Ultra-fast and scalable high-resolution full-length single-cell RNA sequencing using CHART-seq
- 1State Key Laboratory of Digital Medical Engineering, Nantong First People's Hospital, School of Biological Science and Medical Engineering, Southeast University
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.
Related
- Compression Sequencing enables ultra-sensitive and scalable scRNA-seq
- SpCAST enables scalable and interpretable integration of single-cell RNA sequencing and single-cell-resolved spatial transcriptomics
- Accurate and scalable demultiplexing of single-cell RNA sequencing using BEACON
- scOmnom: scalable end-to-end single-cell RNA-seq analysis with auditable resolution selection
- StoichRNA: A Scalable Framework to Map and Optimize Combinatorial RNA Systems at Single-Cell Resolution
BibTeX
@misc{zhang2026ultrafast,
title = {{Ultra-fast and scalable high-resolution full-length single-cell RNA sequencing using CHART-seq}},
author = {W. Zhang and A. Chen and K. Ye and H. Wang and J. Shen and Z. Jiao and Y. Guo and Y. Xu and D. Zhang and Y. Huang and L. He and X. Gao and X. Zhao},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.18.752546},
url = {https://www.biorxiv.org/content/10.64898/2026.09.18.752546v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Ultra-fast and scalable high-resolution full-length single-cell RNA sequencing using CHART-seq
AU - W. Zhang
AU - A. Chen
AU - K. Ye
AU - H. Wang
AU - J. Shen
AU - Z. Jiao
AU - Y. Guo
AU - Y. Xu
AU - D. Zhang
AU - Y. Huang
AU - L. He
AU - X. Gao
AU - X. Zhao
PY - 2026
DA - 2026/09/18
PB - bioRxiv
DO - 10.64898/2026.09.18.752546
UR - https://www.biorxiv.org/content/10.64898/2026.09.18.752546v1
AB - 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.
ER -