Identification of Novel A-RAF Phosphorylation Sites
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Analysis of Trans Esnps Infers Regulatory Network Architecture
Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Anat Kreimer All rights reserved ABSTRACT Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer eSNPs are genetic variants associated with transcript expression levels. The characteristics of such variants highlight their importance and present a unique opportunity for studying gene regulation. eSNPs affect most genes and their cell type specificity can shed light on different processes that are activated in each cell. They can identify functional variants by connecting SNPs that are implicated in disease to a molecular mechanism. Examining eSNPs that are associated with distal genes can provide insights regarding the inference of regulatory networks but also presents challenges due to the high statistical burden of multiple testing. Such association studies allow: simultaneous investigation of many gene expression phenotypes without assuming any prior knowledge and identification of unknown regulators of gene expression while uncovering directionality. This thesis will focus on such distal eSNPs to map regulatory interactions between different loci and expose the architecture of the regulatory network defined by such interactions. We develop novel computational approaches and apply them to genetics-genomics data in human. We go beyond pairwise interactions to define network motifs, including regulatory modules and bi-fan structures, showing them to be prevalent in real data and exposing distinct attributes of such arrangements. We project eSNP associations onto a protein-protein interaction network to expose topological properties of eSNPs and their targets and highlight different modes of distal regulation. -
Bayesian Hierarchical Modeling of High-Throughput Genomic Data with Applications to Cancer Bioinformatics and Stem Cell Differentiation
BAYESIAN HIERARCHICAL MODELING OF HIGH-THROUGHPUT GENOMIC DATA WITH APPLICATIONS TO CANCER BIOINFORMATICS AND STEM CELL DIFFERENTIATION by Keegan D. Korthauer A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Statistics) at the UNIVERSITY OF WISCONSIN–MADISON 2015 Date of final oral examination: 05/04/15 The dissertation is approved by the following members of the Final Oral Committee: Christina Kendziorski, Professor, Biostatistics and Medical Informatics Michael A. Newton, Professor, Statistics Sunduz Kele¸s,Professor, Biostatistics and Medical Informatics Sijian Wang, Associate Professor, Biostatistics and Medical Informatics Michael N. Gould, Professor, Oncology © Copyright by Keegan D. Korthauer 2015 All Rights Reserved i in memory of my grandparents Ma and Pa FL Grandma and John ii ACKNOWLEDGMENTS First and foremost, I am deeply grateful to my thesis advisor Christina Kendziorski for her invaluable advice, enthusiastic support, and unending patience throughout my time at UW-Madison. She has provided sound wisdom on everything from methodological principles to the intricacies of academic research. I especially appreciate that she has always encouraged me to eke out my own path and I attribute a great deal of credit to her for the successes I have achieved thus far. I also owe special thanks to my committee member Professor Michael Newton, who guided me through one of my first collaborative research experiences and has continued to provide key advice on my thesis research. I am also indebted to the other members of my thesis committee, Professor Sunduz Kele¸s,Professor Sijian Wang, and Professor Michael Gould, whose valuable comments, questions, and suggestions have greatly improved this dissertation. -
14-3-3Sigma Negatively Regulates the Stability and Subcellular Localization of Cop1
The Texas Medical Center Library DigitalCommons@TMC The University of Texas MD Anderson Cancer Center UTHealth Graduate School of The University of Texas MD Anderson Cancer Biomedical Sciences Dissertations and Theses Center UTHealth Graduate School of (Open Access) Biomedical Sciences 12-2010 14-3-3SIGMA NEGATIVELY REGULATES THE STABILITY AND SUBCELLULAR LOCALIZATION OF COP1 Chun-Hui Su Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Biology Commons Recommended Citation Su, Chun-Hui, "14-3-3SIGMA NEGATIVELY REGULATES THE STABILITY AND SUBCELLULAR LOCALIZATION OF COP1" (2010). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 101. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/101 This Dissertation (PhD) is brought to you for free and open access by the The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences at DigitalCommons@TMC. It has been accepted for inclusion in The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access) by an authorized administrator of DigitalCommons@TMC. For more information, please contact [email protected]. 14-3-3SIGMA NEGATIVELY REGULATES THE STABILITY AND SUBCELLULAR LOCALIZATION OF COP1 By Chun-Hui Su, M.S. APPROVED: ______________________________ Mong-Hong Lee, Supervisory Professor ______________________________ Randy -
