Quantitative trait loci and crop performance under abiotic stress: where do we stand?

The Genetics and Breeding of Heat Stress Tolerance in Wheat: Advances and Prospects

Heat stress is one of the major concerns for wheat production worldwide. Morphological parameters such as germination, leaf area, shoot, and root growth are affected by heat stress, with affected physiological parameters including photosynthesis, respiration, and water relation. Heat stress also leads to the generation of reactive oxygen species that disrupt the membrane systems of thylakoids, chloroplasts, and the plasma membrane. The deactivation of the photosystems, reduction in photosynthesis, and inactivation of Rubisco affect the production of photo-assimilates and their allocation, consequently resulting in reduced grain yield and quality. The development of thermo-tolerant wheat varieties is the most efficient and fundamental approach for coping with global warming. This review provides a comprehensive overview of various aspects related to heat stress tolerance in wheat, including damages caused by heat stress, mechanisms of heat stress tolerance, genes or QTLs regulating heat stress tolerance, and the methodologies of breeding wheat cultivars with high heat stress tolerance. Such insights are essential for developing thermo-tolerant wheat cultivars with high yield potential in response to an increasingly warmer environment.

Mapping genomic regions for reproductive stage drought tolerance in rice from exotic landrace-derived population

In the rapid climate change scenario and subsequent rainfall patterns, drought has emerged as a bottleneck for crop production across crops, especially in rainfed rice. Drought significantly affects the development and production of most modern rice cultivars. Thus, recent breeding efforts have aimed to integrate drought tolerance traits in existing rice varieties through conventional and molecular approaches. The identification of grain yields quantitative trait loci (QTLs) under drought conditions, an important trait with high selection efficiency, may lead to the development of drought-tolerant rice varieties. The study reported the grain yield QTLs identified under the reproductive stage of drought stress in the F2-derived mapping population from Kasturi (drought-sensitive) × Chao Khaw (drought-tolerant). Thirteen QTLs (qDTYs) were identified based on two years of field data. Comparative analysis revealed two robust and consistent DTY QTLs, qDTY1.1 and qDTY8.1 , which explained the PVEs of 11.61% to 12.88% and 15.79% to 18.77%, respectively. However, qDTY1.1 was found at the nearest position to the previously identified qDTYs. Through candidate gene analysis, the identified QTL regions in chromosome 1 (qDTY1.1 ) and chromosome 8 (qDTY8.1 ) revealed seven and five candidate genes, respectively, based on gene ontology that were significantly associated with rice grain yield-related drought traits. In conclusion, this study identified key consistent drought yield QTLs in a drought-tolerant exotic landrace. The identified QTLs provide valuable insights and resources for ongoing efforts to develop drought-tolerant rice varieties. They can be further utilized in drought breeding programs to enhance the drought resilience of existing varieties or to develop new varieties.

The transcription factor MfbHLH104 from Myrothamnus flabellifolia promotes drought tolerance of Arabidopsis thaliana by enhancing stability of the photosynthesis system

The resurrection plant Myrothamnus flabellifolia can survive extreme drought and desiccation conditions, and quickly recover after rewatering. However, little is known about the mechanism underlying the drought tolerance of M. flabellifolia. In this study, MfbHLH104 was cloned and introduced into Arabidopsis thaliana due to the lack of a transgenic system for M. flabellifolia. MfbHLH104 is localized in the nucleus. Its N-terminal region has transactivation ability in yeast, and the C-terminal region may inhibit the transactivation ability. Overexpressing MfbHLH104 significantly increased drought and salt tolerance of A. thaliana at both seedling and adult stages. It enhanced leaf water retention capacity by decreasing water loss rate and increasing drought- and abscisic acid (ABA) -induced stomatal closure. Additionally, it boosted osmolyte accumulation and ROS scavenging ability by up-regulating genes associated with osmolyte biosynthesis and antioxidant enzymes, and enhancing antioxidant enzyme activities. The expression of ABA-responsive genes were also promoted by MfbHLH104. Remarkably, RNA-seq analysis indicated that MfbHLH104 significantly up-regulated 32 genes (FDR < 0.05 and fold change ≥1.5) involved in photosynthesis related pathways (KEGG pathway No: ko00195, ko00196) under drought, which account for 18.7 % of the total up-regulated genes and the most enriched KEGG pathways. This result suggested that it may help to maintain the stability of the photosynthesis system under drought conditions.

Quantitative Trait Loci Mappings for the Sulfur Utilization Efficiency-Related Traits at the Seedling Stage of Wheat

BACKGROUND

Sulfur (S) is a vital element for the normal growth and development of plants, performing crucial biological functions in various life processes.

METHODS

This study investigated thirteen S utilization efficiency (SUE)-related traits at the seedling stage of wheat using a recombinant inbred line (RIL) population. The quantitative trait loci (QTLs) were mapped by genetic mapping. Thirteen S utilization efficiency-related traits were investigated under two hydroponic culture trials with low S (0.1S, T1), moderate S (0.5S, T2), and high S (1.5S, T3) levels, using the wheat RILs.

RESULTS

A total of 170 QTLs for the thirteen traits in different treatment environments were identified. Among them, 89, 103, and 101 QTLs were found in T1, T2, and T3, respectively. A total of 63 QTLs were found in the multiple treatment environments, the other 107 QTLs only being detected in a single treatment environment. Among them, thirteen relatively high-frequency QTLs (RHF-QTLs) and eleven QTL clusters were found. Five (QSh-1D, QRn-1D, QSdw-1D, QTdw-1D, and QTsc-1D) and six (QRdw-6A, QSdw-6A, QTdw-6A, QRsc-6A, QSsc-6A, and QTsc-6A) RHF-QTLs were identified in QTL clusters C3 and C10, respectively.

CONCLUSION

These thirteen RHF-QTLs and eleven QTL clusters are expected to apply to the molecular marker-assisted selection (MAS) of wheat.

Harnessing landrace diversity empowers wheat breeding

Harnessing genetic diversity in major staple crops through the development of new breeding capabilities is essential to ensure food security1. Here we examined the genetic and phenotypic diversity of the A. E. Watkins landrace collection2 of bread wheat (Triticum aestivum), a major global cereal, by whole-genome re-sequencing of 827 Watkins landraces and 208 modern cultivars and in-depth field evaluation spanning a decade. We found that modern cultivars are derived from two of the seven ancestral groups of wheat and maintain very long-range haplotype integrity. The remaining five groups represent untapped genetic sources, providing access to landrace-specific alleles and haplotypes for breeding. Linkage disequilibrium-based haplotypes and association genetics analyses link Watkins genomes to the thousands of identified high-resolution quantitative trait loci and significant marker-trait associations. Using these structured germplasm, genotyping and informatics resources, we revealed many Watkins-unique beneficial haplotypes that can confer superior traits in modern wheat. Furthermore, we assessed the phenotypic effects of 44,338 Watkins-unique haplotypes, introgressed from 143 prioritized quantitative trait loci in the context of modern cultivars, bridging the gap between landrace diversity and current breeding. This study establishes a framework for systematically utilizing genetic diversity in crop improvement to achieve sustainable food security.

