Document Type


Publication Date


Publication Title

Nat Commun


Algorithms; Animals; Cell Differentiation; Cell Lineage; Computational Biology/methods; GATA1 Transcription Factor/metabolism; Hematopoiesis; Hematopoietic Stem Cells/cytology; Hematopoietic Stem Cells/metabolism; Models, Biological; Myeloid Cells/cytology; Myeloid Cells/metabolism; Proto-Oncogene Proteins/metabolism; Time Factors; Trans-Activators/metabolism


Molecular regulation of cell fate decisions underlies health and disease. To identify molecules that are active or regulated during a decision, and not before or after, the decision time point is crucial. However, cell fate markers are usually delayed and the time of decision therefore unknown. Fortunately, dividing cells induce temporal correlations in their progeny, which allow for retrospective inference of the decision time point. We present a computational method to infer decision time points from correlated marker signals in genealogies and apply it to differentiating hematopoietic stem cells. We find that myeloid lineage decisions happen generations before lineage marker onsets. Inferred decision time points are in agreement with data from colony assay experiments. The levels of the myeloid transcription factor PU.1 do not change during, but long after the predicted lineage decision event, indicating that the PU.1/GATA1 toggle switch paradigm cannot explain the initiation of early myeloid lineage choice.


Institute for Systems Biology