How is gene-regulatory evolution affected by cell-to-cell variability?

TL;DR

This study extends a classical gene-regulatory network evolution model to include developmental noise, revealing that cell-to-cell variability influences the evolution of robust, aligned, and motif-rich gene networks.

Contribution

It introduces an alignment score inspired by Hopfield networks to quantify gene interaction cohesion and demonstrates how noise promotes robustness and specific network motifs.

Findings

Increased noise levels promote network alignment and robustness.

Evolved networks show enriched feedforward and feedback motifs.

Cell-to-cell variability drives the evolution of resilient gene networks.

Abstract

The evolutionary origins of structural features in reconstructed gene-regulatory networks (GRNs) remain poorly understood, especially given the random aspects of gene expression. Here, we extend a classical model of GRN evolution to allow a single network to express a distribution of phenotypes through noisy developmental dynamics. Inspired by Hopfield networks, we introduce an alignment score that quantifies the cohesion of gene-gene interactions in the network to support a target stable phenotype. Overall, evolved populations optimized their fitness and reduced the length of their developmental paths. Increased noise levels promoted alignment, enriched coherent feedforward and positive feedback loops relative to non-evolved and noiseless controls, and buffered against mutational perturbations. Alignment provides intuitive interpretations because an increased number of appropriately signed gene-gene interactions is more redundant and thus more robust against developmental noise and mutations. Together, these results demonstrate that cell-to-cell variability exerts strong selective pressure, driving the evolution of aligned, robust, and motif-enriched GRN architectures.