Temperature-dependent jumonji demethylase modulates flowering time by targeting H3K36me2/3 in Brassica rapa

Global warming has a severe impact on the flowering time and yield of crops. Histone modifications have been well-documented for their roles in enabling plant plasticity in ambient temperature. However, the factor modulating histone modifications and their involvement in habitat adaptation have remained elusive. In this study, through genome-wide pattern analysis and quantitative-trait-locus (QTL) mapping, we reveal that BrJMJ18 is a candidate gene for a QTL regulating thermotolerance in thermotolerant B. rapa subsp. chinensis var. parachinensis (or Caixin, abbreviated to Par). BrJMJ18 encodes an H3K36me2/3 Jumonji demethylase that remodels H3K36 methylation across the genome. We demonstrate that the BrJMJ18 allele from Par (BrJMJ18Par) influences flowering time and plant growth in a temperature-dependent manner via characterizing overexpression and CRISPR/Cas9 mutant plants. We further show that overexpression of BrJMJ18Par can modulate the expression of BrFLC3, one of the five BrFLC orthologs. Furthermore, ChIP-seq and transcriptome data reveal that BrJMJ18Par can regulate chlorophyll biosynthesis under high temperatures. We also demonstrate that three amino acid mutations may account for function differences in BrJMJ18 between subspecies. Based on these findings, we propose a working model in which an H3K36me2/3 demethylase, while not affecting agronomic traits under normal conditions, can enhance resilience under heat stress in Brassica rapa.

Understanding phloem's role in long-distance transport and accumulation of arsenic (As) in rice: toward low-As-accumulating grain development

MAIN CONCLUSION

This review highlights the roles of phloem in the long-distance transport and accumulation of As in rice plants, facilitating the formulation of new strategies to reduce the grain As content. Rice is a staple diet for a significant proportion of the global population. As toxicity is a major issue affecting the rice productivity and quality worldwide. Phloem tissues of rice plants play vital roles in As speciation, long-distance transport, and unloading, thereby controlling the As accumulation in rice grains. Phloem transport accounts for a significant proportion of As transport to grains, ranging from 54 to 100% depending on the species [inorganic arsenate (As(V)), arsenite (As(III)), or organic dimethylarsinic acid (DMA(V)]. However, the specific mechanism of As transport through phloem leading to its accumulation in grains remains unknown. Therefore, understanding the molecular mechanism of phloem-mediated As transport is necessary to determine the roles of phloem in long-distance As transport and subsequently reduce the grain As content via biotechnological interventions. This review discusses the roles of phloem tissues in the long-distance transport and accumulation of As in rice grains. This review also highlights the biotechnological approaches using critical genetic factors involved in nodal accumulation, vacuolar sequestration, and cellular efflux of As in phloem- or phloem-associated tissues. Furthermore, the limitations of existing transgenic techniques are outlined to facilitate the formulation of novel strategies for the development of rice with reduced grain As content.

The crucial role of lateral root angle in enhancing drought resilience in cotton

Introduction

Plant responses to drought stress are influenced by various factors, including the lateral root angle (LRA), stomatal regulation, canopy temperature, transpiration rate and yield. However, there is a lack of research that quantifies their interactions, especially among different cotton varieties.

Methods

This experiment included two water treatments: well-watered (75 ± 5% soil relative water content) and drought stress (50 ± 5% soil relative water content) starting from the three-leaf growth stage.

Results

The results revealed that different LRA varieties show genetic variation under drought stress. Among them, varieties with smaller root angles show greater drought tolerance. Varieties with smaller LRAs had significantly increased stomatal opening by 15% to 43%, transpiration rate by 61.24% and 62.00%, aboveground biomass by 54% to 64%, and increased seed cotton yield by 76% to 79%, and decreased canopy temperature by 9% to 12% under drought stress compared to the larger LRAs. Varieties with smaller LRAs had less yield loss under drought stress, which may be due to enhanced access to deeper soil water, compensating for heightened stomatal opening and elevated transpiration rates. The increase in transpiration rate promotes heat dissipation from leaves, thereby reducing leaf temperature and protecting leaves from damage.

Discussion

Demonstrating the advantages conferred by the development of a smaller LRA under drought stress conditions holds value in enhancing cotton's resilience and promoting its sustainable adaptation to abiotic stressors.

Molecular switches in plant stress adaptation

Climate change poses a significant threat to the global ecosystem, prompting plants to use various adaptive mechanisms via molecular switches to combat biotic and abiotic stress factors. These switches activate stress-induced pathways by altering their configuration between stable states. In this review, we investigated the regulation of molecular switches in different plant species in response to stress, including the stress-regulated response of multiple switches in Arabidopsis thaliana. We also discussed techniques for developing stress-resilient crops using molecular switches through advanced biotechnological tools. The literature search, conducted using databases such as PubMed, Google Scholar, Web of Science, and SCOPUS, utilized keywords such as molecular switch, plant adaptation, biotic and abiotic stresses, transcription factors, Arabidopsis thaliana, and crop improvement. Recent studies have shown that a single molecular switch can regulate multiple stress networks, and multiple switches can regulate a single stress condition. This multifactorial understanding provides clarity to the switch regulatory network and highlights the interrelationships of different molecular switches. Advanced breeding techniques, along with genomic and biotechnological tools, have paved the way for further research on molecular switches in crop improvement. The use of synthetic biology in molecular switches will lead to a better understanding of plant stress biology and potentially bring forth a new era of stress-resilient, climate-smart crops worldwide.

Nitrate improves aluminium resistance through SLAH-mediated citrate exudation from roots

Aluminium (Al) toxicity is one of the major constraint for crop production in acidic soil, and the inappropriate utilization of nitrogen fertilizer can accelerate soil acidification. Despite previous studies investigating the regulation of nitrogen forms in Al toxicity of plants, the underlying mechanism, particularly at the molecular level, remains unclear. This study aims to uncover the potentially regulatory mechanism of nitrate (NO3 - ) in the Al resistance of maize and Arabidopsis. NO3 - conservatively improves Al resistance in maize and Arabidopsis, with nitrate-elevated citrate synthesis and exudation potentially playing critical roles in excluding Al from the root symplast. ZmSLAH2 in maize and AtSLAH1 in Arabidopsis are essential for the regulation of citrate exudation and NO3 - -promoted Al resistance, with ZmMYB81 directly targeting the ZmSLAH2 promoter to activate its activity. Additionally, NO3 - transport is necessary for NO3 - -promoted Al resistance, with ZmNRT1.1A and AtNRT1.1 potentially playing vital roles. The suppression of NO3 - transport in roots by ammonium (NH4 + ) may inhibit NO3 - -promoted Al resistance. This study provides novel insights into the understanding of the crucial role of NO3 - -mediated signalling in the Al resistance of plants and offers guidance for nitrogen fertilization on acid soils.

Effects of Climate Change and Drought Tolerance on Maize Growth

Climate change is affecting all regions of the world with different climates, and the scale of damage is increasing due to the occurrence of various natural disasters. In particular, maize production is highly affected by abnormal climate events such as heat waves and droughts. Increasing temperatures can accelerate growth and shorten the growing season, potentially reducing productivity. Additionally, enhanced temperatures during the ripening period can accelerate the process, reducing crop yields. In addition, drought stress due to water deficit can greatly affect seedling formation, early plant growth, photosynthesis, reproductive growth, and yield, so proper water management is critical to maize growth. Maize, in particular, is tall and broad-leaved, so extreme drought stress at planting can cause leaves to curl and stunt growth. It is important to understand that severe drought can have a detrimental effect on the growth and reproduction of maize. In addition, high temperatures caused by drought stress can inhibit the induction of flowering in male flowers and cause factors that interfere with pollen development. It is therefore important to increase the productivity of all food crops, including maize, while maintaining them in the face of persistent drought caused by climate change. This requires a strategy to develop genetically modified crops and drought-tolerant maize that can effectively respond to climate change. The aim of this paper is to investigate the effects of climate change and drought tolerance on maize growth. We also reviewed molecular breeding techniques to develop drought-tolerant maize varieties in response to climate change.

