DOCSLIB.ORG

Transcriptome Dynamics During the Mammalian Cell Cycle

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Transcriptome Dynamics During the Mammalian Cell Cycle TRANSCRIPTOME DYNAMICS DURING THE MAMMALIAN CELL CYCLE. Daniel I. Dominguez A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Pharmacology Chapel Hill 2014 Approved by: Zefeng Wang Gary L. Johnson William Marzluff Lee M. Graves Henrik Dohlman © 2014 Daniel I. Dominguez ALL RIGHTS RESERVED ii ABSTRACT DANIEL I. DOMINGUEZ: Transcriptome Dynamics during the Mammalian Cell Cycle. (Under the Direction of Zefeng Wang, Ph.D.) In recent years, technologies capable of simultaneously deciphering the nucleotide sequence and expression level of most RNAs in the cell have challenged the simplistic view of one gene-one protein. It is now well-appreciated that the cell has a tremendous level of flexibility during RNA processing (i.e. alternative splicing) to produce multiple coding mRNAs from single gene unit. Another surprising find is that most of the genome is transcribed, which leads to the production of a large proportion of RNAs without coding potential (i.e. lncRNAs). Global transcriptome rearrangements have been shown to occur during and regulate key biological processes like development and differentiation. This work focuses on bettering our current understanding of the mammalian cell cycle in the context of transcriptome-wide dynamics. Progression through the mitotic cell cycle has been shown to require periodic gene function. Conventionally, these biological oscillations are thought to be primarily mediated by transcription and protein degradation. Here we report sequencing of the human transcriptome through two continuous cell cycles, revealing periodic dynamics of over 1,000 coding and non-coding RNAs. Additionally, we uncovered widespread periodic splicing events, many of which affect genes that regulate cell cycle. Mechanistically, we show that Cdc2-like kinase 1 undergoes periodic fluctuations through an auto-inhibitory circuit to control a network of iii periodic splicing events that are required for cell cycle. Our findings elucidate a novel mechanism for periodic gene regulation independent of transcription, suggesting that proteome expansion via splicing adds a new regulatory layer for control of gene function during cell division. iv ACKNOWLEDGEMENTS I would like to thank my advisor, Zefeng Wang, for his continued support over the last five years. When I came to UNC, Zefeng was new at running a lab and I was new at being a graduate student. I think we have done awesome together. Zefeng is a brilliant scientist with a ton of foresight, so I really appreciate that he let me see some of my ideas through, even when they seemed likely to fail. Altogether, I couldn’t be happier with the relationship that we have developed. I am also thankful for the members of the Wang lab, past and present: Yang Wang, Rajarshi Choudhury, Shannon Tsai, Meng Ma, Shuyun Dong, Wenjing Zhang and Russell Maxwell. Yang and Raj were especially helpful in the early days, when the lab was still acquiring momentum. Russell worked alongside with me for a few years to ensure all work gets done. I am also grateful for my thesis committee members: Gary Johnson, Lee Graves, Bill Marzluff and Henrik Dohlman. I thank you for being extremely helpful in both science and career advice. UNC has been a great place to work. The Pharmacology department is full of talented folks that are always willing to chat about science and lend a helping hand. I am highly appreciative of the opportunity to do science here. v TABLE OF CONTENTS LIST OF TABLES ............................................................................................................ ix LIST OF FIGURES .......................................................................................................... x LIST OF ABBREVIATIONS ............................................................................................ xii CHAPTERS I. Introduction ....................................................................................................... 1 The mitotic cell cycle ................................................................................... 1 Regulation of cell cycle progression ................................................ 2 RNA dynamics during the cell cycle ........................................................... 4 The cycle-dependent gene expression program ............................. 4 The G1/S wave ............................................................................... 6 The G2/M wave ............................................................................... 9 The M/G1 wave ............................................................................... 9 Quality control checkpoints ........................................................................ 9 The DNA-damage checkpoint ....................................................... 10 The spindle assembly checkpoint ................................................. 11 RNA processing ...................................................................................... 12 Transcription, RNA splicing and alternative splicing ..................... 12 SR proteins ................................................................................... 13 CLK kinases .................................................................................. 15 Cellular regulation of CLK kinases ................................................ 18 CLK inhibitors ................................................................................ 19 vi CLK homologs............................................................................... 19 Global gene expression by CLKs ................................................. 