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Comparative co‐expression analysis in plant biology
Author(s) -
MOVAHEDI SARA,
VAN BEL MICHIEL,
HEYNDRICKX KEN S.,
VANDEPOELE KLAAS
Publication year - 2012
Publication title -
plant, cell and environment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.646
H-Index - 200
eISSN - 1365-3040
pISSN - 0140-7791
DOI - 10.1111/j.1365-3040.2012.02517.x
Subject(s) - computational biology , biology , gene , gene expression , gene expression profiling , expression (computer science) , phenotype , transcriptome , regulation of gene expression , modular design , genetics , computer science , programming language , operating system
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 protein–protein 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.