Genetic Mapping of the Root Mycobiota in Rice and its Role in Drought Tolerance.

BACKGROUND: Rice is the second most produced crop worldwide, but is highly susceptible to drought. Micro-organisms can potentially alleviate the effects of drought. The aim of the present study was to unravel the genetic factors involved in the rice-microbe interaction, and whether genetics play a role in rice drought tolerance. For this purpose, the composition of the root mycobiota was characterized in 296 rice accessions (Oryza sativa L. subsp. indica) under control and drought conditions. Genome wide association mapping (GWAS) resulted in the identification of ten significant (LOD > 4) single nucleotide polymorphisms (SNPs) associated with six root-associated fungi: Ceratosphaeria spp., Cladosporium spp., Boudiera spp., Chaetomium spp., and with a few fungi from the Rhizophydiales order. Four SNPs associated with fungi-mediated drought tolerance were also found. Genes located around those SNPs, such as a DEFENSIN-LIKE (DEFL) protein, EXOCYST TETHERING COMPLEX (EXO70), RAPID ALKALINIZATION FACTOR-LIKE (RALFL) protein, peroxidase and xylosyltransferase, have been shown to be involved in pathogen defense, abiotic stress responses and cell wall remodeling processes. Our study shows that rice genetics affects the recruitment of fungi, and that some fungi affect yield under drought. We identified candidate target genes for breeding to improve rice-fungal interactions and hence drought tolerance.

Biomarkers for grain yield stability in rice under drought stress.

Crop yield stability requires an attenuation of the reduction of yield losses caused by environmental stresses such as drought. Using a combination of metabolomics and high-throughput colorimetric assays, we analysed central metabolism and oxidative stress status in the flag leaf of 292 indica rice (Oryza sativa) accessions. Plants were grown in the field and were, at the reproductive stage, exposed to either well-watered or drought conditions to identify the metabolic processes associated with drought-induced grain yield loss. Photorespiration, protein degradation, and nitrogen recycling were the main processes involved in the drought-induced leaf metabolic reprogramming. Molecular markers of drought tolerance and sensitivity in terms of grain yield were identified using a multivariate model based on the values of the metabolites and enzyme activities across the population. The model highlights the central role of the ascorbate-glutathione cycle, particularly dehydroascorbate reductase, in minimizing drought-induced grain yield loss. In contrast, malondialdehyde was an accurate biomarker for grain yield loss, suggesting that drought-induced lipid peroxidation is the major constraint under these conditions. These findings highlight new breeding targets for improved rice grain yield stability under drought.

Association mapping and genetic dissection of drought-induced canopy temperature differences in rice.

Drought-stressed plants display reduced stomatal conductance, which results in increased leaf temperature by limiting transpiration. In this study, thermal imaging was used to quantify the differences in canopy temperature under drought in a rice diversity panel consisting of 293 indica accessions. The population was grown under paddy field conditions and drought stress was imposed for 2 weeks at flowering. The canopy temperature of the accessions during stress negatively correlated with grain yield (r= -0.48) and positively with plant height (r=0.56). Temperature values were used to perform a genome-wide association (GWA) analysis using a 45K single nucleotide polynmorphism (SNP) map. A quantitative trait locus (QTL) for canopy temperature under drought was detected on chromosome 3 and fine-mapped using a high-density imputed SNP map. The candidate genes underlying the QTL point towards differences in the regulation of guard cell solute intake for stomatal opening as the possible source of temperature variation. Genetic variation for the significant markers of the QTL was present only within the tall, low-yielding landraces adapted to drought-prone environments. The absence of variation in the shorter genotypes, which showed lower leaf temperature and higher grain yield, suggests that breeding for high grain yield in rice under paddy conditions has reduced genetic variation for stomatal response under drought.

Plant host and drought shape the root associated fungal microbiota in rice.

