W. Yang, Z. Li, X. Yu, P. Wu, X. Zhang, C. Ren, K. Liu, J. Chen, F. Chen, X. He, J. Zhang, X. Chen, J. Yang
Cellular transitions between phenotypic states are fundamental to development and disease, yet quantitative analysis of their dynamics remains challenging. Here we present PASTRI (Phylogenetic Adjacency-based State Transition Rate Inference), a computational framework that infers transition rates from cell lineages/phylogenies annotated with terminal phenotypic states, such as single-cell transcriptomes. We validate PASTRI using simulated lineages and the Caenorhabditis elegans embryonic lineage. Importantly, by leveraging cell pairs at varying phylogenetic distances, PASTRI accurately resolves stage-specific transition rates, circumventing the issue of developmental changes in dynamics. Applied to three cell phylogeny datasets from our lineage-tracing experiments spanning diverse developmental/disease models and tracing systems, PASTRI uncovers rate-limiting steps in the activation of hepatic stellate cells and the differentiation of primordial lung progenitors, as well as attractor states that support cancer cell proliferation. PASTRI thus opens up a venue for dissecting cell state transition dynamics from annotated cell lineage/phylogeny.