Integration of Liver Gene Coexpression Networks and Egwas Analyses
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Negative Regulation of Diacylglycerol Kinase &Theta
Cell Death and Differentiation (2010) 17, 1059–1068 & 2010 Macmillan Publishers Limited All rights reserved 1350-9047/10 $32.00 www.nature.com/cdd Negative regulation of diacylglycerol kinase h mediates adenosine-dependent hepatocyte preconditioning G Baldanzi1,5, E Alchera2,5, C Imarisio2, M Gaggianesi1, C Dal Ponte2, M Nitti3, C Domenicotti3, WJ van Blitterswijk4, E Albano2, A Graziani1,5 and R Carini*,2,5 In liver ischemic preconditioning (IP), stimulation of adenosine A2a receptors (A2aR) prevents ischemia/reperfusion injury by promoting diacylglycerol-mediated activation of protein kinase C (PKC). By concerting diacylglycerol to phosphatidic acid, diacylglycerol kinases (DGKs) act as terminator of diacylglycerol signalling. This study investigates the role of DGK in the development of hepatocyte IP. DGK activity and cell viability were evaluated in isolated rat hepatocytes preconditioned by 10 min hypoxia followed by 10 min re-oxygenation or by the treatment with the A2aR agonist, CGS21680, and subsequently exposed to prolonged hypoxia. We observed that after IP or A2aR activation, a decrease in DGK activity was associated with the onset of hepatocyte tolerance to hypoxia. CGS21680-induced stimulation of A2aR specifically inhibited DGK isoform h by activating RhoA–GTPase. Consistently, both siRNA-mediated downregulation of DGK h and hepatocyte pretreatment with the DGK inhibitor R59949 induced cell tolerance to hypoxia. The pharmacological inhibition of DGK was associated with the diacylglycerol- dependent activation of PKC d and e and of their downstream target p38 MAPK. In conclusion, we unveil a novel signalling pathway contributing to the onset of hepatocyte preconditioning, which through RhoA–GTPase, couples A2aR to the downregulation of DGK. -
Mapping of Diabetes Susceptibility Loci in a Domestic Cat Breed with an Unusually High Incidence of Diabetes Mellitus
G C A T T A C G G C A T genes Article Mapping of Diabetes Susceptibility Loci in a Domestic Cat Breed with an Unusually High Incidence of Diabetes Mellitus 1,2, 3, 4 5 Lois Balmer y , Caroline Ann O’Leary y, Marilyn Menotti-Raymond , Victor David , Stephen O’Brien 6,7, Belinda Penglis 8, Sher Hendrickson 9, Mia Reeves-Johnson 3, 3 10 3 3,11, Susan Gottlieb , Linda Fleeman , Dianne Vankan , Jacquie Rand z and 1, , Grant Morahan * z 1 Centre for Diabetes Research, Harry Perkins Institute for Medical Research, University of Western Australia, Nedlands 6009, Australia; [email protected] 2 School of Medical and Health Sciences, Edith Cowan University, Joondalup, Perth 6027, Australia 3 School of Veterinary Science, the University of Queensland, Gottan 4343, Australia; [email protected] (C.A.O.); [email protected] (M.R.-J.); [email protected] (S.G.); [email protected] (D.V.); [email protected] (J.R.) 4 Laboratory of Genomic Diversity, Center for Cancer Research (FNLCR), Frederick, MD 21702, USA; [email protected] 5 Laboratory of Basic Research, Center for Cancer Research (FNLCR), National Cancer Institute, Frederick, MD 21702, USA; [email protected] 6 Laboratory of Genomics Diversity, Center for Computer Technologies, ITMO University, 197101 St. Petersburg, Russia; [email protected] 7 Guy Harvey Oceanographic Center, Halmos College of Arts and Sciences, Nova Southeastern University, Ft Lauderdale, FL 33004, USA 8 IDEXX Laboratories, East Brisbane 4169, Australia; [email protected] 9 Department of Biology, Shepherd University, Shepherdstown, WV 25443, USA; [email protected] 10 Animal Diabetes Australia, Melbourne 3155, Australia; l.fl[email protected] 11 American College of Veterinary Internal Medicine, University of Zurich, 8006 Zurich, Switzerland * Correspondence: [email protected] These authors contributed equally to this work. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
The Roles of Diacylglycerol Kinases in the Central Nervous System: Review of Genetic Studies in Mice
