Biology subjects

Schofield, P.

Publications and source records attributed to Schofield, P..

15 recordsLinked to original sources

bioRxiv2026

Evaluating Aggregated Gene Level eQTL Scores

Genetic feature engineering, used in methods such as transcriptome-wide association study, supports gene-trait association testing by aggregating single variants into gene-level features predictive of expression. To evaluate how different model architectures, LD filtering thresholds, and variant prioritization methods affect expression prediction quality, we trained over 3 million models and evaluated their performance in independent cohorts. Using the best performing models to impute expression and immunotherapy response as an example trait, we found a significant association with the reactive oxygen species pathway (p=0.032). Our model training workflow will support genetic feature engineering towards improved complex trait modeling.

bioinformatics↗

bioRxiv2026

Transposable elements shape olaparib response according to BRCA1 status in triple-negative breast cancer

BackgroundTriple-negative breast cancer (TNBC) is an aggressive subtype with limited therapeutic options. While PARP inhibitors, such as olaparib, show promise in BRCA1-deficient TNBC through synthetic lethality, up to 50% of patients fail to respond, highlighting the need to understand the molecular mechanisms underlying PARP inhibitors efficacy. Transposable elements (TEs), particularly LINE-1 elements, are increasingly recognized as modulators of genomic instability associated with DNA repair processes and potential key players in synthetic lethality. Here, we investigate the functional relationship between TE activity and olaparib treatment in TNBC with distinct BRCA1 functional status. MethodsWe performed comprehensive multi-OMICs analysis of four TNBC cell lines (two BRCA1-deficient: SUM1315 and MDA-MB-436; two BRCA1-proficient: MDA-MB-468 and BT549) treated with olaparib. We analyzed expression and differential expression of protein-coding genes, TEs, and gene-TE chimeric transcripts. Long-read whole-genome sequencing was employed to detect de novo TE insertions, complemented by a functional assay to quantify LINE-1 retrotransposition activity in olaparib-treated cells. ResultsOlaparib treatment induces extensive transcriptomic and genomic disorganization mediated by TEs, especially LINE-1, exclusively in BRCA1-deficient cells. We observed aberrant overexpression of both genes and TEs, including gene-TE chimeric transcripts harboring poison exons within tumorigenic genes and multi-exonic TE-TE chimeras capable of forming immunostimulatory double-stranded RNA (dsRNA) structures. Functional enrichment analyses revealed activation of antiviral immune pathways linked to LINE-1 activity. Consistently, orthogonal assays confirmed LINE-1 retrotransposition in BRCA1-deficient cells following olaparib exposure. ConclusionsOur findings demonstrate that olaparib treatment induces TE activation especially in BRCA1-deficient cells, a novel mechanism that may underlie synthetic lethality in TNBC. This TE activation triggers immune responses and genomic instability, providing new therapeutic opportunities through immunotherapy combinations and suggesting that TE activity may serve as a potential biomarker for treatment stratification of TNBC. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC="FIGDIR/small/738694v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1cf6ecorg.highwire.dtl.DTLVardef@19725f7org.highwire.dtl.DTLVardef@3d9597org.highwire.dtl.DTLVardef@127f0bb_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

L1 insertion intermediates recombine with one another or with DNA breaks to form genome rearrangements

LINE-1 retrotransposition is common in human cancers and rearrangements at insertion sites can contribute to cancer-driving oncogene amplifications and promote genome instability. However, the mechanisms underlying rearrangements of L1 retrotransposition intermediates are poorly understood. To address this gap, we developed GFP-based recombination reporter assays to study the formation of L1 retrotransposition-mediated rearrangements. Using these reporters combined with long-read sequencing approaches, we find that L1 retrotransposition intermediates can recombine with distal DNA breaks to generate chromosomal rearrangements. We also find that two distinct L1 insertion intermediates can recombine with each other to generate chromosomal rearrangements. Both types of rearrangements depend on L1-encoded ORF2p endonuclease and reverse transcriptase activities. Using these reporters, we discover that L1 retrotransposition-mediated rearrangements are robustly induced when the recombining sequences share homology and that their formation requires the homologous recombination factor BRCA1. Given the repetitive nature of our genome, these findings highlight the risk of L1 insertion intermediates becoming substrates for aberrant recombination and promoting genome instability.

