Gene network architecture, mutation and selection collectively drive developmental pattern evolvability and predictability

Abstract

A hallmark of development is the generation of spatial patterns driven by morphogen gradients and Gene Regulatory Networks (GRNs). Although the mechanistic basis by which GRNs orchestrate cellular responses and tissue patterning during development is well understood, their evolutionary dynamics remain less clear. Still, utations in regulatory elements that govern GRN-driven patterning are a key mechanism for patterning evolution. In this study, we use the de novo evolution of a stripe phenotype as a model framework to investigate the evolutionary dynamics associated with the emergence of new spatial gene expression boundaries and the adjustment of existing boundaries. To probe general principles of GRN-driven pattern evolution we introduce a new high-throughput theoretical framework that rapidly produces a comprehensive dataset of evolutionary trajectories. We leverage this large dataset to investigate the types of mutations that drive different phenotypic shifts in spatial patterning. Our findings suggest that the order in which mutations in gene-gene interactions appear, and the specific combination of gene-gene interactions that mutate together determine the evolvability of novel spatial gene expression patterns. We interpret our results in the context of epistatic effects that naturally arise in networks of interconnected genes, and show how contingencies and constraints emerge in our system. Our results elucidate the interplay between mutation and gene network organization, revealing how historical contingencies arise and impact the evolvability of GRNs and the predictability of their evolutionary outcomes.