Emergence of co-expression in gene regulatory networks

Transcriptomes are known to organize themselves into gene co-expression clusters or modules where groups of genes display distinct patterns coordinated synchronous expression across independent biological samples. The functional significance these is suggested by the fact that highly coexpressed tend be enriched in involved common functions and processes. While widely assumed reflect close regulatory proximity, validity this assumption remains unclear. Here we use a simple synthetic network (GRN) model contrast resulting structure produced networks with their architecture measured available human data. Using randomization tests, found levels observed simulated data were, just as empirical data, significantly higher than expected chance. When examining source correlated expression, individual regulators, both experimental fail, on average, immediate targets. However, pairs share at least one regulator, while most sharing regulators do not necessarily expression. Our results demonstrate widespread naturally emerges networks, it reliable direct indicator active co-regulation given cellular context.