molecular biology↗

bioRxiv2024

Chromosomal rearrangements and instability caused by the LINE-1 retrotransposon

LINE-1 (L1) retrotransposition is widespread in many cancers, especially those with a high burden of chromosomal rearrangements. However, whether and to what degree L1 activity directly impacts genome integrity is unclear. Here, we apply whole-genome sequencing to experimental models of L1 expression to comprehensively define the spectrum of genomic changes caused by L1. Combining the analyses of experimental models of L1 induction and of cancer genomes, we demonstrate that L1 retrotransposition can directly generate reciprocal translocations, genomic DNA inversions, and foldback rearrangements resulting from illegitimate recombination of double-strand DNA ends generated by L1-encoded ORF2p. We further show that L1-induced rearrangements can produce unstable chromosomes that fuel the acquisition of complex rearrangements, large segmental copy-number alterations, and genetic heterogeneity through breakage-fusion bridge cycles or DNA fragmentation. Together, these findings suggest L1 as a potent mutagenic force capable of driving genome evolution in cancers.

genomics↗

bioRxiv2024

Gag proteins encoded by endogenous retroviruses are required for zebrafish development

Transposable elements (TEs) make up the bulk of eukaryotic genomes and examples abound of TE-derived sequences repurposed for organismal function. The process by which TEs become coopted remains obscure because most cases involve ancient, transpositionally inactive elements. Reports of active TEs serving beneficial functions are scarce and often contentious due to difficulties in manipulating repetitive sequences. Here we show that recently active TEs in zebrafish encode products critical for embryonic development. Knockdown and rescue experiments demonstrate that the endogenous retrovirus family BHIKHARI-1 (Bik-1) encodes a Gag protein essential for mesoderm development. Mechanistically, Bik-1 Gag associates with the cell membrane and its ectopic expression in chicken embryos alters cell migration. Similarly, depletion of BHIKHARI-2 Gag, a relative of Bik-1, causes defects in neural crest development in zebrafish. We propose an "addiction" model to explain how active TEs can be integrated into conserved developmental processes.

developmental biology↗

bioRxiv2024

Structure and dynamics of the autoantigen GAD65 in complex with the human autoimmune polyendocrine syndrome type 2-associated autoantibody b96.11

The enzyme glutamate decarboxylase (GAD) produces the neurotransmitter GABA, using pyridoxal-5-phosphate. GAD exists as two isoforms, GAD65 and GAD67. Only GAD65 acts as a major autoantigen, with its autoantibodies frequently found in type 1 diabetes and other autoimmune diseases. Here we characterize the structure and dynamics of GAD65 and its interaction with the autoimmune polyendocrine syndrome type 2-associated autoantibody b96.11. Combining hydrogen-deuterium exchange mass spectrometry (HDX), X-ray crystallography, cryo-electron microscopy and computational approaches, we dissect the conformational dynamics of the inactive apo- and the active holo-forms of GAD65, as well as the structure of the GAD65-autoantibody complex. HDX reveals the time-resolved, local dynamics that accompany autoinactivation, with the catalytic loop playing a key role in promoting collective dynamics at the interface between CTD and PLP domains. In the GAD65-b96.11 complex, heavy chain CDRs dominate the interaction, with the relatively long CDRH3 at the interface centre and uniquely bridging the GAD65 dimer via extensive electrostatic interactions with the 260PEVKEK265 motif. The autoantibody bridges structural elements on GAD65 that contribute to conformational change in GAD65, thus connecting the unique and intrinsic conformational flexibility that governs the autoinactivation mechanism of the enzyme to its autoantigenicity. The intrinsic dynamics, rather than sequence differences within epitopes, appear to be responsible for the contrasting autoantigenicities of GAD65 and GAD67. Our data thus reveal insights into the structural and dynamic differences between GAD65 and GAD67 that dictate their contrasting autoantibody reactivities, provide a new structural rationalisation for the nature of the autoimmune response to GAD65, and may have broader implications for antigenicity in general.

biochemistry↗

bioRxiv2023

Functional variations in gamma-secretase activity are critical determinants of the clinical, biomarker, and cognitive progression of autosomal dominant Alzheimer's disease

