Functional characterization of drought-responsive modules and genes in Oryza sativa: a network-based approach

Stress phenotyping analysis leveraging autofluorescence image sequences with machine learning

Background

Autofluorescence-based imaging has the potential to non-destructively characterize the biochemical and physiological properties of plants regulated by genotypes using optical properties of the tissue. A comparative study of stress tolerant and stress susceptible genotypes of Brassica rapa with respect to newly introduced stress-based phenotypes using machine learning techniques will contribute to the significant advancement of autofluorescence-based plant phenotyping research.

Methods

Autofluorescence spectral images have been used to design a stress detection classifier with two classes, stressed and non-stressed, using machine learning algorithms. The benchmark dataset consisted of time-series image sequences from three Brassica rapa genotypes (CC, R500, and VT), extreme in their morphological and physiological traits captured at the high-throughput plant phenotyping facility at the University of Nebraska-Lincoln, USA. We developed a set of machine learning-based classification models to detect the percentage of stressed tissue derived from plant images and identified the best classifier. From the analysis of the autofluorescence images, two novel stress-based image phenotypes were computed to determine the temporal variation in stressed tissue under progressive drought across different genotypes, i.e., the average percentage stress and the moving average percentage stress.

Results

The study demonstrated that both the computed phenotypes consistently discriminated against stressed versus non-stressed tissue, with oilseed type (R500) being less prone to drought stress relative to the other two Brassica rapa genotypes (CC and VT).

Conclusion

Autofluorescence signals from the 365/400 nm excitation/emission combination were able to segregate genotypic variation during a progressive drought treatment under a controlled greenhouse environment, allowing for the exploration of other meaningful phenotypes using autofluorescence image sequences with significance in the context of plant science.

Delineating the tissue-mediated drought stress governed tuning of conserved miR408 and its targets in rice

Engineering drought tolerance in rice needs to focus on regulators that enhance tolerance while boosting plant growth and vigor. The present study delineated the concealed function and tissue-mediated interplay of the miR408/target module in imparting drought stress tolerance in rice. The plant miR408 family comprises three dominant mature forms (21 nt), including a distinct monocot variant (F-7 with 5' C) and is divided into six groups. miR408 majorly cleaves genes belonging to the blue copper protein in addition to several other species-specific targets in plants. Comparative sequence analysis in 4726 rice accessions identified 22 sequence variants (SNP and InDELs) in its promoter (15) and pre-miR408 region. Haplotype analysis of the sequence variants indicated eight haplotypes (three: Japonica-specific and five: Indica-specific) of the miR408 promoter. In drought-tolerant Nagina 22, miR408 follows flag leaf preferential expression. Under drought conditions, its levels are upregulated in flag leaf and roots which seems to be regulated by a differential fraction of methylated cytosines (mCs) in the precursor region. The active pool of miR408 regulated targets under control and drought conditions is impacted by the tissue type. Comparative expression analysis of the miR408/target module under different sets of conditions features 83 targets exhibiting antagonistic expression in rice, out of which 12 genes, including four PLANTACYANINS (OsUCL6, 7, 9 and 30), PIRIN, OsLPR1, OsCHUP1, OsDOF12, OsBGLU1, glycine-rich cell wall gene, OsDUT, and OsERF7, are among the high confidence targets. Further, overexpression of MIR408 in drought-sensitive rice cultivar (PB1) leads to the massive enhancement of vegetative growth in rice with improved ETR and Y(II) and enhanced dehydration stress tolerance. The above results suggest that miR408 is likely to act as a positive regulator of growth and vigor, as well as dehydration stress, making it a potential candidate for engineering drought tolerance in rice.