BACKGROUND AND AIM: Water is an increasingly scarce resource while some crops, such as paddy rice, require large amounts of water to maintain grain production. A better understanding of rice drought adaptation and tolerance mechanisms could help to reduce this problem. There is evidence of a possible role of root-associated fungi in drought adaptation. Here, we analyzed the endospheric fungal microbiota composition in rice and its relation to plant genotype and drought. METHODS: Fifteen rice genotypes (Oryza sativa ssp. indica) were grown in the field, under well-watered conditions or exposed to a drought period during flowering. The effect of genotype and treatment on the root fungal microbiota composition was analyzed by 18S ribosomal DNA high throughput sequencing. Grain yield was determined after plant maturation. RESULTS: There was a host genotype effect on the fungal community composition. Drought altered the composition of the root-associated fungal community and increased fungal biodiversity. The majority of OTUs identified belonged to the Pezizomycotina subphylum and 37 of these significantly correlated with a higher plant yield under drought, one of them being assigned to Arthrinium phaeospermum. CONCLUSION: This study shows that both plant genotype and drought affect the root-associated fungal community in rice and that some fungi correlate with improved drought tolerance. This work opens new opportunities for basic research on the understanding of how the host affects microbiota recruitment as well as the possible use of specific fungi to improve drought tolerance in rice.

Incorporating genome-wide association into eco-physiological simulation to identify markers for improving rice yields.

We explored the use of the eco-physiological crop model GECROS to identify markers for improved rice yield under well-watered (control) and water deficit conditions. Eight model parameters were measured from the control in one season for 267 indica genotypes. The model accounted for 58% of yield variation among genotypes under control and 40% under water deficit conditions. Using 213 randomly selected genotypes as the training set, 90 single nucleotide polymorphism (SNP) loci were identified using a genome-wide association study (GWAS), explaining 42-77% of crop model parameter variation. SNP-based parameter values estimated from the additive loci effects were fed into the model. For the training set, the SNP-based model accounted for 37% (control) and 29% (water deficit) of yield variation, less than the 78% explained by a statistical genomic prediction (GP) model for the control treatment. Both models failed in predicting yields of the 54 testing genotypes. However, compared with the GP model, the SNP-based crop model was advantageous when simulating yields under either control or water stress conditions in an independent season. Crop model sensitivity analysis ranked the SNP loci for their relative importance in accounting for yield variation, and the rank differed greatly between control and water deficit environments. Crop models have the potential to use single-environment information for predicting phenotypes under different environments.

Genome-wide association reveals novel genomic loci controlling rice grain yield and its component traits under water-deficit stress during the reproductive stage.

A diversity panel comprising of 296 indica rice genotypes was phenotyped under non-stress and water-deficit stress conditions during the reproductive stage in the 2013 and 2014 dry seasons (DSs) at IRRI, Philippines. We investigated the genotypic variability for grain yield, yield components, and related traits, and conducted genome-wide association studies (GWAS) using high-density 45K single nucleotide polymorphisms. We detected 38 loci in 2013 and 64 loci in 2014 for non-stress conditions and 69 loci in 2013 and 55 loci in 2014 for water-deficit stress. Desynchronized flowering time confounded grain yield and its components under water-deficit stress in the 2013 experiment. Statistically corrected grain yield and yield component values using days to flowering helped to detect 31 additional genetic loci for grain yield, its components, and the harvest index in 2013. There were few overlaps in the detected loci between years and treatments, and when compared with previous studies using the same panel, indicating the complexity of yield formation under stress. Nevertheless, our analyses provided important insights into the potential links between grain yield with seed set and assimilate partitioning. Our findings demonstrate the complex genetic architecture of yield formation and we propose exploring the genetic basis of less complex component traits as an alternative route for further yield enhancement.

Genetic Control of Plasticity in Root Morphology and Anatomy of Rice in Response to Water Deficit.

Elucidating the genetic control of rooting behavior under water-deficit stress is essential to breed climate-robust rice (Oryza sativa) cultivars. Using a diverse panel of 274 indica genotypes grown under control and water-deficit conditions during vegetative growth, we phenotyped 35 traits, mostly related to root morphology and anatomy, involving 45,000 root-scanning images and nearly 25,000 cross sections from the root-shoot junction. The phenotypic plasticity of these traits was quantified as the relative change in trait value under water-deficit compared with control conditions. We then carried out a genome-wide association analysis on these traits and their plasticity, using 45,608 high-quality single-nucleotide polymorphisms. One hundred four significant loci were detected for these traits under control conditions, 106 were detected under water-deficit stress, and 76 were detected for trait plasticity. We predicted 296 (control), 284 (water-deficit stress), and 233 (plasticity) a priori candidate genes within linkage disequilibrium blocks for these loci. We identified key a priori candidate genes regulating root growth and development and relevant alleles that, upon validation, can help improve rice adaptation to water-deficit stress.

