Dzip1 and Fam92 Form a Ciliary Transition Zone Complex with Cell
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Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
Downloaded the “Top Edge” Version
bioRxiv preprint doi: https://doi.org/10.1101/855338; this version posted December 6, 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 4.0 International license. 1 Drosophila models of pathogenic copy-number variant genes show global and 2 non-neuronal defects during development 3 Short title: Non-neuronal defects of fly homologs of CNV genes 4 Tanzeen Yusuff1,4, Matthew Jensen1,4, Sneha Yennawar1,4, Lucilla Pizzo1, Siddharth 5 Karthikeyan1, Dagny J. Gould1, Avik Sarker1, Yurika Matsui1,2, Janani Iyer1, Zhi-Chun Lai1,2, 6 and Santhosh Girirajan1,3* 7 8 1. Department of Biochemistry and Molecular Biology, Pennsylvania State University, 9 University Park, PA 16802 10 2. Department of Biology, Pennsylvania State University, University Park, PA 16802 11 3. Department of Anthropology, Pennsylvania State University, University Park, PA 16802 12 4 contributed equally to work 13 14 *Correspondence: 15 Santhosh Girirajan, MBBS, PhD 16 205A Life Sciences Building 17 Pennsylvania State University 18 University Park, PA 16802 19 E-mail: [email protected] 20 Phone: 814-865-0674 21 1 bioRxiv preprint doi: https://doi.org/10.1101/855338; this version posted December 6, 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 4.0 International license. 22 ABSTRACT 23 While rare pathogenic copy-number variants (CNVs) are associated with both neuronal and non- 24 neuronal phenotypes, functional studies evaluating these regions have focused on the molecular 25 basis of neuronal defects. -
The Genetics of Bipolar Disorder
Molecular Psychiatry (2008) 13, 742–771 & 2008 Nature Publishing Group All rights reserved 1359-4184/08 $30.00 www.nature.com/mp FEATURE REVIEW The genetics of bipolar disorder: genome ‘hot regions,’ genes, new potential candidates and future directions A Serretti and L Mandelli Institute of Psychiatry, University of Bologna, Bologna, Italy Bipolar disorder (BP) is a complex disorder caused by a number of liability genes interacting with the environment. In recent years, a large number of linkage and association studies have been conducted producing an extremely large number of findings often not replicated or partially replicated. Further, results from linkage and association studies are not always easily comparable. Unfortunately, at present a comprehensive coverage of available evidence is still lacking. In the present paper, we summarized results obtained from both linkage and association studies in BP. Further, we indicated new potential interesting genes, located in genome ‘hot regions’ for BP and being expressed in the brain. We reviewed published studies on the subject till December 2007. We precisely localized regions where positive linkage has been found, by the NCBI Map viewer (http://www.ncbi.nlm.nih.gov/mapview/); further, we identified genes located in interesting areas and expressed in the brain, by the Entrez gene, Unigene databases (http://www.ncbi.nlm.nih.gov/entrez/) and Human Protein Reference Database (http://www.hprd.org); these genes could be of interest in future investigations. The review of association studies gave interesting results, as a number of genes seem to be definitively involved in BP, such as SLC6A4, TPH2, DRD4, SLC6A3, DAOA, DTNBP1, NRG1, DISC1 and BDNF. -
Genome-Wide Screen for Differentially Methylated Long Noncoding Rnas
OPEN Oncogene (2017) 36, 6446–6461 www.nature.com/onc ORIGINAL ARTICLE Genome-wide screen for differentially methylated long noncoding RNAs identifies Esrp2 and lncRNA Esrp2-as regulated by enhancer DNA methylation with prognostic relevance for human breast cancer K Heilmann, R Toth, C Bossmann, K Klimo, C Plass and C Gerhauser The majority of long noncoding RNAs (lncRNAs) is still poorly characterized with respect to function, interactions with protein- coding genes, and mechanisms that regulate their expression. As for protein-coding RNAs, epigenetic deregulation of lncRNA expression by alterations in DNA methylation might contribute to carcinogenesis. To provide genome-wide information on lncRNAs aberrantly methylated in breast cancer we profiled tumors of the C3(1) SV40TAg mouse model by MCIp-seq (Methylated CpG Immunoprecipitation followed by sequencing). This approach detected 69 lncRNAs differentially methylated between tumor tissue and normal mammary glands, with 26 located in antisense orientation of a protein-coding gene. One of the hypomethylated lncRNAs, 1810019D21Rik (now called Esrp2-antisense (as)) was identified in proximity to the epithelial splicing regulatory protein 2 (Esrp2) that is significantly elevated in C3(1) tumors. ESRPs were shown previously to have a dual role in carcinogenesis. Both gain and loss have been associated with poor prognosis in human cancers, but the mechanisms regulating expression are not known. In- depth analyses indicate that coordinate overexpression of Esrp2 and Esrp2-as inversely correlates with DNA methylation. Luciferase reporter gene assays support co-expression of Esrp2 and the major short Esrp2-as variant from a bidirectional promoter, and transcriptional regulation by methylation of a proximal enhancer. -
