Shao Xin, Yu Lingqi, Li Chengyu, Qian Jingyang, Yang Xinyu, Yang Haihong, Liao Jie, Fan Xueru, Xu Xiao, Fan Xiaohui
Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases, Women'S Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
State Key Laboratory of Chinese Medicine Modernization, Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, 314102, China.
Genome Biol. 2025 Apr 14;26(1):95. doi: 10.1186/s13059-025-03566-x.
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.
微小RNA从细胞中释放到细胞外囊泡（EVs）中，通过对基因表达的调节作用代表了细胞间通讯（CCC）的一种基本模式。单细胞RNA测序技术开创了以单细胞分辨率阐明CCC的时代。在此，我们提出了miRTalk，这是一种用于推断由EV衍生的微小RNA-靶标相互作用（MiTIs）介导的CCC的开创性方法。对模拟和真实世界数据集的基准测试证明了miRTalk的卓越性能，并且在四种疾病场景中的应用揭示了深入的MiTI介导的CCC机制。总体而言，miRTalk可以利用scRNA-seq数据推断EV衍生的MiTI介导的CCC，为生物过程的细胞间动态提供新的见解。