20 Connections between cell cycle and splicing ........................................... 20 Thesis objectives ..................................................................................... 23 II. Materials and methods .................................................................................. 24 Chapter III ................................................................................................ 24 Chapter IV ................................................................................................ 30 Chapter V ................................................................................................. 33 III. Transcriptome dynamics during the mitotic cell cycle ................................... 35 Introduction .............................................................................................. 35 Results ..................................................................................................... 37 Sequencing the cell cycle-dependent transcriptome ..................... 37 Identification, function and regulation of periodic genes ................ 38 Consistency across datasets ........................................................ 40 Identification of periodic alternative splicing .................................. 42 Putative cis-elements and trans-factors that regulate periodic AS ............................................................... 44 Discussion ............................................................................................... 45 IV. CLK1 kinase controls cell cycle processes via an alternative splicing network .......................................................... 57 Introduction .............................................................................................. 58 Results ..................................................................................................... 58 CLK1 is cell cycle regulated .......................................................... 58 CLK1 protein turnover ................................................................... 59 vii CLK1 a kinase is engaged in negative ......................................... 60 CLK1-mediated transcriptome regulation ..................................... 62 CLK1 control CENPE alternative splicing ...................................... 63 CLK1 and SFRS1 regulate CHEK2 splice .................................... 64 CHEK2 variants have different biochemical properties ................ 65 CLK1 is required for normal cell cycle progression and proliferation ......................................... 67 Discussion ............................................................................................... 69 IV. Mitotic trait: A computational method for inferring cell-cycle stage ............... 89 Introduction .............................................................................................. 89 Results ..................................................................................................... 91 Mitotic trait of cells based on transcriptome profile ....................... 91 Mitotic trait of single cells from the human embryo ....................... 92 Mitotic trait of human breast cancers and correlation with molecular subtypes ....................................... 93 Pan-cancer mitotic trait analysis.................................................... 94 Discussion ............................................................................................... 94 VI. Concluding remarks .............................................................................................. 102 Summary ............................................................................................... 102 Outstanding questions ..........................................................................
Load more

Recommended publications
  • An Extensive Program of Periodic Alternative Splicing Linked to Cell
    RESEARCH ARTICLE An extensive program of periodic alternative splicing linked to cell cycle progression Daniel Dominguez1,2, Yi-Hsuan Tsai1,3, Robert Weatheritt4, Yang Wang1,2, Benjamin J Blencowe4*, Zefeng Wang1,5* 1Department of Pharmacology, University of North Carolina at Chapel Hill, Chapel Hill, United States; 2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, United States; 3Program in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, United States; 4Donnelly Centre and Department of Molecular Genetics, University of Toronto, Toronto, Canada; 5Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Science, Shanghai, China Abstract Progression through the mitotic cell cycle requires periodic regulation of gene function at the levels of transcription, translation, protein-protein interactions, post-translational modification and degradation. However, the role of alternative splicing (AS) in the temporal control of cell cycle is not well understood. By sequencing the human transcriptome through two continuous cell cycles, we identify ~ 1300 genes with cell cycle-dependent AS changes. These genes are significantly enriched in functions linked to cell cycle control, yet they do not significantly overlap genes subject to periodic changes in steady-state transcript levels. Many of the periodically spliced genes are controlled by the SR protein kinase CLK1, whose level undergoes cell cycle- dependent fluctuations via an auto-inhibitory circuit. Disruption of CLK1 causes pleiotropic cell cycle defects and loss of proliferation, whereas CLK1 over-expression is associated with various *For correspondence: cancers. These results thus reveal a large program of CLK1-regulated periodic AS intimately [email protected] (BJB); associated with cell cycle control.
