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Systematic identification of functional plant modules through the integration of complementary data sources

Ken Heyndrickx UGent and Klaas Vandepoele UGent (2012) PLANT PHYSIOLOGY. 159(3). p.884-901
abstract
A major challenge is to unravel how genes interact and are regulated to exert specific biological functions. The integration of genome-wide functional genomics data, followed by the construction of gene networks, provides a powerful approach to identify functional gene modules. Large-scale expression data, functional gene annotations, experimental protein-protein interactions, and transcription factor-target interactions were integrated to delineate modules in Arabidopsis (Arabidopsis thaliana). The different experimental input data sets showed little overlap, demonstrating the advantage of combining multiple data types to study gene function and regulation. In the set of 1,563 modules covering 13,142 genes, most modules displayed strong coexpression, but functional and cis-regulatory coherence was less prevalent. Highly connected hub genes showed a significant enrichment toward embryo lethality and evidence for cross talk between different biological processes. Comparative analysis revealed that 58% of the modules showed conserved coexpression across multiple plants. Using module-based functional predictions, 5,562 genes were annotated, and an evaluation experiment disclosed that, based on 197 recently experimentally characterized genes, 38.1% of these functions could be inferred through the module context. Examples of confirmed genes of unknown function related to cell wall biogenesis, xylem and phloem pattern formation, cell cycle, hormone stimulus, and circadian rhythm highlight the potential to identify new gene functions. The module-based predictions offer new biological hypotheses for functionally unknown genes in Arabidopsis (1,701 genes) and six other plant species (43,621 genes). Furthermore, the inferred modules provide new insights into the conservation of coexpression and coregulation as well as a starting point for comparative functional annotation.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
COMPARATIVE GENOMICS, ARABIDOPSIS-THALIANA, TRANSCRIPTION FACTOR, SCALE DATA SETS, CIS-REGULATORY ELEMENTS, PROTEIN-PROTEIN INTERACTIONS, SECONDARY CELL-WALL, GENE-COEXPRESSION NETWORK, BINDING-SITES, HYPOTHESIS GENERATION
journal title
PLANT PHYSIOLOGY
Plant Physiol.
volume
159
issue
3
pages
884 - 901
Web of Science type
Article
Web of Science id
000305958000002
JCR category
PLANT SCIENCES
JCR impact factor
6.555 (2012)
JCR rank
8/193 (2012)
JCR quartile
1 (2012)
ISSN
0032-0889
DOI
10.1104/pp.112.196725
project
Bioinformatics: from nucleotids to networks (N2N)
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
2964899
handle
http://hdl.handle.net/1854/LU-2964899
date created
2012-07-30 11:59:32
date last changed
2013-05-06 11:10:19
@article{2964899,
  abstract     = {A major challenge is to unravel how genes interact and are regulated to exert specific biological functions. The integration of genome-wide functional genomics data, followed by the construction of gene networks, provides a powerful approach to identify functional gene modules. Large-scale expression data, functional gene annotations, experimental protein-protein interactions, and transcription factor-target interactions were integrated to delineate modules in Arabidopsis (Arabidopsis thaliana). The different experimental input data sets showed little overlap, demonstrating the advantage of combining multiple data types to study gene function and regulation. In the set of 1,563 modules covering 13,142 genes, most modules displayed strong coexpression, but functional and cis-regulatory coherence was less prevalent. Highly connected hub genes showed a significant enrichment toward embryo lethality and evidence for cross talk between different biological processes. Comparative analysis revealed that 58\% of the modules showed conserved coexpression across multiple plants. Using module-based functional predictions, 5,562 genes were annotated, and an evaluation experiment disclosed that, based on 197 recently experimentally characterized genes, 38.1\% of these functions could be inferred through the module context. Examples of confirmed genes of unknown function related to cell wall biogenesis, xylem and phloem pattern formation, cell cycle, hormone stimulus, and circadian rhythm highlight the potential to identify new gene functions. The module-based predictions offer new biological hypotheses for functionally unknown genes in Arabidopsis (1,701 genes) and six other plant species (43,621 genes). Furthermore, the inferred modules provide new insights into the conservation of coexpression and coregulation as well as a starting point for comparative functional annotation.},
  author       = {Heyndrickx, Ken and Vandepoele, Klaas},
  issn         = {0032-0889},
  journal      = {PLANT PHYSIOLOGY},
  keyword      = {COMPARATIVE GENOMICS,ARABIDOPSIS-THALIANA,TRANSCRIPTION FACTOR,SCALE DATA SETS,CIS-REGULATORY ELEMENTS,PROTEIN-PROTEIN INTERACTIONS,SECONDARY CELL-WALL,GENE-COEXPRESSION NETWORK,BINDING-SITES,HYPOTHESIS GENERATION},
  language     = {eng},
  number       = {3},
  pages        = {884--901},
  title        = {Systematic identification of functional plant modules through the integration of complementary data sources},
  url          = {http://dx.doi.org/10.1104/pp.112.196725},
  volume       = {159},
  year         = {2012},
}

Chicago
Heyndrickx, Ken, and Klaas Vandepoele. 2012. “Systematic Identification of Functional Plant Modules Through the Integration of Complementary Data Sources.” Plant Physiology 159 (3): 884–901.
APA
Heyndrickx, K., & Vandepoele, K. (2012). Systematic identification of functional plant modules through the integration of complementary data sources. PLANT PHYSIOLOGY, 159(3), 884–901.
Vancouver
1.
Heyndrickx K, Vandepoele K. Systematic identification of functional plant modules through the integration of complementary data sources. PLANT PHYSIOLOGY. 2012;159(3):884–901.
MLA
Heyndrickx, Ken, and Klaas Vandepoele. “Systematic Identification of Functional Plant Modules Through the Integration of Complementary Data Sources.” PLANT PHYSIOLOGY 159.3 (2012): 884–901. Print.