Genes and co-expression modules common to drought and bacterial stress responses in Arabidopsis and rice

Mapping of flumioxazin tolerance in a snap bean diversity panel leads to the discovery of a master genomic region controlling multiple stress resistance genes

Introduction

Effective weed management tools are crucial for maintaining the profitable production of snap bean (Phaseolus vulgaris L.). Preemergence herbicides help the crop to gain a size advantage over the weeds, but the few preemergence herbicides registered in snap bean have poor waterhemp (Amaranthus tuberculatus) control, a major pest in snap bean production. Waterhemp and other difficult-to-control weeds can be managed by flumioxazin, an herbicide that inhibits protoporphyrinogen oxidase (PPO). However, there is limited knowledge about crop tolerance to this herbicide. We aimed to quantify the degree of snap bean tolerance to flumioxazin and explore the underlying mechanisms.

Methods

We investigated the genetic basis of herbicide tolerance using genome-wide association mapping approach utilizing field-collected data from a snap bean diversity panel, combined with gene expression data of cultivars with contrasting response. The response to a preemergence application of flumioxazin was measured by assessing plant population density and shoot biomass variables.

Results

Snap bean tolerance to flumioxazin is associated with a single genomic location in chromosome 02. Tolerance is influenced by several factors, including those that are indirectly affected by seed size/weight and those that directly impact the herbicide's metabolism and protect the cell from reactive oxygen species-induced damage. Transcriptional profiling and co-expression network analysis identified biological pathways likely involved in flumioxazin tolerance, including oxidoreductase processes and programmed cell death. Transcriptional regulation of genes involved in those processes is possibly orchestrated by a transcription factor located in the region identified in the GWAS analysis. Several entries belonging to the Romano class, including Bush Romano 350, Roma II, and Romano Purpiat presented high levels of tolerance in this study. The alleles identified in the diversity panel that condition snap bean tolerance to flumioxazin shed light on a novel mechanism of herbicide tolerance and can be used in crop improvement.

Genome-wide association analysis reveals genes controlling an antagonistic effect of biotic and osmotic stress on Arabidopsis thaliana growth

While the response of Arabidopsis thaliana to drought, herbivory or fungal infection has been well-examined, the consequences of exposure to a series of such (a)biotic stresses are not well studied. This work reports on the genetic mechanisms underlying the Arabidopsis response to single osmotic stress, and to combinatorial stress, either fungal infection using Botrytis cinerea or herbivory using Pieris rapae caterpillars followed by an osmotic stress treatment. Several small-effect genetic loci associated with rosette dry weight (DW), rosette water content (WC), and the projected rosette leaf area in response to combinatorial stress were mapped using univariate and multi-environment genome-wide association approaches. A single-nucleotide polymorphism (SNP) associated with DROUGHT-INDUCED 19 (DI19) was identified by both approaches, supporting its potential involvement in the response to combinatorial stress. Several SNPs were found to be in linkage disequilibrium with known stress-responsive genes such as PEROXIDASE 34 (PRX34), BASIC LEUCINE ZIPPER 25 (bZIP25), RESISTANCE METHYLATED GENE 1 (RMG1) and WHITE RUST RESISTANCE 4 (WRR4). An antagonistic effect between biotic and osmotic stress was found for prx34 and arf4 mutants, which suggests PRX34 and ARF4 play an important role in the response to the combinatorial stress.

A Rapid and Simplified Method to Isolate Specific Regulators Based on Biotin-Avidin Binding Affinities in Crops

Transcription factors (TFs) are indispensable components of transcriptional regulatory pathways involved in crop growth and development. Herein, we developed a new method for the identification of upstream TFs specific to genes in crops based on the binding affinities of biotin and avidin. First, we constructed and verified the new biotin and avidin system (BAS) by a coprecipitation assay. Subsequently, the feasibility of DNA-based BAS (DBAS) was further proved by in vivo and in vitro assays. Furthermore, we cloned the promoter of rice OsNRT1.1B and the possible regulators were screened and identified. Additionally, partial candidates were validated by the electrophoresis mobility shift assay (EMSA), yeast one-hybrid, and luciferase activity assays. Remarkably, the results showed that the candidates PIP3 and PIP19 both responded to nitrate immediately and overexpression of PIP3 caused retard growth, which indicates that the candidates are functional and the new DBAS method is useful to isolate regulators in crops.

Transcriptional survey of abiotic stress response in maize (Zea mays) in the level of gene co-expression network and differential gene correlation analysis

Abstract. Maize may be exposed to several abiotic stresses in the field. Therefore, identifying the tolerance mechanisms of natural field stress is mandatory. Gene expression data of maize upon abiotic stress were collected, and 560 differentially expressed genes (DEGs) were identified through meta-analysis. The most significant gene ontology terms in up-regulated genes were 'response to abiotic stress' and 'chitinase activity'. 'Phosphorelay signal transduction system' was the most significant enriched biological process in down-regulated DEGs. The co-expression analysis unveiled seven modules of DEGs, with a notable positive correlation between the modules and abiotic stress. Furthermore, the statistical significance was strikingly high for the turquoise, green and yellow modules. The turquoise group played a central role in orchestrating crucial adaptations in metabolic and stress response pathways in maize when exposed to abiotic stress. Within three up-regulated modules, Zm.7361.1.A1_at, Zm.10386.1.A1_a_at and Zm.10151.1.A1_at emerged as hub genes. These genes might introduce novel candidates implicated in stress tolerance mechanisms, warranting further comprehensive investigation and research. In parallel, the R package glmnet was applied to fit a logistic LASSO regression model on the DEGs profile to select candidate genes associated with abiotic responses in maize. The identified hub genes and LASSO regression genes were validated on an independent microarray dataset. Additionally, Differential Gene Correlation Analysis (DGCA) was performed on LASSO and hub genes to investigate the gene-gene regulatory relationship. The P value of DGCA of 16 pairwise gene comparisons was lower than 0.01, indicating a gene-gene significant change in correlation between control and abiotic stress. Integrated weighted gene correlation network analysis and logistic LASSO analysis revealed Zm.11185.1.S1_at, Zm.2331.1.S1_x_at and Zm.17003.1.S1_at. Notably, these 3 genes were identified in the 16 gene-pair comparisons. This finding highlights the notable significance of these genes in the abiotic stress response. Additional research into maize stress tolerance may focus on these three genes.

Differential expression of the genes encoding immune system components in response to Pseudomonas syringae and Pseudomonas aeruginosa in Arabidopsis thaliana

In innate immunity, the first layer of defense against any microbial infection is triggered by the perception of pathogen-associated molecular patterns by highly specific pattern recognition receptors. The Pseudomonas syringae pv. tomato and Pseudomonas aeruginosa are plant-pathogenic bacterial species that include pathogenic strains in a wide range of different plant species. In the current study, extensive analysis including gene expression of 12 hub genes, gene ontology, protein-protein interaction, and cis-element prediction to dissect the Arabidopsis response to above-mentioned bacteria were performed. Further, we evaluated weighted co-expression network analysis (WGCNA) in the wild-type plants and coi-1 mutant line and determined changes in responsive genes at two time-points (4 and 8 h) of post-treatment with P. syringae and P. aeruginosa. Compared to the wild-type plants, coi-1 mutant showed significant expression in most of the genes involved, indicating that their protein products have important role in innate immunity and RNA silencing pathways. Our findings showed that 12 hub genes were co-expressed in response to P. syringae and P. aeruginosa infections. Based on the network analysis, transcription factors, receptors, protein kinase, and pathogenesis-related protein (PR1) were involved in the immunity system. Gene ontology related to each module was involved in defense response, protein serine kinase activity, and primary miRNA processing. Based on the cis-elements prediction, MYB, MYC, WRE3, W-box, STRE, and ARE contained the most number of cis-elements in co-expressed network genes. Also, in coi-1 mutant, most responsive genes against theses pathogens were up-regulated. The knowledge gained in the gene expression analysis in response to P. syringae and P. aeruginosa in the model plant, i.e., Arabidopsis, is essential to allow us to gain more insight about the innate immunity in other crops.

