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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.
Afiliação
  • Liu Z; Department of Integrative Biology and Physiology, University of California, Los Angeles, CA, USA.
  • Quinones-Valdez G; Department of Integrative Biology and Physiology, University of California, Los Angeles, CA, USA.
  • Fu T; Molecular, Cellular, and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, CA, USA.
  • Huang E; Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA.
  • Choudhury M; Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA.
  • Reese F; Department of Developmental and Cell Biology, University of California, Irvine, CA, USA.
  • Mortazavi A; Center for Complex Biological Systems, University of California, Irvine, CA, USA.
  • Xiao X; Department of Developmental and Cell Biology, University of California, Irvine, CA, USA.
Genome Biol ; 24(1): 171, 2023 07 20.
Article em En | MEDLINE | ID: mdl-37474948
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Edição de RNA / Transcriptoma Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Edição de RNA / Transcriptoma Idioma: En Ano de publicação: 2023 Tipo de documento: Article