Massively Parallel Functional Analysis of BRCA1 RING Domain Variants

Abstract

Interpreting variants of uncertain significance (VUS) is a central challenge in medical genetics. One approach is to experimentally measure the functional consequences of VUS, but to date this approach has been post hoc and low throughput. Here we use massively parallel assays to measure the effects of nearly 2000 missense substitutions in the RING domain of BRCA1 on its E3 ubiquitin ligase activity and its binding to the BARD1 RING domain. From the resulting scores, we generate a model to predict the capacities of full-length BRCA1 variants to support homology-directed DNA repair, the essential role of BRCA1 in tumor suppression, and show that it outperforms widely used biological-effect prediction algorithms. We envision that massively parallel functional assays may facilitate the prospective interpretation of variants observed in clinical sequencing.KEYWORDS deep mutational scanning; BRCA1; variants of uncertain significance; human genetic variation; protein function I N an era of increasingly widespread genetic testing, DNA sequencing identifies many missense substitutions with unknown effects on protein function and disease risk. In the absence of genetic evidence, experimental measurement is the most reliable way to determine the functional impact of a variant of uncertain significance (VUS). However, initiating an experiment for each new variant observed in a gene is often impractical. When experiments are done, they are nearly always performed in a retrospective manner (Bouwman et al. 2013), such that the resulting data are not useful for the patient in whom the VUS was observed.By prospectively measuring, in a high-throughput fashion, the consequences of all possible missense mutations on a gene's function, we can generate a look-up table for interpreting newly observed VUS. Although functional analysis at this scale is made possible by deep mutational scanning (Fowler and Fields 2014), a central challenge is that any single assay may not recapitulate all the activities of a given protein in human disease. To address this challenge, we hypothesized that integrating the results of assays of multiple biochemical functions would strengthen estimates of the effects of mutations on disease risk (strategy outlined in Figure 1A). As a proof-ofconcept, we initiated massively parallel functional analysis of BRCA1, a protein for which there are multiple biochemical functions as well as known pathogenic and benign missense substitutions to benchmark results.BRCA1 has been subject to intense study since its implication in hereditary, early onset breast and ovarian cancer (Miki et al. 1994). All missense substitutions in BRCA1 that are known to be pathogenic occur in either the amino-terminal RING domain or the carboxy-terminal BRCT repeat (http:// brca.iarc.fr/LOVD/home.php?select_db=BRCA1). Although the RING domain represents only 5% of the BRCA1 protein, 58% of the pathogenic missense substitutions occur within this domain. Sixty-two missense substitutions in the RING domain have been observed in patient...

Variant Interpretation: Functional Assays to the Rescue

“…For example, measurement of the effect of nearly all possible missense variants of the RING domain of BRCA1 and the full open reading frame of PPARG (MIM: 601487) generated functional data that were used for accurately predicting pathogenicity. 20,21 Assessment of tens of thousands of eQTLadjacent, and therefore possibly functional, transcriptional regulatory variants revealed a few hundred that influenced expression. 22 These examples illustrate how the rich and comprehensive datasets that MAVEs produce can generate predictions that are much more accurate than those of currently available variant-effect-prediction algorithms.…”

A framework for exhaustively mapping functional missense variants

“…Recent DMS studies, for example, covered the critical RING domain of BRCA1 (Starita et al , 2015) associated with breast cancer risk, and the PPARG protein associated with Mendelian lipodystrophy and increased risk of type 2 diabetes (Majithia et al , 2016). Such maps can accurately identify functionality of a clinical variant in advance of that variant's first clinical presentation.…”

Massively Parallel Genetics

“…If we want to confidently interpret variants observed even in only one or a few humans, we propose that "observational" genetics in humans must be supplemented with "perturbational" genetics in model systems: in vivo in model organisms, in vitro in tissue culture lines, or in cell-free assays of protein function (Fowler et al 2010;Starita et al 2015). This "massively parallel" paradigm requires that we know enough about the function of a gene to establish a DNA sequencing-based assay for its activity.…”