Evidence map›Paper›PMID 42038404›Full record

ArticleFrontiers in bioinformatics2026

Characterizing miRNA editing patterns in 5 types of cells using single-cell small RNA sequencing data.

Chunyi Mao, Hao Guo, Wenping Xie, Yue Xu, Hongjia Zhang, Kang Luo, Jun Yang, Yun Zheng

Abstract read
In one paragraph

Article in Frontiers in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Chunyi Mao *College of Big Data, Yunnan Agricultural University, Kunming, Yunnan, China.
Hao Guo *Department of Cardiology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Wenping XieCollege of Big Data, Yunnan Agricultural University, Kunming, Yunnan, China.
Yue XuCollege of Horticulture and Landscape, Yunnan Agricultural University, Kunming, Yunnan, China.
Hongjia ZhangCollege of Horticulture and Landscape, Yunnan Agricultural University, Kunming, Yunnan, China.
Kang LuoCollege of Horticulture and Landscape, Yunnan Agricultural University, Kunming, Yunnan, China.
Jun YangSchool of Criminal Investigation, Yunnan Police College, Kunming, Yunnan, China.
Yun ZhengCollege of Big Data, Yunnan Agricultural University, Kunming, Yunnan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

glioblastomahsa-mir-376c_48_A_gMicroRNA (miRNA)miRNA editingsingle cell

Identifiers

PMID42038404
PMCPMC13102661

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