Publications by authors named "Frederick P Roth"

140 Publications

Seeds of their own destruction: Dominant-negative peptide screening yields functional insight and therapeutic leads.

Cell Syst 2021 Jul;12(7):691-693

Donnelly Centre and Departments of Molecular Genetics and Computer Science, University of Toronto and Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada. Electronic address:

Systematic, high-throughput screening for "dominant-negative" protein fragments is an emerging method for mapping functional regions of the parental protein in vivo. In this issue of Cell Systems, Ford et al. apply this approach to 65 cancer drivers, providing functional insights and demonstrating therapeutic potential for several dominant-negative peptides.
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http://dx.doi.org/10.1016/j.cels.2021.06.003DOI Listing
July 2021

Shifting landscapes of human MTHFR missense-variant effects.

Am J Hum Genet 2021 07;108(7):1283-1300

Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON M5G 1X5, Canada; The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada; Department of Computer Science, University of Toronto, Toronto, ON M5S 2E4, Canada. Electronic address:

Most rare clinical missense variants cannot currently be classified as pathogenic or benign. Deficiency in human 5,10-methylenetetrahydrofolate reductase (MTHFR), the most common inherited disorder of folate metabolism, is caused primarily by rare missense variants. Further complicating variant interpretation, variant impacts often depend on environment. An important example of this phenomenon is the MTHFR variant p.Ala222Val (c.665C>T), which is carried by half of all humans and has a phenotypic impact that depends on dietary folate. Here we describe the results of 98,336 variant functional-impact assays, covering nearly all possible MTHFR amino acid substitutions in four folinate environments, each in the presence and absence of p.Ala222Val. The resulting atlas of MTHFR variant effects reveals many complex dependencies on both folinate and p.Ala222Val. MTHFR atlas scores can distinguish pathogenic from benign variants and, among individuals with severe MTHFR deficiency, correlate with age of disease onset. Providing a powerful tool for understanding structure-function relationships, the atlas suggests a role for a disordered loop in retaining cofactor at the active site and identifies variants that enable escape of inhibition by S-adenosylmethionine. Thus, a model based on eight MTHFR variant effect maps illustrates how shifting landscapes of environment- and genetic-background-dependent missense variation can inform our clinical, structural, and functional understanding of MTHFR deficiency.
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http://dx.doi.org/10.1016/j.ajhg.2021.05.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322931PMC
July 2021

MaveRegistry: a collaboration platform for multiplexed assays of variant effect.

Bioinformatics 2021 Mar 27. Epub 2021 Mar 27.

Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada.

Summary: Multiplexed assays of variant effect (MAVEs) are capable of experimentally testing all possible single nucleotide or amino acid variants in selected genomic regions, generating 'variant effect maps', which provide biochemical insight and functional evidence to enable more rapid and accurate clinical interpretation of human variation. Because the international community applying MAVE approaches is growing rapidly, we developed the online MaveRegistry platform to catalyze collaboration, reduce redundant efforts, allow stakeholders to nominate targets, and enable tracking and sharing of progress on ongoing MAVE projects.

Availability And Implementation: MaveRegistry service: https://registry.varianteffect.org. MaveRegistry source code: https://github.com/kvnkuang/maveregistry-front-end.

Supplementary Information: no Supplementary data.
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http://dx.doi.org/10.1093/bioinformatics/btab215DOI Listing
March 2021

Prioritizing genes for systematic variant effect mapping.

Bioinformatics 2021 04;36(22-23):5448-5455

Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada.

Motivation: When rare missense variants are clinically interpreted as to their pathogenicity, most are classified as variants of uncertain significance (VUS). Although functional assays can provide strong evidence for variant classification, such results are generally unavailable. Multiplexed assays of variant effect can generate experimental 'variant effect maps' that score nearly all possible missense variants in selected protein targets for their impact on protein function. However, these efforts have not always prioritized proteins for which variant effect maps would have the greatest impact on clinical variant interpretation.

Results: Here, we mined databases of clinically interpreted variants and applied three strategies, each building on the previous, to prioritize genes for systematic functional testing of missense variation. The strategies ranked genes (i) by the number of unique missense VUS that had been reported to ClinVar; (ii) by movability- and reappearance-weighted impact scores, to give extra weight to reappearing, movable VUS and (iii) by difficulty-adjusted impact scores, to account for the more resource-intensive nature of generating variant effect maps for longer genes. Our results could be used to guide systematic functional testing of missense variation toward greater impact on clinical variant interpretation.

