A time and single-cell resolved model of hematopoiesis

Abstract

The paradigmatic tree model of hematopoiesis 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 the first real- time, quantitative model of in vivo tissue dynamics for any mammalian organ. We couple cascading single-cell expression patterns with dynamic changes in differentiation and growth speeds. The resulting explicit linkage between single cell molecular states and cellular behavior reveals widely varying self-renewal and differentiation properties across distinct lineages. Transplanted stem cells show strong acceleration of neutrophil differentiation, 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 broadly applicable to empower single cell genomics to reveal important tissue scale dynamics information. HighlightsO_LICell flux analysis reveals high-resolution kinetics of native bone marrow hematopoiesis C_LIO_LIQuantitative model simulates cell behavior in real-time and connects it with gene expression patterns C_LIO_LIDistinct lineage-affiliated progenitors have unique self-renewal and differentiation properties C_LIO_LITransplanted HSCs display accelerated stage- and lineage-specific differentiation C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/506735v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@244ad6org.highwire.dtl.DTLVardef@ad632borg.highwire.dtl.DTLVardef@149daf9org.highwire.dtl.DTLVardef@1c7183f_HPS_FORMAT_FIGEXP M_FIG C_FIG