Identification of genes associated with abiotic stress tolerance in sweetpotato using weighted gene co-expression network analysis

Sweetpotato, Ipomoea batatas (L.), a key food security crop, is negatively impacted by heat, drought, and salinity stress. The orange-fleshed sweetpotato cultivar "Beauregard" was exposed to heat, salt, and drought treatments for 24 and 48 h to identify genes responding to each stress condition in leaves. Analysis revealed both common (35 up regulated, 259 down regulated genes in the three stress conditions) and unique sets of up regulated (1337 genes by drought, 516 genes by heat, and 97 genes by salt stress) and down regulated (2445 genes by drought, 678 genes by heat, and 204 genes by salt stress) differentially expressed genes (DEGs) suggesting common, yet stress-specific transcriptional responses to these three abiotic stressors. Gene Ontology analysis of down regulated DEGs common to both heat and salt stress revealed enrichment of terms associated with "cell population proliferation" suggestive of an impact on the cell cycle by the two stress conditions. To identify shared and unique gene co-expression networks under multiple abiotic stress conditions, weighted gene co-expression network analysis was performed using gene expression profiles from heat, salt, and drought stress treated 'Beauregard' leaves yielding 18 co-expression modules. One module was enriched for "response to water deprivation," "response to abscisic acid," and "nitrate transport" indicating synergetic crosstalk between nitrogen, water, and phytohormones with genes encoding osmotin, cell expansion, and cell wall modification proteins present as key hub genes in this drought-associated module. This research lays the groundwork for exploring to a further degree, mechanisms for abiotic stress tolerance in sweetpotato.

Genome-Wide Analysis of Stress-Responsive Genes and Alternative Splice Variants in Arabidopsis Roots under Osmotic Stresses

Plant roots show distinct gene-expression profiles from those of shoots under abiotic stress conditions. In this study, we performed mRNA sequencing (mRNA-Seq) to analyze the transcriptional profiling of Arabidopsis roots under osmotic stress conditions-high salinity (NaCl) and drought (mannitol). The roots demonstrated significantly distinct gene-expression changes from those of the aerial parts under both the NaCl and the mannitol treatment. We identified 68 closely connected transcription-factor genes involved in osmotic stress-signal transduction in roots. Well-known abscisic acid (ABA)-dependent and/or ABA-independent osmotic stress-responsive genes were not considerably upregulated in the roots compared to those in the aerial parts, indicating that the osmotic stress response in the roots may be regulated by other uncharacterized stress pathways. Moreover, we identified 26 osmotic-stress-responsive genes with distinct expressions of alternative splice variants in the roots. The quantitative reverse-transcription polymerase chain reaction further confirmed that alternative splice variants, such as those for ANNAT4, MAGL6, TRM19, and CAD9, were differentially expressed in the roots, suggesting that alternative splicing is an important regulatory mechanism in the osmotic stress response in roots. Altogether, our results suggest that tightly connected transcription-factor families, as well as alternative splicing and the resulting splice variants, are involved in the osmotic stress response in roots.

Network Biology Analyses and Dynamic Modeling of Gene Regulatory Networks under Drought Stress Reveal Major Transcriptional Regulators in Arabidopsis

Drought is one of the most serious abiotic stressors in the environment, restricting agricultural production by reducing plant growth, development, and productivity. To investigate such a complex and multifaceted stressor and its effects on plants, a systems biology-based approach is necessitated, entailing the generation of co-expression networks, identification of high-priority transcription factors (TFs), dynamic mathematical modeling, and computational simulations. Here, we studied a high-resolution drought transcriptome of Arabidopsis. We identified distinct temporal transcriptional signatures and demonstrated the involvement of specific biological pathways. Generation of a large-scale co-expression network followed by network centrality analyses identified 117 TFs that possess critical properties of hubs, bottlenecks, and high clustering coefficient nodes. Dynamic transcriptional regulatory modeling of integrated TF targets and transcriptome datasets uncovered major transcriptional events during the course of drought stress. Mathematical transcriptional simulations allowed us to ascertain the activation status of major TFs, as well as the transcriptional intensity and amplitude of their target genes. Finally, we validated our predictions by providing experimental evidence of gene expression under drought stress for a set of four TFs and their major target genes using qRT-PCR. Taken together, we provided a systems-level perspective on the dynamic transcriptional regulation during drought stress in Arabidopsis and uncovered numerous novel TFs that could potentially be used in future genetic crop engineering programs.

Integrative System Biology Analysis of Transcriptomic Responses to Drought Stress in Soybean (Glycine max L.)

Drought is a major abiotic stressor that causes yield losses and limits the growing area for most crops. Soybeans are an important legume crop that is sensitive to water-deficit conditions and suffers heavy yield losses from drought stress. To improve drought-tolerant soybean cultivars through breeding, it is necessary to understand the mechanisms of drought tolerance in soybeans. In this study, we applied several transcriptome datasets obtained from soybean plants under drought stress in comparison to those grown under normal conditions to identify novel drought-responsive genes and their underlying molecular mechanisms. We found 2168 significant up/downregulated differentially expressed genes (DEGs) and 8 core modules using gene co-expression analysis to predict their biological roles in drought tolerance. Gene Ontology and KEGG analyses revealed key biological processes and metabolic pathways involved in drought tolerance, such as photosynthesis, glyceraldehyde-3-phosphate dehydrogenase and cytokinin dehydrogenase activity, and regulation of systemic acquired resistance. Genome-wide analysis of plants’ cis-acting regulatory elements (CREs) and transcription factors (TFs) was performed for all of the identified DEG promoters in soybeans. Furthermore, the PPI network analysis revealed significant hub genes and the main transcription factors regulating the expression of drought-responsive genes in each module. Among the four modules associated with responses to drought stress, the results indicated that GLYMA_04G209700, GLYMA_02G204700, GLYMA_06G030500, GLYMA_01G215400, and GLYMA_09G225400 have high degrees of interconnection and, thus, could be considered as potential candidates for improving drought tolerance in soybeans. Taken together, these findings could lead to a better understanding of the mechanisms underlying drought responses in soybeans, which may useful for engineering drought tolerance in plants.

A meta-analysis of microarray data revealed hub genes and transcription factors involved in drought stress response in rice (Oryza sativa L.)

Although there are various studies attempted to clarify the genetic mechanism of plant response to drought stress that reduces crop yield, a meta-analysis can integrate the results of them to provide a better picture of the issue. Therefore, in this study, several microarray datasets of rice were meta-analysed under drought stress and normal condition using the R packages. Accordingly, differentially expressed genes (meta-DEGs) were identified. The results showed 643 and 677 upregulated and downregulated genes, respectively. The significant common Gene Ontology (GO) terms between the up- and downregulated genes were responses to abiotic stimulus , water deprivation , oxygen-containing compound and abscisic acid . The transcription factors (TF) survey showed that bHLH under drought stress activates up genes 42% more than down genes while bzip Homeodomain activates down genes 54% more than up genes. The hub downregulated genes obtained from this study were mainly related to photosynthesis and the hub upregulated genes were mainly related to stress tolerance which include heat shock proteins (HSPs), late embryogenesis abundant (LEAs), calmodulin-like protein (CML), phosphatase 2C (PP2Cs) and IAA genes. Moreover, this meta-analysis data were compared with other experimental data and the results confirmed the up and down expression of them. Our findings can provide novel insights into the molecular mechanism of rice (Oryza sativa L.) response to drought stress.

Transcriptomic responses under combined bacterial blight and drought stress in rice reveal potential genes to improve multi-stress tolerance

BACKGROUND

The unprecedented drought and frequent occurrence of pathogen infection in rice is becoming more due to climate change. Simultaneous occurrence of stresses lead to more crop loss. To cope up multiple stresses, the durable resistant cultivars needs to be developed, by identifying relevant genes from combined biotic and abiotic stress exposed plants.

RESULTS

We studied the effect of drought stress, bacterial leaf blight disease causing Xanthomonas oryzae pv. oryzae (Xoo) pathogen infection and combined stress in contrasting BPT5204 and TN1 rice genotypes. Mild drought stress increased Xoo infection irrespective of the genotype. To identify relevant genes that could be used to develop multi-stress tolerant rice, RNA sequencing from individual drought, pathogen and combined stresses in contrasting genotypes has been developed. Many important genes are identified from resistant genotype and diverse group of genes are differentially expressed in contrasting genotypes under combined stress. Further, a meta-analysis from individual drought and Xoo pathogen stress from public domain data sets narrowed- down candidate differentially expressed genes. Many translation associated genes are differentially expressed suggesting their extra-ribosomal function in multi-stress adaptation. Overexpression of many of these genes showed their relevance in improving stress tolerance in rice by different scientific groups. In combined stress, many downregulated genes also showed their relevance in stress adaptation when they were over-expressed.

