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A single cell resolution map of mouse haematopoietic stem and progenitor cell differentiation

Sonia Nestorowa, Fiona K. Hamey, Blanca Pijuan Sala, Evangelia Diamanti, Mairi Shepherd, Elisa Laurenti, Nicola K. Wilson, David G. Kent and Berthold Göttgens

Key points

  • An expression map of HSPC differentiation from single cell RNA-Seq of 1,656 HSPCs provides new insights into blood stem cell differentiation.

  • A user-friendly web resource provides access to single cell gene expression profiles for the wider research community.

Abstract

Maintenance of the blood system requires balanced cell fate decisions of haematopoietic stem and progenitor cells (HSPCs). Since cell fate choices are executed at the level of individual cells, new single cell profiling technologies offer exciting possibilities to map the dynamic molecular changes underlying HSPC differentiation. Here we have used single cell RNA-Seq to profile over 1,600 single HSPCs, where deep sequencing has enabled detection of an average of 6,558 protein-coding genes per cell. Index sorting, in combination with broad sorting gates, allowed us to retrospectively assign cells to 12 commonly sorted HSPC phenotypes while also capturing intermediate cells typically excluded by conventional gating. We further show that independently generated single cell datasets can be projected onto the single cell resolution expression map to directly compare data from multiple groups and to build and refine new hypotheses. Reconstruction of differentiation trajectories reveals dynamic expression changes associated with early lymphoid, erythroid-megakaryocytic and granulocyte-macrophage differentiation. The latter two trajectories were characterized by common upregulation of cell cycle and oxidative phosphorylation transcriptional programs. Using external spike-in controls, we estimate absolute mRNA levels per cell, showing for the first time that despite a general reduction in total mRNA, a subset of genes shows higher expression levels in immature stem cells consistent with active maintenance of the stem cell state. Finally, we report the development of an intuitive web interface as a new community resource, to permit visualization of gene expression in HSPCs at single cell resolution for any gene of choice.

  • Submitted May 13, 2016.
  • Accepted June 28, 2016.