Novel Promoters and Coding First Exons in DLG2
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PARSANA-DISSERTATION-2020.Pdf
DECIPHERING TRANSCRIPTIONAL PATTERNS OF GENE REGULATION: A COMPUTATIONAL APPROACH by Princy Parsana A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland July, 2020 © 2020 Princy Parsana All rights reserved Abstract With rapid advancements in sequencing technology, we now have the ability to sequence the entire human genome, and to quantify expression of tens of thousands of genes from hundreds of individuals. This provides an extraordinary opportunity to learn phenotype relevant genomic patterns that can improve our understanding of molecular and cellular processes underlying a trait. The high dimensional nature of genomic data presents a range of computational and statistical challenges. This dissertation presents a compilation of projects that were driven by the motivation to efficiently capture gene regulatory patterns in the human transcriptome, while addressing statistical and computational challenges that accompany this data. We attempt to address two major difficulties in this domain: a) artifacts and noise in transcriptomic data, andb) limited statistical power. First, we present our work on investigating the effect of artifactual variation in gene expression data and its impact on trans-eQTL discovery. Here we performed an in-depth analysis of diverse pre-recorded covariates and latent confounders to understand their contribution to heterogeneity in gene expression measurements. Next, we discovered 673 trans-eQTLs across 16 human tissues using v6 data from the Genotype Tissue Expression (GTEx) project. Finally, we characterized two trait-associated trans-eQTLs; one in Skeletal Muscle and another in Thyroid. Second, we present a principal component based residualization method to correct gene expression measurements prior to reconstruction of co-expression networks. -
DNA Breakpoint Assay Reveals a Majority of Gross Duplications Occur in Tandem Reducing VUS Classifications in Breast Cancer Predisposition Genes
© American College of Medical Genetics and Genomics ARTICLE Corrected: Correction DNA breakpoint assay reveals a majority of gross duplications occur in tandem reducing VUS classifications in breast cancer predisposition genes Marcy E. Richardson, PhD1, Hansook Chong, PhD1, Wenbo Mu, MS1, Blair R. Conner, MS1, Vickie Hsuan, MS1, Sara Willett, MS1, Stephanie Lam, MS1, Pei Tsai, CGMBS, MB (ASCP)1, Tina Pesaran, MS, CGC1, Adam C. Chamberlin, PhD1, Min-Sun Park, PhD1, Phillip Gray, PhD1, Rachid Karam, MD, PhD1 and Aaron Elliott, PhD1 Purpose: Gross duplications are ambiguous in terms of clinical cohort, while the remainder have unknown tandem status. Among interpretation due to the limitations of the detection methods that the tandem gross duplications that were eligible for reclassification, cannot infer their context, namely, whether they occur in tandem or 95% of them were upgraded to pathogenic. are duplicated and inserted elsewhere in the genome. We Conclusion: DBA is a novel, high-throughput, NGS-based method investigated the proportion of gross duplications occurring in that informs the tandem status, and thereby the classification of, tandem in breast cancer predisposition genes with the intent of gross duplications. This method revealed that most gross duplica- informing their classifications. tions in the investigated genes occurred in tandem and resulted in a Methods: The DNA breakpoint assay (DBA) is a custom, paired- pathogenic classification, which helps to secure the necessary end, next-generation sequencing (NGS) method designed to treatment options for their carriers. capture and detect deep-intronic DNA breakpoints in gross duplications in BRCA1, BRCA2, ATM, CDH1, PALB2, and CHEK2. Genetics in Medicine (2019) 21:683–693; https://doi.org/10.1038/s41436- Results: DBA allowed us to ascertain breakpoints for 44 unique 018-0092-7 gross duplications from 147 probands. -
VISPA: a Computational Pipeline for the Identification and Analysis Of
