The Role of Histone H2B Ubiquitylation and Its Related Factors in Transcriptional Regulation in Mammalian Cells Jaehoon Kim
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Architecture of the RNA Polymerase II-Paf1c-TFIIS Transcription Elongation Complex
Dissertation zur Erlangung des Doktorgrades der Fakultät für Chemie und Pharmazie der Ludwig-Maximilians-Universität München Architecture of the RNA polymerase II- Paf1C-TFIIS transcription elongation complex Youwei Xu aus Gaoyou, Jiangsu Provinz, P.R.China 2016 Dissertation zur Erlangung des Doktorgrades der Fakultät für Chemie und Pharmazie der Ludwig-Maximilians-Universität München Architecture of the RNA polymerase II- Paf1C-TFIIS transcription elongation complex Youwei Xu aus Gaoyou, Jiangsu Provinz, P.R.China 2016 Erklärung Diese Dissertation wurde im Sinne von § 7 der Promotionsordnung vom 28. November 2011 von Herrn Prof. Dr. Patrick Cramer betreut. Eidesstattliche Versicherung Diese Dissertation wurde eigenständig und ohne unerlaubte Hilfe erarbeitet. Göttingen, den 28.11.2016 Youwei Xu Dissertation eingereicht am 01.12.2016 1. Gutachter: Prof. Dr. Patrick Cramer 2. Gutachter: PD Dr. Dietmar Martin Mündliche Prüfung am 25.01.2017 "My apologies to great questions for small answers." - Wislawa Szymborska Acknowledgements Firstly, I would like to express my sincere gratitude to Patrick Cramer for giving me such a great opportunity to study in this lab. This is an excellent lab circumstanced by outstanding scientific atmosphere. I still remember that you asked me whether I had further questions for you at the end of our interview via the phone, I asked how about the weather in Munich. I feel very lucky being your student. You always gave me fantastic suggestions, sufficient support, and enough patience. I learned a lot from you, and your enthusiasm for science and life inspires me. I am most indebted to my past and present colleagues of the Cramer group from Munich and Göttingen for the great assistance, stimulating discussions, advice, encouragement, and joyful life, especially the following people: Carrie Bernecky, Christoph Engel, Simon Neyer, Christian Dienemann, Clemens Plaschka, Sarah Sainsbury, Merle Hantsche, Anna Sawicka, Jinmi Choi, Carina Demel, Margaux Michel, Tobias Gubbey, Dimitry Tengunov, and Sara Osman. -
Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
Interactome Analyses Revealed That the U1 Snrnp Machinery Overlaps Extensively with the RNAP II Machinery and Contains Multiple
www.nature.com/scientificreports OPEN Interactome analyses revealed that the U1 snRNP machinery overlaps extensively with the RNAP II Received: 12 April 2018 Accepted: 24 May 2018 machinery and contains multiple Published: xx xx xxxx ALS/SMA-causative proteins Binkai Chi1, Jeremy D. O’Connell1,2, Tomohiro Yamazaki1, Jaya Gangopadhyay1, Steven P. Gygi1 & Robin Reed1 Mutations in multiple RNA/DNA binding proteins cause Amyotrophic Lateral Sclerosis (ALS). Included among these are the three members of the FET family (FUS, EWSR1 and TAF15) and the structurally similar MATR3. Here, we characterized the interactomes of these four proteins, revealing that they largely have unique interactors, but share in common an association with U1 snRNP. The latter observation led us to analyze the interactome of the U1 snRNP machinery. Surprisingly, this analysis revealed the interactome contains ~220 components, and of these, >200 are shared with the RNA polymerase II (RNAP II) machinery. Among the shared components are multiple ALS and Spinal muscular Atrophy (SMA)-causative proteins and numerous discrete complexes, including the SMN complex, transcription factor complexes, and RNA processing complexes. Together, our data indicate that the RNAP II/U1 snRNP machinery functions in a wide variety of molecular pathways, and these pathways are candidates for playing roles in ALS/SMA pathogenesis. Te neurodegenerative disease Amyotrophic Lateral Sclerosis (ALS) has no known treatment, and elucidation of disease mechanisms is urgently needed. Tis problem has been especially daunting, as mutations in greater than 30 genes are ALS-causative, and these genes function in numerous cellular pathways1. Tese include mitophagy, autophagy, cytoskeletal dynamics, vesicle transport, DNA damage repair, RNA dysfunction, apoptosis, and pro- tein aggregation2–6. -
