About 0.3% of all variants are due to de novo mobile element insertions (MEIs). The massive development of next-generation sequencing has made it possible to identify MEIs on a large scale. We analyzed exome sequencing (ES) data from 3232 individuals (2410 probands) with developmental and/or neurological abnormalities, with MELT, a tool designed to identify MEIs. The results were filtered by frequency, impacted region and gene function. Following phenotype comparison, two candidates were identified in two unrelated probands. The first mobile element (ME) was found in a patient referred for poikilodermia. A homozygous insertion was identified in the FERMT1 gene involved in Kindler syndrome. RNA study confirmed its pathological impact on splicing. The second ME was a de novo Alu insertion in the GRIN2B gene involved in intellectual disability, and detected in a patient with a developmental disorder. The frequency of de novo exonic MEIs in our study is concordant with previous studies on ES data. This project, which aimed to identify pathological MEIs in the coding sequence of genes, confirms that including detection of MEs in the ES pipeline can increase the diagnostic rate. This work provides additional evidence that ES could be used alone as a diagnostic exam.
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We thank the probands and their families for their participation; and the Centre De Calcul (CCuB) at the University of Burgundy for providing technical support and management of the informatics core facility.
This work was supported by grants from the Regional Council of Burgundy (to C.T.‐R.), the FEDER 2017, PARI 2017, and CIFRE (ANRT) between Laboratoire Cerba and Regional Council of Burgundy for the doctoral work at Laboratoire Cerba and GAD.
The authors declare no competing interests.
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Garret, P., Chevarin, M., Vitobello, A. et al. A second look at exome sequencing data: detecting mobile elements insertion in a rare disease cohort. Eur J Hum Genet (2022). https://doi.org/10.1038/s41431-022-01250-3