Gene Section Review

Total Page:16

File Type:pdf, Size:1020Kb

Gene Section Review Atlas of Genetics and Cytogenetics in Oncology and Haematology OPEN ACCESS JOURNAL INIST-CNRS Gene Section Review PPP6R3 (protein phosphatase 6 regulatory subunit 3) Luigi Cristiano Aesthetic and medical biotechnologies research unit, Prestige, Terranuova Bracciolini, Italy. [email protected]; [email protected] Published in Atlas Database: March 2019 Online updated version : http://AtlasGeneticsOncology.org/Genes/PPP6R3ID54550ch11q13.html Printable original version : http://documents.irevues.inist.fr/bitstream/handle/2042/70657/03-2019-PPP6R3ID54550ch11q13.pdf DOI: 10.4267/2042/70657 This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 2.0 France Licence. © 2020 Atlas of Genetics and Cytogenetics in Oncology and Haematology Abstract bladder cancer, lung cancer, nodular fasciitis Protein phosphatase 6 regulatory subunit 3 Identity (PPP6R3) is a regulatory subunit of the PP6 holoenzyme complex involved in the turnover of Other names: Serine/threonine-protein phosphatase serine and threonine phosphorylation events during 6 regulatory subunit 3, chromosome 11 open reading mitosis. PPP6R3 shows abundant mRNA splicing frame 23 C11orf23, SAPS domain family member 3, variants and numerous functional protein isoforms. SAPS3, SAPLa, SAPL, SAP190, sporulation- PPP6R3 gene is often involved in abnormal induced transcript 4-associated protein, chromosomal translocations and it is found as a DKFZp781E2374, DKFZp781O2362, fusion gene partner in different kind of cancers. DKFZp781E17107, FLJ11058, FLJ43065, KIAA1558, MGC125711, MGC125712 Keywords PPP6R3, protein phosphatase 6 regulatory subunit 3, HGNC (Hugo): PPP6R3 C11orf23, SAPS, phosphorylation, breast cancer, Location: 11q13.2 Figure. 1. PPP6R3 gene and splicing variants/isoforms. The figure shows the locus on chromosome 11 of the PPP6R3 gene (reworked from https://www.ncbi.nlm.nih.gov/gene; http://grch37.ensembl.org; www.genecards.org) Atlas Genet Cytogenet Oncol Haematol. 2020; 24(2) 69 PPP6R3 (protein phosphatase 6 regulatory subunit 3) Cristiano L related protein 5) gene. Around the genomic locus of DNA/RNA PPP6R3 take place different promoter or enhancer transcriptional elements that are located at +0.5 kb, Description +837.9 kb and -359.7 kb. PPP6R3, alias protein phosphatase 6 regulatory subunit 3, is a protein coding gene that starts at Transcription 68,460,718 nt and ends at 68,615,334 nt from qter Exists a high number of spliced version of PPP6R3 (RefSeq NC_000011.10) and with a length of (Stefansson and Brautigan, 2006) and their main 154617 bp. It is proximal to LRP5 (LDL receptor characteristics are reported in Table.1 Leng Leng MW Varia Exon Isofor Name RefSeq (1) Transcript ID Type ht Alias RefSeq (2) ht (kDa pI nt s m (bp) (aa) ) PPP6R3-201 ENST0000026563 protein Isofor 88.9 4.4 (PPP6R3- Var.5 NM_018312 23 4992 - NP_060782 793 6.9 coding m 5 5 9 003) PPP6R3- ENST0000026563 202 (PPP6R Var.44 NR_147968.1 22 ncRNA 5124 - - - - - - 7.8 3-021) NM_0011641 