DOCSLIB.ORG

Gene Expression in Broiler Myoblasts (RNA-Seq)

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Tones (Million) meat production Chicken 0 1 2 3 4 5 6 7 8 1950 1952 1954 tones) (Million production Chicken (Billion) Populatin 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 Earth Policy Institute Earth Policy 2008 2010 0 10 20 30 40 50 60 70 80 90 100 Populatin (Billion) Chicken breedings in Japan 名古屋コーチン 比内地鶏 Broiler Import 100%! 長州黒かしわ 天草大王 御殿地鶏 http://www.j-chicken.jp/anshin/guide.html#place6 Layer and broiler chickens Layer (e.g., White Leghorn) Broiler (e.g., UK Chunky) • For egg production • For meat production • Laying 280 eggs/year • Rapid growth • Weight: 2.8~3.4 kg • Weight: 4~5 kg Skeletal muscle tissue A myofiber Skeletal muscle tissue Actomyosin filaments Skeletal muscle development & growth Myoblast Myocyte Myotube Differentiation Cell fusion Muscle formation Muscle Activation Proliferation Stem cell Myofiber Myogenic differentiation of chick myoblasts Day 0 Day 2 Day 4 Phase DAPI / MHC Takaya, Anim Sci J, 2017 Comparison between layer and broiler myoblasts WL (layer) UKC (broiler) Myoblast Myoblast Compare growth, differentiation, and gene expression Growth of layer and broiler myoblasts UKC WL 50 ** cells) 40 4 10 × ( 30 ** 20 * 10 No. of myoblasts No. 0 0 24 48 72 96 Culture (h) 2.5×104 cells/well, GM, n = 3, *p < 0.05, **p < 0.01 Cell proliferation of layer and broiler myoblasts EdU / DAPI 60 * 50 WL 40 (%) 30 cells + 20 EdU 10 UKC 0 WL UKC 1×105 cells/dish, GM, n = 4, *p < 0.05 Differentiation of layer and broiler myoblasts MHC / DAPI (day 2) WL UKC 50 ** WL 40 (%) 30 cells + 20 ** MHC 10 UKC 0 Day 0 Day 1 Day 2 1×105 cells/dish, DM, n = 4, **p < 0.01 Cell characteristics of broiler myoblasts Myoblast Myocyte Myotube Differentiation Cell fusion Proliferation Gene expression patterns in chick myoblasts Myoblast Myocyte Myotube Day 0 Day 1 Day 2 VS Gene expression RNA sequencing RNA sequencing of chicken myoblasts WL (layer) UKC (broiler) Genome 1.2 billion bp 20 K genes DNA Transcription RNA Translation Protein RNA sequencing Day 0 Day 1 Day 2 WL ×3 ×3 ×3 UKC ×3 ×3 ×3 Total RNA isolataion ↓ RNA library preparation ↓ RNA-sequence 23.3 M reads/sample obtained 22.6 M reads/sample mapped to genome (97.2%) 46,389 transcripts identified 26,640 genes quantified RNA-seq by NODAI Genome Research Center Differentially expressed genes (DEGs); UKC vs WL 1,032/26,640 (3.9%) Day 1 genes were differentially expressed between UKC and WL. 80 80 112 336 195 200 29 Day 0 Day 2 RPKM, |fold-change| ≥ 2, FDR p < 0.05 Ontologies of 336 DEGs (81 genes) Gene ontology p Genes Proteinaceous NOV, HAPLN1, COL9A2, COL14A1, CRISPLD2, SMOC1, LUM, 7.1E-6 extracellular matrix ELN, COL6A3, FBN3, ECM2, COL16A1, SLIT3 COL14A1, COL21A1, COMP, F3, MMP27, MMP17, FBN3, TGM4, Extracellular matrix 3.4E-5 AGRN, FBN2 FGF19, BGLAP, CCK, ENPP2, C1R, ESM1, PTGFR, ADCYAP1, Extracellular region 7.7E-5 NOV, PGR, DNASE1, DKK3, BMPER, CXCL14, AGRN, NRG1, CD200R1 ENPP2, PDGFA, LUM, FAM132A, LRRC4C, NRN1, GREM2, ABI3BP, C1QTNF5, COMP, COL6A3, SERPINB10, PTN, NRG1, Extracellular space 3.6E-4 LOC422654, ECM2, SLIT3, PTHLH, GKN2, BMPER, COL14A1, F3, SEMA4D, IL12B, LIPC Axon 0.003 ALCAM, PTPRK, CCK, PVALB, STMN2, CHRNA7, AGRN, GAP43 Neuron projection 0.003 STMN2, TENM2, MAP2, AGRN, GHSR, GAP43, TPH2, ADCYAP1 