Identification of Key Gene Network Modules and Hub Genes Associated with Wheat Response to Biotic Stress Using Combined Microarray Meta-analysis and WGCN Analysis

Wheat (Triticum aestivum) is one of the major crops worldwide and a primary source of calories for human food. Biotic stresses such as fungi, bacteria, and diseases limit wheat production. Although plant breeding and genetic engineering for biotic stress resistance have been suggested as promising solutions to handle losses caused by biotic stress factors, a comprehensive understanding of molecular mechanisms and identifying key genes is a critical step to obtaining success. Here, a network-based meta-analysis approach based on two main statistical methods was used to identify key genes and molecular mechanisms of the wheat response to biotic stress. A total of 163 samples (21,792 genes) from 10 datasets were analyzed. Fisher Z test based on the p-value and REM method based on effect size resulted in 533 differentially expressed genes (p < 0.001 and FDR < 0.001). WGCNA analysis using a dynamic tree-cutting algorithm was used to construct a co-expression network and three significant modules were detected. The modules were significantly enriched by 16 BP terms and 4 KEGG pathways (Benjamini-Hochberg FDR < 0.001). A total of nine hub genes (a top 1.5% of genes with the highest degree) were identified from the constructed network. The identification of DE genes, gene-gene co-expressing network, and hub genes may contribute to uncovering the molecular mechanisms of the wheat response to biotic stress.

NetREx: Network-based Rice Expression Analysis Server for abiotic stress conditions

Recent focus on transcriptomic studies in food crops like rice, wheat and maize provide new opportunities to address issues related to agriculture and climate change. Re-analysis of such data available in public domain supplemented with annotations across molecular hierarchy can be of immense help to the plant research community, particularly co-expression networks representing transcriptionally coordinated genes that are often part of the same biological process. With this objective, we have developed NetREx, a Network-based Rice Expression Analysis Server, that hosts ranked co-expression networks of Oryza sativa using publicly available messenger RNA sequencing data across uniform experimental conditions. It provides a range of interactable data viewers and modules for analysing user-queried genes across different stress conditions (drought, flood, cold and osmosis) and hormonal treatments (abscisic and jasmonic acid) and tissues (root and shoot). Subnetworks of user-defined genes can be queried in pre-constructed tissue-specific networks, allowing users to view the fold change, module memberships, gene annotations and analysis of their neighbourhood genes and associated pathways. The web server also allows querying of orthologous genes from Arabidopsis, wheat, maize, barley and sorghum. Here, we demonstrate that NetREx can be used to identify novel candidate genes and tissue-specific interactions under stress conditions and can aid in the analysis and understanding of complex phenotypes linked to stress response in rice.

Database URL: https://bioinf.iiit.ac.in/netrex/index.html

Identification of Potential Cytokinin Responsive Key Genes in Rice Treated With Trans-Zeatin Through Systems Biology Approach

Rice is an important staple food grain consumed by most of the population around the world. With climate and environmental changes, rice has undergone a tremendous stress state which has impacted crop production and productivity. Plant growth hormones are essential component that controls the overall outcome of the growth and development of the plant. Cytokinin is a hormone that plays an important role in plant immunity and defense systems. Trans-zeatin is an active form of cytokinin that can affect plant growth which is mediated by a multi-step two-component phosphorelay system that has different roles in various developmental stages. Systems biology is an approach for pathway analysis to trans-zeatin treated rice that could provide a deep understanding of different molecules associated with them. In this study, we have used a weighted gene co-expression network analysis method to identify the functional modules and hub genes involved in the cytokinin pathway. We have identified nine functional modules comprising of different hub genes which contribute to the cytokinin signaling route. The biological significance of these identified hub genes has been tested by applying well-proven statistical techniques to establish the association with the experimentally validated QTLs and annotated by the DAVID server. The establishment of key genes in different pathways has been confirmed. These results will be useful to design new stress-resistant cultivars which can provide sustainable yield in stress-specific conditions.

