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Comparative Transcriptome Analyses Indicate Molecular Homology of Zebrafish Swimbladder and Mammalian Lung
Comparative Transcriptome Analyses Indicate Molecular Homology of Zebrafish Swimbladder and Mammalian Lung Weiling Zheng1, Zhengyuan Wang1, John E. Collins2, Robert M. Andrews2, Derek Stemple2, Zhiyuan Gong1* 1 Department of Biological Sciences, National University of Singapore, Singapore, Singapore, 2 Vertebrate Development and Genetics, Wellcome Trust Genome Campus, Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom Abstract The fish swimbladder is a unique organ in vertebrate evolution and it functions for regulating buoyancy in most teleost species. It has long been postulated as a homolog of the tetrapod lung, but the molecular evidence is scarce. In order to understand the molecular function of swimbladder as well as its relationship with lungs in tetrapods, transcriptomic analyses of zebrafish swimbladder were carried out by RNA-seq. Gene ontology classification showed that genes in cytoskeleton and endoplasmic reticulum were enriched in the swimbladder. Further analyses depicted gene sets and pathways closely related to cytoskeleton constitution and regulation, cell adhesion, and extracellular matrix. Several prominent transcription factor genes in the swimbladder including hoxc4a, hoxc6a, hoxc8a and foxf1 were identified and their expressions in developing swimbladder during embryogenesis were confirmed. By comparison of enriched transcripts in the swimbladder with those in human and mouse lungs, we established the resemblance of transcriptome of the zebrafish swimbladder and mammalian lungs. Based on the transcriptomic data of zebrafish swimbladder, the predominant functions of swimbladder are in its epithelial and muscular tissues. Our comparative analyses also provide molecular evidence of the relatedness of the fish swimbladder and mammalian lung. Citation: Zheng W, Wang Z, Collins JE, Andrews RM, Stemple D, et al. -
Genome Wide Association Study of Response to Interval and Continuous Exercise Training: the Predict‑HIIT Study Camilla J
Williams et al. J Biomed Sci (2021) 28:37 https://doi.org/10.1186/s12929-021-00733-7 RESEARCH Open Access Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study Camilla J. Williams1†, Zhixiu Li2†, Nicholas Harvey3,4†, Rodney A. Lea4, Brendon J. Gurd5, Jacob T. Bonafglia5, Ioannis Papadimitriou6, Macsue Jacques6, Ilaria Croci1,7,20, Dorthe Stensvold7, Ulrik Wislof1,7, Jenna L. Taylor1, Trishan Gajanand1, Emily R. Cox1, Joyce S. Ramos1,8, Robert G. Fassett1, Jonathan P. Little9, Monique E. Francois9, Christopher M. Hearon Jr10, Satyam Sarma10, Sylvan L. J. E. Janssen10,11, Emeline M. Van Craenenbroeck12, Paul Beckers12, Véronique A. Cornelissen13, Erin J. Howden14, Shelley E. Keating1, Xu Yan6,15, David J. Bishop6,16, Anja Bye7,17, Larisa M. Haupt4, Lyn R. Grifths4, Kevin J. Ashton3, Matthew A. Brown18, Luciana Torquati19, Nir Eynon6 and Jef S. Coombes1* Abstract Background: Low cardiorespiratory ftness (V̇O2peak) is highly associated with chronic disease and mortality from all causes. Whilst exercise training is recommended in health guidelines to improve V̇O2peak, there is considerable inter-individual variability in the V̇O2peak response to the same dose of exercise. Understanding how genetic factors contribute to V̇O2peak training response may improve personalisation of exercise programs. The aim of this study was to identify genetic variants that are associated with the magnitude of V̇O2peak response following exercise training. Methods: Participant change in objectively measured V̇O2peak from 18 diferent interventions was obtained from a multi-centre study (Predict-HIIT). A genome-wide association study was completed (n 507), and a polygenic predictor score (PPS) was developed using alleles from single nucleotide polymorphisms= (SNPs) signifcantly associ- –5 ated (P < 1 10 ) with the magnitude of V̇O2peak response. -
Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism
ARTICLE Received 24 Aug 2013 | Accepted 14 Mar 2014 | Published 11 Apr 2014 DOI: 10.1038/ncomms4650 OPEN Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism Roser Corominas1,*, Xinping Yang2,3,*, Guan Ning Lin1,*, Shuli Kang1,*, Yun Shen2,3, Lila Ghamsari2,3,w, Martin Broly2,3, Maria Rodriguez2,3, Stanley Tam2,3, Shelly A. Trigg2,3,w, Changyu Fan2,3, Song Yi2,3, Murat Tasan4, Irma Lemmens5, Xingyan Kuang6, Nan Zhao6, Dheeraj Malhotra7, Jacob J. Michaelson7,w, Vladimir Vacic8, Michael A. Calderwood2,3, Frederick P. Roth2,3,4, Jan Tavernier5, Steve Horvath9, Kourosh Salehi-Ashtiani2,3,w, Dmitry Korkin6, Jonathan Sebat7, David E. Hill2,3, Tong Hao2,3, Marc Vidal2,3 & Lilia M. Iakoucheva1 Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases. -
The Utility of Genetic Risk Scores in Predicting the Onset of Stroke March 2021 6
DOT/FAA/AM-21/24 Office of Aerospace Medicine Washington, DC 20591 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke Diana Judith Monroy Rios, M.D1 and Scott J. Nicholson, Ph.D.2 1. KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510 Bogotá D.C. Colombia 2. FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 March 2021 NOTICE This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The United States Government assumes no liability for the contents thereof. _________________ This publication and all Office of Aerospace Medicine technical reports are available in full-text from the Civil Aerospace Medical Institute’s publications Web site: (www.faa.gov/go/oamtechreports) Technical Report Documentation Page 1. Report No. 2. Government Accession No. 3. Recipient's Catalog No. DOT/FAA/AM-21/24 4. Title and Subtitle 5. Report Date March 2021 The Utility of Genetic Risk Scores in Predicting the Onset of Stroke 6. Performing Organization Code 7. Author(s) 8. Performing Organization Report No. Diana Judith Monroy Rios M.D1, and Scott J. Nicholson, Ph.D.2 9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 1 KR 30 # 45-03 University Campus, Building 471, 5th Floor, Office 510, Bogotá D.C. Colombia 11. Contract or Grant No. 2 FAA Civil Aerospace Medical Institute, 6500 S. MacArthur Blvd Rm. 354, Oklahoma City, OK 73125 12. Sponsoring Agency name and Address 13. Type of Report and Period Covered Office of Aerospace Medicine Federal Aviation Administration 800 Independence Ave., S.W. -
New PDF Document
888.267.4436 [email protected] www.origene.com Name:CLDN6 mouse monoclonal antibody, clone OTI3E3 (formerly 3E3) Catalog: TA507011 Product Data Sheet - TRUEMAB Components: • CLDN6 mouse monoclonal antibody, clone OTI3E3 (formerly 3E3) (TA507011) • WB positive control also available: 20ug myc-DDK tagged CLDN6 HEK293T over-expression lysate lyophilized in RIPA buffer (LC412034). (Reconstitute into 20ul of 1x SDS sample buffer before loading; load 5ul per lane as WB control or as desired) Amount: 100ul Immunogen: Full length human recombinant protein of human CLDN6(NP_067018) produced in HEK293T cell. Host: Mouse Isotype: IgG1 Species Reactivity: Human Guaranteed WB, IF Applications: Suggested WB 1:1000, IF 1:100, Dilutions: Concentration: 1 mg/ml Buffer: PBS (PH 7.3) containing 1% BSA, 50% glycerol and 0.02% sodium azide. Purification: Purified from mouse ascites fluids by affinity chromatography Storage Condition: Shipped at -20C or with ice packs. Upon delivery store at -20C. Dilute in PBS (pH7.3) if necessary. Stable for 12 months from date of receipt. Avoid repeated freeze-thaws. Target Target Name: Homo sapiens claudin 6 (CLDN6) Alternative Name: OTTHUMP00000159248; claudin 6 Database Link: NP_067018 Entrez Gene 9074 Human Function: Tight junctions represent one mode of cell-to-cell adhesion in epithelial or endothelial cell sheets, forming continuous seals around cells and serving as a physical barrier to prevent solutes and water from passing freely through the paracellular space. These junctions are comprised of sets of continuous networking strands in the outwardly facing cytoplasmic leaflet, with complementary grooves in the inwardly facing extracytoplasmic leaflet. This gene encodes a component of tight junction strands, which This product is to be used for laboratory only. -
Blood-Based Biomarkers for Predicting the Risk for Five-Year Incident Coronary Heart Disease in the Framingham Heart Study Via Machine Learning
