Transcriptome Analysis of Differentially Expressed Genes
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Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse
Welcome to More Choice CD Marker Handbook For more information, please visit: Human bdbiosciences.com/eu/go/humancdmarkers Mouse bdbiosciences.com/eu/go/mousecdmarkers Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse CD3 CD3 CD (cluster of differentiation) molecules are cell surface markers T Cell CD4 CD4 useful for the identification and characterization of leukocytes. The CD CD8 CD8 nomenclature was developed and is maintained through the HLDA (Human Leukocyte Differentiation Antigens) workshop started in 1982. CD45R/B220 CD19 CD19 The goal is to provide standardization of monoclonal antibodies to B Cell CD20 CD22 (B cell activation marker) human antigens across laboratories. To characterize or “workshop” the antibodies, multiple laboratories carry out blind analyses of antibodies. These results independently validate antibody specificity. CD11c CD11c Dendritic Cell CD123 CD123 While the CD nomenclature has been developed for use with human antigens, it is applied to corresponding mouse antigens as well as antigens from other species. However, the mouse and other species NK Cell CD56 CD335 (NKp46) antibodies are not tested by HLDA. Human CD markers were reviewed by the HLDA. New CD markers Stem Cell/ CD34 CD34 were established at the HLDA9 meeting held in Barcelona in 2010. For Precursor hematopoetic stem cell only hematopoetic stem cell only additional information and CD markers please visit www.hcdm.org. Macrophage/ CD14 CD11b/ Mac-1 Monocyte CD33 Ly-71 (F4/80) CD66b Granulocyte CD66b Gr-1/Ly6G Ly6C CD41 CD41 CD61 (Integrin b3) CD61 Platelet CD9 CD62 CD62P (activated platelets) CD235a CD235a Erythrocyte Ter-119 CD146 MECA-32 CD106 CD146 Endothelial Cell CD31 CD62E (activated endothelial cells) Epithelial Cell CD236 CD326 (EPCAM1) For Research Use Only. -
SHARP1 (BHLHE41) Mouse Monoclonal Antibody [Clone ID: OTI3H4] Product Data
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for TA806354 SHARP1 (BHLHE41) Mouse Monoclonal Antibody [Clone ID: OTI3H4] Product data: Product Type: Primary Antibodies Clone Name: OTI3H4 Applications: IHC, WB Recommended Dilution: WB 1:2000, IHC 1:150 Reactivity: Human Host: Mouse Isotype: IgG1 Clonality: Monoclonal Immunogen: Human recombinant protein fragment corresponding to amino acids 1-297 of human BHLHE41(NP_110389) produced in E.coli. Formulation: PBS (PH 7.3) containing 1% BSA, 50% glycerol and 0.02% sodium azide. Concentration: 1 mg/ml Purification: Purified from mouse ascites fluids or tissue culture supernatant by affinity chromatography (protein A/G) Conjugation: Unconjugated Storage: Store at -20°C as received. Stability: Stable for 12 months from date of receipt. Predicted Protein Size: 50.3 kDa Gene Name: basic helix-loop-helix family member e41 Database Link: NP_110389 Entrez Gene 79365 Human Q9C0J9 Background: This gene encodes a basic helix-loop-helix protein expressed in various tissues. The encoded protein can interact with ARNTL or compete for E-box binding sites in the promoter of PER1 and repress CLOCK/ARNTL's transactivation of PER1. This gene is believed to be involved in the control of circadian rhythm and cell differentiation. Defects in this gene are associated with the short sleep phenotype. [provided by RefSeq, Feb 2014] This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 SHARP1 (BHLHE41) Mouse Monoclonal Antibody [Clone ID: OTI3H4] – TA806354 Synonyms: BHLHB3; DEC2; hDEC2; SHARP1 Protein Families: Transcription Factors Protein Pathways: Circadian rhythm - mammal Product images: HEK293T cells were transfected with the pCMV6- ENTRY control (Left lane) or pCMV6-ENTRY BHLHE41 ([RC206882], Right lane) cDNA for 48 hrs and lysed. -
