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The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells


Defining the transcriptional dynamics of a temporal process such as cell differentiation is challenging owing to the high variability in gene expression between individual cells. Time-series gene expression analyses of bulk cells have difficulty distinguishing early and late phases of a transcriptional cascade or identifying rare subpopulations of cells, and single-cell proteomic methods rely on a priori knowledge of key distinguishing markers1. Here we describe Monocle, an unsupervised algorithm that increases the temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points. Applied to the differentiation of primary human myoblasts, Monocle revealed switch-like changes in expression of key regulatory factors, sequential waves of gene regulation, and expression of regulators that were not known to act in differentiation. We validated some of these predicted regulators in a loss-of function screen. Monocle can in principle be used to recover single-cell gene expression kinetics from a wide array of cellular processes, including differentiation, proliferation and oncogenic transformation.

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Figure 1: Monocle orders single-cell RNA-Seq data of differentiating myoblasts in pseudotime.
Figure 2: Monocle orders individual cells by progress through differentiation.
Figure 3: Pseudotime ordering of cells reveals genes activated or repressed early in differentiation, along with potential upstream regulators.
Figure 4: Loss-of-function screen on selected transcription factors.

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We are grateful to S. Bordbar, C. Zhu, A. Wagers and the Broad RNAi platform for technical assistance and to M. Soumillon for discussions. C.T. was supported by a Damon Runyon Cancer Research Foundation Fellowship. D.C. was supported by a Human Frontier Science Program Fellowship. D.C. and T.S.M. were supported by the Harvard Stem Cell Institute. This work was supported by US National Institutes of Health grants 1DP2OD00667, P01GM099117 and P50HG006193-01. This work was also supported in part by the Single Cell Genomics initiative, a collaboration between the Broad Institute and Fluidigm Inc.

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Authors and Affiliations



C.T. and D.C. conceived the strategy of ordering individual cells by developmental progress. C.T. designed and wrote Monocle and performed the computational analysis. D.C., C.T., J.G., P.P., S.L. and M.M. performed the experiments. D.C., C.T. and J.L.R. designed the study. C.T., D.C., J.G., N.J.L., K.J.L., T.S.M. and J.L.R. wrote the manuscript.

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Correspondence to John L Rinn.

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Competing interests

K.J.L. and S.L. are employees of Fluidigm, Inc. Fluidigm manufactures an instrument used in this study.

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Trapnell, C., Cacchiarelli, D., Grimsby, J. et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells. Nat Biotechnol 32, 381–386 (2014).

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