J Pharmacol Sci 124, 000 – 000 (2014) Journal of Pharmacological Sciences © The Japanese Pharmacological Society Critical Review The Roles of Diacylglycerol Kinases in the Central Nervous System: Review of Genetic Studies in Mice Mitsue Ishisaka1 and Hideaki Hara1,* 1Molecular Pharmacology, Department of Biofunctional Evaluation, Gifu Pharmaceutical University, Gifu 501-1196, Japan Received November 12, 2013; Accepted January 23, 2014 Abstract. Diacylglycerol kinase (DGK) is an enzyme that converts diacylglycerol to phosphatidic acid. To date, 10 isoforms of DGKs (a, b, g, d, e, z, h, q, i, and k) have been identified in mammals, and these DGKs show characteristic expression patterns and roles. The expression levels of DGKs are comparatively higher in the central nervous system than in other organs and may play several important roles in regulating higher brain functions. Currently, many studies have been performed to reveal the roles of DGKs by knocking down or overexpression of DGKs in vitro. Additionally, knockout or overexpression mice of several DGKs have been generated, and phenotypes of these mice have been studied. In this review, we discuss the roles of DGKs in the central nervous system based on recent findings in genetic models. Keywords: central nervous system, diacylglycerol kinase, genetic mouse, mood disorder 1. Introduction DGKs play unique roles in each isoform. To demonstrate the functions of DGKs, many studies After Gq protein–coupled receptors are stimulated, have been performed using a genetic approach in vitro phospholipase C is activated and produces diacylglycerol and in vivo. To date, several overexpression or knockout (DG) from inositol phospholipids (1). DG is an essential (KO)mice have been generated by many research second messenger in mammalian cells and plays impor groups: DGKaKO (23), cardiacspecific overexpression tant roles in gene transcription, lipid signaling, cyto of DGKa (24), DGKbKO (25), DGKdKO (26), DGKe skeletal dynamics, intracellular membrane trafficking, KO (27), DGKzKO (28), and DGKiKO mice (29). -
Effects of Chronic Stress on Prefrontal Cortex Transcriptome in Mice Displaying Different Genetic Backgrounds
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Springer - Publisher Connector J Mol Neurosci (2013) 50:33–57 DOI 10.1007/s12031-012-9850-1 Effects of Chronic Stress on Prefrontal Cortex Transcriptome in Mice Displaying Different Genetic Backgrounds Pawel Lisowski & Marek Wieczorek & Joanna Goscik & Grzegorz R. Juszczak & Adrian M. Stankiewicz & Lech Zwierzchowski & Artur H. Swiergiel Received: 14 May 2012 /Accepted: 25 June 2012 /Published online: 27 July 2012 # The Author(s) 2012. This article is published with open access at Springerlink.com Abstract There is increasing evidence that depression signaling pathway (Clic6, Drd1a,andPpp1r1b). LA derives from the impact of environmental pressure on transcriptome affected by CMS was associated with genetically susceptible individuals. We analyzed the genes involved in behavioral response to stimulus effects of chronic mild stress (CMS) on prefrontal cor- (Fcer1g, Rasd2, S100a8, S100a9, Crhr1, Grm5,and tex transcriptome of two strains of mice bred for high Prkcc), immune effector processes (Fcer1g, Mpo,and (HA)and low (LA) swim stress-induced analgesia that Igh-VJ558), diacylglycerol binding (Rasgrp1, Dgke, differ in basal transcriptomic profiles and depression- Dgkg,andPrkcc), and long-term depression (Crhr1, like behaviors. We found that CMS affected 96 and 92 Grm5,andPrkcc) and/or coding elements of dendrites genes in HA and LA mice, respectively. Among genes (Crmp1, Cntnap4,andPrkcc) and myelin proteins with the same expression pattern in both strains after (Gpm6a, Mal,andMog). The results indicate significant CMS, we observed robust upregulation of Ttr gene contribution of genetic background to differences in coding transthyretin involved in amyloidosis, seizures, stress response gene expression in the mouse prefrontal stroke-like episodes, or dementia. -
Identification of the Differentially Expressed Genes Associated with Familial Combined Hyperlipidemia Using Bioinformatics Analysis
