21 results found
Bergsneider B, Bailey E, Ahmed Y, et al., 2021, Analysis of SARS-CoV-2 infection associated cell entry proteins ACE2, CD147, PPIA, and PPIB in datasets from non SARS-CoV-2 infected neuroblastoma patients, as potential prognostic and infection biomarkers in neuroblastoma., Biochem Biophys Rep, Vol: 27
SARS-CoV-2 viral contagion has given rise to a worldwide pandemic. Although most children experience minor symptoms from SARS-CoV-2 infection, some have severe complications including Multisystem Inflammatory Syndrome in Children. Neuroblastoma patients may be at higher risk of severe infection as treatment requires immunocompromising chemotherapy and SARS-CoV-2 has demonstrated tropism for nervous cells. To date, there is no sufficient epidemiological data on neuroblastoma patients with SARS-CoV-2. Therefore, we evaluated datasets of non-SARS-CoV-2 infected neuroblastoma patients to assess for key genes involved with SARS-CoV-2 infection as possible neuroblastoma prognostic and infection biomarkers. We hypothesized that ACE2, CD147, PPIA and PPIB, which are associated with viral-cell entry, are potential biomarkers for poor prognosis neuroblastoma and SARS-CoV-2 infection. We have analysed three publicly available neuroblastoma gene expression datasets to understand the specific molecular susceptibilities that high-risk neuroblastoma patients have to the virus. Gene Expression Omnibus (GEO) GSE49711 and GEO GSE62564 are the microarray and RNA-Seq data, respectively, from 498 neuroblastoma samples published as part of the Sequencing Quality Control initiative. TARGET, contains microarray data from 249 samples and is part of the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiative. ACE2, CD147, PPIA and PPIB were identified through their involvement in both SARS-CoV-2 infection and cancer pathogenesis. In-depth statistical analysis using Kaplan-Meier, differential gene expression, and Cox multivariate regression analysis, demonstrated that overexpression of ACE2, CD147, PPIA and PPIB is significantly associated with poor-prognosis neuroblastoma samples. These results were seen in the presence of amplified MYCN, unfavourable tumour histology and in patients older than 18 months of age. Previously, we have shown that high levels of t
Greenig M, Melville A, Huntley D, et al., 2020, Cross-sectional transcriptional analysis of the ageing murine heart, Frontiers in Molecular Biosciences, Vol: 7, Pages: 1-14, ISSN: 2296-889X
Cardiovascular disease accounts for millions of deaths each year and is currently the leading cause of mortality worldwide. The ageing process is clearly linked to cardiovascular disease, however, the exact relationship between ageing and heart function is not fully understood. Furthermore, a holistic view of cardiac ageing, linking features of early life development to changes observed in old age, has not been synthesized. Here, we re-purpose RNA-sequencing data previously-collected by our group, investigating gene expression differences between wild-type mice of different age groups that represent key developmental milestones in the murine lifespan. DESeq2’s generalized linear model was applied with two hypothesis6testing approaches to identify differentially-expressed (DE) genes, both between pairs of age groups and across mice of all ages. Pairwise comparisons identified genes associated with specific age transitions, while comparisons across all age groups identified a large set of genes associated with the ageing process more broadly. An unsupervised machine learning approach was then applied to extract common expression patterns from this set of age-associated genes. Sets of genes with both linear and non-linear expression trajectories were identified, suggesting that ageing not only involves the activation of gene expression programs unique to different age groups, but also the re-activation of gene expression programs from earlier ages. Overall, we present a comprehensive transcriptomic analysis of cardiac gene expression patterns across the entirety of the murine lifespan.
Maude H, Davidson M, Charitakis N, et al., 2019, NUMT confounding biases mitochondrial heteroplasmy calls in favor of the reference allele, Frontiers in Cell and Developmental Biology, Vol: 7, ISSN: 2296-634X
Homology between mitochondrial DNA (mtDNA) and nuclear DNA of mitochondrial origin (nuMTs) causes confounding when aligning short sequence reads to the reference human genome, as the true sequence origin cannot be determined. Using a systematic in silico approach, we here report the impact of all potential mitochondrial variants on alignment accuracy and variant calling. A total of 49,707 possible mutations were introduced across the 16,569bp reference mitochondrial genome (16,569 x 3 alternative alleles), one variant at-at-time. The resulting in silico fragmentation and alignment to the entire reference genome (GRCh38) revealed preferential mapping of mutated mitochondrial fragments to nuclear loci, as variants increased loci similarity to nuMTs, for a total of 807, 362 and 41 variants at 333, 144 and 27 positions when using 100bp, 150bp and 300bp single end fragments. We subsequently modelled these affected variants at 50% heteroplasmy and carried out variant calling, observing bias in the reported allele frequencies in favor of the reference allele. Four variants (chrM:6023A, chrM:4456T, chrM:5147A and chrM:7521A) including a possible hypertension factor, chrM:4456T, caused 100% loss of coverage at the mutated position (with all 100bp single-end fragments aligning to homologous, nuclear positions instead of chrM), rendering these variants undetectable when aligning to the entire reference genome. Furthermore, four mitochondrial variants reported to be pathogenic were found to cause significant loss of coverage and select Haplogroup-defining SNPs were shown to exacerbate the loss of coverage caused by surrounding variants. Increased fragment length and use of paired-end reads both improved alignment accuracy.
