Gene Coverage

Total Page:16

File Type:pdf, Size:1020Kb

Gene Coverage Laboratory for Molecular Medicine 65 Landsdowne Street • Cambridge, MA 02139 Phone: (617) 768-8500 • Fax: (617) 768-8513 www.partners.org/personalizedmedicine/lmm LMM/Broad Genome LMM Exome Average Average Completeness Completeness Gene %_above_15X %_above_15X Last Updated 01.06.2020 Last Updated 09.04.2019 A1BG 100.00 100.00 A1CF 100.00 100.00 A2M 100.00 100.00 A2ML1 100.00 99.94 A3GALT2 100.00 98.40 A4GALT 100.00 100.00 A4GNT 100.00 100.00 AAAS 100.00 100.00 AACS 100.00 99.92 AADAC 100.00 100.00 AADACL2 100.00 100.00 AADACL3 100.00 99.23 AADACL4 100.00 100.00 AADAT 100.00 94.59 AAED1 100.00 70.31 AAGAB 100.00 100.00 AAK1 100.00 96.61 AAMDC 100.00 100.00 AAMP 100.00 99.74 AANAT 100.00 100.00 AAR2 100.00 100.00 AARD 100.00 99.03 AARS 100.00 100.00 AARS2 100.00 100.00 AARSD1 100.00 100.00 AASDH 100.00 98.73 AASDHPPT 100.00 99.28 AASS 99.97 100.00 AATF 100.00 99.98 AATK 100.00 96.68 ABAT 100.00 100.00 ABCA1 100.00 100.00 ABCA10 100.00 98.23 ABCA12 100.00 100.00 ABCA13 100.00 100.00 ABCA2 100.00 99.23 ABCA3 100.00 100.00 ABCA4 100.00 100.00 ABCA5 100.00 93.36 ABCA6 100.00 95.45 ABCA7 100.00 99.27 ABCA8 100.00 98.28 ABCA9 100.00 99.58 ABCB1 100.00 96.00 ABCB10 100.00 73.99 ABCB11 100.00 100.00 ABCB4 100.00 100.00 ABCB5 100.00 99.49 ABCB6 100.00 100.00 ABCB7 100.00 99.98 ABCB8 100.00 100.00 ABCB9 100.00 99.80 ABCC1 100.00 98.90 ABCC10 100.00 99.70 ABCC11 100.00 100.00 ABCC12 100.00 99.98 ABCC2 100.00 100.00 ABCC3 100.00 99.73 ABCC4 100.00 100.00 ABCC5 100.00 99.99 ABCC6 100.00 93.40 ABCC8 100.00 100.00 ABCC9 100.00 100.00 ABCD1 100.00 97.63 ABCD2 100.00 99.98 ABCD3 100.00 99.87 ABCD4 100.00 100.00 ABCE1 100.00 77.00 ABCF1 100.00 99.23 ABCF2 100.00 100.00 ABCF3 100.00 100.00 ABCG1 100.00 99.66 ABCG2 100.00 100.00 ABCG4 100.00 99.98 ABCG5 100.00 100.00 ABCG8 100.00 100.00 ABHD1 100.00 100.00 ABHD10 100.00 99.63 ABHD11 100.00 99.99 ABHD12 100.00 93.99 ABHD12B 100.00 88.73 ABHD13 100.00 100.00 ABHD14A 100.00 90.51 ABHD14A-ACY1 100.00 100.00 ABHD14B 100.00 93.97 ABHD15 100.00 98.08 ABHD16A 100.00 99.36 ABHD16B 100.00 100.00 ABHD17A 100.00 29.55 ABHD17B 100.00 100.00 ABHD17C 100.00 91.51 ABHD18 100.00 99.64 ABHD2 100.00 99.99 ABHD3 100.00 99.94 ABHD4 100.00 100.00 ABHD5 100.00 100.00 ABHD6 100.00 99.52 ABHD8 100.00 99.79 ABI1 100.00 99.38 ABI2 100.00 99.61 ABI3 100.00 99.10 ABI3BP 100.00 99.99 ABL1 100.00 100.00 ABL2 100.00 97.04 ABLIM1 100.00 99.73 ABLIM2 100.00 100.00 ABLIM3 100.00 99.12 ABO 100.00 98.10 ABR 100.00 88.72 ABRA 100.00 100.00 ABRACL 100.00 100.00 ABRAXAS1 100.00 99.67 ABRAXAS2 100.00 100.00 ABT1 100.00 100.00 ABTB1 100.00 