Chemico-Biological Interactions 196 (2012) 89–95
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Genome-Wide Analysis of 5-Hmc in the Peripheral Blood of Systemic Lupus Erythematosus Patients Using an Hmedip-Chip
INTERNATIONAL JOURNAL OF MOLECULAR MEDICINE 35: 1467-1479, 2015 Genome-wide analysis of 5-hmC in the peripheral blood of systemic lupus erythematosus patients using an hMeDIP-chip WEIGUO SUI1*, QIUPEI TAN1*, MING YANG1, QIANG YAN1, HUA LIN1, MINGLIN OU1, WEN XUE1, JIEJING CHEN1, TONGXIANG ZOU1, HUANYUN JING1, LI GUO1, CUIHUI CAO1, YUFENG SUN1, ZHENZHEN CUI1 and YONG DAI2 1Guangxi Key Laboratory of Metabolic Diseases Research, Central Laboratory of Guilin 181st Hospital, Guilin, Guangxi 541002; 2Clinical Medical Research Center, the Second Clinical Medical College of Jinan University (Shenzhen People's Hospital), Shenzhen, Guangdong 518020, P.R. China Received July 9, 2014; Accepted February 27, 2015 DOI: 10.3892/ijmm.2015.2149 Abstract. Systemic lupus erythematosus (SLE) is a chronic, Introduction potentially fatal systemic autoimmune disease characterized by the production of autoantibodies against a wide range Systemic lupus erythematosus (SLE) is a typical systemic auto- of self-antigens. To investigate the role of the 5-hmC DNA immune disease, involving diffuse connective tissues (1) and modification with regard to the onset of SLE, we compared is characterized by immune inflammation. SLE has a complex the levels 5-hmC between SLE patients and normal controls. pathogenesis (2), involving genetic, immunologic and envi- Whole blood was obtained from patients, and genomic DNA ronmental factors. Thus, it may result in damage to multiple was extracted. Using the hMeDIP-chip analysis and valida- tissues and organs, especially the kidneys (3). SLE arises from tion by quantitative RT-PCR (RT-qPCR), we identified the a combination of heritable and environmental influences. differentially hydroxymethylated regions that are associated Epigenetics, the study of changes in gene expression with SLE. -
Identifying Novel Disease-Associated Variants and Understanding The
Identifying Novel Disease-variants and Understanding the Role of the STAT1-STAT4 Locus in SLE A dissertation submitted to the Graduate School of University of Cincinnati In partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Immunology Graduate Program of the College of Medicine by Zubin H. Patel B.S., Worcester Polytechnic Institute, 2009 John B. Harley, M.D., Ph.D. Committee Chair Gurjit Khurana Hershey, M.D., Ph.D Leah C. Kottyan, Ph.D. Harinder Singh, Ph.D. Matthew T. Weirauch, Ph.D. Abstract Systemic Lupus Erythematosus (SLE) or lupus is an autoimmune disorder caused by an overactive immune system with dysregulation of both innate and adaptive immune pathways. It can affect all major organ systems and may lead to inflammation of the serosal and mucosal surfaces. The pathogenesis of lupus is driven by genetic factors, environmental factors, and gene-environment interactions. Heredity accounts for a substantial proportion of SLE risk, and the role of specific genetic risk loci has been well established. Identifying the specific causal genetic variants and the underlying molecular mechanisms has been a major area of investigation. This thesis describes efforts to develop an analytical approach to identify candidate rare variants from trio analyses and a fine-mapping analysis at the STAT1-STAT4 locus, a well-replicated SLE-risk locus. For the STAT1-STAT4 locus, subsequent functional biological studies demonstrated genotype dependent gene expression, transcription factor binding, and DNA regulatory activity. Rare variants are classified as variants across the genome with an allele-frequency less than 1% in ancestral populations. -
Anti-PPAP2A (Internal) Polyclonal Antibody (CABT- B799) This Product Is for Research Use Only and Is Not Intended for Diagnostic Use