Availability And Implementation: Source code available at: https://github.com/rothlab/mave-gene-prioritization.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btaa1008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8016487PMC
April 2021

Interrogation of kinase genetic interactions provides a global view of PAK1-mediated signal transduction pathways.

J Biol Chem 2020 12 15;295(50):16906-16919. Epub 2020 Oct 15.

Department of Pharmacology, Brain Science and Engineering Institute, and Department of Biomedical Sciences, BK21 Plus KNU Biomedical Convergence Program, School of Medicine, Kyungpook National University, Daegu, South Korea. Electronic address:

Kinases are critical components of intracellular signaling pathways and have been extensively investigated with regard to their roles in cancer. p21-activated kinase-1 (PAK1) is a serine/threonine kinase that has been previously implicated in numerous biological processes, such as cell migration, cell cycle progression, cell motility, invasion, and angiogenesis, in glioma and other cancers. However, the signaling network linked to PAK1 is not fully defined. We previously reported a large-scale yeast genetic interaction screen using toxicity as a readout to identify candidate genetic interactions. transformation of the gene into 4,653 homozygous diploid yeast deletion mutants identified ∼400 candidates that suppressed yeast toxicity. Here we selected 19 candidate genetic interactions that had human orthologs and were expressed in glioma for further examination in mammalian cells, brain slice cultures, and orthotopic glioma models. RNAi and pharmacological inhibition of potential interactors confirmed that , , , , , , and regulate PAK1-induced cell migration and revealed the importance of genes related to the mitotic spindle, proteolysis, autophagy, and metabolism in PAK1-mediated glioma cell migration, drug resistance, and proliferation. AKT1 was further identified as a downstream mediator of the - genetic interaction. Taken together, these data provide a global view of PAK1-mediated signal transduction pathways and point to potential new drug targets for glioma therapy.
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http://dx.doi.org/10.1074/jbc.RA120.014831DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7863907PMC
December 2020

Systematic analysis of bypass suppression of essential genes.

Mol Syst Biol 2020 09;16(9):e9828

Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.

Essential genes tend to be highly conserved across eukaryotes, but, in some cases, their critical roles can be bypassed through genetic rewiring. From a systematic analysis of 728 different essential yeast genes, we discovered that 124 (17%) were dispensable essential genes. Through whole-genome sequencing and detailed genetic analysis, we investigated the genetic interactions and genome alterations underlying bypass suppression. Dispensable essential genes often had paralogs, were enriched for genes encoding membrane-associated proteins, and were depleted for members of protein complexes. Functionally related genes frequently drove the bypass suppression interactions. These gene properties were predictive of essential gene dispensability and of specific suppressors among hundreds of genes on aneuploid chromosomes. Our findings identify yeast's core essential gene set and reveal that the properties of dispensable essential genes are conserved from yeast to human cells, correlating with human genes that display cell line-specific essentiality in the Cancer Dependency Map (DepMap) project.
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http://dx.doi.org/10.15252/msb.20209828DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7507402PMC
September 2020

Multiplexed measurement of variant abundance and activity reveals VKOR topology, active site and human variant impact.

Elife 2020 09 1;9. Epub 2020 Sep 1.

Department of Genome Sciences, University of Washington, Seattle, United States.

Vitamin K epoxide reductase (VKOR) drives the vitamin K cycle, activating vitamin K-dependent blood clotting factors. VKOR is also the target of the widely used anticoagulant drug, warfarin. Despite VKOR's pivotal role in coagulation, its structure and active site remain poorly understood. In addition, VKOR variants can cause vitamin K-dependent clotting factor deficiency or alter warfarin response. Here, we used multiplexed, sequencing-based assays to measure the effects of 2,695 VKOR missense variants on abundance and 697 variants on activity in cultured human cells. The large-scale functional data, along with an evolutionary coupling analysis, supports a four transmembrane domain topology, with variants in transmembrane domains exhibiting strongly deleterious effects on abundance and activity. Functionally constrained regions of the protein define the active site, and we find that, of four conserved cysteines putatively critical for function, only three are absolutely required. Finally, 25% of human VKOR missense variants show reduced abundance or activity, possibly conferring warfarin sensitivity or causing disease.
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http://dx.doi.org/10.7554/eLife.58026DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462613PMC
September 2020

A Comprehensive, Flexible Collection of SARS-CoV-2 Coding Regions.