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. -
Modes of Interaction of KMT2 Histone H3 Lysine 4 Methyltransferase/COMPASS Complexes with Chromatin
cells Review Modes of Interaction of KMT2 Histone H3 Lysine 4 Methyltransferase/COMPASS Complexes with Chromatin Agnieszka Bochy ´nska,Juliane Lüscher-Firzlaff and Bernhard Lüscher * ID Institute of Biochemistry and Molecular Biology, Medical School, RWTH Aachen University, Pauwelsstrasse 30, 52057 Aachen, Germany; [email protected] (A.B.); jluescher-fi[email protected] (J.L.-F.) * Correspondence: [email protected]; Tel.: +49-241-8088850; Fax: +49-241-8082427 Received: 18 January 2018; Accepted: 27 February 2018; Published: 2 March 2018 Abstract: Regulation of gene expression is achieved by sequence-specific transcriptional regulators, which convey the information that is contained in the sequence of DNA into RNA polymerase activity. This is achieved by the recruitment of transcriptional co-factors. One of the consequences of co-factor recruitment is the control of specific properties of nucleosomes, the basic units of chromatin, and their protein components, the core histones. The main principles are to regulate the position and the characteristics of nucleosomes. The latter includes modulating the composition of core histones and their variants that are integrated into nucleosomes, and the post-translational modification of these histones referred to as histone marks. One of these marks is the methylation of lysine 4 of the core histone H3 (H3K4). While mono-methylation of H3K4 (H3K4me1) is located preferentially at active enhancers, tri-methylation (H3K4me3) is a mark found at open and potentially active promoters. Thus, H3K4 methylation is typically associated with gene transcription. The class 2 lysine methyltransferases (KMTs) are the main enzymes that methylate H3K4. KMT2 enzymes function in complexes that contain a necessary core complex composed of WDR5, RBBP5, ASH2L, and DPY30, the so-called WRAD complex. -
Linked Mental Retardation Detected by Array CGH
JMG Online First, published on September 16, 2005 as 10.1136/jmg.2005.036178 J Med Genet: first published as 10.1136/jmg.2005.036178 on 16 September 2005. Downloaded from Chromosomal copy number changes in patients with non-syndromic X- linked mental retardation detected by array CGH D Lugtenberg1, A P M de Brouwer1, T Kleefstra1, A R Oudakker1, S G M Frints2, C T R M Schrander- Stumpel2, J P Fryns3, L R Jensen4, J Chelly5, C Moraine6, G Turner7, J A Veltman1, B C J Hamel1, B B A de Vries1, H van Bokhoven1, H G Yntema1 1Department of Human Genetics, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands; 2Department of Clinical Genetics, University Hospital Maastricht, Maastricht, The Netherlands; 3Center for Human Genetics, University of Leuven, Leuven, Belgium; 4Max Planck Institute for Molecular Genetics, Berlin, Germany; 5INSERM 129-ICGM, Faculté de Médecine Cochin, Paris, France; 6Service de Génétique et INSERM U316, Hôpital Bretonneau, Tours, France; 7 GOLD Program, Hunter Genetics, University of Newcastle, Callaghan, New South Wales 2308, Australia http://jmg.bmj.com/ Corresponding author: on October 2, 2021 by guest. Protected copyright. Helger G. Yntema, PhD Department of Human Genetics Radboud University Nijmegen Medical Centre P.O. Box 9101 6500 HB Nijmegen The Netherlands E-mail: [email protected] tel: +31-24-3613799 fax: +31-24-3616658 1 Copyright Article author (or their employer) 2005. Produced by BMJ Publishing Group Ltd under licence. J Med Genet: first published as 10.1136/jmg.2005.036178 on 16 September 2005. Downloaded from ABSTRACT Introduction: Several studies have shown that array based comparative genomic hybridization (array CGH) is a powerful tool for the detection of copy number changes in the genome of individuals with a congenital disorder. -
