DOCSLIB.ORG

MOLECULAR GENETI a Thesis Submitted to the School Of

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
MOLECULAR GENETI a Thesis Submitted to the School Of MOLECULAR GENETICS OF CATTLE MUSCULARITY By Irida Novianti A thesis submitted to the University of Adelaide in fulfilment of the requirement of the degree of Master of Agricultural Science The University of Adelaide School of Animal and Veterinary Science December 2010 DECLARATION I declare that this thesis is a record of original work and contains no material that has been accepted for the award of any other degree or diploma in any university or other tertiary institution to Irida Novianti. To the best of my knowledge and belief, this thesis contains no material previously published or written by any other person, except where due reference is made in the text. I give consent to this copy of my thesis, when deposited in the University Library, being made available for loan and photocopying, subject to the provisions of the Copyright Act 1968. I also give permission for the digital version of my thesis to be made available on the web, via the University’s digital research repository, the Library catalogue, the Australasian Digital Theses Program (ADTP) and also through web search engines, unless permission has been granted by the University to restrict access for a period of time. Irida Novianti December, 2010 ii TABLE OF CONTENTS Declaration ........................................................................................................... ii Index of Figures ................................................................................................... vi Index of Tables ..................................................................................................... viii Index of Appendix ............................................................................................... x Dedication ............................................................................................................. xi Acknowledgements .............................................................................................. xii Abstract ................................................................................................................ xiii Chapter 1: Literature Review ............................................................................ 1 1.1 Introduction............................................................................................... 2 1.2 Literature review ...................................................................................... 4 1.2.1 Muscle development in cattle ........................................................... 4 1.2.2 Genetic parameter for growth traits .................................................. 5 1.2.3 Genetic parameter for body dimension related to muscularity ......... 7 1.2.3.1 Heritability for body dimension related to muscularity ....... 8 1.2.3.2 Genetic correlation between body dimension related to muscularity, growth and carcass traits ................ 10 1.2.4 Genetic parameters of carcass traits ................................................. 12 1.2.5 Molecular genetics of muscularity traits .......................................... 13 1.2.5.1 QTL for growth and carcass traits ........................................ 13 1.2.5.2 Genes involved in muscle development and carcass traits .. 16 1.2.5.2a Insulin-like growth factor 1 (IGF1) ............................... 17 1.2.5.2b Myostatin ....................................................................... 17 1.2.6 Summary ........................................................................................... 23 1.3 Research objectives ................................................................................... 24 iii Chapter 2: Materials and Methods .................................................................... 25 2.1 J.S Davies cattle mapping project .................................................... 26 2.2 Mapping quantitative trait loci (QTL) ............................................ 31 2.3 Identification of candidate genes ...................................................... 33 2.4 Optimization of PCR condition ........................................................ 34 2.5 DNA purification from PCR reaction .............................................. 35 2.6 Sequencing reaction of PCR product ............................................... 35 2.7 Genotyping using high resolution melts .......................................... 36 2.8 Statistical analysis .............................................................................. 38 Chapter 3: QTL Mapping and Candidate Gene Selection .............................. 43 3.1 Introduction ....................................................................................... 44 3.2 Results ................................................................................................. 44 3.2.1 QTL for muscularity related traits ............................................. 44 3.2.2 Effects of Myostatin F94L genotype on QTL ........................... 48 3.2.3 Candidate gene selection ........................................................... 52 3.3 Discussion ........................................................................................... 58 3.4 Summary ............................................................................................ 64 Chapter 4: SNP Association Studies .................................................................. 65 4.1 Introduction ....................................................................................... 66 4.2 Results and discussion ....................................................................... 67 4.2.1 Candidate gene polymorphisms identification .......................... 