Analysis of constituents for phenotyping drought tolerance in crop improvement

Dissection of Maize Drought Tolerance at the Flowering Stage Using Genome-Wide Association Studies

Drought is one of the most critical environmental factors constraining maize production. When it occurs at the flowering stage, serious yield losses are caused, and often, the damage is irretrievable. In this study, anthesis to silk interval (ASI), plant height (PH), and ear biomass at the silking date (EBM) of 279 inbred lines were studied under both water-stress (WS) and well-water (WW) field conditions, for three consecutive years. Averagely, ASI was extended by 25.96%, EBM was decreased by 17.54%, and the PH was reduced by 12.47% under drought stress. Genome-wide association studies were carried out using phenotypic values under WS, WW, and drought-tolerance index (WS-WW or WS/WW) and applying a mixed linear model that controls both population structure and relative kinship. In total, 71, 159, and 21 SNPs, located in 32, 59, and 12 genes, were significantly (P < 10−5) associated with ASI, EBM, and PH, respectively. Only a few overlapped candidate genes were found to be associated with the same drought-related traits under different environments, for example, ARABIDILLO 1, glycoprotein, Tic22-like, and zinc-finger family protein for ASI; 26S proteasome non-ATPase and pyridoxal phosphate transferase for EBM; 11-ß-hydroxysteroid dehydrogenase, uncharacterised, Leu-rich repeat protein kinase, and SF16 protein for PH. Furthermore, most candidate genes were revealed to be drought-responsive in an association panel. Meanwhile, the favourable alleles/key variations were identified with a haplotype analysis. These candidate genes and their key variations provide insight into the genetic basis of drought tolerance, especially for the female inflorescence, and will facilitate drought-tolerant maize breeding.

Advances in Cereal Crop Genomics for Resilience under Climate Change

Adapting to climate change, providing sufficient human food and nutritional needs, and securing sufficient energy supplies will call for a radical transformation from the current conventional adaptation approaches to more broad-based and transformative alternatives. This entails diversifying the agricultural system and boosting productivity of major cereal crops through development of climate-resilient cultivars that can sustainably maintain higher yields under climate change conditions, expanding our focus to crop wild relatives, and better exploitation of underutilized crop species. This is facilitated by the recent developments in plant genomics, such as advances in genome sequencing, assembly, and annotation, as well as gene editing technologies, which have increased the availability of high-quality reference genomes for various model and non-model plant species. This has necessitated genomics-assisted breeding of crops, including underutilized species, consequently broadening genetic variation of the available germplasm; improving the discovery of novel alleles controlling important agronomic traits; and enhancing creation of new crop cultivars with improved tolerance to biotic and abiotic stresses and superior nutritive quality. Here, therefore, we summarize these recent developments in plant genomics and their application, with particular reference to cereal crops (including underutilized species). Particularly, we discuss genome sequencing approaches, quantitative trait loci (QTL) mapping and genome-wide association (GWAS) studies, directed mutagenesis, plant non-coding RNAs, precise gene editing technologies such as CRISPR-Cas9, and complementation of crop genotyping by crop phenotyping. We then conclude by providing an outlook that, as we step into the future, high-throughput phenotyping, pan-genomics, transposable elements analysis, and machine learning hold much promise for crop improvements related to climate resilience and nutritional superiority.

Drought stress-induced physiological mechanisms, signaling pathways and molecular response of chloroplasts in common vegetable crops

