RNA Sequencing Reveals the Alteration of the Expression of Novel Genes in Ethanol-Treated Embryoid Bodies
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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 ............................................................................................................. -
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. -
A Clinicopathological and Molecular Genetic Analysis of Low-Grade Glioma in Adults
A CLINICOPATHOLOGICAL AND MOLECULAR GENETIC ANALYSIS OF LOW-GRADE GLIOMA IN ADULTS Presented by ANUSHREE SINGH MSc A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy Brain Tumour Research Centre Research Institute in Healthcare Sciences Faculty of Science and Engineering University of Wolverhampton November 2014 i DECLARATION This work or any part thereof has not previously been presented in any form to the University or to any other body whether for the purposes of assessment, publication or for any other purpose (unless otherwise indicated). Save for any express acknowledgments, references and/or bibliographies cited in the work, I confirm that the intellectual content of the work is the result of my own efforts and of no other person. The right of Anushree Singh to be identified as author of this work is asserted in accordance with ss.77 and 78 of the Copyright, Designs and Patents Act 1988. At this date copyright is owned by the author. Signature: Anushree Date: 30th November 2014 ii ABSTRACT The aim of the study was to identify molecular markers that can determine progression of low grade glioma. This was done using various approaches such as IDH1 and IDH2 mutation analysis, MGMT methylation analysis, copy number analysis using array comparative genomic hybridisation and identification of differentially expressed miRNAs using miRNA microarray analysis. IDH1 mutation was present at a frequency of 71% in low grade glioma and was identified as an independent marker for improved OS in a multivariate analysis, which confirms the previous findings in low grade glioma studies. -
Zinc-Finger Protein 471 Suppresses Gastric Cancer Through
Oncogene (2018) 37:3601–3616 https://doi.org/10.1038/s41388-018-0220-5 ARTICLE Zinc-finger protein 471 suppresses gastric cancer through transcriptionally repressing downstream oncogenic PLS3 and TFAP2A 1 1 1 2 1 3 Lei Cao ● Shiyan Wang ● Yanquan Zhang ● Ka-Chun Wong ● Geicho Nakatsu ● Xiaohong Wang ● 1 3 1 Sunny Wong ● Jiafu Ji ● Jun Yu Received: 28 June 2017 / Revised: 23 December 2017 / Accepted: 23 February 2018 / Published online: 3 April 2018 © The Author(s) 2018. This article is published with open access Abstract Zinc-finger protein 471 (ZNF471) was preferentially methylated in gastric cancer using promoter methylation array. The role of ZNF471 in human cancer is unclear. Here we elucidated the functional significance, molecular mechanisms and clinical impact of ZNF471 in gastric cancer. ZNF471 mRNA was silenced in 15 out of 16 gastric cancer cell lines due to promoter hypermethylation. Significantly higher ZNF471 promoter methylation was also observed in primary gastric cancers compared to their adjacent normal tissues (P<0.001). ZNF471 promoter CpG-site hypermethylation correlated with poor 1234567890();,: survival of gastric cancer patients (n = 120, P = 0.001). Ectopic expression of ZNF471 in gastric cancer cell lines (AGS, BGC823, and MKN74) significantly suppressed cell proliferation, migration, and invasion, while it induced apoptosis in vitro and inhibited xenograft tumorigenesis in nude mice. Transcription factor AP-2 Alpha (TFAP2A) and plastin3 (PLS3) were two crucial downstream targets of ZNF471 demonstrated by bioinformatics modeling and ChIP-PCR assays. ZNF471 directly bound to the promoter of TFAP2A and PLS3 and transcriptionally inhibited their expression. TFAP2A and PLS3 showed oncogenic functions in gastric cancer cell lines. -
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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/) -
Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K
www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1. -
CRISPR Activation Screening of Circulating Tumor Cells Identifies Enhancers of Blood-Based Metastasis
