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TBXA2R Rsnps, Transcriptional Factor Binding Sites and Asthma in Asians
Open Journal of Pediatrics, 2014, 4, 148-161 Published Online June 2014 in SciRes. http://www.scirp.org/journal/ojped http://dx.doi.org/10.4236/ojped.2014.42021 TBXA2R rSNPs, Transcriptional Factor Binding Sites and Asthma in Asians Norman E. Buroker Department of Pediatrics, University of Washington, Seattle, USA Email: [email protected] Received 25 January 2014; revised 20 February 2014; accepted 27 February 2014 Copyright © 2014 by author and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract Four regulatory single nucleotide polymorphisms (rSNPs) (rs2238631, rs2238632, rs2238633 and rs2238634) in intron one, two rSNPs (rs1131882 and rs4523) in exon 3 and one rSNP (rs5756) in the 3’UTR of the thromboxane A2 receptor (TBXA2R) gene have been associated with childhood- onset asthma in Asians. These rSNP alleles alter the DNA landscape for potential transcriptional factors (TFs) to attach resulting in changes in transcriptional factor binding sites (TFBS). These TFBS changes are examined with respect to asthma which has been found to be significantly asso- ciated with the rSNPs. Keywords TBXA2R, rSNPs, TFBS, Asthma 1. Introduction Asthma is a chronic inflammatory condition of the airways characterized by recurrent episodes of reversible air- way obstruction and increased bronchial hyper-responsiveness which results from the interactions between gen- es and environmental factors [1]-[3]. Asthma causes episodes of wheeze, cough, and shortness of breath [4]. Re- cent studies indicate that the genetic factors of childhood-onset asthma differ from those of adult-onset asthma [3] [5]. -
Activated Peripheral-Blood-Derived Mononuclear Cells
Transcription factor expression in lipopolysaccharide- activated peripheral-blood-derived mononuclear cells Jared C. Roach*†, Kelly D. Smith*‡, Katie L. Strobe*, Stephanie M. Nissen*, Christian D. Haudenschild§, Daixing Zhou§, Thomas J. Vasicek¶, G. A. Heldʈ, Gustavo A. Stolovitzkyʈ, Leroy E. Hood*†, and Alan Aderem* *Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103; ‡Department of Pathology, University of Washington, Seattle, WA 98195; §Illumina, 25861 Industrial Boulevard, Hayward, CA 94545; ¶Medtronic, 710 Medtronic Parkway, Minneapolis, MN 55432; and ʈIBM Computational Biology Center, P.O. Box 218, Yorktown Heights, NY 10598 Contributed by Leroy E. Hood, August 21, 2007 (sent for review January 7, 2007) Transcription factors play a key role in integrating and modulating system. In this model system, we activated peripheral-blood-derived biological information. In this study, we comprehensively measured mononuclear cells, which can be loosely termed ‘‘macrophages,’’ the changing abundances of mRNAs over a time course of activation with lipopolysaccharide (LPS). We focused on the precise mea- of human peripheral-blood-derived mononuclear cells (‘‘macro- surement of mRNA concentrations. There is currently no high- phages’’) with lipopolysaccharide. Global and dynamic analysis of throughput technology that can precisely and sensitively measure all transcription factors in response to a physiological stimulus has yet to mRNAs in a system, although such technologies are likely to be be achieved in a human system, and our efforts significantly available in the near future. To demonstrate the potential utility of advanced this goal. We used multiple global high-throughput tech- such technologies, and to motivate their development and encour- nologies for measuring mRNA levels, including massively parallel age their use, we produced data from a combination of two distinct signature sequencing and GeneChip microarrays. -
Core Transcriptional Regulatory Circuitries in Cancer