Anti-PPAP2A (Internal) polyclonal antibody (CABT- B799) This product is for research use only and is not intended for diagnostic use. PRODUCT INFORMATION Target PPAP2A Immunogen Synthetic peptide Isotype IgG Source/Host Rabbit Species Reactivity Human, Mouse, Zebrafish Purification Protein A Purified Total IgG Conjugate Unconjugated Applications IHC, WB Format Liquid Concentration 1 mg/ml (Please refer to the vial label for the specific concentration) Size 100 μg Buffer Phosphate buffered saline (PBS) Preservative None Storage Store at 4°C for short-term use. For longer periods of storage, aliquot and store at -20°C. Avoid repeat freeze-thaw cycles. BACKGROUND Introduction PPAP2A is a member of the phosphatidic acid phosphatase (PAP) family. PAPs convert phosphatidic acid to diacylglycerol, and function in de novo synthesis of glycerolipids as well as in receptor-activated signal transduction mediated by phospholipase D. This protein is an integral membrane glycoprotein, and has been shown to be a surface enzyme that plays an active role in the hydrolysis and uptake of lipids from extracellular space. The expression of PPAP2A is found to be regulated by androgen in a prostatic adenocarcinoma cell line.The protein encoded by this 45-1 Ramsey Road, Shirley, NY 11967, USA Email: [email protected] Tel: 1-631-624-4882 Fax: 1-631-938-8221 1 © Creative Diagnostics All Rights Reserved gene is a member of the phosphatidic acid phosphatase (PAP) family. PAPs convert phosphatidic acid to diacylglycerol, and function in de novo synthesis of glycerolipids as well as in receptor-activated signal transduction mediated by phospholipase D. This protein is an integral membrane glycoprotein, and has been shown to be a surface enzyme that plays an active role in the hydrolysis and uptake of lipids from extracellular space. -
Supplementary Information
Supplementary Information PathwayMatcher: multi-omics pathway mapping and proteoform network generation Luis Francisco Hernández Sánchez1,2,3, Bram Burger4,5, Carlos Horro4,5, Antonio Fabregat3, Stefan Johansson1,2, Pål Rasmus Njølstad1,6, Harald Barsnes4,5, Henning Hermjakob3,7, and Marc Vaudel1,2,* 1 K.G. Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Norway 2 Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway 3 European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom 4 Proteomics Unit, Department of Biomedicine, University of Bergen, Bergen, Norway 5 Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway 6 Department of Pediatrics, Haukeland University Hospital, Bergen, Norway 7 Beijing Proteome Research Center, National Center for Protein Sciences Beijing, Beijing, China * To whom correspondence should be addressed Abstract Mapping biomedical data to functional knowledge is an essential task in biomedicine and can be achieved by querying gene or protein identifiers in pathway knowledgebases. Here, we demonstrate that including fine-granularity information such as post-translational modifications greatly increases the specificity of the analysis. We present PathwayMatcher (github.com/PathwayAnalysisPlatform/PathwayMatcher), a bioinformatic application for mapping multi-omics data to pathways and show how this enables the -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
Two Locus Inheritance of Non-Syndromic Midline Craniosynostosis Via Rare SMAD6 and 4 Common BMP2 Alleles 5 6 Andrew T