Genomics and phenomics enabled prebreeding improved early-season chilling tolerance in Sorghum

In temperate climates, earlier planting of tropical-origin crops can provide longer growing seasons, reduce water loss, suppress weeds, and escape post-flowering drought stress. However, chilling sensitivity of sorghum, a tropical-origin cereal crop, limits early planting, and over 50 years of conventional breeding has been stymied by coinheritance of chilling tolerance (CT) loci with undesirable tannin and dwarfing alleles. In this study, phenomics and genomics-enabled approaches were used for prebreeding of sorghum early-season CT. Uncrewed aircraft systems (UAS) high-throughput phenotyping platform tested for improving scalability showed moderate correlation between manual and UAS phenotyping. UAS normalized difference vegetation index values from the chilling nested association mapping population detected CT quantitative trait locus (QTL) that colocalized with manual phenotyping CT QTL. Two of the 4 first-generation Kompetitive Allele Specific PCR (KASP) molecular markers, generated using the peak QTL single nucleotide polymorphisms (SNPs), failed to function in an independent breeding program as the CT allele was common in diverse breeding lines. Population genomic fixation index analysis identified SNP CT alleles that were globally rare but common to the CT donors. Second-generation markers, generated using population genomics, were successful in tracking the donor CT allele in diverse breeding lines from 2 independent sorghum breeding programs. Marker-assisted breeding, effective in introgressing CT allele from Chinese sorghums into chilling-sensitive US elite sorghums, improved early-planted seedling performance ratings in lines with CT alleles by up to 13-24% compared to the negative control under natural chilling stress. These findings directly demonstrate the effectiveness of high-throughput phenotyping and population genomics in molecular breeding of complex adaptive traits.

Application of machine learning algorithms and feature selection in rapeseed (Brassica napus L.) breeding for seed yield

BACKGROUND

Studying the relationships between rapeseed seed yield (SY) and its yield-related traits can assist rapeseed breeders in the efficient indirect selection of high-yielding varieties. However, since the conventional and linear methods cannot interpret the complicated relations between SY and other traits, employing advanced machine learning algorithms is inevitable. Our main goal was to find the best combination of machine learning algorithms and feature selection methods to maximize the efficiency of indirect selection for rapeseed SY.

RESULTS

To achieve that, twenty-five regression-based machine learning algorithms and six feature selection methods were employed. SY and yield-related data from twenty rapeseed genotypes were collected from field experiments over a period of 2 years (2019-2021). Root mean square error (RMSE), mean absolute error (MAE), and determination coefficient (R²) were used to evaluate the performance of the algorithms. The best performance with all fifteen measured traits as inputs was achieved by the Nu-support vector regression algorithm with quadratic polynomial kernel function (R² = 0.860, RMSE = 0.266, MAE = 0.210). The multilayer perceptron neural network algorithm with identity activation function (MLPNN-Identity) using three traits obtained from stepwise and backward selection methods appeared to be the most efficient combination of algorithms and feature selection methods (R² = 0.843, RMSE = 0.283, MAE = 0.224). Feature selection suggested that the set of pods per plant and days to physiological maturity along with plant height or first pod height from the ground are the most influential traits in predicting rapeseed SY.

CONCLUSION

The results of this study showed that MLPNN-Identity along with stepwise and backward selection methods can provide a robust combination to accurately predict the SY using fewer traits and therefore help optimize and accelerate SY breeding programs of rapeseed.

Mapping of QTLs for morphophysiological and yield traits under water-deficit stress and well-watered conditions in maize

Maize productivity is significantly impacted by drought; therefore, improvement of drought tolerance is a critical goal in maize breeding. To achieve this, a better understanding of the genetic basis of drought tolerance is necessary. Our study aimed to identify genomic regions associated with drought tolerance-related traits by phenotyping a mapping population of recombinant inbred lines (RILs) for two seasons under well-watered (WW) and water-deficit (WD) conditions. We also used single nucleotide polymorphism (SNP) genotyping through genotyping-by-sequencing to map these regions and attempted to identify candidate genes responsible for the observed phenotypic variation. Phenotyping of the RILs population revealed significant variability in most of the traits, with normal frequency distributions, indicating their polygenic nature. We generated a linkage map using 1,241 polymorphic SNPs distributed over 10 chromosomes (chrs), covering a total genetic distance of 5,471.55 cM. We identified 27 quantitative trait loci (QTLs) associated with various morphophysiological and yield-related traits, with 13 QTLs identified under WW conditions and 12 under WD conditions. We found one common major QTL (qCW2-1) for cob weight and a minor QTL (qCH1-1) for cob height that were consistently identified under both water regimes. We also detected one major and one minor QTL for the Normalized Difference Vegetation Index (NDVI) trait under WD conditions on chr 2, bin 2.10. Furthermore, we identified one major QTL (qCH1-2) and one minor QTL (qCH1-1) on chr 1 that were located at different genomic positions to those identified in earlier studies. We found co-localized QTLs for stomatal conductance and grain yield on chr 6 (qgs6-2 and qGY6-1), while co-localized QTLs for stomatal conductance and transpiration rate were identified on chr 7 (qgs7-1 and qTR7-1). We also attempted to identify the candidate genes responsible for the observed phenotypic variation; our analysis revealed that the major candidate genes associated with QTLs detected under water deficit conditions were related to growth and development, senescence, abscisic acid (ABA) signaling, signal transduction, and transporter activity in stress tolerance. The QTL regions identified in this study may be useful in designing markers that can be utilized in marker-assisted selection breeding. In addition, the putative candidate genes can be isolated and functionally characterized so that their role in imparting drought tolerance can be more fully understood.

Identifying physiological and genetic determinants of faba bean transpiration response to evaporative demand

BACKGROUND AND AIMS

Limiting maximum transpiration rate (TR) under high vapour pressure deficit (VPD) works as a water conservation strategy. While some breeding programmes have incorporated this trait into some crops to boost yields in water-limited environments, its underlying physiological mechanisms and genetic regulation remain unknown for faba bean (Vicia faba). Thus, we aimed to identify genetic variation in the TR response to VPD in a population of faba bean recombinant inbred lines (RILs) derived from two parental lines with contrasting water use (Mélodie/2 and ILB 938/2).

METHODS

Plants were grown in well-watered soil in a climate-controlled glasshouse with diurnally fluctuating VPD and light conditions. Whole plant transpiration was measured in a gas exchange chamber that tightly regulated VPD around the shoot under constant light, while whole-plant hydraulic conductance and its components (root and stem hydraulic conductance) were calculated from dividing TR by water potential gradients measured with a pressure chamber.

KEY RESULTS

Although TR of Mélodie/2 increased linearly with VPD, ILB 938/2 limited its TR above 2.0 kPa. Nevertheless, Mélodie/2 had a higher leaf water potential than ILB 938/2 at both low (1.0 kPa) and high (3.2 kPa) VPD. Almost 90 % of the RILs limited their TR at high VPD with a break-point (BP) range of 1.5-3.0 kPa and about 10 % had a linear TR response to VPD. Thirteen genomic regions contributing to minimum and maximum transpiration, and whole-plant and root hydraulic conductance, were identified on chromosomes 1 and 3, while one locus associated with BP transpiration was identified on chromosome 5.

CONCLUSIONS

This study provides insight into the physiological and genetic control of transpiration in faba bean and opportunities for marker-assisted selection to improve its performance in water-limited environments.

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.