4032 MOLECULAR MEDICINE REPORTS 11: 4032-4038, 2015 Identification of the differentially expressed genes associated with familial combined hyperlipidemia using bioinformatics analysis XIAOLI LUO, CHANGQING YU, CHUNJIANG FU, WEIBIN SHI, XUKAI WANG, CHUNYU ZENG and HONGYONG WANG Department of Cardiology, Daping Hospital, The Third Military Medical University, Chongqing Institute of Cardiology, Chongqing 400042, P.R. China Received February 12, 2014; Accepted November 18, 2014 DOI: 10.3892/mmr.2015.3263 Abstract. The aim of the present study was to screen the pathogenesis of FCHL in future studies. However, further differentially expressed genes (DEGs) associated with experiments are required to confirm these results. familial combined hyperlipidemia (FCHL) and examine the changing patterns. The transcription profile of GSE18965 was Introduction obtained from the NCBI Gene Expression Omnibus data- base, including 12 FCHL samples and 12 control specimens. Familial combined hyperlipidemia (FCHL), the most common The DEGs were identified using a linear models for micro- genetic form of hyperlipidemia, is characterized by significant array data package in the R programming language. Gene familial clustering and premature coronary heart disease (1). Ontology (GO) function and Kyoto Encyclopedia of Genes FCHL is a common inherited disorder of lipid metabolism and Genomes (KEGG) pathway enrichment analysis was with a prevalence of 0.5‑2.0%, accounting for 10% of the cases also performed. Protein-protein interaction (PPI) networks of premature coronary heart disease worldwide (2). Therefore, of the DEGs were constructed using the EnrichNet online the research and treatment of FCHL has significance for tool. In addition, cluster analysis of the genes in networks human health. -
Network-Based Method for Drug Target Discovery at the Isoform Level
www.nature.com/scientificreports OPEN Network-based method for drug target discovery at the isoform level Received: 20 November 2018 Jun Ma1,2, Jenny Wang2, Laleh Soltan Ghoraie2, Xin Men3, Linna Liu4 & Penggao Dai 1 Accepted: 6 September 2019 Identifcation of primary targets associated with phenotypes can facilitate exploration of the underlying Published: xx xx xxxx molecular mechanisms of compounds and optimization of the structures of promising drugs. However, the literature reports limited efort to identify the target major isoform of a single known target gene. The majority of genes generate multiple transcripts that are translated into proteins that may carry out distinct and even opposing biological functions through alternative splicing. In addition, isoform expression is dynamic and varies depending on the developmental stage and cell type. To identify target major isoforms, we integrated a breast cancer type-specifc isoform coexpression network with gene perturbation signatures in the MCF7 cell line in the Connectivity Map database using the ‘shortest path’ drug target prioritization method. We used a leukemia cancer network and diferential expression data for drugs in the HL-60 cell line to test the robustness of the detection algorithm for target major isoforms. We further analyzed the properties of target major isoforms for each multi-isoform gene using pharmacogenomic datasets, proteomic data and the principal isoforms defned by the APPRIS and STRING datasets. Then, we tested our predictions for the most promising target major protein isoforms of DNMT1, MGEA5 and P4HB4 based on expression data and topological features in the coexpression network. Interestingly, these isoforms are not annotated as principal isoforms in APPRIS. -
Supplementary Figure 1. Dystrophic Mice Show Unbalanced Stem Cell Niche
Supplementary Figure 1. Dystrophic mice show unbalanced stem cell niche. (A) Single channel images for the merged panels shown in Figure 1A, for of PAX7, MYOD and Laminin immunohistochemical staining in Lmna Δ8-11 mice of PAX7 and MYOD markers at the indicated days of post-natal growth. Basement membrane of muscle fibers was stained with Laminin. Scale bars, 50 µm. (B) Quantification of the % of PAX7+ MuSCs per 100 fibers at the indicated days of post-natal growth in (A). n =3-6 animals per genotype. (C) Immunohistochemical staining in Lmna Δ8-11 mice of activated, ASCs (PAX7+/KI67+) and quiescent QSCs (PAX7+/Ki67-) MuSCs at d19 and relative quantification (below). n= 4-6 animals