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Genetic Analysis of Retinopathy in Type 1 Diabetes
Genetic Analysis of Retinopathy in Type 1 Diabetes by Sayed Mohsen Hosseini A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Institute of Medical Science University of Toronto © Copyright by S. Mohsen Hosseini 2014 Genetic Analysis of Retinopathy in Type 1 Diabetes Sayed Mohsen Hosseini Doctor of Philosophy Institute of Medical Science University of Toronto 2014 Abstract Diabetic retinopathy (DR) is a leading cause of blindness worldwide. Several lines of evidence suggest a genetic contribution to the risk of DR; however, no genetic variant has shown convincing association with DR in genome-wide association studies (GWAS). To identify common polymorphisms associated with DR, meta-GWAS were performed in three type 1 diabetes cohorts of White subjects: Diabetes Complications and Control Trial (DCCT, n=1304), Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR, n=603) and Renin-Angiotensin System Study (RASS, n=239). Severe (SDR) and mild (MDR) retinopathy outcomes were defined based on repeated fundus photographs in each study graded for retinopathy severity on the Early Treatment Diabetic Retinopathy Study (ETDRS) scale. Multivariable models accounted for glycemia (measured by A1C), diabetes duration and other relevant covariates in the association analyses of additive genotypes with SDR and MDR. Fixed-effects meta- analysis was used to combine the results of GWAS performed separately in WESDR, ii RASS and subgroups of DCCT, defined by cohort and treatment group. Top association signals were prioritized for replication, based on previous supporting knowledge from the literature, followed by replication in three independent white T1D studies: Genesis-GeneDiab (n=502), Steno (n=936) and FinnDiane (n=2194). -
Dynamics of Gene Silencing During X Inactivation Using Allele-Specific RNA-Seq Hendrik Marks1*, Hindrik H
Marks et al. Genome Biology (2015) 16:149 DOI 10.1186/s13059-015-0698-x RESEARCH Open Access Dynamics of gene silencing during X inactivation using allele-specific RNA-seq Hendrik Marks1*, Hindrik H. D. Kerstens1, Tahsin Stefan Barakat3, Erik Splinter4, René A. M. Dirks1, Guido van Mierlo1, Onkar Joshi1, Shuang-Yin Wang1, Tomas Babak5, Cornelis A. Albers2, Tüzer Kalkan6, Austin Smith6, Alice Jouneau7, Wouter de Laat4, Joost Gribnau3 and Hendrik G. Stunnenberg1* Abstract Background: During early embryonic development, one of the two X chromosomes in mammalian female cells is inactivated to compensate for a potential imbalance in transcript levels with male cells, which contain a single X chromosome. Here, we use mouse female embryonic stem cells (ESCs) with non-random X chromosome inactivation (XCI) and polymorphic X chromosomes to study the dynamics of gene silencing over the inactive X chromosome by high-resolution allele-specific RNA-seq. Results: Induction of XCI by differentiation of female ESCs shows that genes proximal to the X-inactivation center are silenced earlier than distal genes, while lowly expressed genes show faster XCI dynamics than highly expressed genes. The active X chromosome shows a minor but significant increase in gene activity during differentiation, resulting in complete dosage compensation in differentiated cell types. Genes escaping XCI show little or no silencing during early propagation of XCI. Allele-specific RNA-seq of neural progenitor cells generated from the female ESCs identifies three regions distal to the X-inactivation center that escape XCI. These regions, which stably escape during propagation and maintenance of XCI, coincide with topologically associating domains (TADs) as present in the female ESCs. -
Chromosomal Aberrations in Head and Neck Squamous Cell Carcinomas in Norwegian and Sudanese Populations by Array Comparative Genomic Hybridization
