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  • Mouse Germ Line Mutations Due to Retrotransposon Insertions Liane Gagnier1, Victoria P
    Gagnier et al. Mobile DNA (2019) 10:15 https://doi.org/10.1186/s13100-019-0157-4 REVIEW Open Access Mouse germ line mutations due to retrotransposon insertions Liane Gagnier1, Victoria P. Belancio2 and Dixie L. Mager1* Abstract Transposable element (TE) insertions are responsible for a significant fraction of spontaneous germ line mutations reported in inbred mouse strains. This major contribution of TEs to the mutational landscape in mouse contrasts with the situation in human, where their relative contribution as germ line insertional mutagens is much lower. In this focussed review, we provide comprehensive lists of TE-induced mouse mutations, discuss the different TE types involved in these insertional mutations and elaborate on particularly interesting cases. We also discuss differences and similarities between the mutational role of TEs in mice and humans. Keywords: Endogenous retroviruses, Long terminal repeats, Long interspersed elements, Short interspersed elements, Germ line mutation, Inbred mice, Insertional mutagenesis, Transcriptional interference Background promoter and polyadenylation motifs and often a splice The mouse and human genomes harbor similar types of donor site [10, 11]. Sequences of full-length ERVs can TEs that have been discussed in many reviews, to which encode gag, pol and sometimes env, although groups of we refer the reader for more in depth and general infor- LTR retrotransposons with little or no retroviral hom- mation [1–9]. In general, both human and mouse con- ology also exist [6–9]. While not the subject of this re- tain ancient families of DNA transposons, none view, ERV LTRs can often act as cellular enhancers or currently active, which comprise 1–3% of these genomes promoters, creating chimeric transcripts with genes, and as well as many families or groups of retrotransposons, have been implicated in other regulatory functions [11– which have caused all the TE insertional mutations in 13].
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  • Molecular Mechanisms Involved Involved in the Interaction Effects of HCV and Ethanol on Liver Cirrhosis
    Virginia Commonwealth University VCU Scholars Compass Theses and Dissertations Graduate School 2010 Molecular Mechanisms Involved Involved in the Interaction Effects of HCV and Ethanol on Liver Cirrhosis Ryan Fassnacht Virginia Commonwealth University Follow this and additional works at: https://scholarscompass.vcu.edu/etd Part of the Physiology Commons © The Author Downloaded from https://scholarscompass.vcu.edu/etd/2246 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]. Ryan C. Fassnacht 2010 All Rights Reserved Molecular Mechanisms Involved in the Interaction Effects of HCV and Ethanol on Liver Cirrhosis A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University. by Ryan Christopher Fassnacht, B.S. Hampden Sydney University, 2005 M.S. Virginia Commonwealth University, 2010 Director: Valeria Mas, Ph.D., Associate Professor of Surgery and Pathology Division of Transplant Department of Surgery Virginia Commonwealth University Richmond, Virginia July 9, 2010 Acknowledgement The Author wishes to thank his family and close friends for their support. He would also like to thank the members of the molecular transplant team for their help and advice. This project would not have been possible with out the help of Dr. Valeria Mas and her endearing
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  • 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.
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  • Protein Identities in Evs Isolated from U87-MG GBM Cells As Determined by NG LC-MS/MS
