Supplementary Figure S1 A

Total Page:16

File Type:pdf, Size:1020Kb

Supplementary Figure S1 A Supplementary Figure S1 A B C 1 4 1 3 1 2 1 2 1 0 1 1 (Normalized signal values)] 2 (Normalized signal values) (Normalized 8 2 10 Log 6 AFFX-BioC AFFX-BioB AFFX-BioDn AFFX-CreX hDFs [Log 6 8 10 12 14 hOFs [Log2 (Normalized signal values)] Supplementary Figure S2 GLYCOLYSIS PENTOSE-PHOSPHATE PATHWAY Glucose Purine/pyrimidine Glucose-6-phosphate metabolism AMINO ACID Fluctose-6-phosphate AMPK METABOLISM TIGAR PFKFB2 methylgloxal GloI Ser, Gly, Thr Glyceraldehyde-3-phosphate ALDH Lactate PYRUVATE LDH METABOLISM acetic acid Ethanol Pyruvate GLYCOSPHINGOLIPID NADH BIOSYNTHESIS Ala, Cys DLD PDH PDK3 DLAT Fatty acid Lys, Trp, Leu, Acetyl CoA ACAT2 Ile, Tyr, Phe β-OXIDATION ACACA Citrate Asp, Asn Citrate Acetyl CoA Oxaloacetate Isocitrate MDH1 IDH1 Glu, Gln, His, ME2 TCA Pro, Arg 2-Oxoglutarate MDH1 CYCLE Pyruvate Malate ME2 GLUTAMINOLYSIS FH Succinyl-CoA Fumalate SUCLA2 Tyr, Phe Var, Ile, Met Supplementary Figure S3 Entrez Gene Symbol Gene Name hODs hDFs hOF-iPSCs GeneID 644 BLVRA biliverdin reductase A 223.9 259.3 253.0 3162 HMOX1 heme oxygenase 1 1474.2 2698.0 452.3 9365 KL klotho 54.1 44.8 36.5 nicotinamide 10135 NAMPT 827.7 626.2 2999.8 phosphoribosyltransferase nuclear factor (erythroid- 4780 NFE2L2 2134.5 1331.7 1006.2 derived 2) related factor 2 peroxisome proliferator- 5467 PPARD 1534.6 1352.9 330.8 activated receptor delta peroxisome proliferator- 5468 PPARG 524.4 100.8 63.0 activated receptor gamma 5621 PRNP prion protein 4059.0 3134.1 1065.5 5925 RB1 retinoblastoma 1 882.9 805.8 739.3 23411 SIRT1 sirtuin 1 231.5 216.8 1676.0 7157 TP53 tumor protein p53 2107.7 2197.0 2149.1 Supplementary Figure S4 Entrez Expresse Gene hOF- Location Gene Name hOFs hDFs Gene ID d Allele Symbol iPSCs DIRAS family, GTP- 9077 Paternal 1p31 AS DIRAS3 254.9 140.7 72.4 binding RAS-like 3 23089 Paternal 7q21 PEG10 paternally expressed 10 257.1 374.8 1841.9 H19, imprinted maternally 11p15.5 283120 Maternal H19 expressed transcript (non- 1304.4 801.3 559.8 AS protein coding) 11p15.5 insulin-like growth factor 2 3481 Paternal IGF2 1060.0 184.8 82.6 AS (somatomedin A) potassium voltage-gated 3784 Maternal 11p15.5 KCNQ1 channel, KQT-like 150.2 147.2 107.9 subfamily, member 1 maternally expressed 3 55384 Maternal 14q32 MEG3 738.9 418.8 476.7 (non-protein coding) 8788 Paternal 14q32 DLK1 delta-like 1 homolog 161.4 182.5 173.5 14q32.31 388015 Paternal RTL1 retrotransposon-like 1 78.9 79.0 68.7 AS deiodinase, iodothyronine, 1735 Paternal 14q32 Dio3 76.5 84.5 68.6 type III maternally expressed 8 79104 Maternal 14q32.31 MEG8 n.d. n.d. n.d. (non-protein coding) 15q11.2- 4692 Paternal NDN necdin homolog (mouse) 147.2 122.5 98.9 q12 AS 19q13.4 5178 Paternal PEG3 paternally expressed 3 104.5 107.8 86.7 AS Supplementary Table S1. 