Neuronal Genes for Subcutaneous Fat Thickness in Human and Pig Are Identified by Local Genomic Sequencing and Combined SNP Association Study
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Association Analyses of Known Genetic Variants with Gene
ASSOCIATION ANALYSES OF KNOWN GENETIC VARIANTS WITH GENE EXPRESSION IN BRAIN by Viktoriya Strumba A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Bioinformatics) in The University of Michigan 2009 Doctoral Committee: Professor Margit Burmeister, Chair Professor Huda Akil Professor Brian D. Athey Assistant Professor Zhaohui S. Qin Research Statistician Thomas Blackwell To Sam and Valentina Dmitriy and Elizabeth ii ACKNOWLEDGEMENTS I would like to thank my advisor Professor Margit Burmeister, who tirelessly guided me though seemingly impassable corridors of graduate work. Throughout my thesis writing period she provided sound advice, encouragement and inspiration. Leading by example, her enthusiasm and dedication have been instrumental in my path to becoming a better scientist. I also would like to thank my co-advisor Tom Blackwell. His careful prodding always kept me on my toes and looking for answers, which taught me the depth of careful statistical analysis. His diligence and dedication have been irreplaceable in most difficult of projects. I also would like to thank my other committee members: Huda Akil, Brian Athey and Steve Qin as well as David States. You did not make it easy for me, but I thank you for believing and not giving up. Huda’s eloquence in every subject matter she explained have been particularly inspiring, while both Huda’s and Brian’s valuable advice made the completion of this dissertation possible. I would also like to thank all the members of the Burmeister lab, both past and present: Sandra Villafuerte, Kristine Ito, Cindy Schoen, Karen Majczenko, Ellen Schmidt, Randi Burns, Gang Su, Nan Xiang and Ana Progovac. -
Environmental Influences on Endothelial Gene Expression
ENDOTHELIAL CELL GENE EXPRESSION John Matthew Jeff Herbert Supervisors: Prof. Roy Bicknell and Dr. Victoria Heath PhD thesis University of Birmingham August 2012 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT Tumour angiogenesis is a vital process in the pathology of tumour development and metastasis. Targeting markers of tumour endothelium provide a means of targeted destruction of a tumours oxygen and nutrient supply via destruction of tumour vasculature, which in turn ultimately leads to beneficial consequences to patients. Although current anti -angiogenic and vascular targeting strategies help patients, more potently in combination with chemo therapy, there is still a need for more tumour endothelial marker discoveries as current treatments have cardiovascular and other side effects. For the first time, the analyses of in-vivo biotinylation of an embryonic system is performed to obtain putative vascular targets. Also for the first time, deep sequencing is applied to freshly isolated tumour and normal endothelial cells from lung, colon and bladder tissues for the identification of pan-vascular-targets. Integration of the proteomic, deep sequencing, public cDNA libraries and microarrays, delivers 5,892 putative vascular targets to the science community. -
Identification of Potential Markers for Type 2 Diabetes Mellitus Via Bioinformatics Analysis
1868 MOLECULAR MEDICINE REPORTS 22: 1868-1882, 2020 Identification of potential markers for type 2 diabetes mellitus via bioinformatics analysis YANA LU1, YIHANG LI1, GUANG LI1* and HAITAO LU2* 1Key Laboratory of Dai and Southern Medicine of Xishuangbanna Dai Autonomous Prefecture, Yunnan Branch, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Jinghong, Yunnan 666100; 2Key Laboratory of Systems Biomedicine, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, P.R. China Received March 20, 2019; Accepted January 20, 2020 DOI: 10.3892/mmr.2020.11281 Abstract. Type 2 diabetes mellitus (T2DM) is a multifactorial and cell proliferation’. These candidate genes were also involved in multigenetic disease, and its pathogenesis is complex and largely different signaling pathways associated with ‘PI3K/Akt signaling unknown. In the present study, microarray data (GSE201966) of pathway’, ‘Rap1 signaling pathway’, ‘Ras signaling pathway’ β-cell enriched tissue obtained by laser capture microdissection and ‘MAPK signaling pathway’, which are highly associated were downloaded, including 10 control and 10 type 2 diabetic with the development of T2DM. Furthermore, a microRNA subjects. A comprehensive bioinformatics analysis of microarray (miR)-target gene regulatory network and a transcription data in the context of protein-protein interaction (PPI) networks factor-target gene regulatory network were constructed based was employed, combined with subcellular location information on miRNet and NetworkAnalyst databases, respectively. to mine the potential candidate genes for T2DM and provide Notably, hsa-miR‑192-5p, hsa-miR‑124-5p and hsa-miR‑335-5p further insight on the possible mechanisms involved. First, appeared to be involved in T2DM by potentially regulating the differential analysis screened 108 differentially expressed expression of various candidate genes, including procollagen genes. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Origins and Functional Impact of Copy Number Variation in the Human Genome
