The Transcriptome of Epithelial Transformation
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Supplemental Figure 1. Vimentin
Double mutant specific genes Transcript gene_assignment Gene Symbol RefSeq FDR Fold- FDR Fold- FDR Fold- ID (single vs. Change (double Change (double Change wt) (single vs. wt) (double vs. single) (double vs. wt) vs. wt) vs. single) 10485013 BC085239 // 1110051M20Rik // RIKEN cDNA 1110051M20 gene // 2 E1 // 228356 /// NM 1110051M20Ri BC085239 0.164013 -1.38517 0.0345128 -2.24228 0.154535 -1.61877 k 10358717 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 /// BC 1700025G04Rik NM_197990 0.142593 -1.37878 0.0212926 -3.13385 0.093068 -2.27291 10358713 NM_197990 // 1700025G04Rik // RIKEN cDNA 1700025G04 gene // 1 G2 // 69399 1700025G04Rik NM_197990 0.0655213 -1.71563 0.0222468 -2.32498 0.166843 -1.35517 10481312 NM_027283 // 1700026L06Rik // RIKEN cDNA 1700026L06 gene // 2 A3 // 69987 /// EN 1700026L06Rik NM_027283 0.0503754 -1.46385 0.0140999 -2.19537 0.0825609 -1.49972 10351465 BC150846 // 1700084C01Rik // RIKEN cDNA 1700084C01 gene // 1 H3 // 78465 /// NM_ 1700084C01Rik BC150846 0.107391 -1.5916 0.0385418 -2.05801 0.295457 -1.29305 10569654 AK007416 // 1810010D01Rik // RIKEN cDNA 1810010D01 gene // 7 F5 // 381935 /// XR 1810010D01Rik AK007416 0.145576 1.69432 0.0476957 2.51662 0.288571 1.48533 10508883 NM_001083916 // 1810019J16Rik // RIKEN cDNA 1810019J16 gene // 4 D2.3 // 69073 / 1810019J16Rik NM_001083916 0.0533206 1.57139 0.0145433 2.56417 0.0836674 1.63179 10585282 ENSMUST00000050829 // 2010007H06Rik // RIKEN cDNA 2010007H06 gene // --- // 6984 2010007H06Rik ENSMUST00000050829 0.129914 -1.71998 0.0434862 -2.51672 -
Structural Biology of the Dystrophin-Deficient Muscle Fiber
Dystrophin-deficient muscle fiber REVIEW ISSN- 0102-9010145 STRUCTURAL BIOLOGY OF THE DYSTROPHIN-DEFICIENT MUSCLE FIBER Maria Julia Marques Department of Anatomy, Institute of Biology, State University of Campinas (UNICAMP), Campinas, SP, Brazil. ABSTRACT The discovery of dystrophin and its gene has led to major advances in our understanding of the molecular basis of Duchenne, Becker and other muscular dystrophies related to the dystrophin-associated protein complex. The concept that dystrophin has a mechanical function in stabilizing the muscle fiber membrane has expanded in the last five years. The dystrophin-glycoprotein complex is now considered a multifunctional complex that contains molecules involved in signal transduction cascades important for cell survival. The roles of dystrophin and the dystrophin- glycoprotein complex in positioning and anchoring receptors and ion channels is also important, and much of what is known about these functions is based on studies of the neuromuscular synapse. In this review, we discuss the components and the cellular signaling molecules associated with the dystrophin-glycoprotein complex. We then focus on the molecular organization of the neuromuscular junction and its structural organization in the dystrophin-deficient muscle fibers of mdx mice, a well-established experimental model of Duchenne muscular dystrophy. Key words: Confocal microscopy, Duchenne muscular dystrophy, mdx, neuromuscular junction INTRODUCTION that can improve the quality of life of the patients, Duchenne muscular dystrophy (DMD) is an X- death usually occurs in the early twenties, as a result linked recessive, progressive muscle-wasting disease of cardiac and/or respiratory failures [24]. that affects primarily skeletal and cardiac muscle. Several other muscular dystrophies have been DMD was first reported in 1868 by Dr. -
` Probing the Epigenome Andrea Huston1, Cheryl H Arrowsmith1,2
