Dynamical systems of fate and form

Developmental biology has long drawn on dynamical systems to understand the diverging fates and the emerging form of the developing embryo. Cell differentiation and morphogenesis unfold in high-dimensional gene-expression spaces and position spaces. Yet, their stable and reproducible outcomes suggest low-dimensional geometric structures-e.g., fixed points, manifolds, and dynamic attracting and repelling structures-that organize cell trajectories in both spaces. This review surveys the history and recent advances in dynamical systems frameworks for development. We focus on techniques for extracting the organizing geometric structures of cell fate decisions and morphogenetic movements from experiments, as well as their interconnections.

doi: 10.1016/j.semcdb.2025.103620

Embryogenesis integrates morphogenesis - coordinated cell movements - with morphogen patterning and cell differentiation. While largely studied independently, morphogenesis and patterning often unfold simultaneously in early embryos. Yet how cell movements affect morphogen transport and cells' exposure over time remains unclear, as most pattern formation models assume static tissues. Here we develop a theoretical framework for morphogen patterning in dynamic tissues, recasting advection-reaction-diffusion equations in the cells' moving reference frames. This framework (i) elucidates how morphogenesis mediates morphogen transport and compartmentalization: cell-cell diffusive transport is enhanced at multicellular flow attractors, while repellers act as barriers, affecting cell fate induction and bifurcations. (ii) It formalizes cell-cell signaling ranges in dynamic tissues, deconfounding morphogenetic movements to identify which cells could communicate via morphogens. (iii) It provides two new nondimensional numbers to assess when and where morphogenesis affects morphogen transport. We demonstrate this framework by analyzing classical patterning models with common morphogenetic motifs as well as experimental tissue flows. Our work rationalizes dynamic tissue patterning in development, constraining candidate patterning mechanisms and parameters using accessible cell motion data.

doi: 10.1103/h74q-3dgj