetic basis of wide adaptability and of sorghum would facilitate molecular breeding programs and studies of other C4 crops. The objective of this study is to conduct quantitative trait loci analysis using genotying by sequencing for early seed germination and seedling cold tolerance in two sorghum recombinant inbred lines populations. To accomplish that, we used two populations of recombinant inbred lines (RIL) developed from crosses between cold-tolerant (CT19, ICSV700) and cold-sensitive (TX430, M81E) parents. The derived RIL populations were evaluated for single nucleotide polymorphism (SNP) using genotype-by-sequencing (GBS) in the field and under controlled environments for their response to chilling stress. Linkage maps were constructed with 464 and 875 SNPs for the CT19 X TX430 (C1) and ICSV700 X M81 E (C2) populations respectively. Using quantitative trait loci (QTL) mapping, we identified QTL conferring tolerance to chilling tolerance at the seedling stage. A total of 16 and 39 total QTL were identified in the C1 and C2 populations, respectively. Two major QTL were identified in the C1 population, and three major QTL were mapped in the C2 population. Comparisons between the two populations and with previously identified QTL show a high degree of similarity in QTL locations. Given the amount of co-localization of QTL across traits and the direction of allelic effect supports that these regions have a pleiotropic effect. These QTL regions were also identified to be highly enriched for genes encoding chilling stress and hormonal response genes. This identified QTL can be useful in developing tools for molecular breeding of sorghums with improved low-temperature germinability.

Impact of climate perturbations on seeds and seed quality for global agriculture

In agriculture, seeds are the most basic and vital input on which croplands productivity depends. These implies a good starting material, good production lines and good storage options. High-quality seed lots must be free of pests and pathogens and contain a required degree of genetic purity. Seeds need also to be stored in good condition between harvest and later sowing, to insure later on the field a good plant density and higher crop yield. In general, these parameters are already widely accepted and considered in many countries where advanced technologies evaluate them. However, the more and more frequently devastating climate changes observed around the world has put seed quality under threat, and current seeds may not be adapted to hazardous and unpredictable conditions. Climate-related factors such as temperature and water availability directly affect seed development and later germination. For these reasons, investigating seed quality in response to climate changes is a step to propose new crop varieties and practices that will bring solutions for our future.

Low- and High-Temperature Phenotypic Diversity of Brassica carinata Genotypes for Early-Season Growth and Development

Temperature is a major abiotic stress factor limiting plant growth and development during the early developmental stage. Information on carinata (Brassica carinata A. Braun) traits response to low and high temperatures is necessary for breeding or selecting genotypes suited for specific ecoregions, which is limited. In the present study, 12 carinata genotypes were evaluated under low (17/09°C), optimum (22/14°C), and high (27/19°C) day/night temperatures at the early developmental stage. This study quantified temperature effects on several physiological and morphological characteristics of 12-advanced carinata lines. High-temperature plants decreased (15%) the accumulation of flavonoids and increased the nitrogen balance index by 25%. Low-temperature treatment significantly inhibited the aboveground (plant height, leaf area, number, and shoot weight) and root (length, surface area, and weight) traits. Across all genotypes, the shoot weight decreased by 55% and the root weight by 49% under low temperature. On the other hand, the maximum proportion of biomass was partitioned to roots under low temperature than at the high temperature. A poor relationship (r ² = 0.09) was found between low- and high-temperature indices, indicating differences in trait responses and tolerance mechanisms. AX17004 and AX17009 with higher root to shoot ratios might be suitable for late planting windows or regions with low-temperature spells. The two genotypes (AX17015 and AX17005) accumulated higher biomass under low- and high-temperature treatments can be used for planting in later summer or early winter. The identified low- and high-temperature stress-tolerant carinata genotypes could be a valuable resource for increasing stress tolerance during the early developmental stage.