Combining Genome and Gene Co-expression Network Analyses for the Identification of Genes Potentially Regulating Salt Tolerance in Rice

Salinity stress tolerance is a complex polygenic trait involving multi-molecular pathways. This study aims to demonstrate an effective transcriptomic approach for identifying genes regulating salt tolerance in rice. The chromosome segment substitution lines (CSSLs) of "Khao Dawk Mali 105 (KDML105)" rice containing various regions of DH212 between markers RM1003 and RM3362 displayed differential salt tolerance at the booting stage. CSSL16 and its nearly isogenic parent, KDML105, were used for transcriptome analysis. Differentially expressed genes in the leaves of seedlings, flag leaves, and second leaves of CSSL16 and KDML105 under normal and salt stress conditions were subjected to analyses based on gene co-expression network (GCN), on two-state co-expression with clustering coefficient (CC), and on weighted gene co-expression network (WGCN). GCN identified 57 genes, while 30 and 59 genes were identified using CC and WGCN, respectively. With the three methods, some of the identified genes overlapped, bringing the maximum number of predicted salt tolerance genes to 92. Among the 92 genes, nine genes, OsNodulin, OsBTBZ1, OsPSB28, OsERD, OsSub34, peroxidase precursor genes, and three expressed protein genes, displayed SNPs between CSSL16 and KDML105. The nine genes were differentially expressed in CSSL16 and KDML105 under normal and salt stress conditions. OsBTBZ1 and OsERD were identified by the three methods. These results suggest that the transcriptomic approach described here effectively identified the genes regulating salt tolerance in rice and support the identification of appropriate QTL for salt tolerance improvement.

A comparison of shared patterns of differential gene expression and gene ontologies in response to water-stress in roots and leaves of four diverse genotypes of Lolium and Festuca spp. temperate pasture grasses

Ryegrasses (Lolium spp.) and fescues (Festuca spp.) are closely related and widely cultivated perennial forage grasses. As such, resilience in the face of abiotic stresses is an important component of their traits. We have compared patterns of differentially expressed genes (DEGs) in roots and leaves of two perennial ryegrass genotypes and a single genotype of each of a festulolium (predominantly Italian ryegrass) and meadow fescue with the onset of water stress, focussing on overall patterns of DEGs and gene ontology terms (GOs) shared by all four genotypes. Plants were established in a growing medium of vermiculite watered with nutrient solution. Leaf and root material were sampled at 35% (saturation) and, as the medium dried, at 15%, 5% and 1% estimated water contents (EWCs) and RNA extracted. Differential gene expression was evaluated comparing the EWC sampling points from RNAseq data using a combination of analysis methods. For all genotypes, the greatest numbers of DEGs were identified in the 35/1 and 5/1 comparisons in both leaves and roots. In total, 566 leaf and 643 root DEGs were common to all 4 genotypes, though a third of these leaf DEGs were not regulated in the same up/down direction in all 4 genotypes. For roots, the equivalent figure was 1% of the DEGs. GO terms shared by all four genotypes were often enriched by both up- and down-regulated DEGs in the leaf, whereas generally, only by either up- or down-regulated DEGs in the root. Overall, up-regulated leaf DEGs tended to be more genotype-specific than down-regulated leaf DEGs or root DEGs and were also associated with fewer GOs. On average, only 5–15% of the DEGs enriching common GO terms were shared by all 4 genotypes, suggesting considerable variation in DEGs between related genotypes in enacting similar biological processes.

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.

Weighted Gene Co-expression Network Analysis (WGCNA) Reveals the Hub Role of Protein Ubiquitination in the Acquisition of Desiccation Tolerance in Boea hygrometrica