SLC8A3, LPPR1, FLT4, TRPV3, PTGFR, APCDD1, KDR, ALCAM, Integral component 0.010 SEMA6A, THBD, SLC24A4, SLC6A7, SLC24A2, TENM2, of plasma membrane ADRA1B, CLDN1, TBXA2R, SEMA4D, NRG1, FAM26F Collagen trimer 0.027 COL9A2, C1QTNF5, COL14A1, COL6A3 PTPRK, THBD, CAPN5, CLSTN2, PDGFA, F3, BF2, ITGB5, GHSR, Cell surface 0.039 MDK GOTERM_CC_DIRECT, p < 0.05 The 336 DEGs as surface markers of myoblasts Major members of the 336 DEGs differentially expressed expressed between layer WL and broiler UKC myoblasts were membrane or extracellular proteins. WL UKC These genes may be useful as the markers for selective breeding of the chickens for meat production. Nihashi, Sci Rep, 2019 Further journey for gene exploration Cell characteristics of broiler myoblasts Myoblast Myocyte Myotube Differentiation Cell fusion ↑??? Proliferation ↑??? Gene expression shift during differentiation Day 0→1 Day 1→2 Day 0→2 value) p WL ( 10 log - log2(fold-change) UKC Volcano plot by Dr Koji UMEZAWA 840 DEGs during myogenic differentiation 2 1 0 A1 -1 -2 A2 B1 B2 d0 d1 d2 d0 d1 d2 WL UKC WL UKC Generated by Heatmapper, RPKM, |fold-change| ≥ 4, FDR p < 0.05 Gene ontologies of 840 DEGs A1 A2 B1 B2 Others A2 18 16 A2: Muscle-related B1 B1: Cell cycle 14 WL UKC 12 10 8 6 No. of No. genes 4 2 0 GOTERM_BP_DIRECT, p < 0.05 Protein-protein interaction (A1, 270 genes) A1 WL UKC ・ Collagen triple helix repeat Generated by STRING Protein-protein interaction (A2, 393 genes) A2 WL UKC ・ Muscle contraction ・ Regulation of muscle contraction ・ Regulation of system process ・ Striated muscle contraction ・ Regulation of multicellular organismal process Generated by STRING Protein-protein interaction (B1, 117 genes) B1 WL UKC ・ Cell cycle process ・ Cell cycle ・ Chromosome organization ・ Mitotic nuclear division ・ Organelle organization ・ Mitotic cell cycle ・ Cell division ・ Single-organism organelle organization ・ DNA conformation change ・ DNA integrity checkpoint ・ Cellular response to DNA damage stimulus Generated by STRING Protein-protein interaction (B2, 45 genes) B2 WL UKC No functional cluster Generated by STRING PCA: Principal component analysis (主成分分析) Primary PC Secondary PC Expression in WL Expression level Expression level in UKC PCA: Principal component analysis (主成分分析) 2000 WL day 0 WL day 1 0 PC2 WL day 2 UKC day 0 UKC day 1 UKC day 2 -2000 -5000 0 5000 PC1 Calculated by Dr Koji UMEZAWA PCA: Principal component analysis (主成分分析) PC1 (Differentiation) PC2 (Breed) Calculated by Dr Koji UMEZAWA PENK: pro-enkephalin Tyr-Gly-Gly-Phe-Met: Met-enkephalin (MENK) Tyr-Gly-Gly-Phe-Leu: Leu-enkephalin (LENK) What’s enkephalin Enkephalin is one of opioid peptides. Enkephalin Emotion Endorphin Analgesia Dynorphin Appetite Brain Muscle narcotic narcotic? Enkephalins suppress myoblast proliferation Control MENK LENK 30 25 cells) ** 4 ** 20 10 × ( 15 10 5 No. of myoblasts No. of myoblasts 0 0 24 48 72 Enkephalin treatment (h) 2.5×104 cells/well, GM, n = 4, **p < 0.01 Enkephalin suppresses myoblast proliferation Enkephalin Myoblasts Myocytes Differentiation Proliferation Why does enkephalin suppress myoblast growth? I (anybody) don’t know! It’s science. Nihashi, Sci Rep, 2019 Opioid peptides in foods Milk Spinach Rice Albumin, casein, gluten, lactoferrin, etc. Opioid peptides National Institute of Infectious Diseases, Japan Evolution of Chicken Breeds Gallus gallus Layer Broiler Gene expression in broiler myoblasts (RNA-seq) Myoblast Myocyte Myotube Differentiation Cell fusion ↑Muscle genes Proliferation ↑Cell cycle genes ? 