Drought-adaptive Traits Research Articles

RiceMetaSys: Drought-miR, a one-stop solution for drought responsive miRNAs-mRNA module in rice.

MicroRNAs are key players involved in stress responses in plants and reports are available on the role of miRNAs in drought stress response in rice. This work reports the development of a database, RiceMetaSys: Drought-miR, based on the meta-analysis of publicly available sRNA datasets. From 28 drought stress-specific sRNA datasets, we identified 216 drought-responsive miRNAs (DRMs). The major features of the database include genotype-, tissue- and miRNA ID-specific search options and comparison of genotypes to identify common miRNAs. Co-localization of the DRMs with the known quantitative trait loci (QTLs), i.e., meta-QTL regions governing drought tolerance in rice pertaining to different drought adaptive traits, narrowed down this to 37 promising DRMs. To identify the high confidence target genes of DRMs under drought stress, degradome datasets and web resource on drought-responsive genes (RiceMetaSys: DRG) were used. Out of the 216 unique DRMs, only 193 had targets with high stringent parameters. Out of the 1081 target genes identified by Degradome datasets, 730 showed differential expression under drought stress in at least one accession. To retrieve complete information on the target genes, the database has been linked with RiceMetaSys: DRG. Further, we updated the RiceMetaSys: DRGv1 developed earlier with the addition of DRGs identified from RNA-seq datasets from five rice genotypes. We also identified 759 putative novel miRNAs and their target genes employing stringent criteria. Novel miRNA search has all the search options of known miRNAs and additionally, it gives information on their in silico validation features. Simple sequence repeat markers for both the miRNAs and their target genes have also been designed and made available in the database. Network analysis of the target genes identified 60 hub genes which primarily act through abscisic acid pathway and jasmonic acid pathway. Co-localization of the hub genes with the meta-QTL regions governing drought tolerance narrowed down this to 16 most promising DRGs. Database URL: http://14.139.229.201/RiceMetaSys_miRNA Updated database of RiceMetaSys URL: http://14.139.229.201/RiceMetaSysA/Drought/.

The influence of plant traits on soil microbial communities varies between arid and mesic grasslands

Abstract Background and aims Both soil properties and plant traits shape the diversity, composition and functions of plant-associated soil microbial communities. However, the relative influence of these factors is poorly understood, as are interactive effects between factors and the degree to which their influence varies among climate zones. Methods To address this gap, we compared the diversity and composition of soil microbial communities associated with co-occurring C3 and C4 grasses from arid and mesic environments, and plant traits influencing them. Results Climate emerged as the main determinant of plant traits and microbial community properties. Within each climatic region, above- and below-ground traits and soil properties differentially affected microbial community composition, and their relative influence varied among communities. In both mesic and arid environments aboveground traits related to quantity and quality of leaf litter (e.g., specific leaf area, leaf C content) and nutrient availability were the most influential variables for community composition. However, in arid regions, belowground traits (i.e., root tissue density and specific root area) significantly contributed to structure the eukaryotic community, supporting the role of roots as important driver of eukaryotic differentiation in constrained environments. Further, the presence of C4 plants in the arid region resulted in higher relative abundance of ciliate protists and higher recruitment of potentially beneficial microbial community members from green algae mediated by drought adaptation traits (e.g. decreased abundance of fine roots). Conclusions Overall, our study revealed a differential response of microbial communities to environmental conditions, suggesting that soil microbial community composition is influenced by trade-offs between host adaptive traits across distinct climatic regions.