12,713 gene probe list after differential expression analysis with One-way ANOVA (corrected p < 0.05). Transcripts Gene hOF- corrected p- Entrez Gene Gene description hOFs hDFs p-value Cluster Id symbol iPSCs value (BH) 7980908 10516 fibulin 5 FBLN5 13.59 13.13 7.99 1.86E-11 5.37E-07 7899167 79727 lin-28 homolog A (C. elegans) LIN28A 6.59 6.60 12.95 6.80E-11 9.81E-07 solute carrier family 7 (cationic amino acid transporter, 8173414 84889 SLC7A3 5.97 6.02 12.94 1.98E-10 9.88E-07 y+ system), member 3 7969533 122060 SLAIN motif family, member 1 SLAIN1 5.61 5.41 10.02 2.05E-10 9.88E-07 8102404 407028 microRNA 302a MIR302A 4.52 4.53 11.09 1.22E-10 9.88E-07 5460, 642559, 8178470 POU class 5 homeobox 1 POU5F1 7.34 7.30 13.19 1.67E-10 9.88E-07 645682, 5462 8170648 633 biglycan BGN 13.48 13.57 7.57 2.53E-10 1.04E-06 8041853 4072 epithelial cell adhesion molecule EPCAM 5.42 5.50 12.02 7.89E-10 2.85E-06 8052940 400961 poly(A) binding protein interacting protein 2B PAIP2B 6.37 6.36 9.97 9.95E-10 2.87E-06 8102406 442894 microRNA 302b MIR302B 4.50 4.51 11.33 9.53E-10 2.87E-06 chromosome 13 open reading frame 38 | 728591, C13orf38 7970989 spermatogenesis and oogenesis specific basic helix- 6.04 6.20 10.83 1.14E-09 3.00E-06 54937 |SOHLH2 loop-helix 2 8169385 6998 teratocarcinoma-derived growth factor 3, pseudogene TDGF3 5.97 6.12 10.61 1.57E-09 3.50E-06 5460, 642559, 8124889 POU class 5 homeobox 1 POU5F1 7.13 7.10 12.71 1.62E-09 3.50E-06 645682, 5462 5460, 642559, 8179719 POU class 5 homeobox 1 POU5F1 7.11 7.09 12.71 1.70E-09 3.50E-06 645682, 5462 8089438 151871 developmental pluripotency associated 2 DPPA2 4.97 4.94 9.12 2.27E-09 4.37E-06 8072015 157 adrenergic, beta, receptor kinase 2 ADRBK2 5.91 5.86 9.25 2.93E-09 4.46E-06 7962455 4753 NEL-like 2 (chicken) NELL2 5.35 5.29 9.28 2.79E-09 4.46E-06 sortilin-related receptor, L(DLR class) A repeats- 7944667 6653 SORL1 6.32 6.44 10.00 2.55E-09 4.46E-06 containing NANOG 79923, 7953675 Nanog homeobox | Nanog homeobox pseudogene 1 |NANOGP 6.32 6.28 12.18 2.88E-09 4.46E-06 404635 1 7996837 999 cadherin 1, type 1, E-cadherin (epithelial) CDH1 6.22 6.22 11.45 3.09E-09 4.46E-06 8162652 1515 cathepsin L2 CTSL2 5.30 5.36 9.06 3.44E-09 4.73E-06 8077366 57633 leucine rich repeat neuronal 1 LRRN1 5.04 5.06 11.62 4.09E-09 5.19E-06 8044878 4.48 4.48 5.20 4.13E-09 5.19E-06 7986822 2562 