Quantitative Classification of Chromatin Dynamics Reveals Regulators of Intestinal Stem Cell Differentiation
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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. -
Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database. -
A Flexible Microfluidic System for Single-Cell Transcriptome Profiling
www.nature.com/scientificreports OPEN A fexible microfuidic system for single‑cell transcriptome profling elucidates phased transcriptional regulators of cell cycle Karen Davey1,7, Daniel Wong2,7, Filip Konopacki2, Eugene Kwa1, Tony Ly3, Heike Fiegler2 & Christopher R. Sibley 1,4,5,6* Single cell transcriptome profling has emerged as a breakthrough technology for the high‑resolution understanding of complex cellular systems. Here we report a fexible, cost‑efective and user‑ friendly droplet‑based microfuidics system, called the Nadia Instrument, that can allow 3′ mRNA capture of ~ 50,000 single cells or individual nuclei in a single run. The precise pressure‑based system demonstrates highly reproducible droplet size, low doublet rates and high mRNA capture efciencies that compare favorably in the feld. Moreover, when combined with the Nadia Innovate, the system can be transformed into an adaptable setup that enables use of diferent bufers and barcoded bead confgurations to facilitate diverse applications. Finally, by 3′ mRNA profling asynchronous human and mouse cells at diferent phases of the cell cycle, we demonstrate the system’s ability to readily distinguish distinct cell populations and infer underlying transcriptional regulatory networks. Notably this provided supportive evidence for multiple transcription factors that had little or no known link to the cell cycle (e.g. DRAP1, ZKSCAN1 and CEBPZ). In summary, the Nadia platform represents a promising and fexible technology for future transcriptomic studies, and other related applications, at cell resolution. Single cell transcriptome profling has recently emerged as a breakthrough technology for understanding how cellular heterogeneity contributes to complex biological systems. Indeed, cultured cells, microorganisms, biopsies, blood and other tissues can be rapidly profled for quantifcation of gene expression at cell resolution. -
Hepatitis C Virus As a Unique Human Model Disease to Define
viruses Review Hepatitis C Virus as a Unique Human Model Disease to Define Differences in the Transcriptional Landscape of T Cells in Acute versus Chronic Infection David Wolski and Georg M. Lauer * Liver Center at the Gastrointestinal Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA * Correspondence: [email protected]; Tel.: +1-617-724-7515 Received: 27 June 2019; Accepted: 23 July 2019; Published: 26 July 2019 Abstract: The hepatitis C virus is unique among chronic viral infections in that an acute outcome with complete viral elimination is observed in a minority of infected patients. This unique feature allows direct comparison of successful immune responses with those that fail in the setting of the same human infection. Here we review how this scenario can be used to achieve better understanding of transcriptional regulation of T-cell differentiation. Specifically, we discuss results from a study comparing transcriptional profiles of hepatitis C virus (HCV)-specific CD8 T-cells during early HCV infection between patients that do and do not control and eliminate HCV. Identification of early gene expression differences in key T-cell differentiation molecules as well as clearly distinct transcriptional networks related to cell metabolism and nucleosomal regulation reveal novel insights into the development of exhausted and memory T-cells. With additional transcriptional studies of HCV-specific CD4 and CD8 T-cells in different stages of infection currently underway, we expect HCV infection to become a valuable model disease to study human immunity to viruses. Keywords: viral hepatitis; hepatitis C virus; T cells; transcriptional regulation; transcription factors; metabolism; nucleosome 1. -
Induced Quiescence of Lgr5+ Stem Cells in Intestinal Organoids Enables Differentiation of Hormone-Producing Enteroendocrine Cells