1 2 3 Two locus inheritance of non-syndromic midline craniosynostosis via rare SMAD6 and 4 common BMP2 alleles 5 6 Andrew T. Timberlake1-3, Jungmin Choi1,2, Samir Zaidi1,2, Qiongshi Lu4, Carol Nelson- 7 Williams1,2, Eric D. Brooks3, Kaya Bilguvar1,5, Irina Tikhonova5, Shrikant Mane1,5, Jenny F. 8 Yang3, Rajendra Sawh-Martinez3, Sarah Persing3, Elizabeth G. Zellner3, Erin Loring1,2,5, Carolyn 9 Chuang3, Amy Galm6, Peter W. Hashim3, Derek M. Steinbacher3, Michael L. DiLuna7, Charles 10 C. Duncan7, Kevin A. Pelphrey8, Hongyu Zhao4, John A. Persing3, Richard P. Lifton1,2,5,9 11 12 1Department of Genetics, Yale University School of Medicine, New Haven, CT, USA 13 2Howard Hughes Medical Institute, Yale University School of Medicine, New Haven, CT, USA 14 3Section of Plastic and Reconstructive Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT, USA 15 4Department of Biostatistics, Yale University School of Medicine, New Haven, CT, USA 16 5Yale Center for Genome Analysis, New Haven, CT, USA 17 6Craniosynostosis and Positional Plagiocephaly Support, New York, NY, USA 18 7Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA 19 8Child Study Center, Yale University School of Medicine, New Haven, CT, USA 20 9The Rockefeller University, New York, NY, USA 21 22 ABSTRACT 23 Premature fusion of the cranial sutures (craniosynostosis), affecting 1 in 2,000 24 newborns, is treated surgically in infancy to prevent adverse neurologic outcomes. To 25 identify mutations contributing to common non-syndromic midline (sagittal and metopic) 26 craniosynostosis, we performed exome sequencing of 132 parent-offspring trios and 59 27 additional probands. -
CD56+ T-Cells in Relation to Cytomegalovirus in Healthy Subjects and Kidney Transplant Patients
CD56+ T-cells in Relation to Cytomegalovirus in Healthy Subjects and Kidney Transplant Patients Institute of Infection and Global Health Department of Clinical Infection, Microbiology and Immunology Thesis submitted in accordance with the requirements of the University of Liverpool for the degree of Doctor in Philosophy by Mazen Mohammed Almehmadi December 2014 - 1 - Abstract Human T cells expressing CD56 are capable of tumour cell lysis following activation with interleukin-2 but their role in viral immunity has been less well studied. The work described in this thesis aimed to investigate CD56+ T-cells in relation to cytomegalovirus infection in healthy subjects and kidney transplant patients (KTPs). Proportions of CD56+ T cells were found to be highly significantly increased in healthy cytomegalovirus-seropositive (CMV+) compared to cytomegalovirus-seronegative (CMV-) subjects (8.38% ± 0.33 versus 3.29%± 0.33; P < 0.0001). In donor CMV-/recipient CMV- (D-/R-)- KTPs levels of CD56+ T cells were 1.9% ±0.35 versus 5.42% ±1.01 in D+/R- patients and 5.11% ±0.69 in R+ patients (P 0.0247 and < 0.0001 respectively). CD56+ T cells in both healthy CMV+ subjects and KTPs expressed markers of effector memory- RA T-cells (TEMRA) while in healthy CMV- subjects and D-/R- KTPs the phenotype was predominantly that of naïve T-cells. Other surface markers, CD8, CD4, CD58, CD57, CD94 and NKG2C were expressed by a significantly higher proportion of CD56+ T-cells in healthy CMV+ than CMV- subjects. Functional studies showed levels of pro-inflammatory cytokines IFN-γ and TNF-α, as well as granzyme B and CD107a were significantly higher in CD56+ T-cells from CMV+ than CMV- subjects following stimulation with CMV antigens. -
Identification and Expression of the Laboratory of Genetics and Physiology 2 Gene in Common Carp Cyprinus Carpio
Journal of Fish Biology (2014) doi:10.1111/jfb.12541, available online at wileyonlinelibrary.com Identification and expression of the laboratory of genetics and physiology 2 gene in common carp Cyprinus carpio X. L. Cao*†, J. J. Chen†,Y.Cao†,G.X.Nie†,Q.Y.Wan*,L.F.Wang† and J. G. Su*‡ *College of Animal Science and Technology, Northwest A&F University, Yangling 712100, People’s Republic of China and †College of Fisheries, Henan Normal University, Xinxiang 453007, People’s Republic of China (Received 29 April 2014, Accepted 9 September 2014) In this study, a laboratory of genetics and physiology 2 gene (lgp2) from common carp Cyprinus car- pio was isolated and characterized. The full-length complementary (c)DNA of lgp2 was 3061 bp and encoded a polypeptide of 680 amino acids, with