Drought stress is one of the most adverse abiotic stresses that hinder plants' growth and productivity, threatening sustainable crop production. It impairs normal growth, disturbs water relations and reduces water-use efficiency in plants. However, plants have evolved many physiological and biochemical responses at the cellular and organism levels, in order to cope with drought stress. Photosynthesis, which is considered one of the most crucial biological processes for survival of plants, is greatly affected by drought stress. A gradual decrease in CO₂ assimilation rates, reduced leaf size, stem extension and root proliferation under drought stress, disturbs plant water relations, reducing water-use efficiency, disrupts photosynthetic pigments and reduces the gas exchange affecting the plants adversely. In such conditions, the chloroplast, organelle responsible for photosynthesis, is found to counteract the ill effects of drought stress by its critical involvement as a sensor of changes occurring in the environment, as the first process that drought stress affects is photosynthesis. Beside photosynthesis, chloroplasts carry out primary metabolic functions such as the biosynthesis of starch, amino acids, lipids, and tetrapyroles, and play a central role in the assimilation of nitrogen and sulfur. Because the chloroplasts are central organelles where the photosynthetic reactions take place, modifications in their physiology and protein pools are expected in response to the drought stress-induced variations in leaf gas exchanges and the accumulation of ROS. Higher expression levels of various transcription factors and other proteins including heat shock-related protein, LEA proteins seem to be regulating the heat tolerance mechanisms. However, several aspects of plastid alterations, following a water deficit environment are still poorly characterized. Since plants adapt to various stress tolerance mechanisms to respond to drought stress, understanding mechanisms of drought stress tolerance in plants will lead toward the development of drought tolerance in crop plants. This review throws light on major droughts stress-induced molecular/physiological mechanisms in response to severe and prolonged drought stress and addresses the molecular response of chloroplasts in common vegetable crops. It further highlights research gaps, identifying unexplored domains and suggesting recommendations for future investigations.

Differential adaptation strategies to different levels of soil water deficit in two upland and lowland genotypes of rice: a physiological and metabolic approach

BACKGROUND

Upland genotypes of rice are less sensitive to soil water deficit (SWD), making them suitable candidates for revealing the strategies underlying plant tolerance. The physiological factors, the biochemical traits needed to withstand oxidative stress, and the metabolite fluctuations of an upland genotype (Azucena) and an intolerant lowland genotype (IR64) genotype were measured under two levels of SWD (withholding water for 7- or 14 days) to identify SWD-responsive strategies associated with tolerance.

RESULTS

After withholding water for 7 days, no significant changes in physiological and biochemical traits of Azucena were observed, whereas in IR64, significant decreases in physiological factors were recorded along with increases in oxidative-stress indicators. However, the root length of Azucena increased significantly, showing a clear stress avoidance strategy. Under a prolonged treatment (14 days), IR64 entered an oxidative-damage stage, whereas Azucena exhibited a highly efficient antioxidant system. Our metabolite analysis also revealed two different enriched pathways. After a 7-day SWD, the sugar levels were decreased in the leaves of Azucena but increased in IR64. The reduction in the sugar levels (up to 1.79-log2FC) in the Azucena leaves may be indicative of their transport to the roots, supplying the carbon source needed for root elongation. Under a 14-day treatment, proline and aspartate family members accumulated to the highest levels in Azucena, whereas an increase in the levels of aromatic amino acids with key roles in the biosynthesis of secondary metabolites was detected in IR64.

CONCLUSION

The adaptation strategies identified in two types of rice genotypes in confronting SWD may assist researchers in finding the proper indicators for screening more tolerant genotypes. © 2019 Society of Chemical Industry.

Machine Learning Approaches to Improve Three Basic Plant Phenotyping Tasks Using Three-Dimensional Point Clouds

Developing automated methods to efficiently process large volumes of point cloud data remains a challenge for three-dimensional (3D) plant phenotyping applications. Here, we describe the development of machine learning methods to tackle three primary challenges in plant phenotyping: lamina/stem classification, lamina counting, and stem skeletonization. For classification, we assessed and validated the accuracy of our methods on a dataset of 54 3D shoot architectures, representing multiple growth conditions and developmental time points for two Solanaceous species, tomato (Solanum lycopersicum cv 75 m82D) and Nicotiana benthamiana Using deep learning, we classified lamina versus stems with 97.8% accuracy. Critically, we also demonstrated the robustness of our method to growth conditions and species that have not been trained on, which is important in practical applications but is often untested. For lamina counting, we developed an enhanced region-growing algorithm to reduce oversegmentation; this method achieved 86.6% accuracy, outperforming prior methods developed for this problem. Finally, for stem skeletonization, we developed an enhanced tip detection technique, which ran an order of magnitude faster and generated more precise skeleton architectures than prior methods. Overall, our improvements enable higher throughput and accurate extraction of phenotypic properties from 3D point cloud data.