Boea hygrometrica can survive extreme drought conditions and has been used as a model to study desiccation tolerance. A genome-wide transcriptome analysis of B. hygrometrica showed that the plant can survive rapid air-drying after experiencing a slow soil-drying acclimation phase. In addition, a weighted gene co-expression network analysis was used to study the transcriptomic datasets. A network comprising 22 modules was constructed, and seven modules were found to be significantly related to desiccation response using an enrichment analysis. Protein ubiquitination was observed to be a common process linked to hub genes in all the seven modules. Ubiquitin-modified proteins with diversified functions were identified using immunoprecipitation coupled with mass spectrometry. The lowest level of ubiquitination was noted at the full soil drying priming stage, which coincided the accumulation of dehydration-responsive gene BhLEA2. The highly conserved RY motif (CATGCA) was identified from the promoters of ubiquitin-related genes that were downregulated in the desiccated samples. An in silico gene expression analysis showed that the negative regulation of ubiquitin-related genes is potentially mediated via a B3 domain-containing transcription repressor VAL1. This study suggests that priming may involve the transcriptional regulation of several major processes, and the transcriptional regulation of genes in protein ubiquitination may play a hub role to deliver acclimation signals to posttranslational level in the acquisition of desiccation tolerance in B. hygrometrica.

Expression profiles of cell-wall related genes vary broadly between two common maize inbreds during stem development

Background

The cellular machinery for cell wall synthesis and metabolism is encoded by members of large multi-gene families. Maize is both a genetic model for grass species and a potential source of lignocellulosic biomass from crop residues. Genetic improvement of maize for its utility as a bioenergy feedstock depends on identification of the specific gene family members expressed during secondary wall development in stems.

Results

High-throughput sequencing of transcripts expressed in developing rind tissues of stem internodes provided a comprehensive inventory of cell wall-related genes in maize (Zea mays, cultivar B73). Of 1239 of these genes, 854 were expressed among the internodes at ≥95 reads per 20 M, and 693 of them at ≥500 reads per 20 M. Grasses have cell wall compositions distinct from non-commelinid species; only one-quarter of maize cell wall-related genes expressed in stems were putatively orthologous with those of the eudicot Arabidopsis. Using a slope-metric algorithm, five distinct patterns for sub-sets of co-expressed genes were defined across a time course of stem development. For the subset of genes associated with secondary wall formation, fifteen sequence motifs were found in promoter regions. The same members of gene families were often expressed in two maize inbreds, B73 and Mo17, but levels of gene expression between them varied, with 30% of all genes exhibiting at least a 5-fold difference at any stage. Although presence-absence and copy-number variation might account for much of these differences, fold-changes of expression of a CADa and a FLA11 gene were attributed to polymorphisms in promoter response elements.

Conclusions

Large genetic variation in maize as a species precludes the extrapolation of cell wall-related gene expression networks even from one common inbred line to another. Elucidation of genotype-specific expression patterns and their regulatory controls will be needed for association panels of inbreds and landraces to fully exploit genetic variation in maize and other bioenergy grass species.

Genome-wide transcriptional adaptation to salt stress in Populus

BACKGROUND

Adaptation to abiotic stresses is crucial for the survival of perennial plants in a natural environment. However, very little is known about the underlying mechanisms. Here, we adopted a liquid culture system to investigate plant adaptation to repeated salt stress in Populus trees.

RESULTS

We first evaluated phenotypic responses and found that plants exhibit better stress tolerance after pre-treatment of salt stress. Time-course RNA sequencing (RNA-seq) was then performed to profile changes in gene expression over 12 h of salt treatments. Analysis of differentially expressed genes (DEGs) indicated that significant transcriptional reprogramming and adaptation to repeated salt treatment occurred. Clustering analysis identified two modules of co-expressed genes that were potentially critical for repeated salt stress adaptation, and one key module for salt stress response in general. Gene Ontology (GO) enrichment analysis identified pathways including hormone signaling, cell wall biosynthesis and modification, negative regulation of growth, and epigenetic regulation to be highly enriched in these gene modules.

CONCLUSIONS

This study illustrates phenotypic and transcriptional adaptation of Populus trees to salt stress, revealing novel gene modules which are potentially critical for responding and adapting to salt stress.