Development of bread wheat (Triticum aestivum L) variety HD3411 following marker-assisted backcross breeding for drought tolerance

Marker-assisted backcross breeding enables selective insertion of targeted traits into the genome to improve yield, quality, and stress resistance in wheat. In the current investigation, we transferred four drought tolerance quantitative trait loci (QTLs) controlling traits, viz canopy temperature, normalized difference vegetative index, chlorophyll content, and grain yield from the drought-tolerant donor line, C306, into a popular high-yielding, drought-sensitive variety, HD2733. Marker-assisted selection coupled with stringent phenotypic screening was used to advance each generation. This study resulted in 23 improved lines carrying combinations of four drought tolerance QTLs with a range of 85.35%-95.79% background recovery. The backcross-derived lines gave a higher yield under moisture-deficit stress conditions compared with the recipient parent. They also showed higher phenotypic mean values for physiological traits and stability characteristics of HD2733. A promising genotype, HD3411, derived from this cross was identified for release after national multi-location coordinating trials under the All India Coordinated Wheat Improvement Project. Our study is a prime example of the advantages of precision breeding using integrating markers and phenotypic selection to develop new cultivars with desirable traits like drought tolerance.

Analysis of QTL mapping for germination and seedling response to drought stress in sunflower (Helianthus annuus L.)

Sunflower is an important oilseed crop across the world. It is considered as a moderately drought tolerant plant, however, its yield is still negatively affected by drought stress. Improving drought tolerance is of the outmost important for breeding. Although several studies have documented the relationship between the sunflower phenotype and genotype under drought stress, but relatively few studies have simultaneously investigated the molecular mechanisms of drought tolerance in the sunflower at different growth stages. In this study, we conducted quantitative trait locus (QTL) analysis for different sunflower traits during the germination and seedling stages. Eighteen phenotypic traits were evaluated under well-watered and drought stress conditions. We determined that the germination rate, germination potential, germination index, and root-to-shoot ratio can be used as effective indexes for drought tolerance selection and breeding. A total of 33 QTLs were identified on eight chromosomes (PVE: 0.016%-10.712% with LOD: 2.017-7.439). Within the confidence interval of the QTL, we identified 60 putative drought-related genes. Four genes located on chromosome 13 may function in both germination and seedling stages for drought response. Genes LOC110898128, LOC110898092, LOC110898071, and LOC110898072 were annotated as aquaporin SIP1-2-like, cytochrome P450 94C1, GABA transporter 1-like, and GABA transporter 1-like isoform X2, respectively. These genes will be used for further functional validation. This study provides insight into the molecular mechanisms of the sunflower's in response to drought stress. At the same time, it lays a foundation for sunflower drought tolerance breeding and genetic improvement.

Meta-QTL Analysis for Yield Components in Common Bean (Phaseolus vulgaris L.)

Common bean is one of the most important legumes produced and consumed worldwide because it is a highly valuable food for the human diet. However, its production is mainly carried out by small farmers, who obtain average grain yields below the potential yield of the species. In this sense, numerous mapping studies have been conducted to identify quantitative trait loci (QTL) associated with yield components in common bean. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies. Consequently, the objective of this study was to perform a MQTL analysis to identify the most reliable and stable genomic regions associated with yield-related traits of common bean. A total of 667 QTL associated with yield-related traits reported in 21 different studies were collected. A total of 42 MQTL associated with yield-related traits were identified, in which the average confidence interval (CI) of the MQTL was 3.41 times lower than the CIs of the original QTL. Most of the MQTL (28) identified in this study contain QTL associated with yield and phenological traits; therefore, these MQTL can be useful in common bean breeding programs. Finally, a total of 18 candidate genes were identified and associated with grain yield within these MQTL, with functions related to ubiquitin ligase complex, response to auxin, and translation elongation factor activity.

Quantitative trait loci mapping reveals important genomic regions controlling root architecture and shoot biomass under nitrogen, phosphorus, and potassium stress in rapeseed (Brassica napus L.)

Plants rely on root systems for nutrient uptake from soils. Marker-assisted selection helps breeders to select desirable root traits for effective nutrient uptake. Here, 12 root and biomass traits were investigated at the seedling stage under low nitrogen (LN), low phosphorus (LP), and low potassium (LK) conditions, respectively, in a recombinant inbred line (RIL) population, which was generated from Brassica napus L. Zhongshuang11 and 4D122 with significant differences in root traits and nutrient efficiency. Significant differences for all the investigated traits were observed among RILs, with high heritabilities (0.43-0.74) and high correlations between the different treatments. Quantitative trait loci (QTL) mapping identified 57, 27, and 36 loci, explaining 4.1-10.9, 4.6-10.8, and 4.9-17.4% phenotypic variances under LN, LP, and LK, respectively. Through QTL-meta analysis, these loci were integrated into 18 significant QTL clusters. Four major QTL clusters involved 25 QTLs that could be repeatedly detected and explained more than 10% phenotypic variances, including two NPK-common and two specific QTL clusters (K and NK-specific), indicating their critical role in cooperative nutrients uptake of N, P, and K. Moreover, 264 genes within the four major QTL clusters having high expressions in roots and SNP/InDel variations between two parents were identified as potential candidate genes. Thirty-eight of them have been reported to be associated with root growth and development and/or nutrient stress tolerance. These key loci and candidate genes lay the foundation for deeper dissection of the NPK starvation response mechanisms in B. napus.

Drought-Induced Oxidative Stress in Pearl Millet (Cenchrus americanus L.) at Seedling Stage: Survival Mechanisms through Alteration of Morphophysiological and Antioxidants Activity

We report the impact of drought stress on pearl millet during the early seedling stage and its survival mechanism. Drought stress imposed for a period of 7, 14 and 21 days showed considerable changes in morphophysiological attributes, which were evident by a decline in seedling elongation, fresh and dry biomass, and relative water content (RWC) and degradation of chlorophyll pigment. Besides this, visible chlorosis lesions were observed in leaves as compared to the control. As compared to the respective controls, a nearly 60% decline in chlorophyll content was recorded after 14 and 21 days of drought stress. In both root and shoot, drought stress raised the reactive oxygen species (ROS) levels. Both H2O2 and O2●- levels were significantly elevated along with a significant increase in lipid peroxidation in both roots and shoots, which clearly indicated ROS-induced oxidative stress. Concomitant with the increase in ROS levels and malondialdehyde (MDA) content in roots, membrane integrity was also lost, which clearly indicated ROS-induced peroxidation of membrane lipids. The activities of antioxidant enzymes and levels of non-enzymatic antioxidants were significant (p ≤ 0.001). After 7, 14 and 21 days of drought stress, activities of all the antioxidant enzymes viz., catalase (CAT), guaiacol peroxidase (GPX), superoxide dismutase (SOD) and glutathione reductase (GR) were inhibited, clearly indicating a loss of antioxidant defense machinery. Likewise, the levels of ascorbate (AsA) and reduced glutathione (GSH) levels declined significantly (p ≤ 0.01). Our results reveal that, being tolerant to arid climatic conditions, pearl millet is highly susceptible to drought stress at the early seedling stage.

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.

Understanding the Effect of Different Abiotic Stresses on Wild Marigold (Tagetes minuta L.) and Role of Breeding Strategies for Developing Tolerant Lines

Wild marigold has a growing demand for its essential oil in the flavor and fragrance industries. It can be grown over a broad range of climates, but the changing climatic conditions lead to abiotic stresses, thus restricting its productivity. Abiotic stresses at elevated levels result in the reduction of germination, growth, and essential oil quality of wild marigold leading to heterogeneous and inferior grades of "Tagetes oil." Drought, salinity, and heavy metal stress at elevated levels have common effects in terms of ROS formation, which are the major cause of growth deterioration in wild marigold. Temperatures above 35°C inhibit seed germination. Irradiance stress reduces the biomass and essential oil yield. Waterlogging adversely affects the survival of wild marigold in high rainfall regions. The application of plant nutrients (fertilizers) modulates the biomass and essential oil yield. Wild marigold employs multiple tolerance mechanisms to cope up with the adverse effects of abiotic stresses such as the increased activity of antioxidants to maintain cellular redox homeostasis, enhanced lipid peroxidation in the cell membrane to maintain cell wall architecture, production of secondary metabolites, and accumulation of osmolytes. In this review, we tried to understand how abiotic stresses affect wild marigold. Understanding the physiological changes and biochemical characteristics of stress tolerance will contribute to the development of stress-tolerant lines of wild marigold.

