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Single Cell RNA-Seq Analysis of Human Red Cells.

Publication ,  Journal Article
Jain, V; Yang, W-H; Wu, J; Roback, JD; Gregory, SG; Chi, J-T
Published in: Front Physiol
2022

Human red blood cells (RBCs), or erythrocytes, are the most abundant blood cells responsible for gas exchange. RBC diseases affect hundreds of millions of people and impose enormous financial and personal burdens. One well-recognized, but poorly understood feature of RBC populations within the same individual are their phenotypic heterogeneity. The granular characterization of phenotypic RBC variation in normative and disease states may allow us to identify the genetic determinants of red cell diseases and reveal novel therapeutic approaches for their treatment. Previously, we discovered diverse RNA transcripts in RBCs that has allowed us to dissect the phenotypic heterogeneity and malaria resistance of sickle red cells. However, these analyses failed to capture the heterogeneity found in RBC sub-populations. To overcome this limitation, we have performed single cell RNA-Seq to analyze the transcriptional heterogeneity of RBCs from three adult healthy donors which have been stored in the blood bank conditions and assayed at day 1 and day 15. The expression pattern clearly separated RBCs into seven distinct clusters that include one RBC cluster that expresses HBG2 and a small population of RBCs that express fetal hemoglobin (HbF) that we annotated as F cells. Almost all HBG2-expessing cells also express HBB, suggesting bi-allelic expression in single RBC from the HBG2/HBB loci, and we annotated another cluster as reticulocytes based on canonical gene expression. Additional RBC clusters were also annotated based on the enriched expression of NIX, ACVR2B and HEMGN, previously shown to be involved in erythropoiesis. Finally, we found the storage of RBC was associated with an increase in the ACVR2B and F-cell clusters. Collectively, these data indicate the power of single RBC RNA-Seq to capture and discover known and unexpected heterogeneity of RBC population.

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Published In

Front Physiol

DOI

ISSN

1664-042X

Publication Date

2022

Volume

13

Start / End Page

828700

Location

Switzerland

Related Subject Headings

  • 3208 Medical physiology
  • 3101 Biochemistry and cell biology
  • 1701 Psychology
  • 1116 Medical Physiology
  • 0606 Physiology
 

Citation

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Jain, V., Yang, W.-H., Wu, J., Roback, J. D., Gregory, S. G., & Chi, J.-T. (2022). Single Cell RNA-Seq Analysis of Human Red Cells. Front Physiol, 13, 828700. https://doi.org/10.3389/fphys.2022.828700
Jain, Vaibhav, Wen-Hsuan Yang, Jianli Wu, John D. Roback, Simon G. Gregory, and Jen-Tsan Chi. “Single Cell RNA-Seq Analysis of Human Red Cells.Front Physiol 13 (2022): 828700. https://doi.org/10.3389/fphys.2022.828700.
Jain V, Yang W-H, Wu J, Roback JD, Gregory SG, Chi J-T. Single Cell RNA-Seq Analysis of Human Red Cells. Front Physiol. 2022;13:828700.
Jain, Vaibhav, et al. “Single Cell RNA-Seq Analysis of Human Red Cells.Front Physiol, vol. 13, 2022, p. 828700. Pubmed, doi:10.3389/fphys.2022.828700.
Jain V, Yang W-H, Wu J, Roback JD, Gregory SG, Chi J-T. Single Cell RNA-Seq Analysis of Human Red Cells. Front Physiol. 2022;13:828700.

Published In

Front Physiol

DOI

ISSN

1664-042X

Publication Date

2022

Volume

13

Start / End Page

828700

Location

Switzerland

Related Subject Headings

  • 3208 Medical physiology
  • 3101 Biochemistry and cell biology
  • 1701 Psychology
  • 1116 Medical Physiology
  • 0606 Physiology