Biology subjects

McVicker, G.

Publications and source records attributed to McVicker, G..

11 recordsLinked to original sources

bioRxiv2025

Comprehensive molecular impact mapping of common and rare variants at GWAS loci

Deep learning sequence to function models can predict the molecular effects of genetic variants, but their predictions are limited to the cell types and assays they are trained on. Here we describe DNACipher, a deep learning model that predicts the effects of genetic variants across diverse biological contexts--including those not directly measured. DNACipher takes 196 kb of genome sequences as input and imputes variant effects across 38,582 cell type-assay combinations. DNACipher generates predictions for >7 times as many contexts as Enformer, which allows for better detection of variant effects at expression quantitative trait loci (eQTLs). We also introduce DNACipher Deep Variant Impact Mapping (DVIM), a method to identify variants with molecular effects at genome-wide association study (GWAS) loci. Application of DVIM to type 1 diabetes (T1D) reduced the mean fine-mapping credible set size from 24 to 1.4 variants per signal. DVIM variants had significantly higher fine-mapping posterior probabilities, and their predicted effects were supported by single-nucleus ATAC-seq and luciferase assays. DVIM also detected 6547 rare variants with molecular effects at 96% of GWAS T1D loci, and these were enriched for associations with immune traits. In summary, DNACipher DVIM prioritises common and rare variants at GWAS loci by predicting molecular effects across a broad range of contexts.

genetics↗

bioRxiv2025

Joint single-cell profiling of CRISPR-Cas9 edits and transcriptomes reveals widespread off-target events and their effects on gene expression

A longstanding barrier in genome engineering with CRISPR-Cas9 has been the inability to measure editing outcomes and their functional effects at single-cell resolution. Here we present "Superb-seq", which captures single-cell edits and measures their effects on the transcriptome by integrating Cas9 editing, T7 transcription, and single-cell RNA sequencing. We performed Superb-seq on over 34,000 cells from three cell lines. Using seven guide RNAs to target four chromatin remodeler genes in 10,000 K562 cells, Superb-seq detected 43 total edit sites, including 36 off-target sites, and 5761 edited cells (up to 5 edits per cell). Superb-seq improved estimation of gene perturbation effects compared to Perturb-seq and its edit detection sensitivity was comparable to bulk off-target detection methods. We identified 19 off-target edits associated with differential gene expression, nine of which were cell type specific. In summary, Superb-seq illuminates the consequences of Cas9 genome editing by connecting detected single-cell edits with changes in gene expression.

genomics↗

bioRxiv2025

GenVarLoader: An accelerated dataloader for applying deep learning to personalized genomics

Deep learning sequence models trained on personalized genomics can improve variant effect prediction, however, applications of these models are limited by computational requirements for storing and reading large datasets. We address this with GenVarLoader, which stores personalized genomic data in new memory-mapped formats with optimal data locality to achieve [~]1,000x faster throughput and [~]2,000x better compression compared to existing alternatives.

genomics↗

bioRxiv2024

Genetic and phenotypic analysis of the virulence plasmid of a non-Shigatoxigenic enteroaggregative Escherichia coli O104:H4 outbreak strain

