Gene network modules associated with abiotic stress response in tolerant rice genotypes identified by transcriptome meta-analysis

Deciphering the molecular basis of abiotic stress response in cucumber (Cucumis sativus L.) using RNA-Seq meta-analysis, systems biology, and machine learning approaches

Abiotic stress in cucumber (Cucumis sativus L.) may trigger distinct transcriptome responses, resulting in significant yield loss. More insight into the molecular underpinnings of the stress response can be gained by combining RNA-Seq meta-analysis with systems biology and machine learning. This can help pinpoint possible targets for engineering abiotic tolerance by revealing functional modules and key genes essential for the stress response. Therefore, to investigate the regulatory mechanism and key genes, a combination of these approaches was utilized in cucumber subjected to various abiotic stresses. Three significant abiotic stress-related modules were identified by gene co-expression network analysis (WGCNA). Three hub genes (RPL18, δ-COP, and EXLA2), ten transcription factors (TFs), one transcription regulator, and 12 protein kinases (PKs) were introduced as key genes. The results suggest that the identified PKs probably govern the coordination of cellular responses to abiotic stress in cucumber. Moreover, the C2H2 TF family may play a significant role in cucumber response to abiotic stress. Several C2H2 TF target stress-related genes were identified through co-expression and promoter analyses. Evaluation of the key identified genes using Random Forest, with an area under the curve of ROC (AUC) of 0.974 and an accuracy rate of 88.5%, demonstrates their prominent contributions in the cucumber response to abiotic stresses. These findings provide novel insights into the regulatory mechanism underlying abiotic stress response in cucumber and pave the way for cucumber genetic engineering toward improving tolerance ability under abiotic stress.

Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant's Abiotic Stress Tolerance Responses

The present day's ongoing global warming and climate change adversely affect plants through imposing environmental (abiotic) stresses and disease pressure. The major abiotic factors such as drought, heat, cold, salinity, etc., hamper a plant's innate growth and development, resulting in reduced yield and quality, with the possibility of undesired traits. In the 21st century, the advent of high-throughput sequencing tools, state-of-the-art biotechnological techniques and bioinformatic analyzing pipelines led to the easy characterization of plant traits for abiotic stress response and tolerance mechanisms by applying the 'omics' toolbox. Panomics pipeline including genomics, transcriptomics, proteomics, metabolomics, epigenomics, proteogenomics, interactomics, ionomics, phenomics, etc., have become very handy nowadays. This is important to produce climate-smart future crops with a proper understanding of the molecular mechanisms of abiotic stress responses by the plant's genes, transcripts, proteins, epigenome, cellular metabolic circuits and resultant phenotype. Instead of mono-omics, two or more (hence 'multi-omics') integrated-omics approaches can decipher the plant's abiotic stress tolerance response very well. Multi-omics-characterized plants can be used as potent genetic resources to incorporate into the future breeding program. For the practical utility of crop improvement, multi-omics approaches for particular abiotic stress tolerance can be combined with genome-assisted breeding (GAB) by being pyramided with improved crop yield, food quality and associated agronomic traits and can open a new era of omics-assisted breeding. Thus, multi-omics pipelines together are able to decipher molecular processes, biomarkers, targets for genetic engineering, regulatory networks and precision agriculture solutions for a crop's variable abiotic stress tolerance to ensure food security under changing environmental circumstances.

Comparative transcriptome profiling of near isogenic lines PBW343 and FLW29 to unravel defense related genes and pathways contributing to stripe rust resistance in wheat

Stripe rust (Sr), caused by Puccinia striiformis f. sp. tritici (Pst), is the most devastating disease that poses serious threat to the wheat-growing nations across the globe. Developing resistant cultivars is the most challenging aspect in wheat breeding. The function of resistance genes (R genes) and the mechanisms by which they influence plant-host interactions are poorly understood. In the present investigation, comparative transcriptome analysis was carried out by involving two near-isogenic lines (NILs) PBW343 and FLW29. The seedlings of both the genotypes were inoculated with Pst pathotype 46S119. In total, 1106 differentially expressed genes (DEGs) were identified at early stage of infection (12 hpi), whereas expressions of 877 and 1737 DEGs were observed at later stages (48 and 72 hpi) in FLW29. The identified DEGs were comprised of defense-related genes including putative R genes, 7 WRKY transcriptional factors, calcium, and hormonal signaling associated genes. Moreover, pathways involved in signaling of receptor kinases, G protein, and light showed higher expression in resistant cultivar and were common across different time points. Quantitative real-time PCR was used to further confirm the transcriptional expression of eight critical genes involved in plant defense mechanism against stripe rust. The information about genes are likely to improve our knowledge of the genetic mechanism that controls the stripe rust resistance in wheat, and data on resistance response-linked genes and pathways will be a significant resource for future research.