Characterizing stay-green in barley across diverse environments: unveiling novel haplotypes

Key messageThere is variation in stay-green within barley breeding germplasm, influenced by multiple haplotypes and environmental conditions. The positive genetic correlation between stay-green and yield across multiple environments highlights the potential as a future breeding target.Barley is considered one of the most naturally resilient crops making it an excellent candidate to dissect the genetics of drought adaptive component traits. Stay-green, is thought to contribute to drought adaptation, in which the photosynthetic machinery is maintained for a longer period post-anthesis increasing the photosynthetic duration of the plant. In other cereal crops, including wheat, stay-green has been linked to increased yield under water-limited conditions. Utilizing a panel of diverse barley breeding lines from a commercial breeding program we aimed to characterize stay-green in four environments across two years. Spatiotemporal modeling was used to accurately model senescence patterns from flowering to maturity characterizing the variation for stay-green in barley for the first time. Environmental effects were identified, and multi-environment trait analysis was performed for stay-green characteristics during grain filling. A consistently positive genetic correlation was found between yield and stay-green. Twenty-two chromosomal regions with large effect haplotypes were identified across and within environment types, with ten being identified in multiple environments. In silico stacking of multiple desirable haplotypes showed an opportunity to improve the stay-green phenotype through targeted breeding. This study is the first of its kind to model barley stay-green in a large breeding panel and has detected novel, stable and environment specific haplotypes. This provides a platform for breeders to develop Australian barley with custom senescence profiles for improved drought adaptation.

Multi-trait selection for agronomic performance and drought tolerance among durum wheat genotypes evaluated under rainfed and irrigated environments

Summary Durum wheat (Triticum turgidum L. subsp. durum) is a major crop in the Mediterranean region, widely grown for its nutritional value and economic importance. Durum wheat breeding can contribute to global food security through the introduction of new cultivars exhibiting drought tolerance and higher yield potential in the Mediterranean environments. In this study, 25 durum wheat genotypes (23 elite breeding lines and two national checks) were evaluated for five drought-adaptive traits (days to heading, days to maturity, plant height, 1000-kernel weight and grain yield) and eight drought tolerance indices including stress tolerance index (STI), geometric mean productivity (GMP), mean productivity (MP), stress susceptibility index, tolerance index, yield index, yield stability index and drought response index under rainfed and irrigated conditions during three cropping seasons (2019–2022). Multi-trait stability index (MTSI) technique was applied to select genotypes with higher grain yield, 1000-kernel weight, plant stature and early flowering and maturity simultaneously; as well as for higher drought tolerance in each and across years. A heat map correlation analysis and principal component analysis were applied to study the relationships among drought tolerance indices and the pattern of variation among genotypes studied. Factor analysis was applied for identification of traits that contributed most in stability analyses. Significant and positive correlations were observed among the three drought tolerance indices of STI, GMP and MP with mean yields under both rainfed and irrigated conditions in each and across years, suggest the efficiency of these indices as selection criteria for improved drought tolerance and yield performance in durum wheat. The genotypes ranked based on MTSI varied from environment to environment, showing the impact of environment on genotypes performance, but several of the best performing lines were common across environments. According to MTSI for agronomic traits, the breeding lines G20, G6, G25 and G18 exhibited highest performance and trait stability across environmental conditions, and the selected genotypes had strength towards grain yield, 1000-kernel weight and earliness. Using the MTSI, breeding lines G20, G5, G16 and G7 were selected as drought tolerant genotypes with high mean performance. Breeding line G20 from ICARDA germplasm showed highest trait stability performance and drought tolerance across environments. The MTSI was a useful tool for selecting genotypes based on their agronomic performance and drought tolerance that could be exploited for identification and selection of elite genotypes with desired multi-traits. Based on the results, breeding lines G20 and G6 should be recommended for short-term release programme and/ or utilized in durum wheat population improvement programme for agronomic performance and drought tolerance traits that tolerate climate variations.