Enteroaggregative Escherichia coli O104:H4 is best known for causing a worldwide outbreak in 2011 due to acquisition of a Shiga-like toxin alongside traditional enteroaggregative virulence traits; however, whilst the 2011 outbreak strain has been well-studied, the virulence plasmid of O104:H4 has been subjected to far less experimental analysis. In this paper, we analyse the genetic and phenotypic contribution of the pAA virulence plasmid to a non-Shigatoxigenic O104:H4 strain (1070/13) that was nonetheless implicated in a substantial UK outbreak in 2013. We find that pAA1070 is 99.95% identical across 88% of the plasmid sequence to pTY2 from the 2011 outbreak strain and has a copy number of approximately 2-3 plasmid molecules per chromosome. We demonstrate that pAA1070 carries a functional CcdAB plasmid addiction system that only marginally impacts its stability under the conditions tested and that none of the other toxin-antitoxin systems encoded by the plasmid appear to be functional, though we note a surprisingly high stability of the plasmid in vitro regardless. We demonstrate the expected contribution of pAA1070 to intestinal cell adhesion but find that it does not contribute to biofilm formation. When assessing the impact of pAA1070 on motility, we discovered a region of the O104:H4 chromosome that can be excised, abolishing motility via truncation of the fliR gene. Ultimately this work contributes to our knowledge of enteroaggregative E. coli as an important pathovar in its own right and demonstrates the complexity but necessity of experimentally characterising genuine outbreak strains rather than domesticated laboratory strains in order to understand virulence phenotypes. IMPACT STATEMENTEnteroaggregative Escherichia coli causes severe food-borne illness in humans. One serotype, O104:H4, caused a worldwide outbreak in 2011 that infected almost 4,000 people and killed dozens. The 2011 strain contained two key virulence factors: the Shiga toxin encoded by a bacteriophage and a plasmid that encodes aggregative adherence fimbriae for adhesion to host cell surfaces. Whilst the Shiga toxin has been studied extensively, the virulence plasmid has been far less well-characterised. In this study, we characterise the plasmid of a non-Shigatoxigenic O104:H4 outbreak strain and find that it contributes to host cell adherence, as expected, and that it encodes a functional CcdAB toxin-antitoxin stability system. We also demonstrate that part of the strains chromosome can be spontaneously lost during growth in the laboratory, converting the organism from highly-motile to non-motile, and suggesting a future evolutionary route for the bacterium, as has occurred in similar enteric pathogens such as Shigella. In summary, this work contributes to our knowledge of often-neglected enteroaggregative E. coli as an important pathovar and highlights the necessity of experimentally characterising genuine outbreak strains rather than "domesticated" laboratory strains. Repositories/Data SummaryThe authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. Hybrid whole-genome sequence data is available for strains 1070/13 (accession numbers CP171474, CP171475 and CP171476) and 1070/13 pAA- (accession numbers CP171472 and CP171473). Sequencing data for 1070/13 produced by Dallman et al. (2014) is available from the European Nucleotide Archive: sample accession SAMN02730196.

microbiology↗

bioRxiv2024

The plasmid-borne hipBA operon of Klebsiella michiganensis encodes a potent plasmid stabilization system

AimsKlebsiella michiganensis is a medically-important bacterium that has been subject to relatively little attention in the literature. Interrogation of sequence data from K. michiganensis strains in our collection has revealed the presence of multiple large plasmids encoding type II toxin-antitoxin (TA) systems. Such TA systems are responsible for mediating a range of phenotypes including plasmid stability ("addiction") and antibiotic persistence. In this work, we characterize the hipBA TA locus found within the Klebsiella oxytoca species complex (KoSC). Methods and ResultsThe HipBA TA system is encoded on a plasmid carried by K. michiganensis PS_Koxy4, isolated from an infection outbreak. Employing viability and plasmid stability assays, we demonstrate that PS_Koxy4 HipA is a potent antibacterial toxin and that HipBA is a functional TA module contributing substantially to plasmid maintenance. Further, we provide in silico data comparing HipBA modules across the entire KoSC. ConclusionsWe provide the first evidence of the role of a plasmid-encoded HipBA system in stability of mobile genetic elements and analyze the presence of HipBA across the KoSC. These results expand our knowledge of both a common enterobacterial TA system and a highly medically-relevant group of bacteria. Impact StatementThe HipBA TA system is typically encoded on bacterial chromosomes where it contributes to antimicrobial tolerance by interfering with translation during cellular stress. Here, we show that plasmid-encoded HipBA from a disease isolate of Klebsiella michiganensis is responsible for highly effective plasmid addiction; the first such evidence of a HipBA module contributing to plasmid stability. This has important implications for enteric pathogen evolution and horizontal gene transfer in the era of multidrug resistance.

microbiology↗

bioRxiv2024

Multi-omic QTL mapping in early developmental tissues reveals phenotypic and temporal complexity of regulatory variants underlying GWAS loci