Signal coordination before, during and after stomatal closure in response to drought stress

Signal coordination in response to changes in water availability remains unclear, as does the role of embolism events in signaling drought stress. Sunflowers were exposed to two drought treatments of varying intensity while simultaneously monitoring changes in stomatal conductance, acoustic emissions (AE), turgor pressure, surface-level electrical potential, organ-level water potential and leaf abscisic acid (ABA) concentration. Leaf, stem and root xylem vulnerability to embolism were measured with the single vessel injection technique. In both drought treatments, it was found that AE events and turgor changes preceded the onset of stomatal closure, whereas electrical surface potentials shifted concurrently with stomatal closure. Leaf-level ABA concentration did not change until after stomata were closed. Roots and petioles were equally vulnerable to drought stress based on the single vessel injection technique. However, anatomical analysis of the xylem indicated that the increased AE events were not a result of xylem embolism formation. Additionally, roots and stems never reached a xylem pressure threshold that would initiate runaway embolism throughout the entire experiment. It is concluded that stomatal closure was not embolism-driven, but, rather, that onset of stomatal closure was most closely correlated with the hydraulic signal from changes in leaf turgor.

High-throughput quantitative analysis of phytohormones in sorghum leaf and root tissue by ultra-performance liquid chromatography-mass spectrometry

Plant development, growth, and adaptation to stress are regulated by phytohormones, which can influence physiology even at low concentrations. Phytohormones are chemically grouped according to both structure and function as auxins, cytokinins, abscisic acid, jasmonates, salicylates, gibberellins, and brassinosteroids, among others. This chemical diversity and requirement for highly sensitive detection in complex matrices create unique challenges for comprehensive phytohormone analysis. Here, we present a robust and efficient quantitative UPLC-MS/MS assay for 17 phytohormones, including jasmonates, salicylates, abscisic acid, gibberellins, cytokinins, and auxins. Using this assay, 12 phytohormones were detected and quantified in sorghum plant tissue without the need for solid phase extraction (SPE) or liquid-liquid extraction. Variation of phytohormone profiles was explored in both root and leaf tissues between three genotypes, harvested at two different developmental time points. The results highlight the importance of tissue type, sampling time, and genetic factors when designing experiments that involve phytohormone analysis of sorghum. This research lays the groundwork for future studies, which can combine phytohormone profiling with other datasets such as transcriptome, soil microbiome, genome, and metabolome data, to provide important functional information about adaptation to stress and other environmental variables.

Post photosynthetic carbon partitioning to sugar alcohols and consequences for plant growth

The occurrence of sugar alcohols is ubiquitous among plants. Physiochemical properties of sugar alcohols suggest numerous primary and secondary functions in plant tissues and are often well documented. In addition to functions arising from physiochemical properties, the synthesis of sugar alcohols may have significant influence over photosynthetic, respiratory, and developmental processes owing to their function as a large sink for photosynthates. Sink strength is demonstrated by the high concentrations of sugar alcohols found in plant tissues and their ability to be readily transported. The plant scale distribution and physiochemical function of these compounds renders them strong candidates for functioning as stress metabolites. Despite this, several aspects of sugar alcohol biosynthesis and function are poorly characterised namely: 1) the quantitative characterisation of carbon flux into the sugar alcohol pool; 2) the molecular control governing sugar alcohol biosynthesis on a quantitative basis; 3) the role of sugar alcohols in plant growth and ecology; and 4) consequences of sugar alcohol synthesis for yield production and yield quality. We highlight the need to adopt new approaches to investigating sugar alcohol biosynthesis using modern technologies in gene expression, metabolic flux analysis and agronomy. Combined, these approaches will elucidate the impact of sugar alcohol biosynthesis on growth, stress tolerance, yield and yield quality.

