Quantitative detection of low-abundance somatic structural variants in normal cells by high-throughput sequencing

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• High-throughput sequencing faces challenges in detecting low-abundance somatic DNA mutations.
• Distinguishing sequencing errors from true mutations is difficult.
• Accurate genome-wide assessment of somatic structural variants (somSVs) in bulk DNA remains elusive.

Purpose of the Study:

• To develop a method for accurate detection of rare somSVs using low-coverage sequencing.
• To enable quantitative assessment of somSVs.
• To evaluate the method's performance in detecting somSVs induced by clastogenic agents.

Main Methods:

• Structural Variant Search (SVS), a novel computational method.
• Low-coverage sequencing of DNA.
• Analysis of human primary cells treated with clastogenic compounds.

Main Results:

• SVS accurately detects rare somSVs using low-coverage sequencing data.
• The method allows for direct quantitative assessment of somSV frequencies.
• Elevated somSV frequencies were successfully quantified in cells exposed to clastogenic compounds.

Conclusions:

• SVS provides an accurate and quantitative approach for detecting rare somSVs.
• The method is effective for assessing somSV induction by genotoxic agents.
• This advancement facilitates genome-wide analysis of somatic structural variations.