Evidence map›Paper›PMID 41171131›Full record

ArticleNucleic acids research2026

CellSNVReg: a multidimensional resource for SNV-mediated regulatory perturbations in single-cell and spatial omics.

Jingyi Shi, Shiqian Zhang, Zhenglin Lu, Weiwei Zhou, Weijian Lu, Gengdong Chen, Jianing Li, Wenhui Liu, Jiaqi Huang, Tiantongfei Jiang and 3 more

Abstract read
In one paragraph

Article in Nucleic acids research, 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

13 authors.

Jingyi ShiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.ORCID 0009-0004-0214-0311
Shiqian ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Zhenglin LuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Weiwei ZhouCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.ORCID 0000-0003-1641-8965
Weijian LuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Gengdong ChenCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Jianing LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Wenhui LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Jiaqi HuangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Tiantongfei JiangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Xiyun JinSchool of Interdisciplinary Medicine and Engineering, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Juan XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.ORCID 0000-0002-3709-4165
Tingting ShaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.ORCID 0000-0003-0069-1510

Funding

National Key Research and Development Program of China 2024YFF1206602National Natural Science Foundation of China 32170676National Natural Science Foundation of China 32322020Natural Science Foundation of Heilongjiang Province LH2024C064Natural Science Foundation of Heilongjiang Province ZD2023C007Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province LBH-Q20153
6 · The paper itself

Abstract

Single nucleotide variants (SNVs) represent the most prevalent form of genetic variation and can perturb gene regulation, RNA processing, and protein function across multiple molecular layers, ultimately altering cellular functional states and contributing to disease development. Here, we present CellSNVReg (http://bio-bigdata.hrbmu.edu.cn/CellSNVReg/index.jsp), a comprehensive multidimensional resource systematically characterizing regulatory perturbations caused by SNVs at cell-type and spatial resolutions in humans. By integrating 4.6 million cellular profiles from scRNA-seq, spatial transcriptomics, and scATAC-seq across normal, tumor, and other disease tissues, CellSNVReg identifies an average of over 70 000 regulatory perturbations per sample across six dimensions: miRNA-target, transcription factor (TF)-target, enhancer-target, RBP-target, protein-protein interaction, and neoantigen generation, and further characterizes differential expression of perturbed target genes together with associated perturbation networks. For each perturbation, CellSNVReg provides qualitative annotations and quantitative scores to assess SNV perturbation impact, potentially facilitating prioritization of candidate driver SNVs in disease-relevant contexts. To assess downstream functional consequences, the platform links SNV-perturbed targets to alterations in cell functions, states, stemness, metabolism, cell-cell communication, and drug repurposing. In summary, CellSNVReg offers a high-resolution framework for dissecting the functional impact of SNVs across diverse regulatory layers, enabling exploration of the landscape of SNV-mediated regulatory disruptions and their phenotypic consequences in normal and disease contexts.

Indexed as

Databases, GeneticPolymorphism, Single NucleotideSingle-Cell AnalysisSoftwareGene Expression ProfilingGene Expression RegulationGene Regulatory NetworksGenomicsHumansMicroRNAsTranscription FactorsTranscriptomeMicroRNAsTranscription Factors

Identifiers

PMID41171131
PMCPMC12807710

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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.