ArticleNature communications2020
ORF Capture-Seq as a versatile method for targeted identification of full-length isoforms.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Review
- Customizable host and viral transcript enrichment using CRISPR-Cas9 long-read sequencing for characterization of low-to-moderate abundance isoforms.NAR genomics and bioinformatics · 2026Article
- Tools and tactics for studying alternative splicing.Nature reviews. Genetics · 2026Review
- Transcriptomics in the era of long-read sequencing.Nature reviews. Genetics · 2025Review
- PACLseq: A Standalone Diagnostic Method for Ph-Like Acute Lymphoblastic Leukemia Using Nanopore Sequencing.MedComm · 2025Article
- Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms.Molecular cell · 2025Article
- Detection of mRNA Transcript Variants.Genes · 2025Review
- 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
- Innovative Low-cost Probe Generation Empowers Targeted Long-read RNA Sequencing.Genomics, proteomics & bioinformatics · 2025Article
- Real-time and programmable transcriptome sequencing with PROFIT-seq.Nature cell biology · 2024Article
- Challenges in identifying mRNA transcript starts and ends from long-read sequencing data.Genome research · 2024Review
- Widespread variation in molecular interactions and regulatory properties among transcription factor isoforms.bioRxiv : the preprint server for biology · 2024Article
- Chikungunya virus infection disrupts lymph node lymphatic endothelial cell composition and function via MARCO.JCI insight · 2024Article
- Coordination of alternative splicing and alternative polyadenylation revealed by targeted long read sequencing.Nature communications · 2023Article
- TEQUILA-seq: a versatile and low-cost method for targeted long-read RNA sequencing.Nature communications · 2023Article
- Structure and Alternative Splicing of the Antisense FMR1 (ASFMR1) Gene.Molecular neurobiology · 2023Article
- Coordination of Alternative Splicing and Alternative Polyadenylation revealed by Targeted Long-Read Sequencing.bioRxiv : the preprint server for biology · 2023Article
- Bridging the splicing gap in human genetics with long-read RNA sequencing: finding the protein isoform drivers of disease.Human molecular genetics · 2022Review
- A roadmap for the functional annotation of protein families: a community perspective.Database : the journal of biological databases and curation · 2022Article
- Enhanced protein isoform characterization through long-read proteogenomics.Genome biology · 2022Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
Most human protein-coding genes are expressed as multiple isoforms, which greatly expands the functional repertoire of the encoded proteome. While at least one reliable open reading frame (ORF) model has been assigned for every coding gene, the majority of alternative isoforms remains uncharacterized due to (i) vast differences of overall levels between different isoforms expressed from common genes, and (ii) the difficulty of obtaining full-length transcript sequences. Here, we present ORF Capture-Seq (OCS), a flexible method that addresses both challenges for targeted full-length isoform sequencing applications using collections of cloned ORFs as probes. As a proof-of-concept, we show that an OCS pipeline focused on genes coding for transcription factors increases isoform detection by an order of magnitude when compared to unenriched samples. In short, OCS enables rapid discovery of isoforms from custom-selected genes and will accelerate mapping of the human transcriptome.
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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.