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A Novel Approach to Generate Enzyme-free Single Cell Suspensions from archived Tissues for miRNA Sequencing

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NIAID Data Ecosystem2026-05-01 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE264138
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Obtaining high-quality omics data at the single-cell level from archived human tissue samples is crucial for gaining insights into cellular heterogeneity and pushing the field of personalized medicine forward. In this technical brief we present a comprehensive methodological framework for the efficient enzyme-free preparation of tissue-derived single cell suspensions and their conversion into single-cell miRNA sequencing libraries. The resulting data from this study have the potential to deepen our understanding of miRNA expression at the single-cell level and its relevance in the context of the examined tissues. The workflow encompasses tissue collection, RNALater immersion, storage, thawing, TissueGrinder-mediated dissociation, miRNA lysis, library preparation, sequencing, and data analysis. Quality control measures ensure reliable miRNA data, with specific attention to sample quality. The UMAP analysis reveals tissue-specific cell clustering, while miRNA diversity reflects tissue variations. The presented workflow effectively processes preserved tissues, extending opportunities for retrospective analyses and biobank utilization. Single-cell miRNA sequencing method for archived human tissues
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2024-04-19
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