Dataset Information

Coregulation of transcription factors and microRNAs in human transcriptional regulatory network.

ABSTRACT:

Background

MicroRNAs (miRNAs) are small RNA molecules that regulate gene expression at the post-transcriptional level. Recent studies have suggested that miRNAs and transcription factors are primary metazoan gene regulators; however, the crosstalk between them still remains unclear.

Methods

We proposed a novel model utilizing functional annotation information to identify significant coregulation between transcriptional and post-transcriptional layers. Based on this model, function-enriched coregulation relationships were discovered and combined into different kinds of functional coregulation networks.

Results

We found that miRNAs may engage in a wider diversity of biological processes by coordinating with transcription factors, and this kind of cross-layer coregulation may have higher specificity than intra-layer coregulation. In addition, the coregulation networks reveal several types of network motifs, including feed-forward loops and massive upstream crosstalk. Finally, the expression patterns of these coregulation pairs in normal and tumour tissues were analyzed. Different coregulation types show unique expression correlation trends. More importantly, the disruption of coregulation may be associated with cancers.

Conclusion

Our findings elucidate the combinatorial and cooperative properties of transcription factors and miRNAs regulation, and we proposes that the coordinated regulation may play an important role in many biological processes.

SUBMITTER: Chen CY

PROVIDER: S-EPMC3044298 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Coregulation of transcription factors and microRNAs in human transcriptional regulatory network.

Chen Cho-Yi CY Chen Shui-Tein ST Fuh Chiou-Shann CS Juan Hsueh-Fen HF Huang Hsuan-Cheng HC

BMC bioinformatics 20110215

<h4>Background</h4>MicroRNAs (miRNAs) are small RNA molecules that regulate gene expression at the post-transcriptional level. Recent studies have suggested that miRNAs and transcription factors are primary metazoan gene regulators; however, the crosstalk between them still remains unclear.<h4>Methods</h4>We proposed a novel model utilizing functional annotation information to identify significant coregulation between transcriptional and post-transcriptional layers. Based on this model, function ...[more]

PMID: 21342573

Similar Datasets

Project description:Though the bacterial transcription regulation apparatus is distinct in terms of several structural and functional features from its eukaryotic counterpart, the gross structure of the transcription regulatory network (TRN) is believed to be similar in both superkingdoms. Here, we explore the fine structure of the bacterial TRN and the underlying "co-regulatory network" (CRN) to show that despite the superficial similarities to the TRN of the eukaryotic model organism yeast, the bacterial networks display entirely different organizational principles. In particular unlike in eukaryotes, hubs of the bacterial networks are both global regulators and integrators of diverse disparate transcriptional responses. These and other organizational differences might correlate with the fundamental differences in gene and promoter organization in the two superkingdoms, especially the presence of operons and regulons in bacteria. Further we explored to find the interplay, if any, between network structures, mode of regulatory interactions and signal sensing of transcription factors (TFs) in shaping up the bacterial transcriptional regulatory responses. For this purpose, we first classified TFs according to their regulatory mode (activator, repressor or dual regulator) and sensory mechanism (one-component systems responding to internal or external signals, TFs from two-component systems and chromosomal structure modifying TFs) in the bacterial model organism Escherichia coli and then we studied the overall evolutionary optimization of network structures. The incorporation of TFs in different hierarchical elements of the TRN appears to involve on a multi-dimensional selection process depending on regulatory and sensory modes of TFs in motifs, co-regulatory associations between TFs of different functional classes and transcript half-lives. As a result it appears to have generated circuits that allow intricately regulated physiological state changes. We identified the biological significance of most of these optimizations, which can be further used as the basis to explore similar controls in other bacteria. We also show that, though on the larger evolutionary scale, unrelated TFs have evolved to become hubs, within lineages like gamma-proteobacteria there is strong tendency to retain hubs, as well as certain higher-order network modules that have emerged through lineage specific paralog duplications.