    Protein identities in EVs isolated from U87-MG GBM cells as determined by NG LC-MS/MS. No. Accession Description Σ Coverage Σ# Proteins Σ# Unique Peptides Σ# Peptides Σ# PSMs # AAs MW [kDa] calc. pI 1 A8MS94 Putative golgin subfamily A member 2-like protein 5 OS=Homo sapiens PE=5 SV=2 - [GG2L5_HUMAN] 100 1 1 7 88 110 12,03704523 5,681152344 2 P60660 Myosin light polypeptide 6 OS=Homo sapiens GN=MYL6 PE=1 SV=2 - [MYL6_HUMAN] 100 3 5 17 173 151 16,91913397 4,652832031 3 Q6ZYL4 General transcription factor IIH subunit 5 OS=Homo sapiens GN=GTF2H5 PE=1 SV=1 - [TF2H5_HUMAN] 98,59 1 1 4 13 71 8,048185945 4,652832031 4 P60709 Actin, cytoplasmic 1 OS=Homo sapiens GN=ACTB PE=1 SV=1 - [ACTB_HUMAN] 97,6 5 5 35 917 375 41,70973209 5,478027344 5 P13489 Ribonuclease inhibitor OS=Homo sapiens GN=RNH1 PE=1 SV=2 - [RINI_HUMAN] 96,75 1 12 37 173 461 49,94108966 4,817871094 6 P09382 Galectin-1 OS=Homo sapiens GN=LGALS1 PE=1 SV=2 - [LEG1_HUMAN] 96,3 1 7 14 283 135 14,70620005 5,503417969 7 P60174 Triosephosphate isomerase OS=Homo sapiens GN=TPI1 PE=1 SV=3 - [TPIS_HUMAN] 95,1 3 16 25 375 286 30,77169764 5,922363281 8 P04406 Glyceraldehyde-3-phosphate dehydrogenase OS=Homo sapiens GN=GAPDH PE=1 SV=3 - [G3P_HUMAN] 94,63 2 13 31 509 335 36,03039959 8,455566406 9 Q15185 Prostaglandin E synthase 3 OS=Homo sapiens GN=PTGES3 PE=1 SV=1 - [TEBP_HUMAN] 93,13 1 5 12 74 160 18,68541938 4,538574219 10 P09417 Dihydropteridine reductase OS=Homo sapiens GN=QDPR PE=1 SV=2 - [DHPR_HUMAN] 93,03 1 1 17 69 244 25,77302971 7,371582031 11 P01911 HLA class II histocompatibility antigen,
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  • A Novel Type of SYT/SSX Fusion
    A Novel Type of SYT/SSX Fusion: Methodological and Biological Implications Maria Törnkvist, M.Sc., Bertha Brodin, Ph.D., Armando Bartolazzi, M.D., Ph.D., Olle Larsson, M.D., Ph.D. Department of Cellular and Molecular Tumor Pathology, Cancer Centrum Karolinska, Karolinska Hospital (MT, BB, AB, OL), Stockholm, Sweden; and Department of Pathology, Regina Elena Cancer Institute (AB), Rome, Italy the presence of SYT/SSX transcripts in two cases Synovial sarcoma (SS) is a rare soft-tissue tumor using the proposed RT-PCR approach. Applications that affects children and young adults. It is charac- of optimized RT-PCR can contribute to reduce false- terized by the chromosomal translocation t(X; negative SYT/SSX SS cases reported in literature. 18)(p11.2;q11.2), which results in the fusion of the SYT gene on chromosome 18 with a SSX gene on KEY WORDS: RT-PCR, Synovial sarcoma, SYT/SSX chromosome X. In the majority of cases, SYT is fusion gene, SYT/SSX variants. fused to exon 5 of SSX1 (64%), SSX2 (36%), or, Mod Pathol 2002;15(6):679–685 rarely, SSX4. A novel fusion transcript variant deriv- ing from the fusion of SYT to exon 6 of SSX4 gene Synovial sarcomas (SS) account for 7 to 10% of all (SYT/SSX4v) was found coexpressed in one of the human soft-tissue sarcomas and are mainly located previously reported SYT/SSX4 cases. In the present in the extremities in the vicinity of large joints (1). investigation, we describe a new SS case that was Depending on histomorphological appearance, SSs previously shown to be negative for SYT/SSX1 and are usually subdivided into two major forms, bipha- SYT/SSX2 expression by conventional reverse tran- sic and monophasic.
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  • Mutations in Pi(3,5)P2 Signaling and Neurodegeneration in Mouse and Human
    MUTATIONS IN PI(3,5)P2 SIGNALING AND NEURODEGENERATION IN MOUSE AND HUMAN by Clement Y. Chow A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Human Genetics) in The University of Michigan 2008 Doctoral Committee: Professor Miriam H. Meisler, Chair Professor Sally A. Camper Professor David Ginsburg Associate Professor David C. Kohrman Assistant Professor Geoffrey G. Murphy Clement Y. Chow 2008 To my wife, Candace For all her love and support ii ACKNOWLEDGEMENTS I would first like to thank my mentor, Miriam Meisler. She is the consummate scientist. Miriam is inquisitive and interested in a wide range of topics. This trait has taught me to always ask the right questions and be skeptical of conclusions that are not supported by data. Miriam’s unending desire to make each oral presentation perfect drove me to improve my own skills. I came to this lab without any public presentation skills, but I am now greatly improved in my presentation abilities, a skill crucial for a successful scientific career. Miriam is a perfectionist when it comes to writing and always encouraged me to do the same. I will continue to strive to perfect my writing abilities. I came to the lab wanting to positionally clone a mouse mutant. I told Miriam that I would stay in the lab if she allowed me to do so. She was supportive and excited from the beginning, allowing me to pursue a project with an unknown future. This allowed me to learn, first hand, many aspects of genetics that such a project provides.