Article Induced Quiescence of Lgr5+ Stem Cells in Intestinal Organoids Enables Differentiation of Hormone- Producing Enteroendocrine Cells Graphical Abstract Authors Onur Basak, Joep Beumer, Kay Wiebrands, Hiroshi Seno, Alexander van Oudenaarden, Hans Clevers Correspondence [email protected] In Brief Basak et al. identify signals to generate rare enteroendocrine cells (EECs) at high purity through manipulation of intestinal stem cell quiescence. Single-cell sequencing reveals a high level of heterogeneity in hormonal production, which is influenced by the regional identity of the intestinal organoid cultures. Highlights Data Resources d EGFR inhibition halts DNA replication and proliferation of GSE80636 Lgr5+ ISCs through MEK d Lgr5+ ISCs reactivated from quiescence retain multilineage differentiation potential d Combined EGFR/Wnt/Notch inhibition produces enteroendocrine cells with high purity d RNA sequencing shows regional identity and heterogeneity in hormone-producing EECs Basak et al., 2017, Cell Stem Cell 20, 177–190 February 2, 2017 ª 2016 Elsevier Inc. http://dx.doi.org/10.1016/j.stem.2016.11.001 Cell Stem Cell Article Induced Quiescence of Lgr5+ Stem Cells in Intestinal Organoids Enables Differentiation of Hormone-Producing Enteroendocrine Cells Onur Basak,1,2,5 Joep Beumer,1,2,5 Kay Wiebrands,1,2,5 Hiroshi Seno,4 Alexander van Oudenaarden,1,2 and Hans Clevers1,2,3,6,* 1Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences (KNAW), Uppsalalaan 8, 3584 CT, Utrecht the Netherlands 2Cancer Genomics Netherlands, UMC -
ZEB1-Induced LINC01559 Expedites Cell Proliferation, Migration
Shen et al. Cell Death and Disease (2021) 12:349 https://doi.org/10.1038/s41419-021-03571-5 Cell Death & Disease ARTICLE Open Access ZEB1-induced LINC01559 expedites cell proliferation, migration and EMT process in gastric cancer through recruiting IGF2BP2 to stabilize ZEB1 expression Huojian Shen1, Hongyi Zhu1, Yuanwen Chen1, Zhiyong Shen1, Weiqing Qiu1, Changlin Qian1 and Jie Zhang1 Abstract Gastric cancer (GC) is a common type of tumor that is characterized with high metastatic rate. In recent years, increasing studies have indicated that lncRNAs are involved in the regulation on cancer cell proliferation and migration. However, the functional role of long intergenic non-protein coding RNA 1559 (LINC01559) in GC is still unclear. In this study, we applied quantitative real-time polymerase chain reaction (RT-qPCR) and examined that LINC01559 expression was significantly enhanced in GC cells. Functional assays such as EdU, colony formation, JC-1 and transwell assays displayed that silencing LINC01559 inhibited cell proliferation and migration while promoted cell apoptosis in GC. Besides, western blot analysis and immunofluorescence assays examined the expression of factors related to epithelial- mesenchymal transition (EMT) and indicated that EMT process was blocked by LINC01559 knockdown in GC cells. Besides, LINC01559 silencing inhibited tumor growth in vivo. In addition, Chromatin immunoprecipitation (ChIP) assays demonstrated that zinc finger E-box binding homeobox 1 (ZEB1) served as a transcription factor to combine with 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; LINC01559 promoter and activated the expression of LINC01559 in GC cells. In return, LINC01559 recruited insulin like growth factor 2 mRNA binding protein 2 (IGF2BP2) to stabilize ZEB1 mRNA to up-regulate ZEB1 in GC cells. -
What Your Genome Doesn't Tell
UC San Diego UC San Diego Electronic Theses and Dissertations Title Multi-layered epigenetic control of T cell fate decisions Permalink https://escholarship.org/uc/item/8rs7c7b3 Author Yu, Bingfei Publication Date 2018 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA SAN DIEGO Multi-layered epigenetic control of T cell fate decisions A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Biology by Bingfei Yu Committee in charge: Professor Ananda Goldrath, Chair Professor John Chang Professor Stephen Hedrick Professor Cornelis Murre Professor Wei Wang 2018 Copyright Bingfei Yu, 2018 All rights reserved. The dissertation of Bingfei Yu is approved, and it is ac- ceptable in quality and form for publication on microfilm and electronically: Chair University of California San Diego 2018 iii DEDICATION To my parents who have been giving me countless love, trust and support to make me who I am. iv EPIGRAPH Stay hungary. Stay foolish. | Steve Jobs quoted from the back cover of the 1974 edition of the Whole Earth Catalog v TABLE OF CONTENTS Signature Page.................................. iii Dedication..................................... iv Epigraph.....................................v Table of Contents................................. vi List of Figures.................................. ix Acknowledgements................................x Vita........................................ xii Abstract of -
Original Article Regulation of Gene Expression in HBV- and HCV-Related Hepatocellular Carcinoma: Integrated GWRS and GWGS Analyses