` Probing the Epigenome Andrea Huston1, Cheryl H Arrowsmith1,2, Stefan Knapp3,4,*, Matthieu Schapira1,5,* 1. Structural Genomics Consortium, University of Toronto, Toronto, ON M5G 1L7, Canada 2. Princess Margaret Cancer Centre and Department of Medical Biophysics, University of Toronto , Toronto, ON M5G 1L7, Canada 3. Nuffield Department of Clinical Medicine, Target Discovery Institute, and Structural Genomic Consortium, University of Oxford, Headington, Oxford OX3 7DQ, United Kingdom 4. Institute for Pharmaceutical Chemistry, Johann Wolfgang Goethe University, D-60438 Frankfurt am Main, Germany 5. Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON M5S 1A8, Canada * Correspondence: [email protected], [email protected] Epigenetic chemical probes are having a strong impact on biological discovery and target validation. Systematic coverage of emerging epigenetic target classes with these potent, selective, cell-active chemical tools will profoundly influence our understanding of the human biology and pathology of chromatin-templated mechanisms. ` Chemical probes are research-enablers Advances in genomics and proteomics methodologies in recent years have made it possible to associate thousands of genes and proteins with specific diseases, biological processes, molecular networks and pathways. However, data from these large scale initiatives alone has not translated widely into new studies on these disease-associated proteins, and the biomedical research community still tends to focus on proteins that were already known before the sequencing of the human genome1. The human kinome for instance, a target class of direct relevance to cancer and other disease areas, is a telling example: based on the number of research articles indexed in pubmed in 2011, 75% of the research activity focused on only 10% of the 518 human kinases – largely the same kinases that were the focus of research before sequencing of the human genome - while 60% of the kinome, some 300 enzymes, was virtually ignored by the community2. -
A Genome-Wide Association Study of Body Mass Index
International Journal of Epidemiology, 2015, 700–712 doi: 10.1093/ije/dyv077 Advance Access Publication Date: 7 May 2015 Original article Genetic Epidemiology A genome-wide association study of body mass index across early life and childhood Nicole M Warrington,1,2* Laura D Howe,3,4* Lavinia Paternoster,3,4 Marika Kaakinen,5,6,7 Sauli Herrala,6 Ville Huikari,6 Yan Yan Wu,8 Downloaded from John P Kemp,2,3 Nicholas J Timpson,3,4 Beate St Pourcain,3,4 George Davey Smith,3,4 Kate Tilling,3,4 Marjo-Riitta Jarvelin,5,6,9,10,11 Craig E Pennell,1 David M Evans,2,3,4 Debbie A Lawlor,3,4 Laurent Briollais8,† and Lyle J Palmer12,† http://ije.oxfordjournals.org/ 1School of Women’s and Infants’ Health, University of Western Australia, Perth, WA, Australia, 2University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD, Australia, 3MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK, 4School of Social and Community Medicine, University of Bristol, Bristol, UK, 5Biocenter Oulu, and 6Institute of Health Sciences, University of Oulu, Oulu, Finland, 7Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, UK, 8Lunenfeld-Tanenbaum Research Institute, Mount 9 Sinai Hospital, Toronto, ON, Canada, Department of Children and Young People and Families, National at MPI Psycholinguistics on September 22, 2015 Institute for Health and Welfare, Oulu, Finland, 10Department of Epidemiology and Biostatistics, MRC- HPA Centre for Environment and Health, School of Public Health, Imperial College London, London, UK, 11Unit of Primary Care, Oulu University Hospital, Oulu, Finland and 12The Joanna Briggs Institute, The Robinson Research Institute, and School of Translational Health Science, University of Adelaide, Adelaide, SA, Australia *Corresponding authors. -
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. -
Tropomodulin Isoform-Specific Regulation of Dendrite Development and Synapse Formation