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. -
Systems Analysis Implicates WAVE2&Nbsp
JACC: BASIC TO TRANSLATIONAL SCIENCE VOL.5,NO.4,2020 ª 2020 THE AUTHORS. PUBLISHED BY ELSEVIER ON BEHALF OF THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION. THIS IS AN OPEN ACCESS ARTICLE UNDER THE CC BY-NC-ND LICENSE (http://creativecommons.org/licenses/by-nc-nd/4.0/). PRECLINICAL RESEARCH Systems Analysis Implicates WAVE2 Complex in the Pathogenesis of Developmental Left-Sided Obstructive Heart Defects a b b b Jonathan J. Edwards, MD, Andrew D. Rouillard, PHD, Nicolas F. Fernandez, PHD, Zichen Wang, PHD, b c d d Alexander Lachmann, PHD, Sunita S. Shankaran, PHD, Brent W. Bisgrove, PHD, Bradley Demarest, MS, e f g h Nahid Turan, PHD, Deepak Srivastava, MD, Daniel Bernstein, MD, John Deanfield, MD, h i j k Alessandro Giardini, MD, PHD, George Porter, MD, PHD, Richard Kim, MD, Amy E. Roberts, MD, k l m m,n Jane W. Newburger, MD, MPH, Elizabeth Goldmuntz, MD, Martina Brueckner, MD, Richard P. Lifton, MD, PHD, o,p,q r,s t d Christine E. Seidman, MD, Wendy K. Chung, MD, PHD, Martin Tristani-Firouzi, MD, H. Joseph Yost, PHD, b u,v Avi Ma’ayan, PHD, Bruce D. Gelb, MD VISUAL ABSTRACT Edwards, J.J. et al. J Am Coll Cardiol Basic Trans Science. 2020;5(4):376–86. ISSN 2452-302X https://doi.org/10.1016/j.jacbts.2020.01.012 JACC: BASIC TO TRANSLATIONALSCIENCEVOL.5,NO.4,2020 Edwards et al. 377 APRIL 2020:376– 86 WAVE2 Complex in LVOTO HIGHLIGHTS ABBREVIATIONS AND ACRONYMS Combining CHD phenotype–driven gene set enrichment and CRISPR knockdown screening in zebrafish is an effective approach to identifying novel CHD genes. -
Ageing-Associated Changes in DNA Methylation in X and Y Chromosomes
Kananen and Marttila Epigenetics & Chromatin (2021) 14:33 Epigenetics & Chromatin https://doi.org/10.1186/s13072-021-00407-6 RESEARCH Open Access Ageing-associated changes in DNA methylation in X and Y chromosomes Laura Kananen1,2,3,4* and Saara Marttila4,5* Abstract Background: Ageing displays clear sexual dimorphism, evident in both morbidity and mortality. Ageing is also asso- ciated with changes in DNA methylation, but very little focus has been on the sex chromosomes, potential biological contributors to the observed sexual dimorphism. Here, we sought to identify DNA methylation changes associated with ageing in the Y and X chromosomes, by utilizing datasets available in data repositories, comprising in total of 1240 males and 1191 females, aged 14–92 years. Results: In total, we identifed 46 age-associated CpG sites in the male Y, 1327 age-associated CpG sites in the male X, and 325 age-associated CpG sites in the female X. The X chromosomal age-associated CpGs showed signifcant overlap between females and males, with 122 CpGs identifed as age-associated in both sexes. Age-associated X chro- mosomal CpGs in both sexes were enriched in CpG islands and depleted from gene bodies and showed no strong trend towards hypermethylation nor hypomethylation. In contrast, the Y chromosomal age-associated CpGs were enriched in gene bodies, and showed a clear trend towards hypermethylation with age. Conclusions: Signifcant overlap in X chromosomal age-associated CpGs identifed in males and females and their shared features suggest that despite the uneven chromosomal dosage, diferences in ageing-associated DNA methylation changes in the X chromosome are unlikely to be a major contributor of sex dimorphism in ageing. -
IL21R Expressing CD14+CD16+ Monocytes Expand in Multiple