an estimated molecular mass of 77 341⋅2Daanda predicted isoelectric point of 6⋅53. The predicted protein included four main overlapping structural domains: a conserved restriction domain of bacterial type III restriction enzyme, a DEAD–DEAH box helicase domain, a helicase super family C-terminal domain and a regulatory domain. Real-time quantitative polymerase chain reaction (PCR) showed widespread expression of lgp2, mitochondrial antiviral signalling protein (mavs) and interferon transcription factor 3 (irf3) in tissues of nine organs. lgp2, mavs and irf3 expression levels were significantly induced in all examined organs by infec- tion with koi herpesvirus (KHV). lgp2, mavs and irf3 messenger (m)RNA levels were significantly up-regulated in vivo after KHV infection, and lgp2 transcripts were also significantly enhanced in vitro after stimulation with synthetic, double-stranded RNA polyinosinic polycytidylic [poly(I:C)]. -
Low Abundance of the Matrix Arm of Complex I in Mitochondria Predicts Longevity in Mice
ARTICLE Received 24 Jan 2014 | Accepted 9 Apr 2014 | Published 12 May 2014 DOI: 10.1038/ncomms4837 OPEN Low abundance of the matrix arm of complex I in mitochondria predicts longevity in mice Satomi Miwa1, Howsun Jow2, Karen Baty3, Amy Johnson1, Rafal Czapiewski1, Gabriele Saretzki1, Achim Treumann3 & Thomas von Zglinicki1 Mitochondrial function is an important determinant of the ageing process; however, the mitochondrial properties that enable longevity are not well understood. Here we show that optimal assembly of mitochondrial complex I predicts longevity in mice. Using an unbiased high-coverage high-confidence approach, we demonstrate that electron transport chain proteins, especially the matrix arm subunits of complex I, are decreased in young long-living mice, which is associated with improved complex I assembly, higher complex I-linked state 3 oxygen consumption rates and decreased superoxide production, whereas the opposite is seen in old mice. Disruption of complex I assembly reduces oxidative metabolism with concomitant increase in mitochondrial superoxide production. This is rescued by knockdown of the mitochondrial chaperone, prohibitin. Disrupted complex I assembly causes premature senescence in primary cells. We propose that lower abundance of free catalytic complex I components supports complex I assembly, efficacy of substrate utilization and minimal ROS production, enabling enhanced longevity. 1 Institute for Ageing and Health, Newcastle University, Newcastle upon Tyne NE4 5PL, UK. 2 Centre for Integrated Systems Biology of Ageing and Nutrition, Newcastle University, Newcastle upon Tyne NE4 5PL, UK. 3 Newcastle University Protein and Proteome Analysis, Devonshire Building, Devonshire Terrace, Newcastle upon Tyne NE1 7RU, UK. Correspondence and requests for materials should be addressed to T.v.Z. -
Mir-155 Targets TP53INP1 to Regulate Liver Cancer Stem Cell Acquisition and Self-Renewal ⇑ Fengchao Liu, Xin Kong, Lin Lv, Jian Gao
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector FEBS Letters 589 (2015) 500–506 journal homepage: www.FEBSLetters.org MiR-155 targets TP53INP1 to regulate liver cancer stem cell acquisition and self-renewal ⇑ Fengchao Liu, Xin Kong, Lin Lv, Jian Gao Department of Gastroenterology, Second Affiliated Hospital, Chongqing Medical University, Chongqing, China article info abstract Article history: In liver cancer, miR-155 up-regulation can regulate cancer-cell invasion. However, whether miR-155 Received 29 October 2014 expression is associated with liver cancer stem cells (CSCs) remains unknown. Here, we show that Revised 5 January 2015 miR-155 expression is up-regulated in tumor spheres. Knock-down of miR-155 resulted in suppres- Accepted 9 January 2015 sion of tumor sphere formation, through a decrease in the proportion of CD90+ and CD133+ CSCs and Available online 17 