99.85 ABTB2 100.00 96.78 ACAA1 100.00 99.82 ACAA2 100.00 67.57 ACACA 100.00 99.99 ACACB 100.00 100.00 ACAD10 100.00 100.00 ACAD11 100.00 99.95 ACAD8 100.00 100.00 ACAD9 100.00 100.00 ACADL 100.00 99.45 ACADM 100.00 100.00 ACADS 100.00 98.72 ACADSB 100.00 99.76 ACADVL 100.00 99.81 ACAN 84.80 86.33 ACAP1 100.00 99.62 ACAP2 100.00 99.68 ACAP3 100.00 97.66 ACAT1 99.99 99.75 ACAT2 100.00 100.00 ACBD3 100.00 97.18 ACBD4 100.00 99.49 ACBD5 100.00 99.90 ACBD6 100.00 100.00 ACBD7 100.00 100.00 ACCS 100.00 100.00 ACCSL 100.00 99.98 ACD 100.00 100.00 ACE 100.00 100.00 ACE2 100.00 98.17 ACER1 100.00 100.00 ACER2 100.00 99.97 ACER3 100.00 96.40 ACHE 100.00 100.00 ACIN1 100.00 98.49 ACKR1 100.00 100.00 ACKR2 100.00 100.00 ACKR3 100.00 100.00 ACKR4 100.00 100.00 ACLY 100.00 100.00 ACMSD 100.00 99.92 ACO1 100.00 100.00 ACO2 100.00 99.38 ACOD1 100.00 99.99 ACOT1 81.43 65.89 ACOT11 99.80 97.98 ACOT12 100.00 95.23 ACOT13 100.00 100.00 ACOT2 85.10 95.11 ACOT4 100.00 99.78 ACOT6 100.00 100.00 ACOT7 100.00 97.32 ACOT8 100.00 100.00 ACOT9 100.00 94.44 ACOX1 100.00 100.00 ACOX2 100.00 99.82 ACOX3 100.00 100.00 ACOXL 100.00 99.91 ACP1 100.00 100.00 ACP2 100.00 100.00 ACP4 100.00 89.58 ACP5 100.00 100.00 ACP6 100.00 94.67 ACP7 100.00 99.44 ACPP 100.00 99.34 ACR 89.47 78.25 ACRBP 100.00 100.00 ACRV1 100.00 100.00 ACSBG1 100.00 99.71 ACSBG2 100.00 99.87 ACSF2 100.00 97.04 ACSF3 100.00 100.00 ACSL1 100.00 99.80 ACSL3 100.00 99.23 ACSL4 100.00 99.66 ACSL5 100.00 100.00 ACSL6 100.00 100.00 ACSM1 100.00 99.82 ACSM2A 100.00 100.00 ACSM2B 99.66 100.00 ACSM3 100.00 100.00 ACSM4 100.00 99.28 ACSM5 100.00 91.85 ACSM6 100.00 100.00 ACSS1 100.00 99.16 ACSS2 100.00 93.00 ACSS3 100.00 98.89 ACTA1 100.00 100.00 ACTA2 100.00 100.00 ACTB 100.00 100.00 ACTBL2 100.00 99.93 ACTC1 100.00 100.00 ACTG1 100.00 100.00 ACTG2 100.00 99.98 ACTL10 100.00 100.00 ACTL6A 100.00 99.90 ACTL6B 100.00 99.91 ACTL7A 100.00 100.00 ACTL7B 100.00 100.00 ACTL8 100.00 100.00 ACTL9 100.00 100.00 ACTN1 100.00 99.72 ACTN2 100.00 100.00 ACTN3 100.00 95.64 ACTN4 100.00 98.10 ACTR10 100.00 95.76 ACTR1A 100.00 99.97 ACTR1B 100.00 99.98 ACTR2 100.00 97.19 ACTR3 100.00 91.40 ACTR3B 100.00 98.11 ACTR3C 98.46 89.27 ACTR5 100.00 93.55 ACTR6 100.00 94.24 ACTR8 100.00 100.00 ACTRT1 100.00 99.97 ACTRT2 100.00 99.99 ACTRT3 100.00 100.00 ACVR1 100.00 100.00 ACVR1B 100.00 99.84 ACVR1C 100.00 100.00 ACVR2A 99.80 100.00 ACVR2B 100.00 96.69 ACVRL1 100.00 100.00 ACY1 100.00 100.00 ACY3 100.00 98.61 ACYP1 100.00 100.00 ACYP2 100.00 50.87 ADA 100.00 100.00 ADA2 100.00 96.89 ADAD1 100.00 97.80 ADAD2 100.00 100.00 ADAL 100.00 99.80 ADAM10 100.00 99.97 ADAM11 100.00 97.00 ADAM12 100.00 99.72 