Identification of Promising Three-Way Hybrids of Pearl Millet for Drought-Prone Environments of North-Western India

Stable, drought-tolerant, and high-yielding dual-purpose hybrids are needed for cultivation in the drought-prone areas of India. Working towards this, this study was conducted to assess the associations between grain yield and its component traits and the relationships among genotypes to select the most promising hybrids based on multiple traits. In the present investigation, thirty newly developed three-way hybrids (TWHs), along with four popular commercial single-cross hybrids and two open pollinated varieties (OPVs) were evaluated at three sites in the drought-prone ecology of India during the rainy season of 2021–2022. A principal component analysis (PCA) revealed that the first three component axes (PC) were significant, with eigenvalues more than one, and together contributed to 74.10% of the total variance. A hierarchical cluster analysis based on the Euclidean distance between hybrids suggested the existence of three clusters. Cluster III (C-III) had hybrids with maximum grain yield, dry fodder yield, and important component traits such as panicle harvest index and grain harvest index that are required for adaptation to drought-prone environments. A genotype by yield × trait (GYT) biplot and a superiority index (SI) were generated to identify the best hybrids with high grain yield and other component traits. These results were used to identify TWHs, namely TH-114, TH-138, TH-49, TH-67, and TH-79, with more than 30% standard heterosis and stable performance coupled with better drought-adaptive traits.

A multi-reference parent nested-association mapping population to dissect the genetics of quantitative traits in durum wheat

Durum wheat (Triticum durum Desf.) breeding programs face many challenges surrounding the development of stable varieties with high quality and yield. Therefore, researchers and breeders are focused on deciphering the genetic architecture of biotic and abiotic traits with the aim of pyramiding desirable traits. These efforts require access to diverse genetic resources, including wild relatives, germplasm collections and mapping populations. Advances in accelerated generation technologies have enabled the rapid development of mapping populations with significant genetic diversity. Here, we describe the development of a durum Nested Association Mapping (dNAM) population, which represents a valuable genetic resource for mapping the effects of different alleles on trait performance. We created this population to understand the quantitative nature of drought-adaptive traits in durum wheat. We developed 920 F6 lines in only 18 months using speed breeding technology, including the F4 generation in the field. Large variation in above- and below-ground traits was observed, which could be harnessed using genetic mapping and breeding approaches. We genotyped the population using 13,393 DArTseq markers. Quality control resulted in 6,785 high-quality polymorphic markers used for structure analysis, linkage disequilibrium decay, and marker-trait association analyses. To demonstrate the effectiveness of dNAM as a resource for elucidating the genetic control of quantitative traits, we took a genome-wide mapping approach using the FarmCPU method for plant height and days to flowering. These results highlight the power of using dNAM as a tool to dissect the genetics of durum wheat traits, supporting the development of varieties with improved adaptation and yield.

Infrared Thermal Imaging and Morpho-Physiological Indices Used for Wheat Genotypes Screening under Drought and Heat Stress

Bread wheat, one of the largest broadacre crops, often experiences various environmental stresses during critical growth stages. Terminal drought and heat stress are the primary causes of wheat yield reduction worldwide. This study aimed to determine the drought and heat stress tolerance level of a group of 46 diverse wheat genotypes procured from the Australian Grains Gene Bank, Horsham, VIC Australia. Two separate drought stress (DS) and heat stress (HS) pot experiments were conducted in separate growth chambers. Ten days after complete anthesis, drought (40 ± 3% field capacity for 14 days) and heat stress (36/22 °C for three consecutive days) were induced. A significant genotype × environment interaction was observed and explained by various morpho-physiological traits, including rapid, non-destructive infrared thermal imaging for computational water stress indices. Except for a spike length in DS and harvest index in HS, the analysis of variance showed significant differences for all the recorded traits. Results showed grains per spike, grains weight per spike, spike fertility, delayed flag leaf senescence, and cooler canopy temperature were positively associated with grain yield under DS and HS. The flag leaf senescence and chlorophyll fluorescence were used to measure each genotype's stay-green phenotype and photosystem II activity after DS and HS. This study identified the top ten best and five lowest-performing genotypes from drought and heat stress experiments based on their overall performance. Results suggest that if heat or drought adaptive traits are brought together in a single genotype, grain yield can be improved further, particularly in a rainfed cropping environment.

Canopy spectral reflectance indices correlate with yield traits variability in bread wheat genotypes under drought stress.

