Detection of mobile elements insertions for routine clinical diagnostics in targeted sequencing data.

Area of Science:

• Genomics
• Clinical Diagnostics
• Molecular Biology

Background:

• Targeted sequencing (gene panels, exome sequencing) is standard for genetic disease diagnosis.
• Detection of point mutations, small indels, and copy number variants is well-established.
• Mobile element insertions (MEIs) are difficult to detect and interpret, limiting their role in diagnostics.

Purpose of the Study:

• Investigate the occurrence and diagnostic utility of MEIs in rare disease and cancer cohorts.
• Develop a strategy for detecting, prioritizing, and interpreting MEIs in clinical settings.
• Highlight the potential of MEIs to solve previously undiagnosed genetic conditions.

Main Methods:

• Analyzed 7,693 exome datasets from individuals with rare diseases and controls.
• Examined 788 cancer patient datasets analyzed by panel sequencing.
• Focused on the detection and interpretation of mobile element insertions.

Main Results:

• Presented exemplary cases demonstrating the diagnostic significance of MEIs.
• Proposed a practical strategy for the clinical detection, prioritization, and interpretation of MEIs.
• Showcased the feasibility of MEI analysis in targeted next-generation sequencing data.

Conclusions:

• MEI detection and interpretation in targeted NGS data are feasible for clinical practice.
• MEIs, though rare in coding regions, can significantly impact gene regulation and splicing.
• Reanalysis of existing cohorts for MEIs can resolve previously undiagnosed genetic disorders.