CRISPR Activation Screening of Circulating Tumor Cells Identifies Enhancers of Blood-Based Metastasis The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Ebright, Richard Yon. 2020. CRISPR Activation Screening of Circulating Tumor Cells Identifies Enhancers of Blood-Based Metastasis. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences. Citable link https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37365157 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA CRISPR activation screening of circulating tumor cells identifies enhancers of blood-based metastasis A dissertation presented by Richard Yon Ebright to The Division of Medical Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Biological and Biomedical Sciences Harvard University Cambridge, Massachusetts September 2019 © 2019 Richard Yon Ebright All rights reserved. Dissertation Advisors: Daniel A. Haber & Shyamala Maheswaran Richard Yon Ebright CRISPR activation screening of circulating tumor cells identifies enhancers of blood-based metastasis Abstract Over ninety percent of cancer mortality is attributable to metastasis, most commonly due to the blood-borne dissemination of cancer cells from a primary tumor to secondary tissues. However, the vast majority of these cancer cells in the circulation, known as circulating tumor cells (CTCs), never go on to form clinically relevant metastases, instead dying or senescing in the circulation or at distant sites. -
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) -
Development and Validation of a Novel Immune-Related Prognostic Model
Wang et al. J Transl Med (2020) 18:67 https://doi.org/10.1186/s12967-020-02255-6 Journal of Translational Medicine RESEARCH Open Access Development and validation of a novel immune-related prognostic model in hepatocellular carcinoma Zheng Wang1, Jie Zhu1, Yongjuan Liu3, Changhong Liu2, Wenqi Wang2, Fengzhe Chen1* and Lixian Ma1* Abstract Background: Growing evidence has suggested that immune-related genes play crucial roles in the development and progression of hepatocellular carcinoma (HCC). Nevertheless, the utility of immune-related genes for evaluating the prognosis of HCC patients are still lacking. The study aimed to explore gene signatures and prognostic values of immune-related genes in HCC. Methods: We comprehensively integrated gene expression data acquired from 374 HCC and 50 normal tissues in The Cancer Genome Atlas (TCGA). Diferentially expressed genes (DEGs) analysis and univariate Cox regression analysis were performed to identify DEGs that related to overall survival. An immune prognostic model was constructed using the Lasso and multivariate Cox regression analyses. Furthermore, Cox regression analysis was applied to identify independent prognostic factors in HCC. The correlation analysis between immune-related signature and immune cells infltration were also investigated. Finally, the signature was validated in an external independent dataset. Results: A total of 329 diferentially expressed immune‐related genes were detected. 64 immune‐related genes were identifed to be markedly related to overall survival in HCC patients using univariate Cox regression analysis. Then we established a TF-mediated network for exploring the regulatory mechanisms of these genes. Lasso and multivariate Cox regression analyses were applied to construct the immune-based prognostic model, which consisted of nine immune‐related genes. -
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. -
Per2 Antibody
Product Datasheet Per2 Antibody Catalog No: #SAB436 Orders: [email protected] Description Support: [email protected] Product Name Per2 Antibody Host Species Rabbit Clonality Polyclonal Purification Antibodies were produced by immunizing rabbits with synthetic peptide and KLH conjugates. Antibodies were purified by affinity-chromatography using epitope-specific peptide. Applications Custom antibody Species Reactivity Ms Immunogen Type Peptide-KLH Target Name Per2 Other Names Period circadian protein homolog 2 Accession No. uniprot:O54943 Calculated MW 136kDa Formulation Supplied at 1.0mg/mL in phosphate buffered saline (without Mg2+ and Ca2+), pH 7.4, 150mM NaCl, 0.02% sodium azide and 85% glycerol. Storage Store at -20°C for long term preservation (recommended). Store at 4°C for short term use. Application Details Western blotting: 1:500~1:1000 Background Transcriptional repressor which forms a core component of the circadian clock. The circadian clock, an internal time-keeping system, regulates various physiological processes through the generation of approximately 24 hour circadian rhythms in gene expression, which are translated into rhythms in metabolism and behavior. It is derived from the Latin roots 'circa' (about) and 'diem' (day) and acts as an important regulator of a wide array of physiological functions including metabolism, sleep, body temperature, blood pressure, endocrine, immune, cardiovascular, and renal function. Consists of two major components: the central clock, residing in the suprachiasmatic nucleus (SCN) of the brain, and the peripheral clocks that are present in nearly every tissue and organ system. Both the central and peripheral clocks can be reset by environmental cues, also known as Zeitgebers (German for 'timegivers').