Download Special Issue
BioMed Research International Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 Guest Editors: Tao Huang, Lei Chen, Jiangning Song, Mingyue Zheng, Jialiang Yang, and Zhenguo Zhang Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 BioMed Research International Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 GuestEditors:TaoHuang,LeiChen,JiangningSong, Mingyue Zheng, Jialiang Yang, and Zhenguo Zhang Copyright © 2016 Hindawi Publishing Corporation. All rights reserved. This is a special issue published in “BioMed Research International.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Contents Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016 Tao Huang, Lei Chen, Jiangning Song, Mingyue Zheng, Jialiang Yang, and Zhenguo Zhang Volume 2016, Article ID 6585069, 2 pages New Trends of Digital Data Storage in DNA Pavani Yashodha De Silva and Gamage Upeksha Ganegoda Volume 2016, Article ID 8072463, 14 pages Analyzing the miRNA-Gene Networks to Mine the Important miRNAs under Skin of Human and Mouse Jianghong Wu, Husile Gong, Yongsheng Bai, and Wenguang Zhang Volume 2016, Article ID 5469371, 9 pages Differential Regulatory Analysis Based on Coexpression Network in Cancer Research Junyi -
A Systematic Genome-Wide Association Analysis for Inflammatory Bowel Diseases (IBD)
A systematic genome-wide association analysis for inflammatory bowel diseases (IBD) Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakultät der Christian-Albrechts-Universität zu Kiel vorgelegt von Dipl.-Biol. ANDRE FRANKE Kiel, im September 2006 Referent: Prof. Dr. Dr. h.c. Thomas C.G. Bosch Koreferent: Prof. Dr. Stefan Schreiber Tag der mündlichen Prüfung: Zum Druck genehmigt: der Dekan “After great pain a formal feeling comes.” (Emily Dickinson) To my wife and family ii Table of contents Abbreviations, units, symbols, and acronyms . vi List of figures . xiii List of tables . .xv 1 Introduction . .1 1.1 Inflammatory bowel diseases, a complex disorder . 1 1.1.1 Pathogenesis and pathophysiology. .2 1.2 Genetics basis of inflammatory bowel diseases . 6 1.2.1 Genetic evidence from family and twin studies . .6 1.2.2 Single nucleotide polymorphisms (SNPs) . .7 1.2.3 Linkage studies . .8 1.2.4 Association studies . 10 1.2.5 Known susceptibility genes . 12 1.2.5.1 CARD15. .12 1.2.5.2 CARD4. .15 1.2.5.3 TNF-α . .15 1.2.5.4 5q31 haplotype . .16 1.2.5.5 DLG5 . .17 1.2.5.6 TNFSF15 . .18 1.2.5.7 HLA/MHC on chromosome 6 . .19 1.2.5.8 Other proposed IBD susceptibility genes . .20 1.2.6 Animal models. 21 1.3 Aims of this study . 23 2 Methods . .24 2.1 Laboratory information management system (LIMS) . 24 2.2 Recruitment. 25 2.3 Sample preparation. 27 2.3.1 DNA extraction from blood. 27 2.3.2 Plate design . -
A Comprehensive Portrait of Cilia and Ciliopathies from a CRISPR-Based Screen for Hedgehog Signaling
bioRxiv preprint doi: https://doi.org/10.1101/156059; this version posted June 27, 2017. 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. A comprehensive portrait of cilia and ciliopathies from a CRISPR-based screen for Hedgehog signaling David K. Breslow1,2,6,*, Sascha Hoogendoorn3,6, Adam R. Kopp2, David W. Morgens4, Brandon K. Vu2, Kyuho Han4, Amy Li4, Gaelen T. Hess4, Michael C. Bassik4, James K. Chen3,5,*, Maxence V. Nachury2,* 1. Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06511 2. Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA 94305 3. Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305 4. Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305 5. Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305 6. Co-first author * Correspondence David K. Breslow [email protected] (203) 432-8280 James K. Chen [email protected] (650) 725-3582 Maxence V. Nachury [email protected] (650) 721-1999 bioRxiv preprint doi: https://doi.org/10.1101/156059; this version posted June 27, 2017. 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. -
CREB-Dependent Transcription in Astrocytes: Signalling Pathways, Gene Profiles and Neuroprotective Role in Brain Injury
