Biology subjects

Dunlop, M. G.

Publications and source records attributed to Dunlop, M. G..

7 recordsLinked to original sources

bioRxiv2023

Genetic variation at 11q23.1 confers colorectal cancer risk by dysregulation of colonic tuft cell transcriptional activator POU2AF2

Common genetic variation at 11q23.1 is associated with colorectal cancer (CRC) risk, and exerts local (cis) expression quantitative trait locus (cis-eQTL) effects on POU2AF2, COLCA1 and POU2AF3 genes. However, complex linkage disequilibrium and correlated expression at the 11q23.1 locus has thus far hindered elucidation of the mechanisms by which genetic variants impart CRC risk. Here, we establish that rs3087967 is the likely causal eQTL at this locus, co-localising with expression of POU2AF2 and CRC risk. Furthermore, we show trans-eQTL effects on 21 distant target genes, which are highly enriched for Tuft cell markers. Analysis of available scRNAseq, ChIPseq and scATACseq data implicates POU2AF2 as the primary controller of the tuft cell specific trans-genes through POU2F3-correlated genetic regulation. Immunofluorescence demonstrates that the rs3087967 risk genotype (T) is associated with lower tuft cell abundance in human colonic epithelium. CRISPR-mediated deletion of the 11q23.1 risk locus in the mouse germline exacerbated the ApcMin/+ mouse phenotype upon abrogation of Pou2af2 expression specifically. Taken together, we implicate a key protective role of tuft cells in the large bowel and the importance of mis-regulation of POU2AF2 as the prime tuft cell transcriptional activator at this locus.

genetics↗

bioRxiv2022

Factors influencing patterns of gene expression in large bowel mucosa

AimVariation in genomic sequences that control gene expression in target tissues is increasingly recognized as the underlying basis of disease susceptibility, especially cancer. This is particularly relevant to common genetic variation impacting on cancer risk. Exogenous factors may also influence gene expression, potentially leaving a transcriptomic signature of environmental risk factors in normal tissues. Therefore, understanding endogenous and exogenous influences over gene expression patterns in normal tissue is critical to the study of functional genomics and its relationship to disease susceptibility. Here, we investigated demographic and sampling variables that could impact on gene expression in normal colorectal mucosa. MethodWe prospectively collected normal mucosa from 424 patients undergoing colorectal surgery or outpatient assessment through surgical stripping of normal mucosa from resected colorectal specimens or rectal biopsy. Gene expression was assessed using Illumina HT-12 microarrays and analysed against demographic (age, gender, BMI) and sampling factors (general anaesthesia, cleansing bowel agents, sample site, time to RNA preservation) using adjusted linear regression modelling. ResultsAge, gender, smoking status, sampling under anaesthetic, sample site and sampling method were associated with differential gene expression in the adjusted model. BMI or use of cleansing bowel preparation did not impact gene expression. Age was associated with differential expression of 16 genes and significant enrichment in pathways relevant to tumourigenesis, including immune process, cell proliferation, adhesion and death. Sample site was associated with differential expression of 2515 genes, with 1102 genes more highly expressed in the proximal colon (proximal to splenic flexure). Gender and sampling under anaesthetic were associated with differential expression of 99 and 851 genes respectively. Increased time to RNA preservation (45-90 minutes) was associated with enrichment of pathways consistent with tissue ischaemia including response to wounding, apoptotic process, and response to oxygen levels. ConclusionsDemographic and sampling factors influence gene expression patterns in normal colorectal mucosa, often with a large magnitude of effect. Meanwhile, greater time to RNA preservation is associated with patterns of gene expression consistent with tissue ischaemia which questions the generalisability of assessment of gene expression patterns generated from post-mortem studies. These results highlight the importance of fully adjusted expression analyses and may indicate mechanisms underlying age, gender and site-specific differences in CRC incidence, progression and outcome.

genomics↗

bioRxiv2022

Transcriptional dynamics of colorectal cancer risk associated variation at 11q23.1 are correlated with tuft cell abundance and marker expression in silico

Colorectal cancer (CRC) is characterised by heritable risk that is not well understood. Heritable, genetic variation at 11q23.1 is associated with increased colorectal cancer (CRC) risk, demonstrating eQTL effects on 3 cis- and 23 trans-eQTL targets. We sought to determine the relationship between 11q23.1 cis- and trans-eQTL target expression and test for potential cell-specificity. scRNAseq from 32,361 healthy colonic epithelial cells was aggregated and subject to weighted gene co-expression network analysis (WGCNA). One module (blue) included 19 trans-eQTL targets and was correlated with C11orf53 expression only. Following unsupervised clustering of single cells, the expression of 19 trans-eQTL targets was greatest and most variable in cluster number 11, which transcriptionally resembled tuft cells. 14 trans-eQTL targets were found to demarcate this cluster, 11 of which were corroborated in a second dataset. Intra-cluster WGCNA and module preservation analysis then identified twelve 11q23.1 trans-eQTL targets to comprise a network that was specific to cluster 11. Finally, linear modelling and differential abundance testing showed 11q23.1 trans-eQTL target expression was predictive of cluster 11 abundance. Our findings suggest 11q23.1 trans-eQTL targets comprise a C11orf53-related network that is likely tuft cell-specific and reduced expression of these genes correlates with reduced tuft cell abundance in silico.

bioinformatics↗

bioRxiv2019

Systematic evaluation of normalization methods for glycomics data based on performance of network inference