G3 (Bethesda) 2020 09 2;10(9):3399-3402. Epub 2020 Sep 2.

Donnelly Centre, University of Toronto, Toronto, Ontario, Canada

The world is facing a global pandemic of COVID-19 caused by the SARS-CoV-2 coronavirus. Here we describe a collection of codon-optimized coding sequences for SARS-CoV-2 cloned into Gateway-compatible entry vectors, which enable rapid transfer into a variety of expression and tagging vectors. The collection is freely available. We hope that widespread availability of this SARS-CoV-2 resource will enable many subsequent molecular studies to better understand the viral life cycle and how to block it.
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http://dx.doi.org/10.1534/g3.120.401554DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7467003PMC
September 2020

Yeast-Based Genetic Interaction Analysis of Human Kinome.

Cells 2020 05 7;9(5). Epub 2020 May 7.

Department of Pharmacology, Brain Science and Engineering Institute, and Department of Biomedical Sciences, BK21 Plus KNU Biomedical Convergence Program, School of Medicine, Kyungpook National University, Daegu 41944, Korea.

Kinases are critical intracellular signaling proteins. To better understand kinase-mediated signal transduction, a large-scale human-yeast genetic interaction screen was performed. Among 597 human kinase genes tested, 28 displayed strong toxicity in yeast when overexpressed. transformation of these toxic kinase genes into 4653 homozygous diploid yeast deletion mutants followed by barcode sequencing identified yeast toxicity modifiers and thus their human orthologs. Subsequent network analyses and functional grouping revealed that the 28 kinases and their 676 interaction partners (corresponding to a total of 969 genetic interactions) are enriched in cell death and survival (34%), small-molecule biochemistry (18%) and molecular transport (11%), among others. In the subnetwork analyses, a few kinases were commonly associated with glioma, cell migration and cell death/survival. Our analysis enabled the creation of a first draft of the kinase genetic interactome network and identified multiple drug targets for inflammatory diseases and cancer, in which deregulated kinase signaling plays a pathogenic role.
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http://dx.doi.org/10.3390/cells9051156DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7291280PMC
May 2020

A reference map of the human binary protein interactome.

Nature 2020 04 8;580(7803):402-408. Epub 2020 Apr 8.

Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Boston, MA, USA.

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships. Here we present a human 'all-by-all' reference interactome map of human binary protein interactions, or 'HuRI'. With approximately 53,000 protein-protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome, transcriptome and proteome data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein-protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes.
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http://dx.doi.org/10.1038/s41586-020-2188-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7169983PMC
April 2020

MaveQuest: a web resource for planning experimental tests of human variant effects.

Bioinformatics 2020 06;36(12):3938-3940

Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada.

Summary: Fully realizing the promise of personalized medicine will require rapid and accurate classification of pathogenic human variation. Multiplexed assays of variant effect (MAVEs) can experimentally test nearly all possible variants in selected gene targets. Planning a MAVE study involves identifying target genes with clinical impact, and identifying scalable functional assays for that target. Here, we describe MaveQuest, a web-based resource enabling systematic variant effect mapping studies by identifying potential functional assays, disease phenotypes and clinical relevance for nearly all human protein-coding genes.

Availability And Implementation: MaveQuest service: https://mavequest.varianteffect.org/. MaveQuest source code: https://github.com/kvnkuang/mavequest-front-end/.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btaa228DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320626PMC
June 2020

Systems analysis of RhoGEF and RhoGAP regulatory proteins reveals spatially organized RAC1 signalling from integrin adhesions.

Nat Cell Biol 2020 04 23;22(4):498-511. Epub 2020 Mar 23.

Institute of Cancer Research, Chester Beatty Laboratories, London, UK.

