Molecular Expression Analyses of Mice Treated with Antipsychotic Drugs
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Integrative Genomic and Epigenomic Analyses Identified IRAK1 As a Novel Target for Chronic Inflammation-Driven Prostate Tumorigenesis
bioRxiv preprint doi: https://doi.org/10.1101/2021.06.16.447920; this version posted June 16, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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. Integrative genomic and epigenomic analyses identified IRAK1 as a novel target for chronic inflammation-driven prostate tumorigenesis Saheed Oluwasina Oseni1,*, Olayinka Adebayo2, Adeyinka Adebayo3, Alexander Kwakye4, Mirjana Pavlovic5, Waseem Asghar5, James Hartmann1, Gregg B. Fields6, and James Kumi-Diaka1 Affiliations 1 Department of Biological Sciences, Florida Atlantic University, Florida, USA 2 Morehouse School of Medicine, Atlanta, Georgia, USA 3 Georgia Institute of Technology, Atlanta, Georgia, USA 4 College of Medicine, Florida Atlantic University, Florida, USA 5 Department of Computer and Electrical Engineering, Florida Atlantic University, Florida, USA 6 Department of Chemistry & Biochemistry and I-HEALTH, Florida Atlantic University, Florida, USA Corresponding Author: [email protected] (S.O.O) Running Title: Chronic inflammation signaling in prostate tumorigenesis bioRxiv preprint doi: https://doi.org/10.1101/2021.06.16.447920; this version posted June 16, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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. Abstract The impacts of many inflammatory genes in prostate tumorigenesis remain understudied despite the increasing evidence that associates chronic inflammation with prostate cancer (PCa) initiation, progression, and therapy resistance. -
Analysis of Trans Esnps Infers Regulatory Network Architecture
Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Anat Kreimer All rights reserved ABSTRACT Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer eSNPs are genetic variants associated with transcript expression levels. The characteristics of such variants highlight their importance and present a unique opportunity for studying gene regulation. eSNPs affect most genes and their cell type specificity can shed light on different processes that are activated in each cell. They can identify functional variants by connecting SNPs that are implicated in disease to a molecular mechanism. Examining eSNPs that are associated with distal genes can provide insights regarding the inference of regulatory networks but also presents challenges due to the high statistical burden of multiple testing. Such association studies allow: simultaneous investigation of many gene expression phenotypes without assuming any prior knowledge and identification of unknown regulators of gene expression while uncovering directionality. This thesis will focus on such distal eSNPs to map regulatory interactions between different loci and expose the architecture of the regulatory network defined by such interactions. We develop novel computational approaches and apply them to genetics-genomics data in human. We go beyond pairwise interactions to define network motifs, including regulatory modules and bi-fan structures, showing them to be prevalent in real data and exposing distinct attributes of such arrangements. We project eSNP associations onto a protein-protein interaction network to expose topological properties of eSNPs and their targets and highlight different modes of distal regulation. -
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. -
Microarray Analysis of Gene Expression in the Ovarian Cancer Cell Line HO-8910 with Silencing of the ZNF217 Gene
MOLECULAR MEDICINE REPORTS 2: 851-855, 2009 851 Microarray analysis of gene expression in the ovarian cancer cell line HO-8910 with silencing of the ZNF217 gene GUIQIN SUN1, JINGXIA QIN1, YUWEN QIU1, YUNFEI GAO1, YANHONG YU1, QINKAI DENG2 and MEI ZHONG1 1Department of Obstetrics and Gynecology, Nanfang Hospital, Southern Medical University; 2Department of Bioinformatics, Southern Medical University, Guangzhou 510515, Guangdong, P.R. China Received April 30, 2009; Accepted July 7, 2009 DOI: 10.3892/mmr_00000183 Abstract. Zinc-finger protein 217 (ZNF217), which is over- late stages (stage III or IV) and have a 5-year survival rate of expressed during cancer progression, can promote tumor cell less than 30% (1). Ovarian cancer is a heterogeneous disease immortalization. To examine the function of ZNF217, a global with respect to its histopathology, molecular biology and expression profile was carried out using Affymetrix Gene clinical outcome. Though studies on the etiology of ovarian Chip analysis with HG-U133 plus 2.0 arrays in the ovarian cancer and susceptibility to the disease have shown that the cancer cell line HO-8910 after silencing of the ZNF217 gene. mechanisms of carcinogenesis and cancer development are The results were analyzed using the Gene Ontology program associated with genetic, epigenetic and environmental factors, to investigate the functional network affected by ZNF217 the pathogenesis of ovarian cancer remains unclear (2). in ovarian cancer cells. Changes in the mRNA expression Among the current methods for the identification of gene of the affected genes were confirmed by real-time reverse expression profiles in cancer, microarray analysis is the most transcriptase-polymerase chain reaction (RT-PCR). -
