A Bayesian network structure learning approach to identify genes associated with stress in spleens of chickens

This work was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 812777Differences in the expression patterns of genes have been used to measure the effects of non-stress or stress conditions in poultry species. However, the list of genes identified can be extensive and they might be related to several biological systems. Therefore, the aim of this study was to identify a small set of genes closely associated with stress in a poultry animal model, the chicken (Gallus gallus), by reusing and combining data previously published together with bioinformatic analysis and Bayesian networks in a multi-step approach. Two datasets were collected from publicly available repositories and pre-processed. Bioinformatics analyses were performed to identify genes common to both datasets that showed differential expression patterns between non-stress and stress conditions. Bayesian networks were learnt using a Simulated Annealing algorithm implemented in the software Banjo. The structure of the Bayesian network consisted of 16 out of 19 genes together with the stress condition. Network structure showed CARD19 directly connected to the stress condition plus highlighted CYGB, BRAT1, and EPN3 as relevant, suggesting these genes could play a role in stress. The biological functionality of these genes is related to damage, apoptosis, and oxygen provision, and they could potentially be further explored as biomarkers of stress.Publisher PDFPeer reviewe

Random graphs with arbitrary clustering and their applications

The structure of many real networks is not locally treelike and, hence, network analysis fails to characterize their bond percolation properties. In a recent paper [P. Mann, V. A. Smith, J. B. O. Mitchell, and S. Dobson, arXiv:2006.06744], we developed analytical solutions to the percolation properties of random networks with homogeneous clustering (clusters whose nodes are degree equivalent). In this paper, we extend this model to investigate networks that contain clusters whose nodes are not degree equivalent, including multilayer networks. Through numerical examples, we show how this method can be used to investigate the properties of random complex networks with arbitrary clustering, extending the applicability of the configuration model and generating function formulation.Publisher PDFPeer reviewe

Male frequent attenders of general practice and their help seeking preferences

Background: Low rates of health service usage by men are commonly linked to masculine values and traditional male gender roles. However, not all men conform to these stereotypical notions of masculinity, with some men choosing to attend health services on a frequent basis, for a variety of different reasons. This study draws upon the accounts of male frequent attenders of the General Practitioner's (GP) surgery, examining their help-seeking preferences and their reasons for choosing services within general practice over other sources of support. Methods: The study extends thematic analysis of interview data from the Self Care in Primary Care study (SCinPC), a large scale multi-method evaluation study of a self care programme delivered to frequent attenders of general practice. Data were collected from 34 semi-structured interviews conducted with men prior to their exposure to the intervention. Results: The ages of interviewed men ranged from 16 to 72 years, and 91% of the sample (n= 31) stated that they had a current health condition. The thematic analysis exposed diverse perspectives within male help-seeking preferences and the decision-making behind men's choice of services. The study also draws attention to the large variation in men's knowledge of available health services, particularly alternatives to general practice. Furthermore, the data revealed some men's lack of confidence in existing alternatives to general practice. Conclusions: The study highlights the complex nature of male help-seeking preferences, and provides evidence that there should be no 'one size fits all' approach to male service provision. It also provides impetus for conducting further studies into this under researched area of interest. © 2011 WPMH GmbH

Genome Sequence of the Chestnut Blight Fungus Cryphonectria parasitica EP155: A Fundamental Resource for an Archetypical Invasive Plant Pathogen.

Cryphonectria parasitica is the causal agent of chestnut blight, a fungal disease that almost entirely eliminated mature American chestnut from North America over a 50-year period. Here, we formally report the genome of C. parasitica EP155 using a Sanger shotgun sequencing approach. After finishing and integration with simple-sequence repeat markers, the assembly was 43.8 Mb in 26 scaffolds (L50 = 5; N50 = 4.0Mb). Eight chromosomes are predicted: five scaffolds have two telomeres and six scaffolds have one telomere sequence. In total, 11,609 gene models were predicted, of which 85% show similarities to other proteins. This genome resource has already increased the utility of a fundamental plant pathogen experimental system through new understanding of the fungal vegetative incompatibility system, with significant implications for enhancing mycovirus-based biological control

Dynamic modulation of phosphoprotein expression in ovarian cancer xenograft models

The authors thank Medical Research Scotland and the Scottish Funding Council. This work was su pported by Medical Research Scotland [FRG353 to V.A.S.]; the FP7 -­‐ Directorate -­‐ General for Research and Innovation of the European Commission [EU HEALTH -­‐ F4 -­‐ 2012 -­‐ 305033 to Coordinating Action Systems Medicine -­‐ D.J.H.]; the Chief Scientist Office of Scotland [D.J.H.], the Scottish Funding Council [D.J.H. and S.P.L.]. Health Canada Scholarship (Indspire) [KEF], Scottish Overseas Research Student Award Scheme (University of Edinburgh)[KEF] and the Three Fires Award (Wikwemikong Board of Education)[KEF].Background: The dynamic changes that occur in protein expression after treatment of a cancer in vivo are poorly described. In this study we measure the effect of chemotherapy over time on the expression of a panel of proteins in ovarian cancer xenograft models. The objective was to identify phosphoprotein and other protein changes indicative of pathway activation that might link with drug response. Methods: Two xenograft models, platinum-responsive OV1002 and platinum-unresponsive HOX424, were used. Treatments were carboplatin and carboplatin-paclitaxel. Expression of 49 proteins over 14 days post treatment was measured by quantitative immunofluorescence and analysed by AQUA . Results: Carboplatin treatment in the platinum-sensitive OV1002 model triggered up-regulation of cell cycle, mTOR and DDR pathways, while at late time points WNT, invasion , EMT and MAPK pathways were modulated. Estrogen receptor-alpha (ESR1) and ERBB pathways were down-regulated early, within 24h from treatment administration. Combined carboplatin-paclitaxel treatment triggered a more extensive response in the OV1002 model modulating expression of 23 of 49 proteins. Therefore the cell cycle and DDR pathways showed similar or more pronounced changes than with carboplatin alone . In addition to expression of pS6 and pERK increasing, components of the AKT pathway were modulated with pAKT increasing while its regulator PTEN was down-regulated early. WNT signaling, EMT and invasion markers were modulated at later time points. Additional pathways were also observed with the NFκB and JAK/STAT pathways being up-regulated. ESR1 was down-regulated as was HER4, while further protein members of the ERB B pathway were upregulated late. By contrast, in the carboplatin-unresponsive HOX 424 xenograft, carboplatin only modulated expression of MLH1 while carboplatin-paclitaxel treatment modulated ESR1 and pMET.Publisher PDFPeer reviewe

Inference of Circadian Regulatory Networks

Abstract. We assess the accuracy of various state-of-the-art methods for reconstructing gene and protein regulatory networks in the context of circadian regulation. Gene expression and protein concentration time series are simulated from a recently published regulatory network of the circadian clock in A. thaliana, which is mathematically described by a Markov jump process based on Michaelis-Menten kinetics. Our study provides relative network reconstruction accuracy scores for a critical comparative performance evaluation, quantifies the influence of systematically missing values related to unknown protein concentrations and mRNA transcription rates, and investigates the dependence of the performance on the network topology and the degree of recurrency. An application to recent gene expression time series from qPCR experiments suggests new hypotheses about the structure of the central circadian gene regulatory network in A. thaliana