Biology subjects

Williams, N.

Publications and source records attributed to Williams, N..

42 records · Page 3Linked to original sources

bioRxiv2019

Integration of eQTL and Parkinson’s disease GWAS data implicates 11 disease genes

Substantial genome-wide association study (GWAS) work in Parkinsons disease (PD) has led to an increasing number of loci shown reliably and robustly to be associated with the increased risk of the disease. Prioritising causative genes and pathways from these studies has proven problematic. Here, we present a comprehensive analysis of PD GWAS data with expression and methylation quantitative trait loci (eQTL/mQTL) using Colocalisation analysis (Coloc) and transcriptome-wide association analysis (TWAS) to uncover putative gene expression and splicing mechanisms driving PD GWAS signals. Candidate genes were further characterised by determining cell-type specificity, weighted gene co-expression (WGNCA) and protein-protein interaction (PPI) networks.\n\nGene-level analysis of expression revealed 5 genes (WDR6, CD38, GPNMB, RAB29, TMEM163) that replicated using both Coloc and TWAS analyses in both GTEx and Braineac expression datasets. A further 6 genes (ZRANB3, PCGF3, NEK1, NUPL2, GALC, CTSB) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell-types compared to neurons. The WGNCA analysis showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes related with protein ubiquitination (protein ubiquitination (p=7.47e-10) and ubiquitin-dependent protein catabolic process (p = 2.57e-17) in nucleus accumbens, caudate and putamen, while TMEM163 and ZRANB3 were both important in modules indicating regulation of signalling (p=1.33e-65] and cell communication (p=7.55e-35) in the frontal cortex and caudate respectively. PPI analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known Mendelian PD and parkinsonism proteins than would be expected by chance. The proteins core proteins this network were enriched for regulation of the ERBB receptor tyrosine protein kinase signalling pathways.\n\nTogether, these results point to a number of candidate genes and pathways that are driving the associations observed in PD GWAS studies.

neuroscience↗

bioRxiv2019

Machine learning predicts rapid relapse of triple negative breast cancer

PurposeMetastatic relapse of triple-negative breast cancer (TNBC) within 2 years of diagnosis is associated with particularly aggressive disease and a distinct clinical course relative to TNBCs that relapse beyond 2 years. We hypothesized that rapid relapse TNBCs (rrTNBC; metastatic relapse or death <2 years) reflect unique genomic features relative to late relapse (lrTNBC; >2 years).\n\nPatients and MethodsWe identified 453 primary TNBCs from three publicly-available datasets and characterized each as rrTNBc, lrTNBC, or no relapse (nrTNBC: no relapse/death with at least 5 years follow-up). We compiled primary tumor clinical and multi-omic data, including transcriptome (n=453), copy number alterations (CNAs; n=317), and mutations in 171 cancer-related genes (n=317), then calculated published gene expression and immune signatures.\n\nResultsPatients with rrTNBC were higher stage at diagnosis (Chi-square p<0.0001) while lrTNBC were more likely to be non-basal PAM50 subtype (Chi-square p=0.03). Among 125 expression signatures, five immune signatures were significantly higher in nrTNBCs while lrTNBC were enriched for eight estrogen/luminal signatures (all FDR p<0.05). There was no significant difference in tumor mutation burden or percent genome altered across the groups. Among mutations, only TP53 mutations were significantly more frequent in rrTNBC compared to lrTNBC (Fisher exact FDR p=0.009). To develop an optimal classifier, we used 77 significant clinical and omic features to evaluate six modeling approaches encompassing simple, machine learning, and artificial neural network (ANN). Support vector machine outperformed other models with average receiver-operator characteristic area under curve >0.75.\n\nConclusionsWe provide a new approach to define TNBCs based on timing of relapse. We identify distinct clinical and genomic features that can be incorporated into machine learning models to predict rapid relapse of TNBC.

