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Regulatory module network of basic/helix-loop-helix transcription factors in mouse brain.

Li J, Liu ZJ, Pan YC, Liu Q, Fu X, Cooper NG, Li Y, Qiu M, Shi T - Genome Biol. (2007)

Bottom Line: Literature mining provides additional support for five modules.Our network is reliable and very informative for understanding the role of bHLH TFs in mouse brain development and function.It provides a framework for future experimental analyses.

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China. lijing003@sjtu.edu.cn

ABSTRACT

Background: The basic/helix-loop-helix (bHLH) proteins are important components of the transcriptional regulatory network, controlling a variety of biological processes, especially the development of the central nervous system. Until now, reports describing the regulatory network of the bHLH transcription factor (TF) family have been scarce. In order to understand the regulatory mechanisms of bHLH TFs in mouse brain, we inferred their regulatory network from genome-wide gene expression profiles with the module networks method.

Results: A regulatory network comprising 15 important bHLH TFs and 153 target genes was constructed. The network was divided into 28 modules based on expression profiles. A regulatory-motif search shows the complexity and diversity of the network. In addition, 26 cooperative bHLH TF pairs were also detected in the network. This cooperation suggests possible physical interactions or genetic regulation between TFs. Interestingly, some TFs in the network regulate more than one module. A novel cross-repression between Neurod6 and Hey2 was identified, which may control various functions in different brain regions. The presence of TF binding sites (TFBSs) in the promoter regions of their target genes validates more than 70% of TF-target gene pairs of the network. Literature mining provides additional support for five modules. More importantly, the regulatory relationships among selected key components are all validated in mutant mice.

Conclusion: Our network is reliable and very informative for understanding the role of bHLH TFs in mouse brain development and function. It provides a framework for future experimental analyses.

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Related in: MedlinePlus

Downregulation of Olig2 and TCF4 expression in Olig1 mutants. Spinal cord sections from E18.5 (a) wild-type and (b) Olig1 mutant embryos were subjected to immunofluorescence labeling (in red) with anti-Olig2 antibody. The number of Olig2+ cells was significantly reduced in the mutants. (c) Statistical analysis of Olig2+ cells in the Olig1+/- and Olig1-/- spinal cords compared to the wild-type (wt). Values were presented as mean ± standard deviation. (d) Regulation of the largest module shows that the Olig1 regulates the expression of Olig2. (e, f) Spinal cord sections from E18.5 wild-type (e) and Olig1 mutant (f) embryos were subject to in situ RNA hybridization with TCF4 antisense riboprobe. Expression of TCF4 was not detected in the mutants at this stage.
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Figure 5: Downregulation of Olig2 and TCF4 expression in Olig1 mutants. Spinal cord sections from E18.5 (a) wild-type and (b) Olig1 mutant embryos were subjected to immunofluorescence labeling (in red) with anti-Olig2 antibody. The number of Olig2+ cells was significantly reduced in the mutants. (c) Statistical analysis of Olig2+ cells in the Olig1+/- and Olig1-/- spinal cords compared to the wild-type (wt). Values were presented as mean ± standard deviation. (d) Regulation of the largest module shows that the Olig1 regulates the expression of Olig2. (e, f) Spinal cord sections from E18.5 wild-type (e) and Olig1 mutant (f) embryos were subject to in situ RNA hybridization with TCF4 antisense riboprobe. Expression of TCF4 was not detected in the mutants at this stage.

Mentions: Recent studies in the spinal cord showed that Olig1 comprises the combinatorial code for the subtype specification of neurons and glial cells (astrocytes or oligodendrocytes) together with Olig2 [32], which is a target gene of Olig1 in the largest module of the network. The regulatory module (Figure 5d) shows that Olig1 positively regulates Olig2 in different brain tissues. Otherwise, there are both direct (Olig1→Olig2) and indirect regulatory paths (Olig1→Nuerod6→Mitf→Olig2) connecting Olig1 and Olig2. An indirect connection would presumably render Olig2 less sensitive to the inactivation of Olig1while the directed connection would provide more sensitivity.


