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James Reid, Sandra Kachhia, Paul Dougall, John Shovelton, Duarte Molha, Christina Taylor, Jagath Kasturiarachchi, Jolyon Holdstock, Venu Pullabhatla, Laura Parkes, Ewa Marek, Natalie Milner, Emma Shipstone, Douglas Hurd



The detection of Copy Number Variants (CNVs) in intellectual disability and developmental delay (ID/DD) samples is crucial in elucidating the genetic cause of abnormality. We have developed a targeted NGS panel and analytical software (Interpret) to accurately detect CNVs, as well as SNVs, indels and LOH.

The assay uses a bait capture approach, which is able to capture the exons and untranslated regions (UTRs) from over 700 genes, chosen for their relevance in ID/DD, as well as a range of backbone regions across the genome. Combined with OGTs proprietary CNV detection algorithm in the software, both intragenic and large ‘backbone’ CNVs can be detected robustly.

We implemented a web-based solution that runs OGTs NGS analysis pipeline, comprising many state-of-the-art open-source NGS software tools. These tools were carefully chosen and deployed using containers to ensure cross-platform compatibility and reproducibility. Pipeline optimisation and performance was assessed using equivalent array data and reference materials.

We will outline the results from over 200 intellectual disability and developmental delay research samples to demonstrate the efficiency of the CNV, SNV and LOH detection. The study demonstrated that the assay automatically called 100% of SNVs and 97% of reported pathogenic CNVs (including small intragenic CNVs), the uncalled CNVs were visible on Interpret but the protocol of the study precluded them from being called. We have described an improved method to investigate ID/DD samples, providing critical information on not just CNVs, but SNVs and Indels as well.

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