Next-generation diagnostics: gene panel, exome, or whole genome?

Area of Science:

• Genomics
• Medical Genetics
• Bioinformatics

Background:

• Next-generation sequencing (NGS) aids in diagnosing heterogeneous diseases like intellectual disability (ID).
• Consensus is lacking on the optimal NGS approach: targeted enrichment, whole-exome sequencing (WES), or whole-genome sequencing (WGS).

Purpose of the Study:

• To compare WES and WGS for intellectual disability diagnostics.
• To determine cost-effective sequencing criteria for WES.

Main Methods:

• Comparative analysis of WES and WGS data from nine samples.
• Assessment of variant detection and sequence coverage for a 500-gene panel (500GP) linked to ID.
• Investigation of sequencing read counts versus coverage and variant yield.

Main Results:

• WES identified all variants found by WGS within the 500GP.
• Deeply sequenced WES achieved ~99% coverage of the 500GP, indicating minimal benefit from targeted enrichment.
• 60 million reads provided ~60× mean coverage, covering ~97% of the 500GP with high variant yield (~99.5%) and controlled error rates.

Conclusions:

• Whole-exome sequencing (WES) is currently the optimal method for intellectual disability diagnostics.
• Minimal sequencing criteria (e.g., 60 million reads) can reduce costs while maintaining diagnostic accuracy.
• The framework is adaptable to different sequencing kits and strategies.