Calabria et al. Genome Medicine 2014, 6:67 http://genomemedicine.com/content/6/9/67 SOFTWARE Open Access VISPA: a computational pipeline for the identification and analysis of genomic vector integration sites Andrea Calabria1†, Simone Leo2,3†, Fabrizio Benedicenti1, Daniela Cesana1, Giulio Spinozzi1,4, Massimilano Orsini2, Stefania Merella5, Elia Stupka5, Gianluigi Zanetti2 and Eugenio Montini1* Abstract The analysis of the genomic distribution of viral vector genomic integration sites is a key step in hematopoietic stem cell-based gene therapy applications, allowing to assess both the safety and the efficacy of the treatment and to study the basic aspects of hematopoiesis and stem cell biology. Identifying vector integration sites requires ad-hoc bioinformatics tools with stringent requirements in terms of computational efficiency, flexibility, and usability. We developed VISPA (Vector Integration Site Parallel Analysis), a pipeline for automated integration site identification and annotation based on a distributed environment with a simple Galaxy web interface. VISPA was successfully used for the bioinformatics analysis of the follow-up of two lentiviral vector-based hematopoietic stem-cell gene therapy clinical trials. Our pipeline provides a reliable and efficient tool to assess the safety and efficacy of integrating vectors in clinical settings. Background the proximity of the vector’sintegrationsite(IS),a Viral vectors, due to their ability to permanently integrate phenomenon known as insertional mutagenesis (IM) in a target genome, are used to achieve the stable genetic [1,9-12]. The identification of ISs on leukemic cells from modification of therapeutically relevant cells and their GT patients and preclinical models allowed identifying progeny. In particular, γ-retroviral (γ-RVs) and lentiviral the causes of IM and tracking the evolution of the (LVs) vectors are the preferred choice for hematopoietic malignant clone over time [11-16]. -
Chr21 Protein-Protein Interactions: Enrichment in Products Involved in Intellectual Disabilities, Autism and Late Onset Alzheimer Disease
bioRxiv preprint doi: https://doi.org/10.1101/2019.12.11.872606; this version posted December 12, 2019. 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. Chr21 protein-protein interactions: enrichment in products involved in intellectual disabilities, autism and Late Onset Alzheimer Disease Julia Viard1,2*, Yann Loe-Mie1*, Rachel Daudin1, Malik Khelfaoui1, Christine Plancon2, Anne Boland2, Francisco Tejedor3, Richard L. Huganir4, Eunjoon Kim5, Makoto Kinoshita6, Guofa Liu7, Volker Haucke8, Thomas Moncion9, Eugene Yu10, Valérie Hindie9, Henri Bléhaut11, Clotilde Mircher12, Yann Herault13,14,15,16,17, Jean-François Deleuze2, Jean- Christophe Rain9, Michel Simonneau1, 18, 19, 20** and Aude-Marie Lepagnol- Bestel1** 1 Centre Psychiatrie & Neurosciences, INSERM U894, 75014 Paris, France 2 Laboratoire de génomique fonctionnelle, CNG, CEA, Evry 3 Instituto de Neurociencias CSIC-UMH, Universidad Miguel Hernandez-Campus de San Juan 03550 San Juan (Alicante), Spain 4 Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA 5 Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon 34141, Republic of Korea 6 Department of Molecular Biology, Division of Biological Science, Nagoya University Graduate School of Science, Furo, Chikusa, Nagoya, Japan 7 Department of Biological Sciences, University of Toledo, Toledo, OH, 43606, USA 8 Leibniz Forschungsinstitut für Molekulare Pharmakologie -
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. -
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cells Review Novel Approaches for Identifying the Molecular Background of Schizophrenia Arkadiy K. Golov 1,2,*, Nikolay V. Kondratyev 1 , George P. Kostyuk 3 and Vera E. Golimbet 1 1 Mental Health Research Center, 34 Kashirskoye shosse, 115522 Moscow, Russian; [email protected] (N.V.K.); [email protected] (V.E.G.) 2 Institute of Gene Biology, Russian Academy of Sciences, 34/5 Vavilova Street, 119334 Moscow, Russian 3 Alekseev Psychiatric Clinical Hospital No. 1, 2 Zagorodnoye shosse, 115191 Moscow, Russian; [email protected] * Correspondence: [email protected] Received: 5 November 2019; Accepted: 16 January 