Deciphering the transcriptional circuitry of microRNA genes expressed during human monocytic differentiation
Name:
Article-BMC_Genomi-Decipherin-2009.pdf
Size:
3.042Mb
Format:
PDF
Description:
Article - Full Text
Name:
Supplement_1_-_BMC_Genomi-Decipherin-2009.1471-2164-10-595-S1.XLS
Size:
23Kb
Format:
Microsoft Excel
Description:
Supplemental File 1
Name:
Supplement_2_-_BMC_Genomi-Decipherin-2009.1471-2164-10-595-S2.XLS
Size:
262.5Kb
Format:
Microsoft Excel
Description:
Supplemental File 2
Name:
Supplement_3_-_BMC_Genomi-Decipherin-2009.1471-2164-10-595-S3.XLS
Size:
319Kb
Format:
Microsoft Excel
Description:
Supplemental File 3
Name:
Supplement_4_-_BMC_Genomi-Decipherin-2009.1471-2164-10-595-S4.XLS
Size:
1.732Mb
Format:
Microsoft Excel
Description:
Supplemental File 4
Type
ArticleAuthors
Schmeier, Sebastian
MacPherson, Cameron R
Essack, Magbubah

Kaur, Mandeep
Schaefer, Ulf
Suzuki, Harukazu
Hayashizaki, Yoshihide
Bajic, Vladimir B.

KAUST Department
Computational Bioscience Research Center (CBRC)Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Applied Mathematics and Computational Science Program
Date
2009-12-10Online Publication Date
2009-12-10Print Publication Date
2009Permanent link to this record
http://hdl.handle.net/10754/325239
Metadata
Show full item recordAbstract
Background: Macrophages are immune cells involved in various biological processes including host defence, homeostasis, differentiation, and organogenesis. Disruption of macrophage biology has been linked to increased pathogen infection, inflammation and malignant diseases. Differential gene expression observed in monocytic differentiation is primarily regulated by interacting transcription factors (TFs). Current research suggests that microRNAs (miRNAs) degrade and repress translation of mRNA, but also may target genes involved in differentiation. We focus on getting insights into the transcriptional circuitry regulating miRNA genes expressed during monocytic differentiation. Results: We computationally analysed the transcriptional circuitry of miRNA genes during monocytic differentiation using in vitro time-course expression data for TFs and miRNAs. A set of TF?miRNA associations was derived from predicted TF binding sites in promoter regions of miRNA genes. Time-lagged expression correlation analysis was utilised to evaluate the TF?miRNA associations. Our analysis identified 12 TFs that potentially play a central role in regulating miRNAs throughout the differentiation process. Six of these 12 TFs (ATF2, E2F3, HOXA4, NFE2L1, SP3, and YY1) have not previously been described to be important for monocytic differentiation. The remaining six TFs are CEBPB, CREB1, ELK1, NFE2L2, RUNX1, and USF2. For several miRNAs (miR-21, miR-155, miR-424, and miR-17-92), we show how their inferred transcriptional regulation impacts monocytic differentiation. Conclusions: The study demonstrates that miRNAs and their transcriptional regulatory control are integral molecular mechanisms during differentiation. Furthermore, it is the first study to decipher on a large-scale, how miRNAs are controlled by TFs during human monocytic differentiation. Subsequently, we have identified 12 candidate key controllers of miRNAs during this differentiation process. 2009 Schmeier et al; licensee BioMed Central Ltd.Citation
Schmeier S, MacPherson CR, Essack M, Kaur M, Schaefer U, et al. (2009) Deciphering the transcriptional circuitry of microRNA genes expressed during human monocytic differentiation. BMC Genomics 10: 595. doi:10.1186/1471-2164-10-595.Publisher
Springer NatureJournal
BMC GenomicsPubMed ID
20003307PubMed Central ID
PMC2797535ae974a485f413a2113503eed53cd6c53
10.1186/1471-2164-10-595
Scopus Count
The following license files are associated with this item:
Except where otherwise noted, this item's license is described as This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Related articles
- Inter- and intra-combinatorial regulation by transcription factors and microRNAs.
- Authors: Zhou Y, Ferguson J, Chang JT, Kluger Y
- Issue date: 2007 Oct 30
- Identification of Unique Key miRNAs, TFs, and mRNAs in Virulent MTB Infection Macrophages by Network Analysis.
- Authors: Zhu T, Liu H, Su L, Dawood A, Hu C, Chen X, Chen H, Chen Y, Guo A
- Issue date: 2021 Dec 29
- Network analysis of microRNAs and their regulation in human ovarian cancer.
- Authors: Schmeier S, Schaefer U, Essack M, Bajic VB
- Issue date: 2011 Nov 3
- Integrated transcriptomic and regulatory network analyses identify microRNA-200c as a novel repressor of human pluripotent stem cell-derived cardiomyocyte differentiation and maturation.