43 ERVKs are detected in chicken myoblasts Gene Product Gene Product Gene Product LOC107052718 ERVK-11 Pol protein LOC107053122 ERVK-18 Pol protein-like LOC107049272 ERVK-8 Gag polyprotein-like LOC107054241 ERVK-25 Pol protein-like LOC107053216 ERVK-113 Pol protein-like LOC107049274 ERVK-18 Pol protein-like LOC107054837 ERVK-18 Pol protein-like LOC107056268 ERVK-18 Pol protein-like LOC107049277 ERVK-9 Pol protein-like LOC107050425 ERVK-25 Pol protein-like LOC107053591 ERVK-18 Pol protein-like LOC107049276 ERVK-18 Pol protein-like LOC107050867 ERVK-18 Pol protein-like LOC107056419 ERVK-18 Pol protein-like LOC107051888 ERVK-25 Pol protein-like LOC107051645 ERVK-18 Pol protein-like LOC107054036 ERVK-9 Pol protein-like LOC107051891 ERVK-8 Pol protein-like LOC107051640 ERVK-113 Pol protein-like LOC107057172 ERVK-18 Pol protein-like LOC107052380 ERVK-25 Pol protein-like LOC107055731 ERVK-25 Pol protein-like LOC107057173 ERVK-8 Gag polyprotein-like LOC107049326 ERVK-18 Pol protein-like LOC770574 ERVK-25 Pol protein LOC107055329 ERVK-18 Pol protein-like LOC107049332 ERVK-113 Pol protein-like LOC107052504 ERVK-18 Pol protein-like LOC107049264 ERVK-8 Gag polyprotein-like LOC107049350 ERVK-25 Pol protein-like LOC107052568 ERVK-113 Gag polyprotein-like LOC107055436 ERVK-8 Pol protein-like LOC107049474 ERVK-9 Pol protein-like LOC107051673 ERVK-18 Pol protein-like LOC107055437 ERVK-18 Pol protein-like LOC107052661 ERVL-18 Pol protein-like LOC107055442 ERVK-18 Pol protein-like LOC107052685 ERVK-11 Pol protein-like LOC107055443 ERVK-25 Pol protein-like LOC107052830 ERVK-113 Pol protein-like LOC107055445 ERVK-25 Pol protein-like LOC107052829 ERVK-113 Pol protein-like LOC107049273 ERVK-9 Pol protein-like ERVK: Endogenous retrovirus K member RNA retrovirus ERV Denner, Clin Microbiol Rev, 2012 ERVs in chicken genome ERVL ERVK ERVs occupy > 21 Mb (~2%) of chicken genome! Barr, J Virol, 2005 ERVKs and their neighboring genes 40 30 20 10 No. of genes 0 90 10 20 30 40 50 60 70 80 -30 -90 -80 -70 -60 -50 -40 -20 -10 100 -100 Overlap Distance from ERVK (kb) ERVK should be randomly inserted into the genome. However, there is a lot of genes existing near the transcribed ERVKs. The ERVKs having neighboring genes are transcribed. ERVK regulates its neighboring gene expression ? ERVK Do ERVK transcriptions affect the expression of neighboring genes in myoblasts? Highly-transcribed ERVKs in broiler myoblasts Myoblast Myocyte Myotube BrK1 BrK2 ▭ Layer ▬ Broiler BrK1 and its neighboring genes BrK1 FAM19A2 LOC107052719 Chr 1 10 kb ▭ Layer ▬ Broiler 60 120 0.12 * * * * 50 * 100 0.10 40 (RPKM) 80 * 0.08 (RPKM) 30 60 0.06 (RPKM) ** 20 40 0.04 BrK1 10 20 FAM19A2 0.02 LOC107052719 0 0 0.00 Day 0 Day 1 Day 2 Day 0 Day 1 Day 2 Day 0 Day 1 Day 2 BrK2 and its neighboring genes SLC1A7 SCP2 BrK2 FAM159A ORC1 PODN LOC772243 ZCCHC11 ECHDC2 ZYG11B GPX7 PRPF38A LOC107054037 COA7 MIR6549 Chr 8 10 kb ▭ Layer ▬ Broiler 8 1.2 7 * * * 1.0 6 0.8 5 (RPKM) 4 0.6 (RPKM) 3 * 0.4 ** BrK2 ** 2 LOC772243 0.2 1 0 0.0 Day 0 Day 1 Day 2 Day 0 Day 1 Day 2 ERVK may affect neighboring gene expression The 43 ERVK transcriptions were identified in chicken myoblasts.
Recommended publications
  • Systems Analysis Implicates WAVE2&Nbsp