Glycomics measurements, like all other high-throughput technologies, are subject to technical variation due to fluctuations in the experimental conditions. The removal of this non-biological signal from the data is referred to as normalization. Contrary to other omics data types, a systematic evaluation of normalization options for glycomics data has not been published so far. In this paper, we assess the quality of different normalization strategies for glycomics data with an innovative approach. It has been shown previously that Gaussian Graphical Models (GGMs) inferred from glycomics data are able to identify enzymatic steps in the glycan synthesis pathways in a data-driven fashion. Based on this finding, we here quantify the quality of a given normalization method according to how well a GGM inferred from the respective normalized data reconstructs known synthesis reactions in the glycosylation pathway. The method therefore exploits a biological measure of goodness. We analyzed 23 different normalization combinations applied to six large-scale glycomics cohorts across three experimental platforms (LC-ESI-MS, UHPLC-FLD and MALDI-FTICR-MS). Based on our results, we recommend normalizing glycan data using the Probabilistic Quotient method followed by log-transformation, irrespective of the measurement platform.

bioinformatics↗

bioRxiv2019

Aspirin-mediated DKK-1 increase rescues Wnt-driven stem-like phenotype in human intestinal organoids

Aspirin reduces the incidence and mortality of colorectal cancer (CRC). Wnt signalling drives CRC development from initiation to progression through regulation of epithelial-mesenchymal transition (EMT) and cancer stem cell populations (CSC). Here, we investigated whether aspirin can rescue these pro-invasive phenotypes associated with CRC progression in Wnt-driven human and mouse intestinal organoids. Aspirin rescues the Wnt-driven cystic organoid phenotype by promoting budding in mouse and human Apc deficient organoids, which is paralleled by decreased stem cell marker expression. Aspirin-mediated Wnt inhibition in ApcMin/+ mice is associated with EMT inhibition and decreased cell migration, invasion and motility in CRC cell lines. Chemical Wnt activation induces EMT and stem-like alterations in CRC cells, which are rescued by aspirin. Aspirin increases expression of the Wnt antagonist Dickkopf-1 (DKK-1) in CRC cells and organoids derived from FAP patients. We provide evidence of phenotypic biomarkers of aspirin response with an increased epithelial and reduced stem-like state mediated by an increase in DKK-1. Thus we highlight a novel mechanism of aspirin-mediated Wnt inhibition and potential phenotypic and molecular biomarkers for trials.

cancer biology↗

bioRxiv2019

Physical activity reduces colorectal cancer risk independent of BMI - A two-sample Mendelian randomisation study

BackgroundEvidence from observational studies suggests a protective role for physical activity (PA) against colorectal cancer (CRC) risk. However, it has yet to be established a causal relationship. We conducted a two-sample Mendelian randomisation (MR) study to examine causality between physical activity and CRC risk.\n\nMethodsWe used common genetic variants associated with self-reported and accelerometer-based physical activity as instrumental variables (IVs) in this MR study. The IVs were derived from the largest available genome-wide association study (GWAS) of physical activity, namely UK Biobank. We analysed the effect of the IVs for physical activity in a large CRC GWAS that included 31 197 cases and 61 770 controls. We applied inverse variance weighted (IVW) method as the main analysis method.\n\nResultsOur results demonstrate a protective effect between accelerometer-based physical activity and CRC risk (the outlier-adjusted ORIVW was 0.92 per one standard deviation (SD) increase of accelerometer-base physical activity [95% CI: 0.87-0.98, P: 0.01]). The effect between self-reported physical activity and CRC risk was not statistically significant but was also supportive of an inverse association (the outlier-adjusted ORIVW was 0.61 per 1 SD increase of moderate-to-vigorous physical activity [95%CI: 0.36-1.06, P: 0.08]).\n\nConclusionsThe findings of this large MR study show for the first time that objectively measured physical activity is causally implicated in reducing CRC risk. The limitations of the study are that it is based on only two genetic instruments and that it has limited power, despite the study size. Nonetheless, at a population level, these findings provide strong reinforcing evidence to support public health policy measures that encourage exercise, even in obese individuals.

genetics↗

bioRxiv2018

VEP-G2P: A Tool for Efficient, Flexible and Scalable Diagnostic Filtering of Genomic Variants

PurposeWe aimed to develop an efficient, flexible, scalable and evidence-based approach to sequence-based diagnostic analysis/re-analysis of conditions with very large numbers of different causative genes. We then wished to define the expected rate of plausibly causative variants coming through strict filtering in control in comparison to disease populations to quantify background diagnostic \"noise\".\n\nMethodsWe developed G2P (www.ebi.ac.uk/gene2phenotype) as an online system to facilitate the development, validation, curation and distribution of large-scale, evidence-based datasets for use in diagnostic variant filtering. Each locus-genotype-mechanism-disease-evidence thread (LGMDET) associates an allelic requirement and a mutational consequence at a defined locus with a disease entity and a confidence level and evidence links. We then developed an extension to Ensembl Variant Effect Predictor (VEP), VEP-G2P, which can filter based on G2P other widely used gene panel curation systems. We compared the output of disease-associated and control whole exome sequence (WES) using Developmental Disorders G2P (G2PDD; 2044 LGMDETs) and constitutional cancer predisposition G2P (G2PCancer; 128 LGMDETs).\n\nResultsWe have shown a sensitivity/precision of 97.3%/33% and 81.6%/22.7% for causative de novo and inherited variants respectively using VEP-G2PDD in DDD study probands WES. Many of the apparently diagnostic genotypes \"missed\" are likely false-positive reports with lower minor allele frequencies and more severe predicted consequences being diagnostically-discriminative features.\n\nConclusionCase:control comparisons using VEP-G2PDD established an observed:expected ratio of 1:30,000 plausibly causative variants in proband WES to ~1:40,000 reportable but presumed-benign variants in controls. At least half the filtered variants in probands represent background \"noise\". Supporting phenotypic evidence is, therefore, necessary in genetically-heterogeneous disorders. G2P and VEP-G2P provides a practical approach to optimize disease-specific filtering parameters in diagnostic genetic research.

genetics↗