Identifying and correcting repeat-calling errors in nanopore sequencing of telomeres

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Nanopore long-read sequencing offers a novel approach for genome analysis.
• Telomeres, characterized by long repetitive elements, present challenges for accurate sequencing.
• Existing nanopore sequencing methods exhibit basecalling errors in repetitive genomic regions.

Purpose of the Study:

• To investigate and quantify basecalling errors in telomeric regions using nanopore sequencing.
• To evaluate the impact of different nanopore sequencing parameters and basecallers on telomere accuracy.
• To develop and validate optimized basecalling strategies for improved telomere analysis.

Main Methods:

• Extensive analysis of nanopore sequencing datasets across various platforms and basecallers.
• Systematic evaluation of basecalling-induced errors specifically at telomere repeats.
• Tuning of nanopore basecalling models to assess improvements in telomere recovery.
• Comparative analysis of basecalling performance in telomeric versus non-telomeric genomic regions.

Main Results:

• Significant basecalling errors were identified at telomere repeats across multiple nanopore datasets and platforms.
• Optimization of nanopore basecalling models demonstrably improved the accuracy and recovery of telomeric regions.
• The enhanced basecalling strategies showed minimal adverse effects on the accuracy of other genomic sequences.
• Artefacts in telomeric regions were successfully resolved through improved basecalling model tuning.

Conclusions:

• Nanopore sequencing requires careful basecalling model optimization for accurate analysis of repetitive elements like telomeres.
• Tuned basecalling models enhance the utility of nanopore sequencing for studying telomeres and other complex genomic structures.
• Verification of basecalls in repetitive and poorly defined genomic regions is crucial for reliable genomic research.