Extracellular vesicle-derived miRNA-mediated cell–cell communication inference for single-cell transcriptomic data with miRTalk

MicroRNAs are released from cells in extracellular vesicles (EVs), representing an essential mode of cell-cell communication (CCC) via a regulatory effect on gene expression. Single-cell RNA-sequencing technologies have ushered in an era of elucidating CCC at single-cell resolution. Herein, we present miRTalk, a pioneering approach for inferring CCC mediated by EV-derived miRNA-target interactions (MiTIs). The benchmarking against simulated and real-world datasets demonstrates the superior performance of miRTalk, and the application to four disease scenarios reveals the in-depth MiTI-mediated CCC mechanisms. Collectively, miRTalk can infer EV-derived MiTI-mediated CCC with scRNA-seq data, providing new insights into the intercellular dynamics of biological processes.

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Publication Details

Journal
Genome biology
Published
2025-04-14
DOI
https://doi.org/10.1186/s13059-025-03566-x
Citations
11
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
8.06

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article

Extracellular vesicle-derived miRNA-mediated cell–cell communication inference for single-cell transcriptomic data with miRTalk

Xiao Xu, Xueying Fan, Jie Liao, Lingqi Yu et al.
11 citations
Genome biology
Extracellular vesicles in disease
8.06
article

Extracellular vesicle-derived miRNA-mediated cell–cell communication inference for single-cell transcriptomic data with miRTalk

Xiao Xu, Xueying Fan, Jie Liao, Lingqi Yu, Jingyang Qian, Xiaohui Fan, Xin Shao, Chengyu Li, Haihong Yang, Xinyu Yang
article en
11 citations

Abstract

MicroRNAs are released from cells in extracellular vesicles (EVs), representing an essential mode of cell-cell communication (CCC) via a regulatory effect on gene expression. Single-cell RNA-sequencing technologies have ushered in an era of elucidating CCC at single-cell resolution. Herein, we present miRTalk, a pioneering approach for inferring CCC mediated by EV-derived miRNA-target interactions (MiTIs). The benchmarking against simulated and real-world datasets demonstrates the superior performance of miRTalk, and the application to four disease scenarios reveals the in-depth MiTI-mediated CCC mechanisms. Collectively, miRTalk can infer EV-derived MiTI-mediated CCC with scRNA-seq data, providing new insights into the intercellular dynamics of biological processes.

Genome biologyVol. 26(1)
Zhejiang University of Science and Technology (CN), Westlake University (CN), Ningbo No. 2 Hospital (CN), Ministry of Education (KR), Zhejiang Provincial People's Hospital (CN), Women's Hospital, School of Medicine, Zhejiang University (CN), Zhejiang Pharmaceutical College (CN), Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN), Ningbo University Affiliated Hospital (CN), Ministry of Public Health (MG), Hangzhou Medical College (CN), Zhejiang University (CN)
National Natural Science Foundation of China, Zhejiang University, Major Research Plan, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 2%
Extracellular vesicles in disease
8.06
DOIOpen Access PDFOpenAlex
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