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CapTrap-Seq: A platform-agnostic and quantitative approach for high-fidelity full-length RNA transcript sequencing.

Silvia Carbonell-Sala, Julien Lagarde, Hiromi Nishiyori

Biorxiv : the Preprint Server for Biology

|July 3, 2023

Summary

CapTrap-seq, a novel cDNA library preparation method, identifies full-length RNA transcripts with high accuracy. This method, combined with the LyRic pipeline, improves eukaryotic genome annotation using long-read sequencing.

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Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

Accurate eukaryotic genome annotation relies on comprehensive RNA sequencing.
Identifying full-length RNA transcripts remains a challenge for current long-read sequencing technologies.

Approach:

Developed CapTrap-seq, a cDNA library preparation method combining Cap-trapping and oligo(dT) priming.
Integrated CapTrap-seq with the LyRic data processing pipeline for enhanced transcript identification.
Benchmarked CapTrap-seq against other protocols using human tissues and both ONT and PacBio sequencing platforms.

Key Points:

CapTrap-seq effectively captures 5'capped, full-length transcripts.
The LyRic pipeline, processing CapTrap-seq data, generates highly accurate transcript models.
Up to 90% of transcript models derived from CapTrap-seq reads by LyRic are full-length.

Conclusions:

CapTrap-seq significantly enhances the accuracy and completeness of RNA transcript annotation.
This method enables highly reliable genome annotation with reduced manual curation.
CapTrap-seq represents a substantial advancement for long-read RNA sequencing applications.