Profiling Dynamic Chromatome Reveals HP1BP3 As a Key Regulator of Cell Cycle and Hypoxia Cancer Progression
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Functional Compensation Among HMGN Variants Modulates the Dnase I Hypersensitive Sites at Enhancers
Downloaded from genome.cshlp.org on October 9, 2021 - Published by Cold Spring Harbor Laboratory Press Research Functional compensation among HMGN variants modulates the DNase I hypersensitive sites at enhancers Tao Deng,1,12 Z. Iris Zhu,2,12 Shaofei Zhang,1 Yuri Postnikov,1 Di Huang,2 Marion Horsch,3 Takashi Furusawa,1 Johannes Beckers,3,4,5 Jan Rozman,3,5 Martin Klingenspor,6,7 Oana Amarie,3,8 Jochen Graw,3,8 Birgit Rathkolb,3,5,9 Eckhard Wolf,9 Thure Adler,3 Dirk H. Busch,10 Valérie Gailus-Durner,3 Helmut Fuchs,3 Martin Hrabeˇ de Angelis,3,4,5 Arjan van der Velde,2,13 Lino Tessarollo,11 Ivan Ovcherenko,2 David Landsman,2 and Michael Bustin1 1Protein Section, Laboratory of Metabolism, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892, USA; 2Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, Bethesda, Maryland 20892, USA; 3German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany; 4Experimental Genetics, Center of Life and Food Sciences Weihenstephan, Technische Universität München, 85354 Freising-Weihenstephan, Germany; 5German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany; 6Molecular Nutritional Medicine, Technische Universität München, 85350 Freising, Germany; 7Center for Nutrition and Food Sciences, Technische Universität München, 85350 Freising, Germany; 8Institute of Developmental Genetics (IDG), 85764 -
A Yeast Phenomic Model for the Gene Interaction Network Modulating
Louie et al. Genome Medicine 2012, 4:103 http://genomemedicine.com/content/4/12/103 RESEARCH Open Access A yeast phenomic model for the gene interaction network modulating CFTR-ΔF508 protein biogenesis Raymond J Louie3†, Jingyu Guo1,2†, John W Rodgers1, Rick White4, Najaf A Shah1, Silvere Pagant3, Peter Kim3, Michael Livstone5, Kara Dolinski5, Brett A McKinney6, Jeong Hong2, Eric J Sorscher2, Jennifer Bryan4, Elizabeth A Miller3* and John L Hartman IV1,2* Abstract Background: The overall influence of gene interaction in human disease is unknown. In cystic fibrosis (CF) a single allele of the cystic fibrosis transmembrane conductance regulator (CFTR-ΔF508) accounts for most of the disease. In cell models, CFTR-ΔF508 exhibits defective protein biogenesis and degradation rather than proper trafficking to the plasma membrane where CFTR normally functions. Numerous genes function in the biogenesis of CFTR and influence the fate of CFTR-ΔF508. However it is not known whether genetic variation in such genes contributes to disease severity in patients. Nor is there an easy way to study how numerous gene interactions involving CFTR-ΔF would manifest phenotypically. Methods: To gain insight into the function and evolutionary conservation of a gene interaction network that regulates biogenesis of a misfolded ABC transporter, we employed yeast genetics to develop a ‘phenomic’ model, in which the CFTR-ΔF508-equivalent residue of a yeast homolog is mutated (Yor1-ΔF670), and where the genome is scanned quantitatively for interaction. We first confirmed that Yor1-ΔF undergoes protein misfolding and has reduced half-life, analogous to CFTR-ΔF. Gene interaction was then assessed quantitatively by growth curves for approximately 5,000 double mutants, based on alteration in the dose response to growth inhibition by oligomycin, a toxin extruded from the cell at the plasma membrane by Yor1. -
The Capacity of Long-Term in Vitro Proliferation of Acute Myeloid