Rho GTPases are central regulators of the cytoskeleton and, in humans, are controlled by 145 multidomain guanine nucleotide exchange factors (RhoGEFs) and GTPase-activating proteins (RhoGAPs). How Rho signalling patterns are established in dynamic cell spaces to control cellular morphogenesis is unclear. Through a family-wide characterization of substrate specificities, interactomes and localization, we reveal at the systems level how RhoGEFs and RhoGAPs contextualize and spatiotemporally control Rho signalling. These proteins are widely autoinhibited to allow local regulation, form complexes to jointly coordinate their networks and provide positional information for signalling. RhoGAPs are more promiscuous than RhoGEFs to confine Rho activity gradients. Our resource enabled us to uncover a multi-RhoGEF complex downstream of G-protein-coupled receptors controlling CDC42-RHOA crosstalk. Moreover, we show that integrin adhesions spatially segregate GEFs and GAPs to shape RAC1 activity zones in response to mechanical cues. This mechanism controls the protrusion and contraction dynamics fundamental to cell motility. Our systems analysis of Rho regulators is key to revealing emergent organization principles of Rho signalling.
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http://dx.doi.org/10.1038/s41556-020-0488-xDOI Listing
April 2020

A proactive genotype-to-patient-phenotype map for cystathionine beta-synthase.

Genome Med 2020 01 30;12(1):13. Epub 2020 Jan 30.

The Donnelly Centre, University of Toronto, Toronto, ON, M5S 3E1, Canada.

Background: For the majority of rare clinical missense variants, pathogenicity status cannot currently be classified. Classical homocystinuria, characterized by elevated homocysteine in plasma and urine, is caused by variants in the cystathionine beta-synthase (CBS) gene, most of which are rare. With early detection, existing therapies are highly effective.

Methods: Damaging CBS variants can be detected based on their failure to restore growth in yeast cells lacking the yeast ortholog CYS4. This assay has only been applied reactively, after first observing a variant in patients. Using saturation codon-mutagenesis, en masse growth selection, and sequencing, we generated a comprehensive, proactive map of CBS missense variant function.

Results: Our CBS variant effect map far exceeds the performance of computational predictors of disease variants. Map scores correlated strongly with both disease severity (Spearman's ϱ = 0.9) and human clinical response to vitamin B (ϱ = 0.93).

Conclusions: We demonstrate that highly multiplexed cell-based assays can yield proactive maps of variant function and patient response to therapy, even for rare variants not previously seen in the clinic.
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http://dx.doi.org/10.1186/s13073-020-0711-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6993387PMC
January 2020

MaveDB: an open-source platform to distribute and interpret data from multiplexed assays of variant effect.

Genome Biol 2019 11 4;20(1):223. Epub 2019 Nov 4.

Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.

Multiplex assays of variant effect (MAVEs), such as deep mutational scans and massively parallel reporter assays, test thousands of sequence variants in a single experiment. Despite the importance of MAVE data for basic and clinical research, there is no standard resource for their discovery and distribution. Here, we present MaveDB ( https://www.mavedb.org ), a public repository for large-scale measurements of sequence variant impact, designed for interoperability with applications to interpret these datasets. We also describe the first such application, MaveVis, which retrieves, visualizes, and contextualizes variant effect maps. Together, the database and applications will empower the community to mine these powerful datasets.
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http://dx.doi.org/10.1186/s13059-019-1845-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6827219PMC
November 2019

Highly Combinatorial Genetic Interaction Analysis Reveals a Multi-Drug Transporter Influence Network.

Cell Syst 2020 01 23;10(1):25-38.e10. Epub 2019 Oct 23.

Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada; Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON M5G 1X5, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; Department of Computer Science, University of Toronto, Toronto, ON M5T 3A1, Canada; Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, USA. Electronic address:

Many traits are complex, depending non-additively on variant combinations. Even in model systems, such as the yeast S. cerevisiae, carrying out the high-order variant-combination testing needed to dissect complex traits remains a daunting challenge. Here, we describe "X-gene" genetic analysis (XGA), a strategy for engineering and profiling highly combinatorial gene perturbations. We demonstrate XGA on yeast ABC transporters by engineering 5,353 strains, each deleted for a random subset of 16 transporters, and profiling each strain's resistance to 16 compounds. XGA yielded 85,648 genotype-to-resistance observations, revealing high-order genetic interactions for 13 of the 16 transporters studied. Neural networks yielded intuitive functional models and guided exploration of fluconazole resistance, which was influenced non-additively by five genes. Together, our results showed that highly combinatorial genetic perturbation can functionally dissect complex traits, supporting pursuit of analogous strategies in human cells and other model systems.
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http://dx.doi.org/10.1016/j.cels.2019.09.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6989212PMC
January 2020

Quantifying immune-based counterselection of somatic mutations.

PLoS Genet 2019 07 25;15(7):e1008227. Epub 2019 Jul 25.

Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.