67 4.2.2 SNP association analysis ........................................................... 69 4.2.2.1 Effects of FSTL SNP5 ................................................... 72 4.2.2.2 Effects of FSTL SNP8 ................................................... 74 4.2.2.3 Effect of IGF1 SNP1 ..................................................... 76 iv 4.2.2.4 Effects of FST SNP7 ..................................................... 78 4.2.3 SNP interactions with the myostatin F94L variant .................... 83 4.2.3.1 Interactions between myostatin F94L and SNIP1 SNP3, TGFBR3 SNP6 and IGF1 SNP1 ............. 85 4.2.3.2 Interaction between myostatin F94L and IGF1 SNP2 and FST SNP7 ........................................... 88 4.2.4 Interaction between candidate gene SNP genotype ................... 92 4.2.4.1 ACVR1 haplotype effect on meat to bone ratio ............. 95 4.2.4.2 FSTL5 haplotype effect on hot standard carcass weight ............................................................... 96 4.2.5 QTL mapping ............................................................................ 97 4.3 Summary ............................................................................................ 99 Chapter 5: General Discussion ........................................................................... 101 5.1 Introduction ....................................................................................... 102 5.2 Interactions between SNIP1 and myostatin ..................................... 107 5.3 Interactions between TGFBR3 (betaglycan) and myostatin ........... 109 5.4 IGF1 role in muscularity and its interactions with myostatin ....... 110 5.5 Follistatin role in muscularity and its interaction with myostatin .................................................................................... 112 5.6 Future experiments ............................................................................ 114 5.7 Conclusions ......................................................................................... 116 References ............................................................................................................ 158 v INDEX OF FIGURES Figure 1 : Structure of myostatin protein .......................................................... 18 Figure 2.1 : JS Davies cattle mapping herd ......................................................... 27 Figure 2.2 : Stifle width and hip width measurements ........................................ 28 Figure 3.1 : QTL for meat weight (with HSCW as covariate) on BTA 2 ............ 52 Figure 3.2 : QTL for meat percentage on BTA 2................................................. 53 Figure 3.3 : QTL for muscularity on BTA 2 ........................................................ 53 Figure 3.4 : QTL for meat weight (with HSCW as covariate) on BTA 17 .......... 54 Figure 3.5 : QTL for meat percentage on BTA 17............................................... 54 Figure 3.6 : QTL for meat weight (with HSCW as covariate) on BTA 3 ............ 55 Figure 3.7 : QTL for meat percentage on BTA 3................................................. 55 Figure 4.1 : Effect of FSTL5 SNP5 genotype on meat weight (with bone weight as covariate) ..................................................... 73 Figure 4.2 : Effect of FSTL5 SNP5 genotype on meat-to-bone ratio .................. 74 Figure 4.3 : Effect of FSTL5 SNP8 genotype on meat percentage ...................... 75 Figure 4.4 : Effect of FSTL5 SNP8 genotype on eye muscle area....................... 76 Figure 4.5 : Effect of IGF1 SNP1 genotype on HSCW ....................................... 77 Figure 4.6 : Effect of FST SNP7 genotype on meat weight (with HSCW as covariate) ................................................................. 78 Figure 4.7 : Effect of FST SNP7 genotype on meat percentage .......................... 79 Figure 4.8 : Effect of FST SNP7 genotype
Load more

Recommended publications
  • Transforming Growth Factor-Beta Family Members Are Regulated During Induced Luteolysis in Cattle
    a https://doi.org/10.21451/1984-3143-AR2018-0146 Original Article Animal Reproduction Anim Reprod. 2019;16(4):829-837 Transforming growth factor-beta family members are regulated during induced luteolysis in cattle Cristina Sangoi Haas1, Monique Tomazele Rovani1 , Gustavo Freitas Ilha2 , Kalyne Bertolin2 , Juliana Germano Ferst2 , Alessandra Bridi2 , Vilceu Bordignon3 , Raj Duggavathi3, Alfredo Quites Antoniazzi2 , Paulo Bayard Dias Gonçalves2 , Bernardo Garziera Gasperin1* 1Universidade Federal de Pelotas, Departamento de Patologia Animal, Capão do Leão, RS, Brasil 2Universidade Federal de Santa Maria, Laboratório de Biotecnologia e Reprodução Animal, Santa Maria, RS, Brasil 3McGill University, Department of Animal Science, Sainte-Anne-de-Bellevue, QC, Canada Abstract cell death and tissue remodeling (Miyamoto et al., 2009; Skarzynski and Okuda, 2010; Shirasuna et al., 2012). The transforming growth factors beta (TGFβ) Despite its essential role in reproduction, the cellular and are local factors produced by ovarian cells which, after molecular mechanisms mediating CL regression are not binding to their receptors, regulate follicular deviation fully understood. It is well established that CLs are not fully and ovulation. However, their regulation and function responsive to PGF until day 5-6 after ovulation, whereas during corpus luteum (CL) regression has been poorly after days 15-17, in the absence of gestation, spontaneous investigated. The present study evaluated the mRNA luteolysis occurs. Thus, performing PGF treatment on day regulation of some TGFβ family ligands and their receptors 10 after ovulation represents an adequate model to study in the bovine CL during induced luteolysis in vivo. On day CL regression, because all the CLs are fully responsive to 10 of the estrous cycle, cows received an injection of PGF and still functional.