    [Show full text]
  • Anti-CLK2 Antibody (ARG66787)
    Product datasheet [email protected] ARG66787 Package: 100 μg anti-CLK2 antibody Store at: -20°C Summary Product Description Rabbit Polyclonal antibody recognizes CLK2 Tested Reactivity Hu Tested Application IHC-P, WB Host Rabbit Clonality Polyclonal Isotype IgG Target Name CLK2 Antigen Species Human Immunogen Synthetic peptide between aa. 1-50 of Human CLK2. Conjugation Un-conjugated Alternate Names CDC-like kinase 2; Dual specificity protein kinase CLK2; EC 2.7.12.1 Application Instructions Application table Application Dilution IHC-P 1:100 - 1:300 WB 1:500 - 1:2000 Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Positive Control COLO205 and A549 Calculated Mw 60 kDa Observed Size ~ 60 kDa Properties Form Liquid Purification Affinity purification with immunogen. Buffer PBS, 0.02% Sodium azide, 50% Glycerol and 0.5% BSA. Preservative 0.02% Sodium azide Stabilizer 50% Glycerol and 0.5% BSA Concentration 1 mg/ml Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. www.arigobio.com 1/3 Note For laboratory research only, not for drug, diagnostic or other use. Bioinformation Gene Symbol CLK2 Gene Full Name CDC-like kinase 2 Background This gene encodes a dual specificity protein kinase that phosphorylates serine/threonine and tyrosine- containing substrates.
    [Show full text]
  • 1 Title: Ultra-Conserved Elements in the Human Genome Authors And
    4/22/2004 Title: Ultra-conserved elements in the human genome Authors and affiliations: Gill Bejerano*, Michael Pheasant**, Igor Makunin**, Stuart Stephen**, W. James Kent*, John S. Mattick** and David Haussler*** *Department of Biomolecular Engineering and ***Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA **ARC Special Research Centre for Functional and Applied Genomics, Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia Corresponding authors: Gill Bejerano ([email protected]) and David Haussler ([email protected]) -------------------------------------------------------------------------------------------------------------------- Supporting on-line material: Separate figures, Like Figure 1 but for each individual chromosome are available in postscript and PDF format, at http://www.cse.ucsc.edu/~jill/ultra.html. Table S1. A table listing all 481 ultra conserved elements and their properties can be found at http://www.cse.ucsc.edu/~jill/ultra.html. The elements were extracted from an alignment of NCBI Build 34 of the human genome (July 2003, UCSC hg16), mouse NCBI Build 30 (February 2003, UCSC mm3), and rat Baylor HGSC v3.1 (June 2003, UCSC rn3). This table does not include an additional, probably ultra conserved element (uc.10) overlapping an alternatively spliced exon of FUSIP1, which is not yet placed in the current assembly of human chromosome 1. Nor does the list contain the ultra conserved elements found in ribosomal RNA sequences, as these are not currently present as part of the draft genome sequences. The small subunit 18S rRNA includes 3 ultra conserved regions of sizes 399, 224, 212bp and the large subunit 28S rRNA contains 3 additional regions of sizes 277, 335, 227bp (the later two are one base apart).
    [Show full text]
  • Network-Based Prediction of Drug Combinations
    Corrected: Publisher correction ARTICLE https://doi.org/10.1038/s41467-019-09186-x OPEN Network-based prediction of drug combinations Feixiong Cheng1,2,3,4,5, Istvań A. Kovacś1,2 & Albert-Laszló ́Barabasí1,2,6,7 Drug combinations, offering increased therapeutic efficacy and reduced toxicity, play an important role in treating multiple complex diseases. Yet, our ability to identify and validate effective combinations is limited by a combinatorial explosion, driven by both the large number of drug pairs as well as dosage combinations. Here we propose a network-based methodology to identify clinically efficacious drug combinations for specific diseases. By 1234567890():,; quantifying the network-based relationship between drug targets and disease proteins in the human protein–protein interactome, we show the existence of six distinct classes of drug–drug–disease combinations. Relying on approved drug combinations for hypertension and cancer, we find that only one of the six classes correlates with therapeutic effects: if the targets of the drugs both hit disease module, but target separate neighborhoods. This finding allows us to identify and validate antihypertensive combinations, offering a generic, powerful network methodology to identify efficacious combination therapies in drug development. 1 Center for Complex Networks Research and Department of Physics, Northeastern University, Boston, MA 02115, USA. 2 Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA. 3 Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44106, USA. 4 Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA. 5 Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA.
