Evidence map›Paper›PMID 36683248›Full record

ArticleClinical and translational medicine2023

Stemness-related genes revealed by single-cell profiling of naïve and stimulated human CD34

Guoyi Dong, Xiaojing Xu, Yue Li, Wenjie Ouyang, Weihua Zhao, Ying Gu, Jie Li, Tianbin Liu, Xinru Zeng, Huilin Zou and 5 more

Open access · goldAbstract read
In one paragraph

Article in Clinical and translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

7 citing papers in PubMed, 5 citations in OpenAlex.

  1. Foxs1-mediated transformation of CD34EMBO molecular medicine · 2026
    Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. 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

15 authors at 6 institutions in 1 country.

Guoyi DongCollege of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.ORCID 0000-0003-2563-0917
Xiaojing XuCollege of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
Yue LiDepartment of Hematology and Oncology, Shenzhen Children's Hospital, Shenzhen, China.
Wenjie OuyangChina National GeneBank, BGI-Shenzhen, Shenzhen, 518120, China.
Weihua ZhaoShenzhen Second People's Hospital, First Affiliated Hospital of Shenzhen University, Shenzhen, China.
Ying GuChina National GeneBank, BGI-Shenzhen, Shenzhen, 518120, China.
Jie LiCollege of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
Tianbin LiuCollege of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
Xinru ZengChina National GeneBank, BGI-Shenzhen, Shenzhen, 518120, China.
Huilin ZouChina National GeneBank, BGI-Shenzhen, Shenzhen, 518120, China.
Shuguang WangCollege of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
Yue ChenChina National GeneBank, BGI-Shenzhen, Shenzhen, 518120, China.
Sixi LiuDepartment of Hematology and Oncology, Shenzhen Children's Hospital, Shenzhen, China.
Hai-Xi SunCollege of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.
Chao LiuChina National GeneBank, BGI-Shenzhen, Shenzhen, 518120, China.
BGI Group (China) · CNChina National GeneBank · CNShenzhen Children's Hospital · CNBeijing Graphene Institute · CNShenzhen Second People's Hospital · CNUniversity of Chinese Academy of Sciences · CN

Funding

National Natural Science Foundation of China 31970816Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties SZGSP012Shenzhen Key Medical Discipline Construction Fund SZXK034
6 · The paper itself

Abstract

backgroundHematopoietic stem cells (HSCs) from different sources show varied repopulating capacity, and HSCs lose their stemness after long-time ex vivo culture. A deep understanding of these phenomena may provide helpful insights for HSCs.

methodsHere, we applied single-cell RNA-seq (scRNA-seq) to analyse the naïve and stimulated human CD34

resultsWe collected over 16 000 high-quality single-cell data to construct a comprehensive inference map and characterised the HSCs under a quiescent state on the hierarchy top. Then, we compared HSCs in CB with those in mPB and HSCs of naïve samples to those of cultured samples, and identified stemness-related genes (SRGs) associated with cell source (CS-SRGs) and culture time (CT-SRGs), respectively. Interestingly, CS-SRGs and CT-SRGs share genes enriched in the signalling pathways such as mRNA catabolic process, translational initiation, ribonucleoprotein complex biogenesis and cotranslational protein targeting to membrane, suggesting dynamic protein translation and processing may be a common requirement for stemness maintenance. Meanwhile, CT-SRGs are enriched in pathways involved in glucocorticoid and corticosteroid response that affect HSCs homing and engraftment. In contrast, CS-SRGs specifically contain genes related to purine and ATP metabolic process, which is crucial for HSC homeostasis in the stress settings. Particularly, when CT-SRGs are used as reference genes for the construction of the development trajectory of CD34

conclusionsOur findings provide new perspectives for understanding HSCs, and the strategy to identify candidate molecules through SRGs may be applicable to study other stem cells.

Indexed as

Cell DifferentiationFetal BloodHematopoietic Stem CellsAntigens, CD34Gene Expression ProfilingHumansSingle-Cell AnalysisAntigens, CD34cord bloodhuman hematopoietic stem cellsmobilised peripheral bloodsingle-cell RNA-seqstemness-related genes

Identifiers

PMID36683248
PMCPMC9868212
OpenAlexW4317717574

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.