Isofor NP_0011576 97.6 4.5 Var.6 5127 - 873 61 m 6 33 7 0 NM_0013523 Isofor NP_0013392 86.8 4.5 Var.21 4873 - 782 61 protein m 18 90 8 2 NM_0013523 coding Isofor NP_0013392 97.6 4.5 Var.28 5211 - 873 68 m 6 97 7 0 PPP6R3-203 Var. NM_0013523 ENST0000039380 Isofor NP_0013393 97.6 4.5 (PPP6R3- 24 5233 - 873 35 75 0.6 m 6 04 7 0 001) Var.41 NR_147965 4942 - - - - - - Var.43 NR_147967 5401 - - - - - - Var.45 NR_147969 ncRNA 5235 - - - - - - Var.46 NR_147970 4978 - - - - - - Var.47 NR_147971 5362 - - - - - - A, NM_0011641 Isofor NP_0011576 98.4 4.5 Var.4 5145 C11orf23 879 60 m 4 32 9 4 a, SAPLa NM_0013523 Isofor NP_0013392 73.1 4.4 Var.7 5052 - 664 47 m 7 76 5 4 NM_0013523 Isofor NP_0013392 95.2 4.5 Var.10 5037 - 850 50 m 8 79 6 5 NM_0013523 Isofor NP_0013392 96.4 4.5 Var.12 5073 - 862 52 m 10 81 5 5 NM_0013523 Isofor NP_0013392 79.5 4.4 Var.13 4704 - 717 53 m 11 82 3 9 NM_0013523 Isofor NP_0013392 99.4 4.5 Var.14 5281 - 889 54 m 12 83 7 3 PPP6R3- NM_0013523 ENST0000039380 protein Isofor NP_0013392 99.4 4.5 204 (PPP6R Var.16 25 5154 - 889 56 1.7 coding m 12 85 7 3 3-005) NM_0013523 Isofor NP_0013392 96.2 4.5 Var.20 5194 - 860 60 m 17 89 5 4 A, NM_0013523 Isofor NP_0013392 98.4 4.5 Var.24 5251 C11orf23 879 64 m 4 93 9 4 a, SAPLa NM_0013523 Isofor NP_0013392 72.1 4.4 Var.29 5149 - 654 69 m 20 98 6 5 NM_0013523 Isofor NP_0013392 87.6 4.5 Var.30 4891 - 788 70 m 21 99 9 6 NM_0013523 Isofor NP_0013393 96.4 4.5 Var.31 5200 - 862 71 m 10 00 5 5 NM_0013523 Isofor NP_0013393 97.7 4.5 Var.32 5233 - 873 72 m 24 01 3 4 Atlas Genet Cytogenet Oncol Haematol. 2020; 24(2) 70 PPP6R3 (protein phosphatase 6 regulatory subunit 3) Cristiano L NM_0013523 Isofor NP_0013393 96.2 4.5 Var.33 5067 - 860 73 m 17 02 5 4 NM_0013523 Isofor NP_0013393 84.4 4.5 Var.34 4804 - 759 74 m 22 03 7 8 NM_0013523 Isofor NP_0013393 95.2 4.5 Var.36 5164 - 850 76 m 8 05 6 5 NM_0013523 Isofor NP_0013393 97.7 4.5 Var.37 5106 - 873 77 m 24 06 3 4 NM_0013523 Isofor NP_0013393 84.4 4.5 Var.38 4931 - 759 78 m 22 07 7 8 A, NM_0013523 Isofor NP_0013393 98.4 4.5 Var.39 5390 C11orf23 879 79 m 4 08 9 4 a, SAPLa NM_0013523 Isofor NP_0013393 95.2 4.5 Var.40 5142 - 850 80 m 8 09 6 5 Var.42 NR_147966 ncRNA 5392 - - - - - - NM_0011641 Isofor NP_0011576 94.4 4.5 Var.2 5040 - 844 63 m 2 35 4 1 PPP6R3-205 NM_0013523 ENST0000052484 protein Isofor NP_0013392 83.6 4.5 (PPP6R3- Var.15 23 4786 - 753 55 5.5 coding m 13 84 5 4 026) NM_0013523 Isofor NP_0013392 94.4 4.5 Var.23 5146 - 844 63 m 2 92 4 1 NM_0011641 Isofor NP_0011576 96.9 4.5 Var.1 5109 - 867 62 m 1 34 6 1 NM_0013523 Isofor NP_0013392 96.9 4.5 Var.8 5284 - 867 48 m 1 77 6 1 NM_0013523 Isofor NP_0013392 84.8 4.5 Var.11 4822 - 765 51 m 9 80 4 4 PPP6R3- NM_0013523 ENST0000052490 protein Isofor NP_0013392 90.1 4.4 206 (PPP6R Var.18 24 4902 - 805 58 4.5 coding m 15 87 4 9 3-007) NM_0013523 Isofor NP_0013392 87.1 4.5 Var.19 4885 - 786 59 m 16 88 5 2 NM_0013523 Isofor NP_0013392 95.6 4.5 Var.22 5129 - 856 62 m 19 91 3 2 NM_0013523 Isofor NP_0013392 95.6 4.5 Var.25 5055 - 856 65 m 19 94 3 2 ENST0000052505 