G C A T T A C G G C A T genes Article Blood-Based Biomarkers for Predicting the Risk for Five-Year Incident Coronary Heart Disease in the Framingham Heart Study via Machine Learning Meeshanthini V. Dogan 1,2,3,*, Steven R. H. Beach 4, Ronald L. Simons 5, Amaury Lendasse 6,7, Brandan Penaluna 8 and Robert A. Philibert 1,2,3,8 1 Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA; [email protected] 2 Cardio Diagnostics LLC, 2500 Crosspark Road, Coralville, IA 52241, USA 3 Department of Psychiatry, University of Iowa, Iowa City, IA 52242, USA 4 Department of Psychology, University of Georgia, Athens, GA 30602, USA; [email protected] 5 Department of Sociology, University of Georgia, Athens, GA 30606, USA; [email protected] 6 Information and Logistics Technology Department, University of Houston, Houston, TX 77004, USA; [email protected] 7 Department of Business Management and Analytics, Arcada University of Applied Sciences, 00560 Helsinki, Finland 8 Behavioral Diagnostics LLC, 2500 Crosspark Road, Coralville, IA 52241, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-319-353-4986 Received: 15 November 2018; Accepted: 12 December 2018; Published: 18 December 2018 Abstract: An improved approach for predicting the risk for incident coronary heart disease (CHD) could lead to substantial improvements in cardiovascular health. Previously, we have shown that genetic and epigenetic loci could predict CHD status more sensitively than conventional risk factors. Herein, we examine whether similar machine learning approaches could be used to develop a similar panel for predicting incident CHD. -
Bioinformatics Analyses of Genomic Imprinting
Bioinformatics Analyses of Genomic Imprinting Dissertation zur Erlangung des Grades des Doktors der Naturwissenschaften der Naturwissenschaftlich-Technischen Fakultät III Chemie, Pharmazie, Bio- und Werkstoffwissenschaften der Universität des Saarlandes von Barbara Hutter Saarbrücken 2009 Tag des Kolloquiums: 08.12.2009 Dekan: Prof. Dr.-Ing. Stefan Diebels Berichterstatter: Prof. Dr. Volkhard Helms Priv.-Doz. Dr. Martina Paulsen Vorsitz: Prof. Dr. Jörn Walter Akad. Mitarbeiter: Dr. Tihamér Geyer Table of contents Summary________________________________________________________________ I Zusammenfassung ________________________________________________________ I Acknowledgements _______________________________________________________II Abbreviations ___________________________________________________________ III Chapter 1 – Introduction __________________________________________________ 1 1.1 Important terms and concepts related to genomic imprinting __________________________ 2 1.2 CpG islands as regulatory elements ______________________________________________ 3 1.3 Differentially methylated regions and imprinting clusters_____________________________ 6 1.4 Reading the imprint __________________________________________________________ 8 1.5 Chromatin marks at imprinted regions___________________________________________ 10 1.6 Roles of repetitive elements ___________________________________________________ 12 1.7 Functional implications of imprinted genes _______________________________________ 14 1.8 Evolution and parental conflict ________________________________________________ -
1 Supporting Information for a Microrna Network Regulates
Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Methods in and Applications of the Sequencing of Short Non-Coding Rnas" (2013)
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2013 Methods in and Applications of the Sequencing of Short Non- Coding RNAs Paul Ryvkin University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Bioinformatics Commons, Genetics Commons, and the Molecular Biology Commons Recommended Citation Ryvkin, Paul, "Methods in and Applications of the Sequencing of Short Non-Coding RNAs" (2013). Publicly Accessible Penn Dissertations. 922. https://repository.upenn.edu/edissertations/922 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/922 For more information, please contact [email protected]. Methods in and Applications of the Sequencing of Short Non-Coding RNAs Abstract Short non-coding RNAs are important for all domains of life. With the advent of modern molecular biology their applicability to medicine has become apparent in settings ranging from diagonistic biomarkers to therapeutics and fields angingr from oncology to neurology. In addition, a critical, recent technological development is high-throughput sequencing of nucleic acids. The convergence of modern biotechnology with developments in RNA biology presents opportunities in both basic research and medical settings. Here I present two novel methods for leveraging high-throughput sequencing in the study of short non- coding RNAs, as well as a study in which they are applied to Alzheimer's Disease (AD). The computational methods presented here include High-throughput Annotation of Modified Ribonucleotides (HAMR), which enables researchers to detect post-transcriptional covalent modifications ot RNAs in a high-throughput manner. In addition, I describe Classification of RNAs by Analysis of Length (CoRAL), a computational method that allows researchers to characterize the pathways responsible for short non-coding RNA biogenesis. -
