Comprehensive Array CGH of Normal Karyotype Myelodysplastic
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Identification of the Binding Partners for Hspb2 and Cryab Reveals
Brigham Young University BYU ScholarsArchive Theses and Dissertations 2013-12-12 Identification of the Binding arP tners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non- Redundant Roles for Small Heat Shock Proteins Kelsey Murphey Langston Brigham Young University - Provo Follow this and additional works at: https://scholarsarchive.byu.edu/etd Part of the Microbiology Commons BYU ScholarsArchive Citation Langston, Kelsey Murphey, "Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non-Redundant Roles for Small Heat Shock Proteins" (2013). Theses and Dissertations. 3822. https://scholarsarchive.byu.edu/etd/3822 This Thesis is brought to you for free and open access by BYU ScholarsArchive. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of BYU ScholarsArchive. For more information, please contact [email protected], [email protected]. Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactions and Non-Redundant Roles for Small Heat Shock Proteins Kelsey Langston A thesis submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for the degree of Master of Science Julianne H. Grose, Chair William R. McCleary Brian Poole Department of Microbiology and Molecular Biology Brigham Young University December 2013 Copyright © 2013 Kelsey Langston All Rights Reserved ABSTRACT Identification of the Binding Partners for HspB2 and CryAB Reveals Myofibril and Mitochondrial Protein Interactors and Non-Redundant Roles for Small Heat Shock Proteins Kelsey Langston Department of Microbiology and Molecular Biology, BYU Master of Science Small Heat Shock Proteins (sHSP) are molecular chaperones that play protective roles in cell survival and have been shown to possess chaperone activity. -
Allele-Specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish
Allele-specific Expression of Ribosomal Protein Genes in Interspecific Hybrid Catfish by Ailu Chen A dissertation submitted to the Graduate Faculty of Auburn University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Auburn, Alabama August 1, 2015 Keywords: catfish, interspecific hybrids, allele-specific expression, ribosomal protein Copyright 2015 by Ailu Chen Approved by Zhanjiang Liu, Chair, Professor, School of Fisheries, Aquaculture and Aquatic Sciences Nannan Liu, Professor, Entomology and Plant Pathology Eric Peatman, Associate Professor, School of Fisheries, Aquaculture and Aquatic Sciences Aaron M. Rashotte, Associate Professor, Biological Sciences Abstract Interspecific hybridization results in a vast reservoir of allelic variations, which may potentially contribute to phenotypical enhancement in the hybrids. Whether the allelic variations are related to the downstream phenotypic differences of interspecific hybrid is still an open question. The recently developed genome-wide allele-specific approaches that harness high- throughput sequencing technology allow direct quantification of allelic variations and gene expression patterns. In this work, I investigated allele-specific expression (ASE) pattern using RNA-Seq datasets generated from interspecific catfish hybrids. The objective of the study is to determine the ASE genes and pathways in which they are involved. Specifically, my study investigated ASE-SNPs, ASE-genes, parent-of-origins of ASE allele and how ASE would possibly contribute to heterosis. My data showed that ASE was operating in the interspecific catfish system. Of the 66,251 and 177,841 SNPs identified from the datasets of the liver and gill, 5,420 (8.2%) and 13,390 (7.5%) SNPs were identified as significant ASE-SNPs, respectively. -
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. -
Views of the NIH
