Identification of quantitative trait loci for ABA sensitivity at seed germination and seedling stages in rice

Genome-wide mapping of DNase I hypersensitive sites revealed differential chromatin accessibility and regulatory DNA elements under drought stress in rice cultivars

Drought stress (DS) is one of the major constraints limiting yield in crop plants including rice. Gene regulation under DS is largely governed by accessibility of the transcription factors (TFs) to their cognate cis-regulatory elements (CREs). In this study, we used DNase I hypersensitive assays followed by sequencing to identify the accessible chromatin regions under DS in a drought-sensitive (IR64) and a drought-tolerant (N22) rice cultivar. Our results indicated that DNase I hypersensitive sites (DHSs) were highly enriched at transcription start sites (TSSs) and numerous DHSs were detected in the promoter regions. DHSs were concurrent with epigenetic marks and the genes harboring DHSs in their TSS and promoter regions were highly expressed. In addition, DS induced changes in DHSs (∆DHSs) in TSS and promoter regions were positively correlated with upregulation of several genes involved in drought/abiotic stress response, those encoding TFs and located within drought-associated quantitative trait loci, much preferentially in the drought-tolerant cultivar. The CREs representing the binding sites of TFs involved in DS response were detected within the ∆DHSs, suggesting differential accessibility of TFs to their cognate sites under DS in different rice cultivars, which may be further deployed for enhancing drought tolerance in rice.

Meta-Analysis of Quantitative Traits Loci (QTL) Identified in Drought Response in Rice (Oryza sativa L.)

Rice is an important grain that is the staple food for most of the world's population. Drought is one of the major stresses that negatively affects rice yield. The nature of drought tolerance in rice is complex as it is determined by various components and has low heritability. Therefore, to ensure success in breeding programs for drought tolerant rice, QTLs (quantitative trait loci) of interest must be stable in a variety of plant genotypes and environments. This study identified stable QTLs in rice chromosomes in a variety of backgrounds and environments and conducted a meta-QTL analysis of stable QTLs that have been reported by previous research for use in breeding programs. A total of 653 QTLs for drought tolerance in rice from 27 genetic maps were recorded for analysis. The QTLs recorded were related to 13 traits in rice that respond to drought. Through the use of BioMercartor V4.2, a consensus map containing QTLs and molecular markers were generated using 27 genetic maps that were extracted from the previous 20 studies and meta-QTL analysis was conducted on the consensus map. A total of 70 MQTLs were identified and a total of 453 QTLs were mapped into the meta-QTL areas. Five meta-QTLs from chromosome 1 (MQTL 1.5 and MQTL 1.6), chromosome 2 (MQTL2.1 and MQTL 2.2) and chromosome 3 (MQTL 3.1) were selected for functional annotation as these regions have high number of QTLs and include many traits in rice that respond to drought. A number of genes in MQTL1.5 (268 genes), MQTL1.6 (640 genes), MQTL 2.1 (319 genes), MQTL 2.2 (19 genes) and MQTL 3.1 (787 genes) were annotated through Blast2GO. Few major proteins that respond to drought stress were identified in the meta-QTL areas which are Abscisic Acid-Insensitive Protein 5 (ABI5), the G-box binding factor 4 (GBF4), protein kinase PINOID (PID), histidine kinase 2 (AHK2), protein related to autophagy 18A (ATG18A), mitochondrial transcription termination factor (MTERF), aquaporin PIP 1-2, protein detoxification 48 (DTX48) and inositol-tetrakisphosphate 1-kinase 2 (ITPK2). These proteins are regulatory proteins involved in the regulation of signal transduction and gene expression that respond to drought stress. The meta-QTLs derived from this study and the genes that have been identified can be used effectively in molecular breeding and in genetic engineering for drought resistance/tolerance in rice.

Leaf morphology, rather than plant water status, underlies genetic variation of rice leaf rolling under drought

Soil drying causes leaf rolling in rice, but the relationship between leaf rolling and drought tolerance has historically confounded selection of drought-tolerant genotypes. In this study on tropical japonica and aus diversity panels (170-220 genotypes), the degree of leaf rolling under drought was more affected by leaf morphology than by stomatal conductance, leaf water status, or maintenance of shoot biomass and grain yield. A range of canopy temperature and leaf rolling (measured as change in normalized difference vegetation index [ΔNDVI]) combinations were observed among aus genotypes, indicating that some genotypes continued transpiration while rolled. Association mapping indicated colocation of genomic regions for leaf rolling score and ΔNDVI under drought with previously reported leaf rolling genes and gene networks related to leaf anatomy. The relatively subtle variation across these large diversity panels may explain the lack of agreement of this study with earlier reports that used small numbers of genotypes that were highly divergent in hydraulic traits driving leaf rolling differences. This study highlights the large range of physiological responses to drought among rice genotypes and emphasizes that drought response processes should be understood in detail before incorporating them into a varietal selection programme.