Somatic mutations in protein-coding regions can generate 'neoantigens' causing developing cancers to be eliminated by the immune system. Quantitative estimates of the strength of this counterselection phenomenon have been lacking. We quantified the extent to which somatic mutations are depleted in peptides that are predicted to be displayed by major histocompatibility complex (MHC) class I proteins. The extent of this depletion depended on expression level of the neoantigenic gene, and on whether the patient had one or two MHC-encoding alleles that can display the peptide, suggesting MHC-encoding alleles are incompletely dominant. This study provides an initial quantitative understanding of counter-selection of identifiable subclasses of neoantigenic somatic variation.
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http://dx.doi.org/10.1371/journal.pgen.1008227DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6657826PMC
July 2019

Assessing predictions on fitness effects of missense variants in calmodulin.

Hum Mutat 2019 09 3;40(9):1463-1473. Epub 2019 Sep 3.

Departments of Biophysics and Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas.

This paper reports the evaluation of predictions for the "CALM1" challenge in the fifth round of the Critical Assessment of Genome Interpretation held in 2018. In the challenge, the participants were asked to predict effects on yeast growth caused by missense variants of human calmodulin, a highly conserved protein in eukaryotic cells sensing calcium concentration. The performance of predictors implementing different algorithms and methods is similar. Most predictors are able to identify the deleterious or tolerated variants with modest accuracy, with a baseline predictor based purely on sequence conservation slightly outperforming the submitted predictions. Nevertheless, we think that the accuracy of predictions remains far from satisfactory, and the field awaits substantial improvements. The most poorly predicted variants in this round surround functional CALM1 sites that bind calcium or peptide, which suggests that better incorporation of structural analysis may help improve predictions.
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http://dx.doi.org/10.1002/humu.23857DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6744288PMC
September 2019

Characterizing ABC-Transporter Substrate-Likeness Using a Clean-Slate Genetic Background.

Front Pharmacol 2019 25;10:448. Epub 2019 Apr 25.

Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, United States.

Mutations in ATP Binding Cassette (ABC)-transporter genes can have major effects on the bioavailability and toxicity of the drugs that are ABC-transporter substrates. Consequently, methods to predict if a drug is an ABC-transporter substrate are useful for drug development. Such methods traditionally relied on literature curated collections of ABC-transporter dependent membrane transfer assays. Here, we used a single large-scale dataset of 376 drugs with relative efficacy on an engineered yeast strain with all ABC-transporter genes deleted (ABC-16), to explore the relationship between a drug's chemical structure and ABC-transporter substrate-likeness. We represented a drug's chemical structure by an array of substructure keys and explored several machine learning methods to predict the drug's efficacy in an ABC-16 yeast strain. Gradient-Boosted Random Forest models outperformed all other methods with an AUC of 0.723. We prospectively validated the model using new experimental data and found significant agreement with predictions. Our analysis expands the previously reported chemical substructures associated with ABC-transporter substrates and provides an alternative means to investigate ABC-transporter substrate-likeness.
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http://dx.doi.org/10.3389/fphar.2019.00448DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6494965PMC
April 2019

or human iPSC-derived neurons from individuals with autism develop hyperactive neuronal networks.

Elife 2019 02 12;8. Epub 2019 Feb 12.

Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, Canada.

Induced pluripotent stem cell (iPSC)-derived neurons are increasingly used to model Autism Spectrum Disorder (ASD), which is clinically and genetically heterogeneous. To study the complex relationship of penetrant and weaker polygenic risk variants to ASD, 'isogenic' iPSC-derived neurons are critical. We developed a set of procedures to control for heterogeneity in reprogramming and differentiation, and generated 53 different iPSC-derived glutamatergic neuronal lines from 25 participants from 12 unrelated families with ASD. Heterozygous de novo and rare-inherited presumed-damaging variants were characterized in ASD risk genes/loci. Combinations of putative etiologic variants ( or ) in separate families were modeled. We used a multi-electrode array, with patch-clamp recordings, to determine a reproducible synaptic phenotype in 25% of the individuals with ASD (other relevant data on the remaining lines was collected). Our most compelling new results revealed a consistent spontaneous network hyperactivity in neurons deficient for or The biobank of iPSC-derived neurons and accompanying genomic data are available to accelerate ASD research.

Editorial Note: This article has been through an editorial process in which authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
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http://dx.doi.org/10.7554/eLife.40092DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6372285PMC
February 2019

A web application and service for imputing and visualizing missense variant effect maps.