Most GWAS loci are presumed to affect gene regulation, however, only [~]43% colocalize with expression quantitative trait loci (eQTLs). To address this colocalization gap, we identify eQTLs, chromatin accessibility QTLs (caQTLs), and histone acetylation QTLs (haQTLs) using molecular samples from three early developmental (EDev) tissues. Through colocalization, we annotate 586 GWAS loci for 17 traits by QTL complexity, QTL phenotype, and QTL temporal specificity. We show that GWAS loci are highly enriched for colocalization with complex QTL modules that affect multiple elements (genes and/or peaks). We also demonstrate that caQTLs and haQTLs capture regulatory variations not associated with eQTLs and explain [~]49% of the functionally annotated GWAS loci. Additionally, we show that EDev-unique QTLs are strongly depleted for colocalizing with GWAS loci. By conducting one of the largest multi-omic QTL studies to date, we demonstrate that many GWAS loci exhibit phenotypic complexity and therefore, are missed by traditional eQTL analyses.

genomics↗

bioRxiv2022

Deletion mapping of regulatory elements for GATA3 reveals a distal T helper 2 cell enhancer involved in allergic diseases

The GATA3 gene is essential for T cell differentiation and is surrounded by risk variants for immune traits. Interpretation of these variants is challenging because the regulatory landscape of GATA3 is complex with dozens of potential enhancers spread across a large topological associating domain (TAD) and gene expression quantitative trait locus (eQTL) studies provide limited evidence for variant function. Here, we perform a tiling deletion screen in Jurkat T cells to identify 23 candidate regulatory elements. Using small deletions in primary T helper 2 (Th2) cells, we validate the function of five of these elements, two of which contain risk variants for asthma and allergic diseases. We fine-map genome-wide association study (GWAS) signals in a distal regulatory element, 1 Mb downstream, to identify 14 candidate causal variants. Small deletions spanning candidate rs725861 decrease GATA3 expression in Th2 cells suggesting a causal mechanism for this variant in allergic diseases. Our study demonstrates the power of integrating GWAS signals with deletion mapping and identifies critical regulatory sequences for GATA3.

genomics↗

bioRxiv2021

Discovering single nucleotide variants and indels from bulk and single-cell ATAC-seq

Genetic variants and de novo mutations in regulatory regions of the genome are typically discovered by whole-genome sequencing (WGS), however WGS is expensive and most WGS reads come from non-regulatory regions. The Assay for Transposase-Accessible Chromatin (ATAC-seq) generates reads from regulatory sequences and could potentially be used as a low-cost capture method for regulatory variant discovery, but its use for this purpose has not been systematically evaluated. Here we apply seven variant callers to bulk and single-cell ATAC-seq data and evaluate their ability to identify single nucleotide variants (SNVs) and insertions/deletions (indels). In addition, we develop an ensemble classifier, VarCA, which combines features from individual variant callers to predict variants. The Genome Analysis Toolkit (GATK) is the best-performing individual caller with precision/recall on a bulk ATAC test dataset of 0.92/0.97 for SNVs and 0.87/0.82 for indels. On bulk ATAC-seq reads, VarCA achieves superior performance with precision/recall of 0.99/0.95 for SNVs and 0.93/0.80 for indels. On single-cell ATAC-seq reads, VarCA attains precision/recall of 0.98/0.94 for SNVs and 0.82/0.82 for indels. In summary, ATAC-seq reads can be used to accurately discover non-coding regulatory variants in the absence of whole-genome sequencing data and our ensemble method, VarCA, has the best overall performance.

bioinformatics↗

bioRxiv2020

The role of toxin:antitoxin systems and insertion sequences in the loss of virulence in Shigella sonnei

