Gene co-expression poorly reflects expert-curated transcription factor-target gene regulation

Gene co-expression networks (GCNs) are networks with genes as nodes and edges that indicate correlation between two genes' expression profiles across several samples. Since GCNs are conceptually simply and straightforward to compute from gene expression data, they are often used as proxies for gene regulatory networks (GRNs) whose edges encode transcriptional regulation between transcription factor (TFs) and their target genes. However, many other mechanisms besides direct transcriptional regulation can lead to correlated expression profiles, including joint co-regulation and stoichiometry underlying protein-protein interactions (PPIs). We hence asked the simple question if GCNs are indeed good proxies for GRNs, and addressed it by comparing GCNs inferred from 15 healthy tissue and 15 corresponding cancer gene expression datasets to a state-of-the-art expert-curated GRN, a co-regulation network derived from the expert-curated GRN, as well as a widely used PPI network. Our results indicate that GCNs mostly reflect PPIs and joint co-regulation, casting doubt on the usage of gene co-expression as a proxy for direct transcriptional regulation.