retained PPP6R3-207 - - 4 513 - - - - - - 0.5 intron ENST0000052515 retained PPP6R3-208 - - 2 582 - - - - - - 2.1 intron ENST0000052542 nonsens PPP6R3-209 - - 8 830 - - - - - - 1.5 e md ENST0000052630 retained PPP6R3-210 - - 10 4134 - - - - - - 7.5 intron ENST0000052657 retained PPP6R3-211 - - 4 489 - - - - - - 4.1 intron ENST0000052659 nonsens PPP6R3-212 - - 5 570 - - - - - - 3.1 e md ENST0000052706 retained PPP6R3-213 - - 4 573 - - - - - - 9.5 intron PPP6R3- NM_0013523 ENST0000052740 protein Isofor NP_0013392 94.5 4.5 214 (PPP6R Var.26 22 5019 - 844 66 3.6 coding m 23 95 5 6 3-020) PPP6R3- ENST0000052863 215 (PPP6R - - 5 (?) 538 - - - - - - 5.5 3-012) ENST0000052917 retained PPP6R3-216 - - 4 500 - - - - - - 2.1 intron Atlas Genet Cytogenet Oncol Haematol. 2020; 24(2) 71 PPP6R3 (protein phosphatase 6 regulatory subunit 3) Cristiano L PPP6R3- ENST0000052934 217 (PPP6R - - 4 (?) 603 - - - - - - 4.5 3-011) PPP6R3- B, NM_0011641 ENST0000052971 protein Isofor NP_0011576 88.9 4.4 218 (PPP6R Var.3 23 3426 C11orf23 791 64 0.5 coding m 3 36 1 8 3-004) b, SAPLb PPP6R3- ENST0000052990 219 (PPP6R - - 7 (?) 826 - - - - - - 7.5 3-009) processe ENST0000053042 d PPP6R3-220 - - 5 560 - - - - - - 7.5 transcri pt PPP6R3-221 ENST0000053073 (PPP6R3- - - 2 (?) 576 - - - - - - 4.1 025) PPP6R3- ENST0000053124 222 (PPP6R - - 5 (?) 687 - - - - - - 4.1 3-013) ENST0000053143 retained PPP6R3-223 - - 2 590 - - - - - - 2.1 intron PPP6R3-224 ENST0000053312 (PPP6R3- - - 4 (?) 551 - - - - - - 7.5 027) PPP6R3- NM_0013523 ENST0000053419 protein Isofor NP_0013392 68.1 4.4 225 (PPP6R Var.17 16 5150 - 619 57 0.5 coding m 14 86 2 2 3-018) PPP6R3- ENST0000053453 226 (PPP6R - - 19 (?) 2968 - - - - - - 4.5 3-008) Table.1 Alterative splicing variants and isoforms of PPP6R3. (reworked from http://grch37.ensembl.org; ttps://www.ncbi.nlm.nih.gov; https://web.expasy.org/protparam/; https://www.uniprot.org). ncRNA = non-coding RNA; nonsense md = nonsense mediated decay; (?) = undetermined; MW = molecular weight; pI = theoretical pI. Pseudogene contrary, PPP6R3 protein is found at high levels in lung, bladder, spleen and pancreas (Ziembik et al., Currently, pseudogenes for PPP6R3 have not been 2017). detected in the human genome. Localisation Protein PPP6R3 localize in various subcellular compartments: it is present mainly in the cytoplasm Description but it is also found in Golgi apparatus, nucleoplasm, PPP6R3 encodes the protein phosphatase 6 nucleus and associated with the plasma membrane regulatory subunit 3, which belongs to protein (Stefansson et al., 2008; phosphatase 6 (PP6) complex (York et al., 2014; https://www.ncbi.nlm.nih.gov). Guergnon et al., 2009) in which there are also PPP6R1, PPP6R2 and PPP6C proteins. Function PP6 complex is a member of the PP2A subfamily of PPP6R3 is a subunit of protein phosphatase 6 (PP6), protein phosphatases and shows a Sit4-associated a trimeric holoenzyme of the family of protein domain (SAPS domain) (Stefansson and phosphoprotein phosphatases (PPPs), involved in the Brautigan, 2006).
