Evidence map›Paper›PMID 41994205›Full record

SynthesisFrontiers in cellular and infection microbiology2026

Single-cell RNA sequencing offers novel perspectives in viral infection research.

Hao Zhang, Yafei Li, Hang Li, Shaomeng Liu, Dang Wang, Huanchun Chen, Qingyun Liu, Xiangru Wang

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Hao ZhangNational Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.
Yafei LiNational Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.
Hang LiNational Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.
Shaomeng LiuNational Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.
Dang WangNational Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.
Huanchun ChenNational Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.
Qingyun LiuNational Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.
Xiangru WangNational Key Laboratory of Agricultural Microbiology, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global emergence of multiple viral zoonoses underscores the substantial threats of viral infections to human health. Given the dynamic and complex mechanisms underlying viral pathogenesis, sophisticated approaches are requisite to advance viral research. Here, we present a systematic review of single-cell RNA sequencing (scRNA-seq), a high-throughput technology enabling transcriptomic profiling at the individual cell level, focusing on its pivotal role in elucidating heterogeneous host cellular responses to viral infection and deciphering underlying pathogenic mechanisms. We summarize scRNA-seq's developmental milestones, compare characteristics of various platforms, and outline its key applications in viral infection research: identifying infection-induced novel cell types/subpopulations, characterizing virus-specific host cell gene expression changes, defining viral target cells, elucidating antiviral immune mechanisms, and clarifying

Indexed as

Host-Pathogen InteractionsSequence Analysis, RNASingle-Cell AnalysisVirus DiseasesVirusesAnimalsGene Expression ProfilingHigh-Throughput Nucleotide SequencingHumansSingle-Cell Gene Expression AnalysisTranscriptomecellular heterogeneityhost-virus interactionscRNA-seqtranscriptomicsviral infection

Identifiers

PMID41994205
PMCPMC13079343

What Socratic 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 Socratic graph.