CONCLUSIONS

Our study identifies many important genes, which can be used as molecular markers and targets for genetic manipulation to develop durable resistant rice cultivars. Strategies should be developed to activate downregulated genes, to improve multi-stress tolerance in plants.

Weighted Gene Correlation Network Analysis (WGCNA) of Arabidopsis Somatic Embryogenesis (SE) and Identification of Key Gene Modules to Uncover SE-Associated Hub Genes

Somatic embryogenesis (SE), which occurs naturally in many plant species, serves as a model to elucidate cellular and molecular mechanisms of embryo patterning in plants. Decoding the regulatory landscape of SE is essential for its further application. Hence, the present study was aimed at employing Weighted Gene Correlation Network Analysis (WGCNA) to construct a gene coexpression network (GCN) for Arabidopsis SE and then identifying highly correlated gene modules to uncover the hub genes associated with SE that may serve as potential molecular targets. A total of 17,059 genes were filtered from a microarray dataset comprising four stages of SE, i.e., stage I (zygotic embryos), stage II (proliferating tissues at 7 days of induction), stage III (proliferating tissues at 14 days of induction), and stage IV (mature somatic embryos). This included 1,711 transcription factors and 445 EMBRYO DEFECTIVE genes. GCN analysis identified a total of 26 gene modules with the module size ranging from 35 to 3,418 genes using a dynamic cut tree algorithm. The module-trait analysis revealed that four, four, seven, and four modules were associated with stages I, II, III, and IV, respectively. Further, we identified a total of 260 hub genes based on the degree of intramodular connectivity. Validation of the hub genes using publicly available expression datasets demonstrated that at least 78 hub genes are potentially associated with embryogenesis; of these, many genes remain functionally uncharacterized thus far. In silico promoter analysis of these genes revealed the presence of cis-acting regulatory elements, “soybean embryo factor 4 (SEF4) binding site,” and “E-box” of the napA storage-protein gene of Brassica napus; this suggests that these genes may play important roles in plant embryo development. The present study successfully applied WGCNA to construct a GCN for SE in Arabidopsis and identified hub genes involved in the development of somatic embryos. These hub genes could be used as molecular targets to further elucidate the molecular mechanisms underlying SE in plants.

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.

Digital RNA-seq transcriptome plus tissue anatomy analyses reveal the developmental mechanism of the calabash-shaped root in Tetrastigma hemsleyanum

Tetrastigma hemsleyanum Diels & Gilg ex Diels is a liana plant with promising medicinal and ornamental values. Its calabash-shaped roots (CRs) are served as a traditional Chinese herb. However, it takes a long growth period to form CRs. In this study, three types of architectural roots, including fibrous roots (FRs), bar-shaped roots (BRs) and CRs, were employed as materials, and the characteristics of histo-anatomy and digital RNA-seq transcriptome profiles were analyzed. Among the three types of roots, the vascular bundles in FRs were intact, while some of the vascular bundles degenerated in BRs, and only few traces of vascular bundles existed in CRs. Meanwhile, no obvious cell inclusions were found in the cytoplasm of FRs, while a few inclusions were found in BRs, and abundant inclusions were detected in CRs, which might be the main source of medicinal components in roots. The transcriptome profiles and qRT-PCR validation indicated that seven upregulated genes, encoding xyloglucan glycosyltransferase, ACC oxidase, CYP711A1, SHORT-ROOT transcript factor, galacturonosyltransferas, WAT1 and WRKY, and two downregulated genes, encoding LRR receptor-like serine/threonine-protein kinase and CYP83B1, were probably involved in the formation and development of CRs. In addition, Gene Ontology terms of intrinsic component of membrane, integral component of membrane, cell periphery, membrane part, plasma membrane, membrane, intrinsic component of plasma membrane, cellular chemical homeostasis and plasma membrane part were probably related to the formation of CRs. Kyoto Encyclopedia of Genes and Genomes pathways related to the development of CRs probably included MAPK signaling pathway-plant, plant hormone signal transduction and circadian rhythm-plant. Our finding suggested a probable mode for the formation of CRs.

Rootstock influences the effect of grapevine leafroll-associated viruses on berry development and metabolism via abscisic acid signalling

Grapevine leafroll-associated virus (GLRaV) infections are accompanied by symptoms influenced by host genotype, rootstock, environment, and which individual or combination of GLRaVs is present. Using a dedicated experimental vineyard, we studied the responses to GLRaVs in ripening berries from Cabernet Franc grapevines grafted to different rootstocks and with zero, one, or pairs of leafroll infection(s). RNA sequencing data were mapped to a high-quality Cabernet Franc genome reference assembled to carry out this study and integrated with hormone and metabolite abundance data. This study characterized conserved and condition-dependent responses to GLRaV infection(s). Common responses to GLRaVs were reproduced in two consecutive years and occurred in plants grafted to different rootstocks in more than one infection condition. Though different infections were inconsistently distinguishable from one another, the effects of infections in plants grafted to different rootstocks were distinct at each developmental stage. Conserved responses included the modulation of genes related to pathogen detection, abscisic acid (ABA) signalling, phenylpropanoid biosynthesis, and cytoskeleton remodelling. ABA, ABA glucose ester, ABA and hormone signalling-related gene expression, and the expression of genes in several transcription factor families differentiated the effects of GLRaVs in berries from Cabernet Franc grapevines grafted to different rootstocks. These results support that ABA participates in the shared responses to GLRaV infection and differentiates the responses observed in grapevines grafted to different rootstocks.

Senescence-Associated Glycine max (Gm)NAC Genes: Integration of Natural and Stress-Induced Leaf Senescence

Leaf senescence is a genetically regulated developmental process that can be triggered by a variety of internal and external signals, including hormones and environmental stimuli. Among the senescence-associated genes controlling leaf senescence, the transcriptional factors (TFs) comprise a functional class that is highly active at the onset and during the progression of leaf senescence. The plant-specific NAC (NAM, ATAF, and CUC) TFs are essential for controlling leaf senescence. Several members of Arabidopsis AtNAC-SAGs are well characterized as players in elucidated regulatory networks. However, only a few soybean members of this class display well-known functions; knowledge about their regulatory circuits is still rudimentary. Here, we describe the expression profile of soybean GmNAC-SAGs upregulated by natural senescence and their functional correlation with putative AtNAC-SAGs orthologs. The mechanisms and the regulatory gene networks underlying GmNAC081- and GmNAC030-positive regulation in leaf senescence are discussed. Furthermore, new insights into the role of GmNAC065 as a negative senescence regulator are presented, demonstrating extraordinary functional conservation with the Arabidopsis counterpart. Finally, we describe a regulatory circuit which integrates a stress-induced cell death program with developmental leaf senescence via the NRP-NAC-VPE signaling module.

A meta-analysis of transcriptomic profiles reveals molecular pathways response to cadmium stress of Gramineae

As a non-essential heavy metal, cadmium (Cd) is toxic to plants. In the last 15 years, over 70 transcriptome studies have been published to decipher the molecular response mechanism against Cd stress in different plants. To extract generalization results from transcriptomic data across different plants and obtain some hub genes that respond to Cd stress, we carried out a meta-analysis of 32 published datasets. Cluster analysis revealed that plant species played a more decisive role than the media used and exposure time in the transcriptome patterns of plant roots response to Cd. The datasets from a Gramineae-like (GL) group were closer in clustering. 838 DEGs were commonly Cd-regulated in at least nine of 18 GL datasets. Gene ontology and KEGG pathway analyses revealed that oxidative stress-related terms and lignin synthesis-related terms were significantly enriched. Mapman analysis revealed that these common DEGs were mainly involved in regulation, cellular response, secondary metabolism, transport, cell wall and lipid metabolism. In Oryza sativa, 15 DEGs were up-regulated in at least four of five HM (As, Cr, Cd, Hg and Pb) groups, such as Os10g0517500 (methionine gamma-lyase) and Os01g0159800 (bHLH107). Moreover, our datasets can be used to retrieve log2FC value of specific genes across 29 studies (48 datasets), which provides data reference for the subsequent selection of HM-related genes. Our results provide the basis for further understanding of Cd tolerance mechanisms in plants.