Identification of putative drought-responsive genes in rice using gene co-expression analysis

Drought is one of the major abiotic stresses causing yield losses and restricted growing area for several major crops. Rice being a major staple food crop and sensitive to water-deficit conditions bears heavy yield losses due to drought stress. To breed drought tolerant rice cultivars, it is of interest to understand the mechanisms of drought tolerance. In this regard, large amount of publicly available transcriptome datasets could be utilized. In this study, we used different transcriptome datasets obtained under drought stress in comparison to normal conditions (control) to identify novel drought responsive genes and their underlying molecular mechanisms. We found 517 core drought responsive differentially expressed genes (DEGs) and different modules using gene co-expression analysis to specifically predict their biological roles in drought tolerance. Gene ontology and KEGG analyses showed key biological processes and metabolic pathways involved in drought tolerance. Further, network analysis pinpointed important hub DEGs and major transcription factors regulating the expression of drought responsive genes in each module. These identified novel DEGs and transcription factors could be functionally characterized using systems biology approaches, which can significantly enhance our knowledge about the molecular mechanisms of drought tolerance in rice.

Distinct leaf transcriptomic response of water deficient Eucalyptus grandis submitted to potassium and sodium fertilization

While potassium fertilization increases growth yield in Brazilian eucalyptus plantations, it could also increase water requirements, making trees more vulnerable to drought. Sodium fertilization, which has been shown to promote eucalyptus growth compared to K-deficient trees, could partially mitigate this adverse effect of potassium. However, little is known about the influence of K and Na fertilization on the tree metabolic response to water deficit. The aim of the present study was thus to analyze the transcriptome of leaves sampled from Eucalyptus grandis trees subjected to 37% rainfall reduction, and fertilized with potassium (K), sodium (Na), compared to control trees (C). The multifactorial experiment was set up in a field with a throughfall exclusion system. Transcriptomic analysis was performed on leaves from two-year-old trees, and data analyzed using multifactorial statistical analysis and weighted gene co-expression network analysis (WGCNA). Significant sets of genes were seen to respond to rainfall reduction, in interaction with K or Na fertilization, or to fertilization only (regardless of the water supply regime). The genes were involved in stress signaling, primary and secondary metabolism, secondary cell wall formation and photosynthetic activity. Our focus on key genes related to cation transporters and aquaporins highlighted specific regulation of ion homeostasis, and plant adjustment to water deficit. While water availability significantly affects the transcriptomic response of eucalyptus species, this study points out that the transcriptomic response is highly dependent on the fertilization regime. Our study is based on the first large-scale field trial in a tropical region, specifically designed to study the interaction between water availability and nutrition in eucalyptus. To our knowledge, this is the first global transcriptomic analysis to compare the influence of K and Na fertilization on tree adaptive traits in water deficit conditions.

Meta-analysis of drought-tolerant genotypes in Oryza sativa: A network-based approach

BACKGROUND

Drought is a severe environmental stress. It is estimated that about 50% of the world rice production is affected mainly by drought. Apart from conventional breeding strategies to develop drought-tolerant crops, innovative computational approaches may provide insights into the underlying molecular mechanisms of stress response and identify drought-responsive markers. Here we propose a network-based computational approach involving a meta-analytic study of seven drought-tolerant rice genotypes under drought stress.

RESULTS

Co-expression networks enable large-scale analysis of gene-pair associations and tightly coupled clusters that may represent coordinated biological processes. Considering differentially expressed genes in the co-expressed modules and supplementing external information such as resistance/tolerance QTLs, transcription factors, network-based topological measures, we identify and prioritize drought-adaptive co-expressed gene modules and potential candidate genes. Using the candidate genes that are well-represented across the datasets as 'seed' genes, two drought-specific protein-protein interaction networks (PPINs) are constructed with up- and down-regulated genes. Cluster analysis of the up-regulated PPIN revealed ABA signalling pathway as a central process in drought response with a probable crosstalk with energy metabolic processes. Tightly coupled gene clusters representing up-regulation of core cellular respiratory processes and enhanced degradation of branched chain amino acids and cell wall metabolism are identified. Cluster analysis of down-regulated PPIN provides a snapshot of major processes associated with photosynthesis, growth, development and protein synthesis, most of which are shut down during drought. Differential regulation of phytohormones, e.g., jasmonic acid, cell wall metabolism, signalling and posttranslational modifications associated with biotic stress are elucidated. Functional characterization of topologically important, drought-responsive uncharacterized genes that may play a role in important processes such as ABA signalling, calcium signalling, photosynthesis and cell wall metabolism is discussed. Further transgenic studies on these genes may help in elucidating their biological role under stress conditions.