ADAM15 100.00 96.24 ADAM17 100.00 100.00 ADAM18 100.00 96.77 ADAM19 100.00 99.11 ADAM2 100.00 96.92 ADAM20 100.00 100.00 ADAM21 100.00 99.95 ADAM22 100.00 100.00 ADAM23 100.00 97.03 ADAM28 100.00 98.51 ADAM29 100.00 100.00 ADAM30 100.00 100.00 ADAM32 100.00 90.26 ADAM33 100.00 100.00 ADAM7 100.00 100.00 ADAM8 100.00 95.20 ADAM9 100.00 100.00 ADAMDEC1 100.00 99.46 ADAMTS1 100.00 100.00 ADAMTS10 100.00 99.97 ADAMTS12 100.00 99.86 ADAMTS13 100.00 96.49 ADAMTS14 100.00 99.40 ADAMTS15 100.00 100.00 ADAMTS16 100.00 98.42 ADAMTS17 100.00 89.29 ADAMTS18 100.00 99.90 ADAMTS19 100.00 92.36 ADAMTS2 100.00 95.57 ADAMTS20 100.00 99.41 ADAMTS3 100.00 99.42 ADAMTS4 100.00 97.91 ADAMTS5 100.00 99.64 ADAMTS6 100.00 99.95 ADAMTS7 100.00 47.31 ADAMTS8 100.00 98.95 ADAMTS9 99.99 97.97 ADAMTSL1 100.00 99.93 ADAMTSL2 43.83 39.55 ADAMTSL3 100.00 100.00 ADAMTSL4 100.00 99.99 ADAMTSL5 100.00 99.25 ADAP1 100.00 98.05 ADAP2 100.00 98.97 ADAR 100.00 100.00 ADARB1 100.00 97.47 ADARB2 100.00 99.87 ADAT1 100.00 100.00 ADAT2 100.00 100.00 ADAT3 100.00 99.83 ADCK1 100.00 99.89 ADCK2 100.00 99.91 ADCK5 99.90 99.32 ADCY1 100.00 94.33 ADCY10 100.00 100.00 ADCY2 100.00 98.57 ADCY3 100.00 99.98 ADCY4 100.00 100.00 ADCY5 100.00 99.74 ADCY6 100.00 100.00 ADCY7 100.00 100.00 ADCY8 99.96 99.56 ADCY9 100.00 100.00 ADCYAP1 100.00 99.69 ADCYAP1R1 100.00 100.00 ADD1 100.00 100.00 ADD2 100.00 100.00 ADD3 100.00 100.00 ADGB 100.00 96.88 ADGRA1 100.00 100.00 ADGRA2 100.00 97.39 ADGRA3 100.00 92.59 ADGRB1 99.99 94.09 ADGRB2 100.00 98.82 ADGRB3 100.00 99.12 ADGRD1 100.00 99.92 ADGRE1 100.00 99.78 ADGRE2 96.40 99.46 ADGRE3 100.00 99.91 ADGRE5 96.79 98.41 ADGRF1 100.00 99.84 ADGRF2 100.00 100.00 ADGRF3 100.00 99.99 ADGRF4 100.00 100.00 ADGRF5 100.00 93.10 ADGRG1 100.00 100.00 ADGRG2 100.00 96.15 ADGRG3 100.00 99.99 ADGRG4 100.00 98.88 ADGRG5 100.00 99.98 ADGRG6 100.00 99.66 ADGRG7 100.00 99.93 ADGRL1 100.00 96.59 ADGRL2 100.00 99.87 ADGRL3 99.96 99.68 ADGRL4 100.00 93.95 ADGRV1 100.00 100.00 ADH1A 100.00 100.00 ADH1B 100.00 99.99 ADH1C 100.00 100.00 ADH4 100.00 100.00 ADH5 100.00 100.00 ADH6 100.00 99.86 ADH7 100.00 100.00 ADHFE1 100.00 99.93 ADI1 100.00 97.90 ADIG 100.00 100.00 ADIPOQ 100.00 100.00 ADIPOR1 100.00 100.00 ADIPOR2 100.00 99.94 ADIRF 100.00 100.00 ADK 100.00 99.74 ADM 100.00 100.00 ADM2 100.00 99.84 ADM5 100.00 100.00 ADNP 100.00 100.00 ADNP2 100.00 99.72 ADO 100.00 99.91 ADORA1 100.00 100.00 ADORA2A 100.00 100.00 ADORA2B 100.00 100.00 ADORA3 100.00 100.00 ADPGK 100.00 97.36 ADPRH 100.00 100.00 ADPRHL1 100.00 97.77 ADPRHL2 100.00 100.00 ADPRM 100.00 100.00 ADRA1A 100.00 99.21 ADRA1B 99.97 86.15 ADRA1D 100.00 90.64 ADRA2A 100.00 99.97 