The Capacity of Long-Term in Vitro Proliferation of Acute Myeloid Leukemia Cells Supported Only by Exogenous Cytokines Is Associated with a Patient Subset with Adverse Outcome Annette K. Brenner, Elise Aasebø, Maria Hernandez-Valladares, Frode Selheim, Frode Berven, Ida-Sofie Grønningsæter, Sushma Bartaula-Brevik and Øystein Bruserud Supplementary Material S2 of S31 Table S1. Detailed information about the 68 AML patients included in the study. # of blasts Viability Proliferation Cytokine Viable cells Change in ID Gender Age Etiology FAB Cytogenetics Mutations CD34 Colonies (109/L) (%) 48 h (cpm) secretion (106) 5 weeks phenotype 1 M 42 de novo 241 M2 normal Flt3 pos 31.0 3848 low 0.24 7 yes 2 M 82 MF 12.4 M2 t(9;22) wt pos 81.6 74,686 low 1.43 969 yes 3 F 49 CML/relapse 149 M2 complex n.d. pos 26.2 3472 low 0.08 n.d. no 4 M 33 de novo 62.0 M2 normal wt pos 67.5 6206 low 0.08 6.5 no 5 M 71 relapse 91.0 M4 normal NPM1 pos 63.5 21,331 low 0.17 n.d. yes 6 M 83 de novo 109 M1 n.d. wt pos 19.1 8764 low 1.65 693 no 7 F 77 MDS 26.4 M1 normal wt pos 89.4 53,799 high 3.43 2746 no 8 M 46 de novo 26.9 M1 normal NPM1 n.d. n.d. 3472 low 1.56 n.d. no 9 M 68 MF 50.8 M4 normal D835 pos 69.4 1640 low 0.08 n.d. -
Co-Expression Module Analysis Reveals Biological Processes
Shi et al. BMC Systems Biology 2010, 4:74 http://www.biomedcentral.com/1752-0509/4/74 RESEARCH ARTICLE Open Access Co-expressionResearch article module analysis reveals biological processes, genomic gain, and regulatory mechanisms associated with breast cancer progression Zhiao Shi1,2, Catherine K Derow3 and Bing Zhang*3 Abstract Background: Gene expression signatures are typically identified by correlating gene expression patterns to a disease phenotype of interest. However, individual gene-based signatures usually suffer from low reproducibility and interpretability. Results: We have developed a novel algorithm Iterative Clique Enumeration (ICE) for identifying relatively independent maximal cliques as co-expression modules and a module-based approach to the analysis of gene expression data. Applying this approach on a public breast cancer dataset identified 19 modules whose expression levels were significantly correlated with tumor grade. The correlations were reproducible for 17 modules in an independent breast cancer dataset, and the reproducibility was considerably higher than that based on individual genes or modules identified by other algorithms. Sixteen out of the 17 modules showed significant enrichment in certain Gene Ontology (GO) categories. Specifically, modules related to cell proliferation and immune response were up-regulated in high- grade tumors while those related to cell adhesion was down-regulated. Further analyses showed that transcription factors NYFB, E2F1/E2F3, NRF1, and ELK1 were responsible for the up-regulation of the cell proliferation modules. IRF family and ETS family proteins were responsible for the up-regulation of the immune response modules. Moreover, inhibition of the PPARA signaling pathway may also play an important role in tumor progression. -
The Interactome of KRAB Zinc Finger Proteins Reveals the Evolutionary History of Their Functional Diversification
Resource The interactome of KRAB zinc finger proteins reveals the evolutionary history of their functional diversification Pierre-Yves Helleboid1,†, Moritz Heusel2,†, Julien Duc1, Cécile Piot1, Christian W Thorball1, Andrea Coluccio1, Julien Pontis1, Michaël Imbeault1, Priscilla Turelli1, Ruedi Aebersold2,3,* & Didier Trono1,** Abstract years ago (MYA) (Imbeault et al, 2017). Their products harbor an N-terminal KRAB (Kru¨ppel-associated box) domain related to that of Krüppel-associated box (KRAB)-containing zinc finger proteins Meisetz (a.k.a. PRDM9), a protein that originated prior to the diver- (KZFPs) are encoded in the hundreds by the genomes of higher gence of chordates and echinoderms, and a C-terminal array of zinc vertebrates, and many act with the heterochromatin-inducing fingers (ZNF) with sequence-specific DNA-binding potential (Urru- KAP1 as repressors of transposable elements (TEs) during early tia, 2003; Birtle & Ponting, 2006; Imbeault et al, 2017). KZFP genes embryogenesis. Yet, their widespread expression in adult tissues multiplied by gene and segment duplication to count today more and enrichment at other genetic loci indicate additional roles. than 350 and 700 representatives in the human and mouse Here, we characterized the protein interactome of 101 of the ~350 genomes, respectively (Urrutia, 2003; Kauzlaric et al, 2017). A human KZFPs. Consistent with their targeting of TEs, most KZFPs majority of human KZFPs including all primate-restricted family conserved up to placental mammals essentially recruit KAP1 and members target sequences derived from TEs, that is, DNA trans- associated effectors. In contrast, a subset of more ancient KZFPs posons, ERVs (endogenous retroviruses), LINEs, SINEs (long and rather interacts with factors related to functions such as genome short interspersed nuclear elements, respectively), or SVAs (SINE- architecture or RNA processing. -
HMGB1 in Health and Disease R
Donald and Barbara Zucker School of Medicine Journal Articles Academic Works 2014 HMGB1 in health and disease R. Kang R. C. Chen Q. H. Zhang W. Hou S. Wu See next page for additional authors Follow this and additional works at: https://academicworks.medicine.hofstra.edu/articles Part of the Emergency Medicine Commons Recommended Citation Kang R, Chen R, Zhang Q, Hou W, Wu S, Fan X, Yan Z, Sun X, Wang H, Tang D, . HMGB1 in health and disease. 2014 Jan 01; 40():Article 533 [ p.]. Available from: https://academicworks.medicine.hofstra.edu/articles/533. Free full text article. This Article is brought to you for free and open access by Donald and Barbara Zucker School of Medicine Academic Works. It has been accepted for inclusion in Journal Articles by an authorized administrator of Donald and Barbara Zucker School of Medicine Academic Works. Authors R. Kang, R. C. Chen, Q. H. Zhang, W. Hou, S. Wu, X. G. Fan, Z. W. Yan, X. F. Sun, H. C. Wang, D. L. Tang, and +8 additional authors This article is available at Donald and Barbara Zucker School of Medicine Academic Works: https://academicworks.medicine.hofstra.edu/articles/533 NIH Public Access Author Manuscript Mol Aspects Med. Author manuscript; available in PMC 2015 December 01. NIH-PA Author ManuscriptPublished NIH-PA Author Manuscript in final edited NIH-PA Author Manuscript form as: Mol Aspects Med. 2014 December ; 0: 1–116. doi:10.1016/j.mam.2014.05.001. HMGB1 in Health and Disease Rui Kang1,*, Ruochan Chen1, Qiuhong Zhang1, Wen Hou1, Sha Wu1, Lizhi Cao2, Jin Huang3, Yan Yu2, Xue-gong Fan4, Zhengwen Yan1,5, Xiaofang Sun6, Haichao Wang7, Qingde Wang1, Allan Tsung1, Timothy R. -
Noelia Díaz Blanco
Effects of environmental factors on the gonadal transcriptome of European sea bass (Dicentrarchus labrax), juvenile growth and sex ratios Noelia Díaz Blanco Ph.D. thesis 2014 Submitted in partial fulfillment of the requirements for the Ph.D. degree from the Universitat Pompeu Fabra (UPF). This work has been carried out at the Group of Biology of Reproduction (GBR), at the Department of Renewable Marine Resources of the Institute of Marine Sciences (ICM-CSIC). Thesis supervisor: Dr. Francesc Piferrer Professor d’Investigació Institut de Ciències del Mar (ICM-CSIC) i ii A mis padres A Xavi iii iv Acknowledgements This thesis has been made possible by the support of many people who in one way or another, many times unknowingly, gave me the strength to overcome this "long and winding road". First of all, I would like to thank my supervisor, Dr. Francesc Piferrer, for his patience, guidance and wise advice throughout all this Ph.D. experience. But above all, for the trust he placed on me almost seven years ago when he offered me the opportunity to be part of his team. Thanks also for teaching me how to question always everything, for sharing with me your enthusiasm for science and for giving me the opportunity of learning from you by participating in many projects, collaborations and scientific meetings. I am also thankful to my colleagues (former and present Group of Biology of Reproduction members) for your support and encouragement throughout this journey. To the “exGBRs”, thanks for helping me with my first steps into this world. Working as an undergrad with you Dr. -