CLINICAL EPIDEMIOLOGY www.jasn.org Genetic Variants Associated with Circulating Fibroblast Growth Factor 23 Cassianne Robinson-Cohen ,1 Traci M. Bartz,2 Dongbing Lai,3 T. Alp Ikizler,1 Munro Peacock,4 Erik A. Imel,4 Erin D. Michos,5 Tatiana M. Foroud,3 Kristina Akesson,6,7 Kent D. Taylor,8 Linnea Malmgren,6,7 Kunihiro Matsushita,5,9,10 Maria Nethander,11 Joel Eriksson,12 Claes Ohlsson,12 Daniel Mellström,12 Myles Wolf,13 Osten Ljunggren,14 Fiona McGuigan,6,7 Jerome I. Rotter,8 Magnus Karlsson,6,7 Michael J. Econs,3,4 Joachim H. Ix,15,16 Pamela L. Lutsey,17 Bruce M. Psaty,18,19 Ian H. de Boer ,20 and Bryan R. Kestenbaum 20 Due to the number of contributing authors, the affiliations are listed at the end of this article. ABSTRACT Background Fibroblast growth factor 23 (FGF23), a bone-derived hormone that regulates phosphorus and vitamin D metabolism, contributes to the pathogenesis of mineral and bone disorders in CKD and is an emerging cardiovascular risk factor. Central elements of FGF23 regulation remain incompletely under- stood; genetic variation may help explain interindividual differences. Methods We performed a meta-analysis of genome-wide association studies of circulating FGF23 con- centrations among 16,624 participants of European ancestry from seven cohort studies, excluding par- ticipants with eGFR,30 ml/min per 1.73 m2 to focus on FGF23 under normal conditions. We evaluated the association of single-nucleotide polymorphisms (SNPs) with natural log–transformed FGF23 concentra- tion, adjusted for age, sex, study site, and principal components of ancestry. -
Producing T Cells
Lnk/Sh2b3 Controls the Production and Function of Dendritic Cells and Regulates the Induction of IFN- −γ Producing T Cells This information is current as Taizo Mori, Yukiko Iwasaki, Yoichi Seki, Masanori Iseki, of September 28, 2021. Hiroko Katayama, Kazuhiko Yamamoto, Kiyoshi Takatsu and Satoshi Takaki J Immunol published online 14 July 2014 http://www.jimmunol.org/content/early/2014/07/13/jimmun ol.1303243 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2014/07/14/jimmunol.130324 Material 3.DCSupplemental http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on September 28, 2021 *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2014 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published July 14, 2014, doi:10.4049/jimmunol.1303243 The Journal of Immunology Lnk/Sh2b3 Controls the Production and Function of Dendritic Cells and Regulates the Induction of IFN-g–Producing T Cells Taizo Mori,*,1 Yukiko Iwasaki,*,†,1 Yoichi Seki,* Masanori Iseki,* Hiroko Katayama,* Kazuhiko Yamamoto,† Kiyoshi Takatsu,‡,x and Satoshi Takaki* Dendritic cells (DCs) are proficient APCs that play crucial roles in the immune responses to various Ags and pathogens and polarize Th cell immune responses. -
Co-Expression Module Analysis Reveals Biological Processes
Shi et al. BMC Systems Biology 2010, 4:74 http://www.biomedcentral.com/1752-0509/4/74 RESEARCH ARTICLE Open Access Co-expressionResearch article module analysis reveals biological processes, genomic gain, and regulatory mechanisms associated with breast cancer progression Zhiao Shi1,2, Catherine K Derow3 and Bing Zhang*3 Abstract Background: Gene expression signatures are typically identified by correlating gene expression patterns to a disease phenotype of interest. However, individual gene-based signatures usually suffer from low reproducibility and interpretability. Results: We have developed a novel algorithm Iterative Clique Enumeration (ICE) for identifying relatively independent maximal cliques as co-expression modules and a module-based approach to the analysis of gene expression data. Applying this approach on a public breast cancer dataset identified 19 modules whose expression levels were significantly correlated with tumor grade. The correlations were reproducible for 17 modules in an independent breast cancer dataset, and the reproducibility was considerably higher than that based on individual genes or modules identified by other algorithms. Sixteen out of the 17 modules showed significant enrichment in certain Gene Ontology (GO) categories. Specifically, modules related to cell proliferation and immune response were up-regulated in high- grade tumors while those related to cell adhesion was down-regulated. Further analyses showed that transcription factors NYFB, E2F1/E2F3, NRF1, and ELK1 were responsible for the up-regulation of the cell proliferation modules. IRF family and ETS family proteins were responsible for the up-regulation of the immune response modules. Moreover, inhibition of the PPARA signaling pathway may also play an important role in tumor progression. -
Nucleolin and Its Role in Ribosomal Biogenesis
