HySA: a Hybrid Structural variant Assembly approach using next-generation and single-molecule sequencing technologies

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Accurate human genome assembly is crucial for precision medicine.
• Existing sequencing technologies face limitations with genomic repeats and variations.
• Novel assembly methods are needed to leverage complementary sequencing strengths.

Purpose of the Study:

• To develop a novel approach for accurate human genome assembly and structural variant (SV) detection.
• To integrate data from next-generation sequencing (NGS) and single-molecule sequencing (SMS) technologies.
• To enhance the assembly of complex genomic regions, including those with structural alterations.

Main Methods:

• Proposed a Hybrid Structural variant Assembly (HySA) approach.
• Integrated sequencing reads from NGS and SMS platforms.
• Utilized a bipartite-graph-based clustering algorithm to identify homologous SV-containing reads.
• Decomposed the whole genome assembly into independent SV assembly problems.

Main Results:

• HySA demonstrated a low false discovery rate in genome assembly.
• Significantly improved the detection of various structural variants (SVs).
• Enhanced identification of novel large insertions, small indels (10-50 bp), and repeat expansions/contractions.

Conclusions:

• HySA effectively integrates complementary sequencing technologies for improved SV discovery.
• The approach enhances the assembly of structurally complex regions in the human genome.
• This method provides a solution for extending the capabilities of current sequencing technologies for SV analysis.