Evidence map›Paper›PMID 39794399›Full record

ArticleScientific reports2025

Integrated analysis of miRNAs and mRNAs in thousands of single cells.

Jia Li, Jing Tian, Tao Cai

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  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

3 authors.

Jia LiNational Institute of Biological Sciences, Beijing, China.
Jing TianNational Institute of Biological Sciences, Beijing, China.
Tao CaiNational Institute of Biological Sciences, Beijing, China. caitao@nibs.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The simultaneous sequencing of multiple types of biomolecules can facilitate understanding various forms of regulation occurring in cells. Cosequencing of miRNA and mRNA at single-cell resolution is challenging, and to date, only a few such studies (examining a quite limited number of cells) have been reported. Here, we developed a parallel single-cell small RNA and mRNA coprofiling method (PSCSR-seq V2) that enables miRNA and mRNA coexpression analysis in many cells. The PSCSR-seq V2 method is highly sensitive for miRNA analysis, and it also provides rich mRNA information about the examined cells at the same time. We employed PSCSR-seq V2 to profile miRNA and mRNA in 2310 cultured cells, and detected an average of 181 miRNA species and 7354 mRNA species per cell. An integrated analysis of miRNA and mRNA profiles linked miRNA functions with the negative regulation of tumor suppressor and reprogramming of cellular metabolism. We coprofiled miRNA and mRNA in 9403 lung cells and generated a coexpression atlas for known cell populations in mouse lungs, and detected conserved expression patterns of miRNAs among lineage-related cells. Based on this information, we identified informative age-associated miRNAs in mouse and human lung cells including miR-29, which can be understood as a conserved marker for immunosenescence. PSCSR-seq V2 offers unique functionality to users conducting functional studies of miRNAs in clinical and basic biological research.

Indexed as

MicroRNAsRNA, MessengerSingle-Cell AnalysisAnimalsGene Expression ProfilingHumansLungMiceSequence Analysis, RNAMicroRNAsRNA, Messenger

Identifiers

PMID39794399
PMCPMC11724058

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Registered trials

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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.