A Yeast Phenomic Model for the Influence of Warburg Metabolism on Genetic Buffering of Doxorubicin Sean M
Santos and Hartman Cancer & Metabolism (2019) 7:9 https://doi.org/10.1186/s40170-019-0201-3 RESEARCH Open Access A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin Sean M. Santos and John L. Hartman IV* Abstract Background: The influence of the Warburg phenomenon on chemotherapy response is unknown. Saccharomyces cerevisiae mimics the Warburg effect, repressing respiration in the presence of adequate glucose. Yeast phenomic experiments were conducted to assess potential influences of Warburg metabolism on gene-drug interaction underlying the cellular response to doxorubicin. Homologous genes from yeast phenomic and cancer pharmacogenomics data were analyzed to infer evolutionary conservation of gene-drug interaction and predict therapeutic relevance. Methods: Cell proliferation phenotypes (CPPs) of the yeast gene knockout/knockdown library were measured by quantitative high-throughput cell array phenotyping (Q-HTCP), treating with escalating doxorubicin concentrations under conditions of respiratory or glycolytic metabolism. Doxorubicin-gene interaction was quantified by departure of CPPs observed for the doxorubicin-treated mutant strain from that expected based on an interaction model. Recursive expectation-maximization clustering (REMc) and Gene Ontology (GO)-based analyses of interactions identified functional biological modules that differentially buffer or promote doxorubicin cytotoxicity with respect to Warburg metabolism. Yeast phenomic and cancer pharmacogenomics data were integrated to predict differential gene expression causally influencing doxorubicin anti-tumor efficacy. Results: Yeast compromised for genes functioning in chromatin organization, and several other cellular processes are more resistant to doxorubicin under glycolytic conditions. Thus, the Warburg transition appears to alleviate requirements for cellular functions that buffer doxorubicin cytotoxicity in a respiratory context. -
Association Analyses Based on False Discovery Rate Implicate Many New Loci for Coronary Artery Disease
1 Association analyses based on false discovery rate implicate many new loci 2 for coronary artery disease 3 Christopher P. Nelson1,2,61, Anuj Goel3,4,61, Adam S Butterworth5,6,61, Stavroula Kanoni7,8,61, 4 Tom R. Webb1,2, Eirini Marouli7,8, Lingyao Zeng9, Ioanna Ntalla7,8, Florence Y. Lai1,2, Jemma C. 5 Hopewell10, Olga Giannakopoulou7,8, Tao Jiang5, Stephen E. Hamby1,2, Emanuele Di 6 Angelantonio5,6, Themistocles L. Assimes11, Erwin P. Bottinger12, John C. Chambers13,14,15, 7 Robert Clarke10, Colin NA Palmer16,17, Richard M. Cubbon18, Patrick Ellinor19, Raili Ermel20, 8 Evangelos Evangelou21,22, Paul W. Franks23,24,25, Christopher Grace3,4, Dongfeng Gu26, Aroon 9 D. Hingorani27, Joanna M. M. Howson5, Erik Ingelsson28, Adnan Kastrati9, Thorsten Kessler9, 10 Theodosios Kyriakou3,4, Terho Lehtimäki29, Xiangfeng Lu26, Yingchang Lu12,30, Winfried 11 März31,32,33, Ruth McPherson34, Andres Metspalu35, Mar Pujades-Rodriguez36, Arno 12 Ruusalepp20,37, Eric E. Schadt38, Amand F. Schmidt39, Michael J. Sweeting5, Pierre A. 13 Zalloua40,41, Kamal AIGhalayini42, Bernard D. Keavney43,44, Jaspal S. Kooner14,15,45, Ruth J. F. 14 Loos12,46, Riyaz S. Patel47,48, Martin K. Rutter49,50, Maciej Tomaszewski51,52, Ioanna Tzoulaki21,22, 15 Eleftheria Zeggini53, Jeanette Erdmann54,55,56, George Dedoussis57, Johan L. M. 16 Björkegren37,38,58, EPIC-CVD Consortium, CARDIoGRAMplusC4D, The UK Biobank 17 CardioMetabolic Consortium CHD working group, Heribert Schunkert9,61, Martin Farrall3,4,61, 18 John Danesh5,6,59,61, Nilesh J. Samani1,2,61, Hugh Watkins3,4,61, Panos Deloukas7,8,60,61 19 1. Department of Cardiovascular Sciences, University of Leicester, Leicester LE3 9QP, UK 20 2. -
Atlas Journal