    [Show full text]
  • Identification of Three Additional Genes Contiguous to the Glucocerebrosidase Locus on Chromosome 1Q21: Implications for Gaucher Disease Suzanne L
    Downloaded from genome.cshlp.org on October 2, 2021 - Published by Cold Spring Harbor Laboratory Press LETTER Identification of Three Additional Genes Contiguous to the Glucocerebrosidase Locus on Chromosome 1q21: Implications for Gaucher Disease Suzanne L. Winfield, Nahid Tayebi, Brian M. Martin, Edward I. Ginns, and Ellen Sidransky1 Clinical Neuroscience Branch, Intramural Research Program (IRP), National Institute of Mental Health, Bethesda, Maryland 20892 Gaucher disease results from the deficiency of the lysosomal enzyme glucocerebrosidase (EC 3.2.1.45). Although the functional gene for glucocerebrosidase (GBA) and its pseudogene (psGBA), located in close proximity on chromosome 1q21, have been studied extensively, the flanking sequence has not been well characterized. The recent identification of human metaxin (MTX) immediately downstream of psGBA prompted a closer analysis of the sequence of the entire region surrounding the GBA gene. We now report the genomic DNA sequence and organization of a 75-kb region around GBA, including the duplicated region containing GBA and MTX. The origin and endpoints of the duplication leading to the pseudogenes for GBA and MTX are now clearly established. We also have identified three new genes within the 32 kb of sequence upstream to GBA, all of which are transcribed in the same direction as GBA. Of these three genes, the gene most distal to GBA is a protein kinase (clk2). The second gene, propin1, has a 1.5-kb cDNA and shares homology to a rat secretory carrier membrane protein 37 (SCAMP37). Finally, cote1, a gene of unknown function lies most proximal to GBA. The possible contributions of these closely arrayed genes to the more atypical presentations of Gaucher disease is now under investigation.
    [Show full text]
  • Differentially Methylated Plasticity Genes in the Amygdala of Young
    15548 • The Journal of Neuroscience, November 19, 2014 • 34(47):15548–15556 Neurobiology of Disease Differentially Methylated Plasticity Genes in the Amygdala of Young Primates Are Linked to Anxious Temperament, an at Risk Phenotype for Anxiety and Depressive Disorders X Reid S. Alisch,1 Pankaj Chopra,5 Andrew S. Fox,2,4,6 Kailei Chen,3 Andrew T.J. White,1 Patrick H. Roseboom,1 Sunduz Keles,3 and Ned H. Kalin1,2,4,6 Departments of 1Psychiatry, 2Psychology, 3Statistics, and the 4Health Emotion Research Institute, University of Wisconsin, Madison, Wisconsin 53719, 5Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia 30322, and 6Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin, Madison, Wisconsin 53705 Children with an anxious temperament (AT) are at a substantially increased risk to develop anxiety and depression. The young rhesus monkey is ideal for studying the origin of human AT because it shares with humans the genetic, neural, and phenotypic underpinnings of complex social and emotional functioning. Heritability, functional imaging, and gene expression studies of AT in young monkeys revealed that the central nucleus of the amygdala (Ce) is a key environmentally sensitive substrate of this at risk phenotype. Because epigenetic marks (e.g., DNA methylation) can be modulated by environmental stimuli, these data led us to hypothesize a role for DNA methylation in the development of AT. To test this hypothesis, we used reduced representation bisulfite sequencing to examine the cross-sectional genome-wide methylation levels in the Ce of 23 age-matched monkeys (1.3 Ϯ 0.2 years) phenotyped for AT.