2020; Published: 18 January 2020 Abstract: Recent advances in psychiatric genetics have led to the discovery of dozens of genomic loci associated with schizophrenia. However, a gap exists between the detection of genetic associations and understanding the underlying molecular mechanisms. This review describes the basic approaches used in the so-called post-GWAS studies to generate biological interpretation of the existing population genetic data, including both molecular (creation and analysis of knockout animals, exploration of the transcriptional effects of common variants in human brain cells) and computational (fine-mapping of causal variability, gene set enrichment analysis, partitioned heritability analysis) methods. The results of the crucial studies, in which these approaches were used to uncover the molecular and neurobiological basis of the disease, are also reported. Keywords: schizophrenia; GWAS; causal genetic variants; enhancers; brain epigenomics; genome/epigenome editing 1. Introduction Schizophrenia is a severe mental illness that affects between 0.5% and 0.7% of the human population [1]. Both environmental and genetic factors are thought to be involved in its pathogenesis, with genetic factors playing a key role in disease risk, as the heritability of schizophrenia is estimated to be 70–85% [2,3]. -
INTELLIGENT MEDICINE the Wings of Global Health
INTELLIGENT MEDICINE The Wings of Global Health AUTHOR INFORMATION PACK TABLE OF CONTENTS XXX . • Description p.1 • Editorial Board p.2 • Guide for Authors p.6 ISSN: 2667-1026 DESCRIPTION . Intelligent Medicine is an open access, peer-reviewed journal sponsored and owned by the Chinese Medical Association and designated to publish high-quality research and application in the field of medical-industrial crossover concerning the internet technology, artificial intelligence (AI), data science, medical information, and intelligent devices in the clinical medicine, biomedicine, and public health. Intelligent Medicine appreciates the innovation, pioneering, science, and application, encourages the unique perspectives and suggestions. The topics focus on the computer and data science enabled intelligent medicine, including while not limited to the clinical decision making, computer-assisted surgery, telemedicine, drug development, image analysis and computation, and health management. The journal sets academic columns according to the different disciplines and hotspots. Article types include Research Article: These articles are expected to be original, innovative, and significant, including medical and algorithmic research. The real-world medical research rules and clinical assessment of the usefulness and reliability are recommended for those medical research. The full text is about 6,000 words, with structured abstract of 300 words including Background, Methods, Results, and Conclusion. Editorial: Written by the Editor-in-Chief, Associate Editors, editorial board members, or prestigious invited scientists and policy makers on a broad range of topics from science to policy. Review: Extensive reviews of the recent progress in specific areas of science, involving historical reviews, recent advances made by scientists internationally, and perspective for future development; the full text is about 5,000~6,000 words. -
Developing and Implementing an Institute-Wide Data Sharing Policy Stephanie OM Dyke and Tim JP Hubbard*
Dyke and Hubbard Genome Medicine 2011, 3:60 http://genomemedicine.com/content/3/9/60 CORRESPONDENCE Developing and implementing an institute-wide data sharing policy Stephanie OM Dyke and Tim JP Hubbard* Abstract HapMap Project [7], also decided to follow HGP prac- tices and to share data publicly as a resource for the The Wellcome Trust Sanger Institute has a strong research community before academic publications des- reputation for prepublication data sharing as a result crib ing analyses of the data sets had been prepared of its policy of rapid release of genome sequence (referred to as prepublication data sharing). data and particularly through its contribution to the Following the success of the first phase of the HGP [8] Human Genome Project. The practicalities of broad and of these other projects, the principles of rapid data data sharing remain largely uncharted, especially to release were reaffirmed and endorsed more widely at a cover the wide range of data types currently produced meeting of genomics funders, scientists, public archives by genomic studies and to adequately address and publishers in Fort Lauderdale in 2003 [9]. Meanwhile, ethical issues. This paper describes the processes the Organisation for Economic Co-operation and and challenges involved in implementing a data Develop ment (OECD) Committee on Scientific and sharing policy on an institute-wide scale. This includes Tech nology Policy had established a working group on questions of governance, practical aspects of applying issues of access to research information [10,11], which principles to diverse experimental contexts, building led to a Declaration on access to research data from enabling systems and infrastructure, incentives and public funding [12], and later to a set of OECD guidelines collaborative issues. -
Cancer Genome Interpreter Annotates the Biological and Clinical Relevance of Tumor Alterations David Tamborero1,2, Carlota Rubio-Perez1, Jordi Deu-Pons1,2, Michael P
Tamborero et al. Genome Medicine (2018) 10:25 https://doi.org/10.1186/s13073-018-0531-8 DATABASE Open Access Cancer Genome Interpreter annotates the biological and clinical relevance of tumor alterations David Tamborero1,2, Carlota Rubio-Perez1, Jordi Deu-Pons1,2, Michael P. Schroeder1,3, Ana Vivancos4, Ana Rovira5,6, Ignasi Tusquets5,6,7, Joan Albanell5,6,8, Jordi Rodon4, Josep Tabernero4, Carmen de Torres9, Rodrigo Dienstmann4, Abel Gonzalez-Perez1,2 and Nuria Lopez-Bigas1,2,10* Abstract While tumor genome sequencing has become widely available in clinical and research settings, the interpretation of tumor somatic variants remains an important bottleneck. Here we present the Cancer Genome Interpreter, a versatile platform that automates the interpretation of newly sequenced cancer genomes, annotating the potential of alterations detected in tumors to act as drivers and their possible effect on treatment response. The results are organized in different levels of evidence according to current knowledge, which we envision can support a broad range of oncology use cases. The resource is publicly available at http://www.cancergenomeinterpreter.org. Background to systematically identify genes involved in tumorigen- The accumulation of so-called “driver” genomic alter- esis through the detection of signals of positive selection ations confers on cells tumorigenic capabilities [1]. in their alteration patterns across tumors of some two Thousands of tumor genomes are sequenced around the dozen malignancies [3–6]. However, many of the som- world every year for both research and clinical purposes. atic variants detected in tumors, even those in cancer In some cases the whole genome is sequenced while in genes, still have uncertain significance and thus it is not others the focus is on the exome or a panel of selected clear whether or not they are relevant for tumorigenesis. -
(P -Value<0.05, Fold Change≥1.4), 4 Vs. 0 Gy Irradiation
Table S1: Significant differentially expressed genes (P -Value<0.05, Fold Change≥1.4), 4 vs. 0 Gy irradiation Genbank Fold Change P -Value Gene Symbol Description Accession Q9F8M7_CARHY (Q9F8M7) DTDP-glucose 4,6-dehydratase (Fragment), partial (9%) 6.70 0.017399678 THC2699065 [THC2719287] 5.53 0.003379195 BC013657 BC013657 Homo sapiens cDNA clone IMAGE:4152983, partial cds. [BC013657] 5.10 0.024641735 THC2750781 Ciliary dynein heavy chain 5 (Axonemal beta dynein heavy chain 5) (HL1). 