NMDtxDB: data-driven identification and annotation of human NMD target transcripts

• Verfasst von: Britto-Borges, Thiago [VerfasserIn]
• Verfasst von: Gehring, Niels H. [VerfasserIn]
• Verfasst von: Böhm, Volker [VerfasserIn]
• Verfasst von: Dieterich, Christoph [VerfasserIn]
• Titel: NMDtxDB: data-driven identification and annotation of human NMD target transcripts
• Verf.angabe: Thiago Britto-Borges, Niels H. Gehring, Volker Boehm, and Christoph Dieterich
• E-Jahr: 2024
• Jahr: October 2024
• Umfang: 16 S.
• Illustrationen: Illustrationen
• Fussnoten: Online veröffentlicht: 2. August 2024 ; Gesehen am 25.11.2024
• Titel Quelle: Enthalten in: RNA
• Ort Quelle: Cold Spring Harbor, NY : Laboratory Press, 1995
• Jahr Quelle: 2024
• Band/Heft Quelle: 30(2024), 10, Seite 1277-1291
• ISSN Quelle: 1469-9001
• DOI: doi:10.1261/rna.080066.124
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: alternative splicing
• Sach-SW: computational workflow
• Sach-SW: mRNA decay
• Sach-SW: nonsense-mediated RNA decay
• Sach-SW: premature stop codon
• K10plus-PPN: 1909432709

Abstract

The nonsense-mediated RNA decay (NMD) pathway is a crucial mechanism of mRNA quality control. Current annotations of NMD substrate RNAs are rarely data-driven, but use generally established rules. We present a data set with four cell lines and combinations for SMG5, SMG6, and SMG7 knockdowns or SMG7 knockout. Based on this data set, we implemented a workflow that combines Nanopore and Illumina sequencing to assemble a transcriptome, which is enriched for NMD target transcripts. Moreover, we use coding sequence information (CDS) from Ensembl, Gencode consensus Ribo-seq ORFs, and OpenProt to enhance the CDS annotation of novel transcript isoforms. In summary, 302,889 transcripts were obtained from the transcriptome assembly process, out of which 24% are absent from Ensembl database annotations, 48,213 contain a premature stop codon, and 6433 are significantly upregulated in three or more comparisons of NMD active versus deficient cell lines. We present an in-depth view of these results through the NMDtxDB database, which is available at https://shiny.dieterichlab.org/app/NMDtxDB, and supports the study of NMD-sensitive transcripts. We open sourced our implementation of the respective web-application and analysis workflow at https://github.com/dieterich-lab/NMDtxDB and https://github.com/dieterich-lab/nmd-wf.