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  • Gene Section Review
    Atlas of Genetics and Cytogenetics in Oncology and Haematology OPEN ACCESS JOURNAL AT INIST-CNRS Gene Section Review SSX2 (Synovial Sarcoma, X breakpoint 2) Josiane Eid, Christina Garcia, Andrea Frump Department of Cancer Biology, Vanderbilt University Medical Center, Nashville, TN 37232, USA (JE, CG, AF) Published in Atlas Database: April 2008 Online updated version: http://AtlasGeneticsOncology.org/Genes/SSX2ID42406chXp11.html DOI: 10.4267/2042/44431 This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 2.0 France Licence. © 2009 Atlas of Genetics and Cytogenetics in Oncology and Haematology detected in liver, testis, skin melanoma, endometrium, Identity choriocarcinoma, placenta, spleen of Hodgkins Other names: CT5.2; HD21; HOM-MEL-40; lymphoma. MGC119055; MGC15364; MGC3884; RP11-552J9.2; SSX; SSX2A; SSX2B Protein HGNC (Hugo): SSX2 Location: Xp11.22 Description So far, two SSX2 protein isoforms (a and b) are known DNA/RNA to exist. Their mRNAs correspond to SV1 (1466 bases) and SV3 (1322 bases) splice variants, respectively. The Description start codon for both isoforms is located in Exon 2. The SSX2 gene locus encompasses 9 exons and 10,304 SSX2 isoform a is 233 amino acids (26.5 kD) and bp (Xp11; 52,752,974-52,742,671). SSX2 isoform b 188 amino acids (21.6 kD). Of both isoforms, SSX2 isoform b is the most commonly seen Transcription and so far the best studied. The SSX2 gene is transcribed on the minus strand. 7 SSX2 mRNA splice variants (SV1-SV7) have been SSX2 Locus and mRNA Splice Variants. Note: Exons are drawn to scale. Atlas Genet Cytogenet Oncol Haematol.
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  • HCC and Cancer Mutated Genes Summarized in the Literature Gene Symbol Gene Name References*
    HCC and cancer mutated genes summarized in the literature Gene symbol Gene name References* A2M Alpha-2-macroglobulin (4) ABL1 c-abl oncogene 1, receptor tyrosine kinase (4,5,22) ACBD7 Acyl-Coenzyme A binding domain containing 7 (23) ACTL6A Actin-like 6A (4,5) ACTL6B Actin-like 6B (4) ACVR1B Activin A receptor, type IB (21,22) ACVR2A Activin A receptor, type IIA (4,21) ADAM10 ADAM metallopeptidase domain 10 (5) ADAMTS9 ADAM metallopeptidase with thrombospondin type 1 motif, 9 (4) ADCY2 Adenylate cyclase 2 (brain) (26) AJUBA Ajuba LIM protein (21) AKAP9 A kinase (PRKA) anchor protein (yotiao) 9 (4) Akt AKT serine/threonine kinase (28) AKT1 v-akt murine thymoma viral oncogene homolog 1 (5,21,22) AKT2 v-akt murine thymoma viral oncogene homolog 2 (4) ALB Albumin (4) ALK Anaplastic lymphoma receptor tyrosine kinase (22) AMPH Amphiphysin (24) ANK3 Ankyrin 3, node of Ranvier (ankyrin G) (4) ANKRD12 Ankyrin repeat domain 12 (4) ANO1 Anoctamin 1, calcium activated chloride channel (4) APC Adenomatous polyposis coli (4,5,21,22,25,28) APOB Apolipoprotein B [including Ag(x) antigen] (4) AR Androgen receptor (5,21-23) ARAP1 ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 1 (4) ARHGAP35 Rho GTPase activating protein 35 (21) ARID1A AT rich interactive domain 1A (SWI-like) (4,5,21,22,24,25,27,28) ARID1B AT rich interactive domain 1B (SWI1-like) (4,5,22) ARID2 AT rich interactive domain 2 (ARID, RFX-like) (4,5,22,24,25,27,28) ARID4A AT rich interactive domain 4A (RBP1-like) (28) ARID5B AT rich interactive domain 5B (MRF1-like) (21) ASPM Asp (abnormal
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  • Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
    Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase
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  • Inhibition of Mitochondrial Complex II in Neuronal Cells Triggers Unique