ADRA2B 100.00 100.00 ADRA2C 100.00 97.44 ADRB1 100.00 99.44 ADRB2 100.00 100.00 ADRB3 100.00 100.00 ADRM1 100.00 100.00 ADSL 100.00 100.00 ADSS 100.00 94.71 ADSSL1 100.00 94.63 ADTRP 100.00 100.00 AEBP1 100.00 99.98 AEBP2 100.00 86.97 AEN 100.00 100.00 AES 100.00 80.22 AFAP1 100.00 99.99 AFAP1L1 100.00 99.52 AFAP1L2 100.00 99.97 AFDN 100.00 99.68 AFF1 100.00 98.51 AFF2 100.00 99.78 AFF3 100.00 98.50 AFF4 100.00 99.70 AFG1L 100.00 99.92 AFG3L2 100.00 94.46 AFM 100.00 100.00 AFMID 100.00 100.00 AFP 100.00 99.97 AFTPH 100.00 100.00 AGA 100.00 100.00 AGAP1 100.00 98.47 AGAP11 100.00 78.54 AGAP2 100.00 97.42 AGAP3 99.91 91.79 AGAP4 24.90 9.13 AGAP5 99.70 62.50 AGAP6 100.00 62.43 AGAP9 9.19 7.91 AGBL1 100.00 98.40 AGBL2 100.00 98.31 AGBL3 100.00 99.23 AGBL4 100.00 99.65 AGBL5 100.00 99.99 AGER 100.00 100.00 AGFG1 100.00 99.16 AGFG2 100.00 99.96 AGGF1 100.00 100.00 AGK 100.00 99.61 AGL 100.00 100.00 AGMAT 100.00 98.51 AGMO 100.00 100.00 AGO1 100.00 100.00 AGO2 100.00 98.99 AGO3 100.00 99.95 AGO4 100.00 99.10 AGPAT1 100.00 100.00 AGPAT2 100.00 100.00 AGPAT3 100.00 100.00 AGPAT4 100.00 100.00 AGPAT5 100.00 97.08 AGPS 100.00 99.97 AGR2 100.00 99.98 AGR3 100.00 86.57 AGRN 100.00 96.35 AGRP 100.00 100.00 AGT 100.00 100.00 AGTPBP1 100.00 95.09 AGTR1 100.00 100.00 AGTR2 100.00 100.00 AGTRAP 100.00 99.95 AGXT 100.00 100.00 AGXT2 100.00 100.00 AHCTF1 100.00 79.56 AHCY 100.00 98.90 AHCYL1 100.00 100.00 AHCYL2 100.00 99.33 AHDC1 100.00 97.91 AHI1 100.00 99.94 AHNAK 100.00 99.91 AHNAK2 90.17 96.80 AHR 100.00 100.00 AHRR 100.00 99.72 AHSA1 100.00 100.00 AHSG 100.00 100.00 AHSP 100.00 100.00 AICDA 100.00 100.00 AIDA 100.00 84.71 AIF1 100.00 99.81 AIF1L 100.00 99.50 AIFM1 100.00 99.97 AIFM2 100.00 99.97 AIFM3 100.00 99.58 AIG1 100.00
Recommended publications
  • ANP32A and ANP32B Are Key Factors in the Rev Dependent CRM1 Pathway
    bioRxiv preprint doi: https://doi.org/10.1101/559096; this version posted February 24, 2019. 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. 1 ANP32A and ANP32B are key factors in the Rev dependent CRM1 pathway 2 for nuclear export of HIV-1 unspliced mRNA 3 Yujie Wang1, Haili Zhang1, Lei Na 1, Cheng Du1, Zhenyu Zhang1, Yong-Hui Zheng1,2, Xiaojun Wang1* 4 1State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, the Chinese 5 Academy of Agricultural Sciences, Harbin 150069, China 6 2Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, 7 USA. 8 * Address correspondence to Xiaojun Wang, [email protected]. 9 10 11 12 13 14 15 16 17 18 19 20 21 1 bioRxiv preprint doi: https://doi.org/10.1101/559096; this version posted February 24, 2019. 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. 