Human Bone Marrow Assessment by Single Cell RNA Sequencing, Mass Cytometry and Flow Cytometry [scRNA]

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 twenty 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 good 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 dataset and highlights opportunities for further refinement. [Funding source] Project Number: 1ZIAHL006163-05 Contact PI / Project Leader: HOURIGAN, CHRISTOPHER Title: DETECTION, PREVENTION AND TREATMENT OF ACUTE MYELOID LEUKEMIA (AML) RELAPSE. Awardee Organization: NATIONAL HEART, LUNG, AND BLOOD INSTITUTE Overall design: Using standard operating procedures, mononuclear cells from 20 healthy donors' bone marrow aspirates were isolated using Ficoll density gradient separation and cryopreserved in 90% FBS/ 10% DMSO for storage in 72 liquid nitrogen. scRNAseq was performed using 10X Genomics Single Cell 3' Solution, version 2 according to manufacturer's instructions (protocol rev A). Libraries were sequenced on HiSeq3000. Droplet-based scRNAseq of bone marrow mononuclear cells for all donor samples was performed with goal minimum sequencing depth of 50,000 reads/cell and detected a mean of 880 genes/cells (range 575-1,390 gene/cell).