Optimization of DNA Fragmentation Techniques to Maximize Coverage Uniformity of Clinically Relevant Genes Using Whole...

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Coverage uniformity is critical for accurate whole genome sequencing (WGS).
• Enzyme-based fragmentation can introduce sequence biases, impacting high-GC and low-GC regions.
• PCR-free WGS library preparation workflows vary in their impact on coverage.

Purpose of the Study:

• To compare mechanical vs. enzymatic fragmentation for PCR-free WGS library preparation.
• To assess the impact on coverage uniformity and variant detection across diverse sample types.
• To evaluate performance in clinically relevant gene panels like TSO500.

Main Methods:

• Generated libraries using mechanical and three enzymatic fragmentation methods.
• Used NA12878 and diverse DNA samples (blood, saliva, FFPE).
• Sequenced on Illumina NovaSeq 6000, aligned to GRCh38/hg38, and analyzed coverage and GC content relationships.

Main Results:

• Mechanical fragmentation resulted in more uniform coverage across sample types and GC content.
• Enzymatic methods showed greater coverage imbalances, particularly in high-GC regions.
• Mechanical fragmentation maintained lower SNP error rates at reduced sequencing depths.

Conclusions:

• Mechanical fragmentation is advantageous for WGS coverage uniformity and variant detection accuracy.
• Enzymatic methods may compromise sensitivity in high-GC regions, impacting clinical variant identification.
• This study provides a framework for optimizing WGS library preparation for reliable variant detection.