RNA Editing at Baseline and Following Endoplasmic Reticulum Stress
RNA Editing at Baseline and Following Endoplasmic Reticulum Stress By Allison Leigh Richards A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Human Genetics) in The University of Michigan 2015 Doctoral Committee: Professor Vivian G. Cheung, Chair Assistant Professor Santhi K. Ganesh Professor David Ginsburg Professor Daniel J. Klionsky Dedication To my father, mother, and Matt without whom I would never have made it ii Acknowledgements Thank you first and foremost to my dissertation mentor, Dr. Vivian Cheung. I have learned so much from you over the past several years including presentation skills such as never sighing and never saying “as you can see…” You have taught me how to think outside the box and how to create and explain my story to others. I would not be where I am today without your help and guidance. Thank you to the members of my dissertation committee (Drs. Santhi Ganesh, David Ginsburg and Daniel Klionsky) for all of your advice and support. I would also like to thank the entire Human Genetics Program, and especially JoAnn Sekiguchi and Karen Grahl, for welcoming me to the University of Michigan and making my transition so much easier. Thank you to Michael Boehnke and the Genome Science Training Program for supporting my work. A very special thank you to all of the members of the Cheung lab, past and present. Thank you to Xiaorong Wang for all of your help from the bench to advice on my career. Thank you to Zhengwei Zhu who has helped me immensely throughout my thesis even through my panic. -
Systems Genetics Identifies Hp1bp3 As a Novel Modulator of Cognitive
Neurobiology of Aging 46 (2016) 58e67 Contents lists available at ScienceDirect Neurobiology of Aging journal homepage: www.elsevier.com/locate/neuaging Systems genetics identifies Hp1bp3 as a novel modulator of cognitive aging Sarah M. Neuner a, Benjamin P. Garfinkel b,c,1, Lynda A. Wilmott a,1, Bogna M. Ignatowska-Jankowska c, Ami Citri c, Joseph Orly b,LuLud, Rupert W. Overall e, Megan K. Mulligan d, Gerd Kempermann e,f, Robert W. Williams d, Kristen M.S. O’Connell g, Catherine C. Kaczorowski a,* a Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN 38163, USA b Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel c The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem 91904, Israel d Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN 38163, USA e CRTDeCenter for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden 01307, Germany f German Center for Neurodegenerative Diseases (DZNE) Dresden, Dresden 01307, Germany g Department of Physiology, University of Tennessee Health Science Center, Memphis, TN 38163, USA article info abstract Article history: An individual’s genetic makeup plays an important role in determining susceptibility to cognitive aging. Received 30 March 2016 Identifying the specific genes that contribute to cognitive aging may aid in early diagnosis of at-risk Received in revised form 7 June 2016 patients, as well as identify novel therapeutics targets to treat or prevent development of symptoms. Accepted 11 June 2016 Challenges to identifying these specific genes in human studies include complex genetics, difficulty in Available online 17 June 2016 controlling environmental factors, and limited access to human brain tissue. -
