Assessing the relative contributions of mosaic and regulatory developmental modes from single-cell trajectories.
Solène Song, Paul Villoutreix
Abstract
Open AccessDevelopment is a complex process driven by coordinated cell proliferation, differentiation, and spatial organization. Classically, two ways to specify cell types during development have been hypothesized: the mosaic and regulative modes. In the mosaic mode, a particular cell isolated from the rest of the embryo will still give rise to progeny with the same fate as expected in normal development, relying on lineage-inherited factors. In contrast, in the regulative mode, the fate of a cell depends on its interactions with its environment and thus relies on space-dependent factors. While both modes often co-exist, their relative contributions remain poorly quantified at single-cell resolution. We present a novel approach to measure these contributions from single-cell data from C. elegans development. The invariant lineage of C. elegans allows the integration of spatial positions, lineage relationships, and protein expression data. Using single-cell protein expression profiles as a readout of cell state, we define two quantifiable metrics: 1) a proxy for the contribution of the mosaic mode, computed as the strength of the relationship between the cell-cell lineage distance and the cell-cell expression distance, 2) a proxy for the contribution of the regulative mode, computed as the strength of the relationship between the cell-cell context distance - capturing spatial neighborhood similarity - and the cell-cell expression distance. To validate these metrics, we compared empirical results from C. elegans to artificial models with defined developmental rules. Our analysis reveals the coexistence of mosaic and regulative modes, with their relative contributions varying across tissues and developmental stages. For example, in skin tissue, the mosaic mode dominates in early development, while the regulative mode prevails later. Our approach offers a quantitative, unbiased, and perturbation-free method to study fundamental principles of developmental biology.