Recommended publications
  • Retinoic Acid Induced 1 Gene Analysis in Humans and Zebrafish
    Virginia Commonwealth University VCU Scholars Compass Theses and Dissertations Graduate School 2009 RETINOIC ACID INDUCED 1 GENE ANALYSIS IN HUMANS AND ZEBRAFISH Bijal Vyas Virginia Commonwealth University Follow this and additional works at: https://scholarscompass.vcu.edu/etd Part of the Medical Genetics Commons © The Author Downloaded from https://scholarscompass.vcu.edu/etd/1901 This Thesis is brought to you for free and open access by the Graduate School at VCU Scholars Compass. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of VCU Scholars Compass. For more information, please contact [email protected]. © Bijal Akshay Vyas, 2009 All Rights Reserved RETINOIC ACID INDUCED 1 GENE ANALYSIS IN HUMANS AND ZEBRAFISH A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University. by BIJAL AKSHAY VYAS Bachelor of Biology North Carolina State University, 2007 Director: SARAH H. ELSEA Associate Professor, Department of Human and Molecular Genetics Department of Pediatrics Virginia Commonwealth University Richmond, Virginia August, 2009 Acknowledgement I would like to thank all the people who have supported and motivated me throughout my graduate studies. I had the great opportunity to work in Dr. Sarah Elsea‘s lab and I sincerely thank her for her willingness to help, patience and encouraging me after my failed experiments. I am also greatly thankful to Dr. Jim Lister for guiding and helping me every step of the way in finishing my zebrafish project. I also thank my third committee member, Dr. Andrew Davies for his project consultations, helpful alternatives and encouragement.
    [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]
  • Snps Related to Vitamin D and Breast Cancer Risk
    Huss et al. Breast Cancer Research (2018) 20:1 DOI 10.1186/s13058-017-0925-3 RESEARCHARTICLE Open Access SNPs related to vitamin D and breast cancer risk: a case-control study Linnea Huss1* , Salma Tunå Butt1, Peter Almgren 2, Signe Borgquist3,4, Jasmine Brandt1, Asta Försti5,6, Olle Melander2 and Jonas Manjer1 Abstract Background: It has been suggested that vitamin D might protect from breast cancer, although studies on levels of vitamin D in association with breast cancer have been inconsistent. Genome-wide association studies (GWASs) have identified several single-nucleotide polymorphisms (SNPs) to be associated with vitamin D. The aim of this study was to investigate such vitamin D-SNP associations in relation to subsequent breast cancer risk. A first step included verification of these SNPs as determinants of vitamin D levels. Methods: The Malmö Diet and Cancer Study included 17,035 women in a prospective cohort. Genotyping was performed and was successful in 4058 nonrelated women from this cohort in which 865 were diagnosed with breast cancer. Levels of vitamin D (25-hydroxyvitamin D) were available for 700 of the breast cancer cases and 643 of unaffected control subjects. SNPs previously associated with vitamin D in GWASs were identified. Logistic regression analyses yielding ORs with 95% CIs were performed to investigate selected SNPs in relation to low levels of vitamin D (below median) as well as to the risk of breast cancer. Results: The majority of SNPs previously associated with levels of vitamin D showed a statistically significant association with circulating vitamin D levels. Heterozygotes of one SNP (rs12239582) were found to have a statistically significant association with a low risk of breast cancer (OR 0.82, 95% CI 0.68–0.99), and minor homozygotes of the same SNP were found to have a tendency towards a low risk of being in the group with low vitamin D levels (OR 0.72, 95% CI 0.52–1.00).