This Accepted Manuscript has not been copyedited and formatted. The final version may differ from this version. Research Articles: Cellular/Molecular Tropomodulin Isoform-Specific Regulation of Dendrite Development and Synapse Formation Omotola F. Omotade1,3, Yanfang Rui1,3, Wenliang Lei1,3, Kuai Yu1, H. Criss Hartzell1, Velia M. Fowler4 and James Q. Zheng1,2,3 1Department of Cell Biology, Emory University School of Medicine, Atlanta, GA 30322. 2Department of Neurology 3Center for Neurodegenerative Diseases, Emory University School of Medicine, Atlanta, GA 30322. 4Department of Molecular Medicine, Scripps Research Institute, La Jolla, CA 92037 DOI: 10.1523/JNEUROSCI.3325-17.2018 Received: 22 November 2017 Revised: 25 September 2018 Accepted: 2 October 2018 Published: 9 October 2018 Author contributions: O.F.O. and J.Q.Z. designed research; O.F.O., Y.R., W.L., and K.Y. performed research; O.F.O. and J.Q.Z. analyzed data; O.F.O. and J.Q.Z. wrote the paper; Y.R., H.C.H., V.M.F., and J.Q.Z. edited the paper; V.M.F. contributed unpublished reagents/analytic tools. Conflict of Interest: The authors declare no competing financial interests. This research project was supported in part by research grants from National Institutes of Health to JQZ (GM083889, MH104632, and MH108025), OFO (5F31NS092437-03), VMF (EY017724) and HCH (EY014852, AR067786), as well as by the Emory University Integrated Cellular Imaging Microscopy Core of the Emory Neuroscience NINDS Core Facilities grant (5P30NS055077). We would like to thank Dr. Kenneth Myers for his technical expertise and help throughout the project. We also thank Drs. -
ONLINE SUPPLEMENTARY TABLE Table 2. Differentially Expressed
ONLINE SUPPLEMENTARY TABLE Table 2. Differentially Expressed Probe Sets in Livers of GK Rats. A. Immune/Inflammatory (67 probe sets, 63 genes) Age Strain Probe ID Gene Name Symbol Accession Gene Function 5 WKY 1398390_at small inducible cytokine B13 precursor Cxcl13 AA892854 chemokine activity; lymph node development 5 WKY 1389581_at interleukin 33 Il33 BF390510 cytokine activity 5 WKY *1373970_at interleukin 33 Il33 AI716248 cytokine activity 5 WKY 1369171_at macrophage stimulating 1 (hepatocyte growth factor-like) Mst1; E2F2 NM_024352 serine-throenine kinase; tumor suppression 5 WKY 1388071_x_at major histocompatability antigen Mhc M24024 antigen processing and presentation 5 WKY 1385465_at sialic acid binding Ig-like lectin 5 Siglec5 BG379188 sialic acid-recognizing receptor 5 WKY 1393108_at major histocompatability antigen Mhc BM387813 antigen processing and presentation 5 WKY 1388202_at major histocompatability antigen Mhc BI395698 antigen processing and presentation 5 WKY 1371171_at major histocompatability antigen Mhc M10094 antigen processing and presentation 5 WKY 1370382_at major histocompatability antigen Mhc BI279526 antigen processing and presentation 5 WKY 1371033_at major histocompatability antigen Mhc AI715202 antigen processing and presentation 5 WKY 1383991_at leucine rich repeat containing 8 family, member E Lrrc8e BE096426 proliferation and activation of lymphocytes and monocytes. 5 WKY 1383046_at complement component factor H Cfh; Fh AA957258 regulation of complement cascade 4 WKY 1369522_a_at CD244 natural killer -
A Genome-Wide Association Study of Body Mass
International Journal of Epidemiology, 2015, 700–712 doi: 10.1093/ije/dyv077 Advance Access Publication Date: 7 May 2015 Original article Genetic Epidemiology A genome-wide association study of body mass index across early life and childhood Nicole M Warrington,1,2* Laura D Howe,3,4* Lavinia Paternoster,3,4 Marika Kaakinen,5,6,7 Sauli Herrala,6 Ville Huikari,6 Yan Yan Wu,8 John P Kemp,2,3 Nicholas J Timpson,3,4 Beate St Pourcain,3,4 George Davey Smith,3,4 Kate Tilling,3,4 Marjo-Riitta Jarvelin,5,6,9,10,11 Craig E Pennell,1 David M Evans,2,3,4 Debbie A Lawlor,3,4 Laurent Briollais8,† and Lyle J Palmer12,† 1School of Women’s and Infants’ Health, University of Western Australia, Perth, WA, Australia, 2University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD, Australia, 3MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK, 4School of Social and Community Medicine, University of Bristol, Bristol, UK, 5Biocenter Oulu, and 6Institute of Health Sciences, University of Oulu, Oulu, Finland, 7Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, UK, 8Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada, 9Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, 10Department of Epidemiology and Biostatistics, MRC- HPA Centre for Environment and Health, School of Public Health, Imperial College London, London, UK, 11Unit of Primary Care, Oulu University Hospital, Oulu, Finland and 12The Joanna Briggs Institute, The Robinson Research Institute, and School of Translational Health Science, University of Adelaide, Adelaide, SA, Australia *Corresponding authors. -