BackgroundThe balance between production, clearance, and toxicity of A{beta} peptides is central to Alzheimers disease (AD) pathobiology. Though highly variable in terms of age at symptom onset (AAO), hundreds of variants in PSEN1 cause autosomal dominant forms of AD (ADAD) with nearly complete penetrance. PSEN1 forms the catalytic core of the {gamma}-secretase complex and thereby directly mediates the production of longer, aggregation-prone A{beta} peptides relative to shorter, non-aggregating peptides. We hypothesized that the broad AAO and biomarker heterogeneity seen across ADAD would be predictable based on mutation-specific differences in the production of A{beta} species. MethodsA{beta}-37, 38, 40, 42, and 43 production was quantified from 161 unique PSEN1 variants expressed in HEK293 cells. Prediction of AAO was carried out in 106 variants with available AAO and then replicated in 55 variants represented across 190 PSEN1 mutation carriers who have detailed cognitive and biomarker data from the Dominantly Inherited Alzheimers Network (DIAN). ResultsVariations in A{beta} production across the 161 mutations examined in cell-based models were highly predictive of AAO. In those with corresponding in vivo data from the DIAN study, our cell-based {gamma}-secretase composite was strongly associated with biomarker and cognitive trajectories. ConclusionsThese findings elucidate the critical link between {gamma}-secretase function, A{beta} production, and AD progression and offer mechanistic support for the amyloid hypothesis. The approach used here represents a powerful tool to account for heterogeneity in disease progression in ADAD clinical trials and to assess the pathogenicity of variants of unknown significance or with limited family history.

neuroscience↗

bioRxiv2022

Broadly neutralizing SARS-CoV-2 antibodies through epitope-based selection from convalescent patients

Emerging variants of concern (VOCs) are threatening to limit the effectiveness of SARS-CoV-2 monoclonal antibodies and vaccines currently used in clinical practice; broadly neutralizing antibodies and strategies for their identification are therefore urgently required. Here we demonstrate that broadly neutralizing antibodies can be isolated from peripheral blood mononuclear cells (PBMCs) of convalescent patients using SARS-CoV-2 receptor binding domains (RBDs) carrying epitope-specific mutations. This is exemplified by two human antibodies, GAR05, binding to epitope class 1, and GAR12, binding to a new epitope class 6 (located between class 3 and class 5). Both antibodies broadly neutralize VOCs, exceeding the potency of the clinical monoclonal sotrovimab (mAb S309) by orders of magnitude. They also provide potent prophylactic and therapeutic in vivo protection of hACE2 mice against viral challenge. Our results indicate that exposure to Wuhan SARS-CoV-2 induces antibodies that maintain potent and broad neutralization against emerging VOCs using two unique strategies: either by targeting the divergent class 1 epitope in a manner resistant to VOCs (ACE2 mimicry, as illustrated by GAR05 and mAbs P2C-1F11/S2K14); or alternatively, by targeting rare and highly conserved epitopes, such as the new class 6 epitope identified here (as illustrated by GAR12). Our results provide guidance for next generation monoclonal antibody development and vaccine design.

immunology↗

bioRxiv2021

Klarigi: Explanations for Semantic Groupings

BackgroundAnnotation of biomedical entities with ontology classes provides for formal semantic analysis and mobilisation of background knowledge in determining their relationships. To date enrichment analysis has been routinely employed to identify classes that are over-represented in annotations across sets of groups, such as biosample gene expression profiles or patient phenotypes. These approaches, however, usually consider only univariate relationships, make limited use of the semantic features of ontologies, and provide limited information and evaluation of the explanatory power of both singular and grouped candidate classes. Moreover, they do not solve the problem of deriving cohesive, characteristic, and discriminatory sets of classes for entity groups. ResultsWe have developed a new method, Klarigi, which introduces multiple scoring heuristics for identification of classes that are both compositional and discriminatory for groups of entities annotated with ontology classes. The tool includes a novel algorithm for derivation of multivariable semantic explanations for entity groups, makes use of semantic inference through live use of an ontology reasoner, and includes a classification method for identifying the discriminatory power of candidate sets. We describe the design and implementation of Klarigi, and evaluate its use in two test cases, comparing and contrasting methods and results with literature and enrichment analysis methods. ConclusionsWe demonstrate that Klarigi produces characteristic and discriminatory explanations for groups of biomedical entities in two settings. We also show that these explanations recapitulate and extend the knowledge held in existing biomedical databases and literature for several diseases. We conclude that Klarigi provides a distinct and valuable perspective on biomedical datasets when compared with traditional enrichment methods, and therefore constitutes a new method by which biomedical datasets can be explored, contributing to improved insight into semantic data.