    [Show full text]
  • DPP9 Deficiency: an Inflammasomopathy
    medRxiv preprint doi: https://doi.org/10.1101/2021.01.31.21250067; this version posted June 9, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. DPP9 deficiency: an Inflammasomopathy which can be rescued by lowering NLRP1/IL-1 signaling Cassandra R. HARAPAS1,2,$, Kim S. ROBINSON3,$, Kenneth LAY4,$, Jasmine WONG4, Ricardo MORENO TRASPAS4 , Nasrin NABAVIZADEH4, Annick RAAS-ROTHSCHILD5, Bertrand BOISSON6,7,8, Scott B. DRUTMAN6, Pawat LAOHAMONTHONKUL1,2, Devon BONNER9, Mark GORRELL10, Sophia DAVIDSON1,2, Chien-Hsiung YU1,2, Hulya KAYSERILI11, Nevin HATIPOGLU12, Jean-Laurent CASANOVA6,7,8,13,14, Jonathan A. BERNSTEIN15, Franklin L. ZHONG3,16,*, Seth L. MASTERS1,2,* , Bruno REVERSADE4,10,17,* Affiliations: 1. Inflammation Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia 2. Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia 3. Skin Research Institute of Singapore (SRIS), A*STAR, Singapore 4. Genome Institute of Singapore (GIS), A*STAR, Singapore 5. The Institute for Rare Diseases, The Edmond and Lily Safra Children's Hospital, Sheba Medical Center, Tel-Hashomer, Israel; Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel 6. St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, USA 7. Paris University, Imagine Institute, Paris, France NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. 1 medRxiv preprint doi: https://doi.org/10.1101/2021.01.31.21250067; this version posted June 9, 2021.
    [Show full text]
  • Genes in a Refined Smith-Magenis Syndrome Critical Deletion Interval on Chromosome 17P11.2 and the Syntenic Region of the Mouse
    Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Article Genes in a Refined Smith-Magenis Syndrome Critical Deletion Interval on Chromosome 17p11.2 and the Syntenic Region of the Mouse Weimin Bi,1,6 Jiong Yan,1,6 Paweł Stankiewicz,1 Sung-Sup Park,1,7 Katherina Walz,1 Cornelius F. Boerkoel,1 Lorraine Potocki,1,3 Lisa G. Shaffer,1 Koen Devriendt,4 Małgorzata J.M. Nowaczyk,5 Ken Inoue,1 and James R. Lupski1,2,3,8 Departments of 1Molecular & Human Genetics, 2Pediatrics, Baylor College of Medicine, 3Texas Children’s Hospital, Houston, Texas 77030, USA; 4Centre for Human Genetics, University Hospital Gasthuisberg, Catholic University of Leuven, B-3000 Leuven, Belgium; 5Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario L8S 4J9, Canada Smith-Magenis syndrome (SMS) is a multiple congenital anomaly/mental retardation syndrome associated with behavioral abnormalities and sleep disturbance. Most patients have the same ∼4 Mb interstitial genomic deletion within chromosome 17p11.2. To investigate the molecular bases of the SMS phenotype, we constructed BAC/PAC contigs covering the SMS common deletion interval and its syntenic region on mouse chromosome 11. Comparative genome analysis reveals the absence of all three ∼200-kb SMS-REP low-copy repeats in the mouse and indicates that the evolution of SMS-REPs was accompanied by transposition of adjacent genes. Physical and genetic map comparisons in humans reveal reduced recombination in both sexes. Moreover, by examining the deleted regions in SMS patients with unusual-sized deletions, we refined the minimal Smith-Magenis critical region (SMCR) to an ∼1.1-Mb genomic interval that is syntenic to an ∼1.0-Mb region in the mouse.