NUCLEOLIN: A NUCLEOLAR RNA-BINDING PROTEIN INVOLVED IN RIBOSOME BIOGENESIS Inaugural-Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf vorgelegt von Julia Fremerey aus Hamburg Düsseldorf, April 2016 2 Gedruckt mit der Genehmigung der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf Referent: Prof. Dr. A. Borkhardt Korreferent: Prof. Dr. H. Schwender Tag der mündlichen Prüfung: 20.07.2016 3 Die vorgelegte Arbeit wurde von Juli 2012 bis März 2016 in der Klinik für Kinder- Onkologie, -Hämatologie und Klinische Immunologie des Universitätsklinikums Düsseldorf unter Anleitung von Prof. Dr. A. Borkhardt und in Kooperation mit dem ‚Laboratory of RNA Molecular Biology‘ an der Rockefeller Universität unter Anleitung von Prof. Dr. T. Tuschl angefertigt. 4 Dedicated to my family TABLE OF CONTENTS 5 TABLE OF CONTENTS TABLE OF CONTENTS ............................................................................................... 5 LIST OF FIGURES ......................................................................................................10 LIST OF TABLES .......................................................................................................12 ABBREVIATION .........................................................................................................13 ABSTRACT ................................................................................................................19 ZUSAMMENFASSUNG -
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. -
Supplementary Table
Supporting information Additional Supporting Information may be found in the online version of this article: Supplementary Table S1: List of deregulated genes in serum of cancer patients in comparision to serum of healthy individuals (p < 0.05, logFC ≥ 1). ENTREZ Gene ID Symbol Gene Name logFC p-value q-value 8407 TAGLN2 transgelin 2 3,78 3,40E-07 0,0022 7035 TFPI tissue factor pathway inhibitor (lipoprotein-associated coagulation inhibitor) 3,53 4,30E-05 0,022 28996 HIPK2 homeodomain interacting protein kinase 2 3,49 2,50E-06 0,0066 3690 ITGB3 integrin, beta 3 (platelet glycoprotein IIIa, antigen CD61) 3,48 0,00053 0,081 7035 TFPI tissue factor pathway inhibitor (lipoprotein-associated coagulation inhibitor) 3,45 1,80E-05 0,014 4900 NRGN neurogranin (protein kinase C substrate, RC3) 3,32 0,00012 0,037 10398 MYL9 myosin, light chain 9, regulatory 3,22 8,20E-06 0,011 3796 KIF2A kinesin heavy chain member 2A 3,14 0,00015 0,04 5476 CTSA cathepsin A 3,08 0,00015 0,04 6648 SOD2 superoxide dismutase 2, mitochondrial 3,07 4,20E-06 0,0077 2982 GUCY1A3 guanylate cyclase 1, soluble, alpha 3 3,07 0,0015 0,13 8459 TPST2 tyrosylprotein sulfotransferase 2 3,05 0,00043 0,074 2983 GUCY1B3 guanylate cyclase 1, soluble, beta 3 3,04 3,70E-05 0,021 145781 GCOM1 GRINL1A complex locus 3,02 0,00027 0,059 10611 PDLIM5 PDZ and LIM domain 5 2,87 1,80E-05 0,014 5567 PRKACB protein kinase, cAMP-dependent, catalytic, beta 2,85 0,0015 0,13 25907 TMEM158 transmembrane protein 158 (gene/pseudogene) 2,84 0,0068 0,27 8848 TSC22D1 TSC22 domain family, member 1 2,83 0,00058 0,084 26 351 APP amyloid beta (A4) precursor protein 2,82 0,00018 0,045 9240 PNMA1 paraneoplastic antigen MA1 2,78 0,00028 0,06 400073 C12orf76 chromosome 12 open reading frame 76 2,78 0,00069 0,091 649260 ILMN_35781 PREDICTED: Homo sapiens similar to LIM and senescent cell antigen-like domains 1 (LOC649260), mRNA. -
Mouse Epb42 Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Epb42 Knockout Project (CRISPR/Cas9) Objective: To create a Epb42 knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Epb42 gene (NCBI Reference Sequence: NM_013513 ; Ensembl: ENSMUSG00000023216 ) is located on Mouse chromosome 2. 13 exons are identified, with the ATG start codon in exon 1 and the TAA stop codon in exon 13 (Transcript: ENSMUST00000102490). Exon 2~5 will be selected as target site. Cas9 and gRNA will be co-injected into fertilized eggs for KO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Homozygotes for a targeted null mutation exhibit erythrocytic abnormalities including mild spherocytosis, altered ion transport, and dehydration. Exon 2 starts from about 0.53% of the coding region. Exon 2~5 covers 31.07% of the coding region. The size of effective KO region: ~5547 bp. The KO region does not have any other known gene. Page 1 of 9 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 2 3 4 5 13 Legends Exon of mouse Epb42 Knockout region Page 2 of 9 https://www.alphaknockout.com Overview of the Dot Plot (up) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 1985 bp section upstream of Exon 2 is aligned with itself to determine if there are tandem repeats. No significant tandem repeat is found in the dot plot matrix. So this region is suitable for PCR screening or sequencing analysis. Overview of the Dot Plot (down) Window size: 15 bp Forward Reverse Complement Sequence 12 Note: The 1230 bp section downstream of Exon 5 is aligned with itself to determine if there are tandem repeats. -