Transcriptome-based approaches for clarification of nutritional responses and improvement of crop production

Genome-wide transcriptome profiling is a powerful tool for identifying key genes and pathways involved in plant development and physiological processes. This review summarizes studies that have used transcriptome profiling mainly in rice to focus on responses to macronutrients such as nitrogen, phosphorus and potassium, and spatio-temporal root profiling in relation to the regulation of root system architecture as well as nutrient uptake and transport. We also discuss strategies based on meta- and co-expression analyses with different attributed transcriptome data, which can be used for investigating the regulatory mechanisms and dynamics of nutritional responses and adaptation, and speculate on further advances in transcriptome profiling that could have potential application to crop breeding and cultivation.

Microarray analysis of Arabidopsis thaliana exposed to single and mixed infections with Cucumber mosaic virus and turnip viruses

Cucumber mosaic virus (CMV), Turnip mosaic virus (TuMV) and Turnip crinkle virus (TCV) are important plant infecting viruses. In the present study, whole transcriptome alteration of Arabidopsis thaliana in response to CMV, TuMV and TCV, individual as well as mixed infections of CMV and TuMV/CMV and TCV were investigated using microarray data. In response to CMV, TuMV and TCV infections, a total of 2517, 3985 and 277 specific differentially expressed genes (DEGs) were up-regulated, while 2615, 3620 and 243 specific DEGs were down-regulated, respectively. The number of 1222 and 30 common DEGs were up-regulated during CMV and TuMV as well as CMV and TCV infections, while 914 and 24 common DEGs were respectively down-regulated. Genes encoding immune response mediators, signal transducer activity, signaling and stress response functions were among the most significantly upregulated genes during CMV and TuMV or CMV and TCV mixed infections. The NAC, C3H, C2H2, WRKY and bZIP were the most commonly presented transcription factor (TF) families in CMV and TuMV infection, while AP2-EREBP and C3H were the TF families involved in CMV and TCV infections. Moreover, analysis of miRNAs during CMV and TuMV and CMV and TCV infections have demonstrated the role of miRNAs in the down regulation of host genes in response to viral infections. These results identified the commonly expressed virus-responsive genes and pathways during plant-virus interaction which might develop novel antiviral strategies for improving plant resistance to mixed viral infections.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-00925-3.

Co-expression Networks From Gene Expression Variability Between Genetically Identical Seedlings Can Reveal Novel Regulatory Relationships

Co-expression networks are a powerful tool to understand gene regulation. They have been used to identify new regulation and function of genes involved in plant development and their response to the environment. Up to now, co-expression networks have been inferred using transcriptomes generated on plants experiencing genetic or environmental perturbation, or from expression time series. We propose a new approach by showing that co-expression networks can be constructed in the absence of genetic and environmental perturbation, for plants at the same developmental stage. For this, we used transcriptomes that were generated from genetically identical individual plants that were grown under the same conditions and for the same amount of time. Twelve time points were used to cover the 24-h light/dark cycle. We used variability in gene expression between individual plants of the same time point to infer a co-expression network. We show that this network is biologically relevant and use it to suggest new gene functions and to identify new targets for the transcriptional regulators GI, PIF4, and PRR5. Moreover, we find different co-regulation in this network based on changes in expression between individual plants, compared to the usual approach requiring environmental perturbation. Our work shows that gene co-expression networks can be identified using variability in gene expression between individual plants, without the need for genetic or environmental perturbations. It will allow further exploration of gene regulation in contexts with subtle differences between plants, which could be closer to what individual plants in a population might face in the wild.

Weighted gene coexpression network analysis-based identification of key modules and hub genes associated with drought sensitivity in rice

BACKGROUND

Drought stress is an adverse factor with deleterious effects on several aspects of rice growth. However, the mechanism underlying drought resistance in rice remains unclear. To understand the molecular mechanism of the drought response in rice, drought-sensitive CSSL (Chromosome Single-substitution Segment Line) PY6 was used to map QTLs of sensitive phenotypes and to reveal the impact of the QTLs on transcriptional profiling.

RESULTS

The QTL dss-1 was mapped onto the short arm of chromosome 1 of rice. According to transcriptomic analysis, the identified differentially expressed genes (DEGs) exhibited a downregulated pattern and were mainly enriched in photosynthesis-related GO terms, indicating that photosynthesis was greatly inhibited under drought. Further, according to weighted gene coexpression network analysis (WGCNA), specific gene modules (designating a group of genes with a similar expression pattern) were strongly correlated with H₂O₂ (4 modules) and MDA (3 modules), respectively. Likewise, GO analysis revealed that the photosynthesis-related GO terms were consistently overrepresented in H₂O₂-correlated modules. Functional annotation of the differentially expressed hub genes (DEHGs) in the H₂O₂ and MDA-correlated modules revealed cross-talk between abiotic and biotic stress responses for these genes, which were annotated as encoding WRKYs and PR family proteins, were notably differentially expressed between PY6 and PR403.

CONCLUSIONS

We speculated that drought-induced photosynthetic inhibition leads to H₂O₂ and MDA accumulation, which can then trigger the reprogramming of the rice transcriptome, including the hub genes involved in ROS scavenging, to prevent oxidative stress damage. Our results shed light on and provide deep insight into the drought resistance mechanism in rice.

Comparative Transcriptomics and Co-Expression Networks Reveal Tissue- and Genotype-Specific Responses of qDTYs to Reproductive-Stage Drought Stress in Rice (Oryza sativa L.)

Rice (Oryza sativa L.) is more sensitive to drought stress than other cereals. To dissect molecular mechanisms underlying drought-tolerant yield in rice, we applied differential expression and co-expression network approaches to transcriptomes from flag-leaf and emerging panicle tissues of a drought-tolerant yield introgression line, DTY-IL, and the recurrent parent Swarna, under moderate reproductive-stage drought stress. Protein turnover and efficient reactive oxygen species scavenging were found to be the driving factors in both tissues. In the flag-leaf, the responses further included maintenance of photosynthesis and cell wall reorganization, while in the panicle biosynthesis of secondary metabolites was found to play additional roles. Hub genes of importance in differential drought responses included an expansin in the flag-leaf and two peroxidases in the panicle. Overlaying differential expression data with allelic variation in DTY-IL quantitative trait loci allowed for the prioritization of candidate genes. They included a differentially regulated auxin-responsive protein, with DTY-IL-specific amino acid changes in conserved domains, as well as a protein kinase with a DTY-IL-specific frameshift in the C-terminal region. The approach highlights how the integration of differential expression and allelic variation can aid in the discovery of mechanism and putative causal contribution underlying quantitative trait loci for drought-tolerant yield.

Molecular plant responses to combined abiotic stresses put a spotlight on unknown and abundant genes

Environmental stresses such as drought, heat, and salinity limit plant development and agricultural productivity. While individual stresses have been studied extensively, much less is known about the molecular interaction of responses to multiple stresses. To address this problem, we investigated molecular responses of Arabidopsis to single, double, and triple combinations of salt, osmotic, and heat stresses. A metabolite profiling analysis indicated the production of specific compatible solutes depending on the nature of the stress applied. We found that in combination with other stresses, heat has a dominant effect on global gene expression and metabolite level patterns. Treatments that include heat stress lead to strongly reduced transcription of genes coding for abundant photosynthetic proteins and proteins regulating the cell life cycle, while genes involved in protein degradation are up-regulated. Under combined stress conditions, the plants shifted their metabolism to a survival state characterized by low productivity. Our work provides molecular evidence for the dangers for plant productivity and future world food security posed by heat waves resulting from global warming. We highlight candidate genes, many of which are functionally uncharacterized, for engineering plant abiotic stress tolerance.

Aromatic Amino Acids: A Complex Network Ripe for Future Exploration

In plants, high carbon flux is committed to the biosynthesis of phenylalanine, tyrosine, and tryptophan, owing to their roles not only in the production of proteins, but also as precursors to thousands of primary and specialized metabolites. The core plastidial pathways that supply the majority of aromatic amino acids (AAAs) have previously been described in detail. More recently, the discovery of cytosolic enzymes contributing to overall AAA biosynthesis, as well as the identification of intracellular transporters and the continuing elucidation of transcriptional and post-transcriptional regulatory mechanisms, have revealed the complexity of this intercompartmental metabolic network. Here, we review the latest breakthroughs in AAA production and use the newest findings to highlight both longstanding and newly developed questions.