    [Show full text]
  • Metabolism, Ubiquinone Synthesis, and Longevity
    Downloaded from genesdev.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press PERSPECTIVE Metabolism, ubiquinone synthesis, and longevity Hugo Aguilaniu,1 Jenni Durieux,1 and Andrew Dillin2 Molecular and Cell Biology Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037, USA “You have made your way from worm to man, but much gram of tissue and lived longer than animals with higher within you is still a worm.” metabolic rates. Exceptions have been discovered since —Nieztsche Pearl’s initial observations, such as the high metabolic rates of some long-lived birds (Holmes et al. 2001); how- Until recently, the mechanisms that control the aging ever, Pearl’s initial observation led to the formulation of process were thought to be immensely complex and the “rate of living theory of aging” (Pearl 1928). The nearly impossible to dissect at the molecular level. How- theory suggests that reduced metabolic rates in an ani- ever, genetic analysis, primarily in model organisms mal should result in an increased life span. such as yeast, worms, and flies, is dramatically changing Several years later, the “rate of living theory of aging” this view. It seems that at least three distinct genetic became more refined with the formulation of the “oxy- networks control the aging process. These networks in- gen radical theory of aging” proposed by Denham Har- clude the insulin/IGF-1 signaling pathway, signaling man (Harman 1956). Harman reasoned that reactions us- that arises from the mitochondrial electron transport • ing molecular oxygen create, on occasion, toxic O − radi- chain, and finally, mechanisms that govern the response 2 cals.
    [Show full text]
  • CLK2 (NM 003993) Human Tagged ORF Clone – RC208778 | Origene
    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 RC208778 CLK2 (NM_003993) Human Tagged ORF Clone Product data: Product Type: Expression Plasmids Product Name: CLK2 (NM_003993) Human Tagged ORF Clone Tag: Myc-DDK Symbol: CLK2 Vector: pCMV6-Entry (PS100001) E. coli Selection: Kanamycin (25 ug/mL) Cell Selection: Neomycin 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 / 5 CLK2 (NM_003993) Human Tagged ORF Clone – RC208778 ORF Nucleotide >RC208778 representing NM_003993 Sequence: Red=Cloning site Blue=ORF Green=Tags(s) TTTTGTAATACGACTCACTATAGGGCGGCCGGGAATTCGTCGACTGGATCCGGTACCGAGGAGATCTGCC GCCGCGATCGCC ATGCCGCATCCTCGAAGGTACCACTCCTCAGAGCGAGGCAGCCGGGGGAGTTACCGTGAACACTATCGGA GCCGAAAGCATAAGCGACGAAGAAGTCGCTCCTGGTCAAGTAGTAGTGACCGGACACGACGGCGTCGGCG AGAGGACAGCTACCATGTCCGTTCTCGAAGCAGTTATGATGATCGTTCGTCCGACCGGAGGGTGTATGAC CGGCGATACTGTGGCAGCTACAGACGCAACGATTATAGCCGGGATCGGGGAGATGCCTACTATGACACAG ACTATCGGCATTCCTATGAATATCAGCGGGAGAACAGCAGTTACCGCAGCCAGCGCAGCAGCCGGAGGAA GCACAGACGGCGGAGGAGGCGCAGCCGGACATTTAGCCGCTCATCTTCGCAGCACAGCAGCCGGAGAGCC AAGAGTGTAGAGGACGACGCTGAGGGCCACCTCATCTACCACGTCGGGGACTGGCTACAAGAGCGATATG AAATCGTTAGCACCTTAGGAGAGGGGACCTTCGGCCGAGTTGTACAATGTGTTGACCATCGCAGGGGTGG GGCTCGAGTTGCCCTGAAGATCATTAAGAATGTGGAGAAGTACAAGGAAGCAGCTCGACTTGAGATCAAC GTGCTAGAGAAAATCAATGAGAAAGACCCTGACAACAAGAACCTCTGTGTCCAGATGTTTGACTGGTTTG
    [Show full text]
  • Dual-Specificity, Tyrosine Phosphorylation-Regulated Kinases
