A Unified Framework to Dissect Robustness, Plasticity, Evolvability and Canalisation of Biological Function
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A unique balance of seemingly contradictory properties like robustness and plasticity, or evolvability and functional canalisation, characterises biological systems. To understand the basis of these properties, we look into gene regulation, which is at the core of biological function. We simulate dynamical models of over 190 million genetic circuits covering all possible three-gene circuit structures. We develop a computational pipeline to classify these circuits into functional clusters by matching the shape of their temporal responses. Thus, we generate a dataset containing circuit structure, parameters and a corresponding functional label. Our key finding is a finite list of 20 functions that three-node genetic circuits can perform. Moreover, the space of structure and parameters for these circuits tend to be primed for responses that stabilise over time following a perturbation. Every structure has the potential to exhibit multifunctionality with a range of 2–17 functions contingent upon parameters. We quantify network degeneracy and show that many structural changes can be made to a circuit without changing its function. We then define three quantities: structural, parametric, and functional diversities. For a pair of circuits in our generated dataset, we derive these diversities and present a unified framework that analyses the four key biological properties—robustness, plasticity, evolvability, and functional canalisation. Using this unified framework, we identify that only 6.5% of network structures are non-plastic, while it is always possible to find parameter sets for every three-node network to exhibit parametric robustness. We identify functionally canalised circuits from structure pairs that can be interchanged for a large number of parameter sets without a change in function. Overall, our framework offers insights into the fundamental organisation of biological networks by thorough analysis of three-node networks.
Significance Statement
Biological systems exhibit remarkable properties like robustness, plasticity, evolvability, and canalisation. This study presents a unified computational framework to understand these properties by exhaustively exploring the design space of three-node genetic circuits, identifying that only 20 functions are achievable, and revealing a natural bias toward stability. We uncover key principles of network degeneracy and multifunctionality, highlighting the versatility of genetic circuits. By analysing structural, parametric, and functional diversities, we identify structural and parametric changes that can transition a genetic circuit from robust behaviour to plasticity or from being canalised to becoming evolvable. Our work advances theoretical insights into biological function. It provides a method to identify alternate designs and parametric conditions for genetic circuits, paving the way for the design of novel synthetic genetic circuits.
