Autism Genes, Again and Again
Despite recent advances in sequencing technologies and their lowered costs—effective, highly sensitive, and specific sequencing of multiple genes of interest from large cohorts remains expensive.
O'Roak
et al.
(p.
1619
; published online 15 November) modified molecular inversion probe methods for target-specific capture and sequencing to resequence candidate genes in thousands of patients. The technique was applied to 44 candidate genes to identify de novo mutations in a large cohort of individuals with and without autism spectrum disorder. The analysis revealed several de novo mutations in genes that together contribute to 1% of sporadic autism spectrum disorders, supporting the notion that multiple genes underlie autism-spectrum disorders.
Variants of uncertain significance fundamentally limit the clinical utility of genetic information. The challenge they pose is epitomized by BRCA1, a tumour suppressor gene in which germline loss-of-function variants predispose women to breast and ovarian cancer. Although BRCA1 has been sequenced in millions of women, the risk associated with most newly observed variants cannot be definitively assigned. Here we use saturation genome editing to assay 96.5% of all possible single-nucleotide variants (SNVs) in 13 exons that encode functionally critical domains of BRCA1. Functional effects for nearly 4,000 SNVs are bimodally distributed and almost perfectly concordant with established assessments of pathogenicity. Over 400 non-functional missense SNVs are identified, as well as around 300 SNVs that disrupt expression. We predict that these results will be immediately useful for the clinical interpretation of BRCA1 variants, and that this approach can be extended to overcome the challenge of variants of uncertain significance in additional clinically actionable genes.
Determining the pathogenicity of genetic variants is a critical challenge, and functional assessment is often the only option. Experimentally characterizing millions of possible missense variants in thousands of clinically important genes requires generalizable, scalable assays. We describe Variant Abundance by Massively Parallel Sequencing (VAMP-seq), which measures the effects of thousands of missense variants of a protein on intracellular abundance simultaneously. We apply VAMP-seq to quantify the abundance of 7,801 single amino acid variants of PTEN and TPMT, proteins in which functional variants are clinically actionable. We identify 1,138 PTEN and 777 TPMT variants that result in low protein abundance, and may be pathogenic or alter drug metabolism, respectively. We observe selection for low-abundance PTEN variants in cancer, and reveal that p.Pro38Ser, which accounts for ~10% of PTEN missense variants in melanoma, functions via a dominant negative mechanism. Finally, we demonstrate that VAMP-seq is applicable to other genes, highlighting its generalizability.
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