A time- and single-cell-resolved model of murine bone marrow hematopoiesis

Data, source code, singularity container, extended figures and tables for the article: "A time- and single-cell-resolved model of murine bone marrow hematopoiesis"

The paradigmatic hematopoietic tree model is increasingly recognized to be limited as it is based on heterogeneous populations and largely inferred from non-homeostatic cell fate assays. Here, we combine persistent labeling with time-series single-cell RNA-Seq to build a real-time, quantitative model of in vivo tissue dynamics for murine bone marrow hematopoiesis. We couple cascading single-cell expression patterns with dynamic changes in differentiation and growth speeds. The resulting explicit linkage between molecular states and cellular behavior reveals widely varying self-renewal and differentiation properties across distinct lineages. Transplanted stem cells show strong acceleration of differentiation at specific stages of erythroid and neutrophil production, illustrating how the new model can quantify the impact of perturbations. Our reconstruction of dynamic behavior from snapshot measurements is akin to how a kinetoscope allows sequential images to merge into a movie. We posit that this approach is generally applicable to understanding tissue scale dynamics at high resolution.