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Comparative co-expression analysis in plant biology

Sara Movahedi UGent, Michiel Van Bel UGent, Ken Heyndrickx UGent and Klaas Vandepoele UGent (2012) PLANT CELL AND ENVIRONMENT. 35(10). p.1787-1798
abstract
The analysis of gene expression data generated by high-throughput microarray transcript profiling experiments has shown that transcriptionally coordinated genes are often functionally related. Based on large-scale expression compendia grouping multiple experiments, this guilt-by-association principle has been applied to study modular gene programmes, identify cis-regulatory elements or predict functions for unknown genes in different model plants. Recently, several studies have demonstrated how, through the integration of gene homology and expression information, correlated gene expression patterns can be compared between species. The incorporation of detailed functional annotations as well as experimental data describing proteinprotein interactions, phenotypes or tissue specific expression, provides an invaluable source of information to identify conserved gene modules and translate biological knowledge from model organisms to crops. In this review, we describe the different steps required to systematically compare expression data across species. Apart from the technical challenges to compute and display expression networks from multiple species, some future applications of plant comparative transcriptomics are highlighted.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (review)
publication status
published
subject
keyword
orthology, GENE-EXPRESSION ATLAS, ARABIDOPSIS-THALIANA, MICROARRAY ANALYSIS, TRANSCRIPTOME ATLAS, CORRELATION NETWORK, COMPARATIVE GENOMICS, expression analysis, comparative genomics, bioinformatics, RICE, DATABASE, MODULES, TOOLS
journal title
PLANT CELL AND ENVIRONMENT
Plant Cell Environ.
volume
35
issue
10
pages
1787 - 1798
Web of Science type
Review
Web of Science id
000308395600007
JCR category
PLANT SCIENCES
JCR impact factor
5.135 (2012)
JCR rank
14/193 (2012)
JCR quartile
1 (2012)
ISSN
0140-7791
DOI
10.1111/j.1365-3040.2012.02517.x
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
3033907
handle
http://hdl.handle.net/1854/LU-3033907
date created
2012-10-24 16:02:52
date last changed
2013-05-06 11:10:36
@article{3033907,
  abstract     = {The analysis of gene expression data generated by high-throughput microarray transcript profiling experiments has shown that transcriptionally coordinated genes are often functionally related. Based on large-scale expression compendia grouping multiple experiments, this guilt-by-association principle has been applied to study modular gene programmes, identify cis-regulatory elements or predict functions for unknown genes in different model plants. Recently, several studies have demonstrated how, through the integration of gene homology and expression information, correlated gene expression patterns can be compared between species. The incorporation of detailed functional annotations as well as experimental data describing proteinprotein interactions, phenotypes or tissue specific expression, provides an invaluable source of information to identify conserved gene modules and translate biological knowledge from model organisms to crops. In this review, we describe the different steps required to systematically compare expression data across species. Apart from the technical challenges to compute and display expression networks from multiple species, some future applications of plant comparative transcriptomics are highlighted.},
  author       = {Movahedi, Sara and Van Bel, Michiel and Heyndrickx, Ken and Vandepoele, Klaas},
  issn         = {0140-7791},
  journal      = {PLANT CELL AND ENVIRONMENT},
  keyword      = {orthology,GENE-EXPRESSION ATLAS,ARABIDOPSIS-THALIANA,MICROARRAY ANALYSIS,TRANSCRIPTOME ATLAS,CORRELATION NETWORK,COMPARATIVE GENOMICS,expression analysis,comparative genomics,bioinformatics,RICE,DATABASE,MODULES,TOOLS},
  language     = {eng},
  number       = {10},
  pages        = {1787--1798},
  title        = {Comparative co-expression analysis in plant biology},
  url          = {http://dx.doi.org/10.1111/j.1365-3040.2012.02517.x},
  volume       = {35},
  year         = {2012},
}

Chicago
Movahedi, Sara, Michiel Van Bel, Ken Heyndrickx, and Klaas Vandepoele. 2012. “Comparative Co-expression Analysis in Plant Biology.” Plant Cell and Environment 35 (10): 1787–1798.
APA
Movahedi, S., Van Bel, M., Heyndrickx, K., & Vandepoele, K. (2012). Comparative co-expression analysis in plant biology. PLANT CELL AND ENVIRONMENT, 35(10), 1787–1798.
Vancouver
1.
Movahedi S, Van Bel M, Heyndrickx K, Vandepoele K. Comparative co-expression analysis in plant biology. PLANT CELL AND ENVIRONMENT. 2012;35(10):1787–98.
MLA
Movahedi, Sara, Michiel Van Bel, Ken Heyndrickx, et al. “Comparative Co-expression Analysis in Plant Biology.” PLANT CELL AND ENVIRONMENT 35.10 (2012): 1787–1798. Print.