gamma-aminobutyric acid (GABA) A receptor, beta 3 GABRB3 7.12 7.17 10.87 4.95E-09 5.50E-06 UDP-Gal:betaGlcNAc beta 1,4- galactosyltransferase, 8160637 2683 B4GALT1 10.85 11.37 8.04 4.92E-09 5.50E-06 polypeptide 1 7932109 22929 selenophosphate synthetase 1 SEPHS1 10.69 10.36 13.17 4.87E-09 5.50E-06 8098745 654254 zinc finger protein 732 ZNF732 5.57 5.51 8.65 5.97E-09 6.16E-06 50848, F11 receptor | thiosulfate sulfurtransferase F11R|TST 7921713 6.79 6.81 11.09 5.86E-09 6.16E-06 100131187 (rhodanese)-like domain containing 1 D1 8089448 55211 developmental pluripotency associated 4 DPPA4 5.84 5.74 11.70 6.30E-09 6.27E-06 immunoglobulin superfamily containing leucine-rich 7984813 3671 ISLR 12.42 12.64 6.40 7.29E-09 6.52E-06 repeat protein tyrosine phosphatase, receptor-type, Z 8135774 5803 PTPRZ1 5.28 5.24 11.23 7.01E-09 6.52E-06 polypeptide 1 8100464 10874 neuromedin U NMU 5.54 5.61 8.93 6.98E-09 6.52E-06 8148040 114569 mal, T-cell differentiation protein 2 MAL2 6.11 6.04 12.90 7.46E-09 6.52E-06 8134263 1278 collagen, type I, alpha 2 COL1A2 13.26 13.37 8.83 7.95E-09 6.75E-06 7965565 84101 ubiquitin specific peptidase 44 USP44 5.54 5.86 11.63 8.35E-09 6.89E-06 8121251 389421 lin-28 homolog B (C. elegans) LIN28B 4.78 4.68 9.34 9.02E-09 7.23E-06 7923582 6.21 6.69 9.27 1.00E-08 7.83E-06 8069668 116159 cysteine/tyrosine-rich 1 CYYR1 6.27 6.29 10.23 1.14E-08 8.65E-06 8016646 1277 collagen, type I, alpha 1 COL1A1 13.68 13.78 9.54 1.31E-08 9.24E-06 8020779 1829 desmoglein 2 DSG2 5.12 5.06 10.83 1.36E-08 9.24E-06 8129783 9053 microtubule-associated protein 7 MAP7 7.03 6.90 10.13 1.40E-08 9.24E-06 8133976 10926 DBF4 4.75 4.91 6.91 1.42E-08 9.24E-06 7927631 22943 dickkopf homolog 1 (Xenopus laevis) DKK1 10.71 12.13 6.02 1.44E-08 9.24E-06 8111524 167127 UDP glycosyltransferase 3 family, polypeptide A2 UGT3A2 6.48 6.19 10.34 1.30E-08 9.24E-06 79923, NANOG|N 7987365 Nanog homeobox | Nanog homeobox pseudogene 1 6.54 6.40 11.82 1.37E-08 9.24E-06 404635 ANOGP1 8035855 148213 zinc finger protein 681 ZNF681 5.59 5.40 8.69 1.54E-08 9.64E-06 8046003 25801 grancalcin, EF-hand calcium binding protein GCA 5.19 4.81 8.60 1.65E-08 1.01E-05 matrix metallopeptidase 2 (gelatinase A, 72kDa 7995681 4313 MMP2 13.34 13.54 9.11 1.71E-08 1.02E-05 gelatinase, 72kDa type IV collagenase) 8167185 7076 TIMP metallopeptidase inhibitor 1 TIMP1 13.81 13.86 11.29 1.75E-08 1.02E-05 8133983 53616 ADAM metallopeptidase domain 22 ADAM22 5.14 5.29 7.19 1.77E-08 1.02E-05 carbohydrate (N-acetylgalactosamine 4-0) 8022666 83539 CHST9 5.32 5.29 8.17 1.84E-08 1.03E-05 sulfotransferase 9 8089988 131076 