Stem traits promote wheat climate-resilience.

Introduction: Wheat grain filling processes under post-anthesis stress scenarios depend mainly on stem traits and remobilization of stem water-soluble carbohydrates (WSC). Methods: A diverse panel of advanced semi-dwarf spring wheat lines, representing a natural variation in stem traits (WSC content, stem diameter, peduncle length, and stem wall width), was used to identify specific traits that reliably reflect the relationship between WSC and grain yield. The panel was phenotyped under various environmental conditions: well-watered, water-limited, and heat stress in Mexico, and terminal-drought in Israel. Results: Environmental stresses reduced grain yield (from 626 g m-2 under well-watered to 213 g m-2 under heat), lower internode diameter, and peduncle length. However, stem-WSC generally peaked 3-4 weeks after heading under all environmental conditions except heat (where it peaked earlier) and expressed the highest values under water-limited and terminal-drought environments. Increased investment in internode diameter and peduncle length was associated with a higher accumulation of stem WSC, which showed a positive association with yield and kernel weight. Across all environments, there were no apparent trade-offs between increased crop investment in internode diameter, peduncle length, and grain yield. Discussion: Our results showed that selecting for genotypes with higher resource investment in stem structural biomass, WSC accumulation, and remobilization could be a valuable strategy to ameliorate grain size reduction under stress without compromising grain yield potential. Furthermore, easy-to-measure proxies for WSC (stem diameter at specific internodes and length of the last internode, i.e., the peduncle) could significantly increase throughput, potentially at the breeding scale.

Spectral-genomic chain-model approach enhances the wheat yield component prediction under the Mediterranean climate.

In light of the changing climate that jeopardizes future food security, genomic selection is emerging as a valuable tool for breeders to enhance genetic gains and introduce high-yielding varieties. However, predicting grain yield is challenging due to the genetic and physiological complexities involved and the effect of genetic-by-environment interactions on prediction accuracy. We utilized a chained model approach to address these challenges, breaking down the complex prediction task into simpler steps. A diversity panel with a narrow phenological range was phenotyped across three Mediterranean environments for various morpho-physiological and yield-related traits. The results indicated that a multi-environment model outperformed a single-environment model in prediction accuracy for most traits. However, prediction accuracy for grain yield was not improved. Thus, in an attempt to ameliorate the grain yield prediction accuracy, we integrated a spectral estimation of spike number, being a major wheat yield component, with genomic data. A machine learning approach was used for spike number estimation from canopy hyperspectral reflectance captured by an unmanned aerial vehicle. The spectral-based estimated spike number was utilized as a secondary trait in a multi-trait genomic selection, significantly improving grain yield prediction accuracy. Moreover, the ability to predict the spike number based on data from previous seasons implies that it could be applied to new trials at various scales, even in small plot sizes. Overall, we demonstrate here that incorporating a novel spectral-genomic chain-model workflow, which utilizes spectral-based phenotypes as a secondary trait, improves the predictive accuracy of wheat grain yield.

Refining flowering date enhances sesame yield independently of day-length.

BACKGROUND: The transition from vegetative to reproductive growth is a key factor in yield maximization. Sesame (Sesamum indicum), an indeterminate short-day oilseed crop, is rapidly being introduced into new cultivation areas. Thus, decoding its flowering mechanism is necessary to facilitate adaptation to environmental conditions. In the current study, we uncover the effect of day-length on flowering and yield components using F 2 populations segregating for previously identified quantitative trait loci (Si_DTF QTL) confirming these traits. RESULTS: Generally, day-length affected all phenotypic traits, with short-day preceding days to flowering and reducing yield components. Interestingly, the average days to flowering required for yield maximization was 50 to 55 days, regardless of day-length. In addition, we found that Si_DTF QTL is more associated with seed-yield and yield components than with days to flowering. A bulk-segregation analysis was applied to identify additional QTL differing in allele frequencies between early and late flowering under both day-length conditions. Candidate genes mining within the identified major QTL intervals revealed two flowering-related genes with different expression levels between the parental lines, indicating their contribution to sesame flowering regulation. CONCLUSIONS: Our findings demonstrate the essential role of flowering date on yield components and will serve as a basis for future sesame breeding.

