ERG Deletions in Childhood Acute Lymphoblastic Leukemia with DUX4
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F2RL2 Antibody Cat
F2RL2 Antibody Cat. No.: 56-323 F2RL2 Antibody F2RL2 Antibody immunohistochemistry analysis in formalin fixed and paraffin embedded human heart tissue followed by peroxidase conjugation of the secondary antibody and DAB staining. Specifications HOST SPECIES: Rabbit SPECIES REACTIVITY: Human This F2RL2 antibody is generated from rabbits immunized with a KLH conjugated IMMUNOGEN: synthetic peptide between 21-50 amino acids from the N-terminal region of human F2RL2. TESTED APPLICATIONS: IHC-P, WB For WB starting dilution is: 1:1000 APPLICATIONS: For IHC-P starting dilution is: 1:10~50 PREDICTED MOLECULAR 43 kDa WEIGHT: September 25, 2021 1 https://www.prosci-inc.com/f2rl2-antibody-56-323.html Properties This antibody is purified through a protein A column, followed by peptide affinity PURIFICATION: purification. CLONALITY: Polyclonal ISOTYPE: Rabbit Ig CONJUGATE: Unconjugated PHYSICAL STATE: Liquid BUFFER: Supplied in PBS with 0.09% (W/V) sodium azide. CONCENTRATION: batch dependent Store at 4˚C for three months and -20˚C, stable for up to one year. As with all antibodies STORAGE CONDITIONS: care should be taken to avoid repeated freeze thaw cycles. Antibodies should not be exposed to prolonged high temperatures. Additional Info OFFICIAL SYMBOL: F2RL2 Proteinase-activated receptor 3, PAR-3, Coagulation factor II receptor-like 2, Thrombin ALTERNATE NAMES: receptor-like 2, F2RL2, PAR3 ACCESSION NO.: O00254 GENE ID: 2151 USER NOTE: Optimal dilutions for each application to be determined by the researcher. Background and References Coagulation factor II (thrombin) receptor-like 2 (F2RL2) is a member of the large family of 7-transmembrane-region receptors that couple to guanosine-nucleotide-binding proteins. -
Id4, a New Candidate Gene for Senile Osteoporosis, Acts As a Molecular Switch Promoting Osteoblast Differentiation
Id4, a New Candidate Gene for Senile Osteoporosis, Acts as a Molecular Switch Promoting Osteoblast Differentiation Yoshimi Tokuzawa1., Ken Yagi1., Yzumi Yamashita1, Yutaka Nakachi1, Itoshi Nikaido1, Hidemasa Bono1, Yuichi Ninomiya1, Yukiko Kanesaki-Yatsuka1, Masumi Akita2, Hiromi Motegi3, Shigeharu Wakana3, Tetsuo Noda3,4, Fred Sablitzky5, Shigeki Arai6, Riki Kurokawa6, Toru Fukuda7, Takenobu Katagiri7, Christian Scho¨ nbach8,9, Tatsuo Suda1, Yosuke Mizuno1, Yasushi Okazaki1* 1 Division of Functional Genomics and Systems Medicine, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan, 2 Division of Morphological Science, Biomedical Research Center, Saitama Medical University, Iruma-gun, Saitama, Japan, 3 RIKEN BioResource Center, Tsukuba, Ibaraki, Japan, 4 The Cancer Institute of the Japanese Foundation for Cancer Research, Koto-ward, Tokyo, Japan, 5 Developmental Genetics and Gene Control, Institute of Genetics, University of Nottingham, Queen’s Medical Center, Nottingham, United Kingdom, 6 Division of Gene Structure and Function, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan, 7 Division of Pathophysiology, Research Center for Genomic Medicine, Saitama Medical University, Hidaka, Saitama, Japan, 8 Division of Genomics and Genetics, Nanyang Technological University School of Biological Sciences, Singapore, Singapore, 9 Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Iizuka, Fukuoka, Japan Abstract Excessive accumulation of bone marrow adipocytes observed in senile osteoporosis or age-related osteopenia is caused by the unbalanced differentiation of MSCs into bone marrow adipocytes or osteoblasts. Several transcription factors are known to regulate the balance between adipocyte and osteoblast differentiation. However, the molecular mechanisms that regulate the balance between adipocyte and osteoblast differentiation in the bone marrow have yet to be elucidated. -
A Core Transcriptional Network Composed of Pax2/8, Gata3 and Lim1 Regulates Key Players of Pro/Mesonephros Morphogenesis
