Cooperative Transcription Factor Associations Discovered Using Regulatory Variation
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The REST/NRSF Pathway As a Central Mechanism in CNS Dysfunction
The REST/NRSF Pathway as a Central Mechanism in CNS Dysfunction Thesis submitted in accordance with the requirements of the University of Liverpool for the degree of Doctor in Philosophy by Alix Warburton April 2015 Disclaimer The data in this thesis is a result of my own work. The material collected for this thesis has not been presented, nor is currently being presented, either wholly or in part for any other degree or other qualification. All of the research, unless otherwise stated, was performed in the Department of Physiology and Department of Pharmacology, Institute of Translational Medicine, University of Liverpool. All other parties involved in the research presented here, and the nature of their contribution, are listed in the Acknowledgements section of this thesis. i Acknowledgements First and foremost, I would like to express my upmost gratitude to my primary and secondary supervisors Professor John Quinn (a.k.a Prof. Quinny) and Dr Jill Bubb for all of their support, guidance, wisdom (thank you Jill) and encouragement throughout my PhD; I could not have wished for a better pair. I am also extremely grateful to the BBSRC for funding my PhD project. I would also like to extend my thanks to Dr Graeme Sills for providing samples and assistance with my work on the SANAD epilepsy project, Dr Fabio Miyajima for offering his knowledge and knowhow on many occasions, Dr Gerome Breen for being a bioinformatics wizard and providing support on several projects, Dr Minyan Wang’s lab for their help and hospitality during my 3 month visit to Xi'an Jiaotong-Liverpool University, Dr Roshan Koron for assisting with the breast cancer study, Dr Chris Murgatroyd for his invaluable advice on ChIP and Professor Dan Rujescu’s lab for providing clinical samples and support with statistical analyses on the schizophrenia project. -
2017.08.28 Anne Barry-Reidy Thesis Final.Pdf
REGULATION OF BOVINE β-DEFENSIN EXPRESSION THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF DUBLIN FOR THE DEGREE OF DOCTOR OF PHILOSOPHY 2017 ANNE BARRY-REIDY SCHOOL OF BIOCHEMISTRY & IMMUNOLOGY TRINITY COLLEGE DUBLIN SUPERVISORS: PROF. CLIONA O’FARRELLY & DR. KIERAN MEADE TABLE OF CONTENTS DECLARATION ................................................................................................................................. vii ACKNOWLEDGEMENTS ................................................................................................................... viii ABBREVIATIONS ................................................................................................................................ix LIST OF FIGURES............................................................................................................................. xiii LIST OF TABLES .............................................................................................................................. xvii ABSTRACT ........................................................................................................................................xix Chapter 1 Introduction ........................................................................................................ 1 1.1 Antimicrobial/Host-defence peptides ..................................................................... 1 1.2 Defensins................................................................................................................. 1 1.3 β-defensins ............................................................................................................. -
Mediator of DNA Damage Checkpoint 1 (MDC1) Is a Novel Estrogen Receptor Co-Regulator in Invasive 6 Lobular Carcinoma of the Breast 7 8 Evelyn K
