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EVmiRNA2.0: an updated database for miRNA expression in comprehensive human extracellular vesicles
Gui-Yan Xie1, Dandan Song1, Tao Luo1,2
1Department of Thoracic Surgery, West China Biomedical Big Data Center, West China Hospital, Med-X Center for Informatics, Sichuan University, Chengdu 610041, China.
Abstract:
Extracellular vesicle (EV)-derived microRNAs (miRNAs) are critical mediators of intercellular communication and play important roles in diverse physiological and pathological processes. However, existing EV miRNA databases are limited by outdated datasets, narrow sample diversity, and the absence of integrated analytical functions. Here, we present EVmiRNA2.0, a substantially updated database for miRNA expression in human EVs. EVmiRNA2.0 integrates 7254 human EV small RNA sequencing (smRNA-seq) samples from 45 distinct sources and 143 disease types. Compared with the previous version, EVmiRNA2.0 has the following key improvements: (i) a substantial increase in EVs datasets, expanding from 462 to 7254, a 15-fold augmentation in data volume; (ii) a flexible online differential expression analysis module, allowing users to filter and compare samples based on a project, EV subtype, sample source, and disease stage/treatment; (iii) an enhanced miRNA search system featuring cross-tissue, cross-fluid, and cross-cell-type expression profiles, along with curated functional annotation, predicted target genes, and drug interaction data; (iv) useful download options for both raw expression data and analysis results. With comprehensive datasets and improved functions, EVmiRNA2.0 will serve as a useful and indispensable resource for exploring the expression and function of EV-derived miRNAs. It is freely accessible at https://guolab.wchscu.cn/EVmiRNA2.0/.
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