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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.
Highlights
A major challenge is to unravel how genes interact and are regulated to exert specific biological functions
Numerous expression network analyses have been performed in Arabidopsis, some studies focused on a specific process using guide genes to draw new hypotheses about the functional interplay between functionally known and unknown genes based on guilt by association (Lisso et al, 2005; Persson et al, 2005; Wei et al, 2006)
Our results revealed that currently available experimental data sources are highly complementary, different functional categories show varying levels of regulatory complexity, a large number of Arabidopsis gene modules are conserved in other plant species, and conserved modules provide a valuable source to study gene functions
Summary
A major challenge is to unravel how genes interact and are regulated to exert specific biological functions. A few Arabidopsis studies have been published reporting large networks for function prediction based on multiple data types These networks were built combining expression and PPI data with sequence data (Kourmpetis et al, 2011), genetic and physical interaction data (Warde-Farley et al, 2010), phylogenetic profiles and gene location (Bradford et al, 2010), and the integration of functional genomics, proteomics, and comparative genomics data sets (Lee et al, 2010). The analysis of conserved modules with specific functions provides an invaluable approach for biological gene discovery in model species and for the translation of new gene functions into species with agricultural or economical value (Movahedi et al, 2012)
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