61 research outputs found
The landscape of tolerated genetic variation in humans and primates
No full textPersonalized genome sequencing has revealed millions of genetic differences between individuals, but our understanding of their clinical relevance remains largely incomplete. To systematically decipher the effects of human genetic variants, we obtained whole-genome sequencing data for 809 individuals from 233 primate species and identified 4.3 million common protein-altering variants with orthologs in humans. We show that these variants can be inferred to have nondeleterious effects in humans based on their presence at high allele frequencies in other primate populations. We use this resource to classify 6% of all possible human protein-altering variants as likely benign and impute the pathogenicity of the remaining 94% of variants with deep learning, achieving state-of-the-art accuracy for diagnosing pathogenic variants in patients with genetic diseases.INTRODUCTION Millions of people have received genome and exome sequencing to date, a collective effort that has illuminated for the first time the vast catalog of small genetic differences that distinguish us as individuals within our species. However, the effects of most of these genetic variants remain unknown, limiting their clinical utility and actionability. New approaches that can accurately discern disease-causing from benign mutations and interpret genetic variants on a genome-wide scale would constitute a meaningful initial step towards realizing the potential of personalized genomic medicine. RATIONALE As a result of the short evolutionary distance between humans and nonhuman primates, our proteins share near-perfect amino acid sequence identity. Hence, the effects of a protein-altering mutation found in one species are likely to be concordant in the other species. By systematically cataloging common variants of nonhuman primates, we aimed to annotate these variants as being unlikely to cause human disease as they are tolerated by natural selection in a closely related species. Once collected, the resulting resource may be applied to infer the effects of unobserved variants across the genome using machine learning. RESULTS Following the strategy outlined above we obtained whole-genome sequencing data for 809 individuals from 233 primate species and cataloged 4.3 million common missense variants. We confirmed that human missense variants seen in at least one nonhuman primate species were annotated as benign in the ClinVar clinical variant database in 99% of cases. By contrast, common variants from mammals and vertebrates outside the primate lineage were substantially less likely to be benign in the ClinVar database (71 to 87% benign), restricting this strategy to nonhuman primates. Overall, we reclassified more than 4 million human missense variants of previously unknown consequence as likely benign, resulting in a greater than 50-fold increase in the number of annotated missense variants compared to existing clinical databases. To infer the pathogenicity of the remaining missense variants in the human genome, we constructed PrimateAI-3D, a semisupervised 3D-convolutional neural network that operates on voxelized protein structures. We trained PrimateAI-3D to separate common primate variants from matched control variants in 3D space as a semisupervised learning task. We evaluated the trained PrimateAI-3D model alongside 15 other published machine learning methods on their ability to distinguish between benign and pathogenic variants in six different clinical benchmarks and demonstrated that PrimateAI-3D outperformed all other classifiers in each of the tasks. CONCLUSION Our study addresses one of the key challenges in the variant interpretation field, namely, the lack of sufficient labeled data to effectively train large machine learning models. By generating the most comprehensive primate sequencing dataset to date and pairing this resource with a deep learning architecture that leverages 3D protein structures, we were able to achieve meaningful improvements in variant effect prediction across multiple clinical benchmarks. PrimateAI-3D, a deep learning model trained on millions of benign primate variants. Common primate variants generated from 233 primate species (left) were validated as benign (98.7%) in the human ClinVar database. Voxelized protein structures (middle) with benign primate variants (spheres) were used to train a 3D convolution neural network to predict variant pathogenicity based on regional enrichment or depletion of primate variants. The resulting model was validated in independent clinical cohorts, as illustrated by the correlation of PrimateAI-3D scores and blood cholesterol levels for UK Biobank individuals (right)
The Continuing Appeal of Punitive Damages: An Analysis of Constitutional and Other Challenges to Punitive Damages, Post-Haslip and Moriel
No full textThis article examines the enduring relevance of punitive damages in the U.S. legal system, particularly in the context of constitutional challenges following landmark cases like *Haslip* and *Moriel*. It explores how these decisions have shaped the framework for punitive damages, addressing concerns related to due process and proportionality. The analysis highlights ongoing debates about the fairness and efficacy of punitive damages in deterring misconduct and providing justice to victims. Additionally, it considers the implications of recent court rulings and legislative actions on the future of punitive damages. Ultimately, the author argues that while challenges persist, punitive damages remain a vital tool for accountability in civil litigation
A missense mutation in damage specific DNA binding protein 2 is a genetic risk factor for limbal squamous cell carcinoma in horses.
