Zbtb7b Engages the Long Noncoding RNA Blnc1 to Drive Brown
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Figure 2S 4 7 A - C 080125 CSCs 080418 CSCs - + IFN-a 48 h + IFN-a 48 h + IFN-a 72 h 6 + IFN-a 72 h 3 5 MRFI 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 7 B 13 080125 FBS - D 080418 FBS - + IFN-a 48 h 12 + IFN-a 48 h + IFN-a 72 h + IFN-a 72 h 6 080125 FBS 11 10 5 9 8 4 7 6 3 MRFI 5 4 2 3 2 1 1 0 0 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 MHC I MHC II MICA MICB ULBP-1 ULBP-2 ULBP-3 ULBP-4 Molecule Molecule FIGURE 4S FIGURE 5S Panel A Panel B FIGURE 6S A B C D Supplemental Results Table 1S. Modulation by IFN-α of APM in GBM CSC and FBS tumor cell lines. Molecule * Cell line IFN-α‡ HLA β2-m# HLA LMP TAP1 TAP2 class II A A HC§ 2 7 10 080125 CSCs - 1∞ (1) 3 (65) 2 (91) 1 (2) 6 (47) 2 (61) 1 (3) 1 (2) 1 (3) + 2 (81) 11 (80) 13 (99) 1 (3) 8 (88) 4 (91) 1 (2) 1 (3) 2 (68) 080125 FBS - 2 (81) 4 (63) 4 (83) 1 (3) 6 (80) 3 (67) 2 (86) 1 (3) 2 (75) + 2 (99) 14 (90) 7 (97) 5 (75) 7 (100) 6 (98) 2 (90) 1 (4) 3 (87) 080418 CSCs - 2 (51) 1 (1) 1 (3) 2 (47) 2 (83) 2 (54) 1 (4) 1 (2) 1 (3) + 2 (81) 3 (76) 5 (75) 2 (50) 2 (83) 3 (71) 1 (3) 2 (87) 1 (2) 080418 FBS - 1 (3) 3 (70) 2 (88) 1 (4) 3 (87) 2 (76) 1 (3) 1 (3) 1 (2) + 2 (78) 7 (98) 5 (99) 2 (94) 5 (100) 3 (100) 1 (4) 2 (100) 1 (2) 070104 CSCs - 1 (2) 1 (3) 1 (3) 2 (78) 1 (3) 1 (2) 1 (3) 1 (3) 1 (2) + 2 (98) 8 (100) 10 (88) 4 (89) 3 (98) 3 (94) 1 (4) 2 (86) 2 (79) * expression of APM molecules was evaluated by intracellular staining and cytofluorimetric analysis; ‡ cells were treatead or not (+/-) for 72 h with 1000 IU/ml of IFN-α; # β-2 microglobulin; § β-2 microglobulin-free HLA-A heavy chain; ∞ values are indicated as ratio between the mean of fluorescence intensity of cells stained with the selected mAb and that of the negative control; bold values indicate significant MRFI (≥ 2). -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
GRIM19 Impedes Obesity by Regulating Inflammatory White Fat
cells Article GRIM19 Impedes Obesity by Regulating Inflammatory White Fat Browning and Promoting Th17/Treg Balance JooYeon Jhun 1,†, Jin Seok Woo 1,† , Seung Hoon Lee 2, Jeong-Hee Jeong 1, KyungAh Jung 3, Wonhee Hur 4, Seon-Yeong Lee 1, Jae Yoon Ryu 1, Young-Mee Moon 1, Yoon Ju Jung 5, Kyo Young Song 5, Kiyuk Chang 6, Seung Kew Yoon 4,7 , Sung-Hwan Park 1,8 and Mi-La Cho 1,8,* 1 The Rheumatism Research Center, Catholic Research Institute of Medical Science, The Catholic University of Korea, Seoul 137-040, Korea; [email protected] (J.J.); [email protected] (J.S.W.); [email protected] (J.-H.J.); [email protected] (S.-Y.L.); [email protected] (J.Y.R.); [email protected] (Y.-M.M.); [email protected] (S.-H.P.) 2 Division of Immunology, Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA 02115, USA; [email protected] 3 Research Center, Impact Biotech, Seoul 137-040, Korea; [email protected] 4 The Catholic University Liver Research Center & WHO Collaborating Center of Viral Hepatitis, College of Medicine, The Catholic University of Korea, Seoul 137-040, Korea; [email protected] (W.H.); [email protected] (S.K.Y.) 5 Division of Gastrointestinal Surgery, Department of General Surgery, Seoul St. Mary’s Hospital, The Catholic University of Korea, Seoul 137-040, Korea; [email protected] (Y.J.J.); [email protected] (K.Y.S.) 6 Cardiovascular Center and Cardiology Division, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul 137-040, Korea; [email protected] 7 Department of Internal Medicine, Seoul St. -
Characterization of the Human CIDEA Promoter in Fat Cells