    www.nature.com/scientificreports OPEN Inhibition of mitochondrial complex II in neuronal cells triggers unique pathways culminating in autophagy with implications for neurodegeneration Sathyanarayanan Ranganayaki1, Neema Jamshidi2, Mohamad Aiyaz3, Santhosh‑Kumar Rashmi4, Narayanappa Gayathri4, Pulleri Kandi Harsha5, Balasundaram Padmanabhan6 & Muchukunte Mukunda Srinivas Bharath7* Mitochondrial dysfunction and neurodegeneration underlie movement disorders such as Parkinson’s disease, Huntington’s disease and Manganism among others. As a corollary, inhibition of mitochondrial complex I (CI) and complex II (CII) by toxins 1‑methyl‑4‑phenylpyridinium (MPP+) and 3‑nitropropionic acid (3‑NPA) respectively, induced degenerative changes noted in such neurodegenerative diseases. We aimed to unravel the down‑stream pathways associated with CII inhibition and compared with CI inhibition and the Manganese (Mn) neurotoxicity. Genome‑wide transcriptomics of N27 neuronal cells exposed to 3‑NPA, compared with MPP+ and Mn revealed varied transcriptomic profle. Along with mitochondrial and synaptic pathways, Autophagy was the predominant pathway diferentially regulated in the 3‑NPA model with implications for neuronal survival. This pathway was unique to 3‑NPA, as substantiated by in silico modelling of the three toxins. Morphological and biochemical validation of autophagy markers in the cell model of 3‑NPA revealed incomplete autophagy mediated by mechanistic Target of Rapamycin Complex 2 (mTORC2) pathway. Interestingly, Brain Derived Neurotrophic Factor
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  • Protein ID Gene Symbol Unique + Razor Sequence Coverage
    Dengjel et al. Mol. BioSyst., 2010, Supplementary Material (ESI) for Molecular BioSystems DOI: 10.1039/c003962d This journal is (c) The Royal Society of Chemistry, 2010 Supplementary Table 1: Fibroblast control. Cell lysates were prepared from unlabled (Arg0/Lys0) and labled (Arg10/Lys8 fibroblasts after 14 cell doublings in culture (D14). Shown are normalized log2 transformed protein ratios of identified protein identification a minimum of 2 peptides per protein has to be identified (unique + razor). The database used for identification decoy database based on IPI v. 3.59 containing in total 160,820 entries. As a criterium for identification the posterior errror probaility rate of identified proteins (PEP) is shown. The peptide numbers represent peptides used for quantitation. Unique + Razor Sequence Peptide Variability Protein ID Gene Symbol Coverage [%] PEP Log2 Ratio No. [%] Quantil IPI00021033; COL3A1 11.1 5.91E‐62 ‐4.651 4 165.2 Q1 IPI00761105; TADA2B 1.7 2.46E‐02 ‐4.494 2 57.9 Q1 IPI00152007 ARHGEF17 2.3 5.41E‐09 ‐3.687 2 92.5 Q1 IPI00300725;C KRT6A 27 6.82E‐61 ‐3.299 4 204.0 Q1 IPI00022229; APOB 0.7 5.68E‐29 ‐2.944 8 202.2 Q1 IPI00298860; LTF 51 8.02E‐197 ‐2.834 13 105.6 Q1 IPI00384444; KRT14 36.4 6.18E‐85 ‐2.542 13 143.3 Q1 IPI00305461; ITIH2 5 2.86E‐09 ‐1.174 3 367.3 Q1 IPI00420088; KIAA0174 7.5 9.34E‐03 ‐0.892 2 62.3 Q1 IPI00012887; CTSL1 12 3.13E‐21 ‐0.618 3 47.8 Q1 IPI00375714; HSPB7 17.1 1.31E‐05 ‐0.615 2 69.5 Q1 IPI00384140 ESR2 10.6 4.35E‐04 ‐0.551 3 8.6 Q1 IPI00300599; CTSK 46.5 <1.0E‐304 ‐0.515 9 11.7 Q1 IPI00167949;
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  • Open Data for Differential Network Analysis in Glioma
    International Journal of Molecular Sciences Article Open Data for Differential Network Analysis in Glioma , Claire Jean-Quartier * y , Fleur Jeanquartier y and Andreas Holzinger Holzinger Group HCI-KDD, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 2/V, 8036 Graz, Austria; [email protected] (F.J.); [email protected] (A.H.) * Correspondence: [email protected] These authors contributed equally to this work. y Received: 27 October 2019; Accepted: 3 January 2020; Published: 15 January 2020 Abstract: The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, comparison and extrapolation, merging, enrichment, functional association and statistics. We exploit openly available data via cancer gene expression analysis, we apply refinement as well as enrichment analysis via gene ontology and conclude with graph-based visualization of involved protein interaction networks as a basis for signaling. The different databases allowed for the construction of huge networks or specified ones consisting of high-confidence interactions only. Several genes associated to glioma were isolated via a network analysis from top hub nodes as well as from an outlier analysis. The latter approach highlights a mitogen-activated protein kinase next to a member of histondeacetylases and a protein phosphatase as genes uncommonly associated with glioma. Cluster analysis from top hub nodes lists several identified glioma-associated gene products to function within protein complexes, including epidermal growth factors as well as cell cycle proteins or RAS proto-oncogenes.
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