Developmental Biology 382 (2013) 555–566 Contents lists available at ScienceDirect Developmental Biology journal homepage: www.elsevier.com/locate/developmentalbiology Genomes and Developmental Control A core transcriptional network composed of Pax2/8, Gata3 and Lim1 regulates key players of pro/mesonephros morphogenesis Sami Kamel Boualia a, Yaned Gaitan a, Mathieu Tremblay a, Richa Sharma a, Julie Cardin b, Artur Kania b, Maxime Bouchard a,n a Goodman Cancer Research Centre and Department of Biochemistry, McGill University, 1160 Pine Ave. W., Montreal, Quebec, Canada H3A 1A3 b Institut de Recherches Cliniques de Montréal, Montréal, Québec, Canada H2W 1R7, Department of Anatomy and Cell Biology, Division of Experimental Medicine, McGill University, Montréal, Quebec, Canada, H3A 2B2 and Faculté de médecine, Université de Montréal, Montréal, Quebec, Canada, H3C 3J7. article info abstract Article history: Translating the developmental program encoded in the genome into cellular and morphogenetic Received 23 January 2013 functions requires the deployment of elaborate gene regulatory networks (GRNs). GRNs are especially Received in revised form crucial at the onset of organ development where a few regulatory signals establish the different 27 July 2013 programs required for tissue organization. In the renal system primordium (the pro/mesonephros), Accepted 30 July 2013 important regulators have been identified but their hierarchical and regulatory organization is still Available online 3 August 2013 elusive. Here, we have performed a detailed analysis of the GRN underlying mouse pro/mesonephros Keywords: development. We find that a core regulatory subcircuit composed of Pax2/8, Gata3 and Lim1 turns on a Kidney development deeper layer of transcriptional regulators while activating effector genes responsible for cell signaling Transcription and tissue organization. -
Functional and Molecular Heterogeneity Of
ARTICLE https://doi.org/10.1038/s41467-020-15716-9 OPEN Functional and molecular heterogeneity of D2R neurons along dorsal ventral axis in the striatum ✉ Emma Puighermanal1,2 , Laia Castell1, Anna Esteve-Codina 3, Su Melser4,5, Konstantin Kaganovsky 6, Charleine Zussy1, Jihane Boubaker-Vitre1, Marta Gut3,7, Stephanie Rialle1, Christoph Kellendonk8,9, Elisenda Sanz2, Albert Quintana 2, Giovanni Marsicano4,5, Miquel Martin1, Marcelo Rubinstein10,11,12, ✉ Jean-Antoine Girault 13,14,15, Jun B. Ding6 & Emmanuel Valjent 1 1234567890():,; Action control is a key brain function determining the survival of animals in their environ- ment. In mammals, neurons expressing dopamine D2 receptors (D2R) in the dorsal striatum (DS) and the nucleus accumbens (Acb) jointly but differentially contribute to the fine reg- ulation of movement. However, their region-specific molecular features are presently unknown. By combining RNAseq of striatal D2R neurons and histological analyses, we identified hundreds of novel region-specific molecular markers, which may serve as tools to target selective subpopulations. As a proof of concept, we characterized the molecular identity of a subcircuit defined by WFS1 neurons and evaluated multiple behavioral tasks after its temporally-controlled deletion of D2R. Consequently, conditional D2R knockout mice displayed a significant reduction in digging behavior and an exacerbated hyperlocomotor response to amphetamine. Thus, targeted molecular analyses reveal an unforeseen hetero- geneity in D2R-expressing striatal neuronal populations, underlying specific D2R’s functional features in the control of specific motor behaviors. 1 IGF, CNRS, INSERM, Université Montpellier, Montpellier, France. 2 Neuroscience Institute, Department of Cell Biology, Physiology and Immunology, Autonomous University of Barcelona, Bellaterra, Spain. -
Edinburgh Research Explorer
Edinburgh Research Explorer International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list Citation for published version: Davenport, AP, Alexander, SPH, Sharman, JL, Pawson, AJ, Benson, HE, Monaghan, AE, Liew, WC, Mpamhanga, CP, Bonner, TI, Neubig, RR, Pin, JP, Spedding, M & Harmar, AJ 2013, 'International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list: recommendations for new pairings with cognate ligands', Pharmacological reviews, vol. 65, no. 3, pp. 967-86. https://doi.org/10.1124/pr.112.007179 Digital Object Identifier (DOI): 10.1124/pr.112.007179 Link: Link to publication record in Edinburgh Research Explorer Document Version: Publisher's PDF, also known as Version of record Published In: Pharmacological reviews Publisher Rights Statement: U.S. Government work not protected by U.S. copyright General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 02. Oct. 2021 1521-0081/65/3/967–986$25.00 http://dx.doi.org/10.1124/pr.112.007179 PHARMACOLOGICAL REVIEWS Pharmacol Rev 65:967–986, July 2013 U.S. -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