January 2015 in the expression of Oct4, whereas miR-155 overexpression had the opposite effect. TP53INP1 was Edited by Quan Chen determined to be involved in the CSCs-like properties that were regulated by miR-155. Thus, miR- 155 may play an important role in promoting the generation of stem cell-like cells and their self- renewal by targeting the gene TP53INP1. Keywords: Liver cancer stem cell Ó 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved. MiR-155 Tumor Protein 53-Induced Nuclear Protein 1 Tumor sphere Liver cancer 1. Introduction plants [10]. Recently, increasing studies have revealed that many miRNAs play crucial roles in tumorigenesis [11,12], including CSCs Hepatocellular carcinoma (HCC) is the sixth most prevalent [13,14]. -
Functional Characterization of Epilepsy Associated GABRG2 Mutations
Functional Characterization of Epilepsy Associated GABRG2 Mutations By Mengnan Tian Dissertation Submitted to the Faculty of the Graduate School of Vanderbilt University in Partial Fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY in Pharmacology August, 2012 Nashville, Tennessee Approved: Robert L. Macdonald, M.D., Ph.D. Ronald Emeson, Ph.D. Kevin Ess, M.D., Ph.D. Katherine T. Murray, M.D. Douglas P. Mortlock, Ph.D. To my grandparents, Yunbo Tian and Zhenhua Cao. ii Acknowledgements Throughout my years pursuing Ph.D. degree, I have always been grateful for the opportunity working with an amazing complement of scientists. I would like to express my sincerest gratitude to my thesis advisor Dr. Robert Macdonald. He is by far the best mentor that I could have ever wished. He has provided me with excellent guidance and support, and given me the confidence to develop into an independent scientist. He granted me unprecedented freedom to explore new scientific fields and implement novel research strategies and techniques. I greatly appreciate all his trust in me, and it has fostered my confidence in performing researches. He has shown me, by his example, what a good scientist and mentor should be. I would like to thank my colleagues and collaborators in Macdonald lab. I have been collaborating with Xuan Huang since her rotation and after she joined our lab in 2009. We have also become good friends. She has made important contributions to many parts of my thesis studies, and provided brilliant critiques to help me improve the research plan. I am also deeply indebted to Dr. -
Supplement for TWO-SIGMA-G S1 Additional Type-I Error and Power Results
Supplement for TWO-SIGMA-G Eric Van Buren, Ming Hu, Liang Chen, John Wrobel, Kirk Wilhelmsen, Lishan Su, Yun Li, Di Wu S1 Additional Type-I Error and Power Results Independent Genes (No IGC) Genes Simulated with IGC (A) No Gene-Level Random Effects (B) No Gene-Level Random Effects Test Size = 30, Ref. Size = 30 Test Size = 30, Ref. Size = 30 0.03 0.03 0.02 0.02 0.01 0.01 Type-I Error Type-I Error Observed Set-Level Observed Set-Level 0.00 0.00 0.0000 0.0025 0.0050 0.0075 0.0100 0.0000 0.0025 0.0050 0.0075 0.0100 Significance Threshold Significance Threshold CAMERA MAST TWO-SIGMA-G CAMERA MAST TWO-SIGMA-G Genes Simulated with IGC Genes Simulated with IGC (C) Gene-Level Random Effects Present (D) Gene-Level Random Effects Test Size = 30, Ref. Size = 30 Incorrectly Absent 0.03 Test Size = 30, Ref. Size = 30 0.03 0.02 0.02 0.01 0.01 Type-I Error Type-I Error Observed Set-Level 0.00 Observed Set-Level 0.00 0.0000 0.0025 0.0050 0.0075 0.0100 0.0000 0.0025 0.0050 0.0075 0.0100 Significance Threshold Significance Threshold CAMERA MAST TWO-SIGMA-G CAMERA MAST TWO-SIGMA-G Supplementary Figure S1: Type-I error performance of CAMERA, MAST, and TWO-SIGMA-G as significance threshold varies from 0 to .01. Each panel varies the existence of IGC between genes in the test set and the presence of gene-level random effect terms in gene-level model (CAMERA never includes gene-level random effect terms).