Accurate and rapid single nucleotide variation detection in PCSK9 gene using nanopore sequencing

Area of Science:

• Genomics
• Molecular Diagnostics
• Bioinformatics

Background:

• Genetic testing is crucial for disease screening, diagnosis, prognosis, and guiding pharmacotherapy.
• Oxford Nanopore Technologies (ONT) provides a cost-effective long-read sequencing platform, but its clinical diagnostic utility is still under evaluation.
• This study evaluates nanopore sequencing pipelines for accurate single-nucleotide variant (SNV) detection in a 25kb gene locus.

Purpose of the Study:

• To assess the performance of different nanopore sequencing pipelines for SNV detection.
• To identify optimal basecalling models and variant calling algorithms for clinical applications.
• To evaluate the throughput and cost-effectiveness of ONT platforms for targeted gene sequencing.

Main Methods:

• The *PCSK9* gene was used as a proof of concept due to its cardiovascular relevance.
• Twelve subjects were analyzed using various flow cells, basecalling models (including SUP), and SNV calling algorithms (including Longshot).
• Sanger sequencing was employed as the reference standard for validation, alongside throughput estimations.

Main Results:

• The combination of SUP basecalling and Longshot variant calling achieved the highest SNV detection performance.
• MinION flow cells yielded a perfect 100% F1-score, while Flongle flow cells demonstrated high accuracy (98.2% ± 4.2%).
• Throughput analysis revealed that MinION and Flongle flow cells can process up to 96 samples for targeted sequencing.

Conclusions:

• Proposed nanopore-based SNV identification workflows are promising for developing long-read, targeted gene panels.
• These workflows can support both diagnostic and discovery applications, especially in complex multi-gene settings like oncology and cardiology.
• ONT technology offers a viable and cost-effective solution for clinical genetic variant detection.