International Journal of Obesity (2008) 32, 1380–1387 & 2008 Macmillan Publishers Limited All rights reserved 0307-0565/08 $32.00 www.nature.com/ijo ORIGINAL ARTICLE Characterization of the human CIDEA promoter in fat cells AT Pettersson1, J Laurencikiene1, EA Nordstro¨m1, BM Stenson1, V van Harmelen1, C Murphy2, I Dahlman1 and M Ryde´n1 1Department of Medicine, Huddinge, Lipid Laboratory, Novum, Karolinska Institutet, Stockholm, Sweden and 2Department of Laboratory Medicine, Karolinska Institutet, Stockholm, Sweden. Background: Cell death-inducing DFFA (DNA fragmentation factor-a)-like effector A (CIDEA) is a protein that regulates lipolysis in human adipocytes through cross-talk involving tumor necrosis factor-a (TNF-a). TNF-a downregulates CIDEA mRNA although it is unclear whether this is mediated through transcriptional or post-transcriptional mechanisms. CIDEA has important metabolic effects in human fat cells and genetic variations in the human CIDEA gene have been correlated to the development of obesity. However, little is known about the factors regulating CIDEA expression in human adipocytes. We set out to describe the transcriptional control of human CIDEA. Methods: A 1.1-kb genomic fragment upstream of the transcriptional start site (TSS) of human CIDEA was cloned and deletion fragments were generated. Transcriptional activity of the promoter was analyzed by luciferase reporter assays in in vitro- differentiated human adipocytes. The effect of TNF-a was assessed in human adipocytes and murine 3T3-L1 cells transfected with deletion fragments of the CIDEA promoter. Protein–DNA interactions were analyzed by electrophoretic mobility shift assays (EMSA). Results: Basal transcriptional activity was found in a 97-bp region upstream of the TSS. -
Anti-CIDE a Antibody [V62P1E3*B10] (ARG10830)
Product datasheet [email protected] ARG10830 Package: 100 μg anti-CIDE A antibody [V62P1E3*B10] Store at: -20°C Summary Product Description Mouse Monoclonal antibody recognizes CIDE A Tested Reactivity Hu Tested Application IHC-P, WB Host Mouse Clonality Monoclonal Clone V62P1E3*B10 Isotype IgG1, kappa Target Name CIDE A Antigen Species Human Immunogen Ovalbumin-conjugated synthetic peptide. (QAKGRFTCG) Conjugation Un-conjugated Alternate Names CIDE-A; Cell death-inducing DFFA-like effector A; Cell death activator CIDE-A Application Instructions Application table Application Dilution IHC-P Assay-dependent WB Assay-dependent Application Note Antigen Retrieval: Boil tissue section for 10 - 20 min at 800 - 950W microwave with 10 mM Citrate buffer or Sodium citrate buffer (pH 6.0). * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 25 kDa Properties Form Liquid Purification Affinity purification with immunogen. 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 or below. 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. Note For laboratory research only, not for drug, diagnostic or other use. Bioinformation www.arigobio.com 1/3 Gene Symbol CIDEA Gene Full Name cell death-inducing DFFA-like effector a Background This gene encodes the homolog of the mouse protein Cidea that has been shown to activate apoptosis. This activation of apoptosis is inhibited by the DNA fragmentation factor DFF45 but not by caspase inhibitors. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Microrna Pharmacoepigenetics: Posttranscriptional Regulation Mechanisms Behind Variable Drug Disposition and Strategy to Develop More Effective Therapy
1521-009X/44/3/308–319$25.00 http://dx.doi.org/10.1124/dmd.115.067470 DRUG METABOLISM AND DISPOSITION Drug Metab Dispos 44:308–319, March 2016 Copyright ª 2016 by The American Society for Pharmacology and Experimental Therapeutics Minireview MicroRNA Pharmacoepigenetics: Posttranscriptional Regulation Mechanisms behind Variable Drug Disposition and Strategy to Develop More Effective Therapy Ai-Ming Yu, Ye Tian, Mei-Juan Tu, Pui Yan Ho, and Joseph L. Jilek Department of Biochemistry & Molecular Medicine, University of California Davis School of Medicine, Sacramento, California Received September 30, 2015; accepted November 12, 2015 Downloaded from ABSTRACT Knowledge of drug absorption, distribution, metabolism, and excre- we review the advances in miRNA pharmacoepigenetics including tion (ADME) or pharmacokinetics properties is essential for drug the mechanistic actions of miRNAs in the modulation of Phase I and development and safe use of medicine. Varied or altered ADME may II drug-metabolizing