Plasma Cell Disorders SUPPLEMENTARY APPENDIX IL21R expressing CD14 +CD16 + monocytes expand in multiple myeloma patients leading to increased osteoclasts Marina Bolzoni, 1 Domenica Ronchetti, 2,3 Paola Storti, 1,4 Gaetano Donofrio, 5 Valentina Marchica, 1,4 Federica Costa, 1 Luca Agnelli, 2,3 Denise Toscani, 1 Rosanna Vescovini, 1 Katia Todoerti, 6 Sabrina Bonomini, 7 Gabriella Sammarelli, 1,7 Andrea Vecchi, 8 Daniela Guasco, 1 Fabrizio Accardi, 1,7 Benedetta Dalla Palma, 1,7 Barbara Gamberi, 9 Carlo Ferrari, 8 Antonino Neri, 2,3 Franco Aversa 1,4,7 and Nicola Giuliani 1,4,7 1Myeloma Unit, Dept. of Medicine and Surgery, University of Parma; 2Dept. of Oncology and Hemato-Oncology, University of Milan; 3Hematology Unit, “Fondazione IRCCS Ca’ Granda”, Ospedale Maggiore Policlinico, Milan; 4CoreLab, University Hospital of Parma; 5Dept. of Medical-Veterinary Science, University of Parma; 6Laboratory of Pre-clinical and Translational Research, IRCCS-CROB, Referral Cancer Center of Basilicata, Rionero in Vulture; 7Hematology and BMT Center, University Hospital of Parma; 8Infectious Disease Unit, University Hospital of Parma and 9“Dip. Oncologico e Tecnologie Avanzate”, IRCCS Arcispedale Santa Maria Nuova, Reggio Emilia, Italy ©2017 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol. 2016.153841 Received: August 5, 2016. Accepted: December 23, 2016. Pre-published: January 5, 2017. Correspondence: [email protected] SUPPLEMENTAL METHODS Immunophenotype of BM CD14+ in patients with monoclonal gammopathies. Briefly, 100 μl of total BM aspirate was incubated in the dark with anti-human HLA-DR-PE (clone L243; BD), anti-human CD14-PerCP-Cy 5.5, anti-human CD16-PE-Cy7 (clone B73.1; BD) and anti-human CD45-APC-H 7 (clone 2D1; BD) for 20 min. -
The Ribosomal Protein Rpl22 Controls Ribosome Composition by Directly Repressing Expression of Its Own Paralog, Rpl22l1
The Ribosomal Protein Rpl22 Controls Ribosome Composition by Directly Repressing Expression of Its Own Paralog, Rpl22l1 Monique N. O’Leary1,2, Katherine H. Schreiber1,2, Yong Zhang3, Anne-Ce´cile E. Duc3, Shuyun Rao3,J. Scott Hale4¤, Emmeline C. Academia2, Shreya R. Shah1, John F. Morton5, Carly A. Holstein6, Dan B. Martin6, Matt Kaeberlein7, Warren C. Ladiges5, Pamela J. Fink4, Vivian L. MacKay1, David L. Wiest3, Brian K. Kennedy1,2* 1 Department of Biochemistry, University of Washington, Seattle, Washington, United States of America, 2 Buck Institute for Research on Aging, Novato, California, United States of America, 3 Blood Cell Development and Cancer Keystone, Immune Cell Development and Host Defense Program, Fox Chase Cancer Center, Philadelphia, Pennsylvania, United States of America, 4 Department of Immunology, University of Washington, Seattle, Washington, United States of America, 5 Department of Comparative Medicine, University of Washington, Seattle, Washington, United States of America, 6 Institute for Systems Biology, Seattle, Washington, United States of America, 7 Department of Pathology, University of Washington, Seattle, Washington, United States of America Abstract Most yeast ribosomal protein genes are duplicated and their characterization has led to hypotheses regarding the existence of specialized ribosomes with different subunit composition or specifically-tailored functions. In yeast, ribosomal protein genes are generally duplicated and evidence has emerged that paralogs might have specific roles. Unlike yeast, most mammalian ribosomal proteins are thought to be encoded by a single gene copy, raising the possibility that heterogenous populations of ribosomes are unique to yeast. Here, we examine the roles of the mammalian Rpl22, finding that Rpl222/2 mice have only subtle phenotypes with no significant translation defects. -
Assessment of Hematopoietic Failure Due to Rpl11 Deficiency in a Zebrafish Model of Diamond-Blackfan Anemia by Deep Sequencing
