Temporal control of stem cell fate decisions in C. elegans development

The development of multicellular organisms is a dynamic process requiring cells to coordinate proliferation and differentiation. Such coordination depends on molecular timing mechanisms that measure developmental time and regulate gene expression to direct appropriate fate transitions. However, how such timing information is encoded and interpreted by gene regulatory networks across lineages remains incompletely understood.
 
In recent work, I used single-cell transcriptomics to reconstruct temporal trajectories during C. elegans larval development, a period characterized by oscillatory patterns of gene expression supporting the formation of the cuticle. My analysis highlighted that global oscillations are interpreted differently across cell types, uncovering distinct developmental programs supported by identity-specific transcriptional regulators.
 
Building on this framework, I will next focus on the epidermal lineage, where a stem cell pool switches between symmetric (self-renewing) and asymmetric (differentiating) divisions. This system provides a tractable context to study how temporal regulators interface with stemness-control networks. Single-cell transcriptomics will enable network modeling to define the regulatory architecture underlying these transitions. Building on mechanistic insights from the epidermal system, I will extend these concepts to temporal patterning of neurons using the Q neuroblast lineage as a model. By integrating published datasets with approaches from network dynamics and statistical physics, this work will derive general principles by which transcriptional networks encode developmental time and control cell fate decisions across lineages.