Table SI. Primer List of Genes Used for Reverse Transcription‑Quantitative PCR Validation
Table SI. Primer list of genes used for reverse transcription‑quantitative PCR validation. Genes Forward (5'‑3') Reverse (5'‑3') Length COL1A1 AGTGGTTTGGATGGTGCCAA GCACCATCATTTCCACGAGC 170 COL6A1 CCCCTCCCCACTCATCACTA CGAATCAGGTTGGTCGGGAA 65 COL2A1 GGTCCTGCAGGTGAACCC CTCTGTCTCCTTGCTTGCCA 181 DCT CTACGAAACCAGGATGACCGT ACCATCATTGGTTTGCCTTTCA 192 PDE4D ATTGCCCACGATAGCTGCTC GCAGATGTGCCATTGTCCAC 181 RP11‑428C19.4 ACGCTAGAAACAGTGGTGCG AATCCCCGGAAAGATCCAGC 179 GPC‑AS2 TCTCAACTCCCCTCCTTCGAG TTACATTTCCCGGCCCATCTC 151 XLOC_110310 AGTGGTAGGGCAAGTCCTCT CGTGGTGGGATTCAAAGGGA 187 COL1A1, collagen type I alpha 1; COL6A1, collagen type VI, alpha 1; COL2A1, collagen type II alpha 1; DCT, dopachrome tautomerase; PDE4D, phosphodiesterase 4D cAMP‑specific. Table SII. The differentially expressed mRNAs in the ParoAF_Control group. Gene ID logFC P‑Value Symbol Description ENSG00000165480 ‑6.4838 8.32E‑12 SKA3 Spindle and kinetochore associated complex subunit 3 ENSG00000165424 ‑6.43924 0.002056 ZCCHC24 Zinc finger, CCHC domain containing 24 ENSG00000182836 ‑6.20215 0.000817 PLCXD3 Phosphatidylinositol‑specific phospholipase C, X domain containing 3 ENSG00000174358 ‑5.79775 0.029093 SLC6A19 Solute carrier family 6 (neutral amino acid transporter), member 19 ENSG00000168916 ‑5.761 0.004046 ZNF608 Zinc finger protein 608 ENSG00000134343 ‑5.56371 0.01356 ANO3 Anoctamin 3 ENSG00000110400 ‑5.48194 0.004123 PVRL1 Poliovirus receptor‑related 1 (herpesvirus entry mediator C) ENSG00000124882 ‑5.45849 0.022164 EREG Epiregulin ENSG00000113448 ‑5.41752 0.000577 PDE4D Phosphodiesterase -
Profiling of the Muscle-Specific Dystroglycan Interactome Reveals the Role of Hippo Signaling in Muscular Dystrophy and Age-Dependent Muscle Atrophy Andriy S
Yatsenko et al. BMC Medicine (2020) 18:8 https://doi.org/10.1186/s12916-019-1478-3 RESEARCH ARTICLE Open Access Profiling of the muscle-specific dystroglycan interactome reveals the role of Hippo signaling in muscular dystrophy and age-dependent muscle atrophy Andriy S. Yatsenko1†, Mariya M. Kucherenko2,3,4†, Yuanbin Xie2,5†, Dina Aweida6, Henning Urlaub7,8, Renate J. Scheibe1, Shenhav Cohen6 and Halyna R. Shcherbata1,2* Abstract Background: Dystroglycanopathies are a group of inherited disorders characterized by vast clinical and genetic heterogeneity and caused by abnormal functioning of the ECM receptor dystroglycan (Dg). Remarkably, among many cases of diagnosed dystroglycanopathies, only a small fraction can be linked directly to mutations in Dg or its regulatory enzymes, implying the involvement of other, not-yet-characterized, Dg-regulating factors. To advance disease diagnostics and develop new treatment strategies, new approaches to find dystroglycanopathy-related factors should be considered. The Dg complex is highly evolutionarily conserved; therefore, model genetic organisms provide excellent systems to address this challenge. In particular, Drosophila is amenable to experiments not feasible in any other system, allowing original insights about the functional interactors of the Dg complex. Methods: To identify new players contributing to dystroglycanopathies, we used Drosophila as a genetic muscular dystrophy model. Using mass spectrometry, we searched for muscle-specific Dg interactors. Next, in silico analyses allowed us to determine their association with diseases and pathological conditions in humans. Using immunohistochemical, biochemical, and genetic interaction approaches followed by the detailed analysis of the muscle tissue architecture, we verified Dg interaction with some of the discovered factors. -