825-843 12/9/08 15:31 Page 825 ONCOLOGY REPORTS 20: 825-843, 2008 825 Chromosomal aberrations in head and neck squamous cell carcinomas in Norwegian and Sudanese populations by array comparative genomic hybridization ERIC ROMAN1,2, LEONARDO A. MEZA-ZEPEDA3, STINE H. KRESSE3, OLA MYKLEBOST3,4, ENDRE N. VASSTRAND2 and SALAH O. IBRAHIM1,2 1Department of Biomedicine, Faculty of Medicine and Dentistry, University of Bergen, Jonas Lies vei 91; 2Department of Oral Sciences - Periodontology, Faculty of Medicine and Dentistry, University of Bergen, Årstadveien 17, 5009 Bergen; 3Department of Tumor Biology, Institute for Cancer Research, Rikshospitalet-Radiumhospitalet Medical Center, Montebello, 0310 Oslo; 4Department of Molecular Biosciences, University of Oslo, Blindernveien 31, 0371 Oslo, Norway Received January 30, 2008; Accepted April 29, 2008 DOI: 10.3892/or_00000080 Abstract. We used microarray-based comparative genomic logical parameters showed little correlation, suggesting an hybridization to explore genome-wide profiles of chromosomal occurrence of gains/losses regardless of ethnic differences and aberrations in 26 samples of head and neck cancers compared clinicopathological status between the patients from the two to their pair-wise normal controls. The samples were obtained countries. Our findings indicate the existence of common from Sudanese (n=11) and Norwegian (n=15) patients. The gene-specific amplifications/deletions in these tumors, findings were correlated with clinicopathological variables. regardless of the source of the samples or attributed We identified the amplification of 41 common chromosomal carcinogenic risk factors. regions (harboring 149 candidate genes) and the deletion of 22 (28 candidate genes). Predominant chromosomal alterations Introduction that were observed included high-level amplification at 1q21 (harboring the S100A gene family) and 11q22 (including Head and neck squamous cell carcinoma (HNSCC), including several MMP family members). -
The Popeye Domain Containing Protein Family E a Novel Class of Camp Effectors with Important Functions in Multiple Tissues
Progress in Biophysics and Molecular Biology xxx (2016) 1e9 Contents lists available at ScienceDirect Progress in Biophysics and Molecular Biology journal homepage: www.elsevier.com/locate/pbiomolbio The Popeye domain containing protein family e A novel class of cAMP effectors with important functions in multiple tissues * Roland F.R. Schindler, Thomas Brand Heart Science Centre, National Heart and Lung Institute (NHLI), Imperial College London, United Kingdom article info abstract Article history: Popeye domain containing (Popdc) proteins are a unique family, which combine several different Received 16 September 2015 properties and functions in a surprisingly complex fashion. They are expressed in multiple tissues and Received in revised form cell types, present in several subcellular compartments, interact with different classes of proteins, and 3 December 2015 are associated with a variety of physiological and pathophysiological processes. Moreover, Popdc proteins Accepted 4 January 2016 bind the second messenger cAMP with high affinity and it is thought that they act as a novel class of Available online xxx cAMP effector proteins. Here, we will review the most important findings about the Popdc family, which accumulated since its discovery about 15 years ago. We will be focussing on Popdc protein interaction Keywords: Popeye domain containing genes and function in striated muscle tissue. However, as a full picture only emerges if all aspects are taken into cAMP account, we will also describe what is currently known about the role of Popdc proteins in epithelial cells Proteineprotein interaction and in various types of cancer, and discuss these findings with regard to their relevance for cardiac and Ion channel skeletal muscle. -
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. -
A Private 16Q24.2Q24.3 Microduplication in a Boy with Intellectual Disability, Speech Delay and Mild Dysmorphic Features