Bioinformatics 2019 09;35(17):3191-3193

Donnelly Centre, University of Toronto, Toronto, ON, Canada.

Summary: The promise of personalized genomic medicine depends on our ability to assess the functional impact of rare sequence variation. Multiplexed assays can experimentally measure the functional impact of missense variants on a massive scale. However, even after such assays, many missense variants remain poorly measured. Here we describe a software pipeline and application to impute missing information in experimentally determined variant effect maps.

Availability And Implementation: http://impute.varianteffect.org source code: https://github.com/joewuca/imputation.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btz012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6735881PMC
September 2019

Modeling the impact of drug interactions on therapeutic selectivity.

Nat Commun 2018 08 27;9(1):3452. Epub 2018 Aug 27.

Faculty of Engineering and Natural Sciences, Sabanci University, 34956, Istanbul, Turkey.

Combination therapies that produce synergistic growth inhibition are widely sought after for the pharmacotherapy of many pathological conditions. Therapeutic selectivity, however, depends on the difference between potency on disease-causing cells and potency on non-target cell types that cause toxic side effects. Here, we examine a model system of antimicrobial compound combinations applied to two highly diverged yeast species. We find that even though the drug interactions correlate between the two species, cell-type-specific differences in drug interactions are common and can dramatically alter the selectivity of compounds when applied in combination vs. single-drug activity-enhancing, diminishing, or inverting therapeutic windows. This study identifies drug combinations with enhanced cell-type-selectivity with a range of interaction types, which we experimentally validate using multiplexed drug-interaction assays for heterogeneous cell cultures. This analysis presents a model framework for evaluating drug combinations with increased efficacy and selectivity against pathogens or tumors.
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http://dx.doi.org/10.1038/s41467-018-05954-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6110842PMC
August 2018

Multiplexed assays of variant effects contribute to a growing genotype-phenotype atlas.

Hum Genet 2018 Sep 2;137(9):665-678. Epub 2018 Aug 2.

The Donnelly Centre, University of Toronto, Toronto, ON, Canada.

Given the constantly improving cost and speed of genome sequencing, it is reasonable to expect that personal genomes will soon be known for many millions of humans. This stands in stark contrast with our limited ability to interpret the sequence variants which we find. Although it is, perhaps, easiest to interpret variants in coding regions, knowledge of functional impact is unknown for the vast majority of missense variants. While many computational approaches can predict the impact of coding variants, they are given a little weight in the current guidelines for interpreting clinical variants. Laboratory assays produce comparatively more trustworthy results, but until recently did not scale to the space of all possible mutations. The development of deep mutational scanning and other multiplexed assays of variant effect has now brought feasibility of this endeavour within view. Here, we review progress in this field over the last decade, break down the different approaches into their components, and compare methodological differences.
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http://dx.doi.org/10.1007/s00439-018-1916-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6153521PMC
September 2018

The Impact of Oncogenic EGFRvIII on the Proteome of Extracellular Vesicles Released from Glioblastoma Cells.

Mol Cell Proteomics 2018 10 13;17(10):1948-1964. Epub 2018 Jul 13.

From the ‡Research Institute of the McGill University Health Centre, Glen Site, McGill University, Montreal, Quebec, H4A 3J1, Canada;

Glioblastoma multiforme (GBM) is a highly aggressive and heterogeneous form of primary brain tumors, driven by a complex repertoire of oncogenic alterations, including the constitutively active epidermal growth factor receptor (EGFRvIII). EGFRvIII impacts both cell-intrinsic and non-cell autonomous aspects of GBM progression, including cell invasion, angiogenesis and modulation of the tumor microenvironment. This is, at least in part, attributable to the release and intercellular trafficking of extracellular vesicles (EVs), heterogeneous membrane structures containing multiple bioactive macromolecules. Here we analyzed the impact of EGFRvIII on the profile of glioma EVs using isogenic tumor cell lines, in which this oncogene exhibits a strong transforming activity. We observed that EGFRvIII expression alters the expression of EV-regulating genes (vesiculome) and EV properties, including their protein composition. Using mass spectrometry, quantitative proteomic analysis and Gene Ontology terms filters, we observed that EVs released by EGFRvIII-transformed cells were enriched for extracellular exosome and focal adhesion related proteins. Among them, we validated the association of pro-invasive proteins (CD44, BSG, CD151) with EVs of EGFRvIII expressing glioma cells, and downregulation of exosomal markers (CD81 and CD82) relative to EVs of EGFRvIII-negative cells. Nano-flow cytometry revealed that the EV output from individual glioma cell lines was highly heterogeneous, such that only a fraction of vesicles contained specific proteins (including EGFRvIII). Notably, cells expressing EGFRvIII released EVs double positive for CD44/BSG, and these proteins also colocalized in cellular filopodia. We also detected the expression of homophilic adhesion molecules and increased homologous EV uptake by EGFRvIII-positive glioma cells. These results suggest that oncogenic EGFRvIII reprograms the proteome and uptake of GBM-related EVs, a notion with considerable implications for their biological activity and properties relevant for the development of EV-based cancer biomarkers.
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http://dx.doi.org/10.1074/mcp.RA118.000644DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6166673PMC
October 2018