Identification and Characterization of a Novel Human Testis-Specific
Biochemical and Biophysical Research Communications 285, 400–408 (2001) doi:10.1006/bbrc.2001.5165, available online at http://www.idealibrary.com on Identification and Characterization of a Novel Human Testis-Specific Kinase Substrate Gene Which Is Downregulated in Testicular Tumors Andreas Scorilas,*,† George M. Yousef,*,† Klaus Jung,‡ Ewa Rajpert-De Meyts,§ Stephan Carsten,‡ and Eleftherios P. Diamandis*,†,1 *Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, Toronto, Ontario M5G 1X5, Canada; †Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario M5G 1L5, Canada; ‡Department of Urology, University Hospital Charite, Humboldt University, Berlin, Germany; and §Department of Growth and Reproduction, Juliane Marie Centre, National University Hospital, Copenhagen, Denmark Received June 8, 2001 physiology, most probably in the process of spermato- By using the positional candidate gene approach, we genesis or spermiogenesis. © 2001 Academic Press identified a novel putative serine/threonine kinase Key Words: kinase substrates; testis-specific genes; substrate gene that maps to chromosome 19q13.3. gene mapping; gene characterization; TSKS; testis- Screening of expressed sequence tags and reverse specific kinase substrate; RRAS; IRF3; testicular transcription–polymerase chain reaction of total RNA cancer. from human tissues allowed us to establish the expres- sion of the gene and delineate its genomic organiza- tion (GenBank Accession No. AF200923). This gene (TSKS, for testis-specific kinase substrate) is com- Protein phosphorylation is the most common post- posed of 11 exons and 10 intervening introns and is translational protein modification in eukaryotes and a likely the human homolog of the mouse testis-specific fundamental mechanism for the direct or indirect con- serine kinase substrate gene. -
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. -
YWHAG Antibody (Center) Purified Rabbit Polyclonal Antibody (Pab) Catalog # Ap2939c
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 YWHAG Antibody (Center) Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP2939c Specification YWHAG Antibody (Center) - Product Information Application WB, IHC-P, FC,E Primary Accession P61981 Other Accession Q6NRY9, Q6PCG0, P61983, P61982, Q5F3W6, P68252, P68253 Reactivity Human, Mouse Predicted Bovine, Chicken, Rat, Sheep, Xenopus Host Rabbit Clonality Polyclonal Isotype Rabbit Ig Calculated MW 28303 Western blot analysis of YWHAG Antibody Antigen Region 136-164 (Center) (Cat. #AP2939c) in mouse cerebellum tissue lysates (35ug/lane). YWHAG Antibody (Center) - Additional YWHAG (arrow) was detected using the Information purified Pab. Gene ID 7532 Other Names 14-3-3 protein gamma, Protein kinase C inhibitor protein 1, KCIP-1, 14-3-3 protein gamma, N-terminally processed, YWHAG Target/Specificity This YWHAG antibody is generated from rabbits immunized with a KLH conjugated synthetic peptide between 136-164 amino acids from the Central region of human YWHAG. Dilution Western blot analysis of YWHAG (arrow) WB~~1:1000 using rabbit polyclonal YWHAG Antibody IHC-P~~1:50~100 (Center) (Cat. #AP2939c). 293 cell lysates (2 FC~~1:10~50 ug/lane) either nontransfected (Lane 1) or transiently transfected (Lane 2) with the Format YWHAG gene. Purified polyclonal antibody supplied in PBS with 0.09% (W/V) sodium azide. This antibody is prepared by Saturated Ammonium Sulfate (SAS) precipitation followed by dialysis against PBS. Page 1/3 10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 Storage Maintain refrigerated at 2-8°C for up to 2 weeks. -
RT² Profiler PCR Array (96-Well Format and 384-Well [4 X 96] Format)
