Evidence map›Paper›PMID 37160973›Full record

ArticleScientific reports2023

Small RNA transcriptome analysis using parallel single-cell small RNA sequencing.

Jia Li, Zhirong Zhang, Yinghua Zhuang, Fengchao Wang, Tao Cai

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

12 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Transcriptomics Insights into Spinal Cord Injury for Therapy Development.International journal of molecular sciences · 2026
    Review
  3. Article
  4. Review
  5. MicroRNAs and Their Profiling via Single-Cell Sequencing Technologies.Methods in molecular biology (Clifton, N.J.) · 2026
    Review
  6. Sequencing technologies to measure translation in single cells.Nature reviews. Molecular cell biology · 2025
    Review
  7. Review
  8. Caenorhabditis Elegans as a Model for Environmental Epigenetics.Current environmental health reports · 2025
    Review
  9. Article
  10. Temporal Expression Analysis to Unravel Gene Regulatory Dynamics by microRNAs.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  11. Review
  12. Review
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

5 authors at 2 institutions in 1 country.

Jia LiNational Institute of Biological Sciences, Beijing, China.
Zhirong ZhangNational Institute of Biological Sciences, Beijing, China.
Yinghua ZhuangNational Institute of Biological Sciences, Beijing, China.
Fengchao WangNational Institute of Biological Sciences, Beijing, China.ORCID 0000-0002-3595-2859
Tao CaiNational Institute of Biological Sciences, Beijing, China. caitao@nibs.ac.cn.ORCID 0000-0003-4358-4213
National Institute of Biological Sciences, Beijing · CNCapital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

miRNA and other forms of small RNAs are known to regulate many biological processes. Single-cell small RNA sequencing can be used to profile small RNAs of individual cells; however, limitations of efficiency and scale prevent its widespread application. Here, we developed parallel single-cell small RNA sequencing (PSCSR-seq), which can overcome the limitations of existing methods and enable high-throughput small RNA expression profiling of individual cells. Analysis of PSCSR-seq data indicated that diverse cell types could be identified based on patterns of miRNA expression, and showed that miRNA content in nuclei is informative (for example, cell type marker miRNAs can be detected in isolated nuclei). PSCSR-seq is very sensitive: analysis of only 732 peripheral blood mononuclear cells (PBMCs) detected 774 miRNAs, whereas bulk small RNA analysis would require input RNA from approximately 10

Indexed as

Lung NeoplasmsMicroRNAsGene Expression ProfilingHumansLeukocytes, MononuclearSequence Analysis, RNATranscriptomeMicroRNAs

Identifiers

PMID37160973
PMCPMC10170110
OpenAlexW4376132047

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.