    [Show full text]
  • TET2 Binding to Enhancers Facilitates Transcription Factor Recruitment in Hematopoietic Cells
    Downloaded from genome.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press 1 2 TET2 binding to enhancers facilitates 3 transcription factor recruitment in hematopoietic cells 4 5 Kasper D. Rasmussen1,2,7,8*, Ivan Berest3,8, Sandra Keβler1,2,6, Koutarou Nishimura1,4, 6 Lucía Simón-Carrasco1,2, George S. Vassiliou5, Marianne T. Pedersen1,2, 7 Jesper Christensen1,2, Judith B. Zaugg3* and Kristian Helin1,2,4*. 8 9 1Biotech Research and Innovation Centre (BRIC), Faculty of Health and Medical Sciences, University of 10 Copenhagen, 2200 Copenhagen, Denmark. 2The Novo Nordisk Foundation Center for Stem Cell Biology 11 (Danstem), Faculty or Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, 12 Denmark. 3European Molecular Biology Institute, Structural and Computational Unit. 4Cell Biology Program, 13 Memorial Sloan Kettering Cancer Center, New York, NY, USA. 5Wellcome Trust Sanger Institute, Wellcome 14 Trust Genome Campus, Cambridge, United Kingdom and Department of Haematology, Cambridge 15 University Hospitals NHS Trust, Cambridge, United Kingdom. 6Present address: Friedrich Miescher Institute 16 for Biomedical Research (FMI), CH-4058 Basel, Switzerland. 7Present address: Centre for Gene Regulation 17 and Expression (GRE), School of Life Sciences, University of Dundee, Dundee, UK. 8These authors 18 contributed equally. 19 20 *Correspondence: [email protected], [email protected], [email protected] 21 22 Running title: TET2 and TF binding in enhancers 23 24 Keywords: Acute Myeloid Leukemia; Chromatin; DNA binding; DNA methylation; Epigenetics; 25 Hematopoiesis; TET2; Transcription Factor Downloaded from genome.cshlp.org on October 6, 2021 - Published by Cold Spring Harbor Laboratory Press Rasmussen et al.
    [Show full text]
  • Dissertation
    Regulation of gene silencing: From microRNA biogenesis to post-translational modifications of TNRC6 complexes DISSERTATION zur Erlangung des DOKTORGRADES DER NATURWISSENSCHAFTEN (Dr. rer. nat.) der Fakultät Biologie und Vorklinische Medizin der Universität Regensburg vorgelegt von Johannes Danner aus Eggenfelden im Jahr 2017 Das Promotionsgesuch wurde eingereicht am: 12.09.2017 Die Arbeit wurde angeleitet von: Prof. Dr. Gunter Meister Johannes Danner Summary ‘From microRNA biogenesis to post-translational modifications of TNRC6 complexes’ summarizes the two main projects, beginning with the influence of specific RNA binding proteins on miRNA biogenesis processes. The fate of the mature miRNA is determined by the incorporation into Argonaute proteins followed by a complex formation with TNRC6 proteins as core molecules of gene silencing complexes. miRNAs are transcribed as stem-loop structured primary transcripts (pri-miRNA) by Pol II. The further nuclear processing is carried out by the microprocessor complex containing the RNase III enzyme Drosha, which cleaves the pri-miRNA to precursor-miRNA (pre-miRNA). After Exportin-5 mediated transport of the pre-miRNA to the cytoplasm, the RNase III enzyme Dicer cleaves off the terminal loop resulting in a 21-24 nt long double-stranded RNA. One of the strands is incorporated in the RNA-induced silencing complex (RISC), where it directly interacts with a member of the Argonaute protein family. The miRNA guides the mature RISC complex to partially complementary target sites on mRNAs leading to gene silencing. During this process TNRC6 proteins interact with Argonaute and recruit additional factors to mediate translational repression and target mRNA destabilization through deadenylation and decapping leading to mRNA decay.