Dissecting the Genetic Architecture of Carbon Partitioning in Sorghum Using Multiscale Phenotypes

Carbon partitioning in plants may be viewed as a dynamic process composed of the many interactions between sources and sinks. The accumulation and distribution of fixed carbon is not dictated simply by the sink strength and number but is dependent upon the source, pathways, and interactions of the system. As such, the study of carbon partitioning through perturbations to the system or through focus on individual traits may fail to produce actionable developments or a comprehensive understanding of the mechanisms underlying this complex process. Using the recently published sorghum carbon-partitioning panel, we collected both macroscale phenotypic characteristics such as plant height, above-ground biomass, and dry weight along with microscale compositional traits to deconvolute the carbon-partitioning pathways in this multipurpose crop. Multivariate analyses of traits resulted in the identification of numerous loci associated with several distinct carbon-partitioning traits, which putatively regulate sugar content, manganese homeostasis, and nitrate transportation. Using a multivariate adaptive shrinkage approach, we identified several loci associated with multiple traits suggesting that pleiotropic and/or interactive effects may positively influence multiple carbon-partitioning traits, or these overlaps may represent molecular switches mediating basal carbon allocating or partitioning networks. Conversely, we also identify a carbon tradeoff where reduced lignin content is associated with increased sugar content. The results presented here support previous studies demonstrating the convoluted nature of carbon partitioning in sorghum and emphasize the importance of taking a holistic approach to the study of carbon partitioning by utilizing multiscale phenotypes.

Genetic Dissection and Quantitative Trait Loci Mapping of Agronomic and Fodder Quality Traits in Sorghum Under Different Water Regimes

Livestock provides an additional source of income for marginal cropping farmers, but crop residues that are used as a main source of animal feed are characteristically low in digestibility and protein content. This reduces the potential livestock product yield and quality. The key trait, which influences the quality and the cost of animal feed, is digestibility. In this study, we demonstrate that sorghum breeding can be directed to achieve genetic gains for both fodder biomass and digestibility without any trade-offs. The genotypic variance has shown significant differences for biomass across years (13,035 in 2016 and 3,395 in 2017) while in vitro organic matter digestibility (IVOMD) showed significant genotypic variation in 2016 (0.253) under drought. A range of agronomic and fodder quality traits was found to vary significantly in the population within both the control and drought conditions and across both years of the study. There was significant genotypic variance (σg2) and genotypic × treatment variance (σgxt2) in dry matter production in a recombinant inbred line (RIL) population in both study years, while there was only significant σg2 and σgxt2 in IVOMD under the control conditions. There was no significant correlation identified between biomass and digestibility traits under the control conditions, but there was a positive correlation under drought. However, a negative relation was observed between digestibility and grain yield under the control conditions, while there was no significant correlation under drought population, which was genotyped using the genotyping-by-sequencing (GBS) technique, and 1,141 informative single nucleotide polymorphism (SNP) markers were identified. A linkage map was constructed, and a total of 294 quantitative trait loci (QTLs) were detected, with 534 epistatic interactions, across all of the traits under study. QTL for the agronomic traits fresh and dry weight, together with plant height, mapped on to the linkage group (LG) 7, while QTL for IVOMD mapped on to LG1, 2, and 8. A number of genes previously reported to play a role in nitrogen metabolism and cell wall-related functions were found to be associated with these QTL.

Classical phenotyping and deep learning concur on genetic control of stomatal density and area in sorghum

