ArticleGenome research2025
Accurate fusion transcript identification from long- and short-read isoform sequencing at bulk or single-cell resolution.
Article in Genome research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Review
- Cancer-associated fusion transcripts: mechanisms, functional roles, and clinical implications.Clinical and experimental medicine · 2026Review
- Review
- PFGPred: a stack ensemble classifier for the identification of fusion genes in plants.DNA research : an international journal for rapid publication of reports on genes and genomes · 2026Article
- igv-reports: embedding interactive genomic visualizations in HTML reports to aid variant review.Bioinformatics (Oxford, England) · 2026Article
- The GF-NEO discovery platform unveils a [KQE][DG] sequence motif within fusion neoantigens in pediatric cancer.iScience · 2026Article
- Review
- Fusion gene discovery in single cells from high throughput long read single cell transcriptomes.bioRxiv : the preprint server for biology · 2026Article
- GFSeeker: a splicing-graph-based approach for accurate gene fusion detection from long-read RNA sequencing data.Briefings in bioinformatics · 2026Article
- Long-Read Sequencing Reveals RNA Splicing Complexity in Human Diseases.Computational and structural biotechnology journal · 2026Review
- Beyond counting: how single-cell long-read sequencing turns transcriptome complexity into precision targets.Frontiers in oncology · 2026Review
- Bioinformatics frameworks for single-cell long-read sequencing: unlocking isoform-level resolution.Briefings in bioinformatics · 2025Review
- Long and Accurate: How HiFi Sequencing is Transforming Genomics.Genomics, proteomics & bioinformatics · 2025Review
- Unraveling the hidden complexity of cancer through long-read sequencing.Genome research · 2025Review
- De novo detection of somatic variants in high-quality long-read single-cell RNA sequencing data.Genome research · 2025Article
- Long-read RNA sequencing: A transformative technology for exploring transcriptome complexity in human diseases.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Review
- De novo detection of somatic variants in high-quality long-read single-cell RNA sequencing data.bioRxiv : the preprint server for biology · 2024Article
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14 authors.
Funding
Abstract
Gene fusions are found as cancer drivers in diverse adult and pediatric cancers. Accurate detection of fusion transcripts is essential in cancer clinical diagnostics and prognostics and for guiding therapeutic development. Most currently available methods for fusion transcript detection are compatible with Illumina RNA-seq involving highly accurate short-read sequences. Recent advances in long-read isoform sequencing enable the detection of fusion transcripts at unprecedented resolution in bulk and single-cell samples. Here, we developed a new computational tool, CTAT-LR-Fusion, to detect fusion transcripts from long-read RNA-seq with or without companion short reads, with applications to bulk or single-cell transcriptomes. We demonstrate that CTAT-LR-Fusion exceeds the fusion detection accuracy of alternative methods as benchmarked with simulated and genuine long-read RNA-seq. Using short- and long-read RNA-seq, we further apply CTAT-LR-Fusion to bulk transcriptomes of nine tumor cell lines and to tumor single cells derived from a melanoma sample and three metastatic high-grade serous ovarian carcinoma samples. In both bulk and single-cell RNA-seq, long isoform reads yield higher sensitivity for fusion detection than short reads with notable exceptions. By combining short and long reads in CTAT-LR-Fusion, we are able to further maximize the detection of fusion splicing isoforms and fusion-expressing tumor cells.
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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 Socratic graph.