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Population snapshots predict early haematopoietic and erythroid hierarchies

Author

Listed:
  • Betsabeh Khoramian Tusi

    (Cell and Cancer Biology, University of Massachusetts Medical School)

  • Samuel L. Wolock

    (Harvard Medical School)

  • Caleb Weinreb

    (Harvard Medical School)

  • Yung Hwang

    (Cell and Cancer Biology, University of Massachusetts Medical School)

  • Daniel Hidalgo

    (Cell and Cancer Biology, University of Massachusetts Medical School)

  • Rapolas Zilionis

    (Harvard Medical School)

  • Ari Waisman

    (Institute for Molecular Medicine, University Medical Center of the Johannes Gutenberg-University Mainz)

  • Jun R. Huh

    (Harvard Medical School and Brigham and Women’s Hospital)

  • Allon M. Klein

    (Harvard Medical School)

  • Merav Socolovsky

    (Cell and Cancer Biology, University of Massachusetts Medical School
    University of Massachusetts Medical School)

Abstract

The formation of red blood cells begins with the differentiation of multipotent haematopoietic progenitors. Reconstructing the steps of this differentiation represents a general challenge in stem-cell biology. Here we used single-cell transcriptomics, fate assays and a theory that allows the prediction of cell fates from population snapshots to demonstrate that mouse haematopoietic progenitors differentiate through a continuous, hierarchical structure into seven blood lineages. We uncovered coupling between the erythroid and the basophil or mast cell fates, a global haematopoietic response to erythroid stress and novel growth factor receptors that regulate erythropoiesis. We defined a flow cytometry sorting strategy to purify early stages of erythroid differentiation, completely isolating classically defined burst-forming and colony-forming progenitors. We also found that the cell cycle is progressively remodelled during erythroid development and during a sharp transcriptional switch that ends the colony-forming progenitor stage and activates terminal differentiation. Our work showcases the utility of linking transcriptomic data to predictive fate models, and provides insights into lineage development in vivo.

Suggested Citation

  • Betsabeh Khoramian Tusi & Samuel L. Wolock & Caleb Weinreb & Yung Hwang & Daniel Hidalgo & Rapolas Zilionis & Ari Waisman & Jun R. Huh & Allon M. Klein & Merav Socolovsky, 2018. "Population snapshots predict early haematopoietic and erythroid hierarchies," Nature, Nature, vol. 555(7694), pages 54-60, March.
  • Handle: RePEc:nat:nature:v:555:y:2018:i:7694:d:10.1038_nature25741
    DOI: 10.1038/nature25741
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    Citations

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    Cited by:

    1. Parashar Dhapola & Johan Rodhe & Rasmus Olofzon & Thomas Bonald & Eva Erlandsson & Shamit Soneji & Göran Karlsson, 2022. "Scarf enables a highly memory-efficient analysis of large-scale single-cell genomics data," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    2. Takayoshi Matsumura & Haruhito Totani & Yoshitaka Gunji & Masahiro Fukuda & Rui Yokomori & Jianwen Deng & Malini Rethnam & Chong Yang & Tze King Tan & Tadayoshi Karasawa & Kazuomi Kario & Masafumi Tak, 2022. "A Myb enhancer-guided analysis of basophil and mast cell differentiation," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    3. Trent D. Hall & Hyunjin Kim & Mahmoud Dabbah & Jacquelyn A. Myers & Jeremy Chase Crawford & Antonio Morales-Hernandez & Claire E. Caprio & Pramika Sriram & Emilia Kooienga & Marta Derecka & Esther A. , 2022. "Murine fetal bone marrow does not support functional hematopoietic stem and progenitor cells until birth," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    4. Yuxuan Liu & Zhimin Gu & Hui Cao & Pranita Kaphle & Junhua Lyu & Yuannyu Zhang & Wenhuo Hu & Stephen S. Chung & Kathryn E. Dickerson & Jian Xu, 2021. "Convergence of oncogenic cooperation at single-cell and single-gene levels drives leukemic transformation," Nature Communications, Nature, vol. 12(1), pages 1-17, December.
    5. Kensuke Miyake & Junya Ito & Jun Nakabayashi & Shigeyuki Shichino & Kenji Ishiwata & Hajime Karasuyama, 2023. "Single cell transcriptomics clarifies the basophil differentiation trajectory and identifies pre-basophils upstream of mature basophils," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    6. Jifan Shi & Tiejun Li & Luonan Chen & Kazuyuki Aihara, 2019. "Quantifying pluripotency landscape of cell differentiation from scRNA-seq data by continuous birth-death process," PLOS Computational Biology, Public Library of Science, vol. 15(11), pages 1-17, November.
    7. Grigorios Georgolopoulos & Nikoletta Psatha & Mineo Iwata & Andrew Nishida & Tannishtha Som & Minas Yiangou & John A. Stamatoyannopoulos & Jeff Vierstra, 2021. "Discrete regulatory modules instruct hematopoietic lineage commitment and differentiation," Nature Communications, Nature, vol. 12(1), pages 1-15, December.

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