The success of rice (Oryza sativa L.) germination and survival under submerged conditions is mainly determined by the rapid growth of the coleoptile to reach the water surface. Previous reports have shown the presence of genetic variability within rice accessions in the levels of flooding tolerance during germination or anaerobic germination (AG). Although many studies have focused on the physiological mechanisms of oxygen stress, few studies have explored the breadth of natural variation in AG tolerance-related traits in rice. In this study, we evaluated the coleoptile lengths of a geographically diverse rice panel of 241 accessions, including global accessions along with elite breeding lines and released cultivars from the United States, under the normal and flooded conditions in laboratory and greenhouse environments. A genome-wide association study (GWAS) was performed using a 7K single-nucleotide polymorphism (SNP) array and the phenotypic data of normal coleoptile length, flooded coleoptile length, flooding tolerance index, and survival at 14 d after seeding (DAS). Out of the 30 significant GWAS quantitative trait loci (QTL) regions identified, 14 colocalized with previously identified candidate genes of AG tolerance, whereas 16 were potentially novel. Two rice accessions showing contrasting phenotypic responses to AG stress were selected for the transcriptomics study. The combined approach of GWAS and transcriptomics analysis identified 77 potential candidate genes related to AG tolerance. The findings of our study may assist rice improvement programs in developing rice cultivars with robust tolerance under flooding stress during germination and the early seedling stage.
One of the thrust areas of research in plant breeding is to develop crop cultivars with enhanced tolerance to abiotic stresses. Thus, identifying abiotic stress-responsive genes (SRGs) and proteins is important for plant breeding research. However, identifying such genes via established genetic approaches is laborious and resource intensive. Although transcriptome profiling has remained a reliable method of SRG identification, it is species specific. Additionally, identifying multistress responsive genes using gene expression studies is cumbersome. Thus, endorsing the need to develop a computational method for identifying the genes associated with different abiotic stresses. In this work, we aimed to develop a computational model for identifying genes responsive to six abiotic stresses: cold, drought, heat, light, oxidative, and salt. The predictions were performed using support vector machine (SVM), random forest, adaptive boosting (ADB), and extreme gradient boosting (XGB), where the autocross covariance (ACC) and K-mer compositional features were used as input. With ACC, K-mer, and ACC + K-mer compositional features, the overall accuracy of ∼60–77, ∼75–86, and ∼61–78% were respectively obtained using the SVM algorithm with fivefold cross-validation. The SVM also achieved higher accuracy than the other three algorithms. The proposed model was also assessed with an independent dataset and obtained an accuracy consistent with cross-validation. The proposed model is the first of its kind and is expected to serve the requirement of experimental biologists; however, the prediction accuracy was modest. Given its importance for the research community, the online prediction application, ASRpro, is made freely available (https://iasri-sg.icar.gov.in/asrpro/) for predicting abiotic SRGs and proteins.
Legume crops are rich in nutritional value for human and livestock consumption. With global climate change, developing stress-resilient crops is crucial for ensuring global food security. Because of their nitrogen-fixing ability, legumes are also important for sustainable agriculture. Various abiotic stresses, such as salt, drought, and elevated temperatures, are known to adversely affect legume production. The responses of plants to abiotic stresses involve complicated cellular processes including stress hormone signaling, metabolic adjustments, and transcriptional regulations. Epigenetic mechanisms play a key role in regulating gene expressions at both transcriptional and posttranscriptional levels. Increasing evidence suggests the importance of epigenetic regulations of abiotic stress responses in legumes, and recent investigations have extended the scope to the epigenomic level using next-generation sequencing technologies. In this review, the current knowledge on the involvement of epigenetic features, including DNA methylation, histone modification, and noncoding RNAs, in abiotic stress responses in legumes is summarized and discussed. Since most of the available information focuses on a single aspect of these epigenetic features, integrative analyses involving omics data in multiple layers are needed for a better understanding of the dynamic chromatin statuses and their roles in transcriptional regulation. The inheritability of epigenetic modifications should also be assessed in future studies for their applications in improving stress tolerance in legumes through the stable epigenetic optimization of gene expressions.