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.16.423142; this version posted December 16, 2020. 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. 1 Running Title: MDC1 co-regulates ER in ILC 2 3 Research article 4 5 Mediator of DNA damage checkpoint 1 (MDC1) is a novel estrogen receptor co-regulator in invasive 6 lobular carcinoma of the breast 7 8 Evelyn K. Bordeaux1+, Joseph L. Sottnik1+, Sanjana Mehrotra1, Sarah E. Ferrara2, Andrew E. Goodspeed2,3, James 9 C. Costello2,3, Matthew J. Sikora1 10 11 +EKB and JLS contributed equally to this project. 12 13 Affiliations 14 1Dept. of Pathology, University of Colorado Anschutz Medical Campus 15 2Biostatistics and Bioinformatics Shared Resource, University of Colorado Comprehensive Cancer Center 16 3Dept. of Pharmacology, University of Colorado Anschutz Medical Campus 17 18 Corresponding author 19 Matthew J. Sikora, PhD.; Mail Stop 8104, Research Complex 1 South, Room 5117, 12801 E. 17th Ave.; Aurora, 20 CO 80045. Tel: (303)724-4301; Fax: (303)724-3712; email: [email protected]. Twitter: 21 @mjsikora 22 23 Authors' contributions 24 MJS conceived of the project. MJS, EKB, and JLS designed and performed experiments. JLS developed models 25 for the project. EKB, JLS, SM, and AEG contributed to data analysis and interpretation. SEF, AEG, and JCC 26 developed and performed informatics analyses. MJS wrote the draft manuscript; all authors read and revised the 27 manuscript and have read and approved of this version of the manuscript. -
Intrinsic Specificity of DNA Binding and Function of Class II Bhlh
INTRINSIC SPECIFICITY OF BINDING AND REGULATORY FUNCTION OF CLASS II BHLH TRANSCRIPTION FACTORS APPROVED BY SUPERVISORY COMMITTEE Jane E. Johnson Ph.D. Helmut Kramer Ph.D. Genevieve Konopka Ph.D. Raymond MacDonald Ph.D. INTRINSIC SPECIFICITY OF BINDING AND REGULATORY FUNCTION OF CLASS II BHLH TRANSCRIPTION FACTORS by BRADFORD HARRIS CASEY DISSERTATION Presented to the Faculty of the Graduate School of Biomedical Sciences The University of Texas Southwestern Medical Center at Dallas In Partial Fulfillment of the Requirements For the Degree of DOCTOR OF PHILOSOPHY The University of Texas Southwestern Medical Center at Dallas Dallas, Texas December, 2016 DEDICATION This work is dedicated to my family, who have taught me pursue truth in all forms. To my grandparents for inspiring my curiosity, my parents for teaching me the value of a life in the service of others, my sisters for reminding me of the importance of patience, and to Rachel, who is both “the beautiful one”, and “the smart one”, and insists that I am clever and beautiful, too. Copyright by Bradford Harris Casey, 2016 All Rights Reserved INTRINSIC SPECIFICITY OF BINDING AND REGULATORY FUNCTION OF CLASS II BHLH TRANSCRIPTION FACTORS Publication No. Bradford Harris Casey The University of Texas Southwestern Medical Center at Dallas, 2016 Jane E. Johnson, Ph.D. PREFACE Embryonic development begins with a single cell, and gives rise to the many diverse cells which comprise the complex structures of the adult animal. Distinct cell fates require precise regulation to develop and maintain their functional characteristics. Transcription factors provide a mechanism to select tissue-specific programs of gene expression from the shared genome. -
Accompanies CD8 T Cell Effector Function Global DNA Methylation
Global DNA Methylation Remodeling Accompanies CD8 T Cell Effector Function Christopher D. Scharer, Benjamin G. Barwick, Benjamin A. Youngblood, Rafi Ahmed and Jeremy M. Boss This information is current as of October 1, 2021. J Immunol 2013; 191:3419-3429; Prepublished online 16 August 2013; doi: 10.4049/jimmunol.1301395 http://www.jimmunol.org/content/191/6/3419 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2013/08/20/jimmunol.130139 Material 5.DC1 References This article cites 81 articles, 25 of which you can access for free at: http://www.jimmunol.org/content/191/6/3419.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 1, 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 © 2013 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Global DNA Methylation Remodeling Accompanies CD8 T Cell Effector Function Christopher D. Scharer,* Benjamin G. Barwick,* Benjamin A. Youngblood,*,† Rafi Ahmed,*,† and Jeremy M. -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
Detecting Global in Uence of Transcription
