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Updated: Aug 5, 2026
An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing
Published on: May 23, 2018
Protocol for high-resolution multiplexed sequencing of single-cell full-length transcriptome with CBTi-seq
Liyong He1, Wenyi Zhang2, Peidong Qi2
1Medical Research Center, Jiangsu Provincial Medical Key Discipline (Laboratory) Cultivation Unit of Immunology, Nantong First People's Hospital, Southeast University, Nantong, Jiangsu, China; State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 211196, China.
We developed combinational barcoded Tn5 transposon insertion sequencing (CBTi-seq) to efficiently create full-length transcriptome libraries from single cells. This scalable method balances throughput and coverage for single-cell RNA sequencing (scRNA-seq) applications.
Area of Science:
- Molecular Biology
- Genomics
- Biotechnology
Background:
- Single-cell RNA sequencing (scRNA-seq) faces challenges in balancing high throughput with comprehensive full-length transcriptome coverage.
- Existing methods often require complex protocols or compromise data quality.
Purpose of the Study:
- To introduce combinational barcoded Tn5 transposon insertion sequencing (CBTi-seq), a novel, scalable protocol.
- To enable efficient construction of multiplexed, full-length transcriptome libraries from single cells and micro-region tissues.
Main Methods:
- The CBTi-seq protocol involves sample acquisition, one-step reverse-transcription PCR (RT-PCR) cDNA amplification, and orthogonal combinational barcoded Tn5 tagmentation.
- Key steps include multiplexed pooling, dual-option purification, and final library enrichment.
Main Results:
- CBTi-seq offers a highly scalable solution for transcriptome library preparation.
- The protocol facilitates the generation of full-length cDNA libraries from limited biological samples.
Conclusions:
- CBTi-seq effectively addresses the limitations of current scRNA-seq methods.
- This protocol provides a robust platform for advanced single-cell and tissue transcriptome analysis.
