<i>In silico</i> and experimental approaches for validating RNA editing events in transcriptomes

As a typical RNA virus, SARS-CoV-2 is subjected to RNA editing in host cells. While some researchers believe that a traditional variant calling pipeline retrieves all true-positive RNA editing events from the transcriptome, others argue that conventional methods identify many false-positive sites. Here, I describe several additional <i>in silico</i> and experimental approaches to validate the authenticity of RNA editing in SARS-CoV-2. These approaches include requiring strand-specific sequencing, analysis of hyperedited reads, linkage analysis, orthogonal methods like mass spectrometry, and the use of ADAR-deficient host cells. These findings may improve future analyses on the identification of RNA editing, especially in RNA viruses.

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Publication Details

Journal
RNA Biology
Published
2024-11-24
DOI
https://doi.org/10.1080/15476286.2024.2432729
Citations
1
Primary Topic
RNA regulation and disease
Type
article
Field-Weighted Citation Impact
0.23
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article

In silico and experimental approaches for validating RNA editing events in transcriptomes

Lai Wei
1 citations
RNA Biology
RNA regulation and disease
0.23
article

In silico and experimental approaches for validating RNA editing events in transcriptomes

Lai Wei
article en
1 citations

Abstract

As a typical RNA virus, SARS-CoV-2 is subjected to RNA editing in host cells. While some researchers believe that a traditional variant calling pipeline retrieves all true-positive RNA editing events from the transcriptome, others argue that conventional methods identify many false-positive sites. Here, I describe several additional <i>in silico</i> and experimental approaches to validate the authenticity of RNA editing in SARS-CoV-2. These approaches include requiring strand-specific sequencing, analysis of hyperedited reads, linkage analysis, orthogonal methods like mass spectrometry, and the use of ADAR-deficient host cells. These findings may improve future analyses on the identification of RNA editing, especially in RNA viruses.

RNA BiologyVol. 21(1)
Beijing Normal University (CN)
Openalex Percentile: Top 41%
RNA regulation and disease
0.23
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