Proteome Responses to Individual Pathogens and Abiotic Conditions in Rice Seedlings

Rice plants under field conditions experience various biotic and abiotic stresses and are adapted to survive using a molecular cross-talk of genes and their protein products based on the severity of a given stress. Seedlings of cultivated variety ASD16 (resistant to fungal disease, blast; tolerant to abiotic stress, salinity) were subjected to salt, drought, high temperature and low temperature stress as well as infection by Rhizoctonia solani and Xanthomonas oryzae pv. oryzae (causing reemerging diseases such as sheath blight and leaf blight), respectively, the sheath blight and bacterial leaf blight pathogens. Leaf proteome was analyzed using two-dimensional electrophoresis and differentially expressed proteins were identified using mass spectrometry. In addition to many other differentially expressed proteins, acidic endochitinase was found to be upregulated during fungal infection and drought treatment, and a germin-like protein upregulated during fungal infection and high temperature stress. These two proteins were further validated at the gene expression level using reverse transcription-PCR in dual stress experiments. Pot culture plants were subjected to fungal infection followed by drought and drought followed by fungal infection to validate chitinase gene expression. Similarly, plants subjected to fungal infections followed by high temperature stress and vice versa were used to validate the expression of germin-like protein-coding gene. The results of the present study indicate that chitinase and germin-like protein are potential targets for further exploration to develop rice plants resistant or tolerant to biotic and abiotic stresses.

Microarray analysis of transcriptional responses to salt and drought stress in Arabidopsis thaliana

Microarray expression profile analysis is a useful approach to increase our knowledge about genes involved in regulatory networks and signal transduction pathways related to abiotic stress tolerance. Salt and drought, as two important abiotic stresses, adversely affect plant productivity in the world every year. To understand stress response mechanisms and identify genes and proteins which play critical roles in these mechanisms, the study of individual genes and proteins cannot be considered as an effective approach. On the other hand, the availability of new global data provides us an effective way to shed some light on the central role of molecules involved in stress response mechanisms in the plant. A meta-analysis of salt and drought stress responses was carried out using 38 samples of different experiments from leaves and roots of Arabidopsis plants exposed to drought and salt stresses. We figured out the number of differentially expressed genes (DEGs) was higher in roots under both stresses. Also, we found that the number of common DEGs under both stresses was more in roots and also the number of common DEGs in both tissues under salt stress was more than drought stress. The highest percent of DEGs was related to cell and cell part (about 87%). Around 9% and 7% of DEGs in roots and leaves encoded transcription factors, respectively. Network analysis revealed that three transcription factor families HSF, AP2/ERF and C2H2, may have critical roles in salt and drought stress response mechanisms in Arabidopsis ​and some proteins like STZ may be introduced as a new candidate gene for enhancing salt and drought tolerance in crop plants.

Molecular Effects of Xylella fastidiosa and Drought Combined Stress in Olive Trees

Due to global climate change, complex combinations of stresses are expected to occur, among which the interaction between pathogens and drought stress may have a significant effect on growth and yield. In this study, the Xylella fastidiosa (Xf)-resistant cultivar Leccino and the susceptible one Cellina di Nardò were subjected to (a) individual drought stress, (b) Xf infection and (c) combination of both stress conditions. Here we report the physiological response to stresses in water content in leaves and the modulation in the expression level of seven genes responsive to plant water status and pathogen infection. In Xf-resistant plants, higher expression levels are reported for genes belonging to ROS-scavenging systems and for genes involved in pathogen stress (pathogenesis-related, PR, and leucine-rich repeat genes, LRR-RLK). However, PR and LRR-RLK were not further induced by water deficit. Interestingly, the genes related to drought response (aquaporin, PIP2.1, dehydration responsive element binding, DREB, and dehydrin, DHN), which induction was higher in Cellina di Nardò compared to Leccino during drought stress, was poorly induced in Xf-susceptible plants when Xf occur. Conversely, DHN was induced by Xf presence in Leccino. These results were consistent with observations on water content. Indeed, response was similar in Leccino regardless kind of stress or combination, whereas a strong reduction was observed in Xf-susceptible plants infected by Xf or in presence of combined stresses. Thus, the reported findings indicate that resistance of Leccino to Xf could be linked to its lower resistance to water stress, probably leading to the activation of alternative defense pathways that support the plant in Xf response.

Gene Modules Co-regulated with Biosynthetic Gene Clusters for Allelopathy between Rice and Barnyardgrass

Allelopathy is a central process in crop–weed interactions and is mediated by the release of allelochemicals that result in adverse growth effects on one or the other plant in the interaction. The genomic mechanism for the biosynthesis of many critical allelochemicals is unknown but may involve the clustering of non-homologous biosynthetic genes involved in their formation and regulatory gene modules involved in controlling the coordinated expression within these gene clusters. In this study, we used the transcriptomes from mono- or co-cultured rice and barnyardgrass to investigate the nature of the gene clusters and their regulatory gene modules involved in the allelopathic interactions of these two plants. In addition to the already known biosynthetic gene clusters in barnyardgrass we identified three potential new clusters including one for quercetin biosynthesis and potentially involved in allelopathic interaction with rice. Based on the construction of gene networks, we identified one gene regulatory module containing hub transcription factors, significantly positively co-regulated with both the momilactone A and phytocassane clusters in rice. In barnyardgrass, gene modules and hub genes co-expressed with the gene clusters responsible for 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA) biosynthesis were also identified. In addition, we found three genes in barnyardgrass encoding indole-3-glycerolphosphate synthase that regulate the expression of the DIMBOA cluster. Our findings offer new insights into the regulatory mechanisms of biosynthetic gene clusters involved in allelopathic interactions between rice and barnyardgrass, and have potential implications in controlling weeds for crop protection.

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

Abiotic stress tolerance is a complex trait regulated by multiple genes and gene networks in plants. A range of abiotic stresses are known to limit rice productivity. Meta-transcriptomics has emerged as a powerful approach to decipher stress-associated molecular network in model crops. However, retaining specificity of gene expression in tolerant and susceptible genotypes during meta-transcriptome analysis is important for understanding genotype-dependent stress tolerance mechanisms. Addressing this aspect, we describe here "abiotic stress tolerant" (ASTR) genes and networks specifically and differentially expressing in tolerant rice genotypes in response to different abiotic stress conditions. We identified 6,956 ASTR genes, key hub regulatory genes, transcription factors, and functional modules having significant association with abiotic stress-related ontologies and cis-motifs. Out of the 6956 ASTR genes, 73 were co-located within the boundary of previously identified abiotic stress trait-related quantitative trait loci. Functional annotation of 14 uncharacterized ASTR genes is proposed using multiple computational methods. Around 65% of the top ASTR genes were found to be differentially expressed in at least one of the tolerant genotypes under different stress conditions (cold, salt, drought, or heat) from publicly available RNAseq data comparison. The candidate ASTR genes specifically associated with tolerance could be utilized for engineering rice and possibly other crops for broad-spectrum tolerance to abiotic stresses.

QTL mapping for maize starch content and candidate gene prediction combined with co-expression network analysis

A major QTL Qsta9.1 was identified on chromosome 9, combined with GWAS, and co-expression network analysis showed that GRMZM2G110929 and GRMZM5G852704 are the potential candidates for association with maize kernel starch content. Increasing maize kernel starch content may not only lead to higher maize kernel yields and qualities, but also help meet industry demands. By using the intermated B73 × Mo17 population, QTLs were mapped for starch content in this study. A major QTL Qsta9.1 was detected in a 1.7 Mb interval on chromosome 9 and validated by allele frequency analysis in extreme tails of a newly constructed segregating population. According to genome-wide association study (GWAS) based on genotyping of a natural population, we identified a significant SNP for starch content within the ORF region of GRMZM5G852704_T01 colocalized with QTL Qsta9.1. Co-expression network analysis was also conducted, and 28 modules were constructed during six seed developmental stages. Functional enrichment was performed for each module, and one module showed the most possibility for the association with carbohydrate-related processes. In this module, one transcripts GRMZM2G110929_T01 located in the Qsta9.1 assigned 1.7 Mb interval encoding GLABRA2 expression modulator. Its expression level in B73 was lower than that in Mo17 across all seed developmental stages, implying the possibility for the candidate gene of Qsta9.1. Our studies combined GWAS, mRNA profiling, and traditional QTL analyses to identify a major locus for controlling seed starch content in maize.