G C A T T A C G G C A T genes Article A Private 16q24.2q24.3 Microduplication in a Boy with Intellectual Disability, Speech Delay and Mild Dysmorphic Features Orazio Palumbo * , Pietro Palumbo , Ester Di Muro, Luigia Cinque, Antonio Petracca, Massimo Carella and Marco Castori Division of Medical Genetics, Fondazione IRCCS-Casa Sollievo della Sofferenza, San Giovanni Rotondo, 71013 Foggia, Italy; [email protected] (P.P.); [email protected] (E.D.M.); [email protected] (L.C.); [email protected] (A.P.); [email protected] (M.C.); [email protected] (M.C.) * Correspondence: [email protected]; Tel.: +39-088-241-6350 Received: 5 June 2020; Accepted: 24 June 2020; Published: 26 June 2020 Abstract: No data on interstitial microduplications of the 16q24.2q24.3 chromosome region are available in the medical literature and remain extraordinarily rare in public databases. Here, we describe a boy with a de novo 16q24.2q24.3 microduplication at the Single Nucleotide Polymorphism (SNP)-array analysis spanning ~2.2 Mb and encompassing 38 genes. The patient showed mild-to-moderate intellectual disability, speech delay and mild dysmorphic features. In DECIPHER, we found six individuals carrying a “pure” overlapping microduplication. Although available data are very limited, genomic and phenotype comparison of our and previously annotated patients suggested a potential clinical relevance for 16q24.2q24.3 microduplication with a variable and not (yet) recognizable phenotype predominantly affecting cognition. Comparing the cytogenomic data of available individuals allowed us to delineate the smallest region of overlap involving 14 genes. Accordingly, we propose ANKRD11, CDH15, and CTU2 as candidate genes for explaining the related neurodevelopmental manifestations shared by these patients. -
Análise Integrativa De Perfis Transcricionais De Pacientes Com
UNIVERSIDADE DE SÃO PAULO FACULDADE DE MEDICINA DE RIBEIRÃO PRETO PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Ribeirão Preto – 2012 ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Tese apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo para obtenção do título de Doutor em Ciências. Área de Concentração: Genética Orientador: Prof. Dr. Eduardo Antonio Donadi Co-orientador: Prof. Dr. Geraldo A. S. Passos Ribeirão Preto – 2012 AUTORIZO A REPRODUÇÃO E DIVULGAÇÃO TOTAL OU PARCIAL DESTE TRABALHO, POR QUALQUER MEIO CONVENCIONAL OU ELETRÔNICO, PARA FINS DE ESTUDO E PESQUISA, DESDE QUE CITADA A FONTE. FICHA CATALOGRÁFICA Evangelista, Adriane Feijó Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. Ribeirão Preto, 2012 192p. Tese de Doutorado apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo. Área de Concentração: Genética. Orientador: Donadi, Eduardo Antonio Co-orientador: Passos, Geraldo A. 1. Expressão gênica – microarrays 2. Análise bioinformática por module maps 3. Diabetes mellitus tipo 1 4. Diabetes mellitus tipo 2 5. Diabetes mellitus gestacional FOLHA DE APROVAÇÃO ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. -
Ggbio: Visualization Toolkits for Genomic Data
ggbio: visualization toolkits for genomic data 1 Tengfei Yin [email protected] May 19, 2021 Contents 1 Getting started............................4 1.1 Citation.................................4 1.2 Introduction ..............................4 2 Case study: building your first tracks..............6 2.1 Add an ideogram track ........................6 2.2 Add a gene model track .......................7 2.2.1 Introduction ...........................7 2.2.2 Make gene model from OrganismDb object ............7 2.2.3 Make gene model from TxDb object ................ 11 2.2.4 Make gene model from EnsDb object ............... 12 2.2.5 Make gene model from GRangesList object ............ 16 2.3 Add a reference track ........................ 19 2.3.1 Semantic zoom.......................... 19 2.4 Add an alignment track ....................... 20 2.5 Add a variants track ......................... 25 2.6 Building your tracks ......................... 28 3 Simple navigation .......................... 30 4 Overview plots............................ 32 4.1 how to make circular plots ...................... 32 4.1.1 Introduction ........................... 