Oncogene (2020) 39:6633–6646 https://doi.org/10.1038/s41388-020-01459-w REVIEW ARTICLE Core transcriptional regulatory circuitries in cancer 1 1,2,3 1 2 1,4,5 Ye Chen ● Liang Xu ● Ruby Yu-Tong Lin ● Markus Müschen ● H. Phillip Koeffler Received: 14 June 2020 / Revised: 30 August 2020 / Accepted: 4 September 2020 / Published online: 17 September 2020 © The Author(s) 2020. This article is published with open access Abstract Transcription factors (TFs) coordinate the on-and-off states of gene expression typically in a combinatorial fashion. Studies from embryonic stem cells and other cell types have revealed that a clique of self-regulated core TFs control cell identity and cell state. These core TFs form interconnected feed-forward transcriptional loops to establish and reinforce the cell-type- specific gene-expression program; the ensemble of core TFs and their regulatory loops constitutes core transcriptional regulatory circuitry (CRC). Here, we summarize recent progress in computational reconstitution and biologic exploration of CRCs across various human malignancies, and consolidate the strategy and methodology for CRC discovery. We also discuss the genetic basis and therapeutic vulnerability of CRC, and highlight new frontiers and future efforts for the study of CRC in cancer. Knowledge of CRC in cancer is fundamental to understanding cancer-specific transcriptional addiction, and should provide important insight to both pathobiology and therapeutics. 1234567890();,: 1234567890();,: Introduction genes. Till now, one critical goal in biology remains to understand the composition and hierarchy of transcriptional Transcriptional regulation is one of the fundamental mole- regulatory network in each specified cell type/lineage. -
Cellular Responses to Erbb-2 Overexpression in Human Mammary Luminal Epithelial Cells: Comparison of Mrna and Protein Expression
British Journal of Cancer (2004) 90, 173 – 181 & 2004 Cancer Research UK All rights reserved 0007 – 0920/04 $25.00 www.bjcancer.com Cellular responses to ErbB-2 overexpression in human mammary luminal epithelial cells: comparison of mRNA and protein expression SL White1, S Gharbi1, MF Bertani1, H-L Chan1, MD Waterfield1 and JF Timms*,1 1 Ludwig Institute for Cancer Research, Wing 1.1, Cruciform Building, Gower Street, London WCIE 6BT, UK Microarray analysis offers a powerful tool for studying the mechanisms of cellular transformation, although the correlation between mRNA and protein expression is largely unknown. In this study, a microarray analysis was performed to compare transcription in response to overexpression of the ErbB-2 receptor tyrosine kinase in a model mammary luminal epithelial cell system, and in response to the ErbB-specific growth factor heregulin b1. We sought to validate mRNA changes by monitoring changes at the protein level using a parallel proteomics strategy, and report a surprisingly high correlation between transcription and translation for the subset of genes studied. We further characterised the identified targets and relate differential expression to changes in the biological properties of ErbB-2-overexpressing cells. We found differential regulation of several key cell cycle modulators, including cyclin D2, and downregulation of a large number of interferon-inducible genes, consistent with increased proliferation of the ErbB-2- overexpressing cells. Furthermore, differential expression of genes involved in extracellular matrix modelling and cellular adhesion was linked to altered adhesion of these cells. Finally, we provide evidence for enhanced autocrine activation of MAPK signalling and the AP-1 transcription complex. -
Ovarian Gene Expression in the Absence of FIGLA, an Oocyte
BMC Developmental Biology BioMed Central Research article Open Access Ovarian gene expression in the absence of FIGLA, an oocyte-specific transcription factor Saurabh Joshi*1, Holly Davies1, Lauren Porter Sims2, Shawn E Levy2 and Jurrien Dean1 Address: 1Laboratory of Cellular and Developmental Biology, NIDDK, National Institutes of Health, Bethesda, MD 20892, USA and 2Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA Email: Saurabh Joshi* - [email protected]; Holly Davies - [email protected]; Lauren Porter Sims - [email protected]; Shawn E Levy - [email protected]; Jurrien Dean - [email protected] * Corresponding