Int J Clin Exp Med 2014;7(11):4038-4050 www.ijcem.com /ISSN:1940-5901/IJCEM0002458 Original Article Regulation of gene expression in HBV- and HCV-related hepatocellular carcinoma: integrated GWRS and GWGS analyses Xu Zhou*, Hua-Qiang Zhu*, Jun Lu Department of General Surgery, Provincial Hospital Affiliated to Shandong University, Ji’nan 250014, China. *Equal contributors and co-first authors. Received September 11, 2014; Accepted November 8, 2014; Epub November 15, 2014; Published November 30, 2014 Abstract: Objectives: To explore the molecular mechanism of hepatitis B virus-related and hepatitis C virus-related hepatocellular carcinoma, samples from hepatitis B virus and hepatitis C virus infected patients and the normal were compared, respectively. Methods: In both experiments, genes with high value were selected based on a ge- nome-wide relative significance and genome-wide global significance model. Co-expression network of the selected genes was constructed, and transcription factors in the network were identified. Molecular complex detection al- gorithm was used to obtain sub-networks. Results: Based on the new model, the top 300 genes were selected. Co-expression network was constructed and transcription factors were identified. We obtained two common genes FCN2 and CXCL14, and two common transcription factors RFX5 and EZH2. In hepatitis B virus experiment, cluster 1 and 3 had the higher value. In cluster 1, ten of the 17 genes and one transcription factor were all reported associ- ated with hepatocellular carcinoma. In cluster 3, transcription factor ESR1 was reported related with hepatocellular carcinoma. In hepatitis C virus experiment, the value of cluster 3 and 4 was higher. -
The Intestinal Epithelium Tuft Cells: Specification and Function
Cell. Mol. Life Sci. (2012) 69:2907–2917 DOI 10.1007/s00018-012-0984-7 Cellular and Molecular Life Sciences REVIEW The intestinal epithelium tuft cells: specification and function Franc¸ois Gerbe • Catherine Legraverend • Philippe Jay Received: 23 February 2012 / Revised: 21 March 2012 / Accepted: 26 March 2012 / Published online: 19 April 2012 Ó The Author(s) 2012. This article is published with open access at Springerlink.com Abstract The intestinal epithelium, composed of at least Abbreviations seven differentiated cell types, represents an extraordinary Ac-tubulin Acetylated tubulin model to understand the details of multi-lineage differen- Atoh1 Atonal homolog 1 tiation, a question that is highly relevant in developmental BrdU 5-Bromo-20-deoxyuridine biology as well as for clinical applications. This review CFTR Cystic fibrosis transmembrane conductance focuses on intestinal epithelial tuft cells that have been regulator homolog acknowledged as a separate entity for more than 60 years CK-18 Cytokeratin 18 but whose function remains a mystery. We discuss what is DCLK1 Doublecortin-like kinase 1 currently known about the molecular basis of tuft cell fate Dll Delta-like and differentiation and why elucidating tuft cell function F-actin Fibrillar actin has been so difficult. Finally, we summarize the current Gfi1 Growth factor independent 1 hypotheses on their potential involvement in diseases of the Gfi1b Growth factor independent 1b gastro-intestinal tract. GI Gastro-intestinal GIP Gastric inhibitory polypeptide Keywords Tuft cells Á Brush cells Á Intestinal epithelium Á GLP-1 Glucagon-like peptide 1 Atoh1 Á Cell differentiation Á Dclk1 Hes1 Hairy and enhancer of split 1 Hpgds Hematopoietic prostaglandin D synthase Klf4 Kruppel-like factor 4 L-FABP Fatty acid-binding protein 1, liver Lgr5 Leucine-rich repeat-containing G protein-coupled receptor 5 F. -
Application of Microrna Database Mining in Biomarker Discovery and Identification of Therapeutic Targets for Complex Disease
Article Application of microRNA Database Mining in Biomarker Discovery and Identification of Therapeutic Targets for Complex Disease Jennifer L. Major, Rushita A. Bagchi * and Julie Pires da Silva * Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; [email protected] * Correspondence: [email protected] (R.A.B.); [email protected] (J.P.d.S.) Supplementary Tables Methods Protoc. 2021, 4, 5. https://doi.org/10.3390/mps4010005 www.mdpi.com/journal/mps Methods Protoc. 