The Human Cell Atlas bone marrow single-cell interactive web portal

Exp Hematol. 2018 Dec;68:51-61. doi: 10.1016/j.exphem.2018.09.004. Epub 2018 Sep 21.

Abstract

The Human Cell Atlas (HCA) is expected to facilitate the creation of reference cell profiles, marker genes, and gene regulatory networks that will provide a deeper understanding of healthy and disease cell types from clinical biospecimens. The hematopoietic system includes dozens of distinct, transcriptionally coherent cell types, including intermediate transitional populations that have not been previously described at a molecular level. Using the first data release from the HCA bone marrow tissue project, we resolved common, rare, and potentially transitional cell populations from over 100,000 hematopoietic cells spanning 35 transcriptionally coherent groups across eight healthy donors using emerging new computational approaches. These data highlight novel mixed-lineage progenitor populations and putative trajectories governing granulocytic, monocytic, lymphoid, erythroid, megakaryocytic, and eosinophil specification. Our analyses suggest significant variation in cell-type composition and gene expression among donors, including biological processes affected by donor age. To enable broad exploration of these findings, we provide an interactive website to probe intra-cell and extra-cell population differences within and between donors and reference markers for cellular classification and cellular trajectories through associated progenitor states.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Atlases as Topic*
  • Base Sequence
  • Bone Marrow Cells* / classification
  • Bone Marrow Transplantation
  • Cell Lineage
  • Computational Biology*
  • DNA Barcoding, Taxonomic
  • Female
  • Gene Regulatory Networks
  • Genetic Variation
  • Hematopoietic Stem Cells / classification
  • Humans
  • Internet*
  • Male
  • RNA / genetics
  • Reference Standards
  • Sequence Alignment
  • Tissue Donors
  • Transcriptome
  • User-Computer Interface

Substances

  • RNA