    International Journal of Molecular Sciences Review Dual-Specificity, Tyrosine Phosphorylation-Regulated Kinases (DYRKs) and cdc2-Like Kinases (CLKs) in Human Disease, an Overview Mattias F. Lindberg and Laurent Meijer * Perha Pharmaceuticals, Perharidy Peninsula, 29680 Roscoff, France; [email protected] * Correspondence: [email protected] Abstract: Dual-specificity tyrosine phosphorylation-regulated kinases (DYRK1A, 1B, 2-4) and cdc2- like kinases (CLK1-4) belong to the CMGC group of serine/threonine kinases. These protein ki- nases are involved in multiple cellular functions, including intracellular signaling, mRNA splicing, chromatin transcription, DNA damage repair, cell survival, cell cycle control, differentiation, ho- mocysteine/methionine/folate regulation, body temperature regulation, endocytosis, neuronal development, synaptic plasticity, etc. Abnormal expression and/or activity of some of these kinases, DYRK1A in particular, is seen in many human nervous system diseases, such as cognitive deficits associated with Down syndrome, Alzheimer’s disease and related diseases, tauopathies, demen- tia, Pick’s disease, Parkinson’s disease and other neurodegenerative diseases, Phelan-McDermid syndrome, autism, and CDKL5 deficiency disorder. DYRKs and CLKs are also involved in dia- betes, abnormal folate/methionine metabolism, osteoarthritis, several solid cancers (glioblastoma, breast, and pancreatic cancers) and leukemias (acute lymphoblastic leukemia, acute megakaryoblas- Citation: Lindberg, M.F.; Meijer, L. tic leukemia), viral infections (influenza, HIV-1, HCMV, HCV, CMV, HPV), as well as infections Dual-Specificity, Tyrosine caused by unicellular parasites (Leishmania, Trypanosoma, Plasmodium). This variety of pathological Phosphorylation-Regulated Kinases implications calls for (1) a better understanding of the regulations and substrates of DYRKs and (DYRKs) and cdc2-Like Kinases CLKs and (2) the development of potent and selective inhibitors of these kinases and their evaluation (CLKs) in Human Disease, an as therapeutic drugs.
    [Show full text]
  • Benzobisthiazoles Represent a Novel Scaffold for Kinase Inhibitors of CLK
    This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited. Article pubs.acs.org/biochemistry Benzobisthiazoles Represent a Novel Scaffold for Kinase Inhibitors of CLK Family Members † † ‡ † † † Krisna Prak, Janos Kriston-Vizi, A. W. Edith Chan, Christin Luft, Joana R. Costa, Niccolo Pengo, † and Robin Ketteler*, † MRC Laboratory for Molecular Cell Biology, University College London, London WC1E 6BT, U.K. ‡ Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, U.K. *S Supporting Information ABSTRACT: Protein kinases are essential regulators of most cellular processes and are involved in the etiology and progression of multiple diseases. The cdc2-like kinases (CLKs) have been linked to various neurodegenerative disorders, metabolic regulation, and virus infection, and the kinases have been recognized as potential drug targets. Here, we have developed a screening workflow for the identification of potent CLK2 inhibitors and identified compounds with a novel chemical scaffold structure, the benzobisthiazoles, that has not been previously reported for kinase inhibitors. We propose models for binding of these compounds to CLK family proteins and key residues in CLK2 that are important for the compound interactions and the kinase activity. We identified structural elements within the benzobisthiazole that determine CLK2 and CLK3 inhibition, thus providing a rationale for selectivity assays. In summary, our results will inform structure-based design of CLK family inhibitors based on the novel benzobisthiazole scaffold. rotein kinases control and modulate a wide variety of production by modulating splicing of the provirus and affecting P biological processes through their catalytic activity,1,2 gene expression of viral genes.12 CLK1 inhibitors are also including signal transduction and gene splicing.