doi:10.1038/nature08516 ARTICLES Origins and functional impact of copy number variation in the human genome Donald F. Conrad1*, Dalila Pinto2*, Richard Redon1,3, Lars Feuk2,4, Omer Gokcumen5, Yujun Zhang1, Jan Aerts1, T. Daniel Andrews1, Chris Barnes1, Peter Campbell1, Tomas Fitzgerald1, Min Hu1, Chun Hwa Ihm5, Kati Kristiansson1, Daniel G. MacArthur1, Jeffrey R. MacDonald2, Ifejinelo Onyiah1, Andy Wing Chun Pang2, Sam Robson1, Kathy Stirrups1, Armand Valsesia1, Klaudia Walter1, John Wei2, Wellcome Trust Case Control Consortium{, Chris Tyler-Smith1, Nigel P. Carter1, Charles Lee5, Stephen W. Scherer2,6 & Matthew E. Hurles1 Structural variations of DNA greater than 1 kilobase in size account for most bases that vary among human genomes, but are still relatively under-ascertained. Here we use tiling oligonucleotide microarrays, comprising 42 million probes, to generate a comprehensive map of 11,700 copy number variations (CNVs) greater than 443 base pairs, of which most (8,599) have been validated independently. For 4,978 of these CNVs, we generated reference genotypes from 450 individuals of European, African or East Asian ancestry. The predominant mutational mechanisms differ among CNV size classes. Retrotransposition has duplicated and inserted some coding and non-coding DNA segments randomly around the genome. Furthermore, by correlation with known trait-associated single nucleotide polymorphisms (SNPs), we identified 30 loci with CNVs that are candidates for influencing disease susceptibility. Despite this, having assessed the completeness of our map and the patterns of linkage disequilibrium between CNVs and SNPs, we conclude that, for complex traits, the heritability void left by genome-wide association studies will not be accounted for by common CNVs. -
Areca Catechu-(Betel-Nut)-Induced Whole Transcriptome Changes Associated With
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.03.233932; this version posted August 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 Areca catechu-(Betel-nut)-induced whole transcriptome changes associated with 2 diabetes, obesity and metabolic syndrome in a human monocyte cell line 3 4 Short title: Betel-nut induced whole transcriptome changes 5 6 7 Shirleny Cardoso1¶ , B. William Ogunkolade1¶, Rob Lowe2, Emanuel Savage3, Charles A 8 Mein3, Barbara J Boucher1, Graham A Hitman1* 9 10 11 1Centre for Genomics and Child Health, Blizard Institute, Barts and the London School of 12 Medicine and Dentistry, Queen Mary University of London, United Kingdom 13 14 2Omnigen Biodata Ltd, Cambridge, United Kingdom 15 16 3Barts and The London Genome Centre, Blizard Institute, Queen Mary University of London, 17 United Kingdom 18 19 * Corresponding author 20 Email: [email protected] 21 22 ¶These authors contributed equally to the work 23 24 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.03.233932; this version posted August 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 25 Abstract 26 Betel-nut consumption is the fourth most common addictive habit globally and there is good 27 evidence to link it with obesity, type 2 diabetes and the metabolic syndrome. -
GIPC2 Antibody
Product Datasheet GIPC2 Antibody Catalog No: #32240 Orders: [email protected] Description Support: [email protected] Product Name GIPC2 Antibody Host Species Rabbit Clonality Polyclonal Purification Antibodies were purified by affinity purification using immunogen. Applications WB IHC Species Reactivity Hu Ms Rt Specificity The antibody detects endogenous level of total GIPC2 protein. Immunogen Type Recombinant Protein Immunogen Description Recombinant protein of human GIPC2. Target Name GIPC2 Other Names GIPC2; FLJ20075; SEMCAP-2; SEMCAP2; Accession No. Swiss-Prot:Q8TF65NCBI Gene ID:54810 SDS-PAGE MW 34KD Concentration 1.0mg/ml Formulation Supplied at 1.0mg/mL in phosphate buffered saline (without Mg2+ and Ca2+), pH 7.4, 150mM NaCl, 0.02% sodium azide and 50% glycerol. Storage Store at -20°C Application Details Western blotting: 1:500 - 1:2000 