coiled-coil domain containing 58 CCDC58 7.11 7.39 9.63 1.86E-08 1.03E-05 7955869 3224 homeobox C8 HOXC8 6.91 10.08 6.28 1.93E-08 1.05E-05 8033767 147741 zinc finger protein 560 ZNF560 6.54 5.55 10.02 2.03E-08 1.08E-05 small nuclear ribonucleoprotein D3 polypeptide 18kDa SNRPD3|C 8071920 6634, 83606 8.14 8.16 10.18 2.05E-08 1.08E-05 | chromosome 22 open reading frame 13 22orf13 8179041 3105 major histocompatibility complex, class I, A HLA-A 13.34 13.17 11.36 2.17E-08 1.10E-05 8000574 26471 nuclear protein, transcriptional regulator, 1 NUPR1 12.59 12.48 7.18 2.16E-08 1.10E-05 UDP-Gal:betaGlcNAc beta 1,3-galactosyltransferase, 8046078 8708 B3GALT1 5.47 5.23 10.60 2.45E-08 1.20E-05 polypeptide 1 8020806 54941 ring finger protein 125 RNF125 5.46 5.45 9.19 2.45E-08 1.20E-05 8115691 6586 slit homolog 3 (Drosophila) SLIT3 12.61 12.72 6.58 2.53E-08 1.22E-05 8147351 54845 epithelial splicing regulatory protein 1 ESRP1 5.66 5.90 11.38 2.60E-08 1.23E-05 LOC44166 8045330 441666 zinc finger protein 91 pseudogene 4.64 4.60 6.56 2.67E-08 1.25E-05 6 8171359 2824 glycoprotein M6B GPM6B 5.48 5.49 9.47 3.17E-08 1.38E-05 7980152 4053 latent transforming growth factor beta binding protein 2 LTBP2 11.85 12.51 6.74 3.25E-08 1.38E-05 nuclear factor I/X (CCAAT-binding transcription 8026139 4784 NFIX 11.54 11.60 7.05 3.10E-08 1.38E-05 factor) 8097017 7368 UDP glycosyltransferase 8 UGT8 5.89 5.78 9.96 3.08E-08 1.38E-05 7998898 9074 claudin 6 CLDN6 6.29 6.34 12.57 3.21E-08 1.38E-05 cysteine-rich secretory protein LCCL domain 8146967 83690 CRISPLD1 5.45 5.31 9.12 3.16E-08 1.38E-05 containing 1 8138805 54504 carboxypeptidase, vitellogenic-like CPVL 6.08 5.98 8.52 3.33E-08 1.39E-05 8108217 7045 transforming growth factor, beta-induced, 68kDa TGFBI 13.46 13.68 8.32 3.39E-08 1.40E-05 7996819 1001 cadherin 3, type 1, P-cadherin (placental) CDH3 6.23 6.24 11.23 3.46E-08 1.41E-05 7960744 715 complement component 1, r subcomponent C1R 12.84 12.14 7.67 3.69E-08 1.46E-05 8006187 79915 ATPase family, AAA domain containing 5 ATAD5 5.42 5.42 8.62 3.69E-08 1.46E-05 major histocompatibility complex, class I, C | major HLA- 8124901 3107, 3106 12.78 12.55 10.89 3.90E-08 1.52E-05 histocompatibility complex, class I, B C|HLA-B 8170200 7547 Zic family member 3 (odd-paired homolog, Drosophila) ZIC3 5.76 5.94 10.18 3.96E-08 1.53E-05 solute carrier family 16, member 10 (aromatic amino 8121515 117247 SLC16A10 6.31 6.27 10.36 4.10E-08 1.56E-05 acid transporter) 8067955 1525 coxsackie virus and adenovirus receptor CXADR 6.58 6.51 12.49 4.29E-08 1.59E-05 mutS homolog 2, colon cancer, nonpolyposis type 1 (E.
