Error correction enables use of Oxford Nanopore technology for reference-free transcriptome analysis.

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Oxford Nanopore (ONT) long-read sequencing offers end-to-end transcriptome analysis, revealing complex transcription mechanisms.
• High error rates in ONT data currently limit its application, particularly in reference-free studies.
• Error correction is essential for accurate transcript reconstruction when reference genomes are unavailable or biased.

Purpose of the Study:

• To present isONcorrect, a novel computational method for error correcting ONT cDNA sequencing data.
• To enable accurate transcriptome analysis without relying on a reference genome.
• To improve the feasibility of cost-effective, full-length transcript sequencing.

Main Methods:

• Developed isONcorrect, a computational tool for error correction of ONT cDNA reads.
• The method leverages all gene isoforms simultaneously for improved error correction.
• Evaluated performance at low sequencing depths.

Main Results:

• isONcorrect achieves a median accuracy of 98.9-99.6% for ONT cDNA sequencing data.
• The method effectively corrects errors even at low sequencing depths.
• Demonstrated the potential for reference-free transcriptome analysis using cost-effective full-length transcript sequencing.

Conclusions:

• isONcorrect significantly enhances the accuracy of ONT cDNA sequencing data.
• This method facilitates robust reference-free transcriptome analysis, overcoming limitations of current ONT data.
• Enables broader application of full-length transcript sequencing for diverse biological studies.