22 Abstract 23 The nuclear export receptor CRM1 is an important regulator involved in the shuttling of various cellular 24 and viral RNAs between the nucleus and the cytoplasm. HIV-1 Rev interacts with CRM1 in the late phase of 25 HIV-1 replication to promote nuclear export of unspliced and single spliced HIV-1 transcripts. However, the 26 knowledge of cellular factors that are involved in the CRM1-dependent viral RNA nuclear export remains 27 inadequate. Here, we identified that ANP32A and ANP32B mediate the export of unspliced or partially spliced 28 viral mRNA via interacting with Rev and CRM1.
    [Show full text]
  • 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]
  • Epithelial Delamination Is Protective During Pharmaceutical-Induced Enteropathy
    Epithelial delamination is protective during pharmaceutical-induced enteropathy Scott T. Espenschieda, Mark R. Cronana, Molly A. Mattya, Olaf Muellera, Matthew R. Redinbob,c,d, David M. Tobina,e,f, and John F. Rawlsa,e,1 aDepartment of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC 27710; bDepartment of Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599; cDepartment of Biochemistry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599; dDepartment of Microbiology and Immunology, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, NC 27599; eDepartment of Medicine, Duke University School of Medicine, Durham, NC 27710; and fDepartment of Immunology, Duke University School of Medicine, Durham, NC 27710 Edited by Dennis L. Kasper, Harvard Medical School, Boston, MA, and approved July 15, 2019 (received for review February 12, 2019) Intestinal epithelial cell (IEC) shedding is a fundamental response to in mediating intestinal responses to injury remains poorly un- intestinal damage, yet underlying mechanisms and functions have derstood for most xenobiotics. been difficult to define. Here we model chronic intestinal damage in Gastrointestinal pathology is common in people using phar- zebrafish larvae using the nonsteroidal antiinflammatory drug maceuticals, including nonsteroidal antiinflammatory drugs (NSAID) Glafenine. Glafenine induced the unfolded protein response (NSAIDs) (11). While gastric ulceration has historically been a (UPR) and inflammatory pathways in IECs, leading to delamination. defining clinical presentation of NSAID-induced enteropathy, Glafenine-induced inflammation was augmented by microbial colo- small intestinal pathology has also been observed, although the nizationandassociatedwithchanges in intestinal and environmental incidence may be underreported due to diagnostic limitations microbiotas.
