{
  "abstract": "Plate-based full-length single-cell RNA sequencing resolves transcript structure details but remains difficult to scale because each cell usually requires a separate library. Here we developed CHART-seq (Combinatorial Heteroduplex Assay via Recombinant Tn5), which uses orthogonally indexed Tn5 complexes to tagment RNA/cDNA heteroduplexes and permits early sample pooling. The workflow processed up to 96 cells per library, was compatible with 384-well expansion, and completed library preparation within 3 h at a reagent cost below US$1 per cell. At matched sequencing depth, CHART-seq detected more genes and annotated isoforms than Smart-seq2, Smart-seq3, Flash-seq and SHERRY2, while retaining broad genebody coverage and reproducible expression estimates. In the CHART-seq results of vascular smooth muscle cells, TGF-{beta}1 pretreatment before PDGF-BB exposure partly restored contractile features, suppressed a PDGF-associated inflammatory programme, and induced a distinct metabolic-matrix response with coordinated transcript-usage changes. These biological findings remain exploratory because independent biological replicates were unavailable. CHART-seq provides a rapid, scalable route to full-length single-cell transcript profiling with gene-programme and candidate isoform resolution.",
  "abstract_shown": true,
  "affiliations": [
    "State Key Laboratory of Digital Medical Engineering, Nantong First People's Hospital, School of Biological Science and Medical Engineering, Southeast University"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
      "name": "W. Zhang"
    },
    {
      "name": "A. Chen"
    },
    {
      "name": "K. Ye"
    },
    {
      "name": "H. Wang"
    },
    {
      "name": "J. Shen"
    },
    {
      "name": "Z. Jiao"
    },
    {
      "name": "Y. Guo"
    },
    {
      "name": "Y. Xu"
    },
    {
      "name": "D. Zhang"
    },
    {
      "name": "Y. Huang"
    },
    {
      "name": "L. He"
    },
    {
      "name": "X. Gao"
    },
    {
      "affs": [
        0
      ],
      "name": "X. Zhao"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cc0edm7ma5wgz.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.18.752546",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752546v1.full",
  "id": "cc0edm7ma5wgz",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752546v1",
  "language": null,
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "genomics"
    ],
    [
      "openalex",
      "1312|Single-cell and spatial transcriptomics"
    ]
  ],
  "openalex": "W7214200278",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752546v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-18",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/cc0edm7ma5wgz.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:24:24Z",
      "native_id": "10.64898/2026.09.18.752546",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.18.752546v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:genomics",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "Ultra-fast and scalable high-resolution full-length single-cell RNA sequencing using CHART-seq",
  "title_text": "Ultra-fast and scalable high-resolution full-length single-cell RNA sequencing using CHART-seq",
  "type": "preprint",
  "updated_at": "2026-10-30T12:24:24Z",
  "url": "https://research.draconitic.com/paper/cc0edm7ma5wgz",
  "venue": "bioRxiv",
  "versions": []
}