Zhang et al. BMC Genomics 2013, 14:896 http://www.biomedcentral.com/1471-2164/14/896 RESEARCH ARTICLE Open Access Assessment of hematopoietic failure due to Rpl11 deficiency in a zebrafish model of Diamond- Blackfan anemia by deep sequencing Zhaojun Zhang1†, Haibo Jia2†, Qian Zhang1, Yang Wan3, Yang Zhou2, Qiong Jia2, Wanguang Zhang4, Weiping Yuan3, Tao Cheng3, Xiaofan Zhu3* and Xiangdong Fang1* Abstract Background: Diamond–Blackfan anemia is a rare congenital red blood cell dysplasia that develops soon after birth. RPL11 mutations account for approximately 4.8% of human DBA cases with defective hematopoietic phenotypes. However, the mechanisms by which RPL11 regulates hematopoiesis in DBA remain elusive. In this study, we analyzed the transcriptome using deep sequencing data from an Rpl11-deficient zebrafish model to identify Rpl11-mediated hematopoietic failure and investigate the underlying mechanisms. Results: We characterized hematological defects in Rpl11-deficient zebrafish embryos by identifying affected hematological genes, hematopoiesis-associated pathways, and regulatory networks. We found that hemoglobin biosynthetic and hematological defects in Rpl11-deficient zebrafish were related to dysregulation of iron metabolism-related genes, including tfa, tfr1b, alas2 and slc25a37, which are involved in heme and hemoglobin biosynthesis. In addition, we found reduced expression of the hematopoietic stem cells (HSC) marker cmyb and HSC transcription factors tal1 and hoxb4a in Rpl11-deficient zebrafish embryos, indicating that the hematopoietic defects may be related to impaired HSC formation, differentiation, and proliferation. However, Rpl11 deficiency did not affect the development of other blood cell lineages such as granulocytes and myelocytes. Conclusion: We identified hematopoietic failure of Rpl11-deficient zebrafish embryos using transcriptome deep sequencing and elucidated potential underlying mechanisms. -
Targeting Glioblastoma Stem Cells Through Disruption of the Circadian Clock
Published OnlineFirst August 27, 2019; DOI: 10.1158/2159-8290.CD-19-0215 RESEARCH ARTICLE Targeting Glioblastoma Stem Cells through Disruption of the Circadian Clock Zhen Dong1, Guoxin Zhang1, Meng Qu2, Ryan C. Gimple1,3, Qiulian Wu1, Zhixin Qiu1, Briana C. Prager1,3, Xiuxing Wang1, Leo J.Y. Kim1,3, Andrew R. Morton3, Deobrat Dixit1, Wenchao Zhou4, Haidong Huang4, Bin Li5, Zhe Zhu1, Shideng Bao4, Stephen C. Mack6, Lukas Chavez7, Steve A. Kay2, and Jeremy N. Rich1 Downloaded from cancerdiscovery.aacrjournals.org on September 24, 2021. © 2019 American Association for Cancer Research. Published OnlineFirst August 27, 2019; DOI: 10.1158/2159-8290.CD-19-0215 ABSTRACT Glioblastomas are highly lethal cancers, containing self-renewing glioblastoma stem cells (GSC). Here, we show that GSCs, differentiated glioblastoma cells (DGC), and nonmalignant brain cultures all displayed robust circadian rhythms, yet GSCs alone displayed exquisite dependence on core clock transcription factors, BMAL1 and CLOCK, for optimal cell growth. Downregulation of BMAL1 or CLOCK in GSCs induced cell-cycle arrest and apoptosis. Chromatin immu- noprecipitation revealed that BMAL1 preferentially bound metabolic genes and was associated with active chromatin regions in GSCs compared with neural stem cells. Targeting BMAL1 or CLOCK attenu- ated mitochondrial metabolic function and reduced expression of tricarboxylic acid cycle enzymes. Small-molecule agonists of two independent BMAL1–CLOCK negative regulators, the cryptochromes and REV-ERBs, downregulated stem cell factors and reduced GSC growth. Combination of cryp- tochrome and REV-ERB agonists induced synergistic antitumor effi cacy. Collectively, these fi ndings show that GSCs co-opt circadian regulators beyond canonical circadian circuitry to promote stemness maintenance and metabolism, offering novel therapeutic paradigms.