- Authors: Poon EN, Hao B, Guan D, Jun Li M, Lu J, Yang Y, Wu B, Wu SC, Webb SE, Liang Y, Miller AL, Yao X, Wang J, Yan B, Boheler KR
- Issue date: 2018 May 1
- Bioinformatics Analysis of Chicken miRNAs Associated with Monocyte to Macrophage Differentiation and Subsequent IFNγ Stimulated Activation.
- Authors: Irizarry KJL, Chan A, Kettle D, Kezian S, Ma D, Palacios L, Li QQ, Keeler CL, Drechsler Y
- Issue date: 2017
Related items
Showing items related by title, author, creator and subject.
-
TcoF-DB v2: update of the database of human and mouse transcription co-factors and transcription factor interactionsSchmeier, Sebastian; Alam, Tanvir; Essack, Magbubah; Bajic, Vladimir B. (Nucleic Acids Research, Oxford University Press (OUP), 2016-10-26) [Article]Transcription factors (TFs) play a pivotal role in transcriptional regulation, making them crucial for cell survival and important biological functions. For the regulation of transcription, interactions of different regulatory proteins known as transcription co-factors (TcoFs) and TFs are essential in forming necessary protein complexes. Although TcoFs themselves do not bind DNA directly, their influence on transcriptional regulation and initiation, although indirect, has been shown to be significant, with the functionality of TFs strongly influenced by the presence of TcoFs. In the TcoF-DB v2 database, we collect information on TcoFs. In this article, we describe updates and improvements implemented in TcoF-DB v2. TcoF-DB v2 provides several new features that enables exploration of the roles of TcoFs. The content of the database has significantly expanded, and is enriched with information from Gene Ontology, biological pathways, diseases and molecular signatures. TcoF-DB v2 now includes many more TFs; has substantially increased the number of human TcoFs to 958, and now includes information on mouse (418 new TcoFs). TcoF-DB v2 enables the exploration of information on TcoFs and allows investigations into their influence on transcriptional regulation in humans and mice. TcoF-DB v2 can be accessed at http://tcofdb.org/.
-
Database: TcoF-DB v2: update of the database of human and mouse transcription co-factors and transcription factor interactionsSchmeier, Sebastian; Alam, Tanvir; Essack, Magbubah; Bajic, Vladimir B. (2017-01-01) [Database]Abstract Transcription factors (TFs) play a pivotal role in transcriptional regulation, making them crucial for cell survival and important biological functions. For the regulation of transcription, interactions of different regulatory proteins known as transcription co-factors (TcoFs) and TFs are essential in forming necessary protein complexes. Although TcoFs themselves do not bind DNA directly, their influence on transcriptional regulation and initiation, although indirect, has been shown to be significant, with the functionality of TFs strongly influenced by the presence of TcoFs. In the TcoF-DB v2 database, we collect information on TcoFs. In this article, we describe updates and improvements implemented in TcoF-DB v2. TcoF-DB v2 provides several new features that enable exploration of the roles of TcoFs. The content of the database has significantly expanded and is enriched with information from Gene Ontology, biological pathways, diseases, and molecular signatures. TcoF-DB v2 now includes many more TFs; has substantially increased the number of human TcoFs to 958, and now includes information on mouse (418 new TcoFs). TcoF-DB v2 enables the exploration of information on TcoFs and allows investigations into their influence on transcriptional regulation in humans and mice. TcoF-DB v2 can be accessed at http://tcofdb.org/.
-
TcoF-DB: dragon database for human transcription co-factors and transcription factor interacting proteinsSchaefer, Ulf; Schmeier, Sebastian; Bajic, Vladimir B. (Nucleic Acids Research, Oxford University Press (OUP), 2010-10-21) [Article]The initiation and regulation of transcription in eukaryotes is complex and involves a large number of transcription factors (TFs), which are known to bind to the regulatory regions of eukaryotic DNA. Apart from TF-DNA binding, protein-protein interaction involving TFs is an essential component of the machinery facilitating transcriptional regulation. Proteins that interact with TFs in the context of transcription regulation but do not bind to the DNA themselves, we consider transcription co-factors (TcoFs). The influence of TcoFs on transcriptional regulation and initiation, although indirect, has been shown to be significant with the functionality of TFs strongly influenced by the presence of TcoFs. While the role of TFs and their interaction with regulatory DNA regions has been well-studied, the association between TFs and TcoFs has so far been given less attention. Here, we present a resource that is comprised of a collection of human TFs and the TcoFs with which they interact. Other proteins that have a proven interaction with a TF, but are not considered TcoFs are also included. Our database contains 157 high-confidence TcoFs and additionally 379 hypothetical TcoFs. These have been identified and classified according to the type of available evidence for their involvement in transcriptional regulation and their presence in the cell nucleus. We have divided TcoFs into four groups, one of which contains high-confidence TcoFs and three others contain TcoFs which are hypothetical to different extents. We have developed the Dragon Database for Human Transcription Co-Factors and Transcription Factor Interacting Proteins (TcoF-DB). A web-based interface for this resource can be freely accessed at http://cbrc.kaust.edu.sa/tcof/ and http://apps.sanbi.ac.za/tcof/. © The Author(s) 2010.