Stomatal density (SD) and stomatal complex area (SCA) are important traits that regulate gas exchange and abiotic stress response in plants. Despite sorghum (Sorghum bicolor) adaptation to arid conditions, the genetic potential of stomata-related traits remains unexplored due to challenges in available phenotyping methods. Hence, identifying loci that control stomatal traits is fundamental to designing strategies to breed sorghum with optimized stomatal regulation. We implemented both classical and deep learning methods to characterize genetic diversity in 311 grain sorghum accessions for stomatal traits at two different field environments. Nearly 12,000 images collected from abaxial (Ab) and adaxial (Ad) leaf surfaces revealed substantial variation in stomatal traits. Our study demonstrated significant accuracy between manual and deep learning methods in predicting SD and SCA. In sorghum, SD was 32%-39% greater on the Ab versus the Ad surface, while SCA on the Ab surface was 2%-5% smaller than on the Ad surface. Genome-Wide Association Study identified 71 genetic loci (38 were environment-specific) with significant genotype to phenotype associations for stomatal traits. Putative causal genes underlying the phenotypic variation were identified. Accessions with similar SCA but carrying contrasting haplotypes for SD were tested for stomatal conductance and carbon assimilation under field conditions. Our findings provide a foundation for further studies on the genetic and molecular mechanisms controlling stomata patterning and regulation in sorghum. An integrated physiological, deep learning, and genomic approach allowed us to unravel the genetic control of natural variation in stomata traits in sorghum, which can be applied to other plants.

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 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.

Genome-wide association study and gene network analyses reveal potential candidate genes for high night temperature tolerance in rice

High night temperatures (HNT) are shown to significantly reduce rice (Oryza sativa L.) yield and quality. A better understanding of the genetic architecture of HNT tolerance will help rice breeders to develop varieties adapted to future warmer climates. In this study, a diverse indica rice panel displayed a wide range of phenotypic variability in yield and quality traits under control night (24 °C) and higher night (29 °C) temperatures. Genome-wide association analysis revealed 38 genetic loci associated across treatments (18 for control and 20 for HNT). Nineteen loci were detected with the relative changes in the traits between control and HNT. Positive phenotypic correlations and co-located genetic loci with previously cloned grain size genes revealed common genetic regulation between control and HNT, particularly grain size. Network-based predictive models prioritized 20 causal genes at the genetic loci based on known gene/s expression under HNT in rice. Our study provides important insights for future candidate gene validation and molecular marker development to enhance HNT tolerance in rice. Integrated physiological, genomic, and gene network-informed approaches indicate that the candidate genes for stay-green trait may be relevant to minimizing HNT-induced yield and quality losses during grain filling in rice by optimizing source-sink relationships.

Improved cyber-physical system captured post-flowering high night temperature impact on yield and quality of field grown wheat

Winter wheat (Triticum aestivum L.) is essential to maintain food security for a large proportion of the world’s population. With increased risk from abiotic stresses due to climate variability, it is imperative to understand and minimize the negative impact of these stressors, including high night temperature (HNT). Both globally and at regional scales, a differential rate of increase in day and night temperature is observed, wherein night temperatures are increasing at a higher pace and the trend is projected to continue into the future. Previous studies using controlled environment facilities and small field-based removable chambers have shown that post-anthesis HNT stress can induce a significant reduction in wheat grain yield. A prototype was previously developed by utilizing field-based tents allowing for simultaneous phenotyping of popular winter wheat varieties from US Midwest and advanced breeding lines. Hence, the objectives of the study were to (i) design and build a new field-based infrastructure and test and validate the uniformity of HNT stress application on a scaled-up version of the prototype (ii) improve and develop a more sophisticated cyber-physical system to sense and impose post-anthesis HNT stress uniformly through physiological maturity within the scaled-up tents; and (iii) determine the impact of HNT stress during grain filling on the agronomic and grain quality parameters including starch and protein concentration. The system imposed a consistent post-anthesis HNT stress of + 3.8 °C until maturity and maintained uniform distribution of stress which was confirmed by (i) 0.23 °C temperature differential between an array of sensors within the tents and (ii) statistically similar performance of a common check replicated multiple times in each tent. On average, a reduction in grain-filling duration by 3.33 days, kernel weight by 1.25% per °C, grain number by 2.36% per °C and yield by 3.58% per °C increase in night temperature was documented. HNT stress induced a significant reduction in starch concentration indicating disturbed carbon balance. The pilot field-based facility integrated with a robust cyber-physical system provides a timely breakthrough for evaluating HNT stress impact on large diversity panels to enhance HNT stress tolerance across field crops. The flexibility of the cyber-physical system and movement capabilities of the field-based infrastructure allows this methodology to be adaptable to different crops.