A generic model of transcriptional regulatory networks: Application to plants under abiotic stress (original) (raw)
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Transcriptional regulatory networks in Arabidopsis thaliana during single and combined stresses
Differentially evolved responses to various stress conditions in plants are controlled by complex regulatory circuits of transcriptional activators, and repressors, such as transcription factors (TFs). To understand the general and condition-specific activities of the TFs and their regulatory relationships with the target genes (TGs), we have used a homogeneous stress gene expression dataset generated on ten natural ecotypes of the model plant Arabidopsis thaliana, during five single and six combined stress conditions. Knowledge-based profiles of binding sites for 25 stress-responsive TF families (187 TFs) were generated and tested for their enrichment in the regulatory regions of the associated TGs. Condition-dependent regulatory sub-networks have shed light on the differential utilization of the underlying network topology, by stress-specific regulators and multifunctional regulators. The multifunctional regulators maintain the core stress response processes while the transient regulators confer the specificity to certain conditions. Clustering patterns of transcription factor binding sites (TFBS) have reflected the combinatorial nature of transcriptional regulation, and suggested the putative role of the homotypic clusters of TFBS towards maintaining transcriptional robustness against cis-regulatory mutations to facilitate the preservation of stress response processes. The Gene Ontology enrichment analysis of the TGs reflected sequential regulation of stress response mechanisms in plants.
Structure, function and networks of transcription factors involved in abiotic stress responses
International journal of molecular sciences, 2013
Transcription factors (TFs) are master regulators of abiotic stress responses in plants. This review focuses on TFs from seven major TF families, known to play functional roles in response to abiotic stresses, including drought, high salinity, high osmolarity, temperature extremes and the phytohormone ABA. Although ectopic expression of several TFs has improved abiotic stress tolerance in plants, fine-tuning of TF expression and protein levels remains a challenge to avoid crop yield loss. To further our understanding of TFs in abiotic stress responses, emerging gene regulatory networks based on TFs and their direct targets genes are presented. These revealed components shared between ABA-dependent and independent signaling as well as abiotic and biotic stress signaling. Protein structure analysis suggested that TFs hubs of large interactomes have extended regions with protein intrinsic disorder (ID), referring to their lack of fixed tertiary structures. ID is now an emerging topic i...
2017
Changing environmental conditions are limiting crop productivity and, hence, there is an urgent need to develop stress tolerant plants. Engineering of Cisregulatory elements (CREs) is an effective strategy to design such plants. Transcription factors (TFs) can be used effectively to manipulate gene expression. However, overlapping expression has been observed for several stress-responsive TFs. In order to design improved plants by Cis-engineering, we first need to understand the complex regulatory network of TFs and the cross-talk between them. Advances in systems biology have enabled us to visualize plants from a holistic view during the abiotic stress. The current review discusses major transcriptional regulatory networks involved in abiotic stress tolerance, and how a better understanding of these networks may help in designing stress-tolerant plants. Finally, the review mentions some potential approaches to generate stresstolerant crops to enhance crop productivity, which is the...
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 ...
Prerequisites, performance and profits of transcriptional profiling the abiotic stress response
Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms, 2012
During the last decade, microarrays became a routine tool for the analysis of transcripts in the model plant Arabidopsis thaliana and the crop plant species rice, poplar or barley. The overwhelming amount of data generated by gene expression studies is a valuable resource for every scientist. Here, we summarize the most important findings about the abiotic stress responses in plants. Interestingly, conserved patterns of gene expression responses have been found that are common between different abiotic stresses or that are conserved between different plant species. However, the individual histories of each plant affect the inter-comparability between experiments already before the onset of the actual stress treatment. This review outlines multiple aspects of microarray technology and highlights some of the benefits, limitations and also pitfalls of the technique. This article is part of a Special Issue entitled: Plant gene regulation in response to abiotic stress.
Prediction and characterization of transcription factors involved in drought stress response
2020
Transcription factors (TFs) play a central role in regulating molecular level responses of plants to external stresses such as water limiting conditions, but identification of such TFs in the genome remains a challenge. Here, we describe a network-based supervised machine learning framework that accurately predicts and ranks all TFs in the genome according to their potential association with drought tolerance. We show that top ranked regulators fall mainly into two ‘age’ groups; genes that appeared first in land plants and genes that emerged later in the Oryza clade. TFs predicted to be high in the ranking belong to specific gene families, have relatively simple intron/exon and protein structures, and functionally converge to regulate primary and secondary metabolism pathways. Repeated trials of nested cross-validation tests showed that models trained only on regulatory network patterns, inferred from large transcriptome datasets, outperform models trained on heterogenous genomic fe...
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.
The Plant cell, 2014
The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress ...
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.
Genes Acting on Transcriptional Control during Abiotic Stress Responses
Advances in Agriculture, 2014
Abiotic stresses are the major cause of yield loss in crops around the world. Greater genetic gains are possible by combining the classical genetic improvement with advanced molecular biology techniques. The understanding of mechanisms triggered by plants to meet conditions of stress is of fundamental importance for the elucidation of these processes. Current genetically modified crops help to mitigate the effects of these stresses, increasing genetic gains in order to supply the agricultural market and the demand for better quality food throughout the world. To obtain safe genetic modified organisms for planting and consumption, a thorough grasp of the routes and genes that act in response to these stresses is necessary. This work was developed in order to collect important information about essential TF gene families for transcriptional control under abiotic stress responses.