    [Show full text]
  • DPP9 Mouse Monoclonal Antibody [Clone ID: OTI1G9] – TA504307
    OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for TA504307 DPP9 Mouse Monoclonal Antibody [Clone ID: OTI1G9] Product data: Product Type: Primary Antibodies Clone Name: OTI1G9 Applications: FC, IHC, WB Recommended Dilution: WB 1:500~2000, IHC 1:150, FLOW 1:100 Reactivity: Human, Monkey, Mouse, Rat, Dog Host: Mouse Isotype: IgG1 Clonality: Monoclonal Immunogen: Full length human recombinant protein of human DPP9(NP_631898) produced in HEK293T cell. Formulation: PBS (PH 7.3) containing 1% BSA, 50% glycerol and 0.02% sodium azide. Concentration: 0.7 mg/ml Purification: Purified from mouse ascites fluids or tissue culture supernatant by affinity chromatography (protein A/G) Conjugation: Unconjugated Storage: Store at -20°C as received. Stability: Stable for 12 months from date of receipt. Predicted Protein Size: 96.4 kDa Gene Name: dipeptidyl peptidase 9 Database Link: NP_631898 Entrez Gene 224897 MouseEntrez Gene 485033 DogEntrez Gene 301130 RatEntrez Gene 695587 MonkeyEntrez Gene 91039 Human Q86TI2 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 3 DPP9 Mouse Monoclonal Antibody [Clone ID: OTI1G9] – TA504307 Background: This gene encodes a protein that is a member of the S9B family in clan SC of the serine proteases. The protein has been shown to have post-proline dipeptidyl aminopeptidase activity, cleaving Xaa-Pro dipeptides from the N-termini of proteins.
    [Show full text]
  • Involvement of DPP9 in Gene Fusions in Serous Ovarian Carcinoma
    Smebye et al. BMC Cancer (2017) 17:642 DOI 10.1186/s12885-017-3625-6 RESEARCH ARTICLE Open Access Involvement of DPP9 in gene fusions in serous ovarian carcinoma Marianne Lislerud Smebye1,2, Antonio Agostini1,2, Bjarne Johannessen2,3, Jim Thorsen1,2, Ben Davidson4,5, Claes Göran Tropé6, Sverre Heim1,2,5, Rolf Inge Skotheim2,3 and Francesca Micci1,2* Abstract Background: A fusion gene is a hybrid gene consisting of parts from two previously independent genes. Chromosomal rearrangements leading to gene breakage are frequent in high-grade serous ovarian carcinomas and have been reported as a common mechanism for inactivating tumor suppressor genes. However, no fusion genes have been repeatedly reported to be recurrent driver events in ovarian carcinogenesis. We combined genomic and transcriptomic information to identify novel fusion gene candidates and aberrantly expressed genes in ovarian carcinomas. Methods: Examined were 19 previously karyotyped ovarian carcinomas (18 of the serous histotype and one undifferentiated). First, karyotypic aberrations were compared to fusion gene candidates identified by RNA sequencing (RNA-seq). In addition, we used exon-level gene expression microarrays as a screening tool to identify aberrantly expressed genes possibly involved in gene fusion events, and compared the findings to the RNA-seq data. Results: We found a DPP9-PPP6R3 fusion transcript in one tumor showing a matching genomic 11;19-translocation. Another tumor had a rearrangement of DPP9 with PLIN3. Both rearrangements were associated with diminished expression of the 3′ end of DPP9 corresponding to the breakpoints identified by RNA-seq. For the exon-level expression analysis, candidate fusion partner genes were ranked according to deviating expression compared to the median of the sample set.