Recommended publications
  • Implications in Parkinson's Disease
    Journal of Clinical Medicine Review Lysosomal Ceramide Metabolism Disorders: Implications in Parkinson’s Disease Silvia Paciotti 1,2 , Elisabetta Albi 3 , Lucilla Parnetti 1 and Tommaso Beccari 3,* 1 Laboratory of Clinical Neurochemistry, Department of Medicine, University of Perugia, Sant’Andrea delle Fratte, 06132 Perugia, Italy; [email protected] (S.P.); [email protected] (L.P.) 2 Section of Physiology and Biochemistry, Department of Experimental Medicine, University of Perugia, Sant’Andrea delle Fratte, 06132 Perugia, Italy 3 Department of Pharmaceutical Sciences, University of Perugia, Via Fabretti, 06123 Perugia, Italy; [email protected] * Correspondence: [email protected] Received: 29 January 2020; Accepted: 20 February 2020; Published: 21 February 2020 Abstract: Ceramides are a family of bioactive lipids belonging to the class of sphingolipids. Sphingolipidoses are a group of inherited genetic diseases characterized by the unmetabolized sphingolipids and the consequent reduction of ceramide pool in lysosomes. Sphingolipidoses include several disorders as Sandhoff disease, Fabry disease, Gaucher disease, metachromatic leukodystrophy, Krabbe disease, Niemann Pick disease, Farber disease, and GM2 gangliosidosis. In sphingolipidosis, lysosomal lipid storage occurs in both the central nervous system and visceral tissues, and central nervous system pathology is a common hallmark for all of them. Parkinson’s disease, the most common neurodegenerative movement disorder, is characterized by the accumulation and aggregation of misfolded α-synuclein that seem associated to some lysosomal disorders, in particular Gaucher disease. This review provides evidence into the role of ceramide metabolism in the pathophysiology of lysosomes, highlighting the more recent findings on its involvement in Parkinson’s disease. Keywords: ceramide metabolism; Parkinson’s disease; α-synuclein; GBA; GLA; HEX A-B; GALC; ASAH1; SMPD1; ARSA * Correspondence [email protected] 1.
    [Show full text]
  • Katalog 2015 Cover Paul Lin *Hinweis Förderung.Indd
    Product List 2015 WE LIVE SERVICE Certificates quartett owns two productions sites that are certified according to EN ISO 9001:2008 Quality management systems - Requirements EN ISO 13485:2012 + AC:2012 Medical devices - Quality management systems - Requirements for regulatory purposes GMP Conformity Our quality management guarantees products of highest quality! 2 Foreword to the quartett product list 2015 quartett Immunodiagnostika, Biotechnologie + Kosmetik Vertriebs GmbH welcomes you as one of our new business partners as well as all of our previous loyal clients. You are now member of quartett´s worldwide customers. First of all we would like to introduce ourselves to you. Founded as a family-run company in 1986, quartett ensures for more than a quarter of a century consistent quality of products. Service and support of our valued customers are our daily businesses. And we will continue! In the end 80´s quartett offered radioimmunoassay and enzyme immunoassay kits from different manufacturers in the USA. In the beginning 90´s the company changed its strategy from offering products for routine diagnostic to the increasing field of research and development. Setting up a production plant in 1997 and a second one in 2011 supported this decision. The company specialized its product profile in the field of manufacturing synthetic peptides for antibody production, peptides such as protease inhibitors, biochemical reagents and products for histology, cytology and immunohistology. All products are exclusively manufactured in Germany without outsourcing any production step. Nowadays, we expand into all other diagnostic and research fields and supply our customers in universities, government institutes, pharmaceutical and biotechnological companies, hospitals, and private doctor offices.