No full textSquamous cell carcinoma (SCC) is the most common cancer of the equine eye, frequently originating at the limbus, with the potential to invade the cornea, cause visual impairment, and result in loss of the eye. Several breeds of horses have a high occurrence of limbal SCC implicating a genetic basis for limbal SCC predisposition. Pedigree analysis in the Haflinger breed supports a simple recessive mode of inheritance and a genome wide association study (N=23) identified a 1.5 Mb locus on ECA12 significantly associated with limbal SCC (Pcorrected = 0.04). Sequencing the most physiologically relevant gene from this locus, damage specific DNA binding protein 2 (DDB2), identified a missense mutation (c.1013C>T p.Thr338Met) that was strongly associated with limbal SCC (P=3.41X10(-10) ). Genotyping 42 polymorphisms narrowed the ECA12 candidate interval to 483 kb but did not identify another variant that was more strongly associated. DDB2 binds to ultraviolet light damaged DNA and recruits other proteins to perform global genome nucleotide excision repair. Computational modeling predicts this mutation to be deleterious by altering conformation of the β loop involved in photolesion recognition. This DDB2 variant was also detected in two other closely related breeds with reported cases of ocular SCC, the Belgian and the Percheron, suggesting it may also be a SCC risk factor in these breeds. Further, in humans xeroderma pigmentosum complementation group E, a disease characterized by sun sensitivity and increased risk of cutaneous SCC and melanomas, is explained by mutations in DDB2. Cross species comparison remains to be further evaluated. This article is protected by copyright. All rights reserved
Supplementary materials in support of the thesis "Methods to identify novel disease genes and uplift diagnosis rates in rare diseases"
No full textThis dataset supports the thesis entitled "Methods to identify novel disease genes and uplift diagnosis rates in rare diseases"
AWARDED BY: Univeristy of Southampton
DATE OF AWARD: 2023
This dataset contains:
1. Folder called 'Appendix papers'
This contains 15 published articles in peer review journals or preprint archives which represent work from my thesis.
Appendix Paper 1 | Strategies to Uplift Novel Mendelian Gene Discovery for Improved Clinical Outcomes
Appendix Paper 2 | Challenges in the diagnosis and discovery of rare genetic disorders using contemporary sequencing technologies
Appendix Paper 3 | The mutational constraint spectrum quantified from variation in 141,456 humans
Appendix Paper 4 | Transcript expression-aware annotation improves rare variant interpretation
Appendix Paper 5 | Addendum: The mutational constraint spectrum quantified from variation in 141,456 humans
Appendix Paper 6 | Advanced variant classification framework reduces the false positive rate of predicted loss of function (pLoF) variants in population sequencing data
Appendix Paper 7 | A gene-to-patient approach uplifts novel disease gene discovery and identifies 18 putative novel disease genes
Appendix Paper 8 | Response to Ramos et al.
Appendix Paper 9 | 100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care — Preliminary Report
Appendix Paper 10 | Loss-of-function variants in TAF4 are associated with a neurodevelopmental disorder. Human Mutation
Appendix Paper 11 | Monogenic de novo variants in DDX17 cause a novel neurodevelopmental disorder
Appendix Paper 12 | Targeting de novo loss of function variants in constrained disease genes improves diagnostic rates in the 100,000 Genomes Project
Appendix Paper 13 | A gene pathogenicity tool ‘GenePy’ identifies missed biallelic diagnoses in the 100,000 Genomes Project
Appendix Paper 14 | A panel-agnostic strategy ‘HiPPo’ improves diagnostic efficiency in the UK 2 Genome Medicine Service
Appendix Paper 15 | A novel variant in GATM causes idiopathic renal Fanconi syndrome and predicts progression to end-stage kidney disease
2. Folder called 'Supplementary Datasets'
All data can be opened using Microsoft Excel.
