Researchers Developed Faster, Cheaper Single-Cell Sequencing
The new CHART-seq method cuts costs to under $1 per cell while improving gene annotation accuracy.
Updated on Sept. 24, 2026 in Life Sciences
Researchers have developed CHART-seq, a new method for high-resolution single-cell RNA sequencing that enables library preparation for 96 cells in just 3 hours. The approach is a research-stage technique that aims to solve the scalability issues found in previous plate-based methods.
Why it matters
Plate-based full-length single-cell RNA sequencing has historically been difficult to scale, limiting its utility in high-throughput research. This method accelerates workflows and reduces costs, potentially increasing the accessibility of detailed genomic analysis.
CHART-seq achieves reagent costs of under $1 per cell with a 3-hour library preparation time for 96 cells. In benchmark tests, the method identified more genes and annotated more isoforms than established methods like Smart-seq2 and Flash-seq while maintaining reproducible expression estimates.
The details
CHART-seq uses orthogonally indexed Tn5 complexes—enzymes that insert genetic material into specific DNA sequences—to tagment (cut and tag) RNA/cDNA heteroduplexes. By allowing for early sample pooling and supporting 384-well expansion, the workflow processes single cells more efficiently than previous approaches. The technique retains broad genebody coverage, which allows researchers to observe the full structure of transcribed genes. In validation testing, the method effectively demonstrated that TGF-β1 pretreatment suppresses PDGF-associated inflammatory programs in vascular smooth muscle cells.
Timeline
September 2026: CHART-seq development report published.
The Tech Race
This development follows the trajectory set by the Human Cell Atlas initiative to map all human cell types at high resolution. It aims to surpass the throughput and annotation depth of incumbents like Smart-seq3 and SHERRY2 in the competitive field of plate-based transcriptomics.
This method primarily benefits researchers conducting high-throughput transcriptomic studies who require deeper gene isoform annotation. As a research-stage tool, its implementation depends on laboratories adopting the CHART-seq protocol for their existing sequencing workflows.
The takeaway
The development of CHART-seq indicates a shift toward more economical and rapid full-length single-cell sequencing for large-scale studies. Interested researchers should monitor future validation studies that demonstrate the method's reproducibility across diverse tissue types.
Further reading
For broader trends in genomic analysis, browse the latest research in Life Sciences.
Source note: This article includes information reported by Biorxiv.