Genome-Wide Comprehensive Analysis of the Nitrogen Metabolism Toolbox Reveals Its Evolution and Abiotic Stress Responsiveness in Rice (Oryza sativa L.)

Nitrogen metabolism (NM) plays an essential role in response to abiotic stresses for plants. Enzyme activities have been extensively studied for nitrogen metabolism-associated pathways, but the knowledge of nitrogen metabolism-associated genes involved in stress response is still limited, especially for rice. In this study, we performed the genome-wide characterization of the genes putatively involved in nitrogen metabolism. A total of 1110 potential genes were obtained to be involved in nitrogen metabolism from eight species (Arabidopsis thaliana (L.) Heynh., Glycine max (L.) Merr., Brassica napus L., Triticum aestivum L., Sorghum bicolor L., Zea mays L., Oryza sativa L. and Amborella trichopoda Baill.), especially 104 genes in rice. The comparative phylogenetic analysis of the superfamily revealed the complicated divergence of different NM genes. The expression analysis among different tissues in rice indicates the NM genes showed diverse functions in the pathway of nitrogen absorption and assimilation. Distinct expression patterns of NM genes were observed in rice under drought stress, heat stress, and salt stress, indicating that the NM genes play a curial role in response to abiotic stress. Most NM genes showed a down-regulated pattern under heat stress, while complicated expression patterns were observed for different genes under salt stress and drought stress. The function of four representative NM genes (OsGS2, OsGLU, OsGDH2, and OsAMT1;1) was further validated by using qRT-PCR analysis to confirm their responses to these abiotic stresses. Based on the predicted transcription factor binding sites (TFBSs), we built a co-expression regulatory network containing transcription factors (TFs) and NM genes, of which the constructed ERF and Dof genes may act as the core genes to respond to abiotic stresses. This study provides novel sights to the interaction between nitrogen metabolism and the response to abiotic stresses.

Modulating physiological and transcriptional regulatory mechanisms for enhanced climate resilience in cereal crops

Climate change adversely affects the yield and productivity of cereal crops, which consequently impacts food security. Therefore, studying stress acclimation, particularly transcriptional patterns and morpho-physiological responses of cereal crops to different stresses, will provide insights into the molecular determinants underlying climate resilience. The availability of advanced tools and approaches has enabled the characterization of plants at morphological, physiological, biochemical, and molecular levels, which will lead to the identification of genomic regions regulating the stress responses at these levels. This will further facilitate using transgenic, breeding, or genome editing approaches to manipulate the identified regions (genes, alleles, or QTLs) to enhance stress resilience. Next-generation sequencing approaches have advanced the identification of causal genes and markers in the genomes through forward or reverse genetics. In this context, the review enumerates the progress of dissecting the molecular mechanisms underlying transcriptional and physiological responses of major cereals to climate-induced stresses. The review systematically discusses different tools and approaches available to study the response of plants to various stresses and identify the molecular determinants regulating stress-resilience. Further, the application of genomics-assisted breeding, transgene-, and targeted editing-based approaches for modulating the genetic determinants for enhanced climate resilience has been elaborated.