Atlas of Genetics and Cytogenetics in Oncology and Haematology Home Genes Leukemias Solid Tumours Cancer-Prone Deep Insight Portal Teaching X Y 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 NA Atlas Journal Atlas Journal versus Atlas Database: the accumulation of the issues of the Journal constitutes the body of the Database/Text-Book. TABLE OF CONTENTS Volume 12, Number 6, Nov-Dec 2008 Previous Issue / Next Issue Genes BCL8 (B-cell CLL/lymphoma 8) (15q11). Silvia Rasi, Gianluca Gaidano. Atlas Genet Cytogenet Oncol Haematol 2008; 12 (6): 781-784. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/BCL8ID781ch15q11.html CDC25A (Cell division cycle 25A) (3p21). Dipankar Ray, Hiroaki Kiyokawa. Atlas Genet Cytogenet Oncol Haematol 2008; 12 (6): 785-791. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/CDC25AID40004ch3p21.html CDC73 (cell division cycle 73, Paf1/RNA polymerase II complex component, homolog (S. cerevisiae)) (1q31.2). Leslie Farber, Bin Tean Teh. Atlas Genet Cytogenet Oncol Haematol 2008; 12 (6): 792-797. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/CDC73D181ch1q31.html EIF3C (eukaryotic translation initiation factor 3, subunit C) (16p11.2). Daniel R Scoles. Atlas Genet Cytogenet Oncol Haematol 2008; 12 (6): 798-802. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/EIF3CID44187ch16p11.html ELAC2 (elaC homolog 2 (E. coli)) (17p11.2). Yang Chen, Sean Tavtigian, Donna Shattuck. Atlas Genet Cytogenet Oncol Haematol 2008; 12 (6): 803-806. [Full Text] [PDF] URL : http://atlasgeneticsoncology.org/Genes/ELAC2ID40437ch17p11.html FOXM1 (forkhead box M1) (12p13). Jamila Laoukili, Monica Alvarez Fernandez, René H Medema. -
12619 CTR9 (D1Z4F) Rabbit Mab
Revision 1 C 0 2 - t CTR9 (D1Z4F) Rabbit mAb a e r o t S Orders: 877-616-CELL (2355) [email protected] 9 Support: 877-678-TECH (8324) 1 6 Web: [email protected] 2 www.cellsignal.com 1 # 3 Trask Lane Danvers Massachusetts 01923 USA For Research Use Only. Not For Use In Diagnostic Procedures. Applications: Reactivity: Sensitivity: MW (kDa): Source/Isotype: UniProt ID: Entrez-Gene Id: WB, IP H M R Endogenous 140 Rabbit IgG Q6PD62 9646 Product Usage Information 7. Farber, L.J. et al. (2010) Mol Carcinog 49, 215-23. Application Dilution Western Blotting 1:1000 Immunoprecipitation 1:50 Storage Supplied in 10 mM sodium HEPES (pH 7.5), 150 mM NaCl, 100 µg/ml BSA, 50% glycerol and less than 0.02% sodium azide. Store at –20°C. Do not aliquot the antibody. Specificity / Sensitivity CTR9 (D1Z4F) Rabbit mAb recognizes endogenous levels of total CTR9 protein. Species Reactivity: Human, Mouse, Rat Species predicted to react based on 100% sequence homology: Hamster, Chicken, Xenopus, Zebrafish, Bovine, Dog, Pig Source / Purification Monoclonal antibody is produced by immunizing animals with a synthetic peptide corresponding to residues near the amino terminus of human CTR9 protein. Background The PAF (RNA polymerase II (RNAPII) associated factor) complex was initially identified in yeast and is comprised of subunits PAF1, Leo1, Ctr9, Cdc73, RTF1 and Ski8 (1,2). The PAF complex plays an important role in transcription initiation and elongation by RNAPII by regulating the establishment of proper histone modifications such as histone H2B ubiquitination and the recruitment of the histone chaperone FACT (facilitates chromatin transcription) (3-5). -
I STRUCTURAL and FUNCTIONAL CHARACTERIZATION of RTF1
STRUCTURAL AND FUNCTIONAL CHARACTERIZATION OF RTF1 AND INSIGHT INTO ITS ROLE IN TRANSCRIPTIONAL REGULATION by Adam Douglas Wier B.S., Molecular Biology and Biochemistry, Lebanon Valley College, 2009 Submitted to the Graduate Faculty of the Kenneth P. Dietrich School of Arts and Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2014 i UNIVERSITY OF PITTSBURGH KENNETH P. DIETRICH SCHOOL OF ARTS AND SCIENCES This dissertation was presented by Adam D. Wier It was defended on August 20, 2014 and approved by James M. Pipas, Ph.D., Professor, Biological Sciences Karen M. Arndt, Ph.D., Professor, Biological Sciences John M Rosenberg, Ph.D., Professor, Biological Sciences Martin C. Schmidt, Ph.D., Associate Professor, Microbiology