    Systems Analysis Implicates WAVE2&Nbsp

    JACC: BASIC TO TRANSLATIONAL SCIENCE VOL.5,NO.4,2020 ª 2020 THE AUTHORS. PUBLISHED BY ELSEVIER ON BEHALF OF THE AMERICAN COLLEGE OF CARDIOLOGY FOUNDATION. THIS IS AN OPEN ACCESS ARTICLE UNDER THE CC BY-NC-ND LICENSE (http://creativecommons.org/licenses/by-nc-nd/4.0/). PRECLINICAL RESEARCH Systems Analysis Implicates WAVE2 Complex in the Pathogenesis of Developmental Left-Sided Obstructive Heart Defects a b b b Jonathan J. Edwards, MD, Andrew D. Rouillard, PHD, Nicolas F. Fernandez, PHD, Zichen Wang, PHD, b c d d Alexander Lachmann, PHD, Sunita S. Shankaran, PHD, Brent W. Bisgrove, PHD, Bradley Demarest, MS, e f g h Nahid Turan, PHD, Deepak Srivastava, MD, Daniel Bernstein, MD, John Deanfield, MD, h i j k Alessandro Giardini, MD, PHD, George Porter, MD, PHD, Richard Kim, MD, Amy E. Roberts, MD, k l m m,n Jane W. Newburger, MD, MPH, Elizabeth Goldmuntz, MD, Martina Brueckner, MD, Richard P. Lifton, MD, PHD, o,p,q r,s t d Christine E. Seidman, MD, Wendy K. Chung, MD, PHD, Martin Tristani-Firouzi, MD, H. Joseph Yost, PHD, b u,v Avi Ma’ayan, PHD, Bruce D. Gelb, MD VISUAL ABSTRACT Edwards, J.J. et al. J Am Coll Cardiol Basic Trans Science. 2020;5(4):376–86. ISSN 2452-302X https://doi.org/10.1016/j.jacbts.2020.01.012 JACC: BASIC TO TRANSLATIONALSCIENCEVOL.5,NO.4,2020 Edwards et al. 377 APRIL 2020:376– 86 WAVE2 Complex in LVOTO HIGHLIGHTS ABBREVIATIONS AND ACRONYMS Combining CHD phenotype–driven gene set enrichment and CRISPR knockdown screening in zebrafish is an effective approach to identifying novel CHD genes.
  • In This Table Protein Name, Uniprot Code, Gene Name P-Value

    In This Table Protein Name, Uniprot Code, Gene Name P-Value

    Supplementary Table S1: In this table protein name, uniprot code, gene name p-value and Fold change (FC) for each comparison are shown, for 299 of the 301 significantly regulated proteins found in both comparisons (p-value<0.01, fold change (FC) >+/-0.37) ALS versus control and FTLD-U versus control. Two uncharacterized proteins have been excluded from this list Protein name Uniprot Gene name p value FC FTLD-U p value FC ALS FTLD-U ALS Cytochrome b-c1 complex P14927 UQCRB 1.534E-03 -1.591E+00 6.005E-04 -1.639E+00 subunit 7 NADH dehydrogenase O95182 NDUFA7 4.127E-04 -9.471E-01 3.467E-05 -1.643E+00 [ubiquinone] 1 alpha subcomplex subunit 7 NADH dehydrogenase O43678 NDUFA2 3.230E-04 -9.145E-01 2.113E-04 -1.450E+00 [ubiquinone] 1 alpha subcomplex subunit 2 NADH dehydrogenase O43920 NDUFS5 1.769E-04 -8.829E-01 3.235E-05 -1.007E+00 [ubiquinone] iron-sulfur protein 5 ARF GTPase-activating A0A0C4DGN6 GIT1 1.306E-03 -8.810E-01 1.115E-03 -7.228E-01 protein GIT1 Methylglutaconyl-CoA Q13825 AUH 6.097E-04 -7.666E-01 5.619E-06 -1.178E+00 hydratase, mitochondrial ADP/ATP translocase 1 P12235 SLC25A4 6.068E-03 -6.095E-01 3.595E-04 -1.011E+00 MIC J3QTA6 CHCHD6 1.090E-04 -5.913E-01 2.124E-03 -5.948E-01 MIC J3QTA6 CHCHD6 1.090E-04 -5.913E-01 2.124E-03 -5.948E-01 Protein kinase C and casein Q9BY11 PACSIN1 3.837E-03 -5.863E-01 3.680E-06 -1.824E+00 kinase substrate in neurons protein 1 Tubulin polymerization- O94811 TPPP 6.466E-03 -5.755E-01 6.943E-06 -1.169E+00 promoting protein MIC C9JRZ6 CHCHD3 2.912E-02 -6.187E-01 2.195E-03 -9.781E-01 Mitochondrial 2-
  • Novel Targets of Apparently Idiopathic Male Infertility

