​​Analysis of Structural Variants in Individuals from the NIHR BioResource​ Rare Disease WGS dataset

Summary

​​Advances over the past 10 years in genetic science have led to remarkable progress in understanding the causes of rare genetic diseases, yet more than half of cases are still not fully understood. A primary challenge in this area of research has been the lack of power for gene discovery efforts due to relatively small cohorts and simplistic statistical models that consider only one class of variation or a single mode of inheritance. In this proposal, we will aggregate small variants (SNVs/indels) and structural variants (SVs) from 15,370 rare disease patients with whole-genome sequencing (WGS) from the NIHR BioResource Rare Disease (NIHR BRD) cohort to approach this limitation. Previous studies have focused on the contribution of rare SNVs/indels and deletions in this cohort, but the contribution of other types of SVs to disease remains unknown. In this application we will contribute to characterising a broad spectrum of SVs, and we will develop variant filtering strategies to create a high-quality set of rare variants. We will set up a framework to perform association analyses using the Bayesian analytic framework (TADA), which integrates different variant classes (SNVs, indels, SVs) and modes of inheritance (inherited, de novo) to improve on current gene and variant discovery methods. This work will help elucidate novel causes of rare diseases, which represent an important area for improving clinical genetics and disease studies.