Transposable Element Polymorphisms and Human Genome Regulation
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FK506-Binding Protein 12.6/1B, a Negative Regulator of [Ca2+], Rescues Memory and Restores Genomic Regulation in the Hippocampus of Aging Rats
This Accepted Manuscript has not been copyedited and formatted. The final version may differ from this version. A link to any extended data will be provided when the final version is posted online. Research Articles: Neurobiology of Disease FK506-Binding Protein 12.6/1b, a negative regulator of [Ca2+], rescues memory and restores genomic regulation in the hippocampus of aging rats John C. Gant1, Eric M. Blalock1, Kuey-Chu Chen1, Inga Kadish2, Olivier Thibault1, Nada M. Porter1 and Philip W. Landfield1 1Department of Pharmacology & Nutritional Sciences, University of Kentucky, Lexington, KY 40536 2Department of Cell, Developmental and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL 35294 DOI: 10.1523/JNEUROSCI.2234-17.2017 Received: 7 August 2017 Revised: 10 October 2017 Accepted: 24 November 2017 Published: 18 December 2017 Author contributions: J.C.G. and P.W.L. designed research; J.C.G., E.M.B., K.-c.C., and I.K. performed research; J.C.G., E.M.B., K.-c.C., I.K., and P.W.L. analyzed data; J.C.G., E.M.B., O.T., N.M.P., and P.W.L. wrote the paper. Conflict of Interest: The authors declare no competing financial interests. NIH grants AG004542, AG033649, AG052050, AG037868 and McAlpine Foundation for Neuroscience Research Corresponding author: Philip W. Landfield, [email protected], Department of Pharmacology & Nutritional Sciences, University of Kentucky, 800 Rose Street, UKMC MS 307, Lexington, KY 40536 Cite as: J. Neurosci ; 10.1523/JNEUROSCI.2234-17.2017 Alerts: Sign up at www.jneurosci.org/cgi/alerts to receive customized email alerts when the fully formatted version of this article is published. -
Concentrative Nucleoside Transporter 3 As a Prognostic Indicator for Favorable Outcome of T(8;21)-Positive Acute Myeloid Leukemi
488 ONCOLOGY REPORTS 34: 488-494, 2015 Concentrative nucleoside transporter 3 as a prognostic indicator for favorable outcome of t(8;21)-positive acute myeloid leukemia patients after cytarabine-based chemotherapy JU HAN SONG1, KYUNG-MIN CHO1, HYEOUNG-JOON KIM2, YEO-KYEOUNG KIM2, NAN YOUNG KIM2, HEE-JE KIM3, TAE-Hyang LEE3, SEUNG YONG Hwang4 and TAE SUNG KIM1 1Division of Life Sciences, School of Life Sciences and Biotechnology, Korea University, Seoul; 2Genome Research Center for Hematopoietic Diseases, Chonnam National University Hwasun Hospital, Hwasun; 3Catholic Blood and Marrow Transplantation Center, Seoul St. Mary's Hospital, The Catholic University of Korea, Seoul; 4Division of Molecular and Life Science and GenoCheck Co., Ltd., Hanyang University, Ansan, Republic of Korea Received January 20, 2015; Accepted March 18, 2015 DOI: 10.3892/or.2015.3959 Abstract. Although acute myeloid leukemia (AML) exhibits Introduction diverse responses to chemotherapy, patients harboring the t(8;21) translocation are part of a favorable risk group. Acute myeloid leukemia (AML) is a highly heterogeneous However, the reason why this subgroup is more responsive hematologic malignancy that displays diverse responses to cytarabine-based therapy has not been elucidated. In the to chemotherapy. Although a number of clinical factors present study, we analyzed expression levels of cytarabine affect treatment outcomes, the cytogenetic features of AML metabolism-related genes in patients diagnosed with AML are generally accepted as strong predictors of therapeutic with or without t(8;21) and investigated their correlation with response (1). Pediatric and adult patients carrying the t(8;21) clinical outcomes after cytarabine-based therapy. Among the chromosomal translocation, which is one of the most frequent 8 genes studied, expression of the concentrative nucleoside AML subtypes, are part of a favorable risk group (2). -
Mammalian 5€²-Nucleotidases*
