Transcriptional regulatory networks in Arabidopsis thaliana during single and combined stresses (original) (raw)
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Bioinformation, 2008
The expressions of proteins in the cell are carefully regulated by transcription factors that interact with their downstream targets in specific signal transduction cascades. Our understanding of the regulation of functional genes responsive to stress signals is still nascent. Plants like Arabidopsis thaliana, are convenient model systems to study fundamental questions related to regulation of the stress transcriptome in response to stress challenges. Microarray results of the Arabidopsis transcriptome indicate that several genes could be upregulated during multiple stresses, such as cold, salinity, drought etc. Experimental biochemical validations have proved the involvement of several transcription factors could be involved in the upregulation of these stress responsive genes. In order to follow the intricate and complicated networks of transcription factors and genes that respond to stress situations in plants, we have developed a computer algorithm that can identify key transcription factor binding sites upstream of a gene of interest. Hidden Markov models of the transcription factor binding sites enable the identification of predicted sites upstream of plant stress genes. The search algorithm, STIF, performs very well, with more than 90% sensitivity, when tested on experimentally validated positions of transcription factor binding sites on a dataset of 60 stress upregulated genes.
Cis-regulatory code of stress-responsive transcription in Arabidopsis thaliana
Proceedings of the National Academy of Sciences, 2011
Environmental stress leads to dramatic transcriptional reprogramming, which is central to plant survival. Although substantial knowledge has accumulated on how a few plant cis-regulatory elements (CREs) function in stress regulation, many more CREs remain to be discovered. In addition, the plant stress cis-regulatory code, i.e., how CREs work independently and/or in concert to specify stress-responsive transcription, is mostly unknown. On the basis of gene expression patterns under multiple stresses, we identified a large number of putative CREs (pCREs) in Arabidopsis thaliana with characteristics of authentic cis-elements. Surprisingly, biotic and abiotic responses are mostly mediated by two distinct pCRE superfamilies. In addition, we uncovered cis-regulatory codes specifying how pCRE presence and absence, combinatorial relationships, location, and copy number can be used to predict stress-responsive expression. Expression prediction models based on pCRE combinations perform significantly better than those based on simply pCRE presence and absence, location, and copy number. Furthermore, instead of a few master combinatorial rules for each stress condition, many rules were discovered, and each appears to control only a small subset of stress-responsive genes. Given there are very few documented interactions between plant CREs, the combinatorial rules we have uncovered significantly contribute to a better understanding of the cis-regulatory logic underlying plant stress response and provide prioritized targets for experimentation. machine learning | motif discovery | transcription factor binding site
Understanding the principles of abiotic and biotic stress responses, tolerance and adaptation remains important in plant physiology research to develop better varieties of crop plants. Better understanding of plant stress response mechanisms and application of knowledge derived from integrated experimental and bioinformatics approaches are gaining importance. Earlier, we showed that compiling a database of stress-responsive transcription factors and their corresponding target binding sites in the form of Hidden Markov models at promoter, untranslated and upstream regions of stress-up-regulated genes from expression analysis can help in elucidating various aspects of the stress response in Arabidopsis. In addition to the extensive content in the first version, STIFDB2 is now updated with 15 stress signals, 31 transcription factors and 5,984 stress-responsive genes from three species (Arabidopsis thaliana, Oryza sativa subsp. japonica and Oryza sativa subsp. indica). We have employed an integrated biocuration and genomic data mining approach to characterize the data set of transcription factors and consensus binding sites from literature mining and stress-responsive genes from the Gene Expression Omnibus. STIFDB2 currently has 38,798 associations of stress signals, stress-responsive genes and transcription factor binding sites predicted using the Stress-responsive Transcription Factor (STIF) algorithm, along with various functional annotation data. As a unique plant stress regulatory genomics data platform, STIFDB2 can be utilized for targeted as well as high-throughput experimental and computational studies to unravel principles of the stress regulome in dicots and gramineae. STIFDB2 is available from the URL: http://caps.ncbs.res.in/stifdb2