32 4.1.2 Buidling circular plot layer by layer................. 32 2 ggbio:visualization toolkits for genomic data 4.1.3 Complex arragnment of plots ................... 39 4.2 How to make grandlinear plots ................... 41 4.2.1 Introduction ........................... 41 4.2.2 Corrdinate genome ........................ 43 4.2.3 Convenient plotGrandLinear function ............... 43 4.2.4 How to highlight some points? .................. 45 4.3 How to make stacked karyogram overview plots ......... 46 4.3.1 Introduction ........................... 46 4.3.2 Create karyogram temlate .................... 46 4.3.3 Add data on karyogram layout................... 48 4.3.4 Add more data using layout_karyogram function .......... 51 4.3.5 More flexible layout of karyogram ................ -
SLIC-CAGE: High-Resolution Transcription Start Site Mapping Using Nanogram-Levels of Total RNA
bioRxiv preprint doi: https://doi.org/10.1101/368795; this version posted July 19, 2018. 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 4.0 International license. SLIC-CAGE: high-resolution transcription start site mapping using nanogram-levels of total RNA Nevena Cvetesic1, 2*, Harry G. Leitch1,2, Malgorzata Borkowska1,2, Ferenc Müller3, Piero Carninci4,5, Petra Hajkova1,2 and Boris Lenhard1,2,6* 1Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London W12 0NN, UK 2MRC London Institute of Medical Sciences, London W12 0NN, UK 3Institute of Cancer and Genomic Sciences, University of Birmingham, Edgbaston B15 2TT, UK 4RIKEN Center for Life Science Technologies, Division of Genomic Technologies, Yokohama City, Kanagawa 230-0045, Japan 5RIKEN Omics Science Center, Yokohama City, Kanagawa 230-0045, Japan 6Sars International Centre for Marine Molecular Biology, University of Bergen, N-5008 Bergen, Norway *Correspondence to: Nevena Cvetesic Institute of Clinical Sciences, Faculty of Medicine, Imperial College London and MRC London Institute of Medical Sciences, London, W12 0NN, UK e-mail: [email protected] Boris Lenhard Institute of Clinical Sciences, Faculty of Medicine, Imperial College London and MRC London Institute of Medical Sciences, London, W12 0NN, UK e-mail: [email protected] Running title: TSS discovery using Super-Low Input Carrier-CAGE Keywords: cap analysis of gene expression; low input material; degradable nucleic acid carrier; promoters; gene expression profiling 1 bioRxiv preprint doi: https://doi.org/10.1101/368795; this version posted July 19, 2018. -
Probabilistic Models for Collecting, Analyzing, and Modeling Expression Data
Probabilistic Models for Collecting, Analyzing, and Modeling Expression Data Hai-Son Phuoc Le May 2013 CMU-ML-13-101 Probabilistic Models for Collecting, Analyzing, and Modeling Expression Data Hai-Son Phuoc Le May 2013 CMU-ML-13-101 Machine Learning Department School of Computer Science Carnegie Mellon University Thesis Committee Ziv Bar-Joseph, Chair Christopher Langmead Roni Rosenfeld Quaid Morris Submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy. Copyright @ 2013 Hai-Son Le This research was sponsored by the National Institutes of Health under grant numbers 5U01HL108642 and 1R01GM085022, the National Science Foundation under grant num- bers DBI0448453 and DBI0965316, and the Pittsburgh Life Sciences Greenhouse. The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies, either expressed or implied, of any sponsoring institution, the U.S. government or any other entity. Keywords: genomics, gene expression, gene regulation, microarray, RNA-Seq, transcriptomics, error correction, comparative genomics, regulatory networks, cross-species, expression database, Gene Expression Omnibus, GEO, orthologs, microRNA, target prediction, Dirichlet Process, Indian Buffet Process, hidden Markov model, immune response, cancer. To Mom and Dad. i Abstract Advances in genomics allow researchers to measure the complete set of transcripts in cells. These transcripts include messenger RNAs (which encode for proteins) and microRNAs, short RNAs that play an important regulatory role in cellular networks. While this data is a great resource for reconstructing the activity of networks in cells, it also presents several computational challenges. These challenges include the data collection stage which often results in incomplete and noisy measurement, developing methods to integrate several experiments within and across species, and designing methods that can use this data to map the interactions and networks that are activated in specific conditions. -