enzymes, efflux and uptake transporters, and lead to a loss of efficacy or adverse drug effects. Understanding the xenobiotic receptors or transcription factors after briefly introducing causes of variations in drug disposition and response has proven the characteristics of miRNA-mediated posttranscriptional gene dmd.aspetjournals.org critical for the practice of personalized or precision medicine. The regulation. Consequently, miRNAs may have significant influence rise of noncoding microRNA (miRNA) pharmacoepigenetics and on drug disposition and response. Therefore, research on miRNA pharmacoepigenomics has come with accumulating evidence sup- pharmacoepigenetics shall not only improve mechanistic under- porting the role of miRNAs in the modulation of ADME gene standing of variations in pharmacotherapy but also provide novel expression and then drug disposition and response. -
Proteomics Provides Insights Into the Inhibition of Chinese Hamster V79
www.nature.com/scientificreports OPEN Proteomics provides insights into the inhibition of Chinese hamster V79 cell proliferation in the deep underground environment Jifeng Liu1,2, Tengfei Ma1,2, Mingzhong Gao3, Yilin Liu4, Jun Liu1, Shichao Wang2, Yike Xie2, Ling Wang2, Juan Cheng2, Shixi Liu1*, Jian Zou1,2*, Jiang Wu2, Weimin Li2 & Heping Xie2,3,5 As resources in the shallow depths of the earth exhausted, people will spend extended periods of time in the deep underground space. However, little is known about the deep underground environment afecting the health of organisms. Hence, we established both deep underground laboratory (DUGL) and above ground laboratory (AGL) to investigate the efect of environmental factors on organisms. Six environmental parameters were monitored in the DUGL and AGL. Growth curves were recorded and tandem mass tag (TMT) proteomics analysis were performed to explore the proliferative ability and diferentially abundant proteins (DAPs) in V79 cells (a cell line widely used in biological study in DUGLs) cultured in the DUGL and AGL. Parallel Reaction Monitoring was conducted to verify the TMT results. γ ray dose rate showed the most detectable diference between the two laboratories, whereby γ ray dose rate was signifcantly lower in the DUGL compared to the AGL. V79 cell proliferation was slower in the DUGL. Quantitative proteomics detected 980 DAPs (absolute fold change ≥ 1.2, p < 0.05) between V79 cells cultured in the DUGL and AGL. Of these, 576 proteins were up-regulated and 404 proteins were down-regulated in V79 cells cultured in the DUGL. KEGG pathway analysis revealed that seven pathways (e.g. -
Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights Into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle
animals Article Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle Masoumeh Naserkheil 1 , Abolfazl Bahrami 1 , Deukhwan Lee 2,* and Hossein Mehrban 3 1 Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj 77871-31587, Iran; [email protected] (M.N.); [email protected] (A.B.) 2 Department of Animal Life and Environment Sciences, Hankyong National University, Jungang-ro 327, Anseong-si, Gyeonggi-do 17579, Korea 3 Department of Animal Science, Shahrekord University, Shahrekord 88186-34141, Iran; [email protected] * Correspondence: [email protected]; Tel.: +82-31-670-5091 Received: 25 August 2020; Accepted: 6 October 2020; Published: 9 October 2020 Simple Summary: Hanwoo is an indigenous cattle breed in Korea and popular for meat production owing to its rapid growth and high-quality meat. Its yearling weight and carcass traits (backfat thickness, carcass weight, eye muscle area, and marbling score) are economically important for the selection of young and proven bulls. In recent decades, the advent of high throughput genotyping technologies has made it possible to perform genome-wide association studies (GWAS) for the detection of genomic regions associated with traits of economic interest in different species. In this study, we conducted a weighted single-step genome-wide association study which combines all genotypes, phenotypes and pedigree data in one step (ssGBLUP). It allows for the use of all SNPs simultaneously along with all phenotypes from genotyped and ungenotyped animals. Our results revealed 33 relevant genomic regions related to the traits of interest. -