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. -
ERG Dependence Distinguishes Developmental Control of Hematopoietic Stem Cell Maintenance from Hematopoietic Specification
Downloaded from genesdev.cshlp.org on September 28, 2021 - Published by Cold Spring Harbor Laboratory Press ERG dependence distinguishes developmental control of hematopoietic stem cell maintenance from hematopoietic specification Samir Taoudi,1,2,6 Thomas Bee,3 Adrienne Hilton,1 Kathy Knezevic,3 Julie Scott,4 Tracy A. Willson,1,2 Caitlin Collin,1 Tim Thomas,1,2 Anne K. Voss,1,2 Benjamin T. Kile,1,2 Warren S. Alexander,2,5 John E. Pimanda,3 and Douglas J. Hilton1,2 1Molecular Medicine Division, The Walter and Eliza Institute of Medical Research, Melbourne, Parkville, Victoria 3052, Australia; 2Department of Medical Biology, The University of Melbourne, Melbourne, Parkville, Victoria 3010, Australia; 3Lowy Cancer Research Centre, The Prince of Wales Clinical School, University of New South Wales, Sydney 2052, Australia; 4Microinjection Services, The Walter and Eliza Institute of Medical Research, Melbourne, Parkville, Victoria 3052, Australia; 5Cancer and Haematology Division, The Walter and Eliza Institute of Medical Research, Melbourne, Parkville, Victoria 3052, Australia Although many genes are known to be critical for early hematopoiesis in the embryo, it remains unclear whether distinct regulatory pathways exist to control hematopoietic specification versus hematopoietic stem cell (HSC) emergence and function. Due to their interaction with key regulators of hematopoietic commitment, particular interest has focused on the role of the ETS family of transcription factors; of these, ERG is predicted to play an important role in the initiation of hematopoiesis, yet we do not know if or when ERG is required. Using in vitro and in vivo models of hematopoiesis and HSC development, we provide strong evidence that ERG is at the center of a distinct regulatory program that is not required for hematopoietic specification or differentiation but is critical for HSC maintenance during embryonic development. -
Ubiquitin-Mediated Control of ETS Transcription Factors: Roles in Cancer and Development
International Journal of Molecular Sciences Review Ubiquitin-Mediated Control of ETS Transcription Factors: Roles in Cancer and Development Charles Ducker * and Peter E. Shaw * Queen’s Medical Centre, School of Life Sciences, University of Nottingham, Nottingham NG7 2UH, UK * Correspondence: [email protected] (C.D.); [email protected] (P.E.S.) Abstract: Genome expansion, whole genome and gene duplication events during metazoan evolution produced an extensive family of ETS genes whose members express transcription factors with a conserved winged helix-turn-helix DNA-binding domain. Unravelling their biological roles has proved challenging with functional redundancy manifest in overlapping expression patterns, a common consensus DNA-binding motif and responsiveness to mitogen-activated protein kinase signalling. Key determinants of the cellular repertoire of ETS proteins are their stability and turnover, controlled largely by the actions of selective E3 ubiquitin ligases and deubiquitinases. Here we discuss the known relationships between ETS proteins and enzymes that determine their ubiquitin status, their integration with other developmental signal transduction pathways and how suppression of ETS protein ubiquitination contributes to the malignant cell phenotype in multiple cancers. Keywords: E3 ligase complex; deubiquitinase; gene fusions; mitogens; phosphorylation; DNA damage 1. Introduction Citation: Ducker, C.; Shaw, P.E. Cell growth, proliferation and differentiation are complex, concerted processes that Ubiquitin-Mediated Control of ETS Transcription Factors: Roles in Cancer rely on careful regulation of gene expression. Control over gene expression is maintained and Development. Int. J. Mol. Sci. through signalling pathways that respond to external cellular stimuli, such as growth 2021, 22, 5119. https://doi.org/ factors, cytokines and chemokines, that invoke expression profiles commensurate with 10.3390/ijms22105119 diverse cellular outcomes. -
