Abstract
Structural variants (SVs) contribute to many disorders, yet, functionally annotating them remains a major challenge. Here, we integrate SVs with RNA-sequencing from human post-mortem brains to quantify their dosage and regulatory effects. We show that genic and regulatory SVs exist at significantly lower frequencies than intergenic SVs. Functional impact of copy number variants (CNVs) stems from both the proportion of genic and regulatory content altered and loss-of-function intolerance of the gene. We train a linear model to predict expression effects of rare CNVs and use it to annotate regulatory disruption of CNVs from 14,891 independent genome-sequenced individuals. Pathogenic deletions implicated in neurodevelopmental disorders show significantly more extreme regulatory disruption scores and if rank ordered would be prioritized higher than using frequency or length alone. This work shows the deleteriousness of regulatory SVs, particularly those altering CTCF sites and provides a simple approach for functionally annotating the regulatory consequences of CNVs.
Highlights
Structural variants (SVs) contribute to many disorders, yet, functionally annotating them remains a major challenge
The final set of SVs predominantly consisted of copy number variants (CNVs) (73%) and mobile element insertions (18%)
We identified a subset of rare SVs, representing 88,819 variants
Summary
Structural variants (SVs) contribute to many disorders, yet, functionally annotating them remains a major challenge. This work shows the deleteriousness of regulatory SVs, those altering CTCF sites and provides a simple approach for functionally annotating the regulatory consequences of CNVs. Structural variants (SVs) are a common and complex form of genetic variation that contribute substantially to phenotypic diversity and disease[1,2,3]. The advent of shortread genome sequencing has facilitated SV detection at nucleotide resolution and enabled a generation of large-scale reference studies[2,9,10] Despite this progress, we still have a limited understanding of the functional impact of these variants, for those seen infrequently in populations. In a small number of examples, rare SVs have shown the potential to alter the expression of genes both within and outside the SV locus with disease relevant phenotypic consequences Such SVs often alter the regulatory landscape directly or through positional effects that change the three-dimensional structure of the genome. This work advances our understanding of the transcriptional consequences of SVs in the human brain and provides a framework for functionally annotating these variants to aid in disease studies
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