    [Show full text]
  • An Integrated Data Analysis Approach to Characterize Genes Highly Expressed in Hepatocellular Carcinoma
    Oncogene (2005) 24, 3737–3747 & 2005 Nature Publishing Group All rights reserved 0950-9232/05 $30.00 www.nature.com/onc An integrated data analysis approach to characterize genes highly expressed in hepatocellular carcinoma Mohini A Patil1,6, Mei-Sze Chua2,6, Kuang-Hung Pan3,6, Richard Lin3, Chih-Jian Lih3, Siu-Tim Cheung4, Coral Ho1,RuiLi2, Sheung-Tat Fan4, Stanley N Cohen3, Xin Chen1,5 and Samuel So2 1Department of Biopharmaceutical Sciences, University of California, San Francisco, CA 94143, USA; 2Department of Surgery and Asian Liver Center, Stanford University, Stanford, CA 94305, USA; 3Department of Genetics, Stanford University, Stanford, CA 94305, USA; 4Department of Surgery and Center for the Study of Liver Disease, University of Hong Kong, Hong Kong, China; 5Liver Center, University of California, San Francisco, CA 94143, USA Hepatocellular carcinoma (HCC) is one of the major cancer deaths worldwide (Parkin, 2001; Parkin et al., causes of cancer deaths worldwide. New diagnostic and 2001). Epidemiological and molecular genetic studies therapeutic options are needed for more effective and early have demonstrated that the development of HCC spans detection and treatment of this malignancy. We identified several decades, often starting with hepatitis B virus 703 genes that are highly expressed in HCC using DNA (HBV) or hepatitis C virus (HCV) infections. Chronic microarrays, and further characterized them in order to carriers of HBV or HCV are at much higher risk of uncover novel tumor markers, oncogenes, and therapeutic developing HCC, especially when infection has been targets for HCC. Using Gene Ontology annotations, genes accompanied by liver cirrhosis (El-Serag, H., 2001; El- with functions related to cell proliferation and cell cycle, Serag, H.B., 2002).
    [Show full text]
  • CLK2 (F-4): Sc-393909
    SAN TA C RUZ BI OTEC HNOL OG Y, INC . CLK2 (F-4): sc-393909 BACKGROUND APPLICATIONS The phosphorylation and dephosphorylation of proteins on serine and threo - CLK2 (F-4) is recommended for detection of CLK2 of mouse, rat and human nine residues is an essential means of regulating a broad range of cellular origin by Western Blotting (starting dilution 1:100, dilution range 1:100- functions in eukaryotes, including cell division, homeostasis and apoptosis. 1:1000), immunoprecipitation [1-2 µg per 100-500 µg of total protein (1 ml A group of proteins that are intimately involved in this process are the ser ine/ of cell lysate)], immunofluorescence (starting dilution 1:50, dilution range threonine (Ser/Thr) protein kinases. CLK2 (CDC-like kinase 2) is a 499 amino 1:50-1:500) and solid phase ELISA (starting dilution 1:30, dilution range acid nuclear protein that contains one protein kinase domain and belongs to 1:30- 1:3000). the Ser/Thr protein kinase family. Using ATP, CLK2 phosphorylates serine- and Suitable for use as control antibody for CLK2 siRNA (h): sc-72923, CLK2 arginine-rich (SR) components of the spliceosomal complex, possibly playing siRNA (m): sc-72924, CLK2 shRNA Plasmid (h): sc-72923-SH, CLK2 shRNA a role in the control of RNA splicing. CLK2 exists as two alternatively spliced Plasmid (m): sc-72924-SH, CLK2 shRNA (h) Lentiviral Particles: sc-72923-V isoforms, designated short and long, and is encoded by a gene which maps and CLK2 shRNA (m) Lentiviral Particles: sc-72924-V. to human chromosome 1.
    [Show full text]