Drought stress is a major issue impacting wheat growth and yield worldwide, and it is getting worse as the world's climate changes. Thus, selection for drought-adaptive traits and drought-tolerant genotypes are essential components in wheat breeding programs. The goal of this study was to explore how spectral reflectance indices (SRIs) and yield traits in wheat genotypes changed in irrigated and water-limited environments. In two wheat-growing seasons, we evaluated 56 preselected wheat genotypes for SRIs, stay green (SG), canopy temperature depression (CTD), biological yield (BY), grain yield (GY), and yield contributing traits under control and drought stress, and the SRIs and yield traits exhibited higher heritability (H2) across the growing years. Diverse SRIs associated with SG, pigment content, hydration status, and aboveground biomass demonstrated a consistent response to drought and a strong association with GY. Under drought stress, GY had stronger phenotypic correlations with SG, CTD, and yield components than in control conditions. Three primary clusters emerged from the hierarchical cluster analysis, with cluster I (15 genotypes) showing minimal changes in SRIs and yield traits, indicating a relatively higher level of drought tolerance than clusters II (26 genotypes) and III (15 genotypes). The genotypes were appropriately assigned to distinct clusters, and linear discriminant analysis (LDA) demonstrated that the clusters differed significantly. It was found that the top five components explained 73% of the variation in traits in the principal component analysis, and that vegetation and water-based indices, as well as yield traits, were the most important factors in explaining genotypic drought tolerance variation. Based on the current study's findings, it can be concluded that proximal canopy reflectance sensing could be used to screen wheat genotypes for drought tolerance in water-starved environments.

Leaf Count Aided Novel Framework for Rice (Oryza sativa L.) Genotypes Discrimination in Phenomics: Leveraging Computer Vision and Deep Learning Applications.

Drought is a detrimental factor to gaining higher yields in rice (Oryza sativa L.), especially amid the rising occurrence of drought across the globe. To combat this situation, it is essential to develop novel drought-resilient varieties. Therefore, screening of drought-adaptive genotypes is required with high precision and high throughput. In contemporary emerging science, high throughput plant phenotyping (HTPP) is a crucial technology that attempts to break the bottleneck of traditional phenotyping. In traditional phenotyping, screening significant genotypes is a tedious task and prone to human error while measuring various plant traits. In contrast, owing to the potential advantage of HTPP over traditional phenotyping, image-based traits, also known as i-traits, were used in our study to discriminate 110 genotypes grown for genome-wide association study experiments under controlled (well-watered), and drought-stress (limited water) conditions, under a phenomics experiment in a controlled environment with RGB images. Our proposed framework non-destructively estimated drought-adaptive plant traits from the images, such as the number of leaves, convex hull, plant–aspect ratio (plant spread), and similarly associated geometrical and morphological traits for analyzing and discriminating genotypes. The results showed that a single trait, the number of leaves, can also be used for discriminating genotypes. This critical drought-adaptive trait was associated with plant size, architecture, and biomass. In this work, the number of leaves and other characteristics were estimated non-destructively from top view images of the rice plant for each genotype. The estimation of the number of leaves for each rice plant was conducted with the deep learning model, YOLO (You Only Look Once). The leaves were counted by detecting corresponding visible leaf tips in the rice plant. The detection accuracy was 86–92% for dense to moderate spread large plants, and 98% for sparse spread small plants. With this framework, the susceptible genotypes (MTU1010, PUSA-1121 and similar genotypes) and drought-resistant genotypes (Heera, Anjali, Dular and similar genotypes) were grouped in the core set with a respective group of drought-susceptible and drought-tolerant genotypes based on the number of leaves, and the leaves’ emergence during the peak drought-stress period. Moreover, it was found that the number of leaves was significantly associated with other pertinent morphological, physiological and geometrical traits. Other geometrical traits were measured from the RGB images with the help of computer vision.