The Shigella plasmid, pINV, contains a 30 kb pathogenicity island (PAI) encoding a Type III secretion system (T3SS) which is essential for virulence. During growth in the laboratory, avirulent colonies of Shigella (which do not express a T3SS) arise spontaneously. Avirulence in Shigella flexneri mostly follows loss of the PAI, following recombination between insertion sequences (ISs) on pINV; toxin:antitoxin (TA) systems on pINV promote its retention through post-segregational killing (PSK). We show that avirulence in Shigella sonnei mainly results from plasmid loss, consistent with previous findings; IS-mediated PAI deletions can occur in S. sonnei, but through different ISs than in S. flexneri. We investigated the molecular basis for frequent loss of the S. sonnei plasmid, pINVSsonn. Introduction into pINVSsonn of CcdAB and GmvAT, toxin:antitoxin TA systems in pINV from S. flexneri but not S. sonnei, reduced plasmid loss and the emergence of avirulent bacteria. However, plasmid loss remained the leading cause of avirulence. We show that a single amino acid difference in the VapC toxin of the VapBC TA system in pINV also contributes to high frequency plasmid loss in S. sonnei compared to S. flexneri. Our findings demonstrate that the repertoire of ISs, complement of TA systems, and polymorphisms in TA systems influence plasmid dynamics and virulence loss in S. sonnei. Understanding the impact of polymorphisms should be informative about how TA systems contribute to PSK, and could be exploited for generating strains with stable plasmids.

microbiology↗

bioRxiv2019

Discovering functional sequences with RELICS, an analysis method for CRISPR regulatory screens

CRISPR screens are a powerful new technology for the identification of genome sequences that affect cellular phenotypes such as gene expression, survival, and proliferation. By tiling single-guide RNA (sgRNA) target sites across large genomic regions, CRISPR screens have the potential to systematically discovery novel functional sequences, however, a lack of purpose-built analysis tools limits the effectiveness of this approach. Here we describe RELICS, a Bayesian hierarchical model for the discovery of functional sequences from tiling CRISPR screens. RELICS considers the overlapping effects of multiple nearby functional sequences, accounts for the area of effect surrounding sgRNA target sites, models overdispersion in sgRNA counts, combines information across multiple pools, and estimates the number of functional sequences supported by the data. In simulations, RELICS outperforms existing methods and provides higher resolution predictions. We apply RELICS to published CRISPR interference and CRISPR activation screens and predict novel regulatory sequences, several of which we experimentally validate. In summary, RELICS is a powerful new analysis method for tiling CRISPR screens that enables the discovery of functional sequences with unprecedented resolution and accuracy.

bioinformatics↗

bioRxiv2019

BreakCA, a method to discover indels using ChIP-seq and ATAC-seq reads, finds recurrent indels in regulatory regions of neuroblastoma genomes

Most known cancer driver mutations are within protein coding regions of the genome, however, there are several important examples of oncogenic non-coding regulatory mutations. We developed a method to identify insertions and deletions (indels) in regulatory regions using aligned reads from chromatin immunoprecipitation followed by sequencing (ChIP-seq) or the assay for transposase-accessible chromatin (ATAC-seq). Our method, which we call BreakCA for Breaks in Chromatin Accessible regions, allows non-coding indels to be discovered in the absence of whole genome sequencing data, out-performs popular variant callers such as the GATK-HaplotypeCaller and VarScan2, and detects known oncogenic regulatory mutations in T-cell acute lymphoblastic leukemia cell lines. We apply BreakCA to identify indels in H3K27ac ChIP-seq peaks in 23 neuroblastoma cell lines and, after removing common germline variants, we identify 23 rare germline or somatic indels that occur in multiple neuroblastoma cell lines. Among them, 4 indels are candidate oncogenic drivers that are present in 4 or 5 cell lines, absent from the genome aggregation database of over 15,000 whole genome sequences, and within the promoters or first introns of known genes (PHF21A, ADAMTS19, GPR85 and RALGDS). In addition, we observe a rare 7bp germline deletion in two cell lines, which is associated with high expression of the histone demethylase KDM5B. Overexpression of KDM5B is prognostic for many cancers and further characterization of this indel as a potential oncogenic risk factor is therefore warranted.

bioinformatics↗