and Molecular Genetics Committee Chair: Andrew P. VanDemark, Ph.D., Associate Professor, Biological Sciences ii Copyright © by Adam D. Wier 2014 iii STRUCTURAL AND FUNCTIONAL CHARACTERIZATION OF RTF1 AND INSIGHT INTO ITS ROLE IN TRANSCRIPTIONAL REGULATION Adam D. Wier, PhD University of Pittsburgh, 2014 Originally discovered in a search for RNA polymerase II-associated factors, the Paf1 complex (Paf1C) is best characterized for its roles in regulating transcription elongation. The complex co- localizes with RNA polymerase II from the promoter to the 3’ end of genes and has been linked to a growing list of transcription-related processes including: elongation through chromatin, histone modifications, and recruitment of factors important in transcript maturation. The complex is conserved throughout eukaryotes and is comprised of the proteins Paf1, Ctr9, Cdc73, Rtf1, and Leo1. The domain structures of Paf1C subunits are largely undefined and have few clear homologs, making it difficult to postulate for or localize functions to the individual subunits. -
Unbiased Data Mining Identifies Cell Cycle Transcripts That Predict Non-Indolent Gleason Score 7 Prostate Cancer Wendy L
Johnston et al. BMC Urology (2019) 19:4 https://doi.org/10.1186/s12894-018-0433-5 RESEARCHARTICLE Open Access Unbiased data mining identifies cell cycle transcripts that predict non-indolent Gleason score 7 prostate cancer Wendy L. Johnston1* , Charles N. Catton1,2 and Carol J. Swallow3,4,5,6 Abstract Background: Patients with newly diagnosed non-metastatic prostate adenocarcinoma are typically classified as at low, intermediate, or high risk of disease progression using blood prostate-specific antigen concentration, tumour T category, and tumour pathological Gleason score. Classification is used to both predict clinical outcome and to inform initial management. However, significant heterogeneity is observed in outcome, particularly within the intermediate risk group, and there is an urgent need for additional markers to more accurately hone risk prediction. Recently developed web-based visualization and analysis tools have facilitated rapid interrogation of large transcriptome datasets, and querying broadly across multiple large datasets should identify predictors that are widely applicable. Methods: We used camcAPP, cBioPortal, CRN, and NIH NCI GDC Data Portal to data mine publicly available large prostate cancer datasets. A test set of biomarkers was developed by identifying transcripts that had: 1) altered abundance in prostate cancer, 2) altered expression in patients with Gleason score 7 tumours and biochemical recurrence, 3) correlation of expression with time until biochemical recurrence across three datasets (Cambridge, Stockholm, MSKCC). Transcripts that met these criteria were then examined in a validation dataset (TCGA-PRAD) using univariate and multivariable models to predict biochemical recurrence in patients with Gleason score 7 tumours. Results: Twenty transcripts met the test criteria, and 12 were validated in TCGA-PRAD Gleason score 7 patients. -
Supplementary Information – Postema Et Al., the Genetics of Situs Inversus Totalis Without Primary Ciliary Dyskinesia
1 Supplementary information – Postema et al., The genetics of situs inversus totalis without primary ciliary dyskinesia Table of Contents: Supplementary Methods 2 Supplementary Results 5 Supplementary References 6 Supplementary Tables and Figures Table S1. Subject characteristics 9 Table S2. Inbreeding coefficients per subject 10 Figure S1. Multidimensional scaling to capture overall genomic diversity 11 among the 30 study samples Table S3. Significantly enriched gene-sets under a recessive mutation model 12 Table S4. Broader list of candidate genes, and the sources that led to their 13 inclusion Table S5. Potential recessive and X-linked mutations in the unsolved cases 15 Table S6. Potential mutations in the unsolved cases, dominant model 22 2 1.0 Supplementary Methods 1.1 Participants Fifteen people with radiologically documented SIT, including nine without PCD and six with Kartagener syndrome, and 15 