Evidence map›Paper›PMID 35514346›Full record

ArticleFrontiers in physiology2022

Single Cell RNA-Seq Analysis of Human Red Cells.

Vaibhav Jain, Wen-Hsuan Yang, Jianli Wu, John D Roback, Simon G Gregory, Jen-Tsan Chi

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
7.2field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 59 citations in OpenAlex.

  1. A who's who of cell types in skeletal muscle.Communications biology · 2026
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  6. Main events and mechanism of human erythrocyte ageing.Expert reviews in molecular medicine · 2026
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  8. Review
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  10. Review
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  12. Article
  13. Article
  14. Article
  15. Article
  16. Long non-coding RNAeLife · 2024
    Article
  17. Article
  18. Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Vaibhav JainDepartment of Neurology, Durham, NC, United States.
Wen-Hsuan YangDepartment of Molecular Genetics and Microbiology, Durham, NC, United States.
Jianli WuDepartment of Molecular Genetics and Microbiology, Durham, NC, United States.
John D RobackCenter for Transfusion and Cellular Therapies, Durham, NC, United States.
Simon G GregoryDepartment of Neurology, Durham, NC, United States.
Jen-Tsan ChiDepartment of Molecular Genetics and Microbiology, Durham, NC, United States.
Duke University · USDuke Medical Center · USInstitute for Transfusion Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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

Indexed as

ACVR2Bfetal hemoglobinHEMGNNIXRed cellRNAsingle cell RNA-Seq Storage

Identifiers

PMID35514346
PMCPMC9065680
OpenAlexW4224219498

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.