author Published: 13 June 2007 Received: 11 December 2006 Accepted: 13 June 2007 BMC Developmental Biology 2007, 7:67 doi:10.1186/1471-213X-7-67 This article is available from: http://www.biomedcentral.com/1471-213X/7/67 © 2007 Joshi et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: Ovarian folliculogenesis in mammals is a complex process involving interactions between germ and somatic cells. Carefully orchestrated expression of transcription factors, cell adhesion molecules and growth factors are required for success. We have identified a germ-cell specific, basic helix-loop-helix transcription factor, FIGLA (Factor In the GermLine, Alpha) and demonstrated its involvement in two independent developmental processes: formation of the primordial follicle and coordinate expression of zona pellucida genes. Results: Taking advantage of Figla null mouse lines, we have used a combined approach of microarray and Serial Analysis of Gene Expression (SAGE) to identify potential downstream target genes. -
Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model
Downloaded from http://www.jimmunol.org/ by guest on September 25, 2021 T + is online at: average * The Journal of Immunology , 34 of which you can access for free at: 2016; 197:1477-1488; Prepublished online 1 July from submission to initial decision 4 weeks from acceptance to publication 2016; doi: 10.4049/jimmunol.1600589 http://www.jimmunol.org/content/197/4/1477 Molecular Profile of Tumor-Specific CD8 Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. Waugh, Sonia M. Leach, Brandon L. Moore, Tullia C. Bruno, Jonathan D. Buhrman and Jill E. Slansky J Immunol cites 95 articles Submit online. Every submission reviewed by practicing scientists ? is published twice each month by Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts http://jimmunol.org/subscription Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html http://www.jimmunol.org/content/suppl/2016/07/01/jimmunol.160058 9.DCSupplemental This article http://www.jimmunol.org/content/197/4/1477.full#ref-list-1 Information about subscribing to The JI No Triage! Fast Publication! Rapid Reviews! 30 days* Why • • • Material References Permissions Email Alerts Subscription Supplementary The Journal of Immunology The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. This information is current as of September 25, 2021. The Journal of Immunology Molecular Profile of Tumor-Specific CD8+ T Cell Hypofunction in a Transplantable Murine Cancer Model Katherine A. -
Roles of the CSE1L-Mediated Nuclear Import Pathway in Epigenetic
Roles of the CSE1L-mediated nuclear import pathway PNAS PLUS in epigenetic silencing Qiang Donga,b,c, Xiang Lia,b,c, Cheng-Zhi Wangb, Shaohua Xuc, Gang Yuanc, Wei Shaoc, Baodong Liud, Yong Zhengb, Hailin Wangd, Xiaoguang Leic,e,f, Zhuqiang Zhangb,1, and Bing Zhua,b,g,1 aGraduate Program, Peking Union Medical College and Chinese Academy of Medical Sciences, 100730 Beijing, China; bNational Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101 Beijing, China; cNational Institute of Biological Sciences, 102206 Beijing, China; dThe State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 100085 Beijing, China; eBeijing National Laboratory for Molecular Sciences, Department of Chemical Biology, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China; fPeking-Tsinghua Center for Life Sciences, Peking University, 100871 Beijing, China; and gCollege of Life Sciences, University of Chinese Academy of Sciences, 100049 Beijing, China Edited by Arthur D. Riggs, Beckman Research Institute of City of Hope, Duarte, CA, and approved March 21, 2018 (received for review January 17, 2018) Epigenetic silencing can be mediated by various mechanisms, CSE1L, a key player in the nuclear import pathway, as an es- and many regulators remain to be identified. Here, we report a sential factor for maintaining the repression of many methyl- genome-wide siRNA screening to identify regulators essential for ated genes. Mechanistically, CSE1L functions by facilitating maintaining gene repression of a CMV promoter silenced by DNA the nuclear import of certain cargo proteins that are essential methylation. -