RT² Profiler PCR Array (96-Well Format and 384-Well [4 x 96] Format) Human Mitochondria Cat. no. 330231 PAHS-087ZA For pathway expression analysis Format For use with the following real-time cyclers RT² Profiler PCR Array, Applied Biosystems® models 5700, 7000, 7300, 7500, Format A 7700, 7900HT, ViiA™ 7 (96-well block); Bio-Rad® models iCycler®, iQ™5, MyiQ™, MyiQ2; Bio-Rad/MJ Research Chromo4™; Eppendorf® Mastercycler® ep realplex models 2, 2s, 4, 4s; Stratagene® models Mx3005P®, Mx3000P®; Takara TP-800 RT² Profiler PCR Array, Applied Biosystems models 7500 (Fast block), 7900HT (Fast Format C block), StepOnePlus™, ViiA 7 (Fast block) RT² Profiler PCR Array, Bio-Rad CFX96™; Bio-Rad/MJ Research models DNA Format D Engine Opticon®, DNA Engine Opticon 2; Stratagene Mx4000® RT² Profiler PCR Array, Applied Biosystems models 7900HT (384-well block), ViiA 7 Format E (384-well block); Bio-Rad CFX384™ RT² Profiler PCR Array, Roche® LightCycler® 480 (96-well block) Format F RT² Profiler PCR Array, Roche LightCycler 480 (384-well block) Format G RT² Profiler PCR Array, Fluidigm® BioMark™ Format H Sample & Assay Technologies Description The Human Mitochondria RT² Profiler PCR Array profiles the expression of 84 genes involved in the biogenesis and function of the cell's powerhouse organelle. The genes monitored by this array include regulators and mediators of mitochondrial molecular transport of not only the metabolites needed for the electron transport chain and oxidative phosphorylation, but also the ions required for maintaining the mitochondrial membrane polarization and potential important for ATP synthesis. Metabolism and energy production are not the only functions of mitochondria. -
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Supplementary Figure S1. Results of flow cytometry analysis, performed to estimate CD34 positivity, after immunomagnetic separation in two different experiments. As monoclonal antibody for labeling the sample, the fluorescein isothiocyanate (FITC)- conjugated mouse anti-human CD34 MoAb (Mylteni) was used. Briefly, cell samples were incubated in the presence of the indicated MoAbs, at the proper dilution, in PBS containing 5% FCS and 1% Fc receptor (FcR) blocking reagent (Miltenyi) for 30 min at 4 C. Cells were then washed twice, resuspended with PBS and analyzed by a Coulter Epics XL (Coulter Electronics Inc., Hialeah, FL, USA) flow cytometer. only use Non-commercial 1 Supplementary Table S1. Complete list of the datasets used in this study and their sources. GEO Total samples Geo selected GEO accession of used Platform Reference series in series samples samples GSM142565 GSM142566 GSM142567 GSM142568 GSE6146 HG-U133A 14 8 - GSM142569 GSM142571 GSM142572 GSM142574 GSM51391 GSM51392 GSE2666 HG-U133A 36 4 1 GSM51393 GSM51394 only GSM321583 GSE12803 HG-U133A 20 3 GSM321584 2 GSM321585 use Promyelocytes_1 Promyelocytes_2 Promyelocytes_3 Promyelocytes_4 HG-U133A 8 8 3 GSE64282 Promyelocytes_5 Promyelocytes_6 Promyelocytes_7 Promyelocytes_8 Non-commercial 2 Supplementary Table S2. Chromosomal regions up-regulated in CD34+ samples as identified by the LAP procedure with the two-class statistics coded in the PREDA R package and an FDR threshold of 0.5. Functional enrichment analysis has been performed using DAVID (http://david.abcc.ncifcrf.gov/) -
XIAO-DISSERTATION-2015.Pdf
CELLULAR AND PROCESS ENGINEERING TO IMPROVE MAMMALIAN MEMBRANE PROTEIN EXPRESSION By Su Xiao A dissertation is submitted to Johns Hopkins University in conformity with the requirements for degree of Doctor of Philosophy Baltimore, Maryland May 2015 © 2015 Su Xiao All Rights Reserved Abstract Improving the expression level of recombinant mammalian proteins has been pursued for production of commercial biotherapeutics in industry, as well as for biomedical studies in academia, as an adequate supply of correctly folded proteins is a prerequisite for all structure and function studies. Presented in this dissertation are different strategies to improve protein functional expression level, especially for membrane proteins. The model protein is neurotensin receptor 1 (NTSR1), a hard-to- express G protein-coupled receptor (GPCR). GPCRs are integral membrane proteins playing a central role in cell signaling and are targets for most of the medicines sold worldwide. Obtaining adequate functional GPCRs has been a bottleneck in their structure studies because the expression of these proteins from mammalian cells is very low. The first strategy is the adoption of mammalian inducible expression system. A stable and inducible T-REx-293 cell line overexpressing an engineered rat NTSR1 was constructed. 2.5 million Functional copies of NTSR1 per cell were detected on plasma membrane, which is 167 fold improvement comparing to NTSR1 constitutive expression. The second strategy is production process development including suspension culture adaptation and induction parameter optimization. A further 3.5 fold improvement was achieved and approximately 1 milligram of purified functional NTSR1 per liter suspension culture was obtained. This was comparable yield to the transient baculovirus- insect cell system. -