Reconstruction and inference of the Lactococcus lactis MG1363 gene co-expression network

Lactic acid bacteria are Gram-positive bacteria used throughout the world in many industrial applications for their acidification, flavor and texture formation attributes. One of the species, Lactococcus lactis, is employed for the production of fermented milk products like cheese, buttermilk and quark. It ferments lactose to lactic acid and, thus, helps improve the shelf life of the products. Many physiological and transcriptome studies have been performed in L. lactis in order to comprehend and improve its biotechnological assets. Using large amounts of transcriptome data to understand and predict the behavior of biological processes in bacterial or other cell types is a complex task. Gene networks enable predicting gene behavior and function in the context of transcriptionally linked processes. We reconstruct and present the gene co-expression network (GCN) for the most widely studied L. lactis strain, MG1363, using publicly available transcriptome data. Several methods exist to generate and judge the quality of GCNs. Different reconstruction methods lead to networks with varying structural properties, consequently altering gene clusters. We compared the structural properties of the MG1363 GCNs generated by five methods, namely Pearson correlation, Spearman correlation, GeneNet, Weighted Gene Co-expression Network Analysis (WGCNA), and Sparse PArtial Correlation Estimation (SPACE). Using SPACE, we generated an L. lactis MG1363 GCN and assessed its quality using modularity and structural and biological criteria. The L. lactis MG1363 GCN has structural properties similar to those of the gold-standard networks of Escherichia coli K-12 and Bacillus subtilis 168. We showcase that the network can be used to mine for genes with similar expression profiles that are also generally linked to the same biological process.

Gene co-expression network analysis identifies trait-related modules in Arabidopsis thaliana

A comprehensive network of the Arabidopsis transcriptome was analyzed and may serve as a valuable resource for candidate gene function investigations. A web tool to explore module information was also provided. Arabidopsis thaliana is a widely studied model plant whose transcriptome has been substantially profiled in various tissues, development stages and other conditions. These data can be reused for research on gene function through a systematic analysis of gene co-expression relationships. We collected microarray data from National Center for Biotechnology Information Gene Expression Omnibus, identified modules of co-expressed genes and annotated module functions. These modules were associated with experiments/traits, which provided potential signature modules for phenotypes. Novel heat shock proteins were implicated according to guilt by association. A higher-order module networks analysis suggested that the Arabidopsis network can be further organized into 15 meta-modules and that a chloroplast meta-module has a distinct gene expression pattern from the other 14 meta-modules. A comparison with the rice transcriptome revealed preserved modules and KEGG pathways. All the module gene information was available from an online tool at http://bioinformatics.fafu.edu.cn/arabi/ . Our findings provide a new source for future gene discovery in Arabidopsis.

Revealing shared differential co-expression profiles in rice infected by virus from reoviridae and sequiviridae group

Differential co-expression is a cutting-edge approach to analyze gene expression data and identify both shared and divergent expression patterns. The availability of high-throughput gene expression datasets and efficient computational approaches have unfolded the opportunity to a systems level understanding of functional genomics of different stresses with respect to plants. We performed the meta-analysis of the available microarray data for reoviridae and sequiviridae infection in rice with the aim to identify the shared gene co-expression profile. The microarray data were downloaded from ArrayExpress and analyzed through a modified Weighted Gene Co-expression Network Analysis (WGCNA) protocol. WGCNA clustered the genes based on the expression intensities across the samples followed by identification of modules, eigengenes, principal components, topology overlap, module membership and module preservation. The module preservation analysis identified 4 modules; salmon (638 genes), midnightblue (584 genes), lightcyan (686 genes) and red (562 genes), which are highly preserved in both the cases. The networks in case of reoviridae infection showed neatly packed clusters whereas, in sequiviridae, the clusters were loosely connected which is due to the differences in the correlation values. We also identified 83 common transcription factors targeting the hub genes from all the identified modules. This study provides a coherent view of the comparative aspect of the expression of common genes involved in different virus infections which may aid in the identification of novel targets and development of new intervention strategy against the virus.

Cross-Talk Signaling in Rice During Combined Drought and Bacterial Blight Stress

Due to climatic changes, rice crop is affected by moisture deficit stress and pathogens. Tissue water limitation besides reducing growth rates, also renders the crop susceptible to the infection by Xanthomonas oryzae pv. oryzae (Xoo) that causes bacterial leaf blight. Independently, both drought adaptation and Xoo resistance have been extensively studied. Though the cross-talk between drought and Xoo stress responses have been explored from individual stress studies, examining the combinatorial stress response is limited in rice. Recently published combined stress studies showed that under the combined stress, maintenance of carbon assimilation is hindered and such response is regulated by overlapping cellular mechanisms that are different from either of the individual stresses. Several receptors, MAP kinases, transcription factors, and ribosomal proteins, are predicted for playing a role in cellular homeostasis and protects cells from combined stress effects. Here we provide a critical analysis of these aspects using information from the recently published combined stress literature. This review is useful for researchers to comprehend combinatorial stress response of rice plants to drought and Xoo.

Comparative transcriptome meta-analysis of Arabidopsis thaliana under drought and cold stress

Multiple environmental stresses adversely affect plant growth and development. Plants under multiple stress condition trigger cascade of signals and show response unique to specific stress as well as shared responses, common to individual stresses. Here, we aim to identify common and unique genetic components during stress response mechanisms liable for cross-talk between stresses. Although drought and cold stress have been widely studied, insignificant information is available about how their combination affects plants. To that end, we performed meta-analysis and co-expression network comparison of drought and cold stress response in Arabidopsis thaliana by analyzing 390 microarray samples belonging to 29 microarray studies. We observed 6120 and 7079 DEGs (differentially expressed genes) under drought and cold stress respectively, using Rank Product methodology. Statistically, 28% (2890) DEGs were found to be common in both the stresses (i.e.; drought and cold stress) with most of them having similar expression pattern. Further, gene ontology-based enrichment analysis have identified shared biological processes and molecular mechanisms such as—‘photosynthesis’, ‘respiratory burst’, ‘response to hormone’, ‘signal transduction’, ‘metabolic process’, ‘response to water deprivation’, which were affected under cold and drought stress. Forty three transcription factor families were found to be expressed under both the stress conditions. Primarily, WRKY, NAC, MYB, AP2/ERF and bZIP transcription factor family genes were highly enriched in all genes sets and were found to regulate 56% of common genes expressed in drought and cold stress. Gene co-expression network analysis by WGCNA (weighted gene co-expression network analysis) revealed 21 and 16 highly inter-correlated gene modules with specific expression profiles under drought and cold stress respectively. Detection and analysis of gene modules shared between two stresses revealed the presence of four consensus gene modules.

Gene co-expression network analysis reveals coordinated regulation of three characteristic secondary biosynthetic pathways in tea plant (Camellia sinensis)

BACKGROUND

The leaves of tea plants (Camellia sinensis) are used to produce tea, which is one of the most popular beverages consumed worldwide. The nutritional value and health benefits of tea are mainly related to three abundant characteristic metabolites; catechins, theanine and caffeine. Weighted gene co-expression network analysis (WGCNA) is a powerful system for investigating correlations between genes, identifying modules among highly correlated genes, and relating modules to phenotypic traits based on gene expression profiling. Currently, relatively little is known about the regulatory mechanisms and correlations between these three secondary metabolic pathways at the omics level in tea.

RESULTS

In this study, levels of the three secondary metabolites in ten different tissues of tea plants were determined, 87,319 high-quality unigenes were assembled, and 55,607 differentially expressed genes (DEGs) were identified by pairwise comparison. The resultant co-expression network included 35 co-expression modules, of which 20 modules were significantly associated with the biosynthesis of catechins, theanine and caffeine. Furthermore, we identified several hub genes related to these three metabolic pathways, and analysed their regulatory relationships using RNA-Seq data. The results showed that these hub genes are regulated by genes involved in all three metabolic pathways, and they regulate the biosynthesis of all three metabolites. It is notable that light was identified as an important regulator for the biosynthesis of catechins.

CONCLUSION

Our integrated omics-level WGCNA analysis provides novel insights into the potential regulatory mechanisms of catechins, theanine and caffeine metabolism, and the identified hub genes provide an important reference for further research on the molecular biology of tea plants.