    [Show full text]
  • TGF Beta Signaling Pathway 1 TGF Beta Signaling Pathway
    TGF beta signaling pathway 1 TGF beta signaling pathway The Transforming growth factor beta (TGFβ) signaling pathway is involved in many cellular processes in both the adult organism and the developing embryo including cell growth, cell differentiation, apoptosis, cellular homeostasis and other cellular functions. In spite of the wide range of cellular processes that the TGFβ signaling pathway regulates, the process is relatively simple. TGFβ superfamily ligands bind to a type II receptor, which recruits and phosphorylates a type I receptor. The type I receptor then phosphorylates receptor-regulated SMADs (R-SMADs) which can now bind the coSMAD SMAD4. R-SMAD/coSMAD complexes accumulate in the nucleus where they act as transcription factors and participate in the regulation of target gene expression. Mechanism Ligand Binding The TGF Beta superfamily of ligands include: Bone morphogenetic proteins (BMPs), Growth and differentiation factors (GDFs), Anti-müllerian hormone (AMH), Activin, Nodal and TGFβ's[1] . Signalling begins with the binding of a TGF beta superfamily ligand to a TGF beta type II receptor. The type II receptor is a serine/threonine receptor kinase, which catalyses the phosphorylation of the Type I receptor. Each class of ligand binds to a specific type II receptor[2] .In mammals there are seven known type I receptors and five type II receptors[3] . There are three activins: Activin A, Activin B and Activin AB. Activins are involved in embryogenesis and osteogenesis. They also regulate many hormones including pituitary, gonadal and hypothalamic hormones as well as insulin. They are also nerve cell survival factors. The BMPs bind to the Bone morphogenetic protein receptor type-2 (BMPR2).
    [Show full text]
  • 6 Signaling and BMP Antagonist Noggin in Prostate Cancer
    [CANCER RESEARCH 64, 8276–8284, November 15, 2004] Bone Morphogenetic Protein (BMP)-6 Signaling and BMP Antagonist Noggin in Prostate Cancer Dominik R. Haudenschild, Sabrina M. Palmer, Timothy A. Moseley, Zongbing You, and A. Hari Reddi Center for Tissue Regeneration and Repair, Department of Orthopedic Surgery, School of Medicine, University of California, Davis, Sacramento, California ABSTRACT antagonists has recently been discovered. These are secreted proteins that bind to BMPs and reduce their bioavailability for interactions It has been proposed that the osteoblastic nature of prostate cancer with the BMP receptors. Extracellular BMP antagonists include nog- skeletal metastases is due in part to elevated activity of bone morphoge- gin, follistatin, sclerostatin, chordin, DCR, BMPMER, cerberus, netic proteins (BMPs). BMPs are osteoinductive morphogens, and ele- vated expression of BMP-6 correlates with skeletal metastases of prostate gremlin, DAN, and others (refs. 11–16; reviewed in ref. 17). There are cancer. In this study, we investigated the expression levels of BMPs and several type I and type II receptors that bind to BMPs with different their modulators in prostate, using microarray analysis of cell cultures affinities. BMP activity is also regulated at the cell membrane level by and gene expression. Addition of exogenous BMP-6 to DU-145 prostate receptor antagonists such as BAMBI (18), which acts as a kinase- cancer cell cultures inhibited their growth by up-regulation of several deficient receptor. Intracellularly, the regulation of BMP activity at cyclin-dependent kinase inhibitors such as p21/CIP, p18, and p19. Expres- the signal transduction level is even more complex. There are inhib- sion of noggin, a BMP antagonist, was significantly up-regulated by itory Smads (Smad-6 and Smad-7), as well as inhibitors of inhibitory BMP-6 by microarray analysis and was confirmed by quantitative reverse Smads (AMSH and Arkadia).
