Extracellular vesicle-derived miRNA-mediated cell–cell communication inference for single-cell transcriptomic data with miRTalk
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,...
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| Language: | English |
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BMC
2025-04-01
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| Series: | Genome Biology |
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| Online Access: | https://doi.org/10.1186/s13059-025-03566-x |
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| author | Xin Shao Lingqi Yu Chengyu Li Jingyang Qian Xinyu Yang Haihong Yang Jie Liao Xueru Fan Xiao Xu Xiaohui Fan |
| author_facet | Xin Shao Lingqi Yu Chengyu Li Jingyang Qian Xinyu Yang Haihong Yang Jie Liao Xueru Fan Xiao Xu Xiaohui Fan |
| author_sort | Xin Shao |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9e6aac1be2d34303bbb9c836f3febcd1 |
| institution | OA Journals |
| issn | 1474-760X |
| language | English |
| publishDate | 2025-04-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj-art-9e6aac1be2d34303bbb9c836f3febcd12025-08-20T02:28:08ZengBMCGenome Biology1474-760X2025-04-0126113410.1186/s13059-025-03566-xExtracellular vesicle-derived miRNA-mediated cell–cell communication inference for single-cell transcriptomic data with miRTalkXin Shao0Lingqi Yu1Chengyu Li2Jingyang Qian3Xinyu Yang4Haihong Yang5Jie Liao6Xueru Fan7Xiao Xu8Xiaohui Fan9Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women’S Hospital, Zhejiang University School of MedicineZhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women’S Hospital, Zhejiang University School of MedicineState Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang UniversityState Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang UniversityThe Center for Integrated Oncology and Precision Medicine, School of Medicine, Affiliated Hangzhou First People’S Hospital, Westlake UniversityCollege of Computer Science and Technology, Zhejiang UniversityState Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang UniversityState Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang UniversityDepartment of Hepatobiliary & Pancreatic Surgery and Minimally Invasive Surgery, Zhejiang Provincial People’S Hospital (Affiliated People’s Hospital), Hangzhou Medical CollegeZhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women’S Hospital, Zhejiang University School of MedicineAbstract 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.https://doi.org/10.1186/s13059-025-03566-xCell–cell communicationExtracellular vesicleMiRNAScRNA-seqSpatial transcriptomics |
| spellingShingle | Xin Shao Lingqi Yu Chengyu Li Jingyang Qian Xinyu Yang Haihong Yang Jie Liao Xueru Fan Xiao Xu Xiaohui Fan Extracellular vesicle-derived miRNA-mediated cell–cell communication inference for single-cell transcriptomic data with miRTalk Genome Biology Cell–cell communication Extracellular vesicle MiRNA ScRNA-seq Spatial transcriptomics |
| title | Extracellular vesicle-derived miRNA-mediated cell–cell communication inference for single-cell transcriptomic data with miRTalk |
| title_full | Extracellular vesicle-derived miRNA-mediated cell–cell communication inference for single-cell transcriptomic data with miRTalk |
| title_fullStr | Extracellular vesicle-derived miRNA-mediated cell–cell communication inference for single-cell transcriptomic data with miRTalk |
| title_full_unstemmed | Extracellular vesicle-derived miRNA-mediated cell–cell communication inference for single-cell transcriptomic data with miRTalk |
| title_short | Extracellular vesicle-derived miRNA-mediated cell–cell communication inference for single-cell transcriptomic data with miRTalk |
| title_sort | extracellular vesicle derived mirna mediated cell cell communication inference for single cell transcriptomic data with mirtalk |
| topic | Cell–cell communication Extracellular vesicle MiRNA ScRNA-seq Spatial transcriptomics |
| url | https://doi.org/10.1186/s13059-025-03566-x |
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