per genotype. Scale bars, 50 µm. (D) Quantification of the number of cells per cluster in single myofibers extracted from d19 Lmna Δ8-11 mice and cultured 96h. n= 4-5 animals per group. Data are box with median and whiskers min to max. B, C, Data are mean ± s.e.m. Statistics by one-way (B) or two-way (C, D) analysis of variance (ANOVA) with multiple comparisons. * * P < 0.01, * * * P < 0.001. wt= Lmna Δ8-11 +/+; het= Lmna Δ8-11 +/; hom= Lmna Δ8-11 -/-. Supplementary Figure 2. Heterozygous mice show intermediate Lamin A levels. (A) RNA-seq signal tracks as the effective genome size normalized coverage of each biological replicate of Lmna Δ8-11 mice on Lmna locus. Neomycine cassette is indicated as a dark blue rectangle. (B) Western blot of total protein extracted from the whole Lmna Δ8-11 muscles at d19 hybridized with indicated antibodies. -
Revealing Host Factors Important for Hepatocyte Infection by Plasmodium
Universidade de Lisboa Faculdade de Ciências Departamento de Biologia Vegetal Revealing Host Factors Important for Hepatocyte Infection by Plasmodium Cristina Dias Rodrigues Doutoramento em Biologia Biologia Celular 2007 Cover image | An Anopheles gambiae female mosquito feeding on a mammalian host (adapted from http://www.abc.net.au/science/news/img/health/mosquito190804.jpg). Universidade de Lisboa Faculdade de Ciências Departamento de Biologia Vegetal Revealing Host Factors Important for Hepatocyte Infection by Plasmodium. Cristina Dias Rodrigues Dissertation submitted to obtain a PhD Degree in Biology, speciality of Cellular Biology by the Universidade de Lisboa. Supervisor Maria Manuel Mota, MsD, PhD. Principal Investigator of Instituto de Medicina Molecular and Auxiliary Professor at Faculdade de Medicina, Universidade de Lisboa. Co-Supervisor Maria da Graça Alves Vieira, PhD. Auxiliary Professor of Faculdade de Ciências, Universidade de Lisboa. Research is to see what everybody else has seen, and to think what nobody else has thought. Albert Szent-Györgi All truths are easy to understand once they are discovered; the point is to discover them. Galileo Galilei Preface The present thesis embraces the data obtained during my Ph.D. research project developed from November 2003 to June 2007. The experimental work was supervised by Prof. Doutora Maria Manuel Mota and was carried out at Instituto de Medicina Molecular, in Lisboa and Instituto Gulbenkian de Ciência, in Oeiras, Portugal. The RNAi screens were performed at Cenix BioScience, Dresden, Germany. This Ph.D. was supervised by Prof. Maria da Graça Alves Vieira from Departamento de Biologia Vegetal, Faculdade de Ciências, Universidade de Lisboa, Portugal. The financial support was provided by the portuguese Fundação para a Ciência e Tecnologia, through the Ph.D. -
Expression-Based GWAS Identifies Variants, Gene Interactions and Key
www.nature.com/scientificreports OPEN Expression-based GWAS identifies variants, gene interactions and key regulators affecting intramuscular Received: 12 February 2016 Accepted: 26 July 2016 fatty acid content and composition Published: 18 August 2016 in porcine meat Anna Puig-Oliveras1,2, Manuel Revilla1,2, Anna Castelló1,2, Ana I. Fernández3, Josep M. Folch1,2 & Maria Ballester1,2,4 The aim of this work is to better understand the genetic mechanisms determining two complex traits affecting porcine meat quality: intramuscular fat (IMF) content and its fatty acid (FA) composition. With this purpose, expression Genome-Wide Association Study (eGWAS) of 45 lipid-related genes associated with meat quality traits in swine muscle (Longissimus dorsi) of 114 Iberian × Landrace backcross animals was performed. The eGWAS identified 241 SNPs associated with 11 genes:ACSM5, CROT, FABP3, FOS, HIF1AN, IGF2, MGLL, NCOA1, PIK3R1, PLA2G12A and PPARA. Three expression Quantitative Trait Loci (eQTLs) for IGF2, ACSM5 and MGLL were identified, showingcis -acting effects, whereas 16 eQTLs had trans regulatory effects. A polymorphism in theACSM5 promoter region associated with its expression was identified. In addition, strong candidate genes regulatingACSM5, FOS, PPARA, PIK3R1, PLA2G12A and HIF1AN gene expression were also seen. Notably, the analysis highlighted the NR3C1 transcription factor as a strong candidate gene involved in the regulation of the 45 genes analysed. Finally, the IGF2, MGLL, MC2R, ARHGAP6, and NR3C1 genes were identified as potential regulators co-localizing within QTLs for fatness and growth traits in the IBMAP population. The results obtained increase our knowledge in the functional regulatory mechanisms involved in these complex traits. Pork-meat cuts and their derived products are paid according to the lean percentage in pork carcasses and meat quality, since they determine better acceptance for consumers1. -