    [Show full text]
  • Human Transcription Factor Protein-Protein Interactions in Health and Disease
    HELKA GÖÖS GÖÖS HELKA Recent Publications in this Series 45/2019 Mgbeahuruike Eunice Ego Evaluation of the Medicinal Uses and Antimicrobial Activity of Piper guineense (Schumach & Thonn) 46/2019 Suvi Koskinen AND DISEASE IN HEALTH INTERACTIONS PROTEIN-PROTEIN FACTOR HUMAN TRANSCRIPTION Near-Occlusive Atherosclerotic Carotid Artery Disease: Study with Computed Tomography Angiography 47/2019 Flavia Fontana DISSERTATIONES SCHOLAE DOCTORALIS AD SANITATEM INVESTIGANDAM Biohybrid Cloaked Nanovaccines for Cancer Immunotherapy UNIVERSITATIS HELSINKIENSIS 48/2019 Marie Mennesson Kainate Receptor Auxiliary Subunits Neto1 and Neto2 in Anxiety and Fear-Related Behaviors 49/2019 Zehua Liu Porous Silicon-Based On-Demand Nanohybrids for Biomedical Applications 50/2019 Veer Singh Marwah Strategies to Improve Standardization and Robustness of Toxicogenomics Data Analysis HELKA GÖÖS 51/2019 Iryna Hlushchenko Actin Regulation in Dendritic Spines: From Synaptic Plasticity to Animal Behavior and Human HUMAN TRANSCRIPTION FACTOR PROTEIN-PROTEIN Neurodevelopmental Disorders 52/2019 Heini Liimatta INTERACTIONS IN HEALTH AND DISEASE Efectiveness of Preventive Home Visits among Community-Dwelling Older People 53/2019 Helena Karppinen Older People´s Views Related to Their End of Life: Will-to-Live, Wellbeing and Functioning 54/2019 Jenni Laitila Elucidating Nebulin Expression and Function in Health and Disease 55/2019 Katarzyna Ciuba Regulation of Contractile Actin Structures in Non-Muscle Cells 56/2019 Sami Blom Spatial Characterisation of Prostate Cancer by Multiplex
    [Show full text]
  • The Roles of Histone Deacetylase 5 and the Histone Methyltransferase Adaptor WDR5 in Myc Oncogenesis
    The Roles of Histone Deacetylase 5 and the Histone Methyltransferase Adaptor WDR5 in Myc oncogenesis By Yuting Sun This thesis is submitted in fulfilment of the requirements for the degree of Doctor of Philosophy at the University of New South Wales Children’s Cancer Institute Australia for Medical Research School of Women’s and Children’s Health, Faculty of Medicine University of New South Wales Australia August 2014 PLEASE TYPE THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet Surname or Family name: Sun First name: Yuting Other name/s: Abbreviation for degree as given in the University calendar: PhD School : School of·Women's and Children's Health Faculty: Faculty of Medicine Title: The Roles of Histone Deacetylase 5 and the Histone Methyltransferase Adaptor WDR5 in Myc oncogenesis. Abstract 350 words maximum: (PLEASE TYPE) N-Myc Induces neuroblastoma by regulating the expression of target genes and proteins, and N-Myc protein is degraded by Fbxw7 and NEDD4 and stabilized by Aurora A. The class lla histone deacetylase HDAC5 suppresses gene transcription, and blocks myoblast and leukaemia cell differentiation. While histone H3 lysine 4 (H3K4) trimethylation at target gene promoters is a pre-requisite for Myc· induced transcriptional activation, WDRS, as a histone H3K4 methyltransferase presenter, is required for H3K4 methylation and transcriptional activation mediated by a histone H3K4 methyltransferase complex. Here, I investigated the roles of HDAC5 and WDR5 in N-Myc overexpressing neuroblastoma. I have found that N-Myc upregulates HDAC5 protein expression, and that HDAC5 represses NEDD4 gene expression, increases Aurora A gene expression and consequently upregulates N-Myc protein expression in neuroblastoma cells.