CONCLUSION

Currently, a large number of resources for rice functional genomics exist which are mostly underutilized by the scientific community. In this study, a computational approach integrating information from various resources such as gene co-expression networks, protein-protein interactions and pathway-level information is proposed to provide a systems-level view of complex drought-responsive processes across the drought-tolerant genotypes.

Comparative functional genomics analysis of bHLH gene family in rice, maize and wheat

BACKGROUND

The basic helix-loop-helix transcription factors play important roles in diverse cellular and molecular processes. Comparative functional genomics can provide powerful approaches to draw inferences about gene function and evolution among species. The comprehensive comparison of bHLH gene family in different gramineous plants has not yet been reported.

RESULTS

In this study, a total of 183, 231 and 571 bHLHs were identified in rice, maize and wheat genomes respectively, and 1154 bHLH genes from the three species and Arabidopsis were classified into 36 subfamilies. Of the identified genes, 110 OsbHLHs, 188 ZmbHLHs and 209 TabHLHs with relatively high mRNA abundances were detected in one or more tissues during development, and some of them exhibited tissue-specific expression such as TabHLH454-459, ZmbHLH099-101 and OsbHLH037 in root, TabHLH559-562, - 046, - 047 and ZmbHLH010, - 072, - 226 in leaf, TabHLH216-221, - 333, - 335, - 340 and OsbHLH005, - 141 in inflorescence, TabHLH081, ZmbHLH139 and OsbHLH144 in seed. Forty five, twenty nine and thirty one differentially expressed bHLHs were respectively detected in wheat, maize and rice under drought stresses using RNA-seq technology. Among them, the expressions of TabHLH046, - 047, ZmbHLH097, - 098, OsbHLH006 and - 185 were strongly induced, whereas TabHLH303, - 562, ZmbHLH155, - 154, OsbHLH152 and - 113 showed significant down-regulation. Twenty two TabHLHs were induced after stripe rust infection at 24 h and nine of them were suppressed at 72 hpi, whereas 28 and 6 TabHLHs exhibited obviously down- and up-regulation after powdery mildew attack respectively. Forty one ZmbHLHs were differentially expressed in response to F. verticillioides infection. Twenty two co-expression modules were identified by the WGCNA, some of which were associated with particular tissue types. And GO enrichment analysis for the modules showed that some TabHLHs were involved in the control of several biological processes, such as tapetal PCD, lipid metabolism, iron absorption, stress responses and signal regulation.

CONCLUSION

The present study identifies the bHLH family in rice, maize and wheat genomes, and detailedly discusses the evolutionary relationships, expression and function of bHLHs. This study provides some novel and detail information about bHLHs, and may facilitate understanding the molecular basis of the plant growth, development and stress physiology.