    [Show full text]
  • Global Analysis of Protein Folding Thermodynamics for Disease State Characterization
    Global Analysis of Protein Folding Thermodynamics for Disease State Characterization and Biomarker Discovery by Jagat Adhikari Department of Biochemistry Duke University Date:_______________________ Approved: ___________________________ Michael C. Fitzgerald, Supervisor ___________________________ Kenneth Kreuzer ___________________________ Terrence G. Oas ___________________________ Jiyong Hong ___________________________ Seok-Yong Lee Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Biochemistry in the Graduate School of Duke University 2015 ABSTRACT Global Analysis of Protein Folding Thermodynamics for Disease State Characterization and Biomarker Discovery by Jagat Adhikari Department of Biochemistry Duke University Date:_______________________ Approved: ___________________________ Michael C. Fitzgerald, Supervisor ___________________________ Kenneth Kreuzer ___________________________ Terrence G. Oas ___________________________ Jiyong Hong ___________________________ Seok-Yong Lee An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Biochemistry in the Graduate School of Duke University 2015 Copyright by Jagat Adhikari 2015 Abstract Protein biomarkers can facilitate the diagnosis of many diseases such as cancer and they can be important for the development of effective therapeutic interventions. Current large-scale biomarker discovery and disease state characterization
    [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]
  • Understanding the Molecular Pathobiology of Acid Ceramidase Deficiency
    Understanding the Molecular Pathobiology of Acid Ceramidase Deficiency By Fabian Yu A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Institute of Medical Science University of Toronto © Copyright by Fabian PS Yu 2018 Understanding the Molecular Pathobiology of Acid Ceramidase Deficiency Fabian Yu Doctor of Philosophy Institute of Medical Science University of Toronto 2018 Abstract Farber disease (FD) is a devastating Lysosomal Storage Disorder (LSD) caused by mutations in ASAH1, resulting in acid ceramidase (ACDase) deficiency. ACDase deficiency manifests along a broad spectrum but in its classical form patients die during early childhood. Due to the scarcity of cases FD has largely been understudied. To circumvent this, our lab previously generated a mouse model that recapitulates FD. In some case reports, patients have shown signs of visceral involvement, retinopathy and respiratory distress that may lead to death. Beyond superficial descriptions in case reports, there have been no in-depth studies performed to address these conditions. To improve the understanding of FD and gain insights for evaluating future therapies, we performed comprehensive studies on the ACDase deficient mouse. In the visual system, we reported presence of progressive uveitis. Further tests revealed cellular infiltration, lipid buildup and extensive retinal pathology. Mice developed retinal dysplasia, impaired retinal response and decreased visual acuity. Within the pulmonary system, lung function tests revealed a decrease in lung compliance. Mice developed chronic lung injury that was contributed by cellular recruitment, and vascular leakage. Additionally, we report impairment to lipid homeostasis in the lungs. ii To understand the liver involvement in FD, we characterized the pathology and performed transcriptome analysis to identify gene and pathway changes.
    [Show full text]
  • Supplementary Table S1. Prioritization of Candidate FPC Susceptibility Genes by Private Heterozygous Ptvs