THE JOURNAL OF BIOLOGICAL CHEMISTRY Vol. 278, No. 47, Issue of November 21, pp. 46195–46198, 2003 Minireview © 2003 by The American Society for Biochemistry and Molecular Biology, Inc. Printed in U.S.A. -Mammalian 5-Nucleotidases* residues the best alignment was between the two deoxynucle otidases and cN-III (10). Two 5Ј-nucleotidases, cN-II and cN- III, exhibit phosphotransferase activity (for reviews see Refs. Published, JBC Papers in Press, August 28, 2003, DOI 10.1074/jbc.R300032200 14 and 15) possibly because of higher stability of the phos- phoenzyme intermediate or faster exchange of the nucleoside Vera Bianchi‡§ and Jozef Spychala¶ product with the nucleoside acceptor. From the ‡Department of Biology, University of Padova, The active site of E. coli 5Ј-nucleotidase, the paradigm for I-35131 Padova, Italy and the ¶Lineberger eN, contains two zinc ions and the catalytic dyad Asp-His (11). Comprehensive Cancer Center, University of North No phosphoenzyme intermediate is formed during catalysis, Carolina, Chapel Hill, North Carolina 27599-7295 but a water molecule performs the nucleophilic attack on the phosphate (16). Nucleoside monophosphate phosphohydrolases or 5Ј-nucle- otidases (members of EC 3.1.3.5 and EC 3.1.3.6) dephosphoryl- Properties, Detection, and Inhibition ate non-cyclic nucleoside monophosphates to nucleosides and of 5-Nucleotidases inorganic phosphate. Seven human 5Ј-nucleotidases with dif- All 5Ј-nucleotidases have relatively broad substrate specific- ferent subcellular localization have been cloned (Table I). Se- ities. In agreement with the structural information on the quence comparisons show high homology only between cytoso- active sites (10, 11), all family members except eN are abso- lic 5Ј-nucleotidase IA (cN-IA)1 and B and between cytosolic lutely dependent on magnesium for activity. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Supplemental Table S1
Entrez Gene Symbol Gene Name Affymetrix EST Glomchip SAGE Stanford Literature HPA confirmed Gene ID Profiling profiling Profiling Profiling array profiling confirmed 1 2 A2M alpha-2-macroglobulin 0 0 0 1 0 2 10347 ABCA7 ATP-binding cassette, sub-family A (ABC1), member 7 1 0 0 0 0 3 10350 ABCA9 ATP-binding cassette, sub-family A (ABC1), member 9 1 0 0 0 0 4 10057 ABCC5 ATP-binding cassette, sub-family C (CFTR/MRP), member 5 1 0 0 0 0 5 10060 ABCC9 ATP-binding cassette, sub-family C (CFTR/MRP), member 9 1 0 0 0 0 6 79575 ABHD8 abhydrolase domain containing 8 1 0 0 0 0 7 51225 ABI3 ABI gene family, member 3 1 0 1 0 0 8 29 ABR active BCR-related gene 1 0 0 0 0 9 25841 ABTB2 ankyrin repeat and BTB (POZ) domain containing 2 1 0 1 0 0 10 30 ACAA1 acetyl-Coenzyme A acyltransferase 1 (peroxisomal 3-oxoacyl-Coenzyme A thiol 0 1 0 0 0 11 43 ACHE acetylcholinesterase (Yt blood group) 1 0 0 0 0 12 58 ACTA1 actin, alpha 1, skeletal muscle 0 1 0 0 0 13 60 ACTB actin, beta 01000 1 14 71 ACTG1 actin, gamma 1 0 1 0 0 0 15 81 ACTN4 actinin, alpha 4 0 0 1 1 1 10700177 16 10096 ACTR3 ARP3 actin-related protein 3 homolog (yeast) 0 1 0 0 0 17 94 ACVRL1 activin A receptor type II-like 1 1 0 1 0 0 18 8038 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 1 0 0 0 0 19 8751 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 1 0 0 0 0 20 8728 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 1 0 0 0 0 21 81792 ADAMTS12 ADAM metallopeptidase with thrombospondin type 1 motif, 12 1 0 0 0 0 22 9507 ADAMTS4 ADAM metallopeptidase with thrombospondin type 1 -
Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers
Identification and Characterization of TPRKB Dependency in TP53 Deficient Cancers. by Kelly Kennaley A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Molecular and Cellular Pathology) in the University of Michigan 2019 Doctoral Committee: Associate Professor Zaneta Nikolovska-Coleska, Co-Chair Adjunct Associate Professor Scott A. Tomlins, Co-Chair Associate Professor Eric R. Fearon Associate Professor Alexey I. Nesvizhskii Kelly R. Kennaley [email protected] ORCID iD: 0000-0003-2439-9020 © Kelly R. Kennaley 2019 Acknowledgements I have immeasurable gratitude for the unwavering support and guidance I received throughout my dissertation. First and foremost, I would like to thank my thesis advisor and mentor Dr. Scott Tomlins for entrusting me with a challenging, interesting, and impactful project. He taught me how to drive a project forward through set-backs, ask the important questions, and always consider the impact of my work. I’m truly appreciative for his commitment to ensuring that I would get the most from my graduate education. I am also grateful to the many members of the Tomlins lab that made it the supportive, collaborative, and educational environment that it was. I would like to give special thanks to those I’ve worked closely with on this project, particularly Dr. Moloy Goswami for his mentorship, Lei Lucy Wang, Dr. Sumin Han, and undergraduate students Bhavneet Singh, Travis Weiss, and Myles Barlow. I am also grateful for the support of my thesis committee, Dr. Eric Fearon, Dr. Alexey Nesvizhskii, and my co-mentor Dr. Zaneta Nikolovska-Coleska, who have offered guidance and critical evaluation since project inception. -
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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(19) TZZ¥ ZZ_T (11) EP 3 260 540 A1 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 27.12.2017 Bulletin 2017/52 C12N 15/113 (2010.01) A61K 9/127 (2006.01) A61K 31/713 (2006.01) C12Q 1/68 (2006.01) (21) Application number: 17000579.7 (22) Date of filing: 12.11.2011 (84) Designated Contracting States: • Sarma, Kavitha AL AT BE BG CH CY CZ DE DK EE ES FI FR GB Philadelphia, PA 19146 (US) GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO • Borowsky, Mark PL PT RO RS SE SI SK SM TR Needham, MA 02494 (US) • Ohsumi, Toshiro Kendrick (30) Priority: 12.11.2010 US 412862 P Cambridge, MA 02141 (US) 20.12.2010 US 201061425174 P 28.07.2011 US 201161512754 P (74) Representative: Clegg, Richard Ian et al Mewburn Ellis LLP (62) Document number(s) of the earlier application(s) in City Tower accordance with Art. 76 EPC: 40 Basinghall Street 11840099.3 / 2 638 163 London EC2V 5DE (GB) (71) Applicant: The General Hospital Corporation Remarks: Boston, MA 02114 (US) •Thecomplete document including Reference Tables and the Sequence Listing can be downloaded from (72) Inventors: the EPO website • Lee, Jeannie T •This application was filed on 05-04-2017 as a Boston, MA 02114 (US) divisional application to the application mentioned • Zhao, Jing under INID code 62. San Diego, CA 92122 (US) •Claims filed after the date of receipt of the divisional application (Rule 68(4) EPC). (54) POLYCOMB-ASSOCIATED NON-CODING RNAS (57) This invention relates to long non-coding RNAs (IncRNAs), libraries of those ncRNAs that bind chromatin modifiers, such as Polycomb Repressive Complex 2, inhibitory nucleic acids and methods and compositions for targeting IncRNAs. -
Supplement 1 Microarray Studies
EASE Categories Significantly Enriched in vs MG vs vs MGC4-2 Pt1-C vs C4-2 Pt1-C UP-Regulated Genes MG System Gene Category EASE Global MGRWV Pt1-N RWV Pt1-N Score FDR GO Molecular Extracellular matrix cellular construction 0.0008 0 110 genes up- Function Interpro EGF-like domain 0.0009 0 regulated GO Molecular Oxidoreductase activity\ acting on single dono 0.0015 0 Function GO Molecular Calcium ion binding 0.0018 0 Function Interpro Laminin-G domain 0.0025 0 GO Biological Process Cell Adhesion 0.0045 0 Interpro Collagen Triple helix repeat 0.0047 0 KEGG pathway Complement and coagulation cascades 0.0053 0 KEGG pathway Immune System – Homo sapiens 0.0053 0 Interpro Fibrillar collagen C-terminal domain 0.0062 0 Interpro Calcium-binding EGF-like domain 0.0077 0 GO Molecular Cell adhesion molecule activity 0.0105 0 Function EASE Categories Significantly Enriched in Down-Regulated Genes System Gene Category EASE Global Score FDR GO Biological Process Copper ion homeostasis 2.5E-09 0 Interpro Metallothionein 6.1E-08 0 Interpro Vertebrate metallothionein, Family 1 6.1E-08 0 GO Biological Process Transition metal ion homeostasis 8.5E-08 0 GO Biological Process Heavy metal sensitivity/resistance 1.9E-07 0 GO Biological Process Di-, tri-valent inorganic cation homeostasis 6.3E-07 0 GO Biological Process Metal ion homeostasis 6.3E-07 0 GO Biological Process Cation homeostasis 2.1E-06 0 GO Biological Process Cell ion homeostasis 2.1E-06 0 GO Biological Process Ion homeostasis 2.1E-06 0 GO Molecular Helicase activity 2.3E-06 0 Function GO Biological -