Meta-expression analysis of unannotated genes in rice and approaches for network construction to suggest the probable roles

This work suggests 2020 potential candidates in rice for the functional annotation of unannotated genes using meta-analysis of anatomical samples derived from microarray and RNA-seq technologies and this information will be useful to identify novel morphological agronomic traits. Although the genome of rice (Oryza sativa) has been sequenced, 14,365 genes are considered unannotated because they lack putative annotation information. According to the Rice Genome Annotation Project Database ( http://rice.plantbiology.msu.edu/ ), the proportion of functionally characterized unannotated genes (0.35%) is quite limited when compared with the approximately 3.9% of annotated genes with assigned putative functions. Researchers require additional information to help them investigate the molecular mechanisms associated with those unannotated genes. To determine which of them might regulate morphological or physiological traits in the rice genome, we conducted a meta-analysis of expression data that covered a wide range of tissue/organ samples. Overall, 2020 genes showed cultivar-, tissue-, or organ-preferential patterns of expression. Representative candidates from featured groups were validated by RT-PCR, and the GUS reporter system was used to validate the expression of genes that were clustered according to their leaf or root preference. Taking a molecular and genetics approach, we examined meta-expression data and found that 127 genes were differentially expressed between japonica and indica rice cultivars. This is potentially significant for future agronomic applications. We also used a T-DNA insertional mutant and performed a co-expression network analysis of Sword shape dwarf1 (SSD1), a gene that regulates cell division. This network was refined via RT-PCR analysis. Our results suggested that SSD1 represses the expression of four genes related to the processes of DNA replication or cell division and provides insight into possible molecular mechanisms. Together, these strategies present a valuable tool for in-depth characterization of currently unannotated genes.

Protocol for Coexpression Network Construction and Stress-Responsive Expression Analysis in Brachypodium

Identifying functionally coexpressed genes and modules has increasingly become important to understand the transcriptional flux and to understand large scale gene association. Application of the graph theory and combination of tools has allowed to understand the genic interaction and to understand the role of hub and non-hub proteins in plant development and its ability to cope with stress. Association genetics has also been coupled with network modules to map these key genes as e-QTLs. High throughput sequencing approaches has revolutionized the mining of the gene behavior and also the association of the genes over time-series. The present protocol chapter presents a unified workflow to understand the transcriptional modules in Brachypodium distachyon using weighted coexpressed gene network analysis approach.

High Performance of Photosynthesis and Osmotic Adjustment Are Associated With Salt Tolerance Ability in Rice Carrying Drought Tolerance QTL: Physiological and Co-expression Network Analysis

Understanding specific biological processes involving in salt tolerance mechanisms is important for improving traits conferring tolerance to salinity, one of the most important abiotic stresses in plants. Under drought and salinity stresses, plants share overlapping responsive mechanisms such as physiological changes and activation of signaling molecules, which induce and transmit signals through regulator genes in a regulatory network. In this study, two near isogenic lines of rice carrying chromosome segments of drought tolerance QTL on chromosome 8 from IR68586-F2-CA-31 (DH103) in the genetic background of sensitive cultivar "Khao Dawk Mali 105; KDML105" (designated as CSSL8-94 and CSSL8-95) were used to investigate physiological responses to salt stress [namely growth, Na⁺/K⁺ ratio, water status, osmotic adjustment, photosynthetic parameters, electrolyte leakage (EL), malondialdehyde (MDA), proline and sugar accumulations], compared with the standard salt tolerant (Pokkali; PK) and their recurrent parent (KDML105) rice cultivars. Physiological examination indicated that both CSSLs showed superior salt-tolerant level to KDML105. Our results suggested that salt tolerance ability of these CSSL lines may be resulted from high performance photosynthesis, better osmotic adjustment, and less oxidative stress damage under salt conditions. Moreover, to explore new candidate genes that might take part in salt tolerance mechanisms, we performed co-expression network analysis for genes identified in the CSSL rice, and found that Os08g419090, the gene involved with tetrapyrrole and porphyrin biosynthetic process (chlorophyll biosynthetic process), Os08g43230 and Os08g43440 (encoded TraB family protein and cytochrome P450, respectively) might have unprecedented roles in salt stress tolerance.