bioinformatics↗

bioRxiv2021

DeepMOCCA: A pan-cancer prognostic model identifies personalized prognostic markers through graph attention and multi-omics data integration

Combining multiple types of genomic, transcriptional, proteomic, and epigenetic datasets has the potential to reveal biological mechanisms across multiple scales, and may lead to more accurate models for clinical decision support. Developing efficient models that can derive clinical outcomes from high-dimensional data remains problematical; challenges include the integration of multiple types of omics data, inclusion of biological background knowledge, and developing machine learning models that are able to deal with this high dimensionality while having only few samples from which to derive a model. We developed DeepMOCCA, a framework for multi-omics cancer analysis. We combine different types of omics data using biological relations between genes, transcripts, and proteins, combine the multi-omics data with background knowledge in the form of protein-protein interaction networks, and use graph convolution neural networks to exploit this combination of multi-omics data and background knowledge. DeepMOCCA predicts survival time for individual patient samples for 33 cancer types and outperforms most existing survival prediction methods. Moreover, DeepMOCCA includes a graph attention mechanism which prioritizes driver genes and prognostic markers in a patient-specific manner; the attention mechanism can be used to identify drivers and prognostic markers within cohorts and individual patients. Author summaryLinking the features of tumors to a prognosis for the patient is a critical part of managing cancer. Many methods have been applied to this problem but we still lack accurate prognostic markers for many cancers. We now have more information than ever before on the state of the cancer genome, the epigenetic changes in tumors, and gene expression at both RNA and protein levels. Here, we address the question of how this data can be used to predict cancer survival and discover which tumor genes make the greatest contribution to the prognosis in individual tumor samples. We have developed a computational model, DeepMOCCA, that uses artificial neural networks underpinned by a large graph constructed from background knowledge concerning the functional interactions between genes and their products. We show that with our method, DeepMOCCA can predict cancer survival time based entirely on features of the tumor at a cellular and molecular level. The method confirms many existing genes that affect survival but for some cancers suggests new genes, either not implicated in survival before or not known to be important in that particular cancer. The ability to predict the important features in individual tumors provided by our method raises the possibility of personalized therapy based on the gene or network dominating the prognosis for that patient.

bioinformatics↗

bioRxiv2020

Potent SARS-CoV-2 binding and neutralization through maturation of iconic SARS-CoV-1 antibodies

Antibodies against coronavirus spike protein potently protect against infection and disease, however it remains unclear if such protection can be extended to variant coronaviruses. This is exemplified by a set of iconic and well-characterized monoclonal antibodies developed after the 2003 SARS outbreak including mAbs m396, CR3022, CR3014 and 80R, which potently neutralize SARS-CoV-1, but not SARS-CoV-2. Here we explore antibody maturation strategies to change and broaden their specificity, enabling potent binding and neutralization of SARS-CoV-2. Using targeted mutagenesis as well as light chain shuffling on phage, we identified variants with considerably increased affinity and neutralization potential. The most potent antibody, derived from the NIH-developed mAb m396, neutralized live SARS-CoV-2 virus with a half-maximal inhibitory concentration (IC50) of 160 ng/ml. Intriguingly, while many of the matured clones maintained specificity of the parental antibody, new specificities were also observed, which was further confirmed by X-ray crystallography and cryo-electron microscopy, indicating that a limited set of antibodies can give rise to variants targeting diverse epitopes. Our findings open up over 15 years of antibody development efforts against SARS-CoV-1 to the SARS-CoV-2 field and outline general principles for the maturation of antibody specificity against emerging viruses.

immunology↗

bioRxiv2019

Hypoxia induces rapid changes to histone methylation reprogramming chromatin for the cellular response

