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Updated: Apr 11, 2026

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3' End Sequencing Library Preparation with A-seq2
Published on: October 10, 2017
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ESPeR-seq: Extremely Sensitive and Pure, End-to-end, RNA-seq library preparation
Hui-Min Chen1, Jui-Chun Kao1,2, Ching-Po Yang1,2
1Life Sciences Institute, University of Michigan, 210 Washtenaw Ave, Ann Arbor, 481090, MI, USA.
Biorxiv : the Preprint Server for Biology
|April 10, 2026
Summary
ESPER-seq overcomes key limitations in single-cell RNA sequencing by preventing artificial UMI inflation and precisely capturing transcript ends. This novel method enhances accuracy and enables robust gene discovery.
Area of Science:
- Molecular Biology
- Genomics
- Biotechnology
Background:
- Smart-seq methods are standard for single-cell RNA sequencing but face challenges with PCR bias, imprecise transcription end site (TES) capture, and phantom UMIs.
- Phantom UMIs inflate molecular counts, compromising RNA sequencing data accuracy.
- Accurate quantification and full-length transcript resolution are crucial for single-cell analysis.
Purpose of the Study:
- To introduce ESPeR-seq, a novel single-cell RNA sequencing architecture designed to address existing limitations.
- To enable precise, stranded transcription end site (TES) capture.
- To eliminate PCR background and phantom UMIs for improved molecular count accuracy.
Main Methods:
- Developed an "Omega-dT" primer for direct, high-quality sequencing at transcript termini and precise, stranded TES capture.
- Implemented a biochemical "multi-lock" mechanism using uracil-containing TSOs and a uracil-intolerant DNA polymerase to prevent PCR bias and phantom UMIs.
- Introduced the logQ-slope metric for sensitive diagnosis of UMI fidelity.
Main Results:
- ESPER-seq strictly prevents UMI inflation, unlike current state-of-the-art methods.
- The method achieves precise, stranded TES capture, facilitating robust de novo gene model reconstruction.
- Discovered novel multi-exon genes, unannotated 3' UTR extensions, and candidate eRNAs.
Conclusions:
- ESPER-seq provides a robust framework for absolute quantitative accuracy in single-cell RNA sequencing.
- The technology enables high-resolution, full-length isoform analysis.
- ESPER-seq significantly advances the capabilities of single-cell transcriptomics for gene discovery and quantification.