Teaching an Old Dog New Tricks: Reactivated Developmental Signaling Pathways Regulate ABCB1 and Chemoresistance in Cancer
Lee et al. Cancer Drug Resist 2021;4:424-52 Cancer DOI: 10.20517/cdr.2020.114 Drug Resistance Review Open Access Teaching an old dog new tricks: reactivated developmental signaling pathways regulate ABCB1 and chemoresistance in cancer Wing-Kee Lee, Frank Thévenod Institute for Physiology, Pathophysiology and Toxicology, ZBAF, Witten/Herdecke University, Witten 58453, Germany. Correspondence to: Prof. Wing-Kee Lee, Institute for Physiology, Pathophysiology and Toxicology, Witten/Herdecke University, Stockumer Strasse 12, Witten 58453, Germany. E-mail: [email protected] How to cite this article: Lee WK, Thévenod F. Teaching an old dog new tricks: reactivated developmental signaling pathways regulate ABCB1 and chemoresistance in cancer. Cancer Drug Resist 2021;4:424-52. http://dx.doi.org/10.20517/cdr.2020.114 Received: 11 Dec 2020 First Decision: 27 Jan 2021 Revised: 6 Feb 2021 Accepted: 20 Feb 2021 Available online: 19 Jun 2021 Academic Editor: Godefridus J. Peters Copy Editor: Yue-Yue Zhang Production Editor: Yue-Yue Zhang Abstract Oncogenic multidrug resistance (MDR) is a multifactorial phenotype intimately linked to deregulated expression of detoxification transporters. Drug efflux transporters, particularly the MDR P-glycoprotein ABCB1, represent a central mechanism by which not only chemotherapeutic drugs are extruded or sequestered to prevent drug delivery to their intracellular targets, but also for inhibiting apoptotic cell death cues, such as removal of proapoptotic signals. Several cell populations exhibiting the MDR phenotype co-exist within a tumor, such as cells forming the bulk tumor cell mass, cancer stem cells, and cancer persister cells. The key to regulation of ABCB1 expression is the cellular transcriptional machinery. -
Myopia in African Americans Is Significantly Linked to Chromosome 7P15.2-14.2
Genetics Myopia in African Americans Is Significantly Linked to Chromosome 7p15.2-14.2 Claire L. Simpson,1,2,* Anthony M. Musolf,2,* Roberto Y. Cordero,1 Jennifer B. Cordero,1 Laura Portas,2 Federico Murgia,2 Deyana D. Lewis,2 Candace D. Middlebrooks,2 Elise B. Ciner,3 Joan E. Bailey-Wilson,1,† and Dwight Stambolian4,† 1Department of Genetics, Genomics and Informatics and Department of Ophthalmology, University of Tennessee Health Science Center, Memphis, Tennessee, United States 2Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Baltimore, Maryland, United States 3The Pennsylvania College of Optometry at Salus University, Elkins Park, Pennsylvania, United States 4Department of Ophthalmology, University of Pennsylvania, Philadelphia, Pennsylvania, United States Correspondence: Joan E. PURPOSE. The purpose of this study was to perform genetic linkage analysis and associ- Bailey-Wilson, NIH/NHGRI, 333 ation analysis on exome genotyping from highly aggregated African American families Cassell Drive, Suite 1200, Baltimore, with nonpathogenic myopia. African Americans are a particularly understudied popula- MD 21131, USA; tion with respect to myopia. [email protected]. METHODS. One hundred six African American families from the Philadelphia area with a CLS and AMM contributed equally to family history of myopia were genotyped using an Illumina ExomePlus array and merged this work and should be considered co-first authors. with previous microsatellite data. Myopia was initially measured in mean spherical equiv- JEB-W and DS contributed equally alent (MSE) and converted to a binary phenotype where individuals were identified as to this work and should be affected, unaffected, or unknown. -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002)