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L-GIREMI uncovers RNA editing sites in long-read RNA-seq

Although long-read RNA-seq is increasingly applied to characterize full-length transcripts it can also enable detection of nucleotide variants, such as genetic mutations or RNA editing sites, which is significantly under-explored. Here, we present an in-depth study to detect and analyze RNA editing...

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Autores principales: Liu, Zhiheng, Quinones-Valdez, Giovanni, Fu, Ting, Huang, Elaine, Choudhury, Mudra, Reese, Fairlie, Mortazavi, Ali, Xiao, Xinshu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10360234/
https://www.ncbi.nlm.nih.gov/pubmed/37474948
http://dx.doi.org/10.1186/s13059-023-03012-w
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author Liu, Zhiheng
Quinones-Valdez, Giovanni
Fu, Ting
Huang, Elaine
Choudhury, Mudra
Reese, Fairlie
Mortazavi, Ali
Xiao, Xinshu
author_facet Liu, Zhiheng
Quinones-Valdez, Giovanni
Fu, Ting
Huang, Elaine
Choudhury, Mudra
Reese, Fairlie
Mortazavi, Ali
Xiao, Xinshu
author_sort Liu, Zhiheng
collection PubMed
description Although long-read RNA-seq is increasingly applied to characterize full-length transcripts it can also enable detection of nucleotide variants, such as genetic mutations or RNA editing sites, which is significantly under-explored. Here, we present an in-depth study to detect and analyze RNA editing sites in long-read RNA-seq. Our new method, L-GIREMI, effectively handles sequencing errors and read biases. Applied to PacBio RNA-seq data, L-GIREMI affords a high accuracy in RNA editing identification. Additionally, our analysis uncovered novel insights about RNA editing occurrences in single molecules and double-stranded RNA structures. L-GIREMI provides a valuable means to study nucleotide variants in long-read RNA-seq. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03012-w.
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spelling pubmed-103602342023-07-22 L-GIREMI uncovers RNA editing sites in long-read RNA-seq Liu, Zhiheng Quinones-Valdez, Giovanni Fu, Ting Huang, Elaine Choudhury, Mudra Reese, Fairlie Mortazavi, Ali Xiao, Xinshu Genome Biol Method Although long-read RNA-seq is increasingly applied to characterize full-length transcripts it can also enable detection of nucleotide variants, such as genetic mutations or RNA editing sites, which is significantly under-explored. Here, we present an in-depth study to detect and analyze RNA editing sites in long-read RNA-seq. Our new method, L-GIREMI, effectively handles sequencing errors and read biases. Applied to PacBio RNA-seq data, L-GIREMI affords a high accuracy in RNA editing identification. Additionally, our analysis uncovered novel insights about RNA editing occurrences in single molecules and double-stranded RNA structures. L-GIREMI provides a valuable means to study nucleotide variants in long-read RNA-seq. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03012-w. BioMed Central 2023-07-20 /pmc/articles/PMC10360234/ /pubmed/37474948 http://dx.doi.org/10.1186/s13059-023-03012-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Method
Liu, Zhiheng
Quinones-Valdez, Giovanni
Fu, Ting
Huang, Elaine
Choudhury, Mudra
Reese, Fairlie
Mortazavi, Ali
Xiao, Xinshu
L-GIREMI uncovers RNA editing sites in long-read RNA-seq
title L-GIREMI uncovers RNA editing sites in long-read RNA-seq
title_full L-GIREMI uncovers RNA editing sites in long-read RNA-seq
title_fullStr L-GIREMI uncovers RNA editing sites in long-read RNA-seq
title_full_unstemmed L-GIREMI uncovers RNA editing sites in long-read RNA-seq
title_short L-GIREMI uncovers RNA editing sites in long-read RNA-seq
title_sort l-giremi uncovers rna editing sites in long-read rna-seq
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10360234/
https://www.ncbi.nlm.nih.gov/pubmed/37474948
http://dx.doi.org/10.1186/s13059-023-03012-w
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