Massively Parallel Genetics

Shendure, Jay; Fields, Stanley

doi:10.1534/genetics.115.180562

Cited by 25 publications

(28 citation statements)

References 18 publications

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“…A critical hurdle for the application of massively multiplexed functional assays is bridging the gap between molecular phenotype and human phenotype 66 . We found that fitness scores are able to discriminate between likely pathogenic and benign human alleles in both the germline and somatic condition.…”

Section: Discussionmentioning

confidence: 99%

A saturation mutagenesis approach to understanding PTEN lipid phosphatase activity and genotype-phenotypes relationships

Mighell

Evans-Dutson

O’Roak

2018

Preprint

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Phosphatase and tensin homolog (PTEN) is a tumor suppressor frequently mutated in diverse cancers. Germline PTEN mutations are also associated with a range of clinical outcomes, including PTEN hamartoma tumor syndrome (PHTS) and autism spectrum disorder (ASD). To empower new insights into PTEN function and clinically relevant genotype-phenotype relationships, we systematically evaluated the effect of PTEN mutations on lipid phosphatase activity in vivo. Using a massively parallel approach that leverages an artificial humanized yeast model, we derived high-confidence estimates of functional impact for 7,244 single amino acid PTEN variants (86% of possible). These data uncovered novel insights into PTEN protein structure, biochemistry, and mutation tolerance. Variant functional scores can reliably discriminate likely pathogenic from benign alleles. Further, 32% of ClinVar unclassified missense variants are phosphatase deficient in our assay, supporting their reclassification. ASD associated mutations generally had less severe fitness scores relative to PHTS associated mutations (p = 7.16x10 -5 ) and a higher fraction of hypomorphic mutations, arguing for continued genotype-phenotype studies in larger clinical datasets that can further leverage these rich functional data. MAIN TEXTRecent large-scale exome sequencing studies have highlighted the abundance of protein-coding variation in the human population 1 . It remains challenging to predict variant pathogenicity and clinical outcomes, especially for genes with pleiotropic effects. With most rare variants private to a single family or individual, using traditional approaches to establish pathogenicity such as variant segregation within a pedigree or identification in independent patients is infeasible. Even for well-studied genes, hundreds of variants are currently defined as variants of uncertain significance (VUS). Moreover, purely computational approaches still suffer from high false positive rates 2 and subjective interpretations that limit the clinical utility of these predictions. To address these challenges for genes of clinical importance, one proposed approach is to prospectively measure the functional effects of all possible mutations, allowing these empirical data to be integrated into the clinical assessment of novel rare variants 3,4 . Historically, these types of functional assays have been conducted in a serial nature, which limits scalability, and often only within a portion of the protein of interest. While there are some notable examples of whole-gene brute force saturation mutagenesis, e.g., TP535 , new more scalable experimental paradigms are being developed that allow the functional dissection of the effects of thousands of genetic mutations in parallel 6 . These approaches leverage recent advances in DNA synthesis and sequencing technologies and have proven particularly valuable in understanding the effects of mutations in cancer-associated genes 7,8 . With these issues in mind, we have developed a saturation mutagenesis approach to...

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Section: Discussionmentioning

confidence: 99%

A saturation mutagenesis approach to understanding PTEN lipid phosphatase activity and genotype-phenotypes relationships

Mighell

Evans-Dutson

O’Roak

2018

Preprint

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“…NGS can be used to sequence entire genomes (WGS), or a targeted panel of genes, ranging from a small number of genes (e.g. all genes known to cause PID, hereafter referred to as a gene panel) to the whole exome (WES)(7–10). The technical process of NGS is summarized in Figure 1 and the related vocabulary is explained in Table I.…”

Section: Generating Next Generation Sequencing Datamentioning

confidence: 99%

Exome and genome sequencing for inborn errors of immunity

Meyts

Bosch

Bolze

et al. 2016

Journal of Allergy and Clinical Immunology

162

148

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The advent of next generation sequencing (NGS) in 2010 has transformed medicine and particularly the growing field of monogenic inborn errors of immunity, including primary immunodeficiencies (PID). NGS has facilitated the discovery of novel disease-causing genes and the genetic diagnosis of patients with PID. Whole-exome sequencing (WES) is presently the most cost-effective approach for PID research and diagnostics, though whole genome sequencing (WGS) offers several advantages. The scientific or diagnostic challenge consists in selecting one or two candidate variants among thousands of NGS calls. Variant- and gene-level computational methods as well as immunological hypotheses can help to narrow down this genome-wide search. The key to success is a well-informed genetic hypothesis on three key aspects: mode of inheritance, clinical penetrance, and genetic heterogeneity of the condition. This determines the search strategy and the frequency cut-offs for candidate alleles. Subsequent functional validation of the disease-causing effect of the candidate variant is critical. Even the most up-to-date dry lab cannot clinch this validation without a seasoned wet lab. The multifariousness of variations entails an experimental rigor even greater than traditional Sanger sequencing-based approaches, in order not to assign PID to false positives. Finding the needle in the haystack takes patience, prudence, and discernment.

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“…In [31], this Monte Carlo approach is advocated as providing a more accurate estimate of model parameters than do Eqs. (4) and (5). In what follows, we use 'DT' to label matrix models inferred by dms tools using this Monte Carlo approach.…”

Section: Enrichment Ratio Inferencementioning

confidence: 99%

“…To test the utility of MPAthic in these contexts, we inferred matrix models using MPRA data from [8] and DMS data from [9]. [5] In [8], replicate MPRA experiments were performed on a synthetic cAMP responsive element (CRE). These experiments tested ∼ 2.7 × 10 4 microarray-synthesized CREs having randomly scattered substitution mutations (10% per nucleotide position) throughout an 87 bp region.…”

Section: Mpra and Dms Datamentioning

confidence: 99%

“…Fortunately, a variety of massively parallel assays (MPAs), which have been developed in recent years, * Correspondence: jkinney@cshl.edu 2 Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, 11375, Cold Spring Harbor, NY Full list of author information is available at the end of the article are providing new hope for deciphering quantitative sequence-function relationships. MPAs couple functional measurements to ultra-high-throughput DNA sequencing in ways that allow thousands to millions of sequences to be assayed in a single experiment; see [2,3,4,5,6] for reviews of these methods. Fig.…”

Section: Introductionmentioning

confidence: 99%

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MPAthic: Quantitative Modeling of Sequence-Function Relationships for massively parallel assays

Ireland

Kinney

2016

Preprint

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Massively parallel assays (MPAs) are being rapidly adopted for studying a wide range of DNA, RNA, and protein sequence-function relationships. However, the software available for quantitatively modeling these relationships is severely limited. Here we describe MPAthic, a software package that enables the rapid inference of such models from a variety of MPA datasets. Using both simulated and previously published data, we show that the modeling capabilities of MPAthic greatly improve on those of existing software. In particular, only MPAthic can accurately quantify the strength of epistatic interactions. These capabilities address a major need in the analysis of MPA data.

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Massively Parallel Genetics

Cited by 25 publications

References 18 publications

A saturation mutagenesis approach to understanding PTEN lipid phosphatase activity and genotype-phenotypes relationships

A saturation mutagenesis approach to understanding PTEN lipid phosphatase activity and genotype-phenotypes relationships

Exome and genome sequencing for inborn errors of immunity

MPAthic: Quantitative Modeling of Sequence-Function Relationships for massively parallel assays

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