Mapping DNA damage-dependent genetic interactions in yeast via party mating and barcode fusion genetics.

Mol Syst Biol 2018 05 28;14(5):e7985. Epub 2018 May 28.

Donnelly Centre, University of Toronto, Toronto, ON, Canada

Condition-dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State-of-the-art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double-mutant strains, does not scale readily to multi-condition studies. Here, we describe barcode fusion genetics to map genetic interactions (BFG-GI), by which double-mutant strains generated via "party" mating can also be monitored for growth to detect genetic interactions. By using site-specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG-GI enables multiplexed quantitative tracking of double mutants via next-generation sequencing. We applied BFG-GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4-nitroquinoline 1-oxide (4NQO), bleomycin, zeocin, and three other DNA-damaging environments. BFG-GI recapitulated known genetic interactions and yielded new condition-dependent genetic interactions. We validated and further explored a subnetwork of condition-dependent genetic interactions involving , and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to an increase in the activation of the checkpoint protein kinase Rad53.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5974512PMC
http://dx.doi.org/10.15252/msb.20177985DOI Listing
May 2018

A framework for exhaustively mapping functional missense variants.

Mol Syst Biol 2017 12 21;13(12):957. Epub 2017 Dec 21.

Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada

Although we now routinely sequence human genomes, we can confidently identify only a fraction of the sequence variants that have a functional impact. Here, we developed a deep mutational scanning framework that produces exhaustive maps for human missense variants by combining random codon mutagenesis and multiplexed functional variation assays with computational imputation and refinement. We applied this framework to four proteins corresponding to six human genes: UBE2I (encoding SUMO E2 conjugase), SUMO1 (small ubiquitin-like modifier), TPK1 (thiamin pyrophosphokinase), and CALM1/2/3 (three genes encoding the protein calmodulin). The resulting maps recapitulate known protein features and confidently identify pathogenic variation. Assays potentially amenable to deep mutational scanning are already available for 57% of human disease genes, suggesting that DMS could ultimately map functional variation for all human disease genes.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5740498PMC
http://dx.doi.org/10.15252/msb.20177908DOI Listing
December 2017

CRISPR/Cas9 System as a Valuable Genome Editing Tool for Wine Yeasts with Application to Decrease Urea Production.

Front Microbiol 2017 9;8:2194. Epub 2017 Nov 9.

Donnelly Centre, University of Toronto, Toronto, ON, Canada.

An extensive repertoire of molecular tools is available for genetic analysis in laboratory strains of . Although this has widely contributed to the interpretation of gene functionality within haploid laboratory isolates, the genetics of metabolism in commercially-relevant polyploid yeast strains is still poorly understood. Genetic engineering in industrial yeasts is undergoing major changes due to Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and CRISPR-associated protein (Cas) engineering approaches. Here we apply the CRISPR/Cas9 system to two commercial "starter" strains of (EC1118, AWRI796), eliminating the arginine permease pathway to generate strains with reduced urea production (18.5 and 35.5% for EC1118 and AWRI796, respectively). In a wine-model environment based on two grape musts obtained from Chardonnay and Cabernet Sauvignon cultivars, both starter strains and mutants completed the must fermentation in 8-12 days. However, recombinant strains carrying the mutation failed to produce urea, suggesting that the genetic modification successfully impaired the arginine metabolism. In conclusion, the reduction of urea production in a wine-model environment confirms that the CRISPR/Cas9 system has been successfully established in wine yeasts.
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http://dx.doi.org/10.3389/fmicb.2017.02194DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5678006PMC
November 2017

Variant Interpretation: Functional Assays to the Rescue.