Simulating drought tolerance of peanut varieties by maintaining photosynthesis under water deficit

Over two-third of global peanuts are grown mainly in seasonally rainfed regions across arid and semi-arid zones where drought is a major yield limiting factor. Breeders are targeting drought adaptive traits by selecting high yielding genotypes under water-limited environments. Recently, several peanut varieties have been developed that exhibit drought tolerant characteristics. Crop models can be used to simulate the impact of these traits for different environments. The overall goal of this study was to develop an approach to simulate drought tolerant traits using the CROPGRO-Peanut model and assess the long-term yield response to these desired traits. Four peanut varieties and one advanced breeding line variety with varying degrees of drought tolerance response were grown under both field and rainout shelter conditions in 2019 and 2020. The trait of maintaining photosynthesis under water deficit was observed in the rainout shelter experiments and incorporated into the crop model as a new drought tolerance cultivar coefficient. The evaluation results with independent data showed that the modified model simulated peanut growth and yield under water-limited conditions reasonably well. The rainfed yield, seasonal evapotranspiration (ET), and grain water use efficiency (WUE) were simulated for both drought tolerant and baseline peanut varieties at two representative sites using weather data from 1998 to 2020. The drought tolerant mechanism of maintaining photosynthesis under water deficit was shown to be an advantageous trait for peanut varieties, which produced higher simulated rainfed yield with enhanced seasonal ET and grain WUE, especially for dry seasons. The simulated photosynthesis and yield were sensitive to values of the drought tolerant factor over an expected range of values. Further research is needed on other potential drought tolerant mechanisms, such as maintaining nitrogen fixation, pod harvest index and leaf growth under drought.

Characterization of 'QTL-hotspot' introgression lines reveals physiological mechanisms and candidate genes associated with drought adaptation in chickpea.

'QTL-hotspot' is a genomic region on linkage group 04 (CaLG04) in chickpea (Cicer arietinum) that harbours major-effect quantitative trait loci (QTLs) for multiple drought-adaptive traits, and it therefore represents a promising target for improving drought adaptation. To investigate the mechanisms underpinning the positive effects of 'QTL-hotspot' on seed yield under drought, we introgressed this region from the ICC 4958 genotype into five elite chickpea cultivars. The resulting introgression lines (ILs) and their parents were evaluated in multi-location field trials and semi-controlled conditions. The results showed that the 'QTL-hotspot' region improved seed yield under rainfed conditions by increasing seed weight, reducing the time to flowering, regulating traits related to canopy growth and early vigour, and enhancing transpiration efficiency. Whole-genome sequencing data analysis of the ILs and parents revealed four genes underlying the 'QTL-hotspot' region associated with drought adaptation. We validated diagnostic KASP markers closely linked to these genes using the ILs and their parents for future deployment in chickpea breeding programs. The CaTIFY4b-H2 haplotype of a potential candidate gene CaTIFY4b was identified as the superior haplotype for 100-seed weight. The candidate genes and superior haplotypes identified in this study have the potential to serve as direct targets for genetic manipulation and selection for chickpea improvement.

Pyramiding of drought adaptive traits and development of doubled haploids in the traits pyramided rice (Oryza sativa L.)

Pyramiding of drought adaptive traits and development of doubled haploids in the traits pyramided rice (Oryza sativa L.)

Provenance Differences in Water-Use Efficiency Among Sessile Oak Populations Grown in a Mesic Common Garden