Plant Cell, 2002
Numerous studies have shown that transcription factors are important in regulating plant responses to environmental stress. However, specific functions for most of the genes encoding transcription factors are unclear. In this study, we used mRNA profiles generated from microarray experiments to deduce the functions of genes encoding known and putative Arabidopsis transcription factors. The mRNA levels of 402 distinct transcription factor genes were examined at different developmental stages and under various stress conditions. Transcription factors potentially controlling downstream gene expression in stress signal transduction pathways were identified by observed activation and repression of the genes after certain stress treatments. The mRNA levels of a number of previously characterized transcription factor genes were changed significantly in connection with other regulatory pathways, suggesting their multifunctional nature. The expression of 74 transcription factor genes responsive to bacterial pathogen infection was reduced or abolished in mutants that have defects in salicylic acid, jasmonic acid, or ethylene signaling. This observation indicates that the regulation of these genes is mediated at least partly by these plant hormones and suggests that the transcription factor genes are involved in the regulation of additional downstream responses mediated by these hormones. Among the 43 transcription factor genes that are induced during senescence, 28 of them also are induced by stress treatment, suggesting extensive overlap responses to these stresses. Statistical analysis of the promoter regions of the genes responsive to cold stress indicated unambiguous enrichment of known conserved transcription factor binding sites for the responses. A highly conserved novel promoter motif was identified in genes responding to a broad set of pathogen infection treatments. This observation strongly suggests that the corresponding transcription factors play general and crucial roles in the coordinated regulation of these specific regulons. Although further validation is needed, these correlative results provide a vast amount of information that can guide hypothesis-driven research to elucidate the molecular mechanisms involved in transcriptional regulation and signaling networks in plants.
Transcriptome Responses to Combinations of Stresses in Arabidopsis
PLANT PHYSIOLOGY, 2013
Biotic and abiotic stresses limit agricultural yields, and plants are often simultaneously exposed to multiple stresses. Combinations of stresses such as heat and drought or cold and high light intensity have profound effects on crop performance and yields. Thus, delineation of the regulatory networks and metabolic pathways responding to single and multiple concurrent stresses is required for breeding and engineering crop stress tolerance. Many studies have described transcriptome changes in response to single stresses. However, exposure of plants to a combination of stress factors may require agonistic or antagonistic responses or responses potentially unrelated to responses to the corresponding single stresses. To analyze such responses, we initially compared transcriptome changes in 10 Arabidopsis (Arabidopsis thaliana) ecotypes using cold, heat, high-light, salt, and flagellin treatments as single stress factors as well as their double combinations. This revealed that some 61% of the transcriptome changes in response to double stresses were not predictable from the responses to single stress treatments. It also showed that plants prioritized between potentially antagonistic responses for only 5% to 10% of the responding transcripts. This indicates that plants have evolved to cope with combinations of stresses and, therefore, may be bred to endure them. In addition, using a subset of this data from the Columbia and Landsberg erecta ecotypes, we have delineated coexpression network modules responding to single and combined stresses.
Computational Biology Journal, 2014
Microarray datasets are widely used resources to predict and characterize functional entities of the whole genomics. The study initiated here aims to identify overexpressed stress responsive genes using microarray datasets applyingin silicoapproaches. The target also extended to build a protein-protein interaction model of regulatory genes with their upstream and downstream connection inArabidopsis thaliana. Four microarray datasets generated treating abiotic stresses like salinity, cold, drought, and abscisic acid (ABA) were chosen. Retrieved datasets were firstly filtered based on their expression comparing to control. Filtered datasets were then used to create an expression hub. Extensive literature mining helped to identify the regulatory molecules from the expression hub. The study brought out 42 genes/TF/enzymes as the role player during abiotic stress response. Further bioinformatics study and also literature mining revealed that thirty genes from those forty-two were highly ...