CCAAT/Enhancer Binding Protein Epsilon) Thomas Burmeister Charite, Med
Atlas of Genetics and Cytogenetics in Oncology and Haematology OPEN ACCESS JOURNAL INIST-CNRS Gene Section Short Communication CEBPE (CCAAT/enhancer binding protein epsilon) Thomas Burmeister Charite, Med. Klinik fur Hamatologie, Onkologie und Tumorimmunologie, Hindenburgdamm 30, 12200 Berlin, Germany; [email protected] Published in Atlas Database: March 2017 Online updated version : http://AtlasGeneticsOncology.org/Genes/CEBPEID42984ch14q11.html Printable original version : http://documents.irevues.inist.fr/bitstream/handle/2042/69005/03-2017-CEBPEID42984ch14q11.pdf DOI: 10.4267/2042/69005 This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 2.0 France Licence. © 2017 Atlas of Genetics and Cytogenetics in Oncology and Haematology alternative 3-exon-organization of the human Abstract CEBPE gene (Figure 1b). However, exon 1, as described by Yamanaka et al. contains a frameshift Review on CEBPE, with data on DNA, on the according to the GRCh38.p7 NCBI assembly. protein encoded, and where the gene is implicated. Transcription Keywords CEBPE; Transcription factor; Neutrophil specific Various transcripts have been reported, resulting in granule deficiency; Acute lymphoblastic leukemia; four protein isoforms (Lekstrom-Himes 2001, Translocation. Yamanaka 1997; Figure 1c). All transcripts share a common 3' end. Identity Protein Other names: CRP1 Description HGNC (Hugo): CEBPE CEBPE is a member of the CCAAT/enhancer- Location: 14q11.2 binding protein (C/EBP) family, which also Location (base pair) includes CEBPA, CEBPB, CEBPG, CEBPD and Starts at 23117306 and ends at 23119611 bp from CEBPZ (Ramji & Foka; 2002). A common pter (according to GRCh38.p7 Annotation Release structural feature of the C/EBP proteins is the 108, May 5 2016) presence of a highly conserved 55-65 amino acid sequence at the C-terminus which encodes a basic DNA/RNA leucine zipper motif (bZIP domain) that functions as a dimerization domain. -
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 ............................................................................................................. -
Table S1 the Four Gene Sets Derived from Gene Expression Profiles of Escs and Differentiated Cells
Table S1 The four gene sets derived from gene expression profiles of ESCs and differentiated cells Uniform High Uniform Low ES Up ES Down EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol EntrezID GeneSymbol 269261 Rpl12 11354 Abpa 68239 Krt42 15132 Hbb-bh1 67891 Rpl4 11537 Cfd 26380 Esrrb 15126 Hba-x 55949 Eef1b2 11698 Ambn 73703 Dppa2 15111 Hand2 18148 Npm1 11730 Ang3 67374 Jam2 65255 Asb4 67427 Rps20 11731 Ang2 22702 Zfp42 17292 Mesp1 15481 Hspa8 11807 Apoa2 58865 Tdh 19737 Rgs5 100041686 LOC100041686 11814 Apoc3 26388 Ifi202b 225518 Prdm6 11983 Atpif1 11945 Atp4b 11614 Nr0b1 20378 Frzb 19241 Tmsb4x 12007 Azgp1 76815 Calcoco2 12767 Cxcr4 20116 Rps8 12044 Bcl2a1a 219132 D14Ertd668e 103889 Hoxb2 20103 Rps5 12047 Bcl2a1d 381411 Gm1967 17701 Msx1 14694 Gnb2l1 12049 Bcl2l10 20899 Stra8 23796 Aplnr 19941 Rpl26 12096 Bglap1 78625 1700061G19Rik 12627 Cfc1 12070 Ngfrap1 12097 Bglap2 21816 Tgm1 12622 Cer1 19989 Rpl7 12267 C3ar1 67405 Nts 21385 Tbx2 19896 Rpl10a 12279 C9 435337 EG435337 56720 Tdo2 20044 Rps14 12391 Cav3 545913 Zscan4d 16869 Lhx1 19175 Psmb6 12409 Cbr2 244448 Triml1 22253 Unc5c 22627 Ywhae 12477 Ctla4 69134 2200001I15Rik 14174 Fgf3 19951 Rpl32 12523 Cd84 66065 Hsd17b14 16542 Kdr 66152 1110020P15Rik 12524 Cd86 81879 Tcfcp2l1 15122 Hba-a1 66489 Rpl35 12640 Cga 17907 Mylpf 15414 Hoxb6 15519 Hsp90aa1 12642 Ch25h 26424 Nr5a2 210530 Leprel1 66483 Rpl36al 12655 Chi3l3 83560 Tex14 12338 Capn6 27370 Rps26 12796 Camp 17450 Morc1 20671 Sox17 66576 Uqcrh 12869 Cox8b 79455 Pdcl2 20613 Snai1 22154 Tubb5 12959 Cryba4 231821 Centa1 17897 -
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. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4).