Targeted enrichment beyond the consensus coding DNA sequence exome reveals exons with higher variant densities

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• DNA hybridization-capture followed by high-throughput sequencing is a key tool in genetics.
• Current methods primarily target consensus coding DNA sequence (CCDS) exons.
• CCDS excludes many coding and non-coding functional regions, limiting understanding of variant density and interrogation outside these areas.

Purpose of the Study:

• To investigate the performance of DNA capture sequencing in regions outside the CCDS.
• To assess variant density in non-CCDS regions compared to CCDS.
• To understand the impact of genomic subregions on capture efficiency.

Main Methods:

• Analysis of capture sequence data from regions outside CCDS.
• Examination of sequencing platform biases (Illumina, SOLiD).
• Comparison of variant density between CCDS and non-CCDS regions, including predicted exons and RefSeq/Vega specific exons.

Main Results:

• Extreme GC content in genomic subregions significantly reduces capture sequence coverage outside CCDS (<50% relative to CCDS).
• Sequencing platform biases exacerbate capture inefficiencies.
• microRNA and predicted exons showed higher than expected capture coverage compared to whole genome sequencing.
• Non-CCDS regions, particularly predicted exons and RefSeq/Vega specific exonic regions, exhibit substantially higher variant densities than CCDS.

Conclusions:

• Regions outside CCDS perform less efficiently in capture sequencing experiments.
• Computationally predicted exons demonstrate over 2.5 times higher variant density compared to CCDS.
• Current capture strategies may underestimate genetic variation in non-CCDS regions.