CapTrap-seq: a platform-agnostic and quantitative approach for high-fidelity full-length RNA sequencing

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Accurate eukaryotic genome annotation relies on long-read RNA sequencing.
• Identifying full-length RNA transcripts remains challenging for current long-read methods.

Purpose of the Study:

• To develop and evaluate CapTrap-seq, a novel cDNA library preparation method.
• To assess CapTrap-seq's performance in detecting 5' capped, full-length transcripts.

Main Methods:

• CapTrap-seq combines Cap-trapping with oligo(dT) priming.
• Evaluated CapTrap-seq against other RNA-seq protocols using human and mouse tissues.
• Utilized both Oxford Nanopore (ONT) and PacBio sequencing technologies.
• Incorporated synthetic RNA spike-ins with a capping strategy for quantitative assessment.

Main Results:

• CapTrap-seq demonstrates competitive performance compared to existing methods.
• The method is platform-agnostic, suitable for both ONT and PacBio sequencing.
• Validated using Long-read RNA-seq Genome Annotation Assessment Project (LRGASP) data.

Conclusions:

• CapTrap-seq is an effective RNA library preparation method for generating full-length transcript sequences.
• This method enhances the accuracy and completeness of eukaryotic genome annotation.