Leveraging genomics and temporal high-throughput phenotyping to enhance association mapping and yield prediction in sesame.

Sesame (Sesamum indicum) is an important oilseed crop with rising demand owing to its nutritional and health benefits. There is an urgent need to develop and integrate new genomic-based breeding strategies to meet these future demands. While genomic resources have advanced genetic research in sesame, the implementation of high-throughput phenotyping and genetic analysis of longitudinal traits remains limited. Here, we combined high-throughput phenotyping and random regression models to investigate the dynamics of plant height, leaf area index, and five spectral vegetation indices throughout the sesame growing seasons in a diversity panel. Modeling the temporal phenotypic and additive genetic trajectories revealed distinct patterns corresponding to the sesame growth cycle. We also conducted longitudinal genomic prediction and association mapping of plant height using various models and cross-validation schemes. Moderate prediction accuracy was obtained when predicting new genotypes at each time point, and moderate to high values were obtained when forecasting future phenotypes. Association mapping revealed three genomic regions in linkage groups 6, 8, and 11, conferring trait variation over time and growth rate. Furthermore, we leveraged correlations between the temporal trait and seed-yield and applied multi-trait genomic prediction. We obtained an improvement over single-trait analysis, especially when phenotypes from earlier time points were used, highlighting the potential of using a high-throughput phenotyping platform as a selection tool. Our results shed light on the genetic control of longitudinal traits in sesame and underscore the potential of high-throughput phenotyping to detect a wide range of traits and genotypes that can inform sesame breeding efforts to enhance yield.

Induced mutation in the SiALS gene offers new weed management opportunities for sesame crop.

Weeds are the primary biotic constraint affecting sesame growth and production. Here, we applied EMS mutagenesis to an elite sesame cultivar and discovered a novel point mutation in the sesame SiALS gene conferring resistance to imidazolinone, a group of acetolactate-synthase (ALS)-inhibitors. The mutant line exhibited high resistance to imazamox, an ALS-inhibitor, with hybrid plants displaying an intermediate response. Field-based validation confirmed the mutant line's substantial resistance, leading to a significantly higher yield under imazamox treatment. Under pre-emergence application of imazapic, the mutant plants sustained growth, whereas wild-type and weed were effectively controlled. Field trials using s-metolachlor and imazapic combined resulted in weed-free plots compared to untreated controls. Consequently, this treatment showed a significantly greater yield (2280 vs. 880 Kg ha-1) than the commercial practice (s-metolachlor). Overall, our study unveils the potential of utilizing this point mutation in sesame breeding programs, offering new opportunities for integrated weed management strategies for sesame cultivation. Developing herbicide-resistant crop plants holds promise for supporting sustainable production and addressing the challenges of weed infestations in sesame farming.

Do Traits Travel? Multiple-Herbicide-Resistant A. tuberculatus, an Alien Weed Species in Israel.

Amaranthus tuberculatus is the most common weed in soybean and corn in the USA and Canada. In Israel, it has been a minor riverbank weed. However, in recent years, growing densities of this plant have been observed in field crops, orchards, and roadsides. Between 2017 and 2022, we surveyed the distribution of A. tuberculatus and collected seeds for further study. We identified three main distribution zones in Israel: the Jezreel Valley, Hula Valley, and Coastal Plain. Most of the populations were found near water sources, fishponds, barns, dairies, or bird-feeding sites, suggesting the involvement of imported grain in introducing A. tuberculatus to Israel. Populations were screened for their responses to various post-emergence herbicides (i.e., ALS, EPSPS, PPO, HPPD, and PSII inhibitors). Several populations from the Jezreel Valley were found to be putatively resistant to ALS, EPSPS, and PPO inhibitors. The responses of those populations to trifloxysulfuron, glyphosate, and carfentrazone-ethyl were also studied. A single ALS-, EPSPS- and PPO-resistant plant was vegetatively propagated to create a clonal population, which was treated with foramsulfuron, glyphosate, and carfentrazone-ethyl. No resistance to PSII or HPPD inhibitors was observed, but resistance to herbicides that inhibit ALS, EPSPS, and PPO was observed. A clonal propagation assay revealed the existence of a population that was resistant to ALS, EPSPS, and PPO inhibitors. Since the local A. tuberculatus populations have not been exposed to herbicide selection pressure, these traits probably reached Israel through seed-mediated gene flow via imported grain.