PDF Download
TFIIIC90 Polyclonal Antibody Catalog No : YT4623 Reactivity : Human,Rat,Mouse, Applications : WB,ELISA Gene Name : GTF3C4 Protein Name : General transcription factor 3C polypeptide 4 Human Gene Id : 9329 Human Swiss Prot Q9UKN8 No : Mouse Swiss Prot Q8BMQ2 No : Immunogen : The antiserum was produced against synthesized peptide derived from human TF3C4. AA range:611-660 Specificity : TFIIIC90 Polyclonal Antibody detects endogenous levels of TFIIIC90 protein. Formulation : Liquid in PBS containing 50% glycerol, 0.5% BSA and 0.02% sodium azide. Source : Rabbit Dilution : Western Blot: 1/500 - 1/2000. ELISA: 1/20000. Not yet tested in other applications. Purification : The antibody was affinity-purified from rabbit antiserum by affinity- chromatography using epitope-specific immunogen. Concentration : 1 mg/ml Storage Stability : -20°C/1 year Molecularweight : 92001 Observed Band : 95 1 / 3 Background : catalytic activity:Acetyl-CoA + histone = CoA + acetylhistone.,function:Essential for RNA polymerase III to make a number of small nuclear and cytoplasmic RNAs, including 5S RNA, tRNA, and adenovirus-associated (VA) RNA of both cellular and viral origin. Has histone acetyltransferase activity (HAT) with unique specificity for free and nucleosomal H3. May cooperate with GTF3C5 in facilitating the recruitment of TFIIIB and RNA polymerase through direct interactions with BRF1, POLR3C and POLR3F. May be localized close to the A box.,sequence caution:Contaminating sequence. Potential poly-A sequence.,similarity:Belongs to the TFIIIC subunit 4 family.,subunit:Part of the TFIIIC subcomplex TFIIIC2, consisting of six subunits, GTF3C1, GTF3C2, GTF3C3, GTF3C4, GTF3C5 and GTF3C6. Interacts with BRF1, GTF3C1, GTF3C2, GTF3C5, GTF3C6, POLR3C and POLR3F., Function : catalytic activity:Acetyl-CoA + histone = CoA + acetylhistone.,function:Essential for RNA polymerase III to make a number of small nuclear and cytoplasmic RNAs, including 5S RNA, tRNA, and adenovirus-associated (VA) RNA of both cellular and viral origin. -
The Function and Evolution of C2H2 Zinc Finger Proteins and Transposons
The function and evolution of C2H2 zinc finger proteins and transposons by Laura Francesca Campitelli A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of Molecular Genetics University of Toronto © Copyright by Laura Francesca Campitelli 2020 The function and evolution of C2H2 zinc finger proteins and transposons Laura Francesca Campitelli Doctor of Philosophy Department of Molecular Genetics University of Toronto 2020 Abstract Transcription factors (TFs) confer specificity to transcriptional regulation by binding specific DNA sequences and ultimately affecting the ability of RNA polymerase to transcribe a locus. The C2H2 zinc finger proteins (C2H2 ZFPs) are a TF class with the unique ability to diversify their DNA-binding specificities in a short evolutionary time. C2H2 ZFPs comprise the largest class of TFs in Mammalian genomes, including nearly half of all Human TFs (747/1,639). Positive selection on the DNA-binding specificities of C2H2 ZFPs is explained by an evolutionary arms race with endogenous retroelements (EREs; copy-and-paste transposable elements), where the C2H2 ZFPs containing a KRAB repressor domain (KZFPs; 344/747 Human C2H2 ZFPs) are thought to diversify to bind new EREs and repress deleterious transposition events. However, evidence of the gain and loss of KZFP binding sites on the ERE sequence is sparse due to poor resolution of ERE sequence evolution, despite the recent publication of binding preferences for 242/344 Human KZFPs. The goal of my doctoral work has been to characterize the Human C2H2 ZFPs, with specific interest in their evolutionary history, functional diversity, and coevolution with LINE EREs. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A.