Immunohistochemistry: 1:50 - 1:100 Images Western blot analysis of extracts of various cell lines, using GIPC2 antibody. Background The eukaryotic PDZ domain is a multifunctional protein-protein interacting motif that is found in a variety of proteins and is involved in both the clustering of signaling molecules and the organization of protein networks. GIPC2 (GIPC PDZ domain containing family, member 2), also known as Address: 8400 Baltimore Ave., Suite 302, College Park, MD 20740, USA http://www.sabbiotech.com 1 SEMCAP2, is a 315 amino acid protein that localizes to the cytoplasm and contains one PDZ domain. Expressed at high levels in kidney and colon and at lower levels in adult liver, GIPC2 interacts with SEMA5A and is thought to function as a scaffold protein, possibly modulating cell adhesion and growth factor signaling and playing a role in tumorigenesis. -
A High Throughput, Functional Screen of Human Body Mass Index GWAS Loci Using Tissue-Specific Rnai Drosophila Melanogaster Crosses Thomas J
Washington University School of Medicine Digital Commons@Becker Open Access Publications 2018 A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses Thomas J. Baranski Washington University School of Medicine in St. Louis Aldi T. Kraja Washington University School of Medicine in St. Louis Jill L. Fink Washington University School of Medicine in St. Louis Mary Feitosa Washington University School of Medicine in St. Louis Petra A. Lenzini Washington University School of Medicine in St. Louis See next page for additional authors Follow this and additional works at: https://digitalcommons.wustl.edu/open_access_pubs Recommended Citation Baranski, Thomas J.; Kraja, Aldi T.; Fink, Jill L.; Feitosa, Mary; Lenzini, Petra A.; Borecki, Ingrid B.; Liu, Ching-Ti; Cupples, L. Adrienne; North, Kari E.; and Province, Michael A., ,"A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses." PLoS Genetics.14,4. e1007222. (2018). https://digitalcommons.wustl.edu/open_access_pubs/6820 This Open Access Publication is brought to you for free and open access by Digital Commons@Becker. It has been accepted for inclusion in Open Access Publications by an authorized administrator of Digital Commons@Becker. For more information, please contact [email protected]. Authors Thomas J. Baranski, Aldi T. Kraja, Jill L. Fink, Mary Feitosa, Petra A. Lenzini, Ingrid B. Borecki, Ching-Ti Liu, L. Adrienne Cupples, Kari E. North, and Michael A. Province This open access publication is available at Digital Commons@Becker: https://digitalcommons.wustl.edu/open_access_pubs/6820 RESEARCH ARTICLE A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses Thomas J. -
Identification of Significant Genes with Poor Prognosis in Ovarian Cancer Via Bioinformatical Analysis
Feng et al. Journal of Ovarian Research (2019) 12:35 https://doi.org/10.1186/s13048-019-0508-2 RESEARCH Open Access Identification of significant genes with poor prognosis in ovarian cancer via bioinformatical analysis Hao Feng1†, Zhong-Yi Gu2†, Qin Li2, Qiong-Hua Liu3, Xiao-Yu Yang4* and Jun-Jie Zhang2* Abstract Ovarian cancer (OC) is the highest frequent malignant gynecologic tumor with very complicated pathogenesis. The purpose of the present academic work was to identify significant genes with poor outcome and their underlying mechanisms. Gene expression profiles of GSE36668, GSE14407 and GSE18520 were available from GEO database. There are 69 OC tissues and 26 normal tissues in the three profile datasets. Differentially expressed genes (DEGs) between OC tissues and normal ovarian (OV) tissues were picked out by GEO2R tool and Venn diagram software. Next, we made use of the Database for Annotation, Visualization and Integrated Discovery (DAVID) to analyze Kyoto Encyclopedia of Gene and Genome (KEGG) pathway and gene ontology (GO). Then protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). There were total of 216 consistently expressed genes in the three datasets, including 110 up-regulated genes enriched in cell division, sister chromatid cohesion, mitotic nuclear division, regulation of cell cycle, protein localization to kinetochore, cell proliferation and Cell cycle, progesterone-mediated oocyte maturation and p53 signaling pathway, while 106 down-regulated genes enriched in palate development, blood coagulation, positive regulation of transcription from RNA polymerase II promoter, axonogenesis, receptor internalization, negative regulation of transcription from RNA polymerase II promoter and no significant signaling pathways. -
Anti-GIPC Antibody [1G10] (ARG57115)