Determination of morpho-physiological and yield traits of maize inbred lines (Zea mays L.) under optimal and drought stress conditions

Globally, climate change could hinder future food security that concurrently implies the importance of investigating drought stress and genotype screening under stressed environments. Hence, the current study was performed to screen 45 diverse maize inbred lines for 18 studied traits comprising phenological, physiological, morphological, and yield characters under optimum and water stress conditions for two successive growing seasons (2018 and 2019). The results showed that growing seasons and water regimes significantly influenced (p < 0.01) most of the studied traits, while inbred lines had a significant effect (p < 0.01) on all of the studied traits. The findings also showed a significant increase in all studied characters under normal conditions compared to drought conditions, except chlorophyll content, transpiration rate, and proline content which exhibited higher levels under water stress conditions. Furthermore, the results of the principal component analysis indicated a notable distinction between the performance of the 45 maize inbred lines under normal and drought conditions. In terms of grain yield, the drought tolerance index (DTI) showed that Nub60 (1.56), followed by Nub32 (1.46), Nub66 (1.45), and GZ603 (1.44) were the highest drought-tolerant inbred lines, whereas Nub46 (0.38) was the lowest drought-tolerant inbred line. These drought-tolerant inbred lines were able to maintain a relatively high grain yield under normal and stress conditions, whereas those drought-sensitive inbred lines showed a decline in grain yield when exposed to drought conditions. The hierarchical clustering analysis based on DTI classified the forty-five maize inbred lines and eighteen measured traits into three column- and row-clusters, as inbred lines in cluster-3 followed by those in cluster-2 exhibited greater drought tolerance in most of the studied traits. Utilizing the multi-trait stability index (MTSI) criterion in this study identified nine inbred lines, including GZ603, as stable genotypes in terms of the eighteen studied traits across four environments. The findings of the current investigation motivate plant breeders to explore the genetic potential of the current maize germplasm, especially in water-stressed environments.

Reproductive Stage Drought Tolerance in Wheat: Importance of Stomatal Conductance and Plant Growth Regulators

Drought stress requires plants to adjust their water balance to maintain tissue water levels. Isohydric plants (‘water-savers’) typically achieve this through stomatal closure, while anisohydric plants (‘water-wasters’) use osmotic adjustment and maintain stomatal conductance. Isohydry or anisohydry allows plant species to adapt to different environments. In this paper we show that both mechanisms occur in bread wheat (Triticum aestivum L.). Wheat lines with reproductive drought-tolerance delay stomatal closure and are temporarily anisohydric, before closing stomata and become isohydric at higher threshold levels of drought stress. Drought-sensitive wheat is isohydric from the start of the drought treatment. The capacity of the drought-tolerant line to maintain stomatal conductance correlates with repression of ABA synthesis in spikes and flag leaves. Gene expression profiling revealed major differences in the drought response in spikes and flag leaves of both wheat lines. While the isohydric drought-sensitive line enters a passive growth mode (arrest of photosynthesis, protein translation), the tolerant line mounts a stronger stress defence response (ROS protection, LEA proteins, cuticle synthesis). The drought response of the tolerant line is characterised by a strong response in the spike, displaying enrichment of genes involved in auxin, cytokinin and ethylene metabolism/signalling. While isohydry may offer advantages for longer term drought stress, anisohydry may be more beneficial when drought stress occurs during the critical stages of wheat spike development, ultimately improving grain yield.

Developing Novel Rice Genotypes Harboring Specific QTL Alleles Associated with High Grain Yield under Water Shortage Stress

Rice is considered a strategic crop for many countries around the world, being the main cash crop for farmers. Water shortage stress occurrence as a result of climate change is among the main threats challenging rice breeders in the last few decades. In the current study, 19 Fn-lines were developed from four populations by crossing a reverse thermo-responsive genic male sterile (rTGMS) line, M.J.5460S, with the three high-quality Egyptian commercial cultivars Giza177, Sakha105, Sakha106 and the promising line GZ7768 as male parents. These newly developed lines, along with their parents, and two water shortage stress-tolerant international genotypes (Azucena and IRAT170), were cultivated under water-shortage stress conditions and compared with their performance under well-watered conditions. Results indicated that the yielding ability of the 19 newly developed lines exceeded those for the two Egyptian parents (Giza177 and Sakha105) under well-watered conditions. The lines M.J5460S/GIZA177-3 and M.J5460S/GIZA177-12 were the best performing genotypes under water shortage stress conditions. The genetic and heritability in broad sense estimates indicated that direct selection for grain yield (GY) under water-shortage stress is highly effective in the current study. Molecular marker analysis revealed that M.J5460S/GIZA177-3 had accumulated the quantitative trait loci (QTL)s, on the chromosomes 2, 3, and 9, which contribute to GY under water-shortage stress from their high yielding tolerant ancestor, M.J5460S. It could be concluded that those lines are high yielding under both well-watered and water-stress conditions harboring several QTLs for yield enhancement under both conditions and that the markers RM555, RM14551, RM3199, RM257, RM242, and RM410 are among the markers that could be used in marker-assisted selection (MAS) breeding programs for such stress condition.

Plant strategies for maximizing growth during water stress and subsequent recovery in Solanum melongena L. (eggplant)

Climate change is projected to increase the incidence of severe drought in many regions, potentially requiring selection for different traits in crop species to maintain productivity under water stress. In this study, we identified a suite of hydraulic traits associated with high productivity under water stress in four genotypes of S. melongena L. We also assessed the potential for recovery of this suite of traits from drought stress after re-watering. We observed that two genotypes, PHL 4841 and PHL 2778, quickly grew into large plants with smaller, thicker leaves and increasingly poor hydraulic status (a water-spender strategy), whereas PHL 2789 and Mara maintained safer water status and larger leaves but sacrificed large gains in biomass (a water-saver strategy). The best performing genotype under water stress, PHL 2778, additionally showed a significant increase in root biomass allocation relative to other genotypes. Biomass traits of all genotypes were negatively impacted by water deficit and remained impaired after a week of recovery; however, physiological traits such as electron transport capacity of photosystem II, and proportional allocation to root biomass and fine root length, and leaf area recovered after one week, indicating a strong capacity for eggplant to rebound from short-term deficits via recovery of physiological activity and allocation to resource acquiring tissues. These traits should be considered in selection and breeding of eggplant hybrids for future agricultural outlooks.

Differential regulation of drought stress by biological membrane transporters and channels

Stress arising due to abiotic factors affects the plant's growth and productivity. Among several existing abiotic stressors like cold, drought, heat, salinity, heavy metal, etc., drought condition tends to affect the plant's growth by inducing two-point effect, i.e., it disturbs the water balance as well as induces toxicity by disturbing the ion homeostasis, thus hindering the growth and productivity of plants, and to survive under this condition, plants have evolved several transportation systems that are involved in regulating the drought stress. The role of membrane transporters has gained interest since genetic engineering came into existence, and they were found to be the important modulators for tolerance, avoidance, ion movements, stomatal movements, etc. Here in this comprehensive review, we have discussed the role of transporters (ABA, protein, carbohydrates, etc.) and channels that aids in withstanding the drought stress as well as the regulatory role of transporters involved in osmotic adjustments arising due to drought stress. This review also provides a gist of hydraulic conductivity by roots that are involved in regulating the drought stress.

