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Transcription regulatory networks in Caenorhabditis elegans inferred through reverse-engineering of gene expression profiles constitute biological hypotheses for metazoan development

Vanessa Vermeirssen UGent, Anagha Madhusudan Joshi UGent, Tom Michoel UGent, Eric Bonnet UGent, Tine Casneuf and Yves Van de Peer UGent (2009) MOLECULAR BIOSYSTEMS. 5(12). p.1817-1830
abstract
Differential gene expression governs the development, function and pathology of multicellular organisms. Transcription regulatory networks study differential gene expression at a systems level by mapping the interactions between regulatory proteins and target genes. While microarray transcription profiles are the most abundant data for gene expression, it remains challenging to correctly infer the underlying transcription regulatory networks. The reverse-engineering algorithm LeMoNe (learning module networks) uses gene expression profiles to extract ensemble transcription regulatory networks of coexpression modules and their prioritized regulators. Here we apply LeMoNe to a compendium of microarray studies of the worm Caenorhabditis elegans. We obtain 248 modules with a regulation program for 5020 genes and 426 regulators and a total of 24 012 predicted transcription regulatory interactions. Through GO enrichment analysis, comparison with the gene-gene association network WormNet and integration of other biological data, we show that LeMoNe identifies functionally coherent coexpression modules and prioritizes regulators that relate to similar biological processes as the module genes. Furthermore, we can predict new functional relationships for uncharacterized genes and regulators. Based on modules involved in molting, meiosis and oogenesis, ciliated sensory neurons and mitochondrial metabolism, we illustrate the value of LeMoNe as a biological hypothesis generator for differential gene expression in greater detail. In conclusion, through reverse-engineering of C. elegans expression data, we obtained transcription regulatory networks that can provide further insight into metazoan development.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
DNA INTERACTION NETWORK, ZINC-FINGER PROTEINS, C. ELEGANS, OOCYTE MATURATION, MODULE NETWORKS, MESSENGER-RNAS, LIFE-SPAN, DAF-16, IDENTIFICATION, LONGEVITY
journal title
MOLECULAR BIOSYSTEMS
Mol. Biosyst.
volume
5
issue
12
pages
14 pages
publisher
ROYAL SOC CHEMISTRY
place of publication
CAMBRIDGE
Web of Science type
Article
Web of Science id
000271727600040
JCR category
BIOCHEMISTRY & MOLECULAR BIOLOGY
JCR impact factor
4.015 (2009)
JCR rank
72/281 (2009)
JCR quartile
1 (2009)
ISSN
1742-206X
DOI
10.1039/b908108a
language
English
UGent publication?
yes
classification
A1
copyright statement
I don't know the status of the copyright for this publication
id
798261
handle
http://hdl.handle.net/1854/LU-798261
date created
2009-12-02 17:35:31
date last changed
2009-12-16 14:12:06
@article{798261,
  abstract     = {Differential gene expression governs the development, function and pathology of multicellular organisms. Transcription regulatory networks study differential gene expression at a systems level by mapping the interactions between regulatory proteins and target genes. While microarray transcription profiles are the most abundant data for gene expression, it remains challenging to correctly infer the underlying transcription regulatory networks. The reverse-engineering algorithm LeMoNe (learning module networks) uses gene expression profiles to extract ensemble transcription regulatory networks of coexpression modules and their prioritized regulators. Here we apply LeMoNe to a compendium of microarray studies of the worm Caenorhabditis elegans. We obtain 248 modules with a regulation program for 5020 genes and 426 regulators and a total of 24 012 predicted transcription regulatory interactions. Through GO enrichment analysis, comparison with the gene-gene association network WormNet and integration of other biological data, we show that LeMoNe identifies functionally coherent coexpression modules and prioritizes regulators that relate to similar biological processes as the module genes. Furthermore, we can predict new functional relationships for uncharacterized genes and regulators. Based on modules involved in molting, meiosis and oogenesis, ciliated sensory neurons and mitochondrial metabolism, we illustrate the value of LeMoNe as a biological hypothesis generator for differential gene expression in greater detail. In conclusion, through reverse-engineering of C. elegans expression data, we obtained transcription regulatory networks that can provide further insight into metazoan development.},
  author       = {Vermeirssen, Vanessa and Joshi, Anagha Madhusudan and Michoel, Tom and Bonnet, Eric and Casneuf, Tine and Van de Peer, Yves},
  issn         = {1742-206X},
  journal      = {MOLECULAR BIOSYSTEMS},
  keyword      = {DNA INTERACTION NETWORK,ZINC-FINGER PROTEINS,C. ELEGANS,OOCYTE MATURATION,MODULE NETWORKS,MESSENGER-RNAS,LIFE-SPAN,DAF-16,IDENTIFICATION,LONGEVITY},
  language     = {eng},
  number       = {12},
  pages        = {1817--1830},
  publisher    = {ROYAL SOC CHEMISTRY},
  title        = {Transcription regulatory networks in Caenorhabditis elegans inferred through reverse-engineering of gene expression profiles constitute biological hypotheses for metazoan development},
  url          = {http://dx.doi.org/10.1039/b908108a},
  volume       = {5},
  year         = {2009},
}

Chicago
Vermeirssen, Vanessa, Anagha Madhusudan Joshi, Tom Michoel, Eric Bonnet, Tine Casneuf, and Yves Van de Peer. 2009. “Transcription Regulatory Networks in Caenorhabditis Elegans Inferred Through Reverse-engineering of Gene Expression Profiles Constitute Biological Hypotheses for Metazoan Development.” Molecular Biosystems 5 (12): 1817–1830.
APA
Vermeirssen, Vanessa, Joshi, A. M., Michoel, T., Bonnet, E., Casneuf, T., & Van de Peer, Y. (2009). Transcription regulatory networks in Caenorhabditis elegans inferred through reverse-engineering of gene expression profiles constitute biological hypotheses for metazoan development. MOLECULAR BIOSYSTEMS, 5(12), 1817–1830.
Vancouver
1.
Vermeirssen V, Joshi AM, Michoel T, Bonnet E, Casneuf T, Van de Peer Y. Transcription regulatory networks in Caenorhabditis elegans inferred through reverse-engineering of gene expression profiles constitute biological hypotheses for metazoan development. MOLECULAR BIOSYSTEMS. CAMBRIDGE: ROYAL SOC CHEMISTRY; 2009;5(12):1817–30.
MLA
Vermeirssen, Vanessa, Anagha Madhusudan Joshi, Tom Michoel, et al. “Transcription Regulatory Networks in Caenorhabditis Elegans Inferred Through Reverse-engineering of Gene Expression Profiles Constitute Biological Hypotheses for Metazoan Development.” MOLECULAR BIOSYSTEMS 5.12 (2009): 1817–1830. Print.