Multi-environment analysis enhances genomic prediction accuracy of agronomic traits in sesame.

Introduction: Sesame is an ancient oilseed crop containing many valuable nutritional components. The demand for sesame seeds and their products has recently increased worldwide, making it necessary to enhance the development of high-yielding cultivars. One approach to enhance genetic gain in breeding programs is genomic selection. However, studies on genomic selection and genomic prediction in sesame have yet to be conducted. Methods: In this study, we performed genomic prediction for agronomic traits using the phenotypes and genotypes of a sesame diversity panel grown under Mediterranean climatic conditions over two growing seasons. We aimed to assess prediction accuracy for nine important agronomic traits in sesame using single- and multi-environment analyses. Results: In single-environment analysis, genomic best linear unbiased prediction, BayesB, BayesC, and reproducing kernel Hilbert spaces models showed no substantial differences. The average prediction accuracy of the nine traits across these models ranged from 0.39 to 0.79 for both growing seasons. In the multi-environment analysis, the marker-by-environment interaction model, which decomposed the marker effects into components shared across environments and environment-specific deviations, improved the prediction accuracies for all traits by 15%-58% compared to the single-environment model, particularly when borrowing information from other environments was made possible. Discussion: Our results showed that single-environment analysis produced moderate-to-high genomic prediction accuracy for agronomic traits in sesame. The multi-environment analysis further enhanced this accuracy by exploiting marker-by-environment interaction. We concluded that genomic prediction using multi-environmental trial data could improve efforts for breeding cultivars adapted to the semi-arid Mediterranean climate.

Stress-induced deeper rooting introgression enhances wheat yield under terminal drought.

Water scarcity is the primary environmental constraint affecting wheat growth and production and is increasingly exacerbated due to climatic fluctuation, which jeopardizes future food security. Most breeding efforts to improve wheat yields under drought have focused on above-ground traits. Root traits are closely associated with various drought adaptability mechanisms, but the genetic variation underlying these traits remains untapped, even though it holds tremendous potential for improving crop resilience. Here, we examined this potential by re-introducing ancestral alleles from wild emmer wheat (Triticum turgidum ssp. dicoccoides) and studied their impact on root architecture diversity under terminal drought stress. We applied an active sensing electrical resistivity tomography approach to compare a wild emmer introgression line (IL20) and its drought-sensitive recurrent parent (Svevo) under field conditions. IL20 exhibited greater root elongation under drought, which resulted in higher root water uptake from deeper soil layers. This advantage initiated at the pseudo-stem stage and increased during the transition to the reproductive stage. The increased water uptake promoted higher gas exchange rates and enhanced grain yield under drought. Overall, we show that this presumably 'lost' drought-induced mechanism of deeper rooting profile can serve as a breeding target to improve wheat productiveness under changing climate.

When half is more than the whole: Wheat domestication syndrome reconsidered.

Two opposing models currently dominate Near Eastern plant domestication research. The core area-one event model depicts a knowledge-based, conscious, geographically centered, rapid single-event domestication, while the protracted-autonomous model emphasizes a noncentered, millennia-long process based on unconscious dynamics. The latter model relies, in part, on quantitative depictions of diachronic changes (in archaeological remains) in proportions of spikelet shattering to nonshattering, towards full dominance of the nonshattering (domesticated) phenotypes in cultivated cereal populations. Recent wild wheat genome assembly suggests that shattering and nonshattering spikelets may originate from the same (individual) genotype. Therefore, their proportions among archaeobotanical assemblages cannot reliably describe the presumed protracted-selection dynamics underlying wheat domestication. This calls for a reappraisal of the "domestication syndrome" concept associated with cereal domestication.

A non-destructive approach for measuring rice panicle-level photosynthetic responses using 3D-image reconstruction.