Precise and Sustained Gene Silencing in CD4+ Cells Using Designer Epigenome Modifiers As a Therapeutic Approach to Treat HIV Infection
Precise and sustained gene silencing in CD4+ cells using designer epigenome modifiers as a therapeutic approach to treat HIV infection Inaugural-Dissertation to obtain the Doctoral Degree Faculty of Biology, Albert-Ludwigs-Universität Freiburg im Breisgau presented by Tafadzwa Mlambo born in Harare, Zimbabwe Freiburg im Breisgau February 2018 Dekanin: Prof. Dr. Bettina Warscheid Promotionsvorsitzender: Prof. Dr. Andreas Hiltbrunner Betreuer der Arbeit: Dr. Claudio Mussolino Referent: Prof. Dr. Toni Cathomen Ko-Referent: Prof. Dr. Peter Stäheli Drittprüfer: Dr. Giorgos Pyrowolakis Datum der mündlichen Prüfung: 27.04.2018 iii Table of Contents TABLE OF CONTENTS TABLE OF CONTENTS III ABSTRACT VIII 1. INTRODUCTION 11 1.1 HIV BURDEN AND EPIDEMIOLOGY 11 1.2 HIV LIFE CYCLE AND TROPISM 12 1.3 HIV TREATMENT 14 1.4 CCR5 AND CXCR4 AS TARGETS OF ANTI-HIV THERAPY 15 1.5 DESIGNER NUCLEASE TECHNOLOGY 17 1.5.1 Zinc finger nucleases 19 1.5.2 Transcription activator-like effector nucleases 20 1.5.3 RNA-guided endonucleases 21 1.6 HIV GENE THERAPY 22 1.7 OFF-TARGET EFFECTS 25 1.8 DELIVERY 27 1.9 EPIGENETIC REGULATION 30 1.9.1 Gene expression 30 1.9.2 Transcriptional regulation of gene expression 31 1.9.3 Targeted transcription activation 32 1.9.4 Targeted transcription repression 33 1.9.5 Epigenome editing 36 1.9.6 DNA methylation 38 iv Table of Contents 1.9.7 Designer epigenome modifiers 40 1.10 AIM AND OBJECTIVES OF PHD THESIS 42 2. MATERIALS AND METHODS 44 2.1 STANDARD MOLECULAR BIOLOGY METHODS 44 2.1.1 Restriction digest 44 2.1.2 Ligation 44 2.1.3 Polymerase -
Transcriptome Signatures of Canine Mammary Gland Tumors and Its Comparison to Human Breast Cancers
cancers Article Transcriptome Signatures of Canine Mammary Gland Tumors and Its Comparison to Human Breast Cancers Kang-Hoon Lee 1,†, Hyoung-Min Park 1,†, Keun-Hong Son 2, Tae-Jin Shin 1 and Je-Yoel Cho 1,* 1 Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, School of Veterinary Medicine, Seoul National University, Seoul 08826, Korea; [email protected] (K.-H.L.); [email protected] (H.-M.P.); [email protected] (T.-J.S.) 2 Department of Microbiology, College of Natural Sciences, Dankook University, Cheonan 31116, Korea; [email protected] * Correspondence: [email protected]; Tel.: +82-02-800-1268 † These authors contributed equally to this work. Received: 8 August 2018; Accepted: 4 September 2018; Published: 7 September 2018 Abstract: Breast cancer (BC)/mammary gland carcinoma (MGC) is the most frequently diagnosed and leading cause of cancer-related mortality in both women and canines. To better understand both canine MGC and human BC-specific genes, we sequenced RNAs obtained from eight pairs of carcinomas and adjacent normal tissues in dogs. By comprehensive transcriptome analysis, 351 differentially expressed genes (DEGs) were identified in overall canine MGCs. Based on the DEGs, comparative analysis revealed correlation existing among the three histological subtypes of canine MGC (ductal, simple, and complex) and four molecular subtypes of human BC (HER2+, ER+, ER&HER2+, and TNBC). Eight DEGs shared by all three subtypes of canine MGCs had been previously reported as cancer-associated genes in human studies. Gene ontology and pathway analyses using the identified DEGs revealed that the biological processes of cell proliferation, adhesion, and inflammatory responses are enriched in up-regulated MGC DEGs.