RNA-Seq and GSEA Identifies Suppression of Ligand-Gated
www.nature.com/scientificreports OPEN RNA‑seq and GSEA identifes suppression of ligand‑gated chloride efux channels as the major gene pathway contributing to form deprivation myopia Loretta Giummarra Vocale1,4*, Sheila Crewther1, Nina Riddell1, Nathan E. Hall1,2, Melanie Murphy1 & David Crewther1,3 Currently there is no consensus regarding the aetiology of the excessive ocular volume that characterizes high myopia. Thus, we aimed to test whether the gene pathways identifed by gene set enrichment analysis of RNA‑seq transcriptomics refutes the predictions of the Retinal Ion Driven Efux (RIDE) hypothesis when applied to the induction of form‑deprivation myopia (FDM) and subsequent recovery (post‑occluder removal). We found that the induction of profound FDM led to signifcant suppression in the ligand‑gated chloride ion channel transport pathway via suppression of glycine, GABAA and GABAC ionotropic receptors. Post‑occluder removal for short term recovery from FDM of 6 h and 24 h, induced signifcant upregulation of the gene families linked to cone receptor phototransduction, mitochondrial energy, and complement pathways. These fndings support a model of form deprivation myopia as a Cl− ion driven adaptive fuid response to the modulation of the visual signal cascade by form deprivation that in turn afects the resultant ionic environment of the outer and inner retinal tissues, axial and vitreal elongation as predicted by the RIDE model. Occluder removal and return to normal light conditions led to return to more normal upregulation of phototransduction, slowed growth rate, refractive recovery and apparent return towards physiological homeostasis. Myopia (short-sightedness) is the most common visual disorder worldwide and the greatest risk factor for severe ophthalmic diseases in older individuals especially those with high (-5D) refractive errors1. -
Supplemental Figures 04 12 2017
Jung et al. 1 SUPPLEMENTAL FIGURES 2 3 Supplemental Figure 1. Clinical relevance of natural product methyltransferases (NPMTs) in brain disorders. (A) 4 Table summarizing characteristics of 11 NPMTs using data derived from the TCGA GBM and Rembrandt datasets for 5 relative expression levels and survival. In addition, published studies of the 11 NPMTs are summarized. (B) The 1 Jung et al. 6 expression levels of 10 NPMTs in glioblastoma versus non‐tumor brain are displayed in a heatmap, ranked by 7 significance and expression levels. *, p<0.05; **, p<0.01; ***, p<0.001. 8 2 Jung et al. 9 10 Supplemental Figure 2. Anatomical distribution of methyltransferase and metabolic signatures within 11 glioblastomas. The Ivy GAP dataset was downloaded and interrogated by histological structure for NNMT, NAMPT, 12 DNMT mRNA expression and selected gene expression signatures. The results are displayed on a heatmap. The 13 sample size of each histological region as indicated on the figure. 14 3 Jung et al. 15 16 Supplemental Figure 3. Altered expression of nicotinamide and nicotinate metabolism‐related enzymes in 17 glioblastoma. (A) Heatmap (fold change of expression) of whole 25 enzymes in the KEGG nicotinate and 18 nicotinamide metabolism gene set were analyzed in indicated glioblastoma expression datasets with Oncomine. 4 Jung et al. 19 Color bar intensity indicates percentile of fold change in glioblastoma relative to normal brain. (B) Nicotinamide and 20 nicotinate and methionine salvage pathways are displayed with the relative expression levels in glioblastoma 21 specimens in the TCGA GBM dataset indicated. 22 5 Jung et al. 23 24 Supplementary Figure 4.