the evolution of regulatory systems

From simple prokaryotic gene networks—where transcription factors just switch genes on and off—evolution has produced organisms with thousands of coordinated cell types, and humans have built legal codes covering every corner of life. Across both, one pattern holds: rules beget rules, and regulatory systems keep growing in size and complexity as they evolve. What we don’t yet have is a quantitative account of how. What are the Laws governing evolving Laws?

Gene-regulatory network (GRN) data is a great cross-section—tens of thousands of organisms’ worth—but genuinely long-running data on how regulation evolves over time is rare in biology; even the longest lab evolution experiments only span four decades. Human rule systems don’t have that problem. We’ve shown that the U.S. Code and the Laws of Cricket both grow as power laws in system size—the Laws of Cricket, with 300 years of data behind them, are an especially clean example—echoing how regulatory gene content scales with genome size. Forthcoming work finds the same pattern in Wikipedia and the Laws of Rugby, and across every dataset we’ve studied so far, the same signatures keep showing up: power-law growth, power-law degree distributions, major evolutionary transitions, and increasing rule specificity, pointing to something universal about how regulation evolves.

We’re now testing a simple mechanistic idea: that rule-making is a response to rule-breaking. A broken rule triggers new rules that correct for it, while shifting the threshold for what counts as a violation next time—much like a governing body updating its own laws. We’re checking this against real case studies (tax code, rugby scrums) to work out how much rule growth is organic refinement versus reaction to one-off shocks.

A few open questions we’re chasing:

• What are the Laws governing evolving Laws?
• Is rule-making generically a response to rule-breaking, across systems as different as gene networks and legal codes?
• How much of long-term rule growth is endogenous refinement versus exogenous shocks?

Research from the $R^3$ Lab on the evolution of regulatory systems:

• Jeong*, D., Holehouse*, J., Yoon, J., Kempes, C. P., West, G. B., & Youn, H. (2026). A Dataset Showing a Century of Evolution in the Complexity of the United States Legal Code. Scientific Data. Joint first and corresponding author.
• Chia, D., Youn, H., Singer, J., Jeong, D., Kempes, C., Ogbunugafor, C. B., West, G. B., & Holehouse, J. (2026). Three Centuries of the Laws of Cricket Reveal Core Principles of the Evolution of Regulatory Mechanisms. arXiv:2607.05586. Conditional acceptance at PNAS.
• Kumar, A., & Holehouse, J. (2026). Branching under First-Passage Resetting. arXiv:2605.16693. In revision at Physical Review Letters.
• Dzib, L. I. E., & Holehouse, J. (2026). How is gene-regulatory evolution affected by cell-to-cell variability? arXiv:2604.26082. In revision at Evolution.
• Holehouse, J. (2024–present). The Sports Rules Project.
• Holehouse, J., Chia, D., West, G. B., Salinas, S., Miller, A., & Ogbunugafor, C. B. The Social Systems Biology of Rules and Regulations. Forthcoming.