    [Show full text]
  • A Novel Smad Nuclear Interacting Protein, SNIP1, Suppresses P300-Dependent TGF-␤ Signal Transduction
    Downloaded from genesdev.cshlp.org on October 5, 2021 - Published by Cold Spring Harbor Laboratory Press A novel Smad nuclear interacting protein, SNIP1, suppresses p300-dependent TGF-␤ signal transduction Richard H. Kim,1 David Wang,1 Michael Tsang,2 Jennifer Martin,3,5 Carla Huff,1 Mark P. de Caestecker,1 W. Tony Parks,2 Xianwang Meng,3,5 Robert J. Lechleider,4 Tongwen Wang,3,5 and Anita B. Roberts2,6 1Laboratory of Cell Regulation and Carcinogenesis, National Cancer Institute, Bethesda, Maryland 20892 USA; 2Laboratory of Molecular Genetics, National Institute of Child Health and Human Development, Bethesda, Maryland 20892 USA; 3Department of Surgery, Massachusetts General Hospital, Department of Genetics, Harvard Medical School, Boston, Massachusetts 02114 USA Members of the transforming growth factor-␤ superfamily play critical roles in controlling cell growth and differentiation. Effects of TGF-␤ family ligands are mediated by Smad proteins. To understand the mechanism of Smad function, we sought to identify novel interactors of Smads by use of a yeast two-hybrid system. A 396-amino acid nuclear protein termed SNIP1 was cloned and shown to harbor a nuclear localization signal (NLS) and a Forkhead-associated (FHA) domain. The carboxyl terminus of SNIP1 interacts with Smad1 and Smad2 in yeast two-hybrid as well as in mammalian overexpression systems. However, the amino terminus of SNIP1 harbors binding sites for both Smad4 and the coactivator CBP/p300. Interaction between endogenous levels of SNIP1 and Smad4 or CBP/p300 is detected in NMuMg cells as well as in vitro. Overexpression of full-length SNIP1 or its amino terminus is sufficient to inhibit multiple gene responses to TGF-␤ and CBP/p300, as well as the formation of a Smad4/p300 complex.
    [Show full text]
  • Durbinharly.Pdf (9.770Mb)
    GENOMICS OF SEASONAL HAIR SHEDDING AND ECOREGION-SPECIFIC GROWTH TO IDENTIFY ENVIRONMENTALLY-ADAPTED BEEF CATTLE _______________________________________ A Dissertation presented to the Faculty of the Graduate School at the University of Missouri-Columbia _______________________________________________________ In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy _____________________________________________________ by HARLY JANE DURBIN Dr. Jared Decker, Dissertation Supervisor December 2020 APPROVAL PAGE The undersigned, appointed by the Dean of the Graduate School, have examined the dissertation entitled: GENOMICS OF SEASONAL HAIR SHEDDING AND ECO-REGION SPECIFIC GROWTH TO IDENTIFY ENVIRONMENTALLY-ADAPTED BEEF CATTLE Presented by Harly Jane Durbin, a candidate for the degree of Doctor of Philosophy, and hereby certify that in their opinion it is worthy of acceptance. _____________________________________ Dr. Jared E. Decker, Animal Sciences, UMC _____________________________________ Dr. Robert D. Schnabel, Animal Sciences, UMC _____________________________________ Dr. Jeremy F. Taylor, Animal Sciences, UMC _____________________________________ Dr. Elizabeth G. King, Biological Sciences, UMC _____________________________________ Dr. Stephen P. Miller, Angus Genetics, Inc. DEDICATION Momma – thank you for teaching me compassion and also how to approach life with a sense of humor. You do such an incredible amount for other people and I strive to be as selfless every day. Daddy – thank you for encouraging me to think independently and for teaching me how to stand up for myself. Thank you also for the years of FFA (also known sometimes as Father Feeds Animal) and getting up early to haul heifers to jackpot shows. Darby – thank you for holding me to a high standard. I often think there was some mix-up and that you were meant to be the older sister for how much you hold me up.