Numerous genetic loci identified for drought tolerance in the maize nested association mapping populations

Background

Maize requires more water than most other crops; therefore, the water use efficiency of this crop must be improved for maize production under undesirable land and changing environmental conditions.

Results

To elucidate the genetic control of drought in maize, we evaluated approximately 5000 inbred lines from 30 linkage-association joint mapping populations under two contrasting water regimes for seven drought-related traits, including yield and anthesis-silking interval (ASI). The joint linkage analysis was conducted to identify 220 quantitative trait loci (QTLs) under well-watered conditions and 169 QTLs under water-stressed conditions. The genome-wide association analysis identified 365 single nucleotide polymorphisms (SNPs) associated with drought-related traits, and these SNPs were located in 354 candidate genes. Fifty-two of these genes showed significant differential expression in the inbred line B73 under the well-watered and water-stressed conditions. In addition, genomic predictions suggested that the moderate-density SNPs obtained through genotyping-by-sequencing were able to make accurate predictions in the nested association mapping population for drought-related traits with moderate-to-high heritability under the water-stressed conditions.

Conclusions

The results of the present study provide important information that can be used to understand the genetic basis of drought stress responses and facilitate the use of beneficial alleles for the improvement of drought tolerance in maize.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3170-8) contains supplementary material, which is available to authorized users.

SUMO proteases ULP1c and ULP1d are required for development and osmotic stress responses in Arabidopsis thaliana

Sumoylation is an essential post-translational regulator of plant development and the response to environmental stimuli. SUMO conjugation occurs via an E1-E2-E3 cascade, and can be removed by SUMO proteases (ULPs). ULPs are numerous and likely to function as sources of specificity within the pathway, yet most ULPs remain functionally unresolved. In this report we used loss-of-function reverse genetics and transcriptomics to functionally characterize Arabidopsis thaliana ULP1c and ULP1d SUMO proteases. GUS reporter assays implicated ULP1c/d in various developmental stages, and subsequent defects in growth and germination were uncovered using loss-of-function mutants. Microarray analysis evidenced not only a deregulation of genes involved in development, but also in genes controlled by various drought-associated transcriptional regulators. We demonstrated that ulp1c ulp1d displayed diminished in vitro root growth under low water potential and higher stomatal aperture, yet leaf transpirational water loss and whole drought tolerance were not significantly altered. Generation of a triple siz1 ulp1c ulp1d mutant suggests that ULP1c/d and the SUMO E3 ligase SIZ1 may display separate functions in development yet operate epistatically in response to water deficit. We provide experimental evidence that Arabidopsis ULP1c and ULP1d proteases act redundantly as positive regulators of growth, and operate mainly as isopeptidases downstream of SIZ1 in the control of water deficit responses.

Agriculture in West Africa in the Twenty-First Century: Climate Change and Impacts Scenarios, and Potential for Adaptation