    Novel Targets of Apparently Idiopathic Male Infertility

    International Journal of Molecular Sciences Review Molecular Biology of Spermatogenesis: Novel Targets of Apparently Idiopathic Male Infertility Rossella Cannarella * , Rosita A. Condorelli , Laura M. Mongioì, Sandro La Vignera * and Aldo E. Calogero Department of Clinical and Experimental Medicine, University of Catania, 95123 Catania, Italy; [email protected] (R.A.C.); [email protected] (L.M.M.); [email protected] (A.E.C.) * Correspondence: [email protected] (R.C.); [email protected] (S.L.V.) Received: 8 February 2020; Accepted: 2 March 2020; Published: 3 March 2020 Abstract: Male infertility affects half of infertile couples and, currently, a relevant percentage of cases of male infertility is considered as idiopathic. Although the male contribution to human fertilization has traditionally been restricted to sperm DNA, current evidence suggest that a relevant number of sperm transcripts and proteins are involved in acrosome reactions, sperm-oocyte fusion and, once released into the oocyte, embryo growth and development. The aim of this review is to provide updated and comprehensive insight into the molecular biology of spermatogenesis, including evidence on spermatogenetic failure and underlining the role of the sperm-carried molecular factors involved in oocyte fertilization and embryo growth. This represents the first step in the identification of new possible diagnostic and, possibly, therapeutic markers in the field of apparently idiopathic male infertility. Keywords: spermatogenetic failure; embryo growth; male infertility; spermatogenesis; recurrent pregnancy loss; sperm proteome; DNA fragmentation; sperm transcriptome 1. Introduction Infertility is a widespread condition in industrialized countries, affecting up to 15% of couples of childbearing age [1]. It is defined as the inability to achieve conception after 1–2 years of unprotected sexual intercourse [2].
  • Three Brick Genes Have Distinct Functions in a Common Pathway Promoting Polarized Cell Division and Cell Morphogenesis in the Maize Leaf Epidermis

    Three Brick Genes Have Distinct Functions in a Common Pathway Promoting Polarized Cell Division and Cell Morphogenesis in the Maize Leaf Epidermis

    Development 130, 753-762 753 © 2003 The Company of Biologists Ltd doi:10.1242/dev.00290 Three Brick genes have distinct functions in a common pathway promoting polarized cell division and cell morphogenesis in the maize leaf epidermis Mary J. Frank, Heather N. Cartwright and Laurie G. Smith Section of Cell and Developmental Biology, U.C. San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0116, USA *Author for correspondence (e-mail: [email protected]) Accepted 29 October 2002 SUMMARY We have taken a genetic approach to investigating Brk1 acts non cell-autonomously over a short distance. By cytoskeleton-dependent mechanisms governing cell contrast, Brk2 and Brk3 act cell-autonomously to promote morphogenesis in the maize leaf epidermis. Previously, we pavement cell lobe formation, but Brk3 acts non cell- showed that the Brick1 (Brk1) gene is required for the autonomously, and Brk2 partially non cell-autonomously, formation of epidermal cell lobes as well as for properly to promote polarized subsidiary mother cell divisions. polarized divisions of stomatal subsidiary mother cells, and Together, these observations indicate that all three Brk encodes an 8 kDa protein highly conserved in plants and genes act in a common pathway in which each Brk gene has animals. Here, we show that two additional Brick genes, a distinct function. Recent work demonstrating a function Brk2 and Brk3, are involved in the same aspects of for the mammalian homolog of BRK1 (HSPC300) in epidermal cell morphogenesis and division. As shown activation of Arp2/3-dependent actin polymerization previously for Brk1, analysis of the cytoskeleton shows that implicates the Brk pathway in local regulation of actin Brk2 and Brk3 are required for the formation of local F- polymerization in plant cells.
  • Project Report 7Th

    Project Report 7Th

    IDENTIFICATION OF POTENT BIOMARKERS FOR PROSTATE CANCER THROUGH AR, MAPK AND m-TOR SIGNALING PATHWAYS MINING Enrolment No. - 131503, 131511 Name of Student(s) - Abhinav Mishra, Nimisha Asati Name of Supervisor - Dr. Tiratha Raj Singh May – 2017 Submitted in partial fulfillment of the Degree of Bachelor of Technology DEPARTMENT OF BIOTECHNOLOGY AND BIOINFORMATICS JAYPEE UNIVERSITY OF INFORMATION AND TECHNOLOGY, WAKNAGHAT Certificate This is to certify that the project report entitled “IDENTIFICATION OF POTENT BIOMARKERS FOR PROSTATE CANCER THROUGH AR, MAPK AND m-TOR SIGNALING PATHWAYS MINING”, submitted by Abhinav Mishra and Nimisha Asati in partial completion for the award of degree of Bachelor of Technology in Bioinformatics to Jaypee University of Information Technology, Waknaghat has been carried out under my guidance. This work has not been submitted partly or completely to any other University or Institute for the award of this or any other degree or diploma. …………………….. Dr. Tiratha Raj Singh Assistant Professor (Senior Grade) Date:…………………….. 2 Acknowledgement Known words become inadequate to express our gratitude for our mentor and supervisor Dr. Tiratha Raj Singh, Assistant professor in Department of Biotechnology and Bioinformatics, who initiated us into the realm of research and supervised us with finite patience and without whose invaluable suggestion and unstinted co-operation, the present desertion would not have been possible. We are also thankful to Ms. Ankita Shukla (PhD Scholar) for her incessant upkeep and encouragement. It was her who delivered us the technical guidance and direction to this project and continuously impelled us to work harder on this endeavour. Also, We would like to thank the officials of Jaypee University of Information Technology, Waknaghat for their help and cooperation.
  • Gene Co-Expression Network Analysis in Human Spinal Cord Highlights Mechanisms 2 Underlying Amyotrophic Lateral Sclerosis Susceptibility 3 4 Jerry C

