Article

FateID infers cell fate bias in multipotent progenitors from single-cell RNA-seq data

  • Nature Methods volume 15, pages 379386 (2018)
  • doi:10.1038/nmeth.4662
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Abstract

To understand stem cell differentiation along multiple lineages, it is necessary to resolve heterogeneous cellular states and the ancestral relationships between them. We developed a robotic miniaturized CEL-Seq2 implementation to carry out deep single-cell RNA-seq of 2,000 mouse hematopoietic progenitors enriched for lymphoid lineages, and used an improved clustering algorithm, RaceID3, to identify cell types. To resolve subtle transcriptome differences indicative of lineage biases, we developed FateID, an iterative supervised learning algorithm for the probabilistic quantification of cell fate bias in progenitor populations. Here we used FateID to delineate domains of fate bias and enable the derivation of high-resolution differentiation trajectories, thereby revealing a common progenitor population of B cells and plasmacytoid dendritic cells, which we validated by in vitro differentiation assays. We expect that FateID will improve understanding of the process of cell fate choice in complex multi-lineage differentiation systems.

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Acknowledgements

We thank A. Pospisilik for help in developing mCEL-Seq2. We acknowledge extensive support from S. Hobitz, K. Schuldes, and D. Wild in flow cytometry, and U. Boenisch in deep sequencing. We also thank T. Boehm, C. Happe, and R. Grosschedl for valuable input and support. We thank T. Boehm, N. Cabezas-Wallscheid, and E. Trompouki for critical reading of the manuscript and valuable feedback. S. acknowledges funding from the Behrens-Weise Foundation. This work was supported by the Max Planck Society.

Author information

Affiliations

  1. Max Planck Institute of Immunobiology and Epigenetics, Freiburg, Germany.

    • Josip S Herman
    • , Sagar
    •  & Dominic Grün
  2. Faculty of Biology, University of Freiburg, Freiburg, Germany.

    • Josip S Herman
  3. International Max Planck Research School for Molecular and Cellular Biology (IMPRS-MCB), Freiburg, Germany.

    • Josip S Herman

Authors

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Contributions

J.S.H. performed all experiments, analyzed the data, and created the web interface; S. established the mCEL-Seq2 protocol with help of J.S.H.; D.G. designed the study, developed the algorithm, and wrote the paper; and all authors edited the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Dominic Grün.

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