A second look at exome sequencing data: detecting mobile elements insertion in a rare disease cohort

Area of Science:

• Genetics
• Genomic Medicine
• Molecular Biology

Background:

• Mobile element insertions (MEIs) constitute a small but significant fraction of genetic variants.
• Advances in next-generation sequencing enable large-scale identification of MEIs.

Purpose of the Study:

• To identify pathogenic MEIs within the coding sequences of genes using exome sequencing (ES) data.
• To assess the diagnostic utility of MEI detection in individuals with developmental and/or neurological disorders.

Main Methods:

• Analysis of exome sequencing data from 3232 individuals using the MELT tool for MEI identification.
• Filtering of identified MEIs based on frequency, impacted regions, and gene function.
• Phenotype comparison and RNA studies to confirm pathogenicity.

Main Results:

• Identified a homozygous insertion in the FERMT1 gene associated with Kindler syndrome in one patient.
• Detected a de novo Alu insertion in the GRIN2B gene linked to intellectual disability in another patient.
• Observed a frequency of de novo exonic MEIs consistent with previous ES-based studies.

Conclusions:

• Integrating MEI detection into ES pipelines can enhance diagnostic rates for genetic disorders.
• Exome sequencing alone may be sufficient as a diagnostic tool, particularly with advanced variant detection methods.
• This study provides further evidence for the clinical relevance of MEIs in human disease.