Effect of abiotic and biotic stress factors analysis using machine learning methods in zebrafish

In order to understand the mechanisms underlying stress responses, meta-analysis of transcriptome is made to identify differentially expressed genes (DEGs) and their biological, molecular and cellular mechanisms in response to stressors. The present study is aimed at identifying the effect of abiotic and biotic stress factors, and it is found that several stress responsive genes are common for both abiotic and biotic stress factors in zebrafish. The meta-analysis of micro-array studies revealed that almost 4.7% i.e., 108 common DEGs are differentially regulated between abiotic and biotic stresses. This shows that there is a global coordination and fine-tuning of gene regulation in response to these two types of challenges. We also performed dimension reduction methods, principal component analysis, and partial least squares discriminant analysis which are able to segregate abiotic and biotic stresses into separate entities. The supervised machine learning model, recursive-support vector machine, could classify abiotic and biotic stresses with 100% accuracy using a subset of DEGs. Beside these methods, the random forests decision tree model classified five out of 8 stress conditions with high accuracy. Finally, Functional enrichment analysis revealed the different gene ontology terms, transcription factors and miRNAs factors in the regulation of stress responses.

Genome-wide characterization of the WRKY gene family in radish (Raphanus sativus L.) reveals its critical functions under different abiotic stresses

The radish WRKY gene family was genome-widely identified and played critical roles in response to multiple abiotic stresses. The WRKY is among the largest transcription factors (TFs) associated with multiple biological activities for plant survival, including control response mechanisms against abiotic stresses such as heat, salinity, and heavy metals. Radish is an important root vegetable crop and therefore characterization and expression pattern investigation of WRKY transcription factors in radish is imperative. In the present study, 126 putative WRKY genes were retrieved from radish genome database. Protein sequence and annotation scrutiny confirmed that RsWRKY proteins possessed highly conserved domains and zinc finger motif. Based on phylogenetic analysis results, RsWRKYs candidate genes were divided into three groups (Group I, II and III) with the number 31, 74, and 20, respectively. Additionally, gene structure analysis revealed that intron-exon patterns of the WRKY genes are highly conserved in radish. Linkage map analysis indicated that RsWRKY genes were distributed with varying densities over nine linkage groups. Further, RT-qPCR analysis illustrated the significant variation of 36 RsWRKY genes under one or more abiotic stress treatments, implicating that they might be stress-responsive genes. In total, 126 WRKY TFs were identified from the R. sativus genome wherein, 35 of them showed abiotic stress-induced expression patterns. These results provide a genome-wide characterization of RsWRKY TFs and baseline for further functional dissection and molecular evolution investigation, specifically for improving abiotic stress resistances with an ultimate goal of increasing yield and quality of radish.

Td4IN2: A drought-responsive durum wheat (Triticum durum Desf.) gene coding for a resistance like protein with serine/threonine protein kinase, nucleotide binding site and leucine rich domains

Wheat, the main food source for a third of world population, appears strongly under threat because of predicted increasing temperatures coupled to drought. Plant complex molecular response to drought stress relies on the gene network controlling cell reactions to abiotic stress. In the natural environment, plants are subjected to the combination of abiotic and biotic stresses. Also the response of plants to biotic stress, to cope with pathogens, involves the activation of a molecular network. Investigations on combination of abiotic and biotic stresses indicate the existence of cross-talk between the two networks and a kind of overlapping can be hypothesized. In this work we describe the isolation and characterization of a drought-related durum wheat (Triticum durum Desf.) gene, identified in a previous study, coding for a protein combining features of NBS-LRR type resistance protein with a S/TPK domain, involved in drought stress response. This is one of the few examples reported where all three domains are present in a single protein and, to our knowledge, it is the first report on a gene specifically induced by drought stress and drought-related conditions, with this particular structure.

Differences and commonalities of plant responses to single and combined stresses

In natural or agricultural environments, plants are constantly exposed to a wide range of biotic and abiotic stresses. Given the forecasted global climate changes, plants will cope with heat waves, drought periods and pathogens at the same time or consecutively. Heat and drought cause opposing physiological responses, while pathogens may or may not profit from climate changes depending on their lifestyle. Several studies have been conducted to find stress-specific signatures or stress-independent commonalities. Previously this has been done by comparing different single stress treatments. This approach has been proven difficult since most studies, comparing single and combined stress conditions, have come to the conclusion that each stress treatment results in specific transcriptional changes. Although transcriptional changes at the level of individual genes are highly variable and stress-specific, central metabolic and signaling responses seem to be common, often leading to an overall reduced plant growth. Understanding how specific transcriptional changes are linked to stress adaptations and identifying central hubs controlling this interaction will be the challenge for the coming years. In this review, we will summarize current knowledge on plant responses to different individual and combined stresses and try to find a common thread potentially underlying these responses. We will begin with a brief summary of known physiological, metabolic, transcriptional and hormonal responses to individual stresses, elucidate potential commonalities and conflicts and finally we will describe results obtained during combined stress experiments. Here we will concentrate on simultaneous application of stress conditions but we will also touch consequences of sequential stress treatments.

Identifying gene coexpression networks underlying the dynamic regulation of wood-forming tissues in Populus under diverse environmental conditions

Trees modify wood formation through integration of environmental and developmental signals in complex but poorly defined transcriptional networks, allowing trees to produce woody tissues appropriate to diverse environmental conditions. In order to identify relationships among genes expressed during wood formation, we integrated data from new and publically available datasets in Populus. These datasets were generated from woody tissue and include transcriptome profiling, transcription factor binding, DNA accessibility and genome-wide association mapping experiments. Coexpression modules were calculated, each of which contains genes showing similar expression patterns across experimental conditions, genotypes and treatments. Conserved gene coexpression modules (four modules totaling 8398 genes) were identified that were highly preserved across diverse environmental conditions and genetic backgrounds. Functional annotations as well as correlations with specific experimental treatments associated individual conserved modules with distinct biological processes underlying wood formation, such as cell-wall biosynthesis, meristem development and epigenetic pathways. Module genes were also enriched for DNase I hypersensitivity footprints and binding from four transcription factors associated with wood formation. The conserved modules are excellent candidates for modeling core developmental pathways common to wood formation in diverse environments and genotypes, and serve as testbeds for hypothesis generation and testing for future studies.

The rice OsNAC6 transcription factor orchestrates multiple molecular mechanisms involving root structural adaptions and nicotianamine biosynthesis for drought tolerance

Drought has a serious impact on agriculture worldwide. A plant's ability to adapt to rhizosphere drought stress requires reprogramming of root growth and development. Although physiological studies have documented the root adaption for tolerance to the drought stress, underlying molecular mechanisms is still incomplete, which is essential for crop engineering. Here, we identified OsNAC6-mediated root structural adaptations, including increased root number and root diameter, which enhanced drought tolerance. Multiyear drought field tests demonstrated that the grain yield of OsNAC6 root-specific overexpressing transgenic rice lines was less affected by drought stress than were nontransgenic controls. Genome-wide analyses of loss- and gain-of-function mutants revealed that OsNAC6 up-regulates the expression of direct target genes involved in membrane modification, nicotianamine (NA) biosynthesis, glutathione relocation, 3'-phophoadenosine 5'-phosphosulphate accumulation and glycosylation, which represent multiple drought tolerance pathways. Moreover, overexpression of NICOTIANAMINE SYNTHASE genes, direct targets of OsNAC6, promoted the accumulation of the metal chelator NA and, consequently, drought tolerance. Collectively, OsNAC6 orchestrates novel molecular drought tolerance mechanisms and has potential for the biotechnological development of high-yielding crops under water-limiting conditions.

Aquaporins as potential drought tolerance inducing proteins: Towards instigating stress tolerance

Aquaporins (AQPs) are primarily involved in maintaining cellular water homeostasis. Their role in diverse physiological processes has fascinated plant scientists for more than a decade, particularly concerning abiotic stresses. Increasing examples of evidence in various crop plants indicate that the AQPs are responsible for precise regulation of water movement and consequently play a crucial role in the drought stress tolerance. Since drought is one of the major abiotic stresses affecting agricultural production worldwide, it has become a critical agenda to focus research on the development of drought tolerant crop plants. AQPs can act as key candidate molecules to confront this issue. Hence, there is an important need to explore the potential of AQPs by understanding the molecular mechanisms and pathways through which they induce drought tolerance. Moreover, the signalling network/s involved in such pathways needs to be mined and understood correctly, and that may lead to the development of drought tolerance in crop plants. In the present review, opportunity and challenges regarding the efficient utilization of AQP-related information is presented and discussed. The complied information and the discussion will be helpful for designing future experiments and to set the specific goals for the enhancement of drought tolerance in crop plants. Biological Significance Knowledge on the role of AQPs in maintaining cellular water homeostasis has given new hope for developing drought tolerance in crop plants. Since drought is one of the major abiotic stresses affecting agricultural production worldwide, it has become a critical agenda to focus research on the development of drought-tolerant crop plants. AQPs can act as key candidate molecules to solve this problem through genetic engineering. For this, it is important to understand the molecular mechanisms and inter-related pathways through which AQPs induce drought tolerance and to explore the signaling network/s involved in such pathways.