Mcdonald J, Kaforou M, Clare S, et al., 2016, A Simple Screening Approach To Prioritize Genes for Functional Analysis Identifies a Role for Interferon Regulatory Factor 7 in the Control of Respiratory Syncytial Virus Disease, mSystems, Vol: 1, ISSN: 2379-5077
Greater understanding of the functions of host gene products in response to infection is required. While many of these genes enable pathogen clearance, some enhance pathogen growth or contribute to disease symptoms. Many studies have profiled transcriptomic and proteomic responses to infection, generating large data sets, but selecting targets for further study is challenging. Here we propose a novel data-mining approach combining multiple heterogeneous data sets to prioritize genes for further study by using respiratory syncytial virus (RSV) infection as a model pathogen with a significant health care impact. The assumption was that the more frequently a gene is detected across multiple studies, the more important its role is. A literature search was performed to find data sets of genes and proteins that change after RSV infection. The data sets were standardized, collated into a single database, and then panned to determine which genes occurred in multiple data sets, generating a candidate gene list. This candidate gene list was validated by using both a clinical cohort and in vitro screening. We identified several genes that were frequently expressed following RSV infection with no assigned function in RSV control, including IFI27, IFIT3, IFI44L, GBP1, OAS3, IFI44, and IRF7. Drilling down into the function of these genes, we demonstrate a role in disease for the gene for interferon regulatory factor 7, which was highly ranked on the list, but not for IRF1, which was not. Thus, we have developed and validated an approach for collating published data sets into a manageable list of candidates, identifying novel targets for future analysis.
Aanensen DM, Huntley DM, Menegazzo M, et al., 2014, EpiCollect+: linking smartphones to web applications for complex data collection projects., F1000Res, Vol: 3, Pages: 199-199
Previously, we have described the development of the generic mobile phone data gathering tool, EpiCollect, and an associated web application, providing two-way communication between multiple data gatherers and a project database. This software only allows data collection on the phone using a single questionnaire form that is tailored to the needs of the user (including a single GPS point and photo per entry), whereas many applications require a more complex structure, allowing users to link a series of forms in a linear or branching hierarchy, along with the addition of any number of media types accessible from smartphones and/or tablet devices (e.g., GPS, photos, videos, sound clips and barcode scanning). A much enhanced version of EpiCollect has been developed (EpiCollect+). The individual data collection forms in EpiCollect+ provide more design complexity than the single form used in EpiCollect, and the software allows the generation of complex data collection projects through the ability to link many forms together in a linear (or branching) hierarchy. Furthermore, EpiCollect+ allows the collection of multiple media types as well as standard text fields, increased data validation and form logic. The entire process of setting up a complex mobile phone data collection project to the specification of a user (project and form definitions) can be undertaken at the EpiCollect+ website using a simple 'drag and drop' procedure, with visualisation of the data gathered using Google Maps and charts at the project website. EpiCollect+ is suitable for situations where multiple users transmit complex data by mobile phone (or other Android devices) to a single project web database and is already being used for a range of field projects, particularly public health projects in sub-Saharan Africa. However, many uses can be envisaged from education, ecology and epidemiology to citizen science.
Following the recent availability of high-coverage genomes for Denisovan and Neanderthal hominids, we conducted a screen for endogenized retroviruses, identifying six novel, previously unreported HERV-K(HML2) elements (HERV-K is human endogenous retrovirus K). These elements are absent from the human genome (hg38) and appear to be unique to archaic hominids. These findings provide further evidence supporting the recent activity of the HERV-K(HML2) group, which has been implicated in human disease. They will also provide insights into the evolution of archaic hominids.
Aanensen DM, Huntley D, Menegazzo M, et al., 2014, F1000Research/EcPlusAndroid
EpiCollect+ allows the generation of complex data collection projects and collection of multiple media types, standard text fields, increased data validation and form logic. These files contain the EpiCollect+ mobile code.