Simultaneous Improvement and Genetic Dissection of Drought Tolerance Using Selected Breeding Populations of Rice

Drought is the most important factor limiting rice yield in most rainfed areas of Asia and Africa. Four large BC₂F₂ populations consisted of 3,200 individuals, which were derived from crosses between an elite Geng variety, Jigeng88, and four donors from three different countries, were screened and progeny tested under severe drought stress, resulting in the development of 72 introgression lines (ILs) with significantly improved yield compared to the recurrent parent Jigeng88. These DT ILs plus four random populations (without drought selection population) from the same crosses were evaluated in replicated trials under both drought stress and non-stress conditions in two environments, and characterized with simple sequence repeat (SSR) markers to understand how directional selection was operating on the genetic variation of DT of rice. Thirteen DT QTLs of large effect were identified based on the significant allelic and genotypic frequency shits in the DT ILs by using the joint segregation distortion method. The 13 QTLs were validated by the genotypic differences at individual QTL in the random populations. Putative genetic networks consisting of 30 loci in 29 functional genetic units underlying DT were detected by X² tests and non-random associations between or among DT loci in DT ILs from the four populations. Most large-effect DT QTLs were previously reported and located in the upstream of the genetic networks as putative regulators, and were either mapped to important regulatory genes for DT or drought responsiveness reported previously. In our study, five promising ILs with significantly improved yield were selected under both drought and normal irrigated conditions. The QTLs and their genetic networks underlying DT detected provided useful genetic information for further improving DT and yield using designed QTL pyramiding.

Genetic dissection of pre-harvest sprouting resistance in an upland rice cultivar

Seed dormancy is important in rice breeding because it confers resistance to pre-harvest sprouting (PHS). To detect quantitative trait loci (QTLs) for pre-harvest sprouting resistance, we used chromosome segment substitution lines (CSSLs) derived from a cross between the Japanese upland rice cultivar 'Owarihatamochi' and the lowland rice cultivar 'Koshihikari'. In the CSSLs, several chromosomal regions were associated with PHS resistance. Among these, the chromosome 9 segment from 'Owarihatamochi' had the greatest association with increased PHS resistance. Further QTL analysis using an advanced backcross population (BC₄F₂) derived from a 'Koshihikari' × 'Owarihatamochi' cross revealed two putative QTLs, here designated qSDR9.1 (Seed dormancy 9.1) and qSDR9.2, on chromosome 9. The 'Owarihatamochi' alleles of the two QTLs reduced germination. Further fine mapping revealed that qSDR9.1 and qSDR9.2 were located within 4.1-Mb and 2.3-Mb intervals (based on the 'Nipponbare' reference genome sequence) defined by the simple sequence repeat marker loci RM24039 and RM24260 and Indel_2 and RM24540, respectively. We thus identified two QTLs for PHS resistance in 'Owarihatamochi', even though resistance levels are relatively low in this cultivar. This unexpected finding suggests the advantages of using CSSLs for QTL detection.

Genetic Loci Governing Grain Yield and Root Development under Variable Rice Cultivation Conditions

Drought is the major abiotic stress to rice grain yield under unpredictable changing climatic scenarios. The widely grown, high yielding but drought susceptible rice varieties need to be improved by unraveling the genomic regions controlling traits enhancing drought tolerance. The present study was conducted with the aim to identify quantitative trait loci (QTLs) for grain yield and root development traits under irrigated non-stress and reproductive-stage drought stress in both lowland and upland situations. A mapping population consisting of 480 lines derived from a cross between Dular (drought-tolerant) and IR64-21 (drought susceptible) was used. QTL analysis revealed three major consistent-effect QTLs for grain yield (qDTY1.1, qDTY1.3 , and qDTY8.1 ) under non-stress and reproductive-stage drought stress conditions, and 2 QTLs for root traits (qRT9.1 for root-growth angle and qRT5.1 for multiple root traits, i.e., seedling-stage root length, root dry weight and crown root number). The genetic locus qDTY1.1 was identified as hotspot for grain yield and yield-related agronomic and root traits. The study identified significant positive correlations among numbers of crown roots and mesocotyl length at the seedling stage and root length and root dry weight at depth at later stages with grain yield and yield-related traits. Under reproductive stage drought stress, the grain yield advantage of the lines with QTLs ranged from 24.1 to 108.9% under upland and 3.0-22.7% under lowland conditions over the lines without QTLs. The lines with QTL combinations qDTY1.3 +qDTY8.1 showed the highest mean grain yield advantage followed by lines having qDTY1.1 +qDTY8.1 and qDTY1.1 +qDTY8.1 +qDTY1.3 , across upland/lowland reproductive-stage drought stress. The identified QTLs for root traits, mesocotyl length, grain yield and yield-related traits can be immediately deployed in marker-assisted breeding to develop drought tolerant high yielding rice varieties.