Microrna Regulatory Pathways in the Control of the Actin–Myosin Cytoskeleton
cells Review MicroRNA Regulatory Pathways in the Control of the Actin–Myosin Cytoskeleton , , Karen Uray * y , Evelin Major and Beata Lontay * y Department of Medical Chemistry, Faculty of Medicine, University of Debrecen, 4032 Debrecen, Hungary; [email protected] * Correspondence: [email protected] (K.U.); [email protected] (B.L.); Tel.: +36-52-412345 (K.U. & B.L.) The authors contributed equally to the manuscript. y Received: 11 June 2020; Accepted: 7 July 2020; Published: 9 July 2020 Abstract: MicroRNAs (miRNAs) are key modulators of post-transcriptional gene regulation in a plethora of processes, including actin–myosin cytoskeleton dynamics. Recent evidence points to the widespread effects of miRNAs on actin–myosin cytoskeleton dynamics, either directly on the expression of actin and myosin genes or indirectly on the diverse signaling cascades modulating cytoskeletal arrangement. Furthermore, studies from various human models indicate that miRNAs contribute to the development of various human disorders. The potentially huge impact of miRNA-based mechanisms on cytoskeletal elements is just starting to be recognized. In this review, we summarize recent knowledge about the importance of microRNA modulation of the actin–myosin cytoskeleton affecting physiological processes, including cardiovascular function, hematopoiesis, podocyte physiology, and osteogenesis. Keywords: miRNA; actin; myosin; actin–myosin complex; Rho kinase; cancer; smooth muscle; hematopoiesis; stress fiber; gene expression; cardiovascular system; striated muscle; muscle cell differentiation; therapy 1. Introduction Actin–myosin interactions are the primary source of force generation in mammalian cells. Actin forms a cytoskeletal network and the myosin motor proteins pull actin filaments to produce contractile force. All eukaryotic cells contain an actin–myosin network inferring contractile properties to these cells. -
PHF16 Antibody (C-Term) Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # Ap17166b
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 PHF16 Antibody (C-term) Affinity Purified Rabbit Polyclonal Antibody (Pab) Catalog # AP17166b Specification PHF16 Antibody (C-term) - Product Information Application WB, IHC-P,E Primary Accession Q92613 Other Accession NP_001070913.1, NP_055550.1 Reactivity Human Host Rabbit Clonality Polyclonal Isotype Rabbit Ig Calculated MW 93808 Antigen Region 779-806 PHF16 Antibody (C-term) - Additional Information PHF16 Antibody (C-term) (Cat. #AP17166b) Gene ID 9767 western blot analysis in 293 cell line lysates (35ug/lane).This demonstrates the PHF16 Other Names antibody detected the PHF16 protein (arrow). Protein Jade-3, Jade family PHD finger protein 3, PHD finger protein 16, JADE3, KIAA0215, PHF16 Target/Specificity This PHF16 antibody is generated from rabbits immunized with a KLH conjugated synthetic peptide between 779-806 amino acids from the C-terminal region of human PHF16. Dilution WB~~1:1000 IHC-P~~1:10~50 Format Purified polyclonal antibody supplied in PBS with 0.09% (W/V) sodium azide. This antibody is purified through a protein A column, followed by peptide affinity PHF16 Antibody (C-term) purification. (AP17166b)immunohistochemistry analysis in formalin fixed and paraffin embedded human Storage uterus tissue followed by peroxidase Maintain refrigerated at 2-8°C for up to 2 conjugation of the secondary antibody and weeks. For long term storage store at -20°C DAB staining.This data demonstrates the use in small aliquots to prevent freeze-thaw of PHF16 Antibody (C-term) for cycles. immunohistochemistry. Clinical relevance has not been evaluated. Precautions Page 1/2 10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 PHF16 Antibody (C-term) is for research use PHF16 Antibody (C-term) - Background only and not for use in diagnostic or therapeutic procedures.