2021, 4, 5. https://doi.org/10.3390/mps4010005 2 of 25 Table 1. List of all hsa-miRs identified by Human microRNA Disease Database (HMDD; v3.2) analysis. hsa-miRs were identified using the term “genetics” and “circulating” as input in HMDD. Targets CAD hsa-miR-1 Targets IR injury hsa-miR-423 Targets Obesity hsa-miR-499 hsa-miR-146a Circulating Obesity Genetics CAD hsa-miR-423 hsa-miR-146a Circulating CAD hsa-miR-149 hsa-miR-499 Circulating IR Injury hsa-miR-146a Circulating Obesity hsa-miR-122 Genetics Stroke Circulating CAD hsa-miR-122 Circulating Stroke hsa-miR-122 Genetics Obesity Circulating Stroke hsa-miR-26b hsa-miR-17 hsa-miR-223 Targets CAD hsa-miR-340 hsa-miR-34a hsa-miR-92a hsa-miR-126 Circulating Obesity Targets IR injury hsa-miR-21 hsa-miR-423 hsa-miR-126 hsa-miR-143 Targets Obesity hsa-miR-21 hsa-miR-223 hsa-miR-34a hsa-miR-17 Targets CAD hsa-miR-223 hsa-miR-92a hsa-miR-126 Targets IR injury hsa-miR-155 hsa-miR-21 Circulating CAD hsa-miR-126 hsa-miR-145 hsa-miR-21 Targets Obesity hsa-mir-223 hsa-mir-499 hsa-mir-574 Targets IR injury hsa-mir-21 Circulating IR injury Targets Obesity hsa-mir-21 Targets CAD hsa-mir-22 hsa-mir-133a Targets IR injury hsa-mir-155 hsa-mir-21 Circulating Stroke hsa-mir-145 hsa-mir-146b Targets Obesity hsa-mir-21 hsa-mir-29b Methods Protoc. -
Single Cell Derived Clonal Analysis of Human Glioblastoma Links
SUPPLEMENTARY INFORMATION: Single cell derived clonal analysis of human glioblastoma links functional and genomic heterogeneity ! Mona Meyer*, Jüri Reimand*, Xiaoyang Lan, Renee Head, Xueming Zhu, Michelle Kushida, Jane Bayani, Jessica C. Pressey, Anath Lionel, Ian D. Clarke, Michael Cusimano, Jeremy Squire, Stephen Scherer, Mark Bernstein, Melanie A. Woodin, Gary D. Bader**, and Peter B. Dirks**! ! * These authors contributed equally to this work.! ** Correspondence: [email protected] or [email protected]! ! Supplementary information - Meyer, Reimand et al. Supplementary methods" 4" Patient samples and fluorescence activated cell sorting (FACS)! 4! Differentiation! 4! Immunocytochemistry and EdU Imaging! 4! Proliferation! 5! Western blotting ! 5! Temozolomide treatment! 5! NCI drug library screen! 6! Orthotopic injections! 6! Immunohistochemistry on tumor sections! 6! Promoter methylation of MGMT! 6! Fluorescence in situ Hybridization (FISH)! 7! SNP6 microarray analysis and genome segmentation! 7! Calling copy number alterations! 8! Mapping altered genome segments to genes! 8! Recurrently altered genes with clonal variability! 9! Global analyses of copy number alterations! 9! Phylogenetic analysis of copy number alterations! 10! Microarray analysis! 10! Gene expression differences of TMZ resistant and sensitive clones of GBM-482! 10! Reverse transcription-PCR analyses! 11! Tumor subtype analysis of TMZ-sensitive and resistant clones! 11! Pathway analysis of gene expression in the TMZ-sensitive clone of GBM-482! 11! Supplementary figures and tables" 13" "2 Supplementary information - Meyer, Reimand et al. Table S1: Individual clones from all patient tumors are tumorigenic. ! 14! Fig. S1: clonal tumorigenicity.! 15! Fig. S2: clonal heterogeneity of EGFR and PTEN expression.! 20! Fig. S3: clonal heterogeneity of proliferation.! 21! Fig. -
Dynamic Regulatory Module Networks for Inference of Cell Type
bioRxiv preprint doi: https://doi.org/10.1101/2020.07.18.210328; this version posted July 19, 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-ND 4.0 International license. Dynamic regulatory module networks for inference of cell type specific transcriptional networks Alireza Fotuhi Siahpirani1,2,+, Deborah Chasman1,8,+, Morten Seirup3,4, Sara Knaack1, Rupa Sridharan1,5, Ron Stewart3, James Thomson3,5,6, and Sushmita Roy1,2,7* 1Wisconsin Institute for Discovery, University of Wisconsin-Madison 2Department of Computer Sciences, University of Wisconsin-Madison 3Morgridge Institute for Research 4Molecular and Environmental Toxicology Program, University of Wisconsin-Madison 5Department of Cell and Regenerative Biology, University of Wisconsin-Madison 6Department of Molecular, Cellular, & Developmental Biology, University of California Santa Barbara 7Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison 8Present address: Division of Reproductive Sciences, Department of Obstetrics and Gynecology, University of Wisconsin-Madison +These authors contributed equally. *To whom correspondence should be addressed. 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.07.18.210328; this version posted July 19, 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-ND 4.0 International license. Abstract Changes in transcriptional regulatory networks can significantly alter cell fate. To gain insight into transcriptional dynamics, several studies have profiled transcriptomes and epigenomes at different stages of a developmental process.