Aanensen DM, Huntley D, Menegazzo M, et al., 2014, F1000Research/EpiCollectplus
EpiCollect+ is an enhanced version of EpiCollect. This software allows the generation of complex data collection projects and collection of multiple media types, standard text fields, increased data validation and form logic.
Gendrel AV, Apedaile A, Coker H, et al., 2012, Smchd1-dependent and -independent pathways determine developmental dynamics of CpG island methylation on the inactive X chromosome., Developmental Cell, Vol: 23, Pages: 265-279
Lin B, Huntley D, AbuAli G, et al., 2011, Determining signalling nodes for apoptosis by a genetic high-throughput screen, PLoS ONE, Vol: 6, ISSN: 1932-6203
Background:With the ever-increasing information emerging from the various sequencing and gene annotation projects, there is an urgent need to elucidate the cellular functions of the newly discovered genes. The genetically regulated cell suicide of apoptosis is especially suitable for such endeavours as it is governed by a vast number of factors.Methodology/Principal Findings:We have set up a high-throughput screen in 96-well microtiter plates for genes that induce apoptosis upon their individual transfection into human cells. Upon screening approximately 100,000 cDNA clones we determined 74 genes that initiate this cellular suicide programme. A thorough bioinformatics analysis of these genes revealed that 91% are novel apoptosis regulators. Careful sequence analysis and functional annotation showed that the apoptosis factors exhibit a distinct functional distribution that distinguishes the cell death process from other signalling pathways. While only a minority of classic signal transducers were determined, a substantial number of the genes fall into the transporter- and enzyme-category. The apoptosis factors are distributed throughout all cellular organelles and many signalling circuits, but one distinct signalling pathway connects at least some of the isolated genes. Comparisons with microarray data suggest that several genes are dysregulated in specific types of cancers and degenerative diseases.Conclusions/Significance:Many unknown genes for cell death were revealed through our screen, supporting the enormous complexity of cell death regulation. Our results will serve as a repository for other researchers working with genomics data related to apoptosis or for those seeking to reveal novel signalling pathways for cell suicide.
Aanensen D, Huntley D, Powell C, et al., 2011, EpiCollect - A Mobile Phone/Web Application Framework for Epidemiological Data Collection and Visualisation, ECOHEALTH, Vol: 7, Pages: S48-S49, ISSN: 1612-9202
Huntley DM, Pandis I, Butcher SA, et al., 2010, Bioinformatic analysis of Entamoeba histolytica SINE1 elements, BMC GENOMICS, Vol: 11, ISSN: 1471-2164
Tang A, Huntley D, Montana G, et al., 2010, Efficiency of Xist-mediated silencing on autosomes is linked to chromosomal domain organisation, Epigenetics & Chromatin, Vol: 3, ISSN: 1756-8935
Background: X chromosome inactivation, the mechanism used by mammals to equalise dosage of X-linked genes inXX females relative to XY males, is triggered by chromosome-wide localisation of a cis-acting non-coding RNA, Xist. Themechanism of Xist RNA spreading and Xist-dependent silencing is poorly understood. A large body of evidenceindicates that silencing is more efficient on the X chromosome than on autosomes, leading to the idea that the Xchromosome has acquired sequences that facilitate propagation of silencing. LINE-1 (L1) repeats are relatively enrichedon the X chromosome and have been proposed as candidates for these sequences. To determine the requirements forefficient silencing we have analysed the relationship of chromosome features, including L1 repeats, and the extent ofsilencing in cell lines carrying inducible Xist transgenes located on one of three different autosomes.Results: Our results show that the organisation of the chromosome into large gene-rich and L1-rich domains is a keydeterminant of silencing efficiency. Specifically genes located in large gene-rich domains with low L1 density arerelatively resistant to Xist-mediated silencing whereas genes located in gene-poor domains with high L1 density aresilenced more efficiently. These effects are observed shortly after induction of Xist RNA expression, suggesting thatchromosomal domain organisation influences establishment rather than long-term maintenance of silencing. The Xchromosome and some autosomes have only small gene-rich L1-depleted domains and we suggest that this couldconfer the capacity for relatively efficient chromosome-wide silencing.Conclusions: This study provides insight into the requirements for efficient Xist mediated silencing and specificallyidentifies organisation of the chromosome into gene-rich L1-depleted and gene-poor L1-dense domains as a majorinfluence on the ability of Xist-mediated silencing to be propagated in a continuous manner in cis.