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Patterns of DNA methylation on the human X chromosome and use in analyzing X-chromosome inactivation by Allison Marie Cotton B.Sc., The University of Guelph, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2012 © Allison Marie Cotton, 2012 Abstract The process of X-chromosome inactivation achieves dosage compensation between mammalian males and females. In females one X chromosome is transcriptionally silenced through a variety of epigenetic modifications including DNA methylation. Most X-linked genes are subject to X-chromosome inactivation and only expressed from the active X chromosome. On the inactive X chromosome, the CpG island promoters of genes subject to X-chromosome inactivation are methylated in their promoter regions, while genes which escape from X- chromosome inactivation have unmethylated CpG island promoters on both the active and inactive X chromosomes. The first objective of this thesis was to determine if the DNA methylation of CpG island promoters could be used to accurately predict X chromosome inactivation status. The second objective was to use DNA methylation to predict X-chromosome inactivation status in a variety of tissues. A comparison of blood, muscle, kidney and neural tissues revealed tissue-specific X-chromosome inactivation, in which 12% of genes escaped from X-chromosome inactivation in some, but not all, tissues. X-linked DNA methylation analysis of placental tissues predicted four times higher escape from X-chromosome inactivation than in any other tissue. Despite the hypomethylation of repetitive elements on both the X chromosome and the autosomes, no changes were detected in the frequency or intensity of placental Cot-1 holes. -
Aberrant Promoter Methylation and Tumor Suppressive Activity of the DFNA5 Gene in Colorectal Carcinoma
Oncogene (2008) 27, 3624–3634 & 2008 Nature Publishing Group All rights reserved 0950-9232/08 $30.00 www.nature.com/onc ORIGINAL ARTICLE Aberrant promoter methylation and tumor suppressive activity of the DFNA5 gene in colorectal carcinoma MS Kim1, X Chang1, K Yamashita1, JK Nagpal1, JH Baek2,GWu3, B Trink1, EA Ratovitski1, M Mori4 and D Sidransky1 1Department of Otolaryngology, Head and Neck Cancer Research Division, Johns Hopkins University, Baltimore, MD, USA; 2Department of Genetic Medicine, Institute of Cell Engineering, Johns Hopkins University, Baltimore, MD, USA; 3Karmanos Cancer Institute, Department of Pathology, Wayne State University, Detroit, MI, USA and 4Department of Surgical Oncology, Medical Institute of Bioregulation, Kyushu University, Tsurumibaru, Beppu, Japan To identify novel methylated gene promoters, we com- Introduction pared differential RNA expression profiles of colorectal cancer (CRC) cell lines with or without treatment of Aberrant gene expression is a characteristic of human 5-aza-20-deoxycytidine (5-aza-dC). Out of 1776 genes cancers, and changes in DNA methylation status can that were initially ‘absent (that is, silenced)’ by gene have profound effects on the expression of genes. Tumor expression array analysis, we selected 163 genes that were suppressor genes (TSGs) display both genetic and increased after 5-aza-dC treatment in at least two of three epigenetic inactivation in human tumors, and the CRC cell lines. The microarray results were confirmed by transcriptional silencing of TSGs has established hy- Reverse Transcription–PCR, and CpG island of the gene permethylation as a common mechanism for loss of promoters were amplified and sequenced for examination TSG function in human cancer (Herman, 1999). -
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.