healthy controls matched for age, sex, education and handedness, were recruited from Ghent University Hospital and Middelheim Hospital Antwerp. Details about the recruitment and selection procedure have been described elsewhere (1). Briefly, among the 15 people with radiologically documented SIT, those who had symptoms reminiscent of PCD, or who were formally diagnosed with PCD according to their medical record, were categorized as having Kartagener syndrome. Those who had no reported symptoms or formal diagnosis of PCD were assigned to the non-PCD SIT group. Handedness was assessed using the Edinburgh Handedness Inventory (EHI) (2). Tables 1 and S1 give overviews of the participants and their characteristics. Note that one non-PCD SIT subject reported being forced to switch from left- to right-handedness in childhood, in which case five out of nine of the non-PCD SIT cases are naturally left-handed (Table 1, Table S1). -
Role of Transcription Factors AP-2 and NFI in Development and Glioblastoma by Saket Jain a Thesis Submitted in Partial Fulfillm
Role of Transcription Factors AP-2 and NFI in Development and Glioblastoma by Saket Jain A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Experimental Oncology Department of Oncology University of Alberta ©Saket Jain, 2018 Abstract Gene regulation pathways involved in embryonic development are commonly implicated in cancer. Transcription factors play key roles in all aspects of development including cell proliferation, migration and differentiation. Aberrant expression of many developmentally-regulated transcription factors contributes to many malignancies. In this thesis, we studied the role of transcription factor family AP-2 in retinal development and glioblastoma (GBM) and the role of transcription factor family NFI in GBM. Four of the five members of the AP-2 family (AP-2α, AP-2β, AP-2 and AP-2) have previously been shown to be expressed in developing retina. In Chapter 2, we show that the fifth member of the AP-2 family, AP-2ε, is also expressed in the developing mammalian retina. Our data point to a specialized role for AP-2 in a subset of amacrine cells, with AP-2 being restricted to the GABAergic amacrine lineage. AP-2 is co-expressed with AP-2, AP-2β and AP-2 in subsets of amacrine cells, suggesting roles for both AP-2 homodimers and AP-2 heterodimers in the regulation or AP-2 target genes in the retina. Our work suggests spatially- and temporally-coordinated roles for combinations of AP-2 transcription factors in amacrine cells during retinal development. Several studies have implicated aberrant regulation of AP-2 with cancer. -
Dynamics of Transcription Elongation Are Finely Tuned by Dozens of Regulatory Factors
bioRxiv preprint doi: https://doi.org/10.1101/2021.08.15.456358; this version posted August 15, 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 4.0 International license. Dynamics of transcription elongation are finely tuned by dozens of regulatory factors Mary Couvillion1*, Kevin M. Harlen1*, Kate C. Lachance1*, Kristine L. Trotta1, Erin Smith1, Christian Brion1, Brendan M. Smalec1, L. Stirling Churchman1 1Blavatnik Institute, Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA 02115 *these authors contributed equally 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.08.15.456358; this version posted August 15, 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 4.0 International license. ABSTRACT Understanding the complex network and dynamics that regulate transcription elongation requires the quantitative analysis of RNA polymerase II (Pol II) activity in a wide variety of regulatory environments. We performed native elongating transcript sequencing (NET-seq) in 41 strains of S. cerevisiae lacking known elongation regulators, including RNA processing factors, transcription elongation factors, chromatin modifiers, and remodelers. We found that the opposing effects of these factors balance transcription elongation dynamics. Different sets of factors tightly regulate Pol II progression across gene bodies so that Pol II density peaks at key points of RNA processing.