Detecting global inuence of transcription factor interactions on gene expression in lymphoblastoid cells using neural network models Neel Patel Case Western Reserve University William S. Bush ( [email protected] ) Case Western Reserve University Research Article Keywords: Transcription factors, Gene expression, Machine learning, Neural network, Chromatin-looping, Regulatory module, Multi-omics Posted Date: April 15th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-406028/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Detecting global influence of transcription factor interactions on gene expression in lymphoblastoid cells using neural network models. Neel Patel1,2 and William S. Bush2* 1Department of Nutrition, Case Western Reserve University, Cleveland, OH, USA. 2Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA.*-corresponding author(email:[email protected]) Abstract Background Transcription factor(TF) interactions are known to regulate target gene(TG) expression in eukaryotes via TF regulatory modules(TRMs). Such interactions can be formed due to co- localizing TFs binding proximally to each other in the DNA sequence or over long distances between distally binding TFs via chromatin looping. While the former type of interaction has been characterized extensively, long distance TF interactions are still largely understudied. Furthermore, most prior approaches have focused on characterizing physical TF interactions without accounting for their effects on TG expression regulation. Understanding TRM based TG expression regulation could aid in understanding diseases caused by disruptions to these mechanisms. In this paper, we present a novel neural network based TRM detection approach that consists of using multi-omics TF based regulatory mechanism information to generate features for building non-linear multilayer perceptron TG expression prediction models in the GM12878 immortalized lymphoblastoid cells. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Transcriptome Analysis of Complex I-Deficient Patients Reveals Distinct
van der Lee et al. BMC Genomics (2015) 16:691 DOI 10.1186/s12864-015-1883-8 RESEARCH ARTICLE Open Access Transcriptome analysis of complex I-deficient patients reveals distinct expression programs for subunits and assembly factors of the oxidative phosphorylation system Robin van der Lee1†, Radek Szklarczyk1,2†, Jan Smeitink3,HubertJMSmeets4, Martijn A. Huynen1 and Rutger Vogel3* Abstract Background: Transcriptional control of mitochondrial metabolism is essential for cellular function. A better understanding of this process will aid the elucidation of mitochondrial disorders, in particular of the many genetically unsolved cases of oxidative phosphorylation (OXPHOS) deficiency. Yet, to date only few studies have investigated nuclear gene regulation in the context of OXPHOS deficiency. In this study we performed RNA sequencing of two control and two complex I-deficient patient cell lines cultured in the presence of compounds that perturb mitochondrial metabolism: chloramphenicol, AICAR, or resveratrol. We combined this with a comprehensive analysis of mitochondrial and nuclear gene expression patterns, co-expression calculations and transcription factor binding sites. Results: Our analyses show that subsets of mitochondrial OXPHOS genes respond opposingly to chloramphenicol and AICAR, whereas the response of nuclear OXPHOS genes is less consistent between cell lines and treatments. Across all samples nuclear OXPHOS genes have a significantly higher co-expression with each other than with other genes, including those encoding mitochondrial proteins. We found no evidence for complex-specific mRNA expression regulation: subunits of different OXPHOS complexes are similarly (co-)expressed and regulated by a common set of transcription factors. However, we did observe significant differences between the expression of nuclear genes for OXPHOS subunits versus assembly factors, suggesting divergent transcription programs. -
Supporting Information
Supporting Information Rangel et al. 10.1073/pnas.1613859113 SI Materials and Methods genes were identified, and the microarray data were used to Tumor Xenograft Studies. Female 6- to 7-wk-old Crl:NU(NCr)- determine the closest intrinsic subtype centroid for each sample, Foxn1nu mice were purchased from Charles River Laboratories. based on Spearman correlation using logged mean-centered Mammary fat pad injections into athymic nude mice were per- expression data. To estimate cellular proliferation, a “gene formed using 3 × 106 cells (HCC70, HCC1954, MDA-MB-468, and proliferation signature” (32) was used to generate a proliferation MDA-MB-231). The human cancer cells were resuspended in score for each sample. Briefly, using the logged expression data 100 μL of a 1:1 mix of PBS and matrigel (TREVIGEN). For for a subset of proliferation-related genes, singular value de- HCC1569 