Explorations to improve the completeness of exome sequencing

Area of Science:

• Genomics
• Medical Genetics

Background:

• Exome sequencing is a clinical tool for rare disease diagnosis.
• Approximately 75% of clinical exome studies do not yield a definitive molecular diagnosis.
• Undiagnosed rare disease cases present a significant diagnostic challenge.

Purpose of the Study:

• To quantify analytical performance of current clinical exome analysis.
• To explore strategies for improving the completeness of exome data analysis.
• To identify disease-causing variants missed by standard exome analysis.

Main Methods:

• Analysis of patient data from the Undiagnosed Diseases Program.
• Focus on patient ascertainment, exome capture techniques, and intronic variant inclusion.
• Evaluation of medium-sized structural variants in exome data.

Main Results:

• Preliminary data suggest current standard-of-care exome analysis misses disease-causing variants.
• Limitations in experimental design, technical performance, and data analysis contribute to false negatives.
• Proposed strategies may enable recovery of previously missed variants in second-pass analysis.

Conclusions:

• Current clinical exome analysis has limitations in variant detection.
• Improved methods for disease variant detection are needed.
• Genome-scale sequencing techniques offer potential for enhanced diagnostic yield.