MiRNA Editing

2010 ◽  
pp. 267-279 ◽  
Author(s):  
Dylan E. Dupuis ◽  
Stefan Maas
Keyword(s):  
Mirna Editing

scholarly journals miRmedon: confident detection of microRNA editing

2019 ◽  
Author(s):  
Amitai Mordechai ◽  
Alal Eran
Keyword(s):  
Cancer Progression ◽  
Large Scale ◽  
Complex Processes ◽  
Mirna Genes ◽  
Multiple Loci ◽  
Rnaseq Data ◽  
Error Distributions ◽  
Improved Performance ◽  
Mirna Editing ◽  
Small Rnaseq

SummarymicroRNA (miRNA), key regulators of gene expression, are prime targets for adenosine deaminase acting on RNA (ADAR) enzymes. Although ADAR-mediated A-to-I miRNA editing has been shown to be essential for orchestrating complex processes, including neurodevelopment and cancer progression, only a few human miRNA editing sites have been reported. Several computational approaches have been developed for the detection of miRNA editing in small RNAseq data, all based on the identification of systematic mismatches of ‘G’ at primary adenosine sites in known miRNA sequences. However, these methods have several limitations, including their ability to detect only one editing site per sequence (although editing of multiple sites per miRNA has been reproducibly validated), their focus on uniquely mapping reads (although 20% of human miRNA are transcribed from multiple loci), and their inability to detect editing in miRNA genes harboring genomic variants (although 73% of human miRNA loci include a reported SNP or indel). To overcome these limitations, we developed miRmedon, that leverages large scale human variation data, a combination of local and global alignments, and a comparison of the inferred editing and error distributions, for a confident detection of miRNA editing in small RNAseq data. We demonstrate its improved performance as compared to currently available methods and describe its advantages.Availability and implementationPython source code is available at https://github.com/Amitai88/[email protected]

miRNA editing landscape reveals miR-34c regulated spermatogenesis through structure and target change in pig and mouse

2018 ◽  
Vol 502 (4) ◽  
pp. 486-492 ◽  
Author(s):  
Xiaodan Wang ◽  
Peng Zhang ◽  
Leijie Li ◽  
Dongxue Che ◽  
Tongtong Li ◽  
...  
Keyword(s):  
Mirna Editing

miRNA Editing: New Insights into the Fast Control of Gene Expression in Health and Disease

2018 ◽  
Vol 55 (10) ◽  
pp. 7717-7727 ◽  
Author(s):  
Jessica Mingardi ◽  
Laura Musazzi ◽  
Giuseppina De Petro ◽  
Alessandro Barbon
Keyword(s):  
Gene Expression ◽  
Control Of Gene Expression ◽  
Health And Disease ◽  
Fast Control ◽  
Mirna Editing

scholarly journals The landscape of miRNA editing in animals and its impact on miRNA biogenesis and targeting

2017 ◽  
Vol 28 (1) ◽  
pp. 132-143 ◽  
Author(s):  
Lishi Li ◽  
Yulong Song ◽  
Xinrui Shi ◽  
Jianheng Liu ◽  
Shaolei Xiong ◽  
...  
Keyword(s):  
Mirna Biogenesis ◽  
Mirna Editing

scholarly journals OPTIMIR, a novel algorithm for integrating available genome-wide genotype data into miRNA sequence alignment analysis

2018 ◽  
Author(s):  
Florian Thibord ◽  
Claire Perret ◽  
Maguelonne Roux ◽  
Pierre Suchon ◽  
Marine Germain ◽  
...  
Keyword(s):  
Mirna Sequence ◽  
Biological Knowledge ◽  
Genotype Data ◽  
Link Type ◽  
Genome Wide ◽  
Heterozygous Carriers ◽  
Alignment Analysis ◽  
Mirna Editing ◽  
Novel Algorithm ◽  
Alignment Step

AbstractNext-generation sequencing is an increasingly popular and efficient approach to characterize the full set of microRNAs (miRNAs) present in human biosamples. MiRNAs’ detection and quantification still remain a challenge as they can undergo different post transcriptional modifications and might harbor genetic variations (polymiRs) that may impact on the alignment step. We present a novel algorithm, OPTIMIR, that incorporates biological knowledge on miRNA editing and genome-wide genotype data available in the processed samples to improve alignment accuracy.OPTIMIR was applied to 391 human plasma samples that had been typed with genome-wide genotyping arrays. OPTIMIR was able to detect genotyping errors, suggested the existence of novel miRNAs and highlighted the allelic imbalance expression of polymiRs in heterozygous carriers.OPTIMIR is written in python, and freely available on the GENMED website (http://www.genmed.fr/index.php/fr/) and on Github (github.com/FlorianThibord/OptimiR).