    Gene Co-Expression Network Analysis in Human Spinal Cord Highlights Mechanisms 2 Underlying Amyotrophic Lateral Sclerosis Susceptibility 3 4 Jerry C

    bioRxiv preprint doi: https://doi.org/10.1101/2020.08.16.253377; this version posted August 17, 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 Gene co-expression network analysis in human spinal cord highlights mechanisms 2 underlying amyotrophic lateral sclerosis susceptibility 3 4 Jerry C. Wang1, Gokul Ramaswami1, Daniel H. Geschwind1,2,3,* 5 6 Affiliations 7 1 Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, 8 University of California, Los Angeles, Los Angeles, CA, United States of America 9 10 2 Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, 11 University of California, Los Angeles, Los Angeles, CA, United States of America 12 13 3 Department of Human Genetics, David Geffen School of Medicine, University of California, Los 14 Angeles, Los Angeles, CA, United States of America 15 16 *. Correspondence should be addressed to D.H.G: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.08.16.253377; this version posted August 17, 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. 17 Abstract 18 Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease defined by motor neuron 19 (MN) loss.
  • Transcription of Endogenous Retrovirus Group K Members and Their Neighboring Genes in Chicken Skeletal Muscle Myoblasts

    Transcription of Endogenous Retrovirus Group K Members and Their Neighboring Genes in Chicken Skeletal Muscle Myoblasts

    http://www.jstage.jst.go.jp/browse/jpsa doi:10.2141/ jpsa.0200021 Copyright Ⓒ 2021, Japan Poultry Science Association. Transcription of Endogenous Retrovirus Group K Members and Their Neighboring Genes in Chicken Skeletal Muscle Myoblasts Tomohide Takaya1, 2, 3, Yuma Nihashi1, Tamao Ono2 and Hiroshi Kagami2 1 Department of Science and Technology, Graduate School of Medicine, Science and Technology, Shinshu University, Nagano 399-4598, Japan 2 Department of Agricultural and Life Science, Faculty of Agriculture, Shinshu University, Nagano 399-4598, Japan 3 Department of Biomolecular Innovation, Institute for Biomedical Sciences, Shinshu University, Nagano 399-4598, Japan Skeletal muscle myoblasts are myogenic precursor cells that generate myofibers during muscle development and growth. We recently reported that broiler myoblasts, compared to layer myoblasts, proliferate and differentiate more actively and promptly into myocytes, which corresponds well with the muscle phenotype of broilers. Furthermore, RNA sequencing (RNA-seq) revealed that numerous genes are differentially expressed between layer and broiler myoblasts during myogenic differentiation. Based on the RNA-seq data, we herein report that chicken myoblasts transcribe endogenous retrovirus group K member (ERVK) genes. In total, 16 ERVKs were highly expressed in layer myoblasts and two (termed BrK1 and BrK2) were significantly induced in broiler myoblasts. These transcribed ERVKs had a totalof 182 neighboring genes within ±100 kb on the chromosomes, of which 40% were concentrated within ±10 kb of the ERVKs. We further investigated whether the transcription of ERVKs affects the expression of their neighboring genes. BrK1 had two neighboring genes; LOC107052719 was overlapping with BrK1 and down- regulated in the broiler myoblasts, and FAM19A2 was upregulated in the broiler myoblasts as well as BrK1.
  • High-Resolution X-Ray Structure of the Trimeric Scar/WAVE-Complex Precursor Brk1