Genetics, 2006
The identification and analysis of genes exhibiting large expression responses to several different types of stress may provide insights into the functional basis of multiple stress tolerance in plant species. This study considered whole-genome transcriptional profiles from Arabidopsis thaliana root and shoot organs under nine abiotic stress conditions (cold, osmotic stress, salt, drought, genotoxic stress, ultraviolet light, oxidative stress, wounding, and high temperature) and at six different time points of stress exposure (0.5, 1, 3, 6, 12, and 24 hr). In roots, genomewide correlations between transcriptional responses to different stress treatments peaked following 1 hr of stress exposure, while in shoots, correlations tended to increase following 6 hr of stress exposure. The generality of stress responses at the transcriptional level was therefore time and organ dependent. A total of 67 genes were identified as exhibiting a statistically significant pattern of gene expression characterized by large transcriptional responses to all nine stress treatments. Most genes were identified from early to middle (1–6 hr) time points of stress exposure. Analysis of this gene set indicated that cell rescue/defense/virulence, energy, and metabolism functional classes were overrepresented, providing novel insight into the functional basis of multiple stress tolerance in Arabidopsis.
A generic model of transcriptional regulatory networks: Application to plants under abiotic stress
2013 IEEE International Workshop on Genomic Signal Processing and Statistics, 2013
Understanding the relationships between transcription factors (TFs) and genes in plants under abiotic stress responses, tolerance and adaptation to adverse environments is very important in developing resilient crop varieties. While experimental methods to characterize stress responsive TFs and their targets are highly accurate, identification and characterization of the role of a given gene in a given stress response event are often laborious and time consuming. Computational approaches, on the other hand, offer a platform to identify new knowledge by integrating high throughput omics data and mathematical methods/models. In this research, we have developed a generic linear model of transcriptional regulatory networks (TRNs) and a companion algorithm to identify and to characterize stress responsive genes and their roles in a given stress response event. The proposed methodology was applied to plants, by using Arabidopsis thaliana as an example, under abiotic stress. Well known interactions were inferred as well as putative novel ones that may play important roles in plants under abiotic stress conditions as confirmed by statistical and literature evidences.
Transcription Factors and Environmental Stresses in Plants
Emerging Technologies and Management of Crop Stress Tolerance, 2014
ABSTRACT The plants are exposed to environmental changes which are perceived as stresses when they are quick and extreme. Drought, salt and extreme temperatures, in particular, limit agricultural crops productivity, affecting all stages of plant growth and reproduction and therefore strongly decreasing crop yield. Worldwide estimates show that most yield loss (70%) can be directly due to abiotic stresses. Moreover the increasing phenomena of anthropization and the incorrect use of agricultural land have strongly contributed to land degradation. A large number of abiotic stress responsive genes have been reported in a variety of plants including Arabidopsis and the major crops such as barley, maize, rice and wheat. Transcriptional control of the expression of these genes is a crucial part of the plant response to abiotic stresses. Therefore in the last years the transcriptional mechanisms involved in the response to several abiotic stresses have been the subject of intense research, that have been productive in identifying transcription factors (TFs) as important 'key or master regulators' of gene expression under stress. An increasing number of TFs have been recently described and essential transcription factor binding regions have been identified for many genes. In fact, these systems of regulation work thanks to specific cis-elements located in the promoter regions of target genes, which are called regulons. The main regulons which respond to abiotic stresses are DREB1-CBF (dehydration-responsive element binding protein 1/C-repeat binding factor) which is involved in the cold stress response, DREB2 that acts in ABA-independent gene expression for response to heat and osmotic stress, whereas the ABA-responsive element (ABRE) binding protein (AREB)/ABRE binding factor (ABF) regulon operates in gene expression depending on ABA under osmotic stress. Other regulons, such as MYB/MYC and NAC regulons, induce or repress the expression of genes involved in abiotic stress-responsive. In the last few years, several studies have evidenced that TFs are powerful tools to engineer enhanced stress tolerance in plants. Therefore, in this chapter, we will summarize the major TFs involved in crop plants abiotic stress signalling and responses and the relative plants adaptive mechanisms at the molecular level. A major knowledge on molecular mechanisms that occur in stress condition are the one way pass for the improvement of stress tolerance in crop plants.