    [Show full text]
  • Broad and Thematic Remodeling of the Surface Glycoproteome on Isogenic
    bioRxiv preprint doi: https://doi.org/10.1101/808139; this version posted October 17, 2019. 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-NC-ND 4.0 International license. Broad and thematic remodeling of the surface glycoproteome on isogenic cells transformed with driving proliferative oncogenes Kevin K. Leung1,5, Gary M. Wilson2,5, Lisa L. Kirkemo1, Nicholas M. Riley2,4, Joshua J. Coon2,3, James A. Wells1* 1Department of Pharmaceutical Chemistry, UCSF, San Francisco, CA, USA Departments of Chemistry2 and Biomolecular Chemistry3, University of Wisconsin- Madison, Madison, WI, 53706, USA 4Present address Department of Chemistry, Stanford University, Stanford, CA, 94305, USA 5These authors contributed equally *To whom correspondence should be addressed bioRxiv preprint doi: https://doi.org/10.1101/808139; this version posted October 17, 2019. 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-NC-ND 4.0 International license. Abstract: The cell surface proteome, the surfaceome, is the interface for engaging the extracellular space in normal and cancer cells. Here We apply quantitative proteomics of N-linked glycoproteins to reveal how a collection of some 700 surface proteins is dramatically remodeled in an isogenic breast epithelial cell line stably expressing any of six of the most prominent proliferative oncogenes, including the receptor tyrosine kinases, EGFR and HER2, and downstream signaling partners such as KRAS, BRAF, MEK and AKT.
    [Show full text]
  • 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.
    [Show full text]
  • Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
    Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database.
    [Show full text]
  • Genomic Approaches to Reproductive Disorders
    Genomic Approaches to Reproductive Disorders Aleksandar Rajkovic Dept Obstetrics Gynecology and Reproductive Sciences University of Pittsburgh Magee Womens Research Institute Pittsburgh, PA Preconceptional Care Scope • Half of Pregnancies are Unintended • Medical Conditions • Mental Conditions • Immunization History • Nutritional Issues • Family History/Genetic Risk • Occupational/Environmental Exposures • Tobacco/Drug Abuse • Social Issues Preconceptional genetic screening Ethnic: Sickle cell disease Tay–Sachs disease Pan-ethnic: cystic fibrosis fragile X syndrome Spinal muscular atrophy Mendelian Inheritance • 5593 phenotypes for which molecular basis known • 3452 genes with phenotype causing mutation • Over 15,000 mutations to date known Preconceptional Pan Ethnic Testing • Screens for known mutations in more than 100 genes, easy on genetic counsellors • The screen is pan-ethnic • Useful also for couples undergoing IVF and potentially PGD • 1:5 will be carriers of a Mendelian disorder. • $600 (529 Euros) for the couple Genetic Counselling • Objective of the test • Test Methodology • Type of sample required (parents, siblings) • Possible outcomes (abnormal results, result of unknown clinical significance) ClinVar Stars and their interpretation Number of golden stars No submitter provided an interpretation with assertion criteria (no assertion criteria provided), none or no interpretation was provided (no assertion provided) At least one submitter provided an interpretation with assertion criteria (criteria provided, single submitter)
    [Show full text]
  • Yeast Genome Gazetteer P35-65
    gazetteer Metabolism 35 tRNA modification mitochondrial transport amino-acid metabolism other tRNA-transcription activities vesicular transport (Golgi network, etc.) nitrogen and sulphur metabolism mRNA synthesis peroxisomal transport nucleotide metabolism mRNA processing (splicing) vacuolar transport phosphate metabolism mRNA processing (5’-end, 3’-end processing extracellular transport carbohydrate metabolism and mRNA degradation) cellular import lipid, fatty-acid and sterol metabolism other mRNA-transcription activities other intracellular-transport activities biosynthesis of vitamins, cofactors and RNA transport prosthetic groups other transcription activities Cellular organization and biogenesis 54 ionic homeostasis organization and biogenesis of cell wall and Protein synthesis 48 plasma membrane Energy 40 ribosomal proteins organization and biogenesis of glycolysis translation (initiation,elongation and cytoskeleton gluconeogenesis termination) organization and biogenesis of endoplasmic pentose-phosphate pathway translational control reticulum and Golgi tricarboxylic-acid pathway tRNA synthetases organization and biogenesis of chromosome respiration other protein-synthesis activities structure fermentation mitochondrial organization and biogenesis metabolism of energy reserves (glycogen Protein destination 49 peroxisomal organization and biogenesis and trehalose) protein folding and stabilization endosomal organization and biogenesis other energy-generation activities protein targeting, sorting and translocation vacuolar and lysosomal