Nck Adaptor Proteins Link Nephrin at the Podocyte Slit Diaphragm to the Hippo Regulator WTIP
Nck Adaptor Proteins Link Nephrin at the Podocyte Slit Diaphragm to the Hippo Regulator WTIP by Ava Keyvani Chahi A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Molecular and Cellular Biology Guelph, Ontario, Canada © Ava Keyvani Chahi, December, 2014 ABSTRACT NCK ADAPTOR PROTEINS LINK NEPHRIN AT THE PODOCYTE SLIT DIAPHRAGM TO THE HIPPO REGULATOR WTIP Ava Keyvani Chahi Advisor: University of Guelph, 2014 Dr. Nina Jones Podocytes are specialized epithelial cells that contribute to the kidney blood filtration barrier. Their unique cytoskeletal architecture and other complex biological signals are largely maintained by a modified adherens junction known as the slit diaphragm (SD). A major component of the SD is the transmembrane protein nephrin, which upon tyrosine phosphorylation of the intracellular domain regulates actin remodeling and cell survival. Nck adaptor proteins are a critical component of the filtration barrier and connect nephrin to actin-remodeling proteins by binding phosphotyrosine residues and proline-rich motifs. Herein we identify a novel Nck binding partner, Wilm’s tumor interacting protein (WTIP). WTIP is a transcription regulator in podocytes, though Nck is not nuclear localized under conditions known to induce WTIP nuclear accumulation. However, we demonstrate that WTIP is recruited to nephrin, upon nephrin tyrosine phosphorylation by Src Family Kinases, in an Nck-dependent manner. WTIP is an evolutionarily conserved negative regulator of the Hippo kinase pathway, which inhibits the transcription factor Yap. Yap activity promotes podocyte survival. We show in mice that cannot recruit Nck to nephrin, and by extension WTIP, that Yap protein levels are downregulated. -
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 -
Mitochondrial Carriers Regulating Insulin Secretion Profiled in Human Islets Upon Metabolic Stress
Jiménez-Sánchez et al. Supplementary files Mitochondrial carriers regulating insulin secretion profiled in human islets upon metabolic stress Supplementary Table S1: Clinical Data of the human donors of pancreatic islets, type of analyses performed and tested conditions. Supplementary Table S2: Quantitative data related to the transcriptomic profiles of mitochondrial solute carriers and associated genes in human islets upon metabolic stress. NA: Not applicable, ND: not detected. Supplementary Table S3: Quantitative data related to the transcriptomic profiles of the electron transport chain machinery and related mitochondrial carriers in human islets upon metabolic stress.NA: Not applicable, ND: not detected. Supplementary Table S4: Quantitative data related to the transcriptomic profiles of the outer and inner mitochondrial membrane translocases TOM/TIM machinery in human islets upon metabolic stress.NA: Not applicable, ND: not detected. Supplementary Table S5: Quantitative data related to the transcriptomic profiles of mitochondrial iron transport genes in human islets under metabolic stress. NA: Not applicable, ND: not detected. Supplementary Table S6: Quantitative data related to the transcriptomic profiles of mitochondrial calcium transport genes in human islets upon metabolic stress. NA: Not applicable, ND: not detected. Supplementary Table S7: Primers used for quantitative RT-PCR analysis Supplementary Figure S1: Functional interaction network of human (a) mitochondrial calcium transport genes; (b) outer and inner mitochondrial membrane translocases TOM/TIM machinery; (c) electron transport chain machinery and related carriers; (d) mitochondrial iron transport genes. Nodes were connected using the STRING interaction knowledgebase with a confidence score >0.4. Supplementary Figure S2: Effects of high 25 mM glucose (G25) and 0.4 mM oleate (Olea) or palmitate (Palm) on the transcriptional regulation of the electron transport chain machinery.