Molecular dioxygenases include JmjC-containing histone demethylases and PHD enzymes, but only PHDs are considered to be molecular oxygen sensors in cells. Although, it is known that hypoxia can alter chromatin, whether this is a direct effect on histone demethylases or due to hypoxia induced HIF-dependent transcriptional changes is not known. Here, we report that hypoxia induces a rapid and HIF-independent alteration to a variety of histone methylation marks. Genomic locations of H3K4me3 and H3K36me3 following short hypoxia predict the hypoxia gene signature observed several hours later in cells. We show that KDM5A inactivation mimics hypoxic changes to H3K4me3 in its targets and is required for the cellular response to hypoxia. Our results demonstrate a direct link between oxygen sensing and chromatin changes via KDM inhibition.\n\nOne Sentence SummaryRapid oxygen sensing by chromatin

biochemistry↗

bioRxiv2018

Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium

Cortical thickness, surface area and volumes (MRI cortical measures) vary with age and cognitive function, and in neurological and psychiatric diseases. We examined heritability, genetic correlations and genome-wide associations of cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprised 22,822 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the United Kingdom Biobank. Significant associations were replicated in the Enhancing Neuroimaging Genetics through Meta-analysis (ENIGMA) consortium, and their biological implications explored using bioinformatic annotation and pathway analyses. We identified genetic heterogeneity between cortical measures and brain regions, and 161 genome-wide significant associations pointing to wnt/{beta}-catenin, TGF-{beta} and sonic hedgehog pathways. There was enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

genetics↗

bioRxiv2017

PDGFRα signaling in cardiac stem and stromal cells modulates quiescence, metabolism and self-renewal, and promotes anatomical and functional repair

The interstitial and perivascular spaces of the mammalian heart contain a highly interactive tissue community essential for cardiac homeostasis, repair and regeneration. Mesenchymal cells (fibroblasts) are one of the most abundant cell types, playing key roles as sentinels, tissue architects, paracrine signaling hubs and lineage precursors, and are linked to heart disease through their roles in inflammation and fibrosis. Platelet-derived growth factors (PDGFs) are secreted by several cell types involved in cardiac injury and repair, and are recognized mitogens for cardiac fibroblasts and mesenchymal stem cells. However, their roles are complex and investigations of their impact on heart repair have produced contrasting outcomes, leaving therapeutic potential uncertain. Here, we use new approaches and tools, including single cell RNA sequencing, to explore cardiac fibroblast heterogeneity and how PDGF receptor (PDGFR) signaling impacts fibroblasts during heart repair. Short-term systemic delivery of PDGF-AB to mice from the time of myocardial infarction (MI) led to enhanced anatomical and functional recovery. Underpinning these benefits was a priming effect, in which PDGF-AB accelerated exit of fibroblasts from quiescence and induced a higher translational biosynthetic capacity in both fibroblasts and macrophages without triggering fibrosis. Our study highlights the significant biosynthetic heterogeneity and plasticity in cardiac fibroblast populations, and suggests a rationale for a novel therapeutic approach to cardiac injury involving controlled stimulation of fibroblast activation.

cell biology↗

bioRxiv2017

Mutational signatures of DNA mismatch repair deficiency in C. elegans and human cancers

1.Throughout their lifetime cells are subject to extrinsic and intrinsic mutational processes leaving behind characteristic signatures in the genome. One of these, DNA mismatch repair (MMR) deficiency leads to hypermutation and is found in different cancer types. While it is possible to associate mutational signatures extracted from human cancers with possible mutational processes the exact causation is often unknown. Here we use C. elegans genome sequencing of pms-2 and mlh-1 knockouts to reveal the mutational patterns linked to C. elegans MMR deficiency and their dependency on endogenous replication errors and errors caused by deletion of the polymerase {varepsilon} subunit pole-4. Signature extraction from 215 human colorectal and 289 gastric adenocarcinomas revealed three MMR-associated signatures one of which closely resembles the C. elegans MMR spectrum. A characteristic difference between human and worm MMR deficiency is the lack of elevated levels of NCG>NTG mutations in C. elegans, likely caused by the absence of cytosine (CpG) methylation in worms. The other two human MMR signatures may reflect the interaction between MMR deficiency and other mutagenic processes, but their exact cause remains unknown. In summary, combining information from genetically defined models and cancer samples allows for better aligning mutational signatures to causal mutagenic processes.

genomics↗