human breast cancer cells, we injected 4 × 106 cells in composition was used to produce a “proliferation metagene,” 100 μL of a 1:1 mix of PBS and matrigel. Injections were done which was then scaled to generate a score between 0 and 1, with into the fourth mammary gland. Tumors were measured using a a higher score denoting an increased level of proliferation rela- digital caliper, and the tumor volume was calculated using the tive to samples with lower scores. following formula: volume (mm3) = width × length/2. At the end of the experiment, tumor tissues were sectioned for fixation Human Data. Data from a combined cohort of 2,116 breast tumors (10% formalin or 4% paraformaldehyde) and RNA isolation. -
Early B Cell Factor 1 Regulates B Cell Gene Networks by Activation, Repression, and Transcription- Independent Poising of Chromatin
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Immunity Resource Early B Cell Factor 1 Regulates B Cell Gene Networks by Activation, Repression, and Transcription- Independent Poising of Chromatin Thomas Treiber,1,3 Elizabeth M. Mandel,1,3 Sebastian Pott,2,3 Ildiko Gyo¨ ry,1,3 Sonja Firner,1 Edison T. Liu,2 and Rudolf Grosschedl1,* 1Max Planck Institute of Immunobiology, Department of Cellular and Molecular Immunology, Stuebeweg 51, 79108 Freiburg, Germany 2Genome Institute of Singapore, Cancer Biology and Pharmacology, 60 Biopolis Street, 138672 Singapore 3These authors contributed equally to this work *Correspondence: [email protected] DOI 10.1016/j.immuni.2010.04.013 SUMMARY (reviewed in Hardy et al., 2007; Murre, 2009). Pre-B cells express the pre-B cell receptor (pre-BCR) and further differentiate into The transcription factor early B cell factor-1 (Ebf1) is immature B cells that have undergone Ig light chain gene rear- a key determinant of B lineage specification and rangement and migrate from the bone marrow to the spleen. differentiation. To gain insight into the molecular Each of these B cell differentiation steps is dependent on basis of Ebf1 function in early-stage B cells, we the coordinated expression of cell-type-specific transcription combined a genome-wide ChIP sequencing analysis factors and activities of signaling pathways (reviewed in Mandel with gain- and loss-of-function transcriptome anal- and Grosschedl, 2010). Genetic ablation and complementation studies have demonstrated key roles for transcription factors yses. Among 565 genes that are occupied and tran- such as Ikaros, Pu.1, E2A, early B cell factor-1 (Ebf1), and scriptionally regulated by Ebf1, we identified large Pax5 (reviewed in Busslinger, 2004; Hagman and Lukin, 2006; sets involved in (pre)-B cell receptor and Akt Singh et al., 2007). -
Ebf1-Mediated Down-Regulation of Id2 and Id3 Is Essential for Specification of the B Cell Lineage
Ebf1-mediated down-regulation of Id2 and Id3 is essential for specification of the B cell lineage Melissa A. Thala, Thiago L. Carvalhoa,TiHea, Hyung-Gyoon Kima, Hua Gaob, James Hagmanb, and Christopher A. Kluga,1 aDepartment of Microbiology, The University of Alabama-Birmingham, Birmingham, AL 35294; and bIntegrated Department of Immunology, National Jewish Medical and Research Center, Denver, CO 80206 Edited by Cornelis Murre, University of California, San Diego, La Jolla, CA, and accepted by the Editorial Board November 7, 2008 (received for review March 13, 2008) Gene knockout experiments in mice have suggested a hierarchical of E47 (13) or E12 (14) in non-B-lineage cell lines, suggest that model of early B cell commitment wherein E2A proteins (E47 and E2A activity is essential upstream of Ebf1. Similarly, the Pax5 E12) activate early B cell factor (Ebf1), which in turn activates promoter is bound by Ebf1 based on EMSA and Ebf1 can expression of the B cell commitment factor, Pax5. In IL-7 receptor transactivate the Pax5 promoter in transient co-transfection alpha (IL-7R␣) knockout mice, B cell development is blocked before assays (15, 16). Ebf1 is also present in Pax5-deficient pro-B cells B-lineage commitment at the prepro-B cell stage in adult animals. derived from Pax5Ϫ/Ϫ adult mice (17), suggesting that Ebf1 may In IL-7R␣؊/؊ prepro-B cells, E47 is expressed and yet is insufficient participate in the activation of Pax5 expression. Complicating the to transcriptionally activate the putative downstream target gene, simple hierarchical model where E2A induces expression of Ebf1.