ContextAs a widespread species, sessile oak (Quercus petraea) populations occupy a wide range of ecological conditions, with large gradients of soil water availability. Drought acclimation involves a plastic increase in water-use efficiency (WUE), a trait that is easily measured using the carbon isotope composition (δ13C). However, the question remains whether WUE is an adaptive trait that impacts the fitness of trees in natural environments.Objectives and MethodsTo investigate whether WUE was a drought-adaptive trait, we studied a sample of 600 trees originating from 16 provenances, grown for 21 years in a common garden. Intrinsic WUE (WUEi), estimated from tree ring δ13C, was compared among and within populations for three climatically contrasted years. The adaptive character of WUEi was evaluated by relating population mean WUEi, as well as its plasticity to drought, to the pedoclimatic conditions of their provenance sites. The contribution of WUEi to tree and population fitness was finally assessed from the relationship between WUEi and tree radial growth (GI).ResultsSignificant differences in WUEi were found among populations but a much larger variability was observed within than among populations. The population WUEi of the juvenile oak trees growing in the relatively mesic conditions of the common garden showed no relationship with a modeled water deficit index for the provenance sites. However, a higher population WUEi plasticity to severe drought was related to a higher proportion of silt and carbon and a lower proportion of sand in the soil of the provenance sites. In response to severe drought, populations with a higher increase in WUEi showed a lower decrease in GI. Populations with lower GI reduction were from sites with higher vapor pressure deficit in May–July (VPD). For the wet year only, populations with a higher WUEi also had a higher GI.ConclusionThe correlations observed at the common garden site between (i) population means of WUEi plasticity to drought and soil texture of the provenance sites, and (ii) GI plasticity to drought and VPD, suggested a local adaptation of sessile oak.

Wheat Production in Drought-Prone Agro-Ecologies in Ethiopia: Diagnostic Assessment of Farmers’ Practices and Sustainable Coping Mechanisms and the Role of Improved Cultivars

Wheat (Triticum aestivum L.) is traditionally cultivated under drought-affected and low-input agro-ecologies in sub-Saharan Africa, including Ethiopia. Wheat productivity in these agro-systems is considerably low (<2.4 t/ha) due to climate change-induced drought and heat stress, a lack of modern production technologies, including climate-smart varieties, and an array of biotic and abiotic factors. The objective of this study was to determine the potential of wheat production in drought-prone agro-ecologies and to assess farmers’ practices and sustainable coping mechanisms and the role of improved cultivars in Ethiopia. A participatory rural appraisal (PRA) study was conducted involving 170 randomly selected wheat farmers in the drier areas of Arsi Zone of the Oromia Regional State. Results showed that wheat and tef (Eragrostis tef Zucc.) and barley (Hordeum vulgare L.) were the most widely grown cereal crops in the study areas as the primary food source and cash income. Yield losses varying from 63.1 to 73.8% were reported by farmers due to drought stress occurring mainly during grain filling stage. The majority of the respondent farmers (>50%) planted wheat in early July using the broadcasting method. Their land was of medium fertility, and the application of inorganic fertilizer was suboptimal. Due to crop failures by intense drought conditions in the study areas, above 50% of the respondent farmers had not expressed coping strategies against drought stress except resorting to government food aid. However, about 22% of the respondent farmers reported improved agronomic practices, such as the cultivation of early maturing wheat varieties and soil and water conservation methods as sustainable solutions to mitigate against drought. Therefore, current and future wheat breeding in Ethiopia should target drought and heat stress tolerance and adaptive crop traits as ideal coping strategies under low input agriculture systems for sustainable wheat production and productivity.

Breeding Drought-Tolerant Pearl Millet Using Conventional and Genomic Approaches: Achievements and Prospects.