    [Show full text]
  • Smad Regulation in TGF-(Beta) Signal Transduction
    COMMENTARY 4359 Smad regulation in TGF-β signal transduction Aristidis Moustakas, Serhiy Souchelnytskyi and Carl-Henrik Heldin Ludwig Institute for Cancer Research, Box 595, SE-751 24 Uppsala, Sweden Corresponding author (e-mail: [email protected]) Journal of Cell Science 114, 4359-4369 (2001) © The Company of Biologists Ltd Summary Smad proteins transduce signals from transforming growth promote degradation of transcriptional repressors, thus factor-β (TGF-β) superfamily ligands that regulate cell facilitating target gene regulation by TGF-β. Smads proliferation, differentiation and death through activation themselves can also become ubiquitinated and are of receptor serine/threonine kinases. Phosphorylation of degraded by proteasomes. Finally, the inhibitory Smads (I- receptor-activated Smads (R-Smads) leads to formation of Smads) block phosphorylation of R-Smads by the receptors complexes with the common mediator Smad (Co-Smad), and promote ubiquitination and degradation of receptor which are imported to the nucleus. Nuclear Smad complexes, thus inhibiting signalling. oligomers bind to DNA and associate with transcription factors to regulate expression of target genes. Alternatively, Key words: Phosphorylation, Signal transduction, Smad, nuclear R-Smads associate with ubiquitin ligases and Transforming growth factor-β, Ubiquitination Introduction chromosome 15q21-22, and MADH5, MADH1 and MADH8 Members of the transforming growth factor-β (TGF-β) family to chromosomes 15q31, 4 and 13, respectively (Gene control growth, differentiation
    [Show full text]
  • Fibroblasts from the Human Skin Dermo-Hypodermal Junction Are
    cells Article Fibroblasts from the Human Skin Dermo-Hypodermal Junction are Distinct from Dermal Papillary and Reticular Fibroblasts and from Mesenchymal Stem Cells and Exhibit a Specific Molecular Profile Related to Extracellular Matrix Organization and Modeling Valérie Haydont 1,*, Véronique Neiveyans 1, Philippe Perez 1, Élodie Busson 2, 2 1, 3,4,5,6, , Jean-Jacques Lataillade , Daniel Asselineau y and Nicolas O. Fortunel y * 1 Advanced Research, L’Oréal Research and Innovation, 93600 Aulnay-sous-Bois, France; [email protected] (V.N.); [email protected] (P.P.); [email protected] (D.A.) 2 Department of Medical and Surgical Assistance to the Armed Forces, French Forces Biomedical Research Institute (IRBA), 91223 CEDEX Brétigny sur Orge, France; [email protected] (É.B.); [email protected] (J.-J.L.) 3 Laboratoire de Génomique et Radiobiologie de la Kératinopoïèse, Institut de Biologie François Jacob, CEA/DRF/IRCM, 91000 Evry, France 4 INSERM U967, 92260 Fontenay-aux-Roses, France 5 Université Paris-Diderot, 75013 Paris 7, France 6 Université Paris-Saclay, 78140 Paris 11, France * Correspondence: [email protected] (V.H.); [email protected] (N.O.F.); Tel.: +33-1-48-68-96-00 (V.H.); +33-1-60-87-34-92 or +33-1-60-87-34-98 (N.O.F.) These authors contributed equally to the work. y Received: 15 December 2019; Accepted: 24 January 2020; Published: 5 February 2020 Abstract: Human skin dermis contains fibroblast subpopulations in which characterization is crucial due to their roles in extracellular matrix (ECM) biology.
    [Show full text]
  • Canonical TGF Signaling and Its Contribution to Endometrial Cancer
    Journal of Clinical Medicine Review Canonical TGFβ Signaling and Its Contribution to Endometrial Cancer Development and Progression—Underestimated Target of Anticancer Strategies Piotr K. Zakrzewski Department of Cytobiochemistry, Faculty of Biology and Environmental Protection, University of Lodz, Pomorska 141/143, 90-236 Lodz, Poland; [email protected]; Tel.: +48-42-635-52-99 Abstract: Endometrial cancer is one of the leading gynecological cancers diagnosed among women in their menopausal and postmenopausal age. Despite the progress in molecular biology and medicine, no efficient and powerful diagnostic and prognostic marker is dedicated to endometrial carcinogenesis. The canonical TGFβ pathway is a pleiotropic signaling cascade orchestrating a variety of cellular and molecular processes, whose alterations are responsible for carcinogenesis that originates from different tissue types. This review covers the current knowledge concerning the canonical TGFβ pathway (Smad-dependent) induced by prototypical TGFβ isoforms and the involvement of pathway alterations in the development and progression of endometrial neoplastic lesions. Since Smad-dependent signalization governs opposed cellular processes, such as growth arrest, apoptosis, tumor cells growth and differentiation, as well as angiogenesis and metastasis, TGFβ cascade may act both as a tumor suppressor or tumor promoter. However, the final effect of TGFβ signaling on endometrial cancer cells depends on the cancer disease stage. The multifunctional Citation: Zakrzewski, P.K. Canonical role of the TGFβ pathway indicates the possible utilization of alterations in the TGFβ cascade as a TGFβ Signaling and Its Contribution potential target of novel anticancer strategies. to Endometrial Cancer Development and Progression—Underestimated Keywords: endometrial cancer; TGFβ isoforms; TGFβR1; TGFβR2; Smad proteins; TGFβ co-receptors; Target of Anticancer Strategies.
