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Single Cell RNA-Seq Analysis of Human Red Cells
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065680/ https://www.ncbi.nlm.nih.gov/pubmed/35514346 http://dx.doi.org/10.3389/fphys.2022.828700 |
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author | Jain, Vaibhav Yang, Wen-Hsuan Wu, Jianli Roback, John D. Gregory, Simon G. Chi, Jen-Tsan |
author_facet | Jain, Vaibhav Yang, Wen-Hsuan Wu, Jianli Roback, John D. Gregory, Simon G. Chi, Jen-Tsan |
author_sort | Jain, Vaibhav |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9065680 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90656802022-05-04 Single Cell RNA-Seq Analysis of Human Red Cells Jain, Vaibhav Yang, Wen-Hsuan Wu, Jianli Roback, John D. Gregory, Simon G. Chi, Jen-Tsan Front Physiol Physiology 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. Frontiers Media S.A. 2022-04-20 /pmc/articles/PMC9065680/ /pubmed/35514346 http://dx.doi.org/10.3389/fphys.2022.828700 Text en Copyright © 2022 Jain, Yang, Wu, Roback, Gregory and Chi. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Jain, Vaibhav Yang, Wen-Hsuan Wu, Jianli Roback, John D. Gregory, Simon G. Chi, Jen-Tsan Single Cell RNA-Seq Analysis of Human Red Cells |
title | Single Cell RNA-Seq Analysis of Human Red Cells |
title_full | Single Cell RNA-Seq Analysis of Human Red Cells |
title_fullStr | Single Cell RNA-Seq Analysis of Human Red Cells |
title_full_unstemmed | Single Cell RNA-Seq Analysis of Human Red Cells |
title_short | Single Cell RNA-Seq Analysis of Human Red Cells |
title_sort | single cell rna-seq analysis of human red cells |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9065680/ https://www.ncbi.nlm.nih.gov/pubmed/35514346 http://dx.doi.org/10.3389/fphys.2022.828700 |
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