West Africa is known to be particularly vulnerable to climate change due to high climate variability, high reliance on rain-fed agriculture, and limited economic and institutional capacity to respond to climate variability and change. In this context, better knowledge of how climate will change in West Africa and how such changes will impact crop productivity is crucial to inform policies that may counteract the adverse effects. This review paper provides a comprehensive overview of climate change impacts on agriculture in West Africa based on the recent scientific literature. West Africa is nowadays experiencing a rapid climate change, characterized by a widespread warming, a recovery of the monsoonal precipitation, and an increase in the occurrence of climate extremes. The observed climate tendencies are also projected to continue in the twenty-first century under moderate and high emission scenarios, although large uncertainties still affect simulations of the future West African climate, especially regarding the summer precipitation. However, despite diverging future projections of the monsoonal rainfall, which is essential for rain-fed agriculture, a robust evidence of yield loss in West Africa emerges. This yield loss is mainly driven by increased mean temperature while potential wetter or drier conditions as well as elevated CO2 concentrations can modulate this effect. Potential for adaptation is illustrated for major crops in West Africa through a selection of studies based on process-based crop models to adjust cropping systems (change in varieties, sowing dates and density, irrigation, fertilizer management) to future climate. Results of the cited studies are crop and region specific and no clear conclusions can be made regarding the most effective adaptation options. Further efforts are needed to improve modeling of the monsoon system and to better quantify the uncertainty in its changes under a warmer climate, in the response of the crops to such changes and in the potential for adaptation.

Osmotic stress alters the balance between organic and inorganic solutes in flax (Linum usitatissimum)

Flax (Linum usitatissimum) is grown for its oil and its fiber. This crop, cultivated in temperate regions, has seen a renewed interest due to the presence of abundant molecules of interest for many applications. Little information is available about the behavior of flax during osmotic stress; yet this is considered a major stress that causes significant yield losses in most crops. To control the presence of this stress better, flax behavior was investigated following the application of osmotic stress and the response was examined by applying increasing concentrations of PEG 8000. This resulted in the reorganization of 32 metabolites and 6 mineral ions in the leaves. The analysis of these two types of solute highlighted the contrasting behavior between a higher metabolite content (particularly fructose, glucose and proline) and a decrease in mineral ions (especially nitrate and potassium) following PEG treatment. However, this reorganization did not lead to a greater accumulation of solutes, with the total amount remaining unchanged in leaves during osmotic stress.

Genome-wide association analysis for nine agronomic traits in maize under well-watered and water-stressed conditions

Drought can cause severe reduction in maize production, and strongly threatens crop yields. To dissect this complex trait and identify superior alleles, 350 tropical and subtropical maize inbred lines were genotyped using a 1536-SNP array developed from drought-related genes and an array of 56,110 random SNPs. The inbred lines were crossed with a common tester, CML312, and the testcrosses were phenotyped for nine traits under well-watered and water-stressed conditions in seven environments. Using genome-wide association mapping with correction for population structure, 42 associated SNPs (P ≤ 2.25 × 10(-6) 0.1/N) were identified, located in 33 genes for 126 trait × environment × treatment combinations. Of these genes, three were co-localized to drought-related QTL regions. Gene GRMZM2G125777 was strongly associated with ear relative position, hundred kernel weight and timing of male and female flowering, and encodes NAC domain-containing protein 2, a transcription factor expressed in different tissues. These results provide some good information for understanding the genetic basis for drought tolerance and further studies on identified candidate genes should illuminate mechanisms of drought tolerance and provide tools for designing drought-tolerant maize cultivars tailored to different environmental scenarios.

Antioxidant and photosystem II responses contribute to explain the drought-heat contrasting tolerance of two forage legumes

Identification of metabolic targets of environmental stress factors is critical to improve the stress tolerance of plants. Studying the biochemical and physiological responses of plants with different capacities to deal with stress is a valid approach to reach this objective. Lotus corniculatus (lotus) and Trifolium pratense (clover) are legumes with contrasting summer stress tolerances. In stress conditions, which are defined as drought, heat or a combination of both, we found that differential biochemical responses of leaves explain these behaviours. Lotus and clover showed differences in water loss control, proline accumulation and antioxidant enzymatic capacity. Drought and/or heat stress induced a large accumulation of proline in the tolerant species (lotus), whereas heat stress did not cause proline accumulation in the sensitive species (clover). In lotus, Mn-SOD and Fe-SOD were induced by drought, but in clover, the SOD-isoform profile was not affected by stress. Moreover, lotus has more SOD-isoforms and a higher total SOD activity than clover. The functionality and electrophoretic profile of photosystem II (PSII) proteins under stress also exhibited differences between the two species. In lotus, PSII activity was drastically affected by combined stress and, interestingly, was correlated with D2 protein degradation. Possible implications of this event as an adaption mechanism in tolerant species are discussed. We conclude that the stress-tolerant capability of lotus is related to its ability to respond to oxidative damage and adaption of the photosynthetic machinery. This reveals that these two aspects should be included in the evaluation of the tolerance of species to stress conditions.