    [Show full text]
  • Congenital Disorders of Glycosylation from a Neurological Perspective
    brain sciences Review Congenital Disorders of Glycosylation from a Neurological Perspective Justyna Paprocka 1,* , Aleksandra Jezela-Stanek 2 , Anna Tylki-Szyma´nska 3 and Stephanie Grunewald 4 1 Department of Pediatric Neurology, Faculty of Medical Science in Katowice, Medical University of Silesia, 40-752 Katowice, Poland 2 Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland; [email protected] 3 Department of Pediatrics, Nutrition and Metabolic Diseases, The Children’s Memorial Health Institute, W 04-730 Warsaw, Poland; [email protected] 4 NIHR Biomedical Research Center (BRC), Metabolic Unit, Great Ormond Street Hospital and Institute of Child Health, University College London, London SE1 9RT, UK; [email protected] * Correspondence: [email protected]; Tel.: +48-606-415-888 Abstract: Most plasma proteins, cell membrane proteins and other proteins are glycoproteins with sugar chains attached to the polypeptide-glycans. Glycosylation is the main element of the post- translational transformation of most human proteins. Since glycosylation processes are necessary for many different biological processes, patients present a diverse spectrum of phenotypes and severity of symptoms. The most frequently observed neurological symptoms in congenital disorders of glycosylation (CDG) are: epilepsy, intellectual disability, myopathies, neuropathies and stroke-like episodes. Epilepsy is seen in many CDG subtypes and particularly present in the case of mutations
    [Show full text]
  • Genome-Wide Association Study and Admixture Mapping Reveal New Loci Associated with Total Ige Levels in Latinos
    Henry Ford Health System Henry Ford Health System Scholarly Commons Center for Health Policy and Health Services Center for Health Policy and Health Services Research Articles Research 6-1-2015 Genome-wide association study and admixture mapping reveal new loci associated with total IgE levels in Latinos Maria Pino-Yanes Christopher R. Gignoux Joshua M. Galanter Albert M. Levin Henry Ford Health System, [email protected] Catarina D. Campbell See next page for additional authors Follow this and additional works at: https://scholarlycommons.henryford.com/chphsr_articles Recommended Citation Pino-Yanes M, Gignoux CR, Galanter JM, Levin AM, Campbell CD, Eng C, Huntsman S, Nishimura KK, Gourraud P, Mohajeri K, O'Roak B, Hu D, Mathias RA, Nguyen EA, Roth LA, Padhukasahasram B, Moreno- Estrada A, Sandoval K, Winkler CA, Lurmann F, Davis A, Farber HJ, Meade K, Avila PC, Serebrisky D, Chapela R, Ford JG, Lenoir MA, Thyne SM, Brigino-Buenaventura E, Borrell LN, Rodriguez-Cintron W, Sen S, Kumar R, Rodriguez-Santana JR, Bustamante CD, Martinez FD, Raby BA, Weiss ST, Nicolae DL, Ober C, Meyers DA, Bleecker ER, Mack SJ, Hernandez RD, Eichler EE, Barnes KC, Williams KL, Torgerson DG, Burchard EG. Genome-wide association study and admixture mapping reveal new loci associated with total IgE levels in Latinos. Journal of Allergy and Clinical Immunology 2015; 135(6):1502-1510. This Article is brought to you for free and open access by the Center for Health Policy and Health Services Research at Henry Ford Health System Scholarly Commons. It has been accepted for inclusion in Center for Health Policy and Health Services Research Articles by an authorized administrator of Henry Ford Health System Scholarly Commons.
    [Show full text]
  • Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses
    bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract The high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a proteinprotein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes.
    [Show full text]