Co-expression network analysis of the transcriptomes of rice roots exposed to various cadmium stresses reveals universal cadmium-responsive genes

BACKGROUND

The migration of cadmium (Cd) from contaminated soil to rice is a cause for concern. However, the molecular mechanism underlying the response of rice roots to various Cd stresses remains to be clarified from the viewpoint of the co-expression network at a system-wide scale.

RESULTS

We employed a comparative RNAseq-based approach to identify early Cd-responsive differentially expressed genes (DEGs) in rice 'Nipponbare' seedling roots after 1 h of high-Cd treatment. A multiplicity of the identified 1772 DEGs were implicated in hormone signaling and transcriptional regulation, particularly NACs and WRKYs were all upregulated under Cd stress. All of the 6 Cd-upregulated ABC transporters were pleiotropic drug resistance proteins (PDRs), whereas all of the 6 ZRT/IRT-like proteins (ZIPs) were consistently downregulated by Cd treatment. To further confirm our results of this early transcriptomic response to Cd exposure, we then conducted weighted gene co-expression network analysis (WGCNA) to re-analyze our RNAseq data in combination with other 11 previously published RNAseq datasets for rice roots exposed to diverse concentrations of Cd for extended treatment periods. This integrative approach identified 271 transcripts as universal Cd-regulated DEGs that are key components of the Cd treatment coupled co-expression module. A global view of the 164 transcripts with annotated functions in pathway networks revealed several Cd-upregulated key functional genes, including transporter ABCG36/OsPDR9, 12-oxo-phytodienoic acid reductases (OPRs) for JA synthesis, and ZIM domain proteins JAZs in JA signaling, as well as OsWRKY10, NAC, and ZFP transcription factors. More importantly, 104 of these, including ABCG36/OsPDR9, OsNAC3, as well as several orthologs in group metalloendoproteinase, plastocyanin-like domain containing proteins and pectin methylesterase inhibitor, may respond specifically to various Cd pressures, after subtracting the 60 general stress-responsive genes reported to be commonly upregulated following multiple stresses.

CONCLUSION

An integrative approach was implemented to identify DEGs and co-expression network modules in response to various Cd pressures, and 104 of the 164 annotatable universal Cd-responsive DEGs may specifically respond to various Cd pressures. These results provide insight into the universal molecular mechanisms beneath the Cd response in rice roots, and suggest many promising targets for improving the rice acclimation process against Cd toxicity.

A Meta-Analysis Based Method for Prioritizing Candidate Genes Involved in a Pre-specific Function

The identification of genes associated with a given biological function in plants remains a challenge, although network-based gene prioritization algorithms have been developed for Arabidopsis thaliana and many non-model plant species. Nevertheless, these network-based gene prioritization algorithms have encountered several problems; one in particular is that of unsatisfactory prediction accuracy due to limited network coverage, varying link quality, and/or uncertain network connectivity. Thus, a model that integrates complementary biological data may be expected to increase the prediction accuracy of gene prioritization. Toward this goal, we developed a novel gene prioritization method named RafSee, to rank candidate genes using a random forest algorithm that integrates sequence, evolutionary, and epigenetic features of plants. Subsequently, we proposed an integrative approach named RAP (Rank Aggregation-based data fusion for gene Prioritization), in which an order statistics-based meta-analysis was used to aggregate the rank of the network-based gene prioritization method and RafSee, for accurately prioritizing candidate genes involved in a pre-specific biological function. Finally, we showcased the utility of RAP by prioritizing 380 flowering-time genes in Arabidopsis. The "leave-one-out" cross-validation experiment showed that RafSee could work as a complement to a current state-of-art network-based gene prioritization system (AraNet v2). Moreover, RAP ranked 53.68% (204/380) flowering-time genes higher than AraNet v2, resulting in an 39.46% improvement in term of the first quartile rank. Further evaluations also showed that RAP was effective in prioritizing genes-related to different abiotic stresses. To enhance the usability of RAP for Arabidopsis and non-model plant species, an R package implementing the method is freely available at http://bioinfo.nwafu.edu.cn/software.