Does morphological and anatomical plasticity during the vegetative stage make wheat more tolerant of water deficit stress than rice?

Water scarcity and the increasing severity of water deficit stress are major challenges to sustaining irrigated rice (Oryza sativa) production. Despite the technologies developed to reduce the water requirement, rice growth is seriously constrained under water deficit stress compared with other dryland cereals such as wheat (Triticum aestivum). We exposed rice cultivars with contrasting responses to water deficit stress and wheat cultivars well adapted to water-limited conditions to the same moisture stress during vegetative growth to unravel the whole-plant (shoot and root morphology) and organ/tissue (root anatomy) responses. Wheat cultivars followed a water-conserving strategy by reducing specific leaf area and developing thicker roots and moderate tillering. In contrast, rice 'IR64' and 'Apo' adopted a rapid water acquisition strategy through thinner roots under water deficit stress. Root diameter, stele and xylem diameter, and xylem number were more responsive and varied with different positions along the nodal root under water deficit stress in wheat, whereas they were relatively conserved in rice cultivars. Increased metaxylem diameter and lower metaxylem number near the root tips and exactly the opposite phenomena at the root-shoot junction facilitated the efficient use of available soil moisture in wheat. Tolerant rice 'Nagina 22' had an advantage in root morphological and anatomical attributes over cultivars IR64 and Apo but lacked plasticity, unlike wheat cultivars exposed to water deficit stress. The key traits determining the adaptation of wheat to dryland conditions have been summarized and discussed.

Development and characterization of microsatellite markers for Morus spp. and assessment of their transferability to other closely related species.

BACKGROUND: Adoption of genomics based breeding has emerged as a promising approach for achieving comprehensive crop improvement. Such an approach is more relevant in the case of perennial species like mulberry. However, unavailability of genomic resources of co-dominant marker systems has been the major constraint for adopting molecular breeding to achieve genetic enhancement of Mulberry. The goal of this study was to develop and characterize a large number of locus specific genic and genomic SSR markers which can be effectively used for molecular characterization of mulberry species/genotypes. RESULT: We analyzed a total of 3485 DNA sequences including genomic and expressed sequences (ESTs) of mulberry (Morus alba L.) genome. We identified 358 sequences to develop appropriate microsatellite primer pairs representing 222 genomic and 136 EST regions. Primers amplifying locus specific regions of Dudia white (a genotype of Morus alba L), were identified and 137 genomic and 51 genic SSR markers were standardized. A two pronged strategy was adopted to assess the applicability of these SSR markers using mulberry species and genotypes along with a few closely related species belonging to the family Moraceae viz., Ficus, Fig and Jackfruit. While 100% of these markers amplified specific loci on the mulberry genome, 79% were transferable to other related species indicating the robustness of these markers and the potential they hold in analyzing the molecular and genetic diversity among mulberry germplasm as well as other related species. The inherent ability of these markers in detecting heterozygosity combined with a high average polymorphic information content (PIC) of 0.559 ranging between 0.076 and 0.943 clearly demonstrates their potential as genomic resources in diversity analysis. The dissimilarity coefficient determined based on Neighbor joining method, revealed that the markers were successful in segregating the mulberry species, genotypes and other related species into distinct clusters. CONCLUSION: We report a total of 188 genomic and genic SSR markers in Morus alba L. A large proportion of these markers (164) were polymorphic both among mulberry species and genotypes. A substantial number of these markers (149) were also transferable to other related species like Ficus, Fig and Jackfruit. The extent of polymorphism revealed and the ability to detect heterozygosity among the cross pollinated mulberry species and genotypes render these markers an invaluable genomic resource that can be utilized in assessing molecular diversity as well as in QTL mapping and subsequently mulberry crop improvement through MAS.