Genome-wide association study of salt tolerance at the seed germination stage in rice

BACKGROUND

Improving the salt tolerance of direct-seeding rice at the seed germination stage is a major breeding goal in many Asian rice-growing countries, where seedlings must often establish in soils with a high salt content. Thus, it is important to understand the genetic mechanisms of salt tolerance in rice and to screen for germplasm with salt tolerance at the seed germination stage. Here, we investigated seven seed germination-related traits under control and salt-stress conditions and conducted a genome-wide association study based on the re-sequencing of 478 diverse rice accessions.

RESULTS

The analysis used a mixed linear model and was based on 6,361,920 single nucleotide polymorphisms in 478 rice accessions grouped into whole, indica, and non-indica panels. Eleven loci containing 22 significant salt tolerance-associated single nucleotide polymorphisms were identified based on the stress-susceptibility indices (SSIs) of vigor index (VI) and mean germination time (MGT). From the SSI of VI, six major loci were identified, explaining 20.2% of the phenotypic variation. From the SSI of MGT, five major loci were detected, explaining 26.4% of the phenotypic variation. Of these, seven loci on chromosomes 1, 5, 6, 11, and 12 were close to six previously identified quantitative gene loci/genes related to tolerance to salinity or other abiotic stresses. The strongest association region for the SSI of MGT was identified in a ~ 13.3 kb interval (15450039-15,463,330) on chromosome 1, near salt-tolerance quantitative trait loci controlling the Na⁺: K⁺ ratio, total Na⁺ uptake, and total K⁺ concentration. The strongest association region for the SSI of VI was detected in a ~ 164.2 kb interval (526662-690,854) on chromosome 2 harboring two nitrate transporter family genes (OsNRT2.1 and OsNRT2.2), which affect gene expression under salt stress. The haplotype analysis indicated that OsNRT2.2 was associated with subpopulation differentiation and its minor/rare tolerant haplotype was detected.

CONCLUSIONS

These results provide valuable information for salt tolerance-related gene cloning and for understanding the genetic mechanisms of salt tolerance at the seed germination stage. This information will be useful to improve the salt tolerance of direct-seeding rice varieties by genomic selection or marker-assisted selection.

Analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach

Traditional cultivars of rice in India exhibit tolerance to drought stress due to their inherent genetic variations. Here we present comparative physiological and transcriptome analyses of two contrasting cultivars, drought tolerant Dhagaddeshi (DD) and susceptible IR20. Microarray analysis revealed several differentially expressed genes (DEGs) exclusively in DD as compared to IR20 seedlings exposed to 3 h drought stress. Physiologically, DD seedlings showed higher cell membrane stability and differential ABA accumulation in response to dehydration, coupled with rapid changes in gene expression. Detailed analyses of metabolic pathways enriched in expression data suggest interplay of ABA dependent along with secondary and redox metabolic networks that activate osmotic and detoxification signalling in DD. By co-localization of DEGs with QTLs from databases or published literature for physiological traits of DD and IR20, candidate genes were identified including those underlying major QTL qDTY_1.1 in DD. Further, we identified previously uncharacterized genes from both DD and IR20 under drought conditions including OsWRKY51, OsVP1 and confirmed their expression by qPCR in multiple rice cultivars. OsFBK1 was also functionally validated in susceptible PB1 rice cultivar and Arabidopsis for providing drought tolerance. Some of the DEGs mapped to the known QTLs could thus, be of potential significance for marker-assisted breeding.

Abscisic acid regulates gene expression in cortical fiber cells and silica cells of rice shoots

Drought-induced growth arrest is a major cause of yield loss in crops and is mediated in part by abscisic acid (ABA). The aim of this study was to identify the cell types targeted by ABA during arrest. As transcription factors ABI3 and ABI5 are essential for ABA-induced growth arrest in Arabidopsis, blast was used to identify OsVP1 and OsABF1 as their structural orthologues in rice (Oryza sativa), and employed RNA in situ hybridization to reveal the cell types accumulating the corresponding transcripts in response to ABA. Exogenous ABA arrested the growth of leaves 1, 2 and 3 in young rice shoots and inhibited secondary cell-wall formation in sclerenchyma, including expression of the cellulose synthase gene OsCesA9. Transcripts for OsVP1, OsABF1 and of the putative target genes OsEm, OsLEA3 and WSI18, increased under ABA, accumulating principally in the cytosol of the major support cells (sclerenchymatous cortical fiber cells and epidermal silica cells) of slowly growing leaf 1. Rapidly growing immature tissues in leaves 2 and 3 accumulated OsABF1, OsEm and WSI18 transcripts in the nuclei of all cells, irrespective of ABA treatment. It is concluded that during arrest of leaf growth, ABA targets support cells in maturing tissues. Target cells in immature tissues remain to be identified.