    [Show full text]
  • Nicotinamide Riboside Kinases Display Redundancy in Mediating Nicotinamide Mononucleotide and Nicotinamide Riboside Metabolism in Skeletal Muscle Cells
    Original Article Nicotinamide riboside kinases display redundancy in mediating nicotinamide mononucleotide and nicotinamide riboside metabolism in skeletal muscle cells Rachel S. Fletcher 1,2, Joanna Ratajczak 3,4, Craig L. Doig 1,2, Lucy A. Oakey 2, Rebecca Callingham 5, Gabriella Da Silva Xavier 5, Antje Garten 1,6, Yasir S. Elhassan 1,2, Philip Redpath 7, Marie E. Migaud 7, Andrew Philp 8, Charles Brenner 9, Carles Canto 3,4, Gareth G. Lavery 1,2,* ABSTRACT þ Objective: Augmenting nicotinamide adenine dinucleotide (NAD ) availability may protect skeletal muscle from age-related metabolic decline. þ Dietary supplementation of NAD precursors nicotinamide mononucleotide (NMN) and nicotinamide riboside (NR) appear efficacious in elevating þ þ muscle NAD . Here we sought to identify the pathways skeletal muscle cells utilize to synthesize NAD from NMN and NR and provide insight into mechanisms of muscle metabolic homeostasis. þ Methods: We exploited expression profiling of muscle NAD biosynthetic pathways, single and double nicotinamide riboside kinase 1/2 (NRK1/ þ 2) loss-of-function mice, and pharmacological inhibition of muscle NAD recycling to evaluate NMN and NR utilization. Results: Skeletal muscle cells primarily rely on nicotinamide phosphoribosyltransferase (NAMPT), NRK1, and NRK2 for salvage biosynthesis of þ þ NAD . NAMPT inhibition depletes muscle NAD availability and can be rescued by NR and NMN as the preferred precursors for elevating muscle þ cell NAD in a pathway that depends on NRK1 and NRK2. Nrk2 knockout mice develop normally and show subtle alterations to their NADþ metabolome and expression of related genes. NRK1, NRK2, and double KO myotubes revealed redundancy in the NRK dependent þ metabolism of NR to NAD .
    [Show full text]
  • Variation in Protein Coding Genes Identifies Information
    bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 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. Animal complexity and information flow 1 1 2 3 4 5 Variation in protein coding genes identifies information flow as a contributor to 6 animal complexity 7 8 Jack Dean, Daniela Lopes Cardoso and Colin Sharpe* 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Institute of Biological and Biomedical Sciences 25 School of Biological Science 26 University of Portsmouth, 27 Portsmouth, UK 28 PO16 7YH 29 30 * Author for correspondence 31 [email protected] 32 33 Orcid numbers: 34 DLC: 0000-0003-2683-1745 35 CS: 0000-0002-5022-0840 36 37 38 39 40 41 42 43 44 45 46 47 48 49 Abstract bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 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. Animal complexity and information flow 2 1 Across the metazoans there is a trend towards greater organismal complexity. How 2 complexity is generated, however, is uncertain. Since C.elegans and humans have 3 approximately the same number of genes, the explanation will depend on how genes are 4 used, rather than their absolute number.
    [Show full text]
  • Identification of Potential Key Genes and Pathway Linked with Sporadic Creutzfeldt-Jakob Disease Based on Integrated Bioinformatics Analyses
    medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 , Iranna Kotturshetti 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. 3. Department of Ayurveda, Rajiv Gandhi Education Society`s Ayurvedic Medical College, Ron, Karnataka 562209, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/2020.12.21.20248688; this version posted December 24, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Abstract Sporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened.