Identification of Tumor-Associated Cassette Exons in Human Cancer
Valletti et al. Molecular Cancer 2010, 9:230 http://www.molecular-cancer.com/content/9/1/230 RESEARCH Open Access Identification of tumor-associated cassette exons in human cancer through EST-based computational prediction and experimental validation Alessio Valletti1†, Anna Anselmo2†, Marina Mangiulli1, Ilenia Boria1, Flavio Mignone3, Giuseppe Merla4, Vincenzo D’Angelo5, Apollonia Tullo6, Elisabetta Sbisà6, Anna Maria D’Erchia1, Graziano Pesole1,7* Abstract Background: Many evidences report that alternative splicing, the mechanism which produces mRNAs and proteins with different structures and functions from the same gene, is altered in cancer cells. Thus, the identification and characterization of cancer-specific splice variants may give large impulse to the discovery of novel diagnostic and prognostic tumour biomarkers, as well as of new targets for more selective and effective therapies. Results: We present here a genome-wide analysis of the alternative splicing pattern of human genes through a computational analysis of normal and cancer-specific ESTs from seventeen anatomical groups, using data available in AspicDB, a database resource for the analysis of alternative splicing in human. By using a statistical methodology, normal and cancer-specific genes, splice sites and cassette exons were predicted in silico. The condition association of some of the novel normal/tumoral cassette exons was experimentally verified by RT-qPCR assays in the same anatomical system where they were predicted. Remarkably, the presence in vivo of the predicted alternative transcripts, specific for the nervous system, was confirmed in patients affected by glioblastoma. Conclusion: This study presents a novel computational methodology for the identification of tumor-associated transcript variants to be used as cancer molecular biomarkers, provides its experimental validation, and reports specific biomarkers for glioblastoma. -
Redefining the Specificity of Phosphoinositide-Binding by Human
bioRxiv preprint doi: https://doi.org/10.1101/2020.06.20.163253; this version posted June 21, 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 4.0 International license. Redefining the specificity of phosphoinositide-binding by human PH domain-containing proteins Nilmani Singh1†, Adriana Reyes-Ordoñez1†, Michael A. Compagnone1, Jesus F. Moreno Castillo1, Benjamin J. Leslie2, Taekjip Ha2,3,4,5, Jie Chen1* 1Department of Cell & Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801; 2Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205; 3Department of Biophysics, Johns Hopkins University, Baltimore, MD 21218; 4Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205; 5Howard Hughes Medical Institute, Baltimore, MD 21205, USA †These authors contributed equally to this work. *Correspondence: [email protected]. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.20.163253; this version posted June 21, 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 4.0 International license. ABSTRACT Pleckstrin homology (PH) domains are presumed to bind phosphoinositides (PIPs), but specific interaction with and regulation by PIPs for most PH domain-containing proteins are unclear. Here we employed a single-molecule pulldown assay to study interactions of lipid vesicles with full-length proteins in mammalian whole cell lysates. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig.