GPR21 KO Mice Demonstrate No Resistance to High Fat Diet Induced
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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. -
Genome-Wide Prediction of Small Molecule Binding to Remote
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.04.236729; this version posted August 5, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder.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. 1 Genome-wide Prediction of Small Molecule Binding 2 to Remote Orphan Proteins Using Distilled Sequence 3 Alignment Embedding 1 2 3 4 4 Tian Cai , Hansaim Lim , Kyra Alyssa Abbu , Yue Qiu , 5,6 1,2,3,4,7,* 5 Ruth Nussinov , and Lei Xie 1 6 Ph.D. Program in Computer Science, The Graduate Center, The City University of New York, New York, 10016, USA 2 7 Ph.D. Program in Biochemistry, The Graduate Center, The City University of New York, New York, 10016, USA 3 8 Department of Computer Science, Hunter College, The City University of New York, New York, 10065, USA 4 9 Ph.D. Program in Biology, The Graduate Center, The City University of New York, New York, 10016, USA 5 10 Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, 11 Frederick, MD 21702, USA 6 12 Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel 13 Aviv, Israel 7 14 Helen and Robert Appel Alzheimer’s Disease Research Institute, Feil Family Brain & Mind Research Institute, Weill 15 Cornell Medicine, Cornell University, New York, 10021, USA * 16 [email protected] 17 July 27, 2020 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.04.236729; this version posted August 5, 2020. -
Edinburgh Research Explorer
Edinburgh Research Explorer International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list Citation for published version: Davenport, AP, Alexander, SPH, Sharman, JL, Pawson, AJ, Benson, HE, Monaghan, AE, Liew, WC, Mpamhanga, CP, Bonner, TI, Neubig, RR, Pin, JP, Spedding, M & Harmar, AJ 2013, 'International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list: recommendations for new pairings with cognate ligands', Pharmacological reviews, vol. 65, no. 3, pp. 967-86. https://doi.org/10.1124/pr.112.007179 Digital Object Identifier (DOI): 10.1124/pr.112.007179 Link: Link to publication record in Edinburgh Research Explorer Document Version: Publisher's PDF, also known as Version of record Published In: Pharmacological reviews Publisher Rights Statement: U.S. Government work not protected by U.S. copyright General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 02. Oct. 2021 1521-0081/65/3/967–986$25.00 http://dx.doi.org/10.1124/pr.112.007179 PHARMACOLOGICAL REVIEWS Pharmacol Rev 65:967–986, July 2013 U.S. -
Unbiased Identification of Trans Regulators of ADAR and A-To-I RNA Editing 2 3 Emily C
bioRxiv preprint doi: https://doi.org/10.1101/631200; this version posted May 8, 2019. 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. 1 Unbiased identification of trans regulators of ADAR and A-to-I RNA editing 2 3 Emily C. Freund1, Anne L. Sapiro1, Qin Li1, Sandra Linder1, James J. Moresco2, John R. Yates 4 III2, Jin Billy Li1 5 6 1 Department of Genetics, Stanford University, Stanford, CA, USA 7 2 Department of Molecular Medicine, 10550 North Torrey Pines Road, SR302, The Scripps 8 Research Institute, La Jolla, California 92037 9 10 Correspondence: [email protected] 11 12 13 Abstract 14 Adenosine-to-Inosine RNA editing is catalyzed by ADAR enzymes that deaminate adenosine to 15 inosine. While many RNA editing sites are known, few trans regulators have been identified. We 16 perform BioID followed by mass-spectrometry to identify trans regulators of ADAR1 and ADAR2 17 in HeLa and M17 neuroblastoma cells. We identify known and novel ADAR-interacting proteins. 18 Using ENCODE data we validate and characterize a subset of the novel interactors as global or 19 site-specific RNA editing regulators. Our set of novel trans regulators includes all four members 20 of the DZF-domain-containing family of proteins: ILF3, ILF2, STRBP, and ZFR. We show that 21 these proteins interact with each ADAR and modulate RNA editing levels. -
Knowledge Management Enviroments for High Throughput Biology
Knowledge Management Enviroments for High Throughput Biology Abhey Shah A Thesis submitted for the degree of MPhil Biology Department University of York September 2007 Abstract With the growing complexity and scale of data sets in computational biology and chemoin- formatics, there is a need for novel knowledge processing tools and platforms. This thesis describes a newly developed knowledge processing platform that is different in its emphasis on architecture, flexibility, builtin facilities for datamining and easy cross platform usage. There exist thousands of bioinformatics and chemoinformatics databases, that are stored in many different forms with different access methods, this is a reflection of the range of data structures that make up complex biological and chemical data. Starting from a theoretical ba- sis, FCA (Formal Concept Analysis) an applied branch of lattice theory, is used in this thesis to develop a file system that automatically structures itself by it’s contents. The procedure of extracting concepts from data sets is examined. The system also finds appropriate labels for the discovered concepts by extracting data from ontological databases. A novel method for scaling non-binary data for use with the system is developed. Finally the future of integrative systems biology is discussed in the context of efficiently closed causal systems. Contents 1 Motivations and goals of the thesis 11 1.1 Conceptual frameworks . 11 1.2 Biological foundations . 12 1.2.1 Gene expression data . 13 1.2.2 Ontology . 14 1.3 Knowledge based computational environments . 15 1.3.1 Interfaces . 16 1.3.2 Databases and the character of biological data . -
The Emerging Role of Ncrnas and RNA-Binding Proteins in Mitotic Apparatus Formation
non-coding RNA Review The Emerging Role of ncRNAs and RNA-Binding Proteins in Mitotic Apparatus Formation Kei K. Ito, Koki Watanabe and Daiju Kitagawa * Department of Physiological Chemistry, Graduate School of Pharmaceutical Science, The University of Tokyo, Bunkyo, Tokyo 113-0033, Japan; [email protected] (K.K.I.); [email protected] (K.W.) * Correspondence: [email protected] Received: 11 November 2019; Accepted: 13 March 2020; Published: 20 March 2020 Abstract: Mounting experimental evidence shows that non-coding RNAs (ncRNAs) serve a wide variety of biological functions. Recent studies suggest that a part of ncRNAs are critically important for supporting the structure of subcellular architectures. Here, we summarize the current literature demonstrating the role of ncRNAs and RNA-binding proteins in regulating the assembly of mitotic apparatus, especially focusing on centrosomes, kinetochores, and mitotic spindles. Keywords: ncRNA; centrosome; kinetochore; mitotic spindle 1. Introduction Non-coding RNAs (ncRNAs) are defined as a class of RNA molecules that are transcribed from genomic DNA, but not translated into proteins. They are mainly classified into the following two categories according to their length—small RNA (<200 nt) and long non-coding RNA (lncRNA) (>200 nt). Small RNAs include traditional RNA molecules, such as transfer RNA (tRNA), small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), PIWI-interacting RNA (piRNA), and micro RNA (miRNA), and they have been studied extensively [1]. Research on lncRNA is behind that on small RNA despite that recent transcriptome analysis has revealed that more than 120,000 lncRNAs are generated from the human genome [2–4]. -
G Protein-Coupled Receptors
S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2015/16: G protein-coupled receptors. British Journal of Pharmacology (2015) 172, 5744–5869 THE CONCISE GUIDE TO PHARMACOLOGY 2015/16: G protein-coupled receptors Stephen PH Alexander1, Anthony P Davenport2, Eamonn Kelly3, Neil Marrion3, John A Peters4, Helen E Benson5, Elena Faccenda5, Adam J Pawson5, Joanna L Sharman5, Christopher Southan5, Jamie A Davies5 and CGTP Collaborators 1School of Biomedical Sciences, University of Nottingham Medical School, Nottingham, NG7 2UH, UK, 2Clinical Pharmacology Unit, University of Cambridge, Cambridge, CB2 0QQ, UK, 3School of Physiology and Pharmacology, University of Bristol, Bristol, BS8 1TD, UK, 4Neuroscience Division, Medical Education Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK, 5Centre for Integrative Physiology, University of Edinburgh, Edinburgh, EH8 9XD, UK Abstract The Concise Guide to PHARMACOLOGY 2015/16 provides concise overviews of the key properties of over 1750 human drug targets with their pharmacology, plus links to an open access knowledgebase of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. The full contents can be found at http://onlinelibrary.wiley.com/doi/ 10.1111/bph.13348/full. G protein-coupled receptors are one of the eight major pharmacological targets into which the Guide is divided, with the others being: ligand-gated ion channels, voltage-gated ion channels, other ion channels, nuclear hormone receptors, catalytic receptors, enzymes and transporters. These are presented with nomenclature guidance and summary information on the best available pharmacological tools, alongside key references and suggestions for further reading. -
4 Understanding the Role of GNA13 Deregulation in Lymphomagenesis
Integrative Genomics Reveals a Role for GNA13 in Lymphomagenesis by Adrienne Greenough University Program in Genetics and Genomics Duke University Approved: ___________________________ Sandeep Dave, Supervisor ___________________________ Fred Dietrich ___________________________ Jack Keene ___________________________ Yuan Zhuang Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the University Program in Genetics and Genomics in the Graduate School of Duke University 2014 i v ABSTRACT Integrative Genomics Reveals a Role for GNA13 in Lymphomagenesis by Adrienne Greenough University Program in Genetics and Genomics Duke University Approved: ___________________________ Sandeep Dave, Supervisor ___________________________ Fred Dietrich ___________________________ Jack Keene ___________________________ Yuan Zhuang An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the University Program in Genetics and Genomics in the Graduate School of Duke University 2014 Copyright by Adrienne Greenough 2014 Abstract Lymphomas comprise a diverse group of malignancies derived from immune cells. High throughput sequencing has recently emerged as a powerful and versatile method for analysis of the cancer genome and transcriptome. As these data continue to emerge, the crucial work lies in sorting through the wealth of information to hone in on the critical aspects that will give us a better understanding of biology and new insight for how to treat disease. Finding the important signals within these large data sets is one of the major challenges of next generation sequencing. In this dissertation, I have developed several complementary strategies to describe the genetic underpinnings of lymphomas. I begin with developing a better method for RNA sequencing that enables strand-specific total RNA sequencing and alternative splicing profiling in the same analysis. -
Multi-Functionality of Proteins Involved in GPCR and G Protein Signaling: Making Sense of Structure–Function Continuum with In
Cellular and Molecular Life Sciences (2019) 76:4461–4492 https://doi.org/10.1007/s00018-019-03276-1 Cellular andMolecular Life Sciences REVIEW Multi‑functionality of proteins involved in GPCR and G protein signaling: making sense of structure–function continuum with intrinsic disorder‑based proteoforms Alexander V. Fonin1 · April L. Darling2 · Irina M. Kuznetsova1 · Konstantin K. Turoverov1,3 · Vladimir N. Uversky2,4 Received: 5 August 2019 / Revised: 5 August 2019 / Accepted: 12 August 2019 / Published online: 19 August 2019 © Springer Nature Switzerland AG 2019 Abstract GPCR–G protein signaling system recognizes a multitude of extracellular ligands and triggers a variety of intracellular signal- ing cascades in response. In humans, this system includes more than 800 various GPCRs and a large set of heterotrimeric G proteins. Complexity of this system goes far beyond a multitude of pair-wise ligand–GPCR and GPCR–G protein interactions. In fact, one GPCR can recognize more than one extracellular signal and interact with more than one G protein. Furthermore, one ligand can activate more than one GPCR, and multiple GPCRs can couple to the same G protein. This defnes an intricate multifunctionality of this important signaling system. Here, we show that the multifunctionality of GPCR–G protein system represents an illustrative example of the protein structure–function continuum, where structures of the involved proteins represent a complex mosaic of diferently folded regions (foldons, non-foldons, unfoldons, semi-foldons, and inducible foldons). The functionality of resulting highly dynamic conformational ensembles is fne-tuned by various post-translational modifcations and alternative splicing, and such ensembles can undergo dramatic changes at interaction with their specifc partners. -
Tango GPR21-Bla U2OS Cell–Based Assay User Guide
USER GUIDE Tango™ GPR21-bla U2OS Cell–Based Assay Catalog Number K1840 Doc. Part No. K1840.pps Pub. No. MAN0003008 Rev. 2.0 WARNING! Read the Safety Data Sheets (SDSs) and follow the handling instructions. Wear appropriate protective eyewear, clothing, and gloves. Safety Data Sheets (SDSs) are available from thermofisher.com/support. Product description ™ Tango GPR21-bla U2OS cells contain the human G protein-coupled receptor 21 linked to a TEV protease site and a Ga14‑VP16 ™ transcription factor stably integrated into the Tango GPCR‑bla U2OS cell line. This parental cell line stably expresses a beta‑arrestin/TEV ™ protease fusion protein and the beta‑lactamase reporter gene under the control of a UAS response element. The Tango GPR21-bla U2OS cells have been functionally validated for a response to dFBS. Table 1 Dose response of Tango™ GPR21-bla U2OS cells to dFBS Parameter Response T-Value >2.58 Overview of Tango™ GPCR cell-based assays The Tango™ GPCR assay technology combines the benefits of the Tango™ assay platform with the highly accurate, sensitive, and easy-to- ™ ™ use GeneBLAzer beta-lactamase reporter system. The Tango assay platform is based upon ligand binding to G‑Protein Coupled Receptors (GPCRs) that triggers desensitization, a process mediated by the recruitment of intracellular arrestin proteins to the activated receptor. As a result, the ligand-induced activation of GPCRs may be assayed by monitoring the interaction of arrestin with the test GPCR. A major advantage of this approach is that it does not depend on knowledge of the G‑protein signaling specificity of the target receptor. -
A Distinct Inflammatory Gene Expression Profile in Patients with Psoriatic Arthritis
Genes and Immunity (2006) 7, 583–591 & 2006 Nature Publishing Group All rights reserved 1466-4879/06 $30.00 www.nature.com/gene ORIGINAL ARTICLE A distinct inflammatory gene expression profile in patients with psoriatic arthritis AK Stoeckman1, EC Baechler1, WA Ortmann1, TW Behrens1, CJ Michet2 and EJ Peterson1 1Department of Medicine, University of Minnesota Medical School, Center for Immunology, University of Minnesota, Minneapolis, MN, USA and 2Division of Rheumatology, Mayo Clinic, Rochester, MN, USA Psoriatic arthritis (PsA) is a systemic inflammatory condition featuring polyarthritis associated with psoriasis. Apart from clinical indicators, few biomarkers exist to aid in the diagnosis and management of PsA. We hypothesized that whole blood gene expression profiling would provide new diagnostic markers and/or insights into pathogenesis of the disease. We compared whole blood gene expression profiles in PsA patients and in age-matched controls. We identified 310 differentially expressed genes, the majority of which are upregulated in PsA patients. The PsA expression profile does not significantly overlap with profiles derived from patients with rheumatoid arthritis or systemic lupus erythematosus. Logistic regression identified two lymphocyte-specific genes (zinc-finger protein 395 and phosphoinositide-3-kinase 2B) that discriminate PsA patients from normal controls. In addition, a highly coregulated cluster of overexpressed genes implicated in protein kinase A regulation strongly correlates with erythrocyte sedimentation rate. Other clusters of coregulated, yet suppressed genes in PsA patient blood include molecules involved in T-cell signaling. Finally, differentially expressed genes in PsA fall into diverse functional categories, but many downregulated genes belong to a CD40 signaling pathway. Together, the data suggest that gene expression profiles of PsA patient blood contain candidate novel disease markers and clues to pathogenesis. -
Combinatorial Strategies Using CRISPR/Cas9 for Gene Mutagenesis in Adult Mice
Combinatorial strategies using CRISPR/Cas9 for gene mutagenesis in adult mice Avery C. Hunker A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Washington 2019 Reading Committee: Larry S. Zweifel, Chair Sheri J. Mizumori G. Stanley McKnight Program Authorized to Offer Degree: Pharmacology 2 © Copyright 2019 Avery C. Hunker 3 University of Washington ABSTRACT Combinatorial strategies using CRISPR/Cas9 for gene mutagenesis in adult mice Avery C. Hunker Chair of the Supervisory Committee: Larry Zweifel Department of Pharmacology A major challenge to understanding how genes modulate complex behaviors is the inability to restrict genetic manipulations to defined cell populations or circuits. To circumvent this, we created a simple strategy for limiting gene knockout to specific cell populations using a viral-mediated, conditional CRISPR/SaCas9 system in combination with intersectional genetic strategies. A small single guide RNA (sgRNA) directs Staphylococcus aureus CRISPR-associated protein (SaCas9) to unique sites on DNA in a Cre-dependent manner resulting in double strand breaks and gene mutagenesis in vivo. To validate this technique we targeted nine different genes of diverse function in distinct cell types in mice and performed an array of analyses to confirm gene mutagenesis and subsequent protein loss, including IHC, cell-type specific DNA sequencing, electrophysiology, Western blots, and behavior. We show that these vectors are as efficient as conventional conditional gene knockout and provide a viable alternative to complex genetic crosses. This strategy provides additional benefits of 4 targeting gene mutagenesis to cell types previously difficult to isolate, and the ability to target genes in specific neural projections for gene inactivation.