Functional annotation of rare structural variation in the human brain

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 postmortem 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.

A cross-disorder dosage sensitivity map of the human genome

“…While disease association studies and clinical interpretation of short variants have been revolutionized by gene-level metrics that estimate intolerance to coding mutations, 50 there are few comparable metrics that reflect gene-level intolerance to dosage alterations from CNVs. Over the last decade, studies have developed methods for prioritizing likely pathogenic CNVs and estimating selection against CNVs of individual genes, 33,38,82-84 but there are no widely adopted frameworks to evaluate both haploinsufficiency and triplosensitivity for every human gene. Thus, we reasoned that a catalog of dosage sensitivity scores for all genes—even if imperfect—would provide important insights into the general principles of dosage sensitivity and represent a potentially useful tool for human genetic research and clinical CNV interpretation.…”

The impact of genomic structural variation on the transcriptome, chromatin, and proteome in the human brain

“…Most studies on the impact of SVs have been restricted to the level of mRNA expression 1,14,30,47 . However, mRNA is not the only determinant of cellular functions 48 .…”

“…For downstream analysis, we select only the “full” annotation, that reports all elements overlapping a given SV. Additional annotations such as DNase hypersensitive sites, three-dimensional chromatin architecture and CTCF binding sites obtained from RuderferLab/CNV_FunctionalAnnotation (github.com) 47 are also integrated (details in Methods - Functional genomic annotation sources ).…”

CNVpytor: a tool for CNV/CNA detection and analysis from read depth and allele imbalance in whole genome sequencing

“…Since its development a decade ago, the tool has been widely used in different scientific areas by researchers around the world for detection of CNVs in a variety of species with different genome sizes: bacteria (Coll et al, 2014), fungi (Cabañes et al, 2015), plants (Fuentes et al, 2019, Gordon et al, 2014, Wallace et al, 2014), insects (Choi et al, 2015), fish (Chain et al, 2014), birds (Yi et al, 2014), mammals (Hermsen et al, 2015, Wang et al, 2015, Gokcumen et al, 2013, Pezer et al, 2015) and humans (Abel et al, 2020, Mills et al, 2011, Sudmant et al, 2015, Nagasaki et al, 2015). It has been used to discover somatic variations in cancer and disease studies (Han et al, 2020) and to find mosaic variants in human cells (Guo et al, 2019). Although CNVnator was developed to detect germline CNVs, it is well-suited to discover copy number alteration (CNAs) present in a relatively high (>50%) fraction of cells, such as somatic alteration found in cancers.…”