Pearl millet [Pennisetum glaucum (L.) R. Br.] is a C4 crop cultivated for its grain and stover in crop-livestock-based rain-fed farming systems of tropics and subtropics in the Indian subcontinent and sub-Saharan Africa. The intensity of drought is predicted to further exacerbate because of looming climate change, necessitating greater focus on pearl millet breeding for drought tolerance. The nature of drought in different target populations of pearl millet-growing environments (TPEs) is highly variable in its timing, intensity, and duration. Pearl millet response to drought in various growth stages has been studied comprehensively. Dissection of drought tolerance physiology and phenology has helped in understanding the yield formation process under drought conditions. The overall understanding of TPEs and differential sensitivity of various growth stages to water stress helped to identify target traits for manipulation through breeding for drought tolerance. Recent advancement in high-throughput phenotyping platforms has made it more realistic to screen large populations/germplasm for drought-adaptive traits. The role of adapted germplasm has been emphasized for drought breeding, as the measured performance under drought stress is largely an outcome of adaptation to stress environments. Hybridization of adapted landraces with selected elite genetic material has been stated to amalgamate adaptation and productivity. Substantial progress has been made in the development of genomic resources that have been used to explore genetic diversity, linkage mapping (QTLs), marker-trait association (MTA), and genomic selection (GS) in pearl millet. High-throughput genotyping (HTPG) platforms are now available at a low cost, offering enormous opportunities to apply markers assisted selection (MAS) in conventional breeding programs targeting drought tolerance. Next-generation sequencing (NGS) technology, micro-environmental modeling, and pearl millet whole genome re-sequence information covering circa 1,000 wild and cultivated accessions have helped to greater understand germplasm, genomes, candidate genes, and markers. Their application in molecular breeding would lead to the development of high-yielding and drought-tolerant pearl millet cultivars. This review examines how the strategic use of genetic resources, modern genomics, molecular biology, and shuttle breeding can further enhance the development and delivery of drought-tolerant cultivars.

Genome Wide Association Study Uncovers the QTLome for Osmotic Adjustment and Related Drought Adaptive Traits in Durum Wheat.

Osmotic adjustment (OA) is a major component of drought resistance in crops. The genetic basis of OA in wheat and other crops remains largely unknown. In this study, 248 field-grown durum wheat elite accessions grown under well-watered conditions, underwent a progressively severe drought treatment started at heading. Leaf samples were collected at heading and 17 days later. The following traits were considered: flowering time (FT), leaf relative water content (RWC), osmotic potential (ψs), OA, chlorophyll content (SPAD), and leaf rolling (LR). The high variability (3.89-fold) in OA among drought-stressed accessions resulted in high repeatability of the trait (h2 = 72.3%). Notably, a high positive correlation (r = 0.78) between OA and RWC was found under severe drought conditions. A genome-wide association study (GWAS) revealed 15 significant QTLs (Quantitative Trait Loci) for OA (global R2 = 63.6%), as well as eight major QTL hotspots/clusters on chromosome arms 1BL, 2BL, 4AL, 5AL, 6AL, 6BL, and 7BS, where a higher OA capacity was positively associated with RWC and/or SPAD, and negatively with LR, indicating a beneficial effect of OA on the water status of the plant. The comparative analysis with the results of 15 previous field trials conducted under varying water regimes showed concurrent effects of five OA QTL cluster hotspots on normalized difference vegetation index (NDVI), thousand-kernel weight (TKW), and/or grain yield (GY). Gene content analysis of the cluster regions revealed the presence of several candidate genes, including bidirectional sugar transporter SWEET, rhomboid-like protein, and S-adenosyl-L-methionine-dependent methyltransferases superfamily protein, as well as DREB1. Our results support OA as a valuable proxy for marker-assisted selection (MAS) aimed at enhancing drought resistance in wheat.

Role of Water Soluble Carbohydrates in Improving Drought Stress Tolerance in Wheat: An Overview

Abiotic factors such as drought and heat stress impairs photosynthetic assimilates, shortening the carbon supply to the developing grains leads to yield loss. Under water stress, stem water-soluble carbohydrates (WSCs) mainly fructans, play an important role in buffering yield during the grain filling period in wheat. The stem WSCs may contribute up to 20% of the total dry weight of grain under irrigated conditions and upto 70% of grain dry matter under drought stress. Additionally, it maintains physiological balance under water-stressed conditions by acting as signalling molecules to various phytochemicals and hormones. Therefore, this drought adaptive trait can be a potential breeding target for sustainable wheat production, especially for water limiting conditions. Despite the proven contribution of stem WSCs to water-stress tolerance in wheat and compensating grain yield, a comprehensive review on this trait is still missing in the literature. With this review, efforts are made to compile the available information on the physiological, genetic and molecular aspects of accumulation and remobilisation of stem WSCs to bring more attention of plant scientists to this trait. Furthermore, effective molecular marker systems such as KASP to target stable loci identified using GWAS, QTL or meta-QTL studies may bring precision to the selection and accelerate the WSCs based wheat breeding program.