Identification of Novel Chemotherapeutic Strategies For
www.nature.com/scientificreports OPEN Identification of novel chemotherapeutic strategies for metastatic uveal melanoma Received: 17 November 2016 Paolo Fagone1, Rosario Caltabiano2, Andrea Russo3, Gabriella Lupo1, Accepted: 09 February 2017 Carmelina Daniela Anfuso1, Maria Sofia Basile1, Antonio Longo3, Ferdinando Nicoletti1, Published: 17 March 2017 Rocco De Pasquale4, Massimo Libra1 & Michele Reibaldi3 Melanoma of the uveal tract accounts for approximately 5% of all melanomas and represents the most common primary intraocular malignancy. Despite improvements in diagnosis and more effective local therapies for primary cancer, the rate of metastatic death has not changed in the past forty years. In the present study, we made use of bioinformatics to analyze the data obtained from three public available microarray datasets on uveal melanoma in an attempt to identify novel putative chemotherapeutic options for the liver metastatic disease. We have first carried out a meta-analysis of publicly available whole-genome datasets, that included data from 132 patients, comparing metastatic vs. non metastatic uveal melanomas, in order to identify the most relevant genes characterizing the spreading of tumor to the liver. Subsequently, the L1000CDS2 web-based utility was used to predict small molecules and drugs targeting the metastatic uveal melanoma gene signature. The most promising drugs were found to be Cinnarizine, an anti-histaminic drug used for motion sickness, Digitoxigenin, a precursor of cardiac glycosides, and Clofazimine, a fat-soluble iminophenazine used in leprosy. In vitro and in vivo validation studies will be needed to confirm the efficacy of these molecules for the prevention and treatment of metastatic uveal melanoma. Uveal melanoma is the most common primary intraocular cancer, and after the skin, the uveal tract is the second most common location for melanoma1. -
Literature Mining Sustains and Enhances Knowledge Discovery from Omic Studies
LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES by Rick Matthew Jordan B.S. Biology, University of Pittsburgh, 1996 M.S. Molecular Biology/Biotechnology, East Carolina University, 2001 M.S. Biomedical Informatics, University of Pittsburgh, 2005 Submitted to the Graduate Faculty of School of Medicine in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2016 UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE This dissertation was presented by Rick Matthew Jordan It was defended on December 2, 2015 and approved by Shyam Visweswaran, M.D., Ph.D., Associate Professor Rebecca Jacobson, M.D., M.S., Professor Songjian Lu, Ph.D., Assistant Professor Dissertation Advisor: Vanathi Gopalakrishnan, Ph.D., Associate Professor ii Copyright © by Rick Matthew Jordan 2016 iii LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES Rick Matthew Jordan, M.S. University of Pittsburgh, 2016 Genomic, proteomic and other experimentally generated data from studies of biological systems aiming to discover disease biomarkers are currently analyzed without sufficient supporting evidence from the literature due to complexities associated with automated processing. Extracting prior knowledge about markers associated with biological sample types and disease states from the literature is tedious, and little research has been performed to understand how to use this knowledge to inform the generation of classification models from ‘omic’ data. Using pathway analysis methods to better understand the underlying biology of complex diseases such as breast and lung cancers is state-of-the-art. However, the problem of how to combine literature- mining evidence with pathway analysis evidence is an open problem in biomedical informatics research.