{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Rybacki K"],"funding":["Intellectual and Developmental Disabilities Research Center","University of Pennsylvania","The Children's Hospital of Philadelphia","NIH","National Human Genome Research Institute"],"pagination":["101111"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12461587"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["5(8)"],"pubmed_abstract":["We present a comprehensive gene fusion (GF) detection and analysis workflow that combines targeted panel-based and whole-transcriptome long-read sequencing. We first adapted libraries from the short-read CHOP Cancer Fusion Panel, which targets 119 oncogenes commonly implicated in cancer fusions, for use on Oxford Nanopore Technologies' long-read sequencing platform. Long-read sequencing successfully detected known GFs in panel-positive samples, confirming compatibility, and enabled reduced turnaround times. To expand GF discovery in clinically challenging cases, we analyzed 24 glioma samples with negative short-read fusion panel results using whole-transcriptome long-read sequencing. This identified 20 candidate GFs in panel-negative samples that were absent from current fusion databases, all of which were experimentally validated. In summary, we introduce a computational workflow that combines panel-based and whole-transcriptome long-read sequencing with tailored analysis pipelines to enable fast and comprehensive GF detection in cancer."],"journal":["Cell reports methods"],"pubmed_title":["Combining panel-based and whole-transcriptome-based gene fusion detection by long-read sequencing."],"pmcid":["PMC12461587"],"funding_grant_id":["HG000046","HG013359","GM132713","HD105354"],"pubmed_authors":["Rybacki K","Deutsch HM","Ahsan MU","Chan J","Liang Z","Xu F","Li M","Wang K","Song Y"],"additional_accession":[]},"is_claimable":false,"name":"Combining panel-based and whole-transcriptome-based gene fusion detection by long-read sequencing.","description":"We present a comprehensive gene fusion (GF) detection and analysis workflow that combines targeted panel-based and whole-transcriptome long-read sequencing. We first adapted libraries from the short-read CHOP Cancer Fusion Panel, which targets 119 oncogenes commonly implicated in cancer fusions, for use on Oxford Nanopore Technologies' long-read sequencing platform. Long-read sequencing successfully detected known GFs in panel-positive samples, confirming compatibility, and enabled reduced turnaround times. To expand GF discovery in clinically challenging cases, we analyzed 24 glioma samples with negative short-read fusion panel results using whole-transcriptome long-read sequencing. This identified 20 candidate GFs in panel-negative samples that were absent from current fusion databases, all of which were experimentally validated. In summary, we introduce a computational workflow that combines panel-based and whole-transcriptome long-read sequencing with tailored analysis pipelines to enable fast and comprehensive GF detection in cancer.","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Aug","modification":"2026-06-03T20:13:44.636Z","creation":"2026-05-01T03:11:04.865Z"},"accession":"S-EPMC12461587","cross_references":{"pubmed":["40695274"],"doi":["10.1016/j.crmeth.2025.101111"]}}