EFFECT OF DROUGHT STRESS ON WHEAT AND DROUGHT BREEDING STATUS FOR IT IN NEPAL WITH THE WAY FORWARD: A REVIEW

Wheat is the third most important crop in Nepal that is grown in a dominant rice wheat cropping pattern. The productivity of wheat is at a standstill for the past decade primarily due to abiotic stress like drought and high temperature. Changing climate pattern and high vulnerability of Southeast Asian countries in the future demands extensive work under plant breeding to cope with the challenges. Wheat requires about 266.8-500mm of water for normal attainable yield, but prolonged drought has a serious effect on photosynthesis as it hampers the carbondioxide assimilation rate. It also has a pronounced effect in the reproductive and grain filling period of the wheat. This results in the reduction of yield, and this is expected to increase in the future because of climate change. Varieties like Gautam and Vijay have been reported to show positive drought adaptive traits. Vast resources of biodiversity and landraces have been underutilized in Nepal which can be useful when coupled with advanced biotechnological tools to produce drought adaptive crop.

Genetic resources for enhancing drought tolerance from a mini-core collection of spring bread wheat (Triticum aestivum L.)

An enhanced level of drought tolerance in wheat (Triticum spp.) may be reached through combining agronomic and physiological traits associated with grain yield under drought conditions. We aimed to explore valuable diversity for the drought tolerance, existed in the core collection of Iranian spring bread wheat landraces. A number of 206 spring bread wheat accessions along with the check cultivar were assessed for grain yield, drought-adaptive traits, and estimated drought tolerance criteria during 2016-17 and 2017-18 growing seasons. Analysis of data using the best linear unbiased predictions (BLUPs) approach revealed that the genotype x environment (GE) interactions accounted for the highest variation in grain yield (36.23%) followed by 1000-kernel weight (35.39%), heading date (21.4%), days to maturity (16.38%), and plant height (5.83%). Using the hierarchical cluster analysis and developed pattern heat map based on the values for the agronomic traits and drought resistance indices, the accessions clustered into nine groups of different sets of agronomic and drought tolerance characteristics. Several accessions with high yield potential, early heading, optimal plant stature and high drought tolerance groups were identified. Three drought selection criteria of stress tolerance index (STI), geometric mean productivity (GMP) and mean productivity (MP) were more effective in identifying accessions producing higher yield under both drought and irrigated conditions. The superior accessions identified in this study may be explored further for breeding new wheat cultivars with enhanced level of drought tolerance.

Genome-Wide Association Mapping for Heat and Drought Adaptive Traits in Pea.

Heat and drought, individually or in combination, limit pea productivity. Fortunately, substantial genetic diversity exists in pea germplasm for traits related to abiotic stress resistance. Understanding the genetic basis of resistance could accelerate the development of stress-adaptive cultivars. We conducted a genome-wide association study (GWAS) in pea on six stress-adaptive traits with the aim to detect the genetic regions controlling these traits. One hundred and thirty-five genetically diverse pea accessions were phenotyped in field studies across three or five environments under stress and control conditions. To determine marker trait associations (MTAs), a total of 16,877 valuable single nucleotide polymorphisms (SNPs) were used in association analysis. Association mapping detected 15 MTAs that were significantly (p ≤ 0.0005) associated with the six stress-adaptive traits averaged across all environments and consistent in multiple individual environments. The identified MTAs were four for lamina wax, three for petiole wax, three for stem thickness, two for the flowering duration, one for the normalized difference vegetation index (NDVI), and two for the normalized pigment and chlorophyll index (NPCI). Sixteen candidate genes were identified within a 15 kb distance from either side of the markers. The detected MTAs and candidate genes have prospective use towards selecting stress-hardy pea cultivars in marker-assisted selection.