BACKGROUND: Our understanding of the physiological responses of rice inflorescence (panicle) to environmental stresses is limited by the challenge of accurately determining panicle photosynthetic parameters and their impact on grain yield. This is primarily due to the lack of a suitable gas exchange methodology for panicles and non-destructive methods to accurately determine panicle surface area. RESULTS: To address these challenges, we have developed a custom panicle gas exchange cylinder compatible with the LiCor 6800 Infra-red Gas Analyzer. Accurate surface area measurements were determined using 3D panicle imaging to normalize the panicle-level photosynthetic measurements. We observed differential responses in both panicle and flag leaf for two temperate Japonica rice genotypes (accessions TEJ-1 and TEJ-2) exposed to heat stress during early grain filling. There was a notable divergence in the relative photosynthetic contribution of flag leaf and panicles for the heat-tolerant genotype (TEJ-2) compared to the sensitive genotype (TEJ-1). CONCLUSION: The novelty of this method is the non-destructive and accurate determination of panicle area and photosynthetic parameters, enabling researchers to monitor temporal changes in panicle physiology during the reproductive development. The method is useful for panicle-level measurements under diverse environmental stresses and is sensitive enough to evaluate genotypic variation for panicle physiology and architecture in cereals with compact inflorescences.

Elucidating the pleiotropic effects of sesame KANADI1 locus on leaf and capsule development.

Autonomous seed dispersal is a critical trait for wild plants in natural ecosystems; however, for domesticated crop-plants it can lead to significant yield losses. While seed shattering was a major selection target during the initial domestication of many crops, this trait is still targeted in breeding programs, especially in 'orphan crops' such as sesame, whose capsules dehisce upon ripening. Here we used a mapping population derived from a cross between wild-type (dehiscent) × indehiscent lines to test the hypothesis that the selection against indehiscent alleles in sesame is a consequence of complex genetic interactions associated with yield reduction. We identified a major pleiotropic locus, SiKANADI1, associated with abnormal hyponastic leaf and indehiscent capsule, and genetically dissected its underlying mechanism using a set of near-isogenic lines. Transcriptional, anatomical and physiological information shed light, for the first time, on the polar regulatory gene network in sesame. The pleiotropic effect of SiKANADI1 on leaf and capsule structure and its influence on photosynthetic capacity and final yield are thoroughly characterized. Overall, our results provide new insights on the genetic and morphological mechanisms regulating capsule indehiscence in sesame, and discuss their evolutionary consequences and potential for future sesame breeding.

Modifying root-to-shoot ratio improves root water influxes in wheat under drought stress.

Drought intensity as experienced by plants depends upon soil moisture status and atmospheric variables such as temperature, radiation, and air vapour pressure deficit. Although the role of shoot architecture with these edaphic and atmospheric factors is well characterized, the extent to which shoot and root dynamic interactions as a continuum are controlled by genotypic variation is less well known. Here, we targeted these interactions using a wild emmer wheat introgression line (IL20) with a distinct drought-induced shift in the shoot-to-root ratio and its drought-sensitive recurrent parent Svevo. Using a gravimetric platform, we show that IL20 maintained higher root water influx and gas exchange under drought stress, which supported a greater growth. Interestingly, the advantage of IL20 in root water influx and transpiration was expressed earlier during the daily diurnal cycle under lower vapour pressure deficit and therefore supported higher transpiration efficiency. Application of a structural equation model indicates that under drought, vapour pressure deficit and radiation are antagonistic to transpiration rate, whereas the root water influx operates as a feedback for the higher atmospheric responsiveness of leaves. Collectively, our results suggest that a drought-induced shift in root-to-shoot ratio can improve plant water uptake potential in a short preferable time window during early morning when vapour pressure deficit is low and the light intensity is not a limiting factor for assimilation.

Genome-wide association analysis uncovers the genetic architecture of tradeoff between flowering date and yield components in sesame.

BACKGROUND: Unrevealing the genetic makeup of crop morpho-agronomic traits is essential for improving yield quality and sustainability. Sesame (Sesamum indicum L.) is one of the oldest oil-crops in the world. Despite its economic and agricultural importance, it is an 'orphan crop-plant' that has undergone limited modern selection, and, as a consequence preserved wide genetic diversity. Here we established a new sesame panel (SCHUJI) that contains 184 genotypes representing wide phenotypic variation and is geographically distributed. We harnessed the natural variation of this panel to perform genome-wide association studies for morpho-agronomic traits under the Mediterranean climate conditions. RESULTS: Field-based phenotyping of the SCHUJI panel across two seasons exposed wide phenotypic variation for all traits. Using 20,294 single-nucleotide polymorphism markers, we detected 50 genomic signals associated with these traits. Major genomic region on LG2 was associated with flowering date and yield-related traits, exemplified the key role of the flowering date on productivity. CONCLUSIONS: Our results shed light on the genetic architecture of flowering date and its interaction with yield components in sesame and may serve as a basis for future sesame breeding programs in the Mediterranean basin.