Genome-wide association mapping reveals key genomic regions for physiological and yield-related traits under salinity stress in wheat (Triticum aestivum L.)

A genome-wide association study (GWAS) was conducted using six different multi-locus GWAS models and 35K SNP array to demarcate genomic regions underlying reproductive stage salinity tolerance. Marker-trait association analysis was performed for salt tolerance indices (STI) of 11 morpho-physiological traits, and the actual concentrations of Na⁺ and K⁺, and the Na⁺/K⁺ ratio in flag leaf. A total of 293 significantly associated quantitative trait nucleotides (QTNs) for 14 morpho-physiological traits were identified. Of these 293 QTNs, 12 major QTNs with R² ≥ 10.0% were detected in three or more GWAS models. Novel major QTNs were identified for plant height, number of effective tillers, biomass, grain yield, thousand grain weight, Na⁺ and K⁺ content, and the Na⁺/K⁺ ratio in flag leaf. Moreover, 48 candidate genes were identified from the associated genomic regions. The QTNs identified in this study could potentially be targeted for improving salinity tolerance in wheat.

Using Hybrid Artificial Intelligence and Evolutionary Optimization Algorithms for Estimating Soybean Yield and Fresh Biomass Using Hyperspectral Vegetation Indices

Recent advanced high-throughput field phenotyping combined with sophisticated big data analysis methods have provided plant breeders with unprecedented tools for a better prediction of important agronomic traits, such as yield and fresh biomass (FBIO), at early growth stages. This study aimed to demonstrate the potential use of 35 selected hyperspectral vegetation indices (HVI), collected at the R5 growth stage, for predicting soybean seed yield and FBIO. Two artificial intelligence algorithms, ensemble-bagging (EB) and deep neural network (DNN), were used to predict soybean seed yield and FBIO using HVI. Considering HVI as input variables, the coefficients of determination (R2) of 0.76 and 0.77 for yield and 0.91 and 0.89 for FBIO were obtained using DNN and EB, respectively. In this study, we also used hybrid DNN-SPEA2 to estimate the optimum HVI values in soybeans with maximized yield and FBIO productions. In addition, to identify the most informative HVI in predicting yield and FBIO, the feature recursive elimination wrapper method was used and the top ranking HVI were determined to be associated with red, 670 nm and near-infrared, 800 nm, regions. Overall, this study introduced hybrid DNN-SPEA2 as a robust mathematical tool for optimizing and using informative HVI for estimating soybean seed yield and FBIO at early growth stages, which can be employed by soybean breeders for discriminating superior genotypes in large breeding populations.

Root-omics for drought tolerance in cool-season grain legumes

Root traits can be exploited to increase the physiological efficiency of crop water use under drought. Root length, root hairs, root branching, root diameter, and root proliferation rate are genetically defined traits that can help to improve the water productivity potential of crops. Recently, high-throughput phenotyping techniques/platforms have been used to screen the germplasm of major cool-season grain legumes for root traits and their impact on different physiological processes, including nutrient uptake and yield potential. Advances in omics approaches have led to the dissection of genomic, proteomic, and metabolomic structures of these traits. This knowledge facilitates breeders to improve the water productivity and nutrient uptake of cultivars under limited soil moisture conditions in major cool-season grain legumes that usually face terminal drought. This review discusses the advances in root traits and their potential for developing drought-tolerant cultivars in cool-season grain legumes.

KASPar SNP genetic map of cassava for QTL discovery of productivity traits in moderate drought stress environment in Africa

Cassava is an important staple in Sub-Sahara Africa. While its production has rapidly expanded to the dry savannahs of the continent, productivity is low in this ecology due to drought by farmers, extending the growth cycle from 12 months to 18, and sometimes 24 months to ensure better harvests. Yield is a complex trait and often difficult to manipulate for genetic gain in conventional breeding. Unfortunately, the dearth of molecular tools for decades has hampered molecular breeding (MB) to improve cassava productivity. This study was conducted to explore KASpar SNPs to generate more molecular tools to enhance genetic dissection of elite African germplasm for improved cassava productivity in dry environments of Africa where molecular resources are highly limited for crop improvement. To aid molecular genetic analysis of traits, a linkage map covering 1582.8 cM with an average resolution of 3.69 cM was constructed using 505 polymorphic SNP markers distributed over 21 linkage groups. Composite interval mapping using 267 F1 progeny in initial QTL mapping identified 27 QTLs for productivity traits in the dry savannah of Nigeria. The availability of KASPar SNPs are anticipated to improve the implementation of MB for the development of high performing drought-tolerant cassava varieties in Africa.

Transcriptome analysis of upland cotton revealed novel pathways to scavenge reactive oxygen species (ROS) responding to Na2SO4 tolerance

Salinity is an extensive and adverse environmental stress to crop plants across the globe, and a major abiotic constraint responsible for limited crop production threatening the crop security. Soil salinization is a widespread problem across the globe, threatening the crop production and food security. Salinity impairs plant growth and development via reduction in osmotic potential, cytotoxicity due to excessive uptake of ions such as sodium (Na⁺) and chloride (Cl^-), and nutritional imbalance. Cotton, being the most cultivated crop on saline-alkaline soils, it is of great importance to elucidate the mechanisms involved in Na₂SO₄ tolerance which is still lacking in upland cotton. Zhong 9835, a Na₂SO₄ resistant cultivar was screened for transcriptomic studies through various levels of Na₂SO₄ treatments, which results into identification of 3329 differentially expressed genes (DEGs) in roots, stems and leave at 300 mM Na₂SO₄ stress till 12 h in compared to control. According to gene functional annotation analysis, genes involved in reactive oxygen species (ROS) scavenging system including osmotic stress and ion toxicity were significantly up-regulated, especially GST (glutathione transferase). In addition, analysis for sulfur metabolism, results in to identification of two rate limiting enzymes [APR (Gh_D05G1637) and OASTL (Gh_A13G0863)] during synthesis of GSH from SO₄^2-. Furthermore, we also observed a crosstalk of the hormones and TFs (transcription factors) enriched in hormone signal transduction pathway. Genes related to IAA exceeds the rest of hormones followed by ubiquitin related genes which are greater than TFs. The analysis of the expression profiles of diverse tissues under Na₂SO₄ stress and identification of relevant key hub genes in a network crosstalk will provide a strong foundation and valuable clues for genetic improvements of cotton in response to various salt stresses.

Development of an Australian Bread Wheat Nested Association Mapping Population, a New Genetic Diversity Resource for Breeding under Dry and Hot Climates

Genetic diversity, knowledge of the genetic architecture of the traits of interest and efficient means of transferring the desired genetic diversity into the relevant genetic background are prerequisites for plant breeding. Exotic germplasm is a rich source of genetic diversity; however, they harbor undesirable traits that limit their suitability for modern agriculture. Nested association mapping (NAM) populations are valuable genetic resources that enable incorporation of genetic diversity, dissection of complex traits and providing germplasm to breeding programs. We developed the OzNAM by crossing and backcrossing 73 diverse exotic parents to two Australian elite varieties Gladius and Scout. The NAM parents were genotyped using the iSelect wheat 90K Infinium SNP array, and the progeny were genotyped using a custom targeted genotyping-by-sequencing assay based on molecular inversion probes designed to target 12,179 SNPs chosen from the iSelect wheat 90K Infinium SNP array of the parents. In total, 3535 BC1F4:6 RILs from 125 families with 21 to 76 lines per family were genotyped and we found 4964 polymorphic and multi-allelic haplotype markers that spanned the whole genome. A subset of 530 lines from 28 families were evaluated in multi-environment trials over three years. To demonstrate the utility of the population in QTL mapping, we chose to map QTL for maturity and plant height using the RTM-GWAS approach and we identified novel and known QTL for maturity and plant height.