    [Show full text]
  • Supplementary Table 1 Double Treatment Vs Single Treatment
    Supplementary table 1 Double treatment vs single treatment Probe ID Symbol Gene name P value Fold change TC0500007292.hg.1 NIM1K NIM1 serine/threonine protein kinase 1.05E-04 5.02 HTA2-neg-47424007_st NA NA 3.44E-03 4.11 HTA2-pos-3475282_st NA NA 3.30E-03 3.24 TC0X00007013.hg.1 MPC1L mitochondrial pyruvate carrier 1-like 5.22E-03 3.21 TC0200010447.hg.1 CASP8 caspase 8, apoptosis-related cysteine peptidase 3.54E-03 2.46 TC0400008390.hg.1 LRIT3 leucine-rich repeat, immunoglobulin-like and transmembrane domains 3 1.86E-03 2.41 TC1700011905.hg.1 DNAH17 dynein, axonemal, heavy chain 17 1.81E-04 2.40 TC0600012064.hg.1 GCM1 glial cells missing homolog 1 (Drosophila) 2.81E-03 2.39 TC0100015789.hg.1 POGZ Transcript Identified by AceView, Entrez Gene ID(s) 23126 3.64E-04 2.38 TC1300010039.hg.1 NEK5 NIMA-related kinase 5 3.39E-03 2.36 TC0900008222.hg.1 STX17 syntaxin 17 1.08E-03 2.29 TC1700012355.hg.1 KRBA2 KRAB-A domain containing 2 5.98E-03 2.28 HTA2-neg-47424044_st NA NA 5.94E-03 2.24 HTA2-neg-47424360_st NA NA 2.12E-03 2.22 TC0800010802.hg.1 C8orf89 chromosome 8 open reading frame 89 6.51E-04 2.20 TC1500010745.hg.1 POLR2M polymerase (RNA) II (DNA directed) polypeptide M 5.19E-03 2.20 TC1500007409.hg.1 GCNT3 glucosaminyl (N-acetyl) transferase 3, mucin type 6.48E-03 2.17 TC2200007132.hg.1 RFPL3 ret finger protein-like 3 5.91E-05 2.17 HTA2-neg-47424024_st NA NA 2.45E-03 2.16 TC0200010474.hg.1 KIAA2012 KIAA2012 5.20E-03 2.16 TC1100007216.hg.1 PRRG4 proline rich Gla (G-carboxyglutamic acid) 4 (transmembrane) 7.43E-03 2.15 TC0400012977.hg.1 SH3D19
    [Show full text]
  • Decrypting Noncoding RNA Interactions, Structures, and Functional Networks
    Downloaded from genome.cshlp.org on October 7, 2021 - Published by Cold Spring Harbor Laboratory Press Perspective Decrypting noncoding RNA interactions, structures, and functional networks Muller Fabbri,1,6 Leonard Girnita,2,6 Gabriele Varani,3 and George A. Calin4,5 1University of Hawaii Cancer Center, Cancer Biology Program, Honolulu, Hawaii 96813, USA; 2Department of Oncology-Pathology, Cellular and Molecular Tumor Pathology, Karolinska Institute, and Karolinska University Hospital, Stockholm, 17164 Sweden; 3Department of Chemistry, University of Washington, Seattle, Washington 98195-1700, USA; 4Department of Experimental Therapeutics, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA; 5Center for RNA Interference and Non-Coding RNAs, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA The world of noncoding RNAs (ncRNAs) is composed of an enormous and growing number of transcripts, ranging in length from tens of bases to tens of kilobases, involved in all biological processes and altered in expression and/or function in many types of human disorders. The premise of this review is the concept that ncRNAs, like many large proteins, have a multidomain architecture that organizes them spatially and functionally. As ncRNAs are beginning to be imprecisely clas- sified into functional families, we review here how their structural properties might inform their functions with focus on structural architecture–function relationships. We will describe the properties of “interactor elements” (IEs) involved in di- rect physical interaction with nucleic acids, proteins, or lipids and of “structural elements” (SEs) directing their wiring within the “ncRNA interactor networks” through the emergence of secondary and/or tertiary structures.
    [Show full text]