Wild emmer introgression alters root-to-shoot growth dynamics in durum wheat in response to water stress.

Water deficit during the early vegetative growth stages of wheat (Triticum) can limit shoot growth and ultimately impact grain productivity. Introducing diversity in wheat cultivars to enhance the range of phenotypic responses to water limitations during vegetative growth can provide potential avenues for mitigating subsequent yield losses. We tested this hypothesis in an elite durum wheat background by introducing a series of introgressions from a wild emmer (Triticum turgidum ssp. dicoccoides) wheat. Wild emmer populations harbor rich phenotypic diversity for drought-adaptive traits. To determine the effect of these introgressions on vegetative growth under water-limited conditions, we used image-based phenotyping to catalog divergent growth responses to water stress ranging from high plasticity to high stability. One of the introgression lines exhibited a significant shift in root-to-shoot ratio in response to water stress. We characterized this shift by combining genetic analysis and root transcriptome profiling to identify candidate genes (including a root-specific kinase) that may be linked to the root-to-shoot carbon reallocation under water stress. Our results highlight the potential of introducing functional diversity into elite durum wheat for enhancing the range of water stress adaptation.

Genomic Architecture of Phenotypic Plasticity in Response to Water Stress in Tetraploid Wheat.

Phenotypic plasticity is one of the main mechanisms of adaptation to abiotic stresses via changes in critical developmental stages. Altering flowering phenology is a key evolutionary strategy of plant adaptation to abiotic stresses, to achieve the maximum possible reproduction. The current study is the first to apply the linear regression residuals as drought plasticity scores while considering the variation in flowering phenology and traits under non-stress conditions. We characterized the genomic architecture of 17 complex traits and their drought plasticity scores for quantitative trait loci (QTL) mapping, using a mapping population derived from a cross between durum wheat (Triticum turgidum ssp. durum) and wild emmer wheat (T. turgidum ssp. dicoccoides). We identified 79 QTLs affected observed traits and their plasticity scores, of which 33 reflected plasticity in response to water stress and exhibited epistatic interactions and/or pleiotropy between the observed and plasticity traits. Vrn-B3 (TaTF1) residing within an interval of a major drought-escape QTL was proposed as a candidate gene. The favorable alleles for most of the plasticity QTLs were contributed by wild emmer wheat, demonstrating its high potential for wheat improvement. Our study presents a new approach for the quantification of plant adaptation to various stresses and provides new insights into the genetic basis of wheat complex traits under water-deficit stress.

Deciphering the genetic basis of wheat seminal root anatomy uncovers ancestral axial conductance alleles.

Root axial conductance, which describes the ability of water to move through the xylem, contributes to the rate of water uptake from the soil throughout the whole plant lifecycle. Under the rainfed wheat agro-system, grain-filling is typically occurring during declining water availability (i.e., terminal drought). Therefore, preserving soil water moisture during grain filling could serve as a key adaptive trait. We hypothesized that lower wheat root axial conductance can promote higher yields under terminal drought. A segregating population derived from a cross between durum wheat and its direct progenitor wild emmer wheat was used to underpin the genetic basis of seminal root architectural and functional traits. We detected 75 QTL associated with seminal roots morphological, anatomical and physiological traits, with several hotspots harbouring co-localized QTL. We further validated the axial conductance and central metaxylem QTL using wild introgression lines. Field-based characterization of genotypes with contrasting axial conductance suggested the contribution of low axial conductance as a mechanism for water conservation during grain filling and consequent increase in grain size and yield. Our findings underscore the potential of harnessing wild alleles to reshape the wheat root system architecture and associated hydraulic properties for greater adaptability under changing climate.

Genetic improvement of wheat early vigor promote weed-competitiveness under Mediterranean climate.