Induction of Acquired Tolerance Through Gradual Progression of Drought Is the Key for Maintenance of Spikelet Fertility and Yield in Rice Under Semi-irrigated Aerobic Conditions

Plants have evolved several adaptive mechanisms to cope with water-limited conditions. While most of them are through constitutive traits, certain "acquired tolerance" traits also provide significant improvement in drought adaptation. Most abiotic stresses, especially drought, show a gradual progression of stress and hence provide an opportunity to upregulate specific protective mechanisms collectively referred to as "acquired tolerance" traits. Here, we demonstrate a significant genetic variability in acquired tolerance traits among rice germplasm accessions after standardizing a novel gradual stress progress protocol. Two contrasting genotypes, BPT 5204 (drought susceptible) and AC 39000 (tolerant), were used to standardize methodology for capturing acquired tolerance traits at seedling phase. Seedlings exposed to gradual progression of stress showed higher recovery with low free radical accumulation in both the genotypes compared to rapid stress. Further, the gradual stress progression protocol was used to examine the role of acquired tolerance at flowering phase using a set of 17 diverse rice genotypes. Significant diversity in free radical production and scavenging was observed among these genotypes. Association of these parameters with yield attributes showed that genotypes that managed free radical levels in cells were able to maintain high spikelet fertility and hence yield under stress. This study, besides emphasizing the importance of acquired tolerance, explains a high throughput phenotyping approach that significantly overcomes methodological constraints in assessing genetic variability in this important drought adaptive mechanism.

QTL Mapping for Seed Germination Response to Drought Stress in Brassica napus

Drought stress is one of the most environmental abiotic stresses affecting seed germination and crop growth. In the present study, the genetic characteristics of seed germination under drought stress in a Brassica napus double haploid population were analyzed. Five germination-related indexes, including germination percentage (GP), root length (RL), shoot length (SL), fresh weight (FW), and root-to-shoot length ratio (R/S) under control and drought stress, were calculated, and the drought stress index (DSI), including DSI-GP, DSI-RL, DSI-SL, DSI-FW, and DSI-R/S, was determined using the quantitative trait loci (QTLs) analysis based on high-density genetic linkage map. The phenotypic analysis indicated that the R/S is an effective morphological trait in the determination of drought tolerance in the seedling stage. Thirty-nine identified QTLs were observed for these traits and then integrated into 36 consensus QTLs, in which 18 QTLs were found to affect the DSI of four traits (GP, RL, SL, and R/S). Based on the co-linearity between genetic and physical maps of B. napus, 256 candidate genes were detected, and 128 genes have single-nucleotidepolymorphisms/insertion-deletion (SNP/InDel) variations between two parents, some of which were associated with the drought stress tolerance (for example, BnaC03g32780D, BnaC03g37030D, and BnaC09g27300D). The present results laid insights into drought tolerance and its genetic bases in B. napus.

Development and validation of heat-responsive candidate gene and miRNA gene based SSR markers to analysis genetic diversity in wheat for heat tolerance breeding

Being a major staple food crop of the world, wheat provides nutritional food security to the global populations. Heat stress is a major abiotic stress that adversely affects wheat production throughout the world including Indo-Gangatic Plains (IGP) where four wheat growing countries viz., India, Bangladesh, Nepal and Pakistan produce 42% of the total wheat production. Therefore, identification of heat stress responsive molecular markers is imperative to marker assisted breeding programs. Information about trait specific gene based SSRs is available but there is lack of information on SSRs from non-coding regions. In the present study, we developed 177 heat-responsive gene-based SSRs (cg-SSR) and MIR gene-based SSR (miRNA-SSR) markers from wheat genome for assessing genetic diversity analysis of thirty- six contrasting wheat genotypes for heat tolerance. Of the 177 SSR loci, 144 yielded unambiguous and repeatable amplicons, however, thirty-seven were found polymorphic among the 36 wheat genotypes. The polymorphism information content (PIC) of primers used in this study ranged from 0.03-0.73, with a mean of 0.35. Number of alleles produced per primer varied from 2 to 6, with a mean of 2.58. The UPGMA dendrogram analysis grouped all wheat genotypes into four clusters. The markers developed in this study has potential application in the MAS based breeding programs for developing heat tolerant wheat cultivars and genetic diversity analysis of wheat germplasm. Identification of noncoding region based SSRs will be fruitful for identification of trait specific wheat germplasm.

Molecular Markers Improve Abiotic Stress Tolerance in Crops: A Review

Plants endure many abiotic stresses, such as temperature (heat or frost), drought, and salt. Such factors are primary and frequent stressors that reduce agriculture crop yields. Often alterations in nutrient management and constituents, along with variations in biosynthetic capacity, ultimately reduce or halt plant growth. Genetically, stress is an environmental condition that interferes with complete genetic expression. A vast range of molecular genomic markers is available for the analysis of agricultural crops. These markers are classified into various groups based on how the markers are used: RAPD (Random amplified polymorphic DNA) markers serve to identify and screen hybrids based on salinity and drought stress tolerance, while simple sequence repeat (SSR) markers are excellent for the assessment of stress tolerance. Such markers also play an important role in the QTL (Quantitative trait loci) mapping of stress-related genes. Dehydrins for drought and saltol for salinity stresses are primitive genes which regulate responses to these conditions. Further, a focus on traits using single-gene single nucleotide polymorphisms (SNP) markers supports genetic mapping and the sequencing of stress-related traits in inbred lines. DNA markers facilitate marker-assisted breeding to enhance abiotic stress tolerance using advanced techniques and marker modification.

Genetic control of root architectural plasticity in maize

Root phenotypes regulate soil resource acquisition; however, their genetic control and phenotypic plasticity are poorly understood. We hypothesized that the responses of root architectural phenes to water deficit (stress plasticity) and different environments (environmental plasticity) are under genetic control and that these loci are distinct. Root architectural phenes were phenotyped in the field using a large maize association panel with and without water deficit stress for three seasons in Arizona and without water deficit stress for four seasons in South Africa. All root phenes were plastic and varied in their plastic response. We identified candidate genes associated with stress and environmental plasticity and candidate genes associated with phenes in well-watered conditions in South Africa and in well-watered and water-stress conditions in Arizona. Few candidate genes for plasticity overlapped with those for phenes expressed under each condition. Our results suggest that phenotypic plasticity is highly quantitative, and plasticity loci are distinct from loci that control phene expression in stress and non-stress, which poses a challenge for breeding programs. To make these loci more accessible to the wider research community, we developed a public online resource that will allow for further experimental validation towards understanding the genetic control underlying phenotypic plasticity.

Genetics of yield, abiotic stress tolerance and biofortification in wheat (Triticum aestivum L.)

A review of the available literature on genetics of yield and its component traits, tolerance to abiotic stresses and biofortification should prove useful for future research in wheat in the genomics era. The work reviewed in this article mainly covers the available information on genetics of some important quantitative traits including yield and its components, tolerance to abiotic stresses (heat, drought, salinity and pre-harvest sprouting = PHS) and biofortification (Fe/Zn and phytate contents with HarvestPlus Program) in wheat. Major emphasis is laid on the recent literature on QTL interval mapping and genome-wide association studies, giving lists of known QTL and marker-trait associations. Candidate genes for different traits and the cloned and characterized genes for yield traits along with the molecular mechanism are also described. For each trait, an account of the present status of marker-assisted selection has also been included. The details of available results have largely been presented in the form of tables; some of these tables are included as supplementary files.