Am J Hum Genet 2017 Sep;101(3):315-325

Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA; Department of Bioengineering, University of Washington, Seattle, WA 98195, USA. Electronic address:

Classical genetic approaches for interpreting variants, such as case-control or co-segregation studies, require finding many individuals with each variant. Because the overwhelming majority of variants are present in only a few living humans, this strategy has clear limits. Fully realizing the clinical potential of genetics requires that we accurately infer pathogenicity even for rare or private variation. Many computational approaches to predicting variant effects have been developed, but they can identify only a small fraction of pathogenic variants with the high confidence that is required in the clinic. Experimentally measuring a variant's functional consequences can provide clearer guidance, but individual assays performed only after the discovery of the variant are both time and resource intensive. Here, we discuss how multiplex assays of variant effect (MAVEs) can be used to measure the functional consequences of all possible variants in disease-relevant loci for a variety of molecular and cellular phenotypes. The resulting large-scale functional data can be combined with machine learning and clinical knowledge for the development of "lookup tables" of accurate pathogenicity predictions. A coordinated effort to produce, analyze, and disseminate large-scale functional data generated by multiplex assays could be essential to addressing the variant-interpretation crisis.
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http://dx.doi.org/10.1016/j.ajhg.2017.07.014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5590843PMC
September 2017

Assessing predictions of fitness effects of missense mutations in SUMO-conjugating enzyme UBE2I.

Hum Mutat 2017 09;38(9):1051-1063

Departments of Biophysics and Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas.

The exponential growth of genomic variants uncovered by next-generation sequencing necessitates efficient and accurate computational analyses to predict their functional effects. A number of computational methods have been developed for the task, but few unbiased comparisons of their performance are available. To fill the gap, The Critical Assessment of Genome Interpretation (CAGI) comprehensively assesses phenotypic predictions on newly collected experimental datasets. Here, we present the results of the SUMO conjugase challenge where participants were predicting functional effects of missense mutations in human SUMO-conjugating enzyme UBE2I. The performance of the predictors is similar to each other and is far from perfection. Evolutionary information from sequence alignments dominates the success: deleterious mutations at conserved positions and benign mutations at variable positions are accurately predicted. Prediction accuracy of other mutations remains unsatisfactory, and this fast-growing field of research is yet to learn the use of spatial structure information to improve the predictions significantly.
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http://dx.doi.org/10.1002/humu.23293DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5746193PMC
September 2017

Quantitative analysis of protein interaction network dynamics in yeast.

Mol Syst Biol 2017 07 13;13(7):934. Epub 2017 Jul 13.

Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA

Many cellular functions are mediated by protein-protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment-dependent protein complex dynamics, we used a DNA-barcode-based multiplexed protein interaction assay in to measure abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that "concerted" protein-centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass-action-based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5527849PMC
http://dx.doi.org/10.15252/msb.20177532DOI Listing
July 2017

Yeast genetic interaction screen of human genes associated with amyotrophic lateral sclerosis: identification of MAP2K5 kinase as a potential drug target.

Genome Res 2017 09 8;27(9):1487-1500. Epub 2017 Jun 8.

Department of Pharmacology, Brain Science and Engineering Institute, and Department of Biomedical Sciences, BK21 Plus KNU Biomedical Convergence Program, Kyungpook National University School of Medicine, Daegu, 41944, Korea.

To understand disease mechanisms, a large-scale analysis of human-yeast genetic interactions was performed. Of 1305 human disease genes assayed, 20 genes exhibited strong toxicity in yeast. Human-yeast genetic interactions were identified by en masse transformation of the human disease genes into a pool of 4653 homozygous diploid yeast deletion mutants with unique barcode sequences, followed by multiplexed barcode sequencing to identify yeast toxicity modifiers. Subsequent network analyses focusing on amyotrophic lateral sclerosis (ALS)-associated genes, such as optineurin () and angiogenin (), showed that the human orthologs of the yeast toxicity modifiers of these ALS genes are enriched for several biological processes, such as cell death, lipid metabolism, and molecular transport. When yeast genetic interaction partners held in common between human OPTN and ANG were validated in mammalian cells and zebrafish, MAP2K5 kinase emerged as a potential drug target for ALS therapy. The toxicity modifiers identified in this study may deepen our understanding of the pathogenic mechanisms of ALS and other devastating diseases.
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http://dx.doi.org/10.1101/gr.211649.116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5580709PMC
September 2017
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