CREB-dependent transcription in astrocytes: signalling pathways, gene profiles and neuroprotective role in brain injury. Tesis doctoral Luis Pardo Fernández Bellaterra, Septiembre 2015 Instituto de Neurociencias Departamento de Bioquímica i Biologia Molecular Unidad de Bioquímica y Biologia Molecular Facultad de Medicina CREB-dependent transcription in astrocytes: signalling pathways, gene profiles and neuroprotective role in brain injury. Memoria del trabajo experimental para optar al grado de doctor, correspondiente al Programa de Doctorado en Neurociencias del Instituto de Neurociencias de la Universidad Autónoma de Barcelona, llevado a cabo por Luis Pardo Fernández bajo la dirección de la Dra. Elena Galea Rodríguez de Velasco y la Dra. Roser Masgrau Juanola, en el Instituto de Neurociencias de la Universidad Autónoma de Barcelona. Doctorando Directoras de tesis Luis Pardo Fernández Dra. Elena Galea Dra. Roser Masgrau In memoriam María Dolores Álvarez Durán Abuela, eres la culpable de que haya decidido recorrer el camino de la ciencia. Que estas líneas ayuden a conservar tu recuerdo. A mis padres y hermanos, A Meri INDEX I Summary 1 II Introduction 3 1 Astrocytes: physiology and pathology 5 1.1 Anatomical organization 6 1.2 Origins and heterogeneity 6 1.3 Astrocyte functions 8 1.3.1 Developmental functions 8 1.3.2 Neurovascular functions 9 1.3.3 Metabolic support 11 1.3.4 Homeostatic functions 13 1.3.5 Antioxidant functions 15 1.3.6 Signalling functions 15 1.4 Astrocytes in brain pathology 20 1.5 Reactive astrogliosis 22 2 The transcription -
A Novel Function of YWHAZ/B-Catenin Axis in Promoting Epithelial–Mesenchymal Transition and Lung Cancer Metastasis
Published OnlineFirst August 21, 2012; DOI: 10.1158/1541-7786.MCR-12-0189 Molecular Cancer Angiogenesis, Metastasis, and the Cellular Microenvironment Research A Novel Function of YWHAZ/b-Catenin Axis in Promoting Epithelial–Mesenchymal Transition and Lung Cancer Metastasis Ching-Hsien Chen1,4, Show-Mei Chuang1, Meng-Fang Yang1, Jiunn-Wang Liao2, Sung-Liang Yu4, and Jeremy J.W. Chen1,3 Abstract YWHAZ, also known as 14-3-3zeta, has been reportedly elevated in many human tumors, including non–small cell lung carcinoma (NSCLC) but little is known about its specific contribution to lung cancer malignancy. Through a combined array-based comparative genomic hybridization and expression microarray analysis, we identified YWHAZ as a potential metastasis enhancer in lung cancer. Ectopic expression of YWHAZ on low invasive cancer cells showed enhanced cell invasion, migration in vitro, and both the tumorigenic and metastatic potentials in vivo. Gene array analysis has indicated these changes associated with an elevation of pathways relevant to epithelial–mesenchymal transition (EMT), with an increase of cell protrusions and branchings. Conversely, knockdown of YWHAZ levels with siRNA or short hairpin RNA (shRNA) in invasive cancer cells led to a reversal of EMT. We observed that high levels of YWHAZ protein are capable of activating b-catenin–mediated transcription by facilitating the accumulation of b-catenin in cytosol and nucleus. Coimmunoprecipitation assays showed a decrease of ubiquitinated b-catenin in presence of the interaction between YWHAZ and b-catenin. This interaction resulted in disassociating b-catenin from the binding of b-TrCP leading to increase b-catenin stability. Using enforced expression of dominant-negative and -positive b-catenin mutants, we confirmed that S552 phosphorylation of b-catenin increases the b-catenin/YWHAZ complex formation, which is important in pro- moting cell invasiveness and the suppression of ubiquitnated b-catenin. -
In Silico Analysis of Gene Expression Data from Bald Frontal and Haired Occipital Scalp to Identify Candidate Genes in Male Androgenetic Alopecia
Archives of Dermatological Research (2019) 311:815–824 https://doi.org/10.1007/s00403-019-01973-2 ORIGINAL PAPER In silico analysis of gene expression data from bald frontal and haired occipital scalp to identify candidate genes in male androgenetic alopecia A. Premanand1 · B. Reena Rajkumari1 Received: 5 September 2018 / Revised: 6 July 2019 / Accepted: 30 August 2019 / Published online: 11 September 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2019 Abstract Androgenetic alopecia (AGA) is a progressive dermatological disorder of frontal and vertex scalp hair loss leading to bald- ness in men. This study aimed to identify candidate genes involved in AGA through an in silico search strategy. The gene expression profle GS36169, which contains microarray gene expression data from bald frontal and haired occipital scalps of fve men with AGA, was downloaded from the Gene Expression Omnibus (GEO) database. The diferential gene expression analysis for all fve subjects was carried out separately by PUMA package in R and identifed 32 diferentially expressed genes (DEGs) common to all fve subjects. Gene ontology (GO) biological process and pathway- enrichment analyses of the DEGs were conducted separately for the up-regulated and down-regulated genes. ReactomeFIViz app was utilized to construct the protein functional interaction network for the DEGs. Through GO biological process and pathway analysis on the clusters of the Reactome FI network, we found that the down-regulated DEGs participate in Wnt signaling, TGF-beta signaling, -
Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ......................................................