    [Show full text]
  • (P -Value<0.05, Fold Change≥1.4), 4 Vs. 0 Gy Irradiation
    Table S1: Significant differentially expressed genes (P -Value<0.05, Fold Change≥1.4), 4 vs. 0 Gy irradiation Genbank Fold Change P -Value Gene Symbol Description Accession Q9F8M7_CARHY (Q9F8M7) DTDP-glucose 4,6-dehydratase (Fragment), partial (9%) 6.70 0.017399678 THC2699065 [THC2719287] 5.53 0.003379195 BC013657 BC013657 Homo sapiens cDNA clone IMAGE:4152983, partial cds. [BC013657] 5.10 0.024641735 THC2750781 Ciliary dynein heavy chain 5 (Axonemal beta dynein heavy chain 5) (HL1). 4.07 0.04353262 DNAH5 [Source:Uniprot/SWISSPROT;Acc:Q8TE73] [ENST00000382416] 3.81 0.002855909 NM_145263 SPATA18 Homo sapiens spermatogenesis associated 18 homolog (rat) (SPATA18), mRNA [NM_145263] AA418814 zw01a02.s1 Soares_NhHMPu_S1 Homo sapiens cDNA clone IMAGE:767978 3', 3.69 0.03203913 AA418814 AA418814 mRNA sequence [AA418814] AL356953 leucine-rich repeat-containing G protein-coupled receptor 6 {Homo sapiens} (exp=0; 3.63 0.0277936 THC2705989 wgp=1; cg=0), partial (4%) [THC2752981] AA484677 ne64a07.s1 NCI_CGAP_Alv1 Homo sapiens cDNA clone IMAGE:909012, mRNA 3.63 0.027098073 AA484677 AA484677 sequence [AA484677] oe06h09.s1 NCI_CGAP_Ov2 Homo sapiens cDNA clone IMAGE:1385153, mRNA sequence 3.48 0.04468495 AA837799 AA837799 [AA837799] Homo sapiens hypothetical protein LOC340109, mRNA (cDNA clone IMAGE:5578073), partial 3.27 0.031178378 BC039509 LOC643401 cds. [BC039509] Homo sapiens Fas (TNF receptor superfamily, member 6) (FAS), transcript variant 1, mRNA 3.24 0.022156298 NM_000043 FAS [NM_000043] 3.20 0.021043295 A_32_P125056 BF803942 CM2-CI0135-021100-477-g08 CI0135 Homo sapiens cDNA, mRNA sequence 3.04 0.043389246 BF803942 BF803942 [BF803942] 3.03 0.002430239 NM_015920 RPS27L Homo sapiens ribosomal protein S27-like (RPS27L), mRNA [NM_015920] Homo sapiens tumor necrosis factor receptor superfamily, member 10c, decoy without an 2.98 0.021202829 NM_003841 TNFRSF10C intracellular domain (TNFRSF10C), mRNA [NM_003841] 2.97 0.03243901 AB002384 C6orf32 Homo sapiens mRNA for KIAA0386 gene, partial cds.
    [Show full text]
  • An Integrated Platform to Systematically Identify Causal Variants 2 and Genes for Polygenic Human Traits
    bioRxiv preprint doi: https://doi.org/10.1101/813618; this version posted January 15, 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-NC-ND 4.0 International license. 1 An integrated platform to systematically identify causal variants 2 and genes for polygenic human traits. 3 Damien J. Downes1, Ron Schwessinger1,2,*, Stephanie J. Hill1,*, Lea Nussbaum1,*, Caroline 4 Scott1, Matthew E. Gosden1, Priscila P. Hirschfeld1, Jelena M. Telenius1,2, Chris Q. 5 Eijsbouts1,3,4, Simon J. McGowan2, Antony J. Cutler4,5, Jon Kerry1, Jessica L. Davies6, 6 Calliope A. Dendrou4,6, Jamie R.J. Inshaw5, Martin S.C. Larke1, A. Marieke Oudelaar1,2, 7 Yavor Bozhilov1, Andrew J. King1, Richard C. Brown2, Maria C. Suciu1, James O.J. Davies1, 8 Philip Hublitz7, Chris Fisher1, Ryo Kurita8, Yukio Nakamura9, Gerton Lunter2, Stephen 9 Taylor2, Veronica J. Buckle1, John A. Todd5, Douglas R. Higgs1, & Jim R. Hughes1,2,†. 10 11 * These authors contributed equally: Ron Schwessinger, Stephanie J. Hill, Lea Nussbaum. 12 13 † Corresponding author: [email protected] 14 15 Affiliations: 16 1 MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, 17 Radcliffe Department of Medicine, University of Oxford, Oxford, UK 18 2 MRC WIMM Centre for Computational Biology, MRC Weatherall Institute of 19 Molecular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, 20 UK
    [Show full text]