Project description:BACKGROUND: MicroRNA (miRNA) is a class of small RNAs of ~22nt which play essential roles in many crucial biological processes and numerous human diseases at post-transcriptional level of gene expression. It has been revealed that miRNA genes tend to be clustered, and the miRNAs organized into one cluster are usually transcribed coordinately. This implies a coordinated regulation mode exerted by clustered miRNAs. However, how the clustered miRNAs coordinate their regulations on large scale gene expression is still unclear. RESULTS: We constructed the miRNA-transcription factor regulatory network that contains the interactions between transcription factors (TFs), miRNAs and non-TF protein-coding genes, and made a genome-wide study on the regulatory coordination of clustered miRNAs. We found that there are two types of miRNA clusters, i.e. homo-clusters that contain miRNAs of the same family and hetero-clusters that contain miRNAs of various families. In general, the homo-clustered as well as the hetero-clustered miRNAs both exhibit coordinated regulation since the miRNAs belonging to one cluster tend to be involved in the same network module, which performs a relatively isolated biological function. However, the homo-clustered miRNAs show a direct regulatory coordination that is realized by one-step regulation (i.e. the direct regulation of the coordinated targets), whereas the hetero-clustered miRNAs show an indirect regulatory coordination that is realized by a regulation comprising at least three steps (e.g. the regulation on the coordinated targets by a miRNA through a sequential action of two TFs). The direct and indirect regulation target different categories of genes, the former predominantly regulating genes involved in emergent responses, the latter targeting genes that imply long-term effects. CONCLUSION: The genomic clustering of miRNAs is closely related to the coordinated regulation in the gene regulatory network. The pattern of regulatory coordination is dependent on the composition of the miRNA cluster. The homo-clustered miRNAs mainly coordinate their regulation rapidly, while the hetero-clustered miRNAs exert control with a delay. The diverse pattern of regulatory coordination suggests distinct roles of the homo-clustered and the hetero-clustered miRNAs in biological processes.

Project description:MYB transcription factor (TF) is one of the largest TF families and regulates defense responses to various stresses, hormone signaling as well as many metabolic and developmental processes in plants. Understanding these regulatory hierarchies of gene expression networks in response to developmental and environmental cues is a major challenge due to the complex interactions between the genetic elements. Correlation analyses are useful to unravel co-regulated gene pairs governing biological process as well as identification of new candidate hub genes in response to these complex processes. High throughput expression profiling data are highly useful for construction of co-expression networks. In the present study, we utilized transcriptome data for comprehensive regulatory network studies of MYB TFs by "top-down" and "guide-gene" approaches. More than 50% of OsMYBs were strongly correlated under 50 experimental conditions with 51 hub genes via "top-down" approach. Further, clusters were identified using Markov Clustering (MCL). To maximize the clustering performance, parameter evaluation of the MCL inflation score (I) was performed in terms of enriched GO categories by measuring F-score. Comparison of co-expressed cluster and clads analyzed from phylogenetic analysis signifies their evolutionarily conserved co-regulatory role. We utilized compendium of known interaction and biological role with Gene Ontology enrichment analysis to hypothesize function of coexpressed OsMYBs. In the other part, the transcriptional regulatory network analysis by "guide-gene" approach revealed 40 putative targets of 26 OsMYB TF hubs with high correlation value utilizing 815 microarray data. The putative targets with MYB-binding cis-elements enrichment in their promoter region, functional co-occurrence as well as nuclear localization supports our finding. Specially, enrichment of MYB binding regions involved in drought-inducibility implying their regulatory role in drought response in rice. Thus, the co-regulatory network analysis facilitated the identification of complex OsMYB regulatory networks, and candidate target regulon genes of selected guide MYB genes. The results contribute to the candidate gene screening, and experimentally testable hypotheses for potential regulatory MYB TFs, and their targets under stress conditions.

Dataset Information

Coregulation of transcription factors and microRNAs in human transcriptional regulatory network.

Background

Methods

Results

Conclusion

Publications

Coregulation of transcription factors and microRNAs in human transcriptional regulatory network.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets