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SRC Antibody - N-Terminal Region (ARP32476 P050) Data Sheet
SRC antibody - N-terminal region (ARP32476_P050) Data Sheet Product Number ARP32476_P050 Product Name SRC antibody - N-terminal region (ARP32476_P050) Size 50ug Gene Symbol SRC Alias Symbols ASV; SRC1; c-SRC; p60-Src Nucleotide Accession# NM_005417 Protein Size (# AA) 536 amino acids Molecular Weight 60kDa Product Format Lyophilized powder NCBI Gene Id 6714 Host Rabbit Clonality Polyclonal Official Gene Full Name V-src sarcoma (Schmidt-Ruppin A-2) viral oncogene homolog (avian) Gene Family SH2D This is a rabbit polyclonal antibody against SRC. It was validated on Western Blot by Aviva Systems Biology. At Aviva Systems Biology we manufacture rabbit polyclonal antibodies on a large scale (200-1000 Description products/month) of high throughput manner. Our antibodies are peptide based and protein family oriented. We usually provide antibodies covering each member of a whole protein family of your interest. We also use our best efforts to provide you antibodies recognize various epitopes of a target protein. For availability of antibody needed for your experiment, please inquire (). Peptide Sequence Synthetic peptide located within the following region: QTPSKPASADGHRGPSAAFAPAAAEPKLFGGFNSSDTVTSPQRAGPLAGG This gene is highly similar to the v-src gene of Rous sarcoma virus. This proto-oncogene may play a role in the Description of Target regulation of embryonic development and cell growth. SRC protein is a tyrosine-protein kinase whose activity can be inhibited by phosphorylation by c-SRC kinase. Mutations in this gene could be involved in the -
Interplay Between Coding and Exonic Splicing Regulatory Sequences
Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press Research Interplay between coding and exonic splicing regulatory sequences Nicolas Fontrodona,1,4 Fabien Aubé,1,4 Jean-Baptiste Claude,1 Hélène Polvèche,1,5 Sébastien Lemaire,1 Léon-Charles Tranchevent,2 Laurent Modolo,3 Franck Mortreux,1 Cyril F. Bourgeois,1 and Didier Auboeuf1 1Université Lyon, ENS de Lyon, Université Claude Bernard, CNRS UMR 5239, INSERM U1210, Laboratory of Biology and Modelling of the Cell, F-69007, Lyon, France; 2Proteome and Genome Research Unit, Department of Oncology, Luxembourg Institute of Health (LIH), L-1445 Strassen, Luxembourg; 3LBMC Biocomputing Center, CNRS UMR 5239, INSERM U1210, F-69007, Lyon, France The inclusion of exons during the splicing process depends on the binding of splicing factors to short low-complexity reg- ulatory sequences. The relationship between exonic splicing regulatory sequences and coding sequences is still poorly un- derstood. We demonstrate that exons that are coregulated by any given splicing factor share a similar nucleotide composition bias and preferentially code for amino acids with similar physicochemical properties because of the nonran- domness of the genetic code. Indeed, amino acids sharing similar physicochemical properties correspond to codons that have the same nucleotide composition bias. In particular, we uncover that the TRA2A and TRA2B splicing factors that bind to adenine-rich motifs promote the inclusion of adenine-rich exons coding preferentially for hydrophilic amino acids that correspond to adenine-rich codons. SRSF2 that binds guanine/cytosine-rich motifs promotes the inclusion of GC-rich exons coding preferentially for small amino acids, whereas SRSF3 that binds cytosine-rich motifs promotes the inclusion of exons coding preferentially for uncharged amino acids, like serine and threonine that can be phosphorylated. -
Stefano Sellitto 19-05-2020.Pdf
RNA Binding Proteins: from physiology to pathology An update Stefano Sellitto RBPs regulate the RNA metabolism A ‘conventional’ RNA-Binding Protein (RBP) participates in the formation of ribonucleoprotein (RNP) complexes that are principally involved in gene expression. Keene, 2007 High-Throughuput sequencing to study the RBPs world RIP-Seq (i)CLIP PAR-CLIP Hentze et al., 2018 The concept of RNA operon The RBPs profile is highly dynamic The combinatorial association of many RBPs acting in trans on RNA molecules results in the metabolic regulation of a distinct RNA subpopulations. Keene, 2007 The molecular features of protein-RNA interactions "Classical" RNA-Binding Domains Lunde et al., 2007 "Classical" RNA-Binding Domains RNA-recognition motif (RRM) double-stranded RNA-binding motif (dsRBM) Zinc-finger motif Stefl et al., 2005 Modularity of RBPs RBPs are usually composed by several repeated domains Lunde et al., 2007 Expanding the concept of the RNA Binding Hentze et al., 2018 Novel types of RNA binding Hentze et al., 2018 Lunde et al., 2007 RNA metabolism and neurological diseases RNA binding proteins preserves neuronal integrity De Conti et al., 2017 Alterations of RBPs in neurological disorders Nussbacher et al., 2019 Microsatellite expansion in FXS: reduced FMR1 transcription The reduction of FMRP levels induces an overexpressed LTD activity Bassell & Warren, 2008 Huber et al., 2002 Microsatellite expansion in FXTAS: FMR1 RNA-meidated toxicity FMR1 expanded RNA impairs the miRNA processing Sellier et al., 2013 Loss-of-function VS Gain-of-function Park et al., 2015 TDP-43 and FUS/TLS Ling et al., 2013 TDP-43 and FUS/TLS in ALS and FTD Ling et al., 2013 Cookson, 2017 Loss-of-function VS Gain-of-function Nucelar clearance (LOF) TDP-43 Nuclear TDP-43 (LOF) Loss of TDP-43 negative autoregulation Nucleus Abolishing RNA binding ability Cytoplasmatic stress (GOF) mitigates mutant TDP-43 toxicity Prevent mutant TDP-43 toxic activity on RNAs (GOF) Ihara et al., 2013 . -
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58 cambridge.org/jcts 2172 with these clinical observations, we observed altered myelopoiesis in HnrnpkTg mice. These mice demonstrate increased CD11b + Gr1 + populations in the Association between CYP450 polymorphisms and the bone marrow and peripheral blood. Indeed, these mice develop myeloid use of complementary medicine among patients with leukemia, indicated by >20% of circulating white blood cells harboring markers drug-resistant epilepsy in Puerto Rico of immature stem cells in conjunction with positive myeloperoxidase staining Bianca A. Torres-Hernández, Miriam E. Ríos Motta, Adrián Llerenaes and blast-appearing morphology. RPPA revealed expression of c-Myc positively correlated with increased hnRNP K levels. In HnrnpkTg mice, c-Myc protein and Jorge Duconge was increased, yet MYC RNA was invariably decreased compared to wildtype. University of Puerto Rico-Medical Sciences Campus, San Juan, Puerto To decipher a mechanism by which this may occur, we demonstrated a post- Rico transcriptional interaction between hnRNP K and c-Myc in vivo. JQ1, a BRD4 inhibitor, that epigenetically decreases c-Myc expression showed preferential activity against myeloid cells expressing high levels of hnRNP K both in vitro and OBJECTIVES/SPECIFIC AIMS: Patients with epilepsy often combine their in vivo. DISCUSSION/SIGNIFICANCE OF IMPACT: These preliminary studies antiepileptic drugs (AEDs) with complementary medicine (CM). They use CM demonstrate that hnRNP K overexpression causes myeloid malignancies in to treat their symptoms of comorbidities disorder, to reduce the side effect of both mouse and man. We have determined that c-Myc contributes in part to the AEDs or trying to achieve better control of their seizures. However, the hnRNP K-mediated leukemogenesis, and that targeting c-Myc may be an inconsistent patters of the use of CM among countries have been attributed to effective strategy for hnRNP K-overexpressing AML. -
KH Domain Containing RNA-Binding Proteins Coordinate with Micrornas to Regulate
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.03.235127; this version posted August 4, 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. 1 KH domain containing RNA-binding proteins coordinate with microRNAs to regulate 2 Caenorhabditis elegans development. 3 4 Haskell D 1, Zinovyeva A1*. 5 6 7 (1) Division of Biology. Kansas State University. Manhattan, KS, 66506 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.03.235127; this version posted August 4, 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. 24 Running title: KH domain proteins coordinate with microRNAs, C. elegans 25 26 27 28 29 30 Keywords: microRNA, RNA binding protein, KH domain, hnRNPK 31 32 33 34 35 * Corresponding author: Anna Zinovyeva, PhD, 28 Ackert Hall, 1717 Claflin Road, Manhattan, 36 KS 66506, phone: 1-785-532-7727, email: [email protected] 37 38 39 40 41 42 43 44 45 46 2 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.03.235127; this version posted August 4, 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. -
Genetic and Pharmacological Approaches to Preventing Neurodegeneration
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2012 Genetic and Pharmacological Approaches to Preventing Neurodegeneration Marco Boccitto University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Neuroscience and Neurobiology Commons Recommended Citation Boccitto, Marco, "Genetic and Pharmacological Approaches to Preventing Neurodegeneration" (2012). Publicly Accessible Penn Dissertations. 494. https://repository.upenn.edu/edissertations/494 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/494 For more information, please contact [email protected]. Genetic and Pharmacological Approaches to Preventing Neurodegeneration Abstract The Insulin/Insulin-like Growth Factor 1 Signaling (IIS) pathway was first identified as a major modifier of aging in C.elegans. It has since become clear that the ability of this pathway to modify aging is phylogenetically conserved. Aging is a major risk factor for a variety of neurodegenerative diseases including the motor neuron disease, Amyotrophic Lateral Sclerosis (ALS). This raises the possibility that the IIS pathway might have therapeutic potential to modify the disease progression of ALS. In a C. elegans model of ALS we found that decreased IIS had a beneficial effect on ALS pathology in this model. This beneficial effect was dependent on activation of the transcription factor daf-16. To further validate IIS as a potential therapeutic target for treatment of ALS, manipulations of IIS in mammalian cells were investigated for neuroprotective activity. Genetic manipulations that increase the activity of the mammalian ortholog of daf-16, FOXO3, were found to be neuroprotective in a series of in vitro models of ALS toxicity. -
Anti-HIST1H1E K51ac Antibody
FOR RESEARCH USE ONLY! 02/20 Anti-HIST1H1E K51ac Antibody CATALOG NO.: A2051-100 (100 µl) BACKGROUND DESCRIPTION: Histones are basic nuclear proteins responsible for nucleosome structure of the chromosomal fiber in eukaryotes. Two molecules of each of the four core histones (H2A, H2B, H3, and H4) form an octamer, around which approximately 146 bp of DNA is wrapped in repeating units, called nucleosomes. The linker histone, H1, interacts with linker DNA between nucleosomes and functions in the compaction of chromatin into higher order structures. This gene is intronless and encodes a replication-dependent histone that is a member of the histone H1 family. Transcripts from this gene lack poly A tails but instead contain a palindromic termination element. This gene is found in the large histone gene cluster on chromosome 6. Histone H1.4 (Histone H1b) (Histone H1s-4), HIST1H1E, H1F4 ALTERNATE NAMES: ANTIBODY TYPE: Polyclonal HOST/ISOTYPE: Rabbit / IgG IMMUNOGEN: Acetylated peptide sequence targeting residues around Lysine 51 of human Histone H1.4 PURIFICATION: Antigen Affinity purified FORM: Liquid FORMULATION: In 0.01 M PBS, pH 7.4, 50% Glycerol, 0.03% proclin 300 SPECIES REACTIVITY: Human STORAGE CONDITIONS: Store at -20ºC. Avoid freeze / thaw cycles. APPLICATIONS AND USAGE: ICC 1:20-1:200, IF 1:50-1:200 This information is only intended as a guide. The optimal dilutions must be determined by the user Immunocytochemistry analysis of HeLa cells using Anti-HIST1H1E K51ac antibody at dilution of 1:100. Immunofluorescent analysis of HeLa cells (treated with sodium butyrate, 30 mM, 4 hrs) using Anti-HIST1H1E K51ac antibody at dilution of 1:100 and Alexa Fluor 488-conjugated Goat Anti-Rabbit IgG (H+L) as secondary antibody. -
Deletions of IKZF1 and SPRED1 Are Associated with Poor Prognosis in A
Leukemia (2014) 28, 302–310 & 2014 Macmillan Publishers Limited All rights reserved 0887-6924/14 www.nature.com/leu ORIGINAL ARTICLE Deletions of IKZF1 and SPRED1 are associated with poor prognosis in a population-based series of pediatric B-cell precursor acute lymphoblastic leukemia diagnosed between 1992 and 2011 L Olsson1, A Castor2, M Behrendtz3, A Biloglav1, E Forestier4, K Paulsson1 and B Johansson1,5 Despite the favorable prognosis of childhood acute lymphoblastic leukemia (ALL), a substantial subset of patients relapses. As this occurs not only in the high risk but also in the standard/intermediate groups, the presently used risk stratification is suboptimal. The underlying mechanisms for treatment failure include the presence of genetic changes causing insensitivity to the therapy administered. To identify relapse-associated aberrations, we performed single-nucleotide polymorphism array analyses of 307 uniformly treated, consecutive pediatric ALL cases accrued during 1992–2011. Recurrent aberrations of 14 genes in patients who subsequently relapsed or had induction failure were detected. Of these, deletions/uniparental isodisomies of ADD3, ATP10A, EBF1, IKZF1, PAN3, RAG1, SPRED1 and TBL1XR1 were significantly more common in B-cell precursor ALL patients who relapsed compared with those remaining in complete remission. In univariate analyses, age (X10 years), white blood cell counts (4100 Â 109/l), t(9;22)(q34;q11), MLL rearrangements, near-haploidy and deletions of ATP10A, IKZF1, SPRED1 and the pseudoautosomal 1 regions on Xp/Yp were significantly associated with decreased 10-year event-free survival, with IKZF1 abnormalities being an independent risk factor in multivariate analysis irrespective of the risk group. Older age and deletions of IKZF1 and SPRED1 were also associated with poor overall survival. -
Molecular Basis of Sequence-Specific Single-Stranded DNA Recognition By
The EMBO Journal Vol. 21 No. 13 pp. 3476±3485, 2002 Molecular basis of sequence-speci®c single-stranded DNA recognition by KH domains: solution structure of a complex between hnRNP K KH3 and single-stranded DNA Demetrios T.Braddock1,2, James L.Baber1, mitosis (Michelotti et al., 1997) and the tight control of David Levens2 and G.Marius Clore1,3 oncogenes (He et al., 2000; Liu et al., 2001). Recently, we solved the structure of a complex between 1Laboratory of Chemical Physics, Building 5, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of the KH3 and KH4 domains of FBP (FBP3/4) and a Health, Bethesda, MD 20892-0510 and 2Laboratory of Pathology, ssDNA 29mer from FUSE (Braddock et al., 2002). In the Building 10, National Cancer Institute, National Institutes of Health, FBP3/4±FUSE complex, KH3 and KH4 bind in a speci®c Bethesda, MD 20892, USA orientation and register to the ssDNA 29mer, which is 3Corresponding author preserved in complexes of the individual KH domains e-mail: [email protected] bound to shorter oligonucleotides, 9±10 bp in length, encompassing their respective target sites in the larger To elucidate the basis of sequence-speci®c single- complex. Although the ssDNA binding site is located stranded (ss) DNA recognition by K homology (KH) within a relatively narrow groove that generally favors domains, we have solved the solution structure of a pyrimidines over purines, the origin of further sequence- complex between the KH3 domain of the transcrip- speci®c base recognition appears to be subtle. -
Gene Ontology Functional Annotations and Pleiotropy
Network based analysis of genetic disease associations Sarah Gilman Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2013 Sarah Gilman All Rights Reserved ABSTRACT Network based analysis of genetic disease associations Sarah Gilman Despite extensive efforts and many promising early findings, genome-wide association studies have explained only a small fraction of the genetic factors contributing to common human diseases. There are many theories about where this “missing heritability” might lie, but increasingly the prevailing view is that common variants, the target of GWAS, are not solely responsible for susceptibility to common diseases and a substantial portion of human disease risk will be found among rare variants. Relatively new, such variants have not been subject to purifying selection, and therefore may be particularly pertinent for neuropsychiatric disorders and other diseases with greatly reduced fecundity. Recently, several researchers have made great progress towards uncovering the genetics behind autism and schizophrenia. By sequencing families, they have found hundreds of de novo variants occurring only in affected individuals, both large structural copy number variants and single nucleotide variants. Despite studying large cohorts there has been little recurrence among the genes implicated suggesting that many hundreds of genes may underlie these complex phenotypes. The question -
Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients with Stable Coronary Heart Disease
Supplementary Online Content Ganz P, Heidecker B, Hveem K, et al. Development and validation of a protein-based risk score for cardiovascular outcomes among patients with stable coronary heart disease. JAMA. doi: 10.1001/jama.2016.5951 eTable 1. List of 1130 Proteins Measured by Somalogic’s Modified Aptamer-Based Proteomic Assay eTable 2. Coefficients for Weibull Recalibration Model Applied to 9-Protein Model eFigure 1. Median Protein Levels in Derivation and Validation Cohort eTable 3. Coefficients for the Recalibration Model Applied to Refit Framingham eFigure 2. Calibration Plots for the Refit Framingham Model eTable 4. List of 200 Proteins Associated With the Risk of MI, Stroke, Heart Failure, and Death eFigure 3. Hazard Ratios of Lasso Selected Proteins for Primary End Point of MI, Stroke, Heart Failure, and Death eFigure 4. 9-Protein Prognostic Model Hazard Ratios Adjusted for Framingham Variables eFigure 5. 9-Protein Risk Scores by Event Type This supplementary material has been provided by the authors to give readers additional information about their work. Downloaded From: https://jamanetwork.com/ on 10/02/2021 Supplemental Material Table of Contents 1 Study Design and Data Processing ......................................................................................................... 3 2 Table of 1130 Proteins Measured .......................................................................................................... 4 3 Variable Selection and Statistical Modeling ........................................................................................ -
ACE2 Gene Variants May Underlie Interindividual Variability and Susceptibility to COVID-19 in the Italian Population
medRxiv preprint doi: https://doi.org/10.1101/2020.04.03.20047977; this version posted June 2, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. ACE2 gene variants may underlie interindividual variability and susceptibility to COVID-19 in the Italian population ACE2 gene variants in the Italian population Benetti Elisa1 , Tita Rossella2 , Spiga Ottavia3, Ciolfi Andrea4, Birolo Giovanni5, Bruselles Alessandro6, Doddato Gabriella7, Giliberti Annarita7, Marconi Caterina8, Musacchia Francesco9, Pippucci Tommaso10, Torella Annalaura11, Trezza Alfonso3, Valentino Floriana7, Baldassarri Margherita7, Brusco Alfredo5,12, Asselta Rosanna13,14, Bruttini Mirella2,7, Furini Simone1, Seri Marco8,10, Nigro Vincenzo9,11, Matullo Giuseppe5,12, Tartaglia Marco4, Mari Francesca2,7, Renieri Alessandra2,7*, Pinto Anna Maria2 1 Department of Medical Biotechnologies, University of Siena, Siena, Italy 2 Genetica Medica, Azienda Ospedaliera Universitaria Senese, Siena, Italy 3 Dept. of Biotechnology, Chemistry and Pharmacy, University of Siena, Siena, Italy 4 Genetics and Rare Diseases Research Division, Ospedale Pediatrico Bambino Gesù, Rome, Italy 5 Department of Medical Sciences, University of Turin, Turin, Italy 6 Department of Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy 7 Medical Genetics, University of Siena, Siena, Italy 8 Department of