Coupling of Spliceosome Complexity to Intron Diversity
bioRxiv preprint doi: https://doi.org/10.1101/2021.03.19.436190; this version posted March 20, 2021. 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. Coupling of spliceosome complexity to intron diversity Jade Sales-Lee1, Daniela S. Perry1, Bradley A. Bowser2, Jolene K. Diedrich3, Beiduo Rao1, Irene Beusch1, John R. Yates III3, Scott W. Roy4,6, and Hiten D. Madhani1,6,7 1Dept. of Biochemistry and Biophysics University of California – San Francisco San Francisco, CA 94158 2Dept. of Molecular and Cellular Biology University of California - Merced Merced, CA 95343 3Department of Molecular Medicine The Scripps Research Institute, La Jolla, CA 92037 4Dept. of Biology San Francisco State University San Francisco, CA 94132 5Chan-Zuckerberg Biohub San Francisco, CA 94158 6Corresponding authors: [email protected], [email protected] 7Lead Contact 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.03.19.436190; this version posted March 20, 2021. 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. SUMMARY We determined that over 40 spliceosomal proteins are conserved between many fungal species and humans but were lost during the evolution of S. cerevisiae, an intron-poor yeast with unusually rigid splicing signals. We analyzed null mutations in a subset of these factors, most of which had not been investigated previously, in the intron-rich yeast Cryptococcus neoformans. -
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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Supplementary Figure S1. Results of flow cytometry analysis, performed to estimate CD34 positivity, after immunomagnetic separation in two different experiments. As monoclonal antibody for labeling the sample, the fluorescein isothiocyanate (FITC)- conjugated mouse anti-human CD34 MoAb (Mylteni) was used. Briefly, cell samples were incubated in the presence of the indicated MoAbs, at the proper dilution, in PBS containing 5% FCS and 1% Fc receptor (FcR) blocking reagent (Miltenyi) for 30 min at 4 C. Cells were then washed twice, resuspended with PBS and analyzed by a Coulter Epics XL (Coulter Electronics Inc., Hialeah, FL, USA) flow cytometer. only use Non-commercial 1 Supplementary Table S1. Complete list of the datasets used in this study and their sources. GEO Total samples Geo selected GEO accession of used Platform Reference series in series samples samples GSM142565 GSM142566 GSM142567 GSM142568 GSE6146 HG-U133A 14 8 - GSM142569 GSM142571 GSM142572 GSM142574 GSM51391 GSM51392 GSE2666 HG-U133A 36 4 1 GSM51393 GSM51394 only GSM321583 GSE12803 HG-U133A 20 3 GSM321584 2 GSM321585 use Promyelocytes_1 Promyelocytes_2 Promyelocytes_3 Promyelocytes_4 HG-U133A 8 8 3 GSE64282 Promyelocytes_5 Promyelocytes_6 Promyelocytes_7 Promyelocytes_8 Non-commercial 2 Supplementary Table S2. Chromosomal regions up-regulated in CD34+ samples as identified by the LAP procedure with the two-class statistics coded in the PREDA R package and an FDR threshold of 0.5. Functional enrichment analysis has been performed using DAVID (http://david.abcc.ncifcrf.gov/) -
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Patterns of DNA methylation on the human X chromosome and use in analyzing X-chromosome inactivation by Allison Marie Cotton B.Sc., The University of Guelph, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2012 © Allison Marie Cotton, 2012 Abstract The process of X-chromosome inactivation achieves dosage compensation between mammalian males and females. In females one X chromosome is transcriptionally silenced through a variety of epigenetic modifications including DNA methylation. Most X-linked genes are subject to X-chromosome inactivation and only expressed from the active X chromosome. On the inactive X chromosome, the CpG island promoters of genes subject to X-chromosome inactivation are methylated in their promoter regions, while genes which escape from X- chromosome inactivation have unmethylated CpG island promoters on both the active and inactive X chromosomes. The first objective of this thesis was to determine if the DNA methylation of CpG island promoters could be used to accurately predict X chromosome inactivation status. The second objective was to use DNA methylation to predict X-chromosome inactivation status in a variety of tissues. A comparison of blood, muscle, kidney and neural tissues revealed tissue-specific X-chromosome inactivation, in which 12% of genes escaped from X-chromosome inactivation in some, but not all, tissues. X-linked DNA methylation analysis of placental tissues predicted four times higher escape from X-chromosome inactivation than in any other tissue. Despite the hypomethylation of repetitive elements on both the X chromosome and the autosomes, no changes were detected in the frequency or intensity of placental Cot-1 holes. -
Large Scale Organization of Chromatin
