ArticleRNA biology2024
An optimized workflow of full-length transcriptome sequencing for accurate fusion transcript identification.
Article in RNA biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Nanopore long-read transcriptome sequencing reveals miR-22-3p-mediated transcriptomic remodeling and alternative splicing in chicken pectoral muscle.Poultry science · 2026Article
- Long-Read Transcriptome Sequencing and Functional Validation Reveals Novel and Oncogenic Gene Fusions in Fusion Panel-Negative Gliomas.bioRxiv : the preprint server for biology · 2026Article
- Next generation sequencing and beyond: a review of genomic sequencing methods.Functional & integrative genomics · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Next-generation sequencing has revolutionized cancer genomics by enabling high-throughput mutation screening yet detecting fusion genes reliably remains challenging. Long-read sequencing offers potential for accurate fusion transcript identification, though challenges persist. In this study, we present an optimized workflow using nanopore sequencing technology to precisely identify fusion transcripts. Our approach encompasses a tailored library preparation protocol, data processing, and fusion gene analysis pipeline. We evaluated the performance using Universal Human Reference RNA and human adenocarcinoma cell lines. Our optimized nanopore sequencing workflow generated high-quality full-length transcriptome data characterized by an extended length distribution and comprehensive transcript coverage. Validation experiments confirmed novel fusion events with potential clinical relevance. Our protocol aims to mitigate biases and enhance accuracy, facilitating increased adoption in clinical diagnostics. Continued advancements in long-read sequencing promise deeper insights into fusion gene biology and improved cancer diagnostics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.