Aanensen DM, Huntley DM, Feil EJ, et al., 2009, EpiCollect: linking smartphones to web applications for epidemiology, ecology and community data collection, PLOS One, Vol: 4, ISSN: 1932-6203
Background:Epidemiologists and ecologists often collect data in the field and, on returning to their laboratory, enter theirdata into a database for further analysis. The recent introduction of mobile phones that utilise the open source Androidoperating system, and which include (among other features) both GPS and Google Maps, provide new opportunities fordeveloping mobile phone applications, which in conjunction with web applications, allow two-way communicationbetween field workers and their project databases.Methodology:Here we describe a generic framework, consisting of mobile phone software, EpiCollect, and a webapplication located within www.spatialepidemiology.net. Data collected by multiple field workers can be submitted byphone, together with GPS data, to a common web database and can be displayed and analysed, along with previouslycollected data, using Google Maps (or Google Earth). Similarly, data from the web database can be requested and displayedon the mobile phone, again using Google Maps. Data filtering options allow the display of data submitted by the individualfield workers or, for example, those data within certain values of a measured variable or a time period.Conclusions:Data collection frameworks utilising mobile phones with data submission to and from central databases arewidely applicable and can give a field worker similar display and analysis tools on their mobile phone that they would haveif viewing the data in their laboratory via the web. We demonstrate their utility for epidemiological data collection anddisplay, and briefly discuss their application in ecological and community data collection. Furthermore, such frameworksoffer great potential for recruiting ‘citizen scientists’ to contribute data easily to central databases through their mobilephone.
Sequeira-Mendes J, Diaz-Uriarte R, Apedaile A, et al., 2009, Transcription Initiation Activity Sets Replication Origin Efficiency in Mammalian Cells, PLOS GENETICS, Vol: 5, ISSN: 1553-7404
Wijchers PJEC, Huntley D, Kazazi D, et al., 2009, VISUALISATION OF HETEROCHROMATIN-MEDIATED SILENCING: TARGETING OF HP1 AND SUV39H1 TO CHROMOSOMAL REGIONS IN VIVO IN MAMMALS, 3rd Marie Curie-Genome Architecture in Relation to Disease Meeting (MC-GARD), Publisher: IOS PRESS, Pages: 107-107, ISSN: 1570-5870
Huntley D, Tang YA, Nesterova TB, et al., 2008, Genome Environment Browser (GEB): a dynamic browser for visualising high-throughput experimental data in the context of genome features, BMC BIOINFORMATICS, Vol: 9, ISSN: 1471-2105
Huntley D, Baldo A, Johri S, et al., 2006, SEAN: SNP prediction and display program utilizing EST sequence clusters, BIOINFORMATICS, Vol: 22, Pages: 495-496, ISSN: 1367-4803
Agrafioti I, Swire J, Abbott J, et al., 2005, Comparative analysis of the Saccharomyces cerevisiae and Caenorhabditis elegans protein interaction networks, BMC Evolutionary Biology, Vol: 5, ISSN: 1471-2148
BackgroundProtein interaction networks aim to summarize the complex interplay of proteins in an organism. Early studies suggested that the position of a protein in the network determines its evolutionary rate but there has been considerable disagreement as to what extent other factors, such as protein abundance, modify this reported dependence.ResultsWe compare the genomes of Saccharomyces cerevisiae and Caenorhabditis elegans with those of closely related species to elucidate the recent evolutionary history of their respective protein interaction networks. Interaction and expression data are studied in the light of a detailed phylogenetic analysis. The underlying network structure is incorporated explicitly into the statistical analysis. The increased phylogenetic resolution, paired with high-quality interaction data, allows us to resolve the way in which protein interaction network structure and abundance of proteins affect the evolutionary rate. We find that expression levels are better predictors of the evolutionary rate than a protein's connectivity. Detailed analysis of the two organisms also shows that the evolutionary rates of interacting proteins are not sufficiently similar to be mutually predictive.ConclusionIt appears that meaningful inferences about the evolution of protein interaction networks require comparative analysis of reasonably closely related species. The signature of protein evolution is shaped by a protein's abundance in the organism and its function and the biological process it is involved in. Its position in the interaction networks and its connectivity may modulate this but they appear to have only minor influence on a protein's evolutionary rate.
Huntley D, Hummerich H, Smedley D, et al., 2003, GANESH: Software for customized annotation of genome regions, GENOME RESEARCH, Vol: 13, Pages: 2195-2202, ISSN: 1088-9051
Witherden AS, Hafezparast M, Nicholson SJ, et al., 2002, An integrated genetic, radiation hybrid, physical and transcription map of a region of distal mouse chromosome 12, including an imprinted locus and the 'Legs at odd angles' (Loa) mutation, GENE, Vol: 283, Pages: 71-82, ISSN: 0378-1119
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