PurposeIdentifying structural variations (SVs) associated with developmental disorder (DD) patient phenotype missed by conventional approaches. MethodsWe have developed a novel SV discovery approach that mines split-read information, InDelible, and applied it to exome sequencing (ES) of 13,438 probands with severe DD recruited as part of the Deciphering Developmental Disorders (DDD) study. ResultsUsing InDelible we were able to find 59 previously undetected variants in genes previously associated with DD, of which 49.2% (29) had phenotypic features that accord with those of the patient in which they were found, and were deemed plausibly pathogenic. InDelible was particularly effective at ascertaining variants between 21-500 bps in size, and increased the total number of potentially pathogenic variants identified by DDD in this size range by 42.0% (n = 29 variants). Of particular interest were seven confirmed de novo SVs in the gene MECP2; these variants represent 31.8% of all de novo protein truncating variants in MECP2 among DDD patients. ConclusionInDelible provides a rapid framework for the discovery of likely pathogenic SVs that are likely to be missed by standard analytical workflows and has the potential to improve the diagnostic yield of ES.

Download data

• Downloaded 248 times
• Download rankings, all-time:
  • Site-wide: 91,057
  • In genetic and genomic medicine: 320
• Year to date:
  • Site-wide: 33,669
• Since beginning of last month:
  • Site-wide: 33,669

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide