Telomere-to-telomere assembly using HERRO-corrected Nanopore Simplex reads.

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Telomere-to-telomere (T2T) phased assemblies are the gold standard for reference genomes but are costly and complex.
• Current T2T assembly methods often require multiple sequencing platforms and large DNA inputs.
• High-accuracy long reads (e.g., PacBio HiFi) and ultra-long reads (ONT Simplex) are typically combined.

Purpose of the Study:

• To demonstrate that high-quality T2T genome assemblies can be achieved using only error-corrected ultra-long Oxford Nanopore (ONT) Simplex reads.
• To introduce HERRO, a deep learning framework for haplotype-aware error correction of ONT Simplex reads.
• To reduce the cost and complexity of generating reference-quality genome assemblies.

Main Methods:

• Development of the HERRO (Haplotype-aware ERRor cOrrection) deep learning framework.
• Correction of ultra-long ONT Simplex reads, preserving haplotype-specific differences.
• Assembly of corrected reads using the Verkko assembler.

Main Results:

• HERRO increased read accuracy up to 100-fold for diploid human genomes.
• T2T assemblies of up to 32 chromosomes, including sex chromosomes, were reconstructed.
• Consistent NGA50 values of >= 100 Mb were achieved across multiple human genomes.
• The method supports R9.4.1 and R10.4.1 ONT Simplex reads and generalizes to other species.

Conclusions:

• Error-corrected ONT Simplex reads can generate high-quality T2T genome assemblies.
• The HERRO framework significantly improves read accuracy while preserving haplotype information.
• This approach offers a cost-effective and efficient alternative for high-quality genome sequencing and analysis.