HvGST4 enhances tolerance to multiple abiotic stresses in barley: Evidence from integrated meta-analysis to functional verification

Extreme weather events have become more frequent, increasing crop yield fluctuations in many regions and thus the risk to global food security. Breeding crop cultivars with improved tolerance to a combination of abiotic stresses is an effective solution to counter the adverse impact of climate change. The ever-increasing genomic data and analytical tools provide unprecedented opportunities to mine genes with tolerance to multiple abiotic stresses through bioinformatics analysis. We undertook an integrated meta-analysis using 260 transcriptome data of barley related to drought, salt, heat, cold, and waterlogging stresses. A total of 223 shared differentially expressed genes (DEGs) were identified in response to five abiotic stresses, and significantly enriched in 'glutathione metabolism' and 'monoterpenoid biosynthesis' pathways. Using weighted gene co-expression network analysis (WGCNA), we further identified 15 hub genes (e.g., MYB, WRKY, NADH, and GST4) and selected the GST4 gene for functional validation. HvGST4 overexpression in Arabidopsis thaliana enhanced the tolerance to multiple abiotic stresses, likely through increasing the content of glutathione to scavenge reactive oxygen species and alleviate cell membrane peroxidation. Furthermore, we showed that virus-induced gene silencing (VIGS) of HvGST4 in barley leaves exacerbated cell membrane peroxidation under five abiotic stresses, reducing tolerance to multiple abiotic stress. Our study provides a new solution for identifying genes with tolerance to multiple abiotic stresses based on meta-analysis, which could contribute to breeding new varieties adapted genetically to adverse environmental conditions.

Phenotypic and transcriptomic responses of cultivated sunflower seedlings (Helianthus annuus L.) to four abiotic stresses

Plants encounter and respond to numerous abiotic stresses during their lifetimes. These stresses are often related and could therefore elicit related responses. There are, however, relatively few detailed comparisons between multiple different stresses at the molecular level. Here, we investigated the phenotypic and transcriptomic response of cultivated sunflower (Helianthus annuus L.) seedlings to three water-related stresses (i.e., dry-down, an osmotic challenge, and salt stress), as well as a generalized low-nutrient stress. All four stresses negatively impacted seedling growth, with the nutrient stress having a more divergent response from control as compared to the water-related stresses. Phenotypic responses were consistent with expectations for growth in low-resource environments, including increased (i.e., less negative) carbon fractionation values and leaf C:N ratios, as well as increased belowground biomass allocation. The number of differentially expressed genes (DEGs) under stress was greater in leaf tissue, but roots exhibited a higher proportion of DEGs unique to individual stresses. Overall, the three water-related stresses had a more similar transcriptomic response to each other vs. nutrient stress, though this pattern was more pronounced in root vs. leaf tissue. In contrast to our DEG analyses, co-expression network analysis revealed that there was little indication of a shared response between the four stresses in despite the majority of DEGs being shared between multiple stresses. Importantly, osmotic stress, which is often used to simulate drought stress in experimental settings, had little transcriptomic resemblance to true water limitation (i.e., dry-down) in our study, calling into question its utility as a means for simulating drought.

Identification of major candidate genes for multiple abiotic stress tolerance at seedling stage by network analysis and their validation by expression profiling in rice (Oryza sativa L.)

A wealth of microarray and RNA-seq data for studying abiotic stress tolerance in rice exists but only limited studies have been carried out on multiple stress-tolerance responses and mechanisms. In this study, we identified 6657 abiotic stress-responsive genes pertaining to drought, salinity and heat stresses from the seedling stage microarray data of 83 samples and used them to perform unweighted network analysis and to identify key hub genes or master regulators for multiple abiotic stress tolerance. Of the total 55 modules identified from the analysis, the top 10 modules with 8-61 nodes comprised 239 genes. From these 10 modules, 10 genes common to all the three stresses were selected. Further, based on the centrality properties and highly dense interactions, we identified 7 intra-modular hub genes leading to a total of 17 potential candidate genes. Out of these 17 genes, 15 were validated by expression analysis using a panel of 4 test genotypes and a pair of standard check genotypes for each abiotic stress response. Interestingly, all the 15 genes showed upregulation under all stresses and in all the genotypes, suggesting that they could be representing some of the core abiotic stress-responsive genes. More pertinently, eight of the genes were found to be co-localized with the stress-tolerance QTL regions. Thus, in conclusion, our study not only provided an effective approach for studying abiotic stress tolerance in rice, but also identified major candidate genes which could be further validated by functional genomics for abiotic stress tolerance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03182-7.