cancer biology↗

bioRxiv2018

Long-range phase synchronization of high-gamma activity in human cortex

Inter-areal synchronization of neuronal oscillations below 100 Hz is ubiquitous in cortical circuitry and thought to regulate neuronal communication. In contrast, faster activities are generally considered to be exclusively local-circuit phenomena. We show with human intracerebral recordings that 100-300 Hz high-gamma activity (HGA) may be synchronized between widely distributed regions. HGA synchronization was not attributable to artefacts or to epileptic pathophysiology. Instead, HGA synchronization exhibited a reliable cortical connectivity and community structures, and a laminar profile opposite to that of lower frequencies. Importantly, HGA synchronization among functional brain systems during non-REM sleep was distinct from that in resting state. Moreover, HGA synchronization was transiently enhanced for correctly inhibited responses in a Go/NoGo task. These findings show that HGA synchronization constitutes a new, functionally significant form of neuronal spike-timing relationships in brain activity. We suggest that HGA synchronization reflects the temporal microstructure of spiking-based neuronal communication per se in cortical circuits.

neuroscience↗

bioRxiv2018

Zika Virus Subverts Stress Granules to Promote and Restrict Viral Gene Expression

Flaviviruses limit the cell stress response by preventing the formation of stress granules and utilize different proteins involved in the stress granule pathway to modulate viral gene expression. In this study, we investigated the formation of stress granules during Zika virus (ZIKV) infection and the role stress granule proteins play during the viral life cycle. Using immunofluorescence and confocal microscopy, we determined that ZIKV disrupted the formation of arsenite-induced stress granules and changed the subcellular distribution, but not the abundance or integrity of stress granule proteins. To investigate the role of different stress granule proteins in ZIKV infection we used target-specific siRNAs to deplete six proteins, namely Ataxin2, G3BP1, HuR, TIA-1, TIAR and YB-1. Depletion of TIA-1 and TIAR affected ZIKV protein and RNA levels, but viral titers did not change. Conversely, depletion of Ataxin2 and YB-1 decreased virion production despite having only a small effect on ZIKV protein and expression. Notably, however, depletion of G3BP1 and HuR decreased and increased ZIKV gene expression and virion production, respectively. Using an MR766 Gaussia luciferase reporter genome together with knockdown and overexpression assays, G3BP1 and HuR were found to modulate ZIKV replication. These data indicate that ZIKV disrupts the formation of stress granules by sequestering stress granule proteins required for replication, which is where G3BP1 functions to promote ZIKV infection, while HuR exhibits an antiviral effect. The consequence of ZIKV re-localizing and subverting select stress granule proteins might have broader consequences on cellular RNA homeostasis contributing to cellular gene dysregulation and ZIKV pathogenesis.\n\nImportanceIn response to viral infection, cellular translation is stalled, and translation initiation complexes, cellular mRNAs, and RNA binding proteins aggregate in stress granules. Because the assembly of stress granules antagonize translation of viral proteins, which is a critical step for single-stranded positive-sense RNA viruses to replicate the viral genome, many viruses have developed strategies to inhibit stress granule formation. In this study, we observed that Zika virus restricts the formation of stress granules likely by re-localizing specific stress granule proteins during infection. We also determined that specific stress granule proteins function to facilitate and limit Zika virus replication. This interaction of Zika virus with stress granule proteins is interesting, as many stress granule proteins are also known to function in neuronal granules, which are critical in neural development and function. Moreover, dysregulation of different stress granule proteins in neurons has been shown to play a role in the progression of neurodegenerative diseases. The likely consequences of Zika virus modulating stress granule assembly and subverting specific stress granule proteins are alterations to cellular mRNA transcription, splicing, RNA stability, and translation. Such changes in cellular ribostasis could have profound effects on neural development and contribute to the devastating developmental and neurological anomalies observed following intrauterine Zika virus infection. Our study provides new insights into virus-host interactions and the identification of the stress granule proteins that may contribute to the unusual pathogenesis associated with this reemerging arbovirus.

microbiology↗

bioRxiv2018

Genetic risk for schizophrenia and developmental delay is associated with shape and microstructure of midline white matter structures

