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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. -
Virus Interactions with Human Signal Transduction Pathways
Int. J. Computational Biology and Drug Design, Vol. 4, No. 1, 2011 83 Virus interactions with human signal transduction pathways Zhongming Zhao Departments of Biomedical Informatics, Psychiatry, and Cancer Biology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA E-mail: [email protected] Junfeng Xia Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA E-mail: [email protected] Oznur Tastan Language Technologies Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA E-mail: [email protected] Irtisha Singh Department of Structural Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA E-mail: [email protected] Meghana Kshirsagar Language Technologies Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA E-mail: [email protected] Copyright © 2011 Inderscience Enterprises Ltd. 84 Z. Zhao et al. Jaime Carbonell Language Technologies Institute, Computer Science Department, Machine Learning Department and Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA E-mail: [email protected] Judith Klein-Seetharaman* Department of Structural Biology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA E-mail: [email protected] *Corresponding author Abstract: Viruses depend on their hosts at every stage of their life cycles and must therefore communicate with them via Protein-Protein Interactions (PPIs). To investigate the mechanisms of communication by different viruses, we overlay reported pairwise human-virus PPIs on human signalling pathways. Of 671 pathways obtained from NCI and Reactome databases, 355 are potentially targeted by at least one virus. -
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. -
By Submitted in Partial Satisfaction of the Requirements for Degree of in In
Developments of Two Imaging based Technologies for Cell Biology Researches by Xiaowei Yan DISSERTATION Submitted in partial satisfaction of the requirements for degree of DOCTOR OF PHILOSOPHY in Biochemistry and Molecular Biology in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, SAN FRANCISCO Approved: ______________________________________________________________________________Ronald Vale Chair ______________________________________________________________________________Jonathan Weissman ______________________________________________________________________________Orion Weiner ______________________________________________________________________________ ______________________________________________________________________________ Committee Members Copyright 2021 By Xiaowei Yan ii DEDICATION Everything happens for the best. To my family, who supported me with all their love. iii ACKNOWLEDGEMENTS The greatest joy of my PhD has been joining UCSF, working and learning with such a fantastic group of scientists. I am extremely grateful for all the support and mentorship I received and would like to thank: My mentor, Ron Vale, who is such a great and generous person. Thank you for showing me that science is so much fun and thank you for always giving me the freedom in pursuing my interest. I am grateful for all the guidance from you and thank you for always supporting me whenever I needed. You are a person full of wisdom, and I have been learning so much from you and your attitude to science, science community and even life will continue inspire me. Thank you for being my mentor and thank you for being such a great mentor. Everyone else in Vale lab, past and present, for making our lab a sweet home. I would like to give my special thank to Marvin (Marvin Tanenbaum) and Nico (Nico Stuurman), two other mentors for me in the lab. I would like to thank them for helping me adapt to our lab, for all the valuable advice and for all the happiness during the time that we work together. -
Mouse Casp8ap2 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Casp8ap2 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Casp8ap2 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Casp8ap2 gene (NCBI Reference Sequence: NM_011997 ; Ensembl: ENSMUSG00000028282 ) is located on Mouse chromosome 4. 11 exons are identified, with the ATG start codon in exon 2 and the TAG stop codon in exon 10 (Transcript: ENSMUST00000029950). Exon 4 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Casp8ap2 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-75H14 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Mice homozygous for disruption of this gene die before implantation. Exon 4 starts from about 2.12% of the coding region. The knockout of Exon 4 will result in frameshift of the gene. The size of intron 3 for 5'-loxP site insertion: 819 bp, and the size of intron 4 for 3'-loxP site insertion: 639 bp. The size of effective cKO region: ~601 bp. The cKO region does not have any other known gene. Page 1 of 7 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 3 4 5 11 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Casp8ap2 Homology arm cKO region loxP site Page 2 of 7 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
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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/) -
Cytotoxic Effects and Changes in Gene Expression Profile
Toxicology in Vitro 34 (2016) 309–320 Contents lists available at ScienceDirect Toxicology in Vitro journal homepage: www.elsevier.com/locate/toxinvit Fusarium mycotoxin enniatin B: Cytotoxic effects and changes in gene expression profile Martina Jonsson a,⁎,MarikaJestoib, Minna Anthoni a, Annikki Welling a, Iida Loivamaa a, Ville Hallikainen c, Matti Kankainen d, Erik Lysøe e, Pertti Koivisto a, Kimmo Peltonen a,f a Chemistry and Toxicology Research Unit, Finnish Food Safety Authority (Evira), Mustialankatu 3, FI-00790 Helsinki, Finland b Product Safety Unit, Finnish Food Safety Authority (Evira), Mustialankatu 3, FI-00790 Helsinki, c The Finnish Forest Research Institute, Rovaniemi Unit, P.O. Box 16, FI-96301 Rovaniemi, Finland d Institute for Molecular Medicine Finland (FIMM), University of Helsinki, P.O. Box 20, FI-00014, Finland e Plant Health and Biotechnology, Norwegian Institute of Bioeconomy, Høyskoleveien 7, NO -1430 Ås, Norway f Finnish Safety and Chemicals Agency (Tukes), Opastinsilta 12 B, FI-00521 Helsinki, Finland article info abstract Article history: The mycotoxin enniatin B, a cyclic hexadepsipeptide produced by the plant pathogen Fusarium,isprevalentin Received 3 December 2015 grains and grain-based products in different geographical areas. Although enniatins have not been associated Received in revised form 5 April 2016 with toxic outbreaks, they have caused toxicity in vitro in several cell lines. In this study, the cytotoxic effects Accepted 28 April 2016 of enniatin B were assessed in relation to cellular energy metabolism, cell proliferation, and the induction of ap- Available online 6 May 2016 optosis in Balb 3T3 and HepG2 cells. The mechanism of toxicity was examined by means of whole genome ex- fi Keywords: pression pro ling of exposed rat primary hepatocytes. -
Global Analysis of Chaperone Effects Using a Reconstituted Cell-Free Translation System
Global analysis of chaperone effects using a reconstituted cell-free translation system Tatsuya Niwaa, Takashi Kanamorib,1, Takuya Uedab,2, and Hideki Taguchia,2 aDepartment of Biomolecular Engineering, Graduate School of Biosciences and Biotechnology, Tokyo Institute of Technology, Midori-ku, Yokohama 226-8501, Japan; and bDepartment of Medical Genome Sciences, Graduate School of Frontier Sciences, University of Tokyo, Kashiwa, Chiba 277-8562, Japan Edited by George H. Lorimer, University of Maryland, College Park, MD, and approved April 19, 2012 (received for review January 25, 2012) Protein folding is often hampered by protein aggregation, which can three chaperone systems are known to act cooperatively: TF and be prevented by a variety of chaperones in the cell. A dataset that DnaK exhibit overlapping cotranslational roles in vivo (13–15). evaluates which chaperones are effective for aggregation-prone Overexpression of DnaK/DnaJ and GroEL/GroES in E. coli proteins would provide an invaluable resource not only for un- rpoH mutant cells, which are deficient in heat-shock proteins, derstanding the roles of chaperones, but also for broader applications prevents aggregation of newly translated proteins (16). GroEL is in protein science and engineering. Therefore, we comprehensively believed to be involved in folding after the polypeptides are re- evaluated the effects of the major Escherichia coli chaperones, trigger leased from the ribosome, although the possible cotranslational factor, DnaK/DnaJ/GrpE, and GroEL/GroES, on ∼800 aggregation- involvement of GroEL has also been reported (17–20). prone cytosolic E. coli proteins, using a reconstituted chaperone-free Over the past two decades many efforts have been focused on translation system. -
Proteomic Analysis Uncovers Measles Virus Protein C Interaction with P65
bioRxiv preprint doi: https://doi.org/10.1101/2020.05.08.084418; this version posted May 9, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Proteomic Analysis Uncovers Measles Virus Protein C Interaction with p65/iASPP/p53 Protein Complex Alice Meignié1,2*, Chantal Combredet1*, Marc Santolini 3,4, István A. Kovács4,5,6, Thibaut Douché7, Quentin Giai Gianetto 7,8, Hyeju Eun9, Mariette Matondo7, Yves Jacob10, Regis Grailhe9, Frédéric Tangy1**, and Anastassia V. Komarova1, 10** 1 Viral Genomics and Vaccination Unit, Department of Virology, Institut Pasteur, CNRS UMR-3569, 75015 Paris, France 2 Université Paris Diderot, Sorbonne Paris Cité, Paris, France 3 Center for Research and Interdisciplinarity (CRI), Université de Paris, INSERM U1284 4 Network Science Institute and Department of Physics, Northeastern University, Boston, MA 02115, USA 5 Department of Physics and Astronomy, Northwestern University, Evanston, IL 60208-3109, USA 6 Department of Network and Data Science, Central European University, Budapest, H-1051, Hungary 7 Proteomics platform, Mass Spectrometry for Biology Unit (MSBio), Institut Pasteur, CNRS USR 2000, Paris, France. 8 Bioinformatics and Biostatistics Hub, Computational Biology Department, Institut Pasteur, CNRS USR3756, Paris, France 9 Technology Development Platform, Institut Pasteur Korea, Seongnam-si, Republic of Korea 10 Laboratory of Molecular Genetics of RNA Viruses, Institut Pasteur, CNRS UMR-3569, -
Supplementary Data
SUPPLEMENTARY DATA A cyclin D1-dependent transcriptional program predicts clinical outcome in mantle cell lymphoma Santiago Demajo et al. 1 SUPPLEMENTARY DATA INDEX Supplementary Methods p. 3 Supplementary References p. 8 Supplementary Tables (S1 to S5) p. 9 Supplementary Figures (S1 to S15) p. 17 2 SUPPLEMENTARY METHODS Western blot, immunoprecipitation, and qRT-PCR Western blot (WB) analysis was performed as previously described (1), using cyclin D1 (Santa Cruz Biotechnology, sc-753, RRID:AB_2070433) and tubulin (Sigma-Aldrich, T5168, RRID:AB_477579) antibodies. Co-immunoprecipitation assays were performed as described before (2), using cyclin D1 antibody (Santa Cruz Biotechnology, sc-8396, RRID:AB_627344) or control IgG (Santa Cruz Biotechnology, sc-2025, RRID:AB_737182) followed by protein G- magnetic beads (Invitrogen) incubation and elution with Glycine 100mM pH=2.5. Co-IP experiments were performed within five weeks after cell thawing. Cyclin D1 (Santa Cruz Biotechnology, sc-753), E2F4 (Bethyl, A302-134A, RRID:AB_1720353), FOXM1 (Santa Cruz Biotechnology, sc-502, RRID:AB_631523), and CBP (Santa Cruz Biotechnology, sc-7300, RRID:AB_626817) antibodies were used for WB detection. In figure 1A and supplementary figure S2A, the same blot was probed with cyclin D1 and tubulin antibodies by cutting the membrane. In figure 2H, cyclin D1 and CBP blots correspond to the same membrane while E2F4 and FOXM1 blots correspond to an independent membrane. Image acquisition was performed with ImageQuant LAS 4000 mini (GE Healthcare). Image processing and quantification were performed with Multi Gauge software (Fujifilm). For qRT-PCR analysis, cDNA was generated from 1 µg RNA with qScript cDNA Synthesis kit (Quantabio). qRT–PCR reaction was performed using SYBR green (Roche). -
Genome-Wide Screen of Cell-Cycle Regulators in Normal and Tumor Cells
bioRxiv preprint doi: https://doi.org/10.1101/060350; this version posted June 23, 2016. 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. Genome-wide screen of cell-cycle regulators in normal and tumor cells identifies a differential response to nucleosome depletion Maria Sokolova1, Mikko Turunen1, Oliver Mortusewicz3, Teemu Kivioja1, Patrick Herr3, Anna Vähärautio1, Mikael Björklund1, Minna Taipale2, Thomas Helleday3 and Jussi Taipale1,2,* 1Genome-Scale Biology Program, P.O. Box 63, FI-00014 University of Helsinki, Finland. 2Science for Life laboratory, Department of Biosciences and Nutrition, Karolinska Institutet, SE- 141 83 Stockholm, Sweden. 3Science for Life laboratory, Division of Translational Medicine and Chemical Biology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, S-171 21 Stockholm, Sweden To identify cell cycle regulators that enable cancer cells to replicate DNA and divide in an unrestricted manner, we performed a parallel genome-wide RNAi screen in normal and cancer cell lines. In addition to many shared regulators, we found that tumor and normal cells are differentially sensitive to loss of the histone genes transcriptional regulator CASP8AP2. In cancer cells, loss of CASP8AP2 leads to a failure to synthesize sufficient amount of histones in the S-phase of the cell cycle, resulting in slowing of individual replication forks. Despite this, DNA replication fails to arrest, and tumor cells progress in an elongated S-phase that lasts several days, finally resulting in death of most of the affected cells. -
Chaperonin-Assisted Protein Folding: a Chronologue
Quarterly Reviews of Chaperonin-assisted protein folding: Biophysics a chronologue cambridge.org/qrb Arthur L. Horwich1,2 and Wayne A. Fenton2 1Howard Hughes Medical Institute, Yale School of Medicine, Boyer Center, 295 Congress Avenue, New Haven, CT 06510, USA and 2Department of Genetics, Yale School of Medicine, Boyer Center, 295 Congress Avenue, New Invited Review Haven, CT 06510, USA Cite this article: Horwich AL, Fenton WA (2020). Chaperonin-assisted protein folding: a Abstract chronologue. Quarterly Reviews of Biophysics This chronologue seeks to document the discovery and development of an understanding of – 53, e4, 1 127. https://doi.org/10.1017/ oligomeric ring protein assemblies known as chaperonins that assist protein folding in the cell. S0033583519000143 It provides detail regarding genetic, physiologic, biochemical, and biophysical studies of these Received: 16 August 2019 ATP-utilizing machines from both in vivo and in vitro observations. The chronologue is orga- Revised: 21 November 2019 nized into various topics of physiology and mechanism, for each of which a chronologic order Accepted: 26 November 2019 is generally followed. The text is liberally illustrated to provide firsthand inspection of the key Key words: pieces of experimental data that propelled this field. Because of the length and depth of this Chaperonin; GroEL; GroES; Hsp60; protein piece, the use of the outline as a guide for selected reading is encouraged, but it should also be folding of help in pursuing the text in direct order. Author for correspondence: Arthur L. Horwich, E-mail: [email protected] Table of contents I. Foundational discovery of Anfinsen and coworkers – the amino acid sequence of a polypeptide contains all of the information required for folding to the native state 7 II.