Comprehensive Array CGH of Normal Karyotype Myelodysplastic
Leukemia (2011) 25, 387–399 & 2011 Macmillan Publishers Limited All rights reserved 0887-6924/11 www.nature.com/leu LEADING ARTICLE Comprehensive array CGH of normal karyotype myelodysplastic syndromes reveals hidden recurrent and individual genomic copy number alterations with prognostic relevance A Thiel1, M Beier1, D Ingenhag1, K Servan1, M Hein1, V Moeller1, B Betz1, B Hildebrandt1, C Evers1,3, U Germing2 and B Royer-Pokora1 1Institute of Human Genetics and Anthropology, Medical Faculty, Heinrich Heine University, Duesseldorf, Germany and 2Department of Hematology, Oncology and Clinical Immunology, Heinrich Heine University, Duesseldorf, Germany About 40% of patients with myelodysplastic syndromes (MDSs) 40–50% of MDS cases have a normal karyotype. MDS patients present with a normal karyotype, and they are facing different with a normal karyotype and low-risk clinical parameters are courses of disease. To advance the biological understanding often assigned into the IPSS low and intermediate-1 risk groups. and to find molecular prognostic markers, we performed a high- resolution oligonucleotide array study of 107 MDS patients In the absence of genetic or biological markers, prognostic (French American British) with a normal karyotype and clinical stratification of these patients is difficult. To better prognosticate follow-up through the Duesseldorf MDS registry. Recurrent these patients, new parameters to identify patients at higher risk hidden deletions overlapping with known cytogenetic aberra- are urgently needed. With the more recently introduced modern tions or sites of known tumor-associated genes were identi- technologies of whole-genome-wide surveys of genetic aberra- fied in 4q24 (TET2, 2x), 5q31.2 (2x), 7q22.1 (3x) and 21q22.12 tions, it is hoped that more insights into the biology of disease (RUNX1, 2x). -
The MAP4K4-STRIPAK Complex Promotes Growth and Tissue Invasion In
bioRxiv preprint doi: https://doi.org/10.1101/2021.05.07.442906; this version posted May 8, 2021. 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 The MAP4K4-STRIPAK complex promotes growth and tissue invasion in 2 medulloblastoma 3 Jessica Migliavacca1, Buket Züllig1, Charles Capdeville1, Michael Grotzer2 and Martin Baumgartner1,* 4 1 Division of Oncology, Children’s Research Center, University Children’s Hospital Zürich, Zürich, 5 Switzerland 6 2 Division of Oncology, University Children’s Hospital Zürich, Zürich, Switzerland 7 8 *e-mail: [email protected] 9 10 Abstract 11 Proliferation and motility are mutually exclusive biological processes associated with cancer that depend 12 on precise control of upstream signaling pathways with overlapping functionalities. We find that STRN3 13 and STRN4 scaffold subunits of the STRIPAK complex interact with MAP4K4 for pathway regulation in 14 medulloblastoma. Disruption of the MAP4K4-STRIPAK complex impairs growth factor-induced 15 migration and tissue invasion and stalls YAP/TAZ target gene expression and oncogenic growth. The 16 migration promoting functions of the MAP4K4-STRIPAK complex involve the activation of novel PKCs 17 and the phosphorylation of the membrane targeting S157 residue of VASP through MAP4K4. The anti- 18 proliferative effect of complex disruption is associated with reduced YAP/TAZ target gene expression 19 and results in repressed tumor growth in the brain tissue. This dichotomous functionality of the STRIPAK 20 complex in migration and proliferation control acts through MAP4K4 regulation in tumor cells and 21 provides relevant mechanistic insights into novel tumorigenic functions of the STRIPAK complex in 22 medulloblastoma.