Genomic copy number variants (CNVs) are amongst the most highly penetrant genetic risk factors for neuropsychiatric disorders. The scarcity of carriers of individual CNVs and their phenotypical heterogeneity limits investigations of the associated neural mechanisms and endophenotypes. We applied a novel design based on CNV penetrance for schizophrenia and developmental delay that allows us to identify structural sequelae that are most relevant to neuropsychiatric disorders. Our focus on brain structural abnormalities was based on the hypothesis that convergent mechanisms contributing to neurodevelopmental disorders would likely manifest in the macro- and microstructure of white matter and cortical and subcortical grey matter. 21 adult participants carrying neuropsychiatric risk CNVs (including those located at 22q11.2, 15q11.2, 1q21.1, 16p11.2, and 17q12) and 15 age- and gender matched controls underwent T1-weighted structural, diffusion and quantitative T1 relaxometry MRI.\n\nThe macro- and microstructural properties of the cingulum bundles were associated with penetrance for both developmental delay and schizophrenia, in particular curvature along the anterior-posterior axis (Sz: pcorr=0.026; DD: pcorr=0.035) and intracellular volume fraction (Sz: pcorr=0.019; DD: pcorr=0.064) Further principal component analysis showed alterations in the interrelationships between the volumes of several mid-line white matter structures (Sz: pcorr=0.055; DD, pcorr=0.027). In particular, the ratio of volumes in the splenium and body of the corpus callosum was significantly associated with both penetrance scores (Sz: p=0.037; DD; p=0.006). Our results are consistent with the notion that a significant alteration in developmental trajectories of mid-line white-matter structures constitutes a common neurodevelopmental aberration contributing to risk for schizophrenia and intellectual disability.

neuroscience↗

bioRxiv2016

Genome-Wide Fitness Analyses of the Foodborne Pathogen Campylobacter jejuni in In Vitro and In Vivo Models

Infection by Campylobacter is recognised as the most common cause of foodborne bacterial illness worldwide. Faecal contamination of meat, especially chicken, during processing represents a key route of transmission to humans. There is currently no licenced vaccine and no Campylobacter-resistant chickens. In addition, preventative measures aimed at reducing environmental contamination and exposure of chickens to Campylobacter jejuni (biosecurity) have been ineffective. There is much interest in the factors/mechanisms that drive C. jejuni colonisation and infection of animals, and survival in the environment. It is anticipated that understanding these mechanisms will guide the development of effective intervention strategies to reduce the burden of C. jejuni infection. Here we present a comprehensive analysis of C. jejuni fitness during growth and survival within and outside hosts. A comparative analysis of transposon (Tn) gene inactivation libraries in three C. jejuni strains by Tn-seq demonstrated that a large proportion, 331 genes, of the C. jejuni genome is dedicated to (in vitro) growth. An extensive Tn library in C. jejuni M1cam (~10,000 mutants) was screened for the colonisation of commercial broiler chickens, survival in houseflies and under nutrient-rich and-poor conditions at low temperature, and infection of human gut epithelial cells. We report C. jejuni factors essential throughout its life cycle and we have identified genes that fulfil important roles across multiple conditions, including maf3, fliW, fliD, pflB and capM, as well as novel genes uniquely implicated in survival outside hosts. Taking a comprehensive screening approach has confirmed previous studies, that the flagella are central to the ability of C. jejuni to interact with its hosts. Future efforts should focus on how to exploit this knowledge to effectively control infections caused by C. jejuni.\n\nAuthor SummaryCampylobacter jejuni is the leading bacterial cause of human diarrhoeal disease. C. jejuni encounters and has to overcome a wide range of \"stress\" conditions whilst passing through the gastrointestinal tract of humans and other animals, during processing of food products, on/in food and in the environment. We have taken a comprehensive approach to understand the basis of C. jejuni growth and within/outside host survival, with the aim to inform future development of intervention strategies. Using a genome-wide transposon gene inactivation approach we identified genes core to the growth of C. jejuni. We also determined genes that were required during the colonisation of chickens, survival in the housefly and under nutrient-rich and -poor conditions at low temperature, and during interaction with human gut epithelial tissue culture cells. This study provides a comprehensive dataset linking C. jejuni genes to growth and survival in models relevant to its life cycle. Genes important across multiple models were identified as well as genes only required under specific conditions. We identified that a large proportion of the C. jejuni genome is dedicated to growth and that the flagella fulfil a prominent role in the interaction with hosts. Our data will aid development of effective control strategies.

microbiology↗