4.07 0.04353262 DNAH5 [Source:Uniprot/SWISSPROT;Acc:Q8TE73] [ENST00000382416] 3.81 0.002855909 NM_145263 SPATA18 Homo sapiens spermatogenesis associated 18 homolog (rat) (SPATA18), mRNA [NM_145263] AA418814 zw01a02.s1 Soares_NhHMPu_S1 Homo sapiens cDNA clone IMAGE:767978 3', 3.69 0.03203913 AA418814 AA418814 mRNA sequence [AA418814] AL356953 leucine-rich repeat-containing G protein-coupled receptor 6 {Homo sapiens} (exp=0; 3.63 0.0277936 THC2705989 wgp=1; cg=0), partial (4%) [THC2752981] AA484677 ne64a07.s1 NCI_CGAP_Alv1 Homo sapiens cDNA clone IMAGE:909012, mRNA 3.63 0.027098073 AA484677 AA484677 sequence [AA484677] oe06h09.s1 NCI_CGAP_Ov2 Homo sapiens cDNA clone IMAGE:1385153, mRNA sequence 3.48 0.04468495 AA837799 AA837799 [AA837799] Homo sapiens hypothetical protein LOC340109, mRNA (cDNA clone IMAGE:5578073), partial 3.27 0.031178378 BC039509 LOC643401 cds. [BC039509] Homo sapiens Fas (TNF receptor superfamily, member 6) (FAS), transcript variant 1, mRNA 3.24 0.022156298 NM_000043 FAS [NM_000043] 3.20 0.021043295 A_32_P125056 BF803942 CM2-CI0135-021100-477-g08 CI0135 Homo sapiens cDNA, mRNA sequence 3.04 0.043389246 BF803942 BF803942 [BF803942] 3.03 0.002430239 NM_015920 RPS27L Homo sapiens ribosomal protein S27-like (RPS27L), mRNA [NM_015920] Homo sapiens tumor necrosis factor receptor superfamily, member 10c, decoy without an 2.98 0.021202829 NM_003841 TNFRSF10C intracellular domain (TNFRSF10C), mRNA [NM_003841] 2.97 0.03243901 AB002384 C6orf32 Homo sapiens mRNA for KIAA0386 gene, partial cds. -
Macrophage Activation JUNB Is a Key Transcriptional Modulator Of
JUNB Is a Key Transcriptional Modulator of Macrophage Activation Mary F. Fontana, Alyssa Baccarella, Nidhi Pancholi, Miles A. Pufall, De'Broski R. Herbert and Charles C. Kim This information is current as of October 2, 2021. J Immunol 2015; 194:177-186; Prepublished online 3 December 2014; doi: 10.4049/jimmunol.1401595 http://www.jimmunol.org/content/194/1/177 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2014/12/03/jimmunol.140159 Material 5.DCSupplemental References This article cites 40 articles, 7 of which you can access for free at: http://www.jimmunol.org/content/194/1/177.full#ref-list-1 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 by guest on October 2, 2021 • Fast Publication! 4 weeks from acceptance to publication *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. The Journal of Immunology JUNB Is a Key Transcriptional Modulator of Macrophage Activation Mary F. Fontana,* Alyssa Baccarella,* Nidhi Pancholi,* Miles A. -
Accelerating Matchmaking of Novel Dysmorphology Syndromes Through Clinical and Genomic Characterization of a Large Cohort
ORIGINAL RESEARCH ARTICLE © American College of Medical Genetics and Genomics Accelerating matchmaking of novel dysmorphology syndromes through clinical and genomic characterization of a large cohort Ranad Shaheen, PhD1, Nisha Patel, PhD1, Hanan Shamseldin, MSc1, Fatema Alzahrani, BSc1, Ruah Al-Yamany, MD1, Agaadir ALMoisheer, MSc1, Nour Ewida, BSc1, Shamsa Anazi, MSc1, Maha Alnemer, MD2, Mohamed Elsheikh, MD3, Khaled Alfaleh, MD3,4, Muneera Alshammari, MD4, Amal Alhashem, MD5, Abdullah A. Alangari, MD4, Mustafa A. Salih, MD4, Martin Kircher, MD6, Riza M. Daza, PhD6, Niema Ibrahim, BSc1, Salma M. Wakil, PhD1, Ahmed Alaqeel, MD7, Ikhlas Altowaijri, MD7, Jay Shendure, MD, PhD6, Amro Al-Habib, MD7, Eissa Faqieh, MD8 and Fowzan S. Alkuraya, MD1,9 Purpose: Dysmorphology syndromes are among the most common and C3ORF17). A significant minority of the phenotypes (6/31, 19%), referrals to clinical genetics specialists. Inability to match the dysmor- however, were caused by genes known to cause Mendelian pheno- phology pattern to a known syndrome can pose a major diagnostic chal- types, thus expanding the phenotypic spectrum of the diseases linked lenge. With an aim to accelerate the establishment of new syndromes to these genes. The conspicuous inheritance pattern and the highly and their genetic etiology, we describe our experience with multiplex specific phenotypes appear to have contributed to the high yield consanguineous families that appeared to represent novel autosomal (90%) of plausible molecular diagnoses in our study cohort. recessive dysmorphology syndromes at the time of evaluation. Conclusion: Reporting detailed clinical and genomic analysis of Methods: Combined autozygome/exome analysis of multiplex a large series of apparently novel dysmorphology syndromes will consanguineous families with apparently novel dysmorphology syn- likely lead to a trend to accelerate the establishment of novel syn- dromes.