QTL Mapping and Identification of Candidate Genes for Heat Tolerance at the Flowering Stage in Rice

High-temperature stress can cause serious abiotic damage that limits the yield and quality of rice. Heat tolerance (HT) during the flowering stage of rice is a key trait that can guarantee a high and stable yield under heat stress. HT is a complex trait that is regulated by multiple quantitative trait loci (QTLs); however, few underlying genes have been fine mapped and cloned. In this study, the F_2:3 population derived from a cross between Huanghuazhan (HHZ), a heat-tolerant cultivar, and 9311, a heat-sensitive variety, was used to map HT QTLs during the flowering stage in rice. A new major QTL, qHTT8, controlling HT was identified on chromosome 8 using the bulked-segregant analysis (BSA)-seq method. The QTL qHTT8 was mapped into the 3,555,000–4,520,000 bp, which had a size of 0.965 Mb. The candidate region of qHTT8 on chromosome 8 contained 65 predicted genes, and 10 putative predicted genes were found to be associated with abiotic stress tolerance. Furthermore, qRT-PCR was performed to analyze the differential expression of these 10 genes between HHZ and 9311 under high temperature conditions. LOC_Os08g07010 and LOC_Os08g07440 were highly induced in HHZ compared with 9311 under heat stress. Orthologous genes of LOC_Os08g07010 and LOC_Os08g07440 in plants played a role in abiotic stress, suggesting that they may be the candidate genes of qHTT8. Generally, the results of this study will prove useful for future efforts to clone qHTT8 and breed heat-tolerant varieties of rice using marker-assisted selection.

Model approaches to advance crassulacean acid metabolism system integration

This review summarises recent progress in understanding crassulacean acid metabolism (CAM) systems and the integration of internal and external stimuli to maximise water-use efficiency. Complex CAM traits have been reduced to their minimum and captured as computational models, which can now be refined using recently available data from transgenic manipulations and large-scale omics studies. We identify three key areas in which an appropriate choice of modelling tool could help capture relevant comparative molecular data to address the evolutionary drivers and plasticity of CAM. One focus is to identify the environmental and internal signals that drive inverse stomatal opening at night. Secondly, it is important to identify the regulatory processes required to orchestrate the diel pattern of carbon fluxes within mesophyll layers. Finally, the limitations imposed by contrasting succulent systems and associated hydraulic conductance components should be compared in the context of water-use and evolutionary strategies. While network analysis of transcriptomic data can provide insights via co-expression modules and hubs, alternative forms of computational modelling should be used iteratively to define the physiological significance of key components and informing targeted functional gene manipulation studies. We conclude that the resultant improvements of bottom-up, mechanistic modelling systems can enhance progress towards capturing the physiological controls for phylogenetically diverse CAM systems in the face of the recent surge of information in this omics era.

A Meta-Analysis of Comparative Transcriptomic Data Reveals a Set of Key Genes Involved in the Tolerance to Abiotic Stresses in Rice

Several environmental factors, such as drought, salinity, and extreme temperatures, negatively affect plant growth and development, which leads to yield losses. The tolerance or sensitivity to abiotic stressors are the expression of a complex machinery involving molecular, biochemical, and physiological mechanisms. Here, a meta-analysis on previously published RNA-Seq data was performed to identify the genes conferring tolerance to chilling, osmotic, and salt stresses, by comparing the transcriptomic changes between tolerant and susceptible rice genotypes. Several genes encoding transcription factors (TFs) were identified, suggesting that abiotic stress tolerance involves upstream regulatory pathways. A gene co-expression network defined the metabolic and signalling pathways with a prominent role in the differentiation between tolerance and susceptibility: (i) the regulation of endogenous abscisic acid (ABA) levels, through the modulation of genes that are related to its biosynthesis/catabolism, (ii) the signalling pathways mediated by ABA and jasmonic acid, (iii) the activity of the "Drought and Salt Tolerance" TF, involved in the negative regulation of stomatal closure, and (iv) the regulation of flavonoid biosynthesis by specific MYB TFs. The identified genes represent putative key players for conferring tolerance to a broad range of abiotic stresses in rice; a fine-tuning of their expression seems to be crucial for rice plants to cope with environmental cues.