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A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools
Published on: August 21, 2019
Characterizing miRNA editing patterns in 5 types of cells using single-cell small RNA sequencing data
Chunyi Mao1,2, Hao Guo3, Wenping Xie1,2
1College of Big Data, Yunnan Agricultural University, Kunming, Yunnan, China.
Abstract:
Numerous studies have identified a large number of miRNA editing sites via deep sRNA sequencing profiling of tissue samples. However, the single-cell landscape of miRNA editing patterns has remained largely unknown to date. To investigate miRNA editing and mutation characteristics at single cell level, this study analyzed miRNA editing and mutation events in 448 single-cell small RNA sequencing profiles from 5 different cell types. Our results revealed that PCA and clustering analysis, performed based on the editing levels of identified miRNA editing sites, could distinguish distinct cell types, indicating that miRNA editing patterns are cell-type-specific across different cellular populations. We further demonstrated that a subset of miRNA editing sites exhibited strict cell-type-specific editing patterns. Meanwhile, within the same cell type, the identified sites presented different distributions of editing levels in different cells. A fraction of sites showed highly variable editing levels among different cells of the same cell type, while some sites displayed relatively uniform and consistent editing patterns. An A-to-I editing site in hsa-mir-376c, i.e., hsa-mir-376c 48 A g, showed a significantly higher editing level in glioblastoma cells than in naive embryonic stem cells, suggesting a potential role in the initiation and progression of glioblastoma. Furthermore, our results also suggest that in leukemia cells, TENT4A, TENT5A, TENT5B, TENT5C, TENT5D, and TUT1 may mediate the non-templated nucleotide additions to the 3'ends of miRNAs.
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