    Supplementary Table S1. Prioritization of candidate FPC susceptibility genes by private heterozygous PTVs Number of private Number of private Number FPC patient heterozygous PTVs in heterozygous PTVs in tumors with somatic FPC susceptibility Hereditary cancer Hereditary Gene FPC kindred BCCS samples mutation DNA repair gene Cancer driver gene gene gene pancreatitis gene ATM 19 1 - Yes Yes Yes Yes - SSPO 12 8 1 - - - - - DNAH14 10 3 - - - - - - CD36 9 3 - - - - - - TET2 9 1 - - Yes - - - MUC16 8 14 - - - - - - DNHD1 7 4 1 - - - - - DNMT3A 7 1 - - Yes - - - PKHD1L1 7 9 - - - - - - DNAH3 6 5 - - - - - - MYH7B 6 1 - - - - - - PKD1L2 6 6 - - - - - - POLN 6 2 - Yes - - - - POLQ 6 7 - Yes - - - - RP1L1 6 6 - - - - - - TTN 6 5 4 - - - - - WDR87 6 7 - - - - - - ABCA13 5 3 1 - - - - - ASXL1 5 1 - - Yes - - - BBS10 5 0 - - - - - - BRCA2 5 6 1 Yes Yes Yes Yes - CENPJ 5 1 - - - - - - CEP290 5 5 - - - - - - CYP3A5 5 2 - - - - - - DNAH12 5 6 - - - - - - DNAH6 5 1 1 - - - - - EPPK1 5 4 - - - - - - ESYT3 5 1 - - - - - - FRAS1 5 4 - - - - - - HGC6.3 5 0 - - - - - - IGFN1 5 5 - - - - - - KCP 5 4 - - - - - - LRRC43 5 0 - - - - - - MCTP2 5 1 - - - - - - MPO 5 1 - - - - - - MUC4 5 5 - - - - - - OBSCN 5 8 2 - - - - - PALB2 5 0 - Yes - Yes Yes - SLCO1B3 5 2 - - - - - - SYT15 5 3 - - - - - - XIRP2 5 3 1 - - - - - ZNF266 5 2 - - - - - - ZNF530 5 1 - - - - - - ACACB 4 1 1 - - - - - ALS2CL 4 2 - - - - - - AMER3 4 0 2 - - - - - ANKRD35 4 4 - - - - - - ATP10B 4 1 - - - - - - ATP8B3 4 6 - - - - - - C10orf95 4 0 - - - - - - C2orf88 4 0 - - - - - - C5orf42 4 2 - - - -
    [Show full text]
  • A. Cellular Senescence
    Generation of antisense RNAs at convergent gene loci in cells undergoing senescence Maharshi Krishna Deb To cite this version: Maharshi Krishna Deb. Generation of antisense RNAs at convergent gene loci in cells undergo- ing senescence. Human genetics. Université Paul Sabatier - Toulouse III, 2016. English. NNT : 2016TOU30274. tel-03209213 HAL Id: tel-03209213 https://tel.archives-ouvertes.fr/tel-03209213 Submitted on 27 Apr 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. 5)µ4& &OWVFEFMPCUFOUJPOEV %0$503"5%&-6/*7&34*5²%&506-064& %ÏMJWSÏQBS Université Toulouse 3 Paul Sabatier (UT3 Paul Sabatier) 1SÏTFOUÏFFUTPVUFOVFQBS DEB Maharshi Krishna -F mercredi 30 mars 2016 5Jtre : Generation of antisense RNAs at convergent gene loci in cells undergoing senescence École doctorale et discipline ou spécialité : ED BSB : Génétique moléculaire 6OJUÏEFSFDIFSDIF CNRS-UMR5088; LBCMCP %JSFDUFVS T EFʾÒTF Dr. TROUCHE Didier Co-Directeur/trice(s) de Thèse : Dr. NICOLAS Estelle 3BQQPSUFVST Prof. GILSON Eric, Dr. LIBRI Domenico, Dr. VERDEL Andre "VUSF T NFNCSF T EVKVSZ Prof. GLEIZES Pierre Emmanuel, President of Jury Dr. TROUCHE Didier, Thesis Supervisor This thesis is dedicated to any patients who may get cured with treatments manifesting from this work.
    [Show full text]
  • Supplemental Materials Supplemental Table 1
    Electronic Supplementary Material (ESI) for RSC Advances. This journal is © The Royal Society of Chemistry 2016 Supplemental Materials Supplemental Table 1. The differentially expressed proteins from rat pancreas identified by proteomics (SAP vs. SO) No. Protein name Gene name ratio P value 1 Metallothionein Mt1m 3.35 6.34E-07 2 Neutrophil antibiotic peptide NP-2 Defa 3.3 8.39E-07 3 Ilf2 protein Ilf2 3.18 1.75E-06 4 Numb isoform o/o rCG 3.12 2.73E-06 5 Lysozyme Lyz2 3.01 5.63E-06 6 Glucagon Gcg 2.89 1.17E-05 7 Serine protease HTRA1 Htra1 2.75 2.97E-05 8 Alpha 2 macroglobulin cardiac isoform (Fragment) 2.75 2.97E-05 9 Myosin IF (Predicted) Myo1f 2.65 5.53E-05 10 Neuroendocrine secretory protein 55 Gnas 2.61 7.60E-05 11 Matrix metallopeptidase 8 Mmp8 2.57 9.47E-05 12 Protein Tnks1bp1 Tnks1bp1 2.53 1.22E-04 13 Alpha-parvin Parva 2.47 1.78E-04 14 C4b-binding protein alpha chain C4bpa 2.42 2.53E-04 15 Protein KTI12 homolog Kti12 2.41 2.74E-04 16 Protein Rab11fip5 Rab11fip5 2.41 2.84E-04 17 Protein Mcpt1l3 Mcpt1l3 2.33 4.43E-04 18 Phospholipase B-like 1 Plbd1 2.33 4.76E-04 Aldehyde dehydrogenase (NAD), cytosolic 19 2.32 4.93E-04 (Fragments) 20 Protein Dpy19l2 Dpy19l2 2.3 5.68E-04 21 Regenerating islet-derived 3 alpha, isoform CRA_a Reg3a 2.27 6.74E-04 22 60S acidic ribosomal protein P1 Rplp1 2.26 7.22E-04 23 Serum albumin Alb 2.25 7.98E-04 24 Ribonuclease 4 Rnase4 2.24 8.25E-04 25 Cct-5 protein (Fragment) Cct5 2.24 8.52E-04 26 Protein S100-A9 S100a9 2.22 9.71E-04 27 Creatine kinase M-type Ckm 2.21 1.00E-03 28 Protein Larp4b Larp4b 2.18 1.25E-03