Transgenic Breeding Approaches for Improving Abiotic Stress Tolerance: Recent Progress and Future Perspectives

The recent rapid climate changes and increasing global population have led to an increased incidence of abiotic stress and decreased crop productivity. Environmental stresses, such as temperature, drought, nutrient deficiency, salinity, and heavy metal stresses, are major challenges for agriculture, and they lead to a significant reduction in crop growth and productivity. Abiotic stress is a very complex phenomenon, involving a variety of physiological and biochemical changes in plant cells. Plants exposed to abiotic stress exhibit enhanced levels of ROS (reactive oxygen species), which are highly reactive and toxic and affect the biosynthesis of chlorophyll, photosynthetic capacity, and carbohydrate, protein, lipid, and antioxidant enzyme activities. Transgenic breeding offers a suitable alternative to conventional breeding to achieve plant genetic improvements. Over the last two decades, genetic engineering/transgenic breeding techniques demonstrated remarkable developments in manipulations of the genes for the induction of desired characteristics into transgenic plants. Transgenic approaches provide us with access to identify the candidate genes, miRNAs, and transcription factors (TFs) that are involved in specific plant processes, thus enabling an integrated knowledge of the molecular and physiological mechanisms influencing the plant tolerance and productivity. The accuracy and precision of this phenomenon assures great success in the future of plant improvements. Hence, transgenic breeding has proven to be a promising tool for abiotic stress improvement in crops. This review focuses on the potential and successful applications, recent progress, and future perspectives of transgenic breeding for improving abiotic stress tolerance and productivity in plants.

Photosynthesis research: a model to bridge fundamental science, translational products, and socio-economic considerations in agriculture

Despite impressive success in molecular physiological understanding of photosynthesis, and preliminary evidence on its potential for quantum shifts in agricultural productivity, the question remains of whether increased photosynthesis, without parallel fine-tuning of the associated processes, is enough. There is a distinct lack of formal socio-economic impact studies that address the critical questions of product profiling, cost-benefit analysis, environmental trade-offs, and technological and market forces in product acceptability. When a relatively well understood process gains enough traction for translational value, its broader scientific and technical gap assessment, in conjunction with its socio-economic impact assessment for success, should be a prerequisite. The successes in the upstream basic understanding of photosynthesis should be integrated with a gap analysis for downstream translational applications to impact the farmers' and customers' lifestyles and livelihoods. The purpose of this review is to assess how the laboratory, the field, and the societal demands from photosynthesis could generate a transformative product. Two crucial recommendations from the analysis of the state of knowledge and potential ways forward are (i) the formulation of integrative mega-projects, which span the multistakeholder spectrum, to ensure rapid success in harnessing the transformative power of photosynthesis; and (ii) stipulating spatiotemporal, labour, and economic criteria to stage-gate deliverables.

Root Response to Drought Stress in Rice (Oryza sativa L.)

The current unpredictable climate changes are causing frequent and severe droughts. Such circumstances emphasize the need to understand the response of plants to drought stress, especially in rice, one of the most important grain crops. Knowledge of the drought stress response components is especially important in plant roots, the major organ for the absorption of water and nutrients from the soil. Thus, this article reviews the root response to drought stress in rice. It is presented to provide readers with information of use for their own research and breeding program for tolerance to drought stress in rice.

Genetic Dissection of Grain Yield and Agronomic Traits in Maize under Optimum and Low-Nitrogen Stressed Environments

Understanding the genetic basis of maize grain yield and other traits under low-nitrogen (N) stressed environments could improve selection efficiency. In this study, five doubled haploid (DH) populations were evaluated under optimum and N-stressed conditions, during the main rainy season and off-season in Kenya and Rwanda, from 2014 to 2015. Identifying the genomic regions associated with grain yield (GY), anthesis date (AD), anthesis-silking interval (ASI), plant height (PH), ear height (EH), ear position (EPO), and leaf senescence (SEN) under optimum and N-stressed environments could facilitate the use of marker-assisted selection to develop N-use-efficient maize varieties. DH lines were genotyped with genotyping by sequencing. A total of 13, 43, 13, 25, 30, 21, and 10 QTL were identified for GY, AD ASI, PH, EH, EPO, and SEN, respectively. For GY, PH, EH, and SEN, the highest number of QTL was found under low-N environments. No common QTL between optimum and low-N stressed conditions were identified for GY and ASI. For secondary traits, there were some common QTL for optimum and low-N conditions. Most QTL conferring tolerance to N stress was on a different chromosome position under optimum conditions.

Genetic Mapping Identifies Consistent Quantitative Trait Loci for Yield Traits of Rice under Greenhouse Drought Conditions

Improving drought resistance in crops is imperative under the prevailing erratic rainfall patterns. Drought affects the growth and yield of most modern rice varieties. Recent breeding efforts aim to incorporate drought resistance traits in rice varieties that can be suitable under alternative irrigation schemes, such as in a (semi)aerobic system, as row (furrow-irrigated) rice. The identification of quantitative trait loci (QTLs) controlling grain yield, the most important trait with high selection efficiency, can lead to the identification of markers to facilitate marker-assisted breeding of drought-resistant rice. Here, we report grain yield QTLs under greenhouse drought using an F_2:3 population derived from Cocodrie (drought sensitive) × Nagina 22 (N22) (drought tolerant). Eight QTLs were identified for yield traits under drought. Grain yield QTL under drought on chromosome 1 (phenotypic variance explained (PVE) = 11.15%) co-localized with the only QTL for panicle number (PVE = 37.7%). The drought-tolerant parent N22 contributed the favorable alleles for all QTLs except qGN3.2 and qGN5.1 for grain number per panicle. Stress-responsive transcription factors, such as ethylene response factor, WD40 domain protein, zinc finger protein, and genes involved in lipid/sugar metabolism were linked to the QTLs, suggesting their possible role in drought tolerance mechanism of N22 in the background of Cocodrie, contributing to higher yield under drought.

Application of Machine Learning Algorithms in Plant Breeding: Predicting Yield From Hyperspectral Reflectance in Soybean

Recent substantial advances in high-throughput field phenotyping have provided plant breeders with affordable and efficient tools for evaluating a large number of genotypes for important agronomic traits at early growth stages. Nevertheless, the implementation of large datasets generated by high-throughput phenotyping tools such as hyperspectral reflectance in cultivar development programs is still challenging due to the essential need for intensive knowledge in computational and statistical analyses. In this study, the robustness of three common machine learning (ML) algorithms, multilayer perceptron (MLP), support vector machine (SVM), and random forest (RF), were evaluated for predicting soybean (Glycine max) seed yield using hyperspectral reflectance. For this aim, the hyperspectral reflectance data for the whole spectra ranged from 395 to 1005 nm, which were collected at the R4 and R5 growth stages on 250 soybean genotypes grown in four environments. The recursive feature elimination (RFE) approach was performed to reduce the dimensionality of the hyperspectral reflectance data and select variables with the largest importance values. The results indicated that R5 is more informative stage for measuring hyperspectral reflectance to predict seed yields. The 395 nm reflectance band was also identified as the high ranked band in predicting the soybean seed yield. By considering either full or selected variables as the input variables, the ML algorithms were evaluated individually and combined-version using the ensemble-stacking (E-S) method to predict the soybean yield. The RF algorithm had the highest performance with a value of 84% yield classification accuracy among all the individual tested algorithms. Therefore, by selecting RF as the metaClassifier for E-S method, the prediction accuracy increased to 0.93, using all variables, and 0.87, using selected variables showing the success of using E-S as one of the ensemble techniques. This study demonstrated that soybean breeders could implement E-S algorithm using either the full or selected spectra reflectance to select the high-yielding soybean genotypes, among a large number of genotypes, at early growth stages.