Chemical weed-control is the most effective practice for wheat, however, rapid evolution of herbicide-resistant weeds threat food-security and calls for integration of non-chemical practices. We hypothesis that integration of alternative GA-responsive dwarfing genes into elite wheat cultivars can promote early vigor and weed-competitiveness under Mediterranean climate. We develop near-isogenic lines of bread wheat cultivars with GAR dwarfing genes and evaluate them for early vigor and weed-competitiveness under various environmental and management conditions to identify promising NIL for weed-competitiveness and grain yield. While all seven NILs responded to external gibberellic acid application, they exhibited differences in early vigor. Greenhouse and field evaluations highlighted NIL OC1 (Rht8andRht12) as a promising line, with significant advantage in canopy early vigor over its parental. To facilitate accurate and continuous early vigor data collection, we applied non-destructive image-based phenotyping approaches which offers non-expensive and end-user friendly solution for selection. NIL OC1 was tested under different weed density level, infestation waves, and temperatures and highlight the complex genotypic × environmental × management interactions. Our findings demonstrate the potential of genetic modification of dwarfing genes as promising approach to improve weed-competitiveness, and serve as basis for future breeding efforts to support sustainable wheat production under semi-arid Mediterranean climate.

A Cytoplasmic Receptor-like Kinase Contributes to Salinity Tolerance.

Receptor-like cytoplasmic kinases (RLCKs) are receptor kinases that lack extracellular ligand-binding domains and have emerged as a major class of signaling proteins that regulate plant cellular activities in response to biotic/abiotic stresses and endogenous extracellular signaling molecules. We have identified a rice RLCK (OsRLCK311) that was significantly higher in transgenic pSARK-IPT rice (Oryza sativa) that exhibited enhanced growth under saline conditions. Overexpression of OsRLCK311 full-length protein (RLCK311FL) and the C-terminus of OsRLCK311 (ΔN) in Arabidopsis confirmed its role in salinity tolerance, both in seedlings and mature plants. Protein interaction assays indicated that OsRLCK311 and ΔN interacted in-vivo with the plasma membrane AQP AtPIP2;1. The RLCK311-PIP2;1 binding led to alterations in the stomata response to ABA, which was characterized by more open stomata of transgenic plants. Moreover, OsRLCK311-ΔN effect in mediating enhanced plant growth under saline conditions was also observed in the perennial grass Brachypodium sylvaticum, confirming its role in both dicots and monocots species. Lastly, OsRLCK311 interacted with the rice OsPIP2;1. We suggest that the rice OsRLCK311 play a role in regulating the plant growth response under saline conditions via the regulation of the stomata response to stress. This role seems to be independent of the RLCK311 kinase activity, since the overexpression of the RLCK311 C-terminus (ΔN), which lacks the kinase full domain, has a similar phenotype to RLCK311FL.

Genetic Architecture Underpinning Yield Components and Seed Mineral-Nutrients in Sesame.

Genetic dissection of yield components and seed mineral-nutrient is crucial for understanding plant physiological and biochemical processes and alleviate nutrient malnutrition. Sesame (Sesamum indicum L.) is an orphan crop that harbors rich allelic repertoire for seed mineral-nutrients. Here, we harness this wide diversity to study the genetic architecture of yield components and seed mineral-nutrients using a core-collection of worldwide genotypes and segregating mapping population. We also tested the association between these traits and the effect of seed nutrients concentration on their bio-accessibility. Wide genetic diversity for yield components and seed mineral-nutrients was found among the core-collection. A high-density linkage map consisting of 19,309 markers was constructed and used for genetic mapping of 84 QTL associated with yield components and 50 QTL for seed minerals. To the best of our knowledge, this is the first report on mineral-nutrients QTL in sesame. Genomic regions with a cluster of overlapping QTL for several morphological and nutritional traits were identified and considered as genomic hotspots. Candidate gene analysis revealed potential functional associations between QTL and corresponding genes, which offers unique opportunities for synchronous improvement of mineral-nutrients. Our findings shed-light on the genetic architecture of yield components, seed mineral-nutrients and their inter- and intra- relationships, which may facilitate future breeding efforts to develop bio-fortified sesame cultivars.