Regulatory module network of basic/helix-loop-helix transcription factors in mouse brain.

Li J, Liu ZJ, Pan YC, Liu Q, Fu X, Cooper NG, Li Y, Qiu M, Shi T - Genome Biol. (2007)

Downregulation of Olig2 and TCF4 expression in Olig1 mutants. Spinal cord sections from E18.5 (a) wild-type and (b) Olig1 mutant embryos were subjected to immunofluorescence labeling (in red) with anti-Olig2 antibody. The number of Olig2+ cells was significantly reduced in the mutants. (c) Statistical analysis of Olig2+ cells in the Olig1+/- and Olig1-/- spinal cords compared to the wild-type (wt). Values were presented as mean ± standard deviation. (d) Regulation of the largest module shows that the Olig1 regulates the expression of Olig2. (e, f) Spinal cord sections from E18.5 wild-type (e) and Olig1 mutant (f) embryos were subject to in situ RNA hybridization with TCF4 antisense riboprobe. Expression of TCF4 was not detected in the mutants at this stage.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2258200&req=5

Figure 5: Downregulation of Olig2 and TCF4 expression in Olig1 mutants. Spinal cord sections from E18.5 (a) wild-type and (b) Olig1 mutant embryos were subjected to immunofluorescence labeling (in red) with anti-Olig2 antibody. The number of Olig2+ cells was significantly reduced in the mutants. (c) Statistical analysis of Olig2+ cells in the Olig1+/- and Olig1-/- spinal cords compared to the wild-type (wt). Values were presented as mean ± standard deviation. (d) Regulation of the largest module shows that the Olig1 regulates the expression of Olig2. (e, f) Spinal cord sections from E18.5 wild-type (e) and Olig1 mutant (f) embryos were subject to in situ RNA hybridization with TCF4 antisense riboprobe. Expression of TCF4 was not detected in the mutants at this stage.
Mentions: Recent studies in the spinal cord showed that Olig1 comprises the combinatorial code for the subtype specification of neurons and glial cells (astrocytes or oligodendrocytes) together with Olig2 [32], which is a target gene of Olig1 in the largest module of the network. The regulatory module (Figure 5d) shows that Olig1 positively regulates Olig2 in different brain tissues. Otherwise, there are both direct (Olig1→Olig2) and indirect regulatory paths (Olig1→Nuerod6→Mitf→Olig2) connecting Olig1 and Olig2. An indirect connection would presumably render Olig2 less sensitive to the inactivation of Olig1while the directed connection would provide more sensitivity.

Bottom Line: Literature mining provides additional support for five modules.Our network is reliable and very informative for understanding the role of bHLH TFs in mouse brain development and function.It provides a framework for future experimental analyses.

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China. lijing003@sjtu.edu.cn

ABSTRACT

Background: The basic/helix-loop-helix (bHLH) proteins are important components of the transcriptional regulatory network, controlling a variety of biological processes, especially the development of the central nervous system. Until now, reports describing the regulatory network of the bHLH transcription factor (TF) family have been scarce. In order to understand the regulatory mechanisms of bHLH TFs in mouse brain, we inferred their regulatory network from genome-wide gene expression profiles with the module networks method.

Results: A regulatory network comprising 15 important bHLH TFs and 153 target genes was constructed. The network was divided into 28 modules based on expression profiles. A regulatory-motif search shows the complexity and diversity of the network. In addition, 26 cooperative bHLH TF pairs were also detected in the network. This cooperation suggests possible physical interactions or genetic regulation between TFs. Interestingly, some TFs in the network regulate more than one module. A novel cross-repression between Neurod6 and Hey2 was identified, which may control various functions in different brain regions. The presence of TF binding sites (TFBSs) in the promoter regions of their target genes validates more than 70% of TF-target gene pairs of the network. Literature mining provides additional support for five modules. More importantly, the regulatory relationships among selected key components are all validated in mutant mice.

Conclusion: Our network is reliable and very informative for understanding the role of bHLH TFs in mouse brain development and function. It provides a framework for future experimental analyses.

Show MeSH
Related in: MedlinePlus