    High-Resolution X-Ray Structure of the Trimeric Scar/WAVE-Complex Precursor Brk1

    High-Resolution X-Ray Structure of the Trimeric Scar/ WAVE-Complex Precursor Brk1 Joern Linkner1., Gregor Witte2*., Theresia Stradal3,4, Ute Curth1, Jan Faix1* 1 Institute for Biophysical Chemistry, Hannover Medical School, Hannover, Germany, 2 Gene Center and Department of Biochemistry, Munich Center for Advanced Photonics (MAP) and Center for Integrated Protein Science Munich (CIPSM) at the Ludwig-Maximilians-University, Munich, Germany, 3 Institute for Molecular Cell Biology, University of Muenster, Muenster, Germany, 4 Signaling and Motility Group, Helmholtz Centre for Infection Research (HZI), Braunschweig, Germany Abstract The Scar/WAVE-complex links upstream Rho-GTPase signaling to the activation of the conserved Arp2/3-complex. Scar/ WAVE-induced and Arp2/3-complex-mediated actin nucleation is crucial for actin assembly in protruding lamellipodia to drive cell migration. The heteropentameric Scar/WAVE-complex is composed of Scar/WAVE, Abi, Nap, Pir and a small polypeptide Brk1/HSPC300, and recent work suggested that free Brk1 serves as a homooligomeric precursor in the assembly of this complex. Here we characterized the Brk1 trimer from Dictyostelium by analytical ultracentrifugation and gelfiltration. We show for the first time its dissociation at concentrations in the nanomolar range as well as an exchange of subunits within different DdBrk1 containing complexes. Moreover, we determined the three-dimensional structure of DdBrk1 at 1.5 A˚ resolution by X-ray crystallography. Three chains of DdBrk1 are associated with each other forming a parallel triple coiled- coil bundle. Notably, this structure is highly similar to the heterotrimeric a-helical bundle of HSPC300/WAVE1/Abi2 within the human Scar/WAVE-complex. This finding, together with the fact that Brk1 is collectively sandwiched by the remaining subunits and also constitutes the main subunit connecting the triple-coil domain of the HSPC300/WAVE1/Abi2/ heterotrimer to Sra1(Pir1), implies a critical function of this subunit in the assembly process of the entire Scar/WAVE- complex.
  • Table S1. 103 Ferroptosis-Related Genes Retrieved from the Genecards

    Table S1. 103 Ferroptosis-Related Genes Retrieved from the Genecards

    Table S1. 103 ferroptosis-related genes retrieved from the GeneCards. Gene Symbol Description Category GPX4 Glutathione Peroxidase 4 Protein Coding AIFM2 Apoptosis Inducing Factor Mitochondria Associated 2 Protein Coding TP53 Tumor Protein P53 Protein Coding ACSL4 Acyl-CoA Synthetase Long Chain Family Member 4 Protein Coding SLC7A11 Solute Carrier Family 7 Member 11 Protein Coding VDAC2 Voltage Dependent Anion Channel 2 Protein Coding VDAC3 Voltage Dependent Anion Channel 3 Protein Coding ATG5 Autophagy Related 5 Protein Coding ATG7 Autophagy Related 7 Protein Coding NCOA4 Nuclear Receptor Coactivator 4 Protein Coding HMOX1 Heme Oxygenase 1 Protein Coding SLC3A2 Solute Carrier Family 3 Member 2 Protein Coding ALOX15 Arachidonate 15-Lipoxygenase Protein Coding BECN1 Beclin 1 Protein Coding PRKAA1 Protein Kinase AMP-Activated Catalytic Subunit Alpha 1 Protein Coding SAT1 Spermidine/Spermine N1-Acetyltransferase 1 Protein Coding NF2 Neurofibromin 2 Protein Coding YAP1 Yes1 Associated Transcriptional Regulator Protein Coding FTH1 Ferritin Heavy Chain 1 Protein Coding TF Transferrin Protein Coding TFRC Transferrin Receptor Protein Coding FTL Ferritin Light Chain Protein Coding CYBB Cytochrome B-245 Beta Chain Protein Coding GSS Glutathione Synthetase Protein Coding CP Ceruloplasmin Protein Coding PRNP Prion Protein Protein Coding SLC11A2 Solute Carrier Family 11 Member 2 Protein Coding SLC40A1 Solute Carrier Family 40 Member 1 Protein Coding STEAP3 STEAP3 Metalloreductase Protein Coding ACSL1 Acyl-CoA Synthetase Long Chain Family Member 1 Protein
  • Characterization of Drug-Induced Splicing Complexity in Prostate Cancer Cell Line Using Long Read Technology Abstract Introducti

    Characterization of Drug-Induced Splicing Complexity in Prostate Cancer Cell Line Using Long Read Technology Abstract Introducti

