Inferring the dynamics of selective constraints across complex ontogenies

Organisms undergo a series of complex phenotypic changes throughout their life cycles to exploit different ecological niches. Theory suggests the coordination required for such transitions can constrain evolutionary variation, producing developmental hourglass patterns—stages marked by reduced phenotypic and/or genetic variation. Although well established in animal embryogenesis, it remains unclear whether such patterns occur in other developmental programmes. Existing approaches for studying developmental hourglass patterns, which relate gene age and sequence divergence to their temporal expression pattern, are often susceptible to noise because of historical contingency and developmental system drift. Furthermore, recent studies suggest selective constraints fluctuate more dynamically across ontogeny. Here, I present a theoretical and empirical framework for using population-level variation in developmental gene/trait expression dynamics to infer the strength of selective constraints across an ontogeny. I first provide theoretical precedence for this approach, showing that patterns of variation in gene/trait expression within populations are stable and recapitulate the latent ontogenetic selective dynamics. I then describe an empirical approach for inferring latent selective dynamics and use it to infer the dynamics of selective constraints from population-level transcriptional data of various stages across the monarch butterfly Danaus plexippus metamorphosis.