Supplementary Dataset SD1 | Enriched biological processes in DDX17 RNA-seq data [Co-author Cyril F. Bourgeois; University of Lyon]
Supplementary Dataset SD2 | Curation of pLoF variants in haploinsufficient genes
Supplementary Dataset SD3 | Curation of 3362 homozygous pLoF variants [Co-authors Moriel Singer-Berk, Eleina England; Broad Institute of MIT and Harvard]
Supplementary Dataset SD4 | Detailed phenotype table of patients with DDX17 variants
Supplementary Dataset SD5 | Differentially expressed genes in DDX17-KD cells compared to control cells [Co-author Cyril F. Bourgeois; University of Lyon]
Supplementary Dataset SD6 | Detailed phenotype table of patients with HDLBP variants
Supplementary Dataset SD7 | Manual curation of 45 remaining variants [Co-author N. Simon Thomas, University of Southampton]
Supplementary Dataset SD8 | Re-analysis of DeNovoLOEUF on 100,000 Genomes Project data
Supplementary Dataset SD9 | 36 possible missed diagnoses in patients with a cardiomyopathy phenotype
Supplementary Dataset SD10 | Genes associated with cardiomyopathies
Supplementary Dataset SD11 | Autosomal recessive disease genes
Supplementary Dataset SD12 | 682 participants with a potential missed diagnosis
Supplementary Dataset SD13 | Variants identified using the HiPPo protocol
3. Folder called 'Supplementary Tables'
All data can be opened using Microsoft Excel.
Supplementary Table S1 | Environmental tools in GEL
Supplementary Table S2 | List of 1,815 genes tolerant of homozygous loss-of-function variation [Co-author Moriel Singer-Berk; Broad Institute of MIT and Harvard]
Supplementary Table S3 | Genes tolerant of homozygous loss-of-function variation with an OMIM dominant association
Supplementary Table S4 | 27 genes with more than one Genomics England kindred affected
Supplementary Table S5 | 99 Class 2 and Class 3 genes
Supplementary Table S6 | Sequences of siRNAs against DDX17 [Co-author Cyril F. Bourgeois; University of Lyon]
Supplementary Table S7 | A summary of high-level phenotypes of the 100,000 Genomes Project patient population
Supplementary Table S8 | All human genes curated with a LOEUF score
Supplementary Table S9 | 182 participants without a listed cardiomyopathy phenotype that had a pathogenic variant returned by 100KGP in a cardiomyopathy-related gene
Supplementary Table S10 | Quality control of 24 samples from 8 families undergoing parallel research exome and clinical genome [Co-author Nichola Grahame; University of Southampton]
4. Folder called 'Supplementary Figures'
Contains a single word document will the following figures:
Supplementary Figure S1 | Crispr/Cas9 microinjection into X. tropicalis eggs produces mosaic homozygous crispant tadpoles encoding truncated Ddx17 which is inherited in the F1 generation [Co-authors Annie Godwin, Matt Guille; University of Portsmouth]
Supplementary Figure S2 | The amino acid alignment between the H. sapiens and X. tropicalis Ddx17 proteins [Co-authors Annie Godwin, Matt Guille; University of Portsmouth]
Supplementary Figure S3 | F0 mosaic homozygous X. tropicalis display reduced axon outgrowth, and working memory like F1 models, but also gastrulation defects and short term microcephaly [Co-authors Annie Godwin, Matt Guille]
Supplementary Figure S4 | Results of dark-light transitions assay and neuronal outgrowth [Co-authors Annie Godwin, Matt Guille; University of Portsmouth]
Supplementary Figure S5 | Compound heterozygous ddx17-/- tadpoles are morphologically normal but show working memory deficits [Co-authors Annie Godwin, Matt Guille; University of Portsmouth]
Supplementary Figure S6 | Network representation of the top 40 enriched biological processes [Co-author Cyril F. Bourgeois; University of Lyon]
Supplementary Figure S7 | Enriched biological processes for down-regulated and up-regulated genes [Co-author Cyril F. Bourgeois; University of Lyon]
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First person – Gonzalo Quiroga-Artigas