    Pacific Symposium on Biocomputing 2018 Characterization of drug-induced splicing complexity in prostate cancer cell line using long read technology Xintong Chen1, Sander Houten1, Kimaada Allette1, Robert P.Sebra1, Gustavo Stolovitzky*1,2 and Bojan Losic*1 1. Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave, New York, NY 10029, USA 2. IBM Translational Systems Biology and Nanobiotechnology Research, Yorktown Heights, NY 10598, USA *Corresponding Authors: Email: [email protected], [email protected] Abstract We characterize the transcriptional splicing landscape of a prostate cancer cell line treated with a previously identified synergistic drug combination. We use a combination of third generation long-read RNA sequencing technology and short-read RNAseq to create a high-fidelity map of expressed isoforms and fusions to quantify splicing events triggered by treatment. We find strong evidence for drug-induced, coherent splicing changes which disrupt the function of oncogenic proteins, and detect novel transcripts arising from previously unreported fusion events. Keywords: Combination treatment; Long read sequencing; Alternative splicing; Cancer. Introduction Background Prostate cancer is the second-most common cancer and has the third leading cancer mortality among men in the USA.[1] Major clinical interventions for prostate cancer include surgical procedure, radiation, androgen depletion treatment (ADT) and chemotherapy. As with other cancers, prognosis of prostate cancer varies largely depending on its molecular characteristics [2]. A number of large-scale collaborative efforts and crowd-sourcing initiatives have recently been used to profile genomic data on cancer systems perturbed by thousands of compounds to infer agents with curing potential.

  • Brick1 Is an Essential Regulator of Actin Cytoskeleton Required for Embryonic Development and Cell Transformation by B

    Supplementary Information Brick1 is an essential regulator of actin cytoskeleton required for embryonic development and cell transformation by B. Escobar et al… Supplementary Methods BRK1 expression and reporter assays. Brk1-EGFP fusion proteins were generated by subcloning the Brk1 cDNA into the pEGFP-N1 vector (Clontech). Brk1 transcripts were analyzed in a variety of mouse tissues by hybridization on RNA membranes (Zyagen) using the full mouse Brk1 cDNA was used as a probe. For detection of -galactosidase activity in embryos and adult tissues, samples were included in OCT compound (Sakura) and frozen. X-Gal staining of 10 m thick cryosections was performed as described (1). Counter-staining of cryostat sections was performed with nuclear fast red. Whole-mount staining of embryos or tissues was performed after fixation with glutaraldehyde and paraformaldehyde by incubating these samples with the X-Gal solution during 24 h (1). After X-Gal staining, these embryos or organs were fixed in formalin, embedded in paraffin and five- m sections were counterstained with nuclear fast red. Collagen degradation assays. These assays were performed essentially as described in Bravo-Cordero et al. (2). Briefly, U2OS, 786O and SN12C cells were transfected with the different constructs and 24 h after transfection, cells were plated at low density onto 1 2D-Collagen I-coated coverslips, and incubated for additional 24 h. After fixation, the collagen layer was immunostained using anti-Collagen I antibody (Sigma C2456) and cells were labelled using CellMask dye (C10046 from Invitrogen). As negative control for degradation we used a general MMP inhibitor (GW6001) that set up the background of the experiment.

  • Global Dna Methylation and Gene Expression Analysis in Pre-B Cell Acute Lymphoblastic Leukemia

    GLOBAL DNA METHYLATION AND GENE EXPRESSION ANALYSIS IN PRE-B CELL ACUTE LYMPHOBLASTIC LEUKEMIA 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 MD ALMAMUN Dr. Kristen H. Taylor, Dissertation Supervisor JULY 2015 © Copyright by Md Almamun 2015 All Rights Reserved The undersigned, appointed by the dean of the Graduate School, have examined the Dissertation entitled GLOBAL DNA METHYLATION AND GENE EXPRESSION ANALYSIS IN PRE-B CELL ACUTE LYMPHOBLASTIC LEUKEMIA Presented by Md Almamun A candidate for the degree of Doctor of Philosophy And hereby certify that, in their opinion, it is worthy of acceptance. Kristen H. Taylor James M. Amos-Landgraf Gerald L. Arthur Mark A. Daniels J. Wade Davis DEDICATION This work is dedicated to my parents, Abdul Aziz & Khosh Nahar Begum, my inspiration. ACKNOWLEDGMENTS I would first like to acknowledge my advisor, Dr. Kristen H. Taylor for her guidance and patience throughout this research project. I was able to gain knowledge, research passion and complete this project with her tremendous helps and encouragement. Thank you for being so positive and for everything you did for me. I would also like to thank my degree committee members, Dr. J. Wade Davis, Dr. Gerald L. Arthur, Dr. James M. Amos-Landgraf, and Dr. Mark A. Daniels for their advice and guidance in this endeavor. I would like to special thank Dr. J. Wade Davis, Benjamin T. Levinson, and Nathan T. Johnson for analyzing MIRA-seq and RNA-seq data, and Annette C.