Surface feature based classification of plant organs from 3D laserscanned point clouds for plant phenotyping

BACKGROUND

Laserscanning recently has become a powerful and common method for plant parameterization and plant growth observation on nearly every scale range. However, 3D measurements with high accuracy, spatial resolution and speed result in a multitude of points that require processing and analysis. The primary objective of this research has been to establish a reliable and fast technique for high throughput phenotyping using differentiation, segmentation and classification of single plants by a fully automated system. In this report, we introduce a technique for automated classification of point clouds of plants and present the applicability for plant parameterization.

RESULTS

A surface feature histogram based approach from the field of robotics was adapted to close-up laserscans of plants. Local geometric point features describe class characteristics, which were used to distinguish among different plant organs. This approach has been proven and tested on several plant species. Grapevine stems and leaves were classified with an accuracy of up to 98%. The proposed method was successfully transferred to 3D-laserscans of wheat plants for yield estimation. Wheat ears were separated with an accuracy of 96% from other plant organs. Subsequently, the ear volume was calculated and correlated to the ear weight, the kernel weights and the number of kernels. Furthermore the impact of the data resolution was evaluated considering point to point distances between 0.3 and 4.0 mm with respect to the classification accuracy.

CONCLUSION

We introduced an approach using surface feature histograms for automated plant organ parameterization. Highly reliable classification results of about 96% for the separation of grapevine and wheat organs have been obtained. This approach was found to be independent of the point to point distance and applicable to multiple plant species. Its reliability, flexibility and its high order of automation make this method well suited for the demands of high throughput phenotyping.

HIGHLIGHTS

• Automatic classification of plant organs using geometrical surface information• Transfer of analysis methods for low resolution point clouds to close-up laser measurements of plants• Analysis of 3D-data requirements for automated plant organ classification.

Phenotypic approaches to drought in cassava: review

Cassava is an important crop in Africa, Asia, Latin America, and the Caribbean. Cassava can be produced adequately in drought conditions making it the ideal food security crop in marginal environments. Although cassava can tolerate drought stress, it can be genetically improved to enhance productivity in such environments. Drought adaptation studies in over three decades in cassava have identified relevant mechanisms which have been explored in conventional breeding. Drought is a quantitative trait and its multigenic nature makes it very challenging to effectively manipulate and combine genes in breeding for rapid genetic gain and selection process. Cassava has a long growth cycle of 12-18 months which invariably contributes to a long breeding scheme for the crop. Modern breeding using advances in genomics and improved genotyping, is facilitating the dissection and genetic analysis of complex traits including drought tolerance, thus helping to better elucidate and understand the genetic basis of such traits. A beneficial goal of new innovative breeding strategies is to shorten the breeding cycle using minimized, efficient or fast phenotyping protocols. While high throughput genotyping have been achieved, this is rarely the case for phenotyping for drought adaptation. Some of the storage root phenotyping in cassava are often done very late in the evaluation cycle making selection process very slow. This paper highlights some modified traits suitable for early-growth phase phenotyping that may be used to reduce drought phenotyping cycle in cassava. Such modified traits can significantly complement the high throughput genotyping procedures to fast track breeding of improved drought tolerant varieties. The need for metabolite profiling, improved phenomics to take advantage of next generation sequencing technologies and high throughput phenotyping are basic steps for future direction to improve genetic gain and maximize speed for drought tolerance breeding.