No full textInternational audienceFirst Person is a series of interviews with the first authors of a selection of papers published in Biology Open, helping researchers promote themselves alongside their papers. Gonzalo Quiroga-Artigas is first author on ‘ Storage cell proliferation during somatic growth establishes that tardigrades are not eutelic organisms’, published in BiO. Gonzalo is a postdoc in the lab of María Moriel-Carretero at Centre de Recherche en Biologie cellulaire de Montpellier (CRBM), Université de Montpellier, France, delving into the genetic factors that influence the extremophile abilities of tardigrades
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A novel DDB2 mutation causes defective recognition of UV-induced DNA damages and prevalent equine squamous cell carcinoma
No full textSquamous cell carcinoma (SCC) occurs frequently in the human Xeroderma Pigmentosum (XP) syndrome and is characterized by deficient UV-damage repair. SCC is the most common equine ocular cancer and the only associated genetic risk factor is a UV-damage repair protein. Specifically, a missense mutation in horse DDB2 (T338M) was strongly associated with both limbal SCC and third eyelid SCC in three breeds of horses (Halflinger, Belgian, and Rocky Mountain Horses) and was hypothesized to impair binding to UV-damaged DNA. Here, we investigate DDB2-T338M mutant's capacity to recognize UV lesions in vitro and in vivo, together with human XP mutants DDB2-R273H and -K244E. We show that the recombinant DDB2-T338M assembles with DDB1, but fails to show any detectable binding to DNA substrates with or without UV lesions, due to a potential structural disruption of the rigid DNA recognition β-loop. Consistently, we demonstrate that the cellular DDB2-T338M is defective in its recruitment to focally radiated DNA damages, and in its access to chromatin. Thus, we provide direct functional evidence indicating the DDB2-T338M recapitulates molecular defects of human XP mutants, and is the causal loss-of-function allele that gives rise to equine ocular SCCs. Our findings shed new light on the mechanism of DNA recognition by UV-DDB and on the initiation of ocular malignancy
A novel DDB2 mutation causes defective recognition of UV-induced DNA damages and prevalent equine squamous cell carcinoma
No full textSquamous cell carcinoma (SCC) occurs frequently in the human Xeroderma Pigmentosum (XP) syndrome and is characterized by deficient UV-damage repair. SCC is the most common equine ocular cancer and the only associated genetic risk factor is a UV-damage repair protein. Specifically, a missense mutation in horse DDB2 (T338M) was strongly associated with both limbal SCC and third eyelid SCC in three breeds of horses (Halflinger, Belgian, and Rocky Mountain Horses) and was hypothesized to impair binding to UV-damaged DNA. Here, we investigate DDB2-T338M mutant’s capacity to recognize UV lesions in vitro and in vivo, together with human XP mutants DDB2-R273H and -K244E. We show that the recombinant DDB2-T338M assembles with DDB1, but fails to show any detectable binding to DNA substrates with or without UV lesions, due to a potential structural disruption of the rigid DNA recognition β-loop. Consistently, we demonstrate that the cellular DDB2-T338M is defective in its recruitment to focally radiated DNA damages, and in its access to chromatin. Thus, we provide direct functional evidence indicating the DDB2-T338M recapitulates molecular defects of human XP mutants, and is the causal loss-of-function allele that gives rise to equine ocular SCCs. Our findings shed new light on the mechanism of DNA recognition by UV-DDB and on the initiation of ocular malignancy.Lewis Katz School of MedicineCancer and Cellular Biolog
A novel DDB2 mutation causes defective recognition of UV-induced DNA damages and prevalent equine squamous cell carcinoma
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