Product datasheet [email protected] ARG57115 Package: 50 μl anti-GIPC antibody [1G10] Store at: -20°C Summary Product Description Mouse Monoclonal antibody [1G10] recognizes GIPC Tested Reactivity Hu Tested Application FACS, WB Host Mouse Clonality Monoclonal Clone 1G10 Isotype IgG1, kappa Target Name GIPC Antigen Species Human Immunogen Recombinant fragment around aa. 1-315 of Human GIPC Conjugation Un-conjugated Alternate Names PDZ domain-containing protein GIPC2; SEMCAP2; SEMCAP-2 Application Instructions Application table Application Dilution FACS Assay-dependent WB 1:1000 Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 34 kDa Properties Form Liquid Purification Purification with Protein G. Buffer PBS (pH 7.4), 0.02% Sodium azide and 10% Glycerol. Preservative 0.02% Sodium azide Stabilizer 10% Glycerol Concentration 1 mg/ml Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. www.arigobio.com 1/2 Note For laboratory research only, not for drug, diagnostic or other use. Bioinformation Database links GeneID: 54810 Human Swiss-port # Q8TF65 Human Gene Symbol GIPC2 Gene Full Name GIPC PDZ domain containing family, member 2 Images ARG57115 anti-GIPC antibody [1G10] FACS image Flow Cytometry: HeLa cells stained with ARG57115 anti-GIPC antibody [1G10] at 2-5 µg / 10^6 cells (red). -
Robles JTO Supplemental Digital Content 1
Supplementary Materials An Integrated Prognostic Classifier for Stage I Lung Adenocarcinoma based on mRNA, microRNA and DNA Methylation Biomarkers Ana I. Robles1, Eri Arai2, Ewy A. Mathé1, Hirokazu Okayama1, Aaron Schetter1, Derek Brown1, David Petersen3, Elise D. Bowman1, Rintaro Noro1, Judith A. Welsh1, Daniel C. Edelman3, Holly S. Stevenson3, Yonghong Wang3, Naoto Tsuchiya4, Takashi Kohno4, Vidar Skaug5, Steen Mollerup5, Aage Haugen5, Paul S. Meltzer3, Jun Yokota6, Yae Kanai2 and Curtis C. Harris1 Affiliations: 1Laboratory of Human Carcinogenesis, NCI-CCR, National Institutes of Health, Bethesda, MD 20892, USA. 2Division of Molecular Pathology, National Cancer Center Research Institute, Tokyo 104-0045, Japan. 3Genetics Branch, NCI-CCR, National Institutes of Health, Bethesda, MD 20892, USA. 4Division of Genome Biology, National Cancer Center Research Institute, Tokyo 104-0045, Japan. 5Department of Chemical and Biological Working Environment, National Institute of Occupational Health, NO-0033 Oslo, Norway. 6Genomics and Epigenomics of Cancer Prediction Program, Institute of Predictive and Personalized Medicine of Cancer (IMPPC), 08916 Badalona (Barcelona), Spain. List of Supplementary Materials Supplementary Materials and Methods Fig. S1. Hierarchical clustering of based on CpG sites differentially-methylated in Stage I ADC compared to non-tumor adjacent tissues. Fig. S2. Confirmatory pyrosequencing analysis of DNA methylation at the HOXA9 locus in Stage I ADC from a subset of the NCI microarray cohort. 1 Fig. S3. Methylation Beta-values for HOXA9 probe cg26521404 in Stage I ADC samples from Japan. Fig. S4. Kaplan-Meier analysis of HOXA9 promoter methylation in a published cohort of Stage I lung ADC (J Clin Oncol 2013;31(32):4140-7). Fig. S5. Kaplan-Meier analysis of a combined prognostic biomarker in Stage I lung ADC. -
Investigating the Effect of Chronic Activation of AMP-Activated Protein
Investigating the effect of chronic activation of AMP-activated protein kinase in vivo Alice Pollard CASE Studentship Award A thesis submitted to Imperial College London for the degree of Doctor of Philosophy September 2017 Cellular Stress Group Medical Research Council London Institute of Medical Sciences Imperial College London 1 Declaration I declare that the work presented in this thesis is my own, and that where information has been derived from the published or unpublished work of others it has been acknowledged in the text and in the list of references. This work has not been submitted to any other university or institute of tertiary education in any form. Alice Pollard The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives license. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the license terms of this work. 2 Abstract The prevalence of obesity and associated diseases has increased significantly in the last decade, and is now a major public health concern. It is a significant risk factor for many diseases, including cardiovascular disease (CVD) and type 2 diabetes. Characterised by excess lipid accumulation in the white adipose tissue, which drives many associated pathologies, obesity is caused by chronic, whole-organism energy imbalance; when caloric intake exceeds energy expenditure. Whilst lifestyle changes remain the most effective treatment for obesity and the associated metabolic syndrome, incidence continues to rise, particularly amongst children, placing significant strain on healthcare systems, as well as financial burden.