10) where R(pCa) represents the column of the measured ratios, and
16. We recommend applying a broad range of concentrations for test compounds with unknown toxicity profile
Acknowledgments
The authors gratefully acknowledge funding of the Staedtler Stiftung and Bavarian Equal Opportunities Sponsorship—
Fửrderung von Frauen in Forschung und Lehre (FFL)—Promoting Equal Opportunities for Women in Research and Teaching.
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Chapter 17
Systematic Cell-Based Phenotyping of Missense Alleles
Aenne S. Thormọhlen and Heiko Runz
Abstract
Sequencing of the protein-coding genome, the exome, has proven powerful to unravel links between genetic variation and disease for both Mendelian and complex conditions. Importantly, however, the increasing number of sequenced human exomes and mapping of disease-associated alleles is accompanied by a simultaneous, yet exponential increase in the overall number of rare and low frequency alleles identi- fied. For most of these novel alleles, biological consequences remain unknown since reliable experimental approaches to better characterize their impact on protein function are only slowly emerging.
Here we review a scalable, cell-based strategy that we have recently established to systematically profile the biological impact of rare and low frequency missense variants in vitro. By applying this approach to missense alleles identified through cohort-level exome sequencing in the low-density lipoprotein receptor (LDLR) we are able to distinguish rare alleles that predispose to familial hypercholesterolemia and myocardial infarction from alleles without obvious impact on LDLR levels or functions. We propose that systematic implementation of such and similar strategies will significantly advance our understanding of the protein-coding human genome and how rare and low frequency genetic variation impacts on health and disease.
Key words High-throughput functional profiling, Missense alleles, RNAi, Exome sequencing, LDLR, Rare-variant association studies, RVAS
1 Introduction
Since it has first been shown to reliably map protein-coding varia- tion across the entire human genome, sequencing of the exome, the ~1.5% of the human genome that encode for proteins, has inevitably transformed human genetics. Whole-exome sequencing (WES) has now become a routine tool to unravel and better under- stand the molecular basis of monogenetic diseases and it is increas- ingly being applied in clinical diagnostic settings [1]. Moreover, WES has further demonstrated its value when being applied to large clinical cohorts and extreme families where it has helped to associate multiple protein-coding low frequency and rare variants to complex human traits and diseases, thereby massively increasing the resolution of genome-wide association studies (GWAS) [2].
Daniel F. Gilbert and Oliver Friedrich (eds.), Cell Viability Assays: Methods and Protocols, Methods in Molecular Biology, vol. 1601, DOI 10.1007/978-1-4939-6960-9_17, © Springer Science+Business Media LLC 2017
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However, with WES being conducted in an ever-increasing num- ber of individuals and across all ethnicities, the overall number of human alleles identified through sequencing by far exceeds the number of variants that can reliably be linked to a distinct physio- logical function or human disease [3]. To a large degree this owes to the fact that methods that would allow to thoroughly distin- guish alleles that disrupt protein functions from the overwhelming number of alleles without obvious functional consequences are still in their infancies. This is particularly true for the missense variants as the largest and clinically most relevant group of human alleles [4]. Our inability to distinguish relevant from less relevant genetic variation poses a considerable bottleneck for contemporary human genetics.
We here review an experimental strategy that may help to par- tially address this problem and that is based on the systematic par- allelized testing of missense alleles for a biological consequence in cultured cells. We have applied this strategy to thoroughly charac- terize the impact of WES-identified rare and low frequency mis- sense alleles in the low-density lipoprotein receptor gene (LDLR) on LDLR functions in cells [5]. We further validated our in vitro findings through comparison with clinical parameters from >3000 individuals, specifically with plasma lipid levels and the incidence of myocardial infarction. Through merging our experimental with clinical data, we could massively increase the power of rare-variant association testing that had previously linked rare variation in LDLR to the risk of myocardial infarction [6].
Our experimental strategy includes two separate, but comple- mentary workflows that are high throughput, unbiased, and quan- titative. First, we use systematic overexpression of GFP-tagged cDNAs encoding human LDLR to compare the uptake of fluorescent- labeled LDL into cells expressing mutated LDLR-GFP relative to wild-type-LDLR. Second, the same experiments are conducted under a “complementation” setting where endogenous LDLR is knocked down with siRNA prior to overexpression. Then, it is tested by how much cells expressing the siRNA-resistant wild- type- LDLR or mutated LDLR-GFP are able to reconstitute LDLR function. Automated high-content automated microscopy joint with customized multiparametric computational image analysis routines allows to selectively quantify LDLR expression and LDL uptake from large numbers of GFP-positive and GFP-negative cells. Definition of distinct cellular phenotypes makes it possible to relate the tested genetic variants to the mechanisms by which LDLR function is impaired. When applying this strategy to large numbers of exome-identified rare missense alleles we could objec- tively distinguish disruptive missense alleles with a high likelihood to be relevant for disease from variants without obvious consequence on LDLR functions. This allowed us to independently validate Mendelian missense mutations that had previously been described Aenne S. Thormọhlen and Heiko Runz
as causing Familial Hypercholesterolemia (FH), but also to iden- tify variants previously described as of unclear significance as very probably causing FH. Importantly, carriers of LDLR missense alleles classified by our experimental strategy as disruptive on pro- tein functions showed significantly higher plasma LDL levels as well as a higher risk for early-onset myocardial infarction than car- riers of alleles classified as neutral. Our systematic in vitro variant profiling strategy has proven powerful to functionally characterize rare and low frequency missense alleles in LDLR and can be applied in a high-throughput manner to any other gene for which gene function can be monitored in cells.
2 Materials