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Patterns of development regulation within tissues
Expression of a given gene at the RNA level does not always correlate with expression at the protein level for many organisms. Walley et al. have built an integrated atlas of gene expression and regulatory networks in developing maize, using the same tissue samples to measure the transcriptome, proteome, and phosphoproteome. Coexpression networks from the transcriptome and proteome showed little overlap with each other, even though they showed enrichment of similar pathways. Integration of mRNA, protein, and phosphoprotein data sets improved the predictive power of the gene regulatory networks.
Science, this issue p. 814
Coexpression networks and gene regulatory networks (GRNs) are emerging as important tools for predicting functional roles of individual genes at a system-wide scale. To enable network reconstructions, we built a large-scale gene expression atlas composed of 62,547 messenger RNAs (mRNAs), 17,862 nonmodified proteins, and 6227 phosphoproteins harboring 31,595 phosphorylation sites quantified across maize development. Networks in which nodes are genes connected on the basis of highly correlated expression patterns of mRNAs were very different from networks that were based on coexpression of proteins. Roughly 85% of highly interconnected hubs were not conserved in expression between RNA and protein networks. However, networks from either data type were enriched in similar ontological categories and were effective in predicting known regulatory relationships. Integration of mRNA, protein, and phosphoprotein data sets greatly improved the predictive power of GRNs.