Abstract LB-166: miRNA editing in seed region is in synergy with cellular changes in hypoxic conditions

2016 ◽  
Author(s):  
Mario Acunzo ◽  
Giovanni Nigita ◽  
Giulia Romano ◽  
Dario Veneziano ◽  
Alessandro Lagana’ ◽  
...  
Keyword(s):  
Seed Region ◽  
Hypoxic Conditions ◽  
Cellular Changes ◽  
Mirna Editing

scholarly journals Comprehensive analysis of human small RNA sequencing data provides insights into expression profiles and miRNA editing

RNA Biology ◽  
2014 ◽  
Vol 11 (11) ◽  
pp. 1375-1385 ◽  
Author(s):  
Jing Gong ◽  
Yuliang Wu ◽  
Xiantong Zhang ◽  
Yifang Liao ◽  
Vusumuzi Leroy Sibanda ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Small Rna ◽  
Expression Profiles ◽  
Comprehensive Analysis ◽  
Small Rna Sequencing ◽  
Sequencing Data ◽  
Mirna Editing

scholarly journals MiREDiBase, a manually curated database of validated and putative editing events in microRNAs

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Gioacchino P. Marceca ◽  
Rosario Distefano ◽  
Luisa Tomasello ◽  
Alessandro Lagana ◽  
Francesco Russo ◽  
...  
Keyword(s):  
Rna Editing ◽  
Cell Biology ◽  
Enrichment Analysis ◽  
Minimum Free Energy ◽  
Binding Ability ◽  
Cellular Processes ◽  
Non Coding Rnas ◽  
Target Binding ◽  
And Function ◽  
Mirna Editing

AbstractMicroRNAs (miRNAs) are regulatory small non-coding RNAs that function as translational repressors. MiRNAs are involved in most cellular processes, and their expression and function are presided by several factors. Amongst, miRNA editing is an epitranscriptional modification that alters the original nucleotide sequence of selected miRNAs, possibly influencing their biogenesis and target-binding ability. A-to-I and C-to-U RNA editing are recognized as the canonical types, with the A-to-I type being the predominant one. Albeit some bioinformatics resources have been implemented to collect RNA editing data, it still lacks a comprehensive resource explicitly dedicated to miRNA editing. Here, we present MiREDiBase, a manually curated catalog of editing events in miRNAs. The current version includes 3,059 unique validated and putative editing sites from 626 pre-miRNAs in humans and three primates. Editing events in mature human miRNAs are supplied with miRNA-target predictions and enrichment analysis, while minimum free energy structures are inferred for edited pre-miRNAs. MiREDiBase represents a valuable tool for cell biology and biomedical research and will be continuously updated and expanded at https://ncrnaome.osumc.edu/miredibase.

scholarly journals Editing and Expression of miR-589-5p as an Important Biomarker in Colorectal Cancer

2020 ◽  
Author(s):  
Yuanyi Yue ◽  
Qiang Zhang ◽  
Li Xiao
Keyword(s):  
Colorectal Cancer ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Expression Levels ◽  
The Third ◽  
Common Cancer ◽  
Cancer Genome Atlas ◽  
The Relationship ◽  
Mirna Editing ◽  
Editing Level

Abstract Objectives: Colorectal cancer (CRC) is recognized as the third most common cancer worldwide. Recently, emerging evidence showed that microRNA (miRNA) A-to-I editing plays crucial roles in cancer prognosis as well as cancer therapy. However, the relationship between CRC and miRNA editing remains not fully understood. Herein, we presented the first comprehensive analysis of miRNA editing events in CRC. Methods: Using patient data from The Cancer Genome Atlas (TCGA), we performed editing events and detected the expression levels of miR-589-5p. Results: we identified both editing events and the expression levels of miR-589-5p are significantly associated with Consensus Molecular Subtyping (CMS), especially for CMS4. The editing and expression levels of miR-589-5p impact almost completely different sets of gene expression, indicating the edited miR-589-5p plays a different role in CRC progression, compared to the wildtype miR-589-5p. Conclusions: In conclusion, our study provided the first association of miRNA editing and CRC. We demonstrated that expression and editing level of miR‑589‑5p may work as a novel biomarker for both prognosis and diagnosis in CRC.

scholarly journals Detecting and Characterizing A-to-I MicroRNA Editing in Cancer

2021 ◽  
Author(s):  
Gioacchino P. Marceca ◽  
Luisa Tomasello ◽  
Rosario Distefano ◽  
Mario Acunzo ◽  
Carlo Croce ◽  
...  
Keyword(s):  
Rna Editing ◽  
Rna Splicing ◽  
Cancer Biology ◽  
Human Cancer ◽  
Detection Methods ◽  
Rna Modification ◽  
Messenger Rnas ◽  
Validation Methods ◽  
Non Coding Rnas ◽  
Mirna Editing

RNA editing involves the insertion, deletion or substitution of single nucleotides within a RNA molecule, without altering the DNA sequence. Adenosine to inosine (A-to-I) editing consists of an RNA modification where single adenosines along the RNA sequence are converted into inosines. Such a biochemical transformation is catalyzed by enzymes belonging to the family of adenosine deaminases acting on RNA (ADARs) and occurs either co- or post-transcriptionally. Initially, the A-to-I RNA editing phenomenon was discovered and studied in messenger RNAs (mRNAs), where it can influence RNA splicing and cause the recoding of codon sequences. The employment of more powerful, high-throughput detection methods has recently revealed that A-to-I editing widely occurs in non-coding RNAs, including microRNAs (miRNAs). MiRNAs are a class of small regulatory non-coding RNAs (ncRNAs) acting as translation inhibitors, known to exert relevant roles in controlling cell cycle, proliferation, and cancer development. Indeed, a growing number of recent researches have evidenced the importance of miRNA editing in cancer biology by exploiting various detection and validation methods. Herein, we briefly overview early and currently available A-to-I miRNA editing detection and validation methods and discuss the significance of A-to-I miRNA editing in human cancer.

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