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Human bone marrow assessment by single-cell RNA sequencing, mass cytometry, and flow cytometry
Karolyn A. Oetjen, … , J. Philip McCoy, Christopher S. Hourigan
Karolyn A. Oetjen, … , J. Philip McCoy, Christopher S. Hourigan
Published December 6, 2018
Citation Information: JCI Insight. 2018;3(23):e124928. https://doi.org/10.1172/jci.insight.124928.
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Categories: Research Article Hematology Immunology

Human bone marrow assessment by single-cell RNA sequencing, mass cytometry, and flow cytometry

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Abstract

New techniques for single-cell analysis have led to insights into hematopoiesis and the immune system, but the ability of these techniques to cross-validate and reproducibly identify the biological variation in diverse human samples is currently unproven. We therefore performed a comprehensive assessment of human bone marrow cells using both single-cell RNA sequencing and multiparameter flow cytometry from 20 healthy adult human donors across a broad age range. These data characterize variation between healthy donors as well as age-associated changes in cell population frequencies. Direct comparison of techniques revealed discrepancy in the quantification of T lymphocyte and natural killer cell populations. Orthogonal validation of immunophenotyping using mass cytometry demonstrated a strong correlation with flow cytometry. Technical replicates using single-cell RNA sequencing matched robustly, while biological replicates showed variation. Given the increasing use of single-cell technologies in translational research, this resource serves as an important reference data set and highlights opportunities for further refinement.

Authors

Karolyn A. Oetjen, Katherine E. Lindblad, Meghali Goswami, Gege Gui, Pradeep K. Dagur, Catherine Lai, Laura W. Dillon, J. Philip McCoy, Christopher S. Hourigan

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Figure 1

Single-cell RNA sequencing of healthy bone marrow cells.

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Single-cell RNA sequencing of healthy bone marrow cells.
(A) Cluster ide...
(A) Cluster identification visualized using t-SNE. HSPCs: hematopoietic stem/progenitor cells; cDCs: conventional DCs; pDCs: plasmacytoid DCs. (B) Single-cell trajectory analysis using UMAP/Monocle 3. Color is as in (A). (C) Examples of canonical gene expression used for annotation. (D) Reproducibility of technical replicates for single-cell RNA sequencing. Linear regression line displayed in gray.
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