LARGE SCALE ORGANIZATION OF CHROMATIN MARIO Nicodemi Dip.to di Fisica, Uni.NA “Federico II”, INFN In the cell nucleus chromosomes have a complex architecture serving vital functional purposes. Problem: how is their 3D structure orchestrated? Our contribution: a model of the molecular mechanisms of their self- organization by use of classical polymer physics. (Mirò, Chiffres & Constellations 1941) Research collaborators MRC, Imperial College, London Ana Pombo,, Mita Chotalia, Ines de Santiago, Liron-Mark Lavitas, Sheila Xie, Kedar Natarajan, Carmelo Ferrai, Robert Beagrie, ... Biology, McGill, CA Josée Dostie, James Fraser Physics, Univ. di Napoli, Italy Mariano Barbieri, Ilaria Cataudella, Antonio Scialdone, Melania Barile, Paolo Casale, Valentino Bianco, Emanuela de Falco, Deborah Pallotti, Gaetano Pellegrino, Andrea Piccolo, ... Chromatin organization (I) (A) Linear expression units in compact genomes v.s. spatially assembled units in complex genomes. (B) Colocalization of coregulated genes. (C) ChromatinGene localization organizationat transcription factories (TFs). Example: the Xicʼs of the X Chromosome territories and map chrom.s colocalize at XCI (Heard et al.; Lee et al. ʻ07) Chromatin organizationNuclear scale (I) (A) Linear expression units in compact genomes v.s. spatially assembled units in complex genomes. (B) Colocalization of coregulated genes. (C) Gene localization at transcription factories (TFs). Colocalization of coregulated genes at transcription factories Example: the Xicʼs of the X Transcription chrom.s colocalize at XCI Factory (Heard et al.; Lee et al. ʻ07) (Pictures: Dekker et al. Science ʻ08) Distal regulatory elements Gene Gene Expression Units Assembly of expression units Gene scale (Pictures: Bolzer et al. PLoS Bio. ʼ05; Dekker et al. Science ʼ08) (Pictures: Dekker et al. -
1 UST College of Science Department of Biological Sciences
UST College of Science Department of Biological Sciences 1 Pharmacogenomics of Myofascial Pain Syndrome An Undergraduate Thesis Submitted to the Department of Biological Sciences College of Science University of Santo Tomas In Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Biology Jose Marie V. Lazaga Marc Llandro C. Fernandez May 2021 UST College of Science Department of Biological Sciences 2 PANEL APPROVAL SHEET This undergraduate research manuscript entitled: Pharmacogenomics of Myofascial Pain Syndrome prepared and submitted by Jose Marie V. Lazaga and Marc Llandro C. Fernandez, was checked and has complied with the revisions and suggestions requested by panel members after thorough evaluation. This final version of the manuscript is hereby approved and accepted for submission in partial fulfillment of the requirements for the degree of Bachelor of Science in Biology. Noted by: Asst. Prof. Marilyn G. Rimando, PhD Research adviser, Bio/MicroSem 602-603 Approved by: Bio/MicroSem 603 panel member Bio/MicroSem 603 panel member Date: Date: UST College of Science Department of Biological Sciences 3 DECLARATION OF ORIGINALITY We hereby affirm that this submission is our own work and that, to the best of our knowledge and belief, it contains no material previously published or written by another person nor material to which a substantial extent has been accepted for award of any other degree or diploma of a university or other institute of higher learning, except where due acknowledgement is made in the text. We also declare that the intellectual content of this undergraduate research is the product of our work, even though we may have received assistance from others on style, presentation, and language expression. -
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. -
Systems Consequences of Amplicon Formation in Human Breast Cancer
Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Research Systems consequences of amplicon formation in human breast cancer Koichiro Inaki,1,2,9 Francesca Menghi,1,2,9 Xing Yi Woo,1,9 Joel P. Wagner,1,2,3 4,5 1 2 Pierre-Etienne Jacques, Yi Fang Lee, Phung Trang Shreckengast, Wendy WeiJia Soon,1 Ankit Malhotra,2 Audrey S.M. Teo,1 Axel M. Hillmer,1 Alexis Jiaying Khng,1 Xiaoan Ruan,6 Swee Hoe Ong,4 Denis Bertrand,4 Niranjan Nagarajan,4 R. Krishna Murthy Karuturi,4,7 Alfredo Hidalgo Miranda,8 andEdisonT.Liu1,2,7 1Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Genome, Singapore 138672, Singapore; 2The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06030, USA; 3Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA; 4Computational and Systems Biology, Genome Institute of Singapore, Genome, Singapore 138672, Singapore; 5Universite de Sherbrooke, Sherbrooke, Quebec, J1K 2R1, Canada; 6Genome Technology and Biology, Genome Institute of Singapore, Genome, Singapore 138672, Singapore; 7The Jackson Laboratory, Bar Harbor, Maine 04609, USA; 8National Institute of Genomic Medicine, Periferico Sur 4124, Mexico City 01900, Mexico Chromosomal structural variations play an important role in determining the transcriptional landscape of human breast cancers. To assess the nature of these structural variations, we analyzed eight breast tumor samples with a focus on regions of gene amplification using mate-pair sequencing of long-insert genomic DNA with matched transcriptome profiling. We found that tandem duplications appear to be early events in tumor evolution, especially in the genesis of amplicons.