ArticleNature communications2023
High-throughput and high-accuracy single-cell RNA isoform analysis using PacBio circular consensus sequencing.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed.
- ZC3H14 phosphorylation is required for nuclear speckle assembly during zygotic splicing activation in mice.EMBO reports · 2026Article
- Review
- Full-length single-cell spatial transcriptomics reveals spatial and cell-type-specific transcript isoforms in the primate brain.Nature methods · 2026Article
- Long-Read Single-Cell RNA Sequencing Reveals Dynamic Isoform Changes During Corneal Epithelial Wound Healing in Cynomolgus Monkeys.Investigative ophthalmology & visual science · 2026Article
- Tools and tactics for studying alternative splicing.Nature reviews. Genetics · 2026Review
- Amaranth: enhanced single-cell transcript assembly via discriminative modelling of UMI reads and internal reads.Bioinformatics (Oxford, England) · 2026Article
- Nanopore direct RNA sequencing and the epitranscriptome: Advances in mapping native RNA landscapes.iMeta · 2026Review
- SCOTCH: isoform-level characterization of gene expression through long-read single-cell RNA sequencing.Nature communications · 2026Article
- Current trends and challenges in deciphering single molecule resolution maps of single cell transcriptomes.Briefings in bioinformatics · 2026Review
- A practical guide to targeted single-cell RNA sequencing technologies.Communications biology · 2026Review
- Opportunities for RNA sequencing in physiology: from big data to understanding homeostasis and heterogeneity.Function (Oxford, England) · 2026Review
- Analyzing cell-type-specific isoform expression using IsoDiffR and long-read single-cell RNA sequencing.Bioinformatics (Oxford, England) · 2026Article
- Review
- Decoding the human PBMC isonome: isoform-level resolution with single-cell long-read transcriptomics.Frontiers in genetics · 2026Article
- The emerging role of circular RNAs in neuropsychiatric disorders.Translational psychiatry · 2025Review
- Amaranth: Enhanced Single-Cell Transcript Assembly via Discriminative Modeling of UMI Reads and Internal Reads.bioRxiv : the preprint server for biology · 2025Article
- Decoding the human PBMC isonome: Isoform-level resolution with single-cell long-read transcriptomics.bioRxiv : the preprint server for biology · 2025Article
- Single-Cell Transcriptomics Reveals a Multi-Compartmental Cellular Cascade Underlying Elahere-Induced Ocular Toxicity in Rats.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Transcriptomics in the era of long-read sequencing.Nature reviews. Genetics · 2025Review
- MitoDelta: identifying mitochondrial DNA deletions at cell-type resolution from single-cell RNA sequencing data.BMC genomics · 2025Article
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Authors and funding
12 authors.
Funding
Abstract
Although long-read single-cell RNA isoform sequencing (scISO-Seq) can reveal alternative RNA splicing in individual cells, it suffers from a low read throughput. Here, we introduce HIT-scISOseq, a method that removes most artifact cDNAs and concatenates multiple cDNAs for PacBio circular consensus sequencing (CCS) to achieve high-throughput and high-accuracy single-cell RNA isoform sequencing. HIT-scISOseq can yield >10 million high-accuracy long-reads in a single PacBio Sequel II SMRT Cell 8M. We also report the development of scISA-Tools that demultiplex HIT-scISOseq concatenated reads into single-cell cDNA reads with >99.99% accuracy and specificity. We apply HIT-scISOseq to characterize the transcriptomes of 3375 corneal limbus cells and reveal cell-type-specific isoform expression in them. HIT-scISOseq is a high-throughput, high-accuracy, technically accessible method and it can accelerate the burgeoning field of long-read single-cell transcriptomics.
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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.