    [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]
  • Supplementary Data
    SUPPLEMENTARY DATA A cyclin D1-dependent transcriptional program predicts clinical outcome in mantle cell lymphoma Santiago Demajo et al. 1 SUPPLEMENTARY DATA INDEX Supplementary Methods p. 3 Supplementary References p. 8 Supplementary Tables (S1 to S5) p. 9 Supplementary Figures (S1 to S15) p. 17 2 SUPPLEMENTARY METHODS Western blot, immunoprecipitation, and qRT-PCR Western blot (WB) analysis was performed as previously described (1), using cyclin D1 (Santa Cruz Biotechnology, sc-753, RRID:AB_2070433) and tubulin (Sigma-Aldrich, T5168, RRID:AB_477579) antibodies. Co-immunoprecipitation assays were performed as described before (2), using cyclin D1 antibody (Santa Cruz Biotechnology, sc-8396, RRID:AB_627344) or control IgG (Santa Cruz Biotechnology, sc-2025, RRID:AB_737182) followed by protein G- magnetic beads (Invitrogen) incubation and elution with Glycine 100mM pH=2.5. Co-IP experiments were performed within five weeks after cell thawing. Cyclin D1 (Santa Cruz Biotechnology, sc-753), E2F4 (Bethyl, A302-134A, RRID:AB_1720353), FOXM1 (Santa Cruz Biotechnology, sc-502, RRID:AB_631523), and CBP (Santa Cruz Biotechnology, sc-7300, RRID:AB_626817) antibodies were used for WB detection. In figure 1A and supplementary figure S2A, the same blot was probed with cyclin D1 and tubulin antibodies by cutting the membrane. In figure 2H, cyclin D1 and CBP blots correspond to the same membrane while E2F4 and FOXM1 blots correspond to an independent membrane. Image acquisition was performed with ImageQuant LAS 4000 mini (GE Healthcare). Image processing and quantification were performed with Multi Gauge software (Fujifilm). For qRT-PCR analysis, cDNA was generated from 1 µg RNA with qScript cDNA Synthesis kit (Quantabio). qRT–PCR reaction was performed using SYBR green (Roche).
    [Show full text]
  • UNIVERSITY of CALIFORNIA RIVERSIDE Investigations Into The
    UNIVERSITY OF CALIFORNIA RIVERSIDE Investigations into the Role of TAF1-mediated Phosphorylation in Gene Regulation A Dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Cell, Molecular and Developmental Biology by Brian James Gadd December 2012 Dissertation Committee: Dr. Xuan Liu, Chairperson Dr. Frank Sauer Dr. Frances M. Sladek Copyright by Brian James Gadd 2012 The Dissertation of Brian James Gadd is approved Committee Chairperson University of California, Riverside Acknowledgments I am thankful to Dr. Liu for her patience and support over the last eight years. I am deeply indebted to my committee members, Dr. Frank Sauer and Dr. Frances Sladek for the insightful comments on my research and this dissertation. Thanks goes out to CMDB, especially Dr. Bachant, Dr. Springer and Kathy Redd for their support. Thanks to all the members of the Liu lab both past and present. A very special thanks to the members of the Sauer lab, including Silvia, Stephane, David, Matt, Stephen, Ninuo, Toby, Josh, Alice, Alex and Flora. You have made all the years here fly by and made them so enjoyable. From the Sladek lab I want to thank Eugene, John, Linh and Karthi. Special thanks go out to all the friends I’ve made over the years here. Chris, Amber, Stephane and David, thank you so much for feeding me, encouraging me and keeping me sane. Thanks to the brothers for all your encouragement and prayers. To any I haven’t mentioned by name, I promise I haven’t forgotten all you’ve done for me during my graduate years.
    [Show full text]