Genetic architecture of cold tolerance in rice (Oryza sativa) determined through high resolution genome-wide analysis

Cold temperature is an important abiotic stress which negatively affects morphological development and seed production in rice (Oryza sativa L.). At the seedling stage, cold stress causes poor germination, seedling injury and poor stand establishment; and at the reproductive stage cold decreases seed yield. The Rice Diversity Panel 1 (RDP1) is a global collection of over 400 O. sativa accessions representing the five major subpopulations from the INDICA and JAPONICA varietal groups, with a genotypic dataset consisting of 700,000 SNP markers. The objectives of this study were to evaluate the RDP1 accessions for the complex, quantitatively inherited cold tolerance traits at the germination and reproductive stages, and to conduct genome-wide association (GWA) mapping to identify SNPs and candidate genes associated with cold stress at these stages. GWA mapping of the germination index (calculated as percent germination in cold divided by warm treatment) revealed 42 quantitative trait loci (QTLs) associated with cold tolerance at the seedling stage, including 18 in the panel as a whole, seven in temperate japonica, six in tropical japonica, 14 in JAPONICA, and nine in INDICA, with five shared across all subpopulations. Twenty-two of these QTLs co-localized with 32 previously reported cold tolerance QTLs. GWA mapping of cold tolerance at the reproductive stage detected 29 QTLs, including seven associated with percent sterility, ten with seed weight per panicle, 14 with seed weight per plant and one region overlapping for two traits. Fifteen co-localized with previously reported QTLs for cold tolerance or yield components. Candidate gene ontology searches revealed these QTLs were associated with significant enrichment for genes related to with lipid metabolism, response to stimuli, response to biotic stimuli (suggesting cross-talk between biotic and abiotic stresses), and oxygen binding. Overall the JAPONICA accessions were more tolerant to cold stress than INDICA accessions.

Genome-wide association analysis of seedling traits in diverse Sorghum germplasm under thermal stress

BACKGROUND

Climate variability due to fluctuation in temperature is a worldwide concern that imperils crop production. The need to understand how the germplasm variation in major crops can be utilized to aid in discovering and developing breeding lines that can withstand and adapt to temperature fluctuations is more necessary than ever. Here, we analyzed the genetic variation associated with responses to thermal stresses in a sorghum association panel (SAP) representing major races and working groups to identify single nucleotide polymorphisms (SNPs) that are associated with resilience to temperature stress in a major cereal crop.

RESULTS

The SAP exhibited extensive variation for seedling traits under cold and heat stress. Genome-wide analyses identified 30 SNPs that were strongly associated with traits measured at seedling stage under cold stress and tagged genes that act as regulators of anthocyanin expression and soluble carbohydrate metabolism. Meanwhile, 12 SNPs were significantly associated with seedling traits under heat stress and these SNPs tagged genes that function in sugar metabolism, and ion transport pathways. Evaluation of co-expression networks for genes near the significantly associated SNPs indicated complex gene interactions for cold and heat stresses in sorghum. We focused and validated the expression of four genes in the network of Sb06g025040, a basic-helix-loop-helix (bHLH) transcription factor that was proposed to be involved in purple color pigmentation of leaf, and observed that genes in this network were upregulated during cold stress in a moderately tolerant line as compared to the more sensitive line.

CONCLUSION

This study facilitated the tagging of genome regions associated with variation in seedling traits of sorghum under cold and heat stress. These findings show the potential of genotype information for development of temperature resilient sorghum cultivars and further characterization of genes and their networks responsible for adaptation to thermal stresses. Knowledge on the gene networks from this research can be extended to the other cereal crops to better understand the genetic basis of resilience to temperature fluctuations during plant developmental stages.

Statistical Approaches for Gene Selection, Hub Gene Identification and Module Interaction in Gene Co-Expression Network Analysis: An Application to Aluminum Stress in Soybean (Glycine max L.)

Selection of informative genes is an important problem in gene expression studies. The small sample size and the large number of genes in gene expression data make the selection process complex. Further, the selected informative genes may act as a vital input for gene co-expression network analysis. Moreover, the identification of hub genes and module interactions in gene co-expression networks is yet to be fully explored. This paper presents a statistically sound gene selection technique based on support vector machine algorithm for selecting informative genes from high dimensional gene expression data. Also, an attempt has been made to develop a statistical approach for identification of hub genes in the gene co-expression network. Besides, a differential hub gene analysis approach has also been developed to group the identified hub genes into various groups based on their gene connectivity in a case vs. control study. Based on this proposed approach, an R package, i.e., dhga (https://cran.r-project.org/web/packages/dhga) has been developed. The comparative performance of the proposed gene selection technique as well as hub gene identification approach was evaluated on three different crop microarray datasets. The proposed gene selection technique outperformed most of the existing techniques for selecting robust set of informative genes. Based on the proposed hub gene identification approach, a few number of hub genes were identified as compared to the existing approach, which is in accordance with the principle of scale free property of real networks. In this study, some key genes along with their Arabidopsis orthologs has been reported, which can be used for Aluminum toxic stress response engineering in soybean. The functional analysis of various selected key genes revealed the underlying molecular mechanisms of Aluminum toxic stress response in soybean.

RECoN: Rice Environment Coexpression Network for Systems Level Analysis of Abiotic-Stress Response

Transcriptional profiling is a prevalent and powerful approach for capturing the response of crop plants to environmental stresses, e.g., response of rice to drought. However, functionally interpreting the resulting genome-wide gene expression changes is severely hampered by the large gaps in our genomic knowledge about which genes work together in cellular pathways/processes in rice. Here, we present a new web resource - RECoN - that relies on a network-based approach to go beyond currently limited annotations in delineating functional and regulatory perturbations in new rice transcriptome datasets generated by a researcher. To build RECoN, we first enumerated 1,744 abiotic stress-specific gene modules covering 28,421 rice genes (>72% of the genes in the genome). Each module contains a group of genes tightly coexpressed across a large number of environmental conditions and, thus, is likely to be functionally coherent. When a user provides a new differential expression profile, RECoN identifies modules substantially perturbed in their experiment and further suggests deregulated functional and regulatory mechanisms based on the enrichment of current annotations within the predefined modules. We demonstrate the utility of this resource by analyzing new drought transcriptomes of rice in three developmental stages, which revealed large-scale insights into the cellular processes and regulatory mechanisms involved in common and stage-specific drought responses. RECoN enables biologists to functionally explore new data from all abiotic stresses on a genome-scale and to uncover gene candidates, including those that are currently functionally uncharacterized, for engineering stress tolerance.

Global Transcriptome Analysis of Combined Abiotic Stress Signaling Genes Unravels Key Players in Oryza sativa L.: An In silico Approach

Combined abiotic stress (CAbS) affects the field grown plants simultaneously. The multigenic and quantitative nature of uncontrollable abiotic stresses complicates the process of understanding the stress response by plants. Considering this, we analyzed the CAbS response of C3 model plant, Oryza sativa by meta-analysis. The datasets of commonly expressed genes by drought, salinity, submergence, metal, natural expression, biotic, and abiotic stresses were data mined through publically accessible transcriptomic abiotic stress (AbS) responsive datasets. Of which 1,175, 12,821, and 42,877 genes were commonly expressed in meta differential, individual differential, and unchanged expressions respectively. Highly regulated 100 differentially expressed AbS genes were derived through integrative meta-analysis of expression data (INMEX). Of this 30 genes were identified from AbS gene families through expression atlas that were computationally analyzed for their physicochemical properties. All AbS genes were physically mapped against O. sativa genome. Comparative mapping of these genes demonstrated the orthologous relationship with related C4 panicoid genome. In silico expression analysis of these genes showed differential expression patterns in different developmental tissues. Protein-protein interaction of these genes, represented the complexity of AbS. Computational expression profiling of candidate genes in response to multiple stresses suggested the putative involvement of OS05G0350900, OS02G0612700, OS05G0104200, OS03G0596200, OS12G0225900, OS07G0152000, OS08G0119500, OS06G0594700, and Os01g0393100 in CAbS. These potential candidate genes need to be studied further to decipher their functional roles in AbS dynamics.