Feed-forward motifs in transcription factor networks evolved to filter out spurious signals? ‘Just-so’ no longer

Biosystems Analytics

Mechanistic computational models, particularly rule-based stochastic models, are a vital complement to wet-lab experiments (and a vital chunk of our work at Amber Biology), but can also provide insights into evolutionary processes. In a paper just published in Nature Communications, the team, which included Kun Xiong, myself, Mark Siegal and Joanna Masel, asked whether a particular 3-node feed-forward loop motif (specifically the type 1 coherent FFL, or C1-FFL, widely hypothesized to have evolved to filter out spurious signals, actually evolved for that purpose. Due to it’s overrepresentation in the transcriptional networks of many species, and it’s demonstrated function in filtering out these signals many researchers have previously accepted a kind of ‘just-so’ account of the feed-forward motif. To test this hypothesis properly, we built a detailed stochastic model of the dynamics of transcriptional networks, and then allowed the network to evolve under selection for the function, and without…

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