DOCSLIB.ORG

Transcriptomic Analysis of Ribosome-Bound Mrna in Cortical Neurites in Vivo

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

This Accepted Manuscript has not been copyedited and formatted. The final version may differ from this version. A link to any extended data will be provided when the final version is posted online. Research Articles: Cellular/Molecular Transcriptomic Analysis of Ribosome-Bound mRNA in Cortical Neurites In Vivo Rebecca Ouwenga1,2,3, Allison M. Lake2,3, David O'Brien2,3, Amit Mogha4, Adish Dani5,6 and Joseph D. Dougherty2,3,6 1Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA 2Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA 3Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA 4Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA 5Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA 6Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA DOI: 10.1523/JNEUROSCI.3044-16.2017 Received: 29 September 2016 Revised: 29 June 2017 Accepted: 21 July 2017 Published: 8 August 2017 Author Contributions: RO: Developed and conducted SynapTRAP, data analysis, validation studies, and writing of manuscript; AL: Contributed to data analysis and writing of manuscript; AM: Conducted EM imaging.; DO: Contributed to data analysis; AD: Conducted STORM imaging; JD: Conceived of study, contributed to data analysis, and writing of manuscript. Conflict of Interest: JDD has received royalties related to TRAP in the past. No other authors declare a conflict of interest. We would like to thank M. Wong for Thy-1 mice, K. Monk, C. Weichselbaum and members of the Dougherty lab for helpful comments, N. Pisat, N. Kopp, K. Sakers, and S. Pyfrom for training, advice, and assistance. This work was supported by the CDI (MD-II-2013-269), and NIH (R21DA038458, R21MH099798, R01NS102272). Key technical support was provided by the Genome Technology Resource Center at Washington University (supported by NIH grants P30 CA91842 and UL1TR000448). RO was supported by T32 GM081739. JDD is a NARSAD investigator. Correspondence should be addressed to Contact: Dr. Joseph Dougherty, Dougherty Lab, Department of Genetics, 660 S. Euclid Ave, Campus Box 8232, St. Louis, MO 63110-1093, P: 314-286-0752, F: 314-362-7855, E: [email protected] Cite as: J. Neurosci ; 10.1523/JNEUROSCI.3044-16.2017 Alerts: Sign up at www.jneurosci.org/cgi/alerts to receive customized email alerts when the fully formatted version of this article is published. Accepted manuscripts are peer-reviewed but have not been through the copyediting, formatting, or proofreading process. Copyright © 2017 the authors 1 Title: Transcriptomic Analysis of Ribosome-Bound mRNA in Cortical Neurites In Vivo 2 3 Running Title: In Vivo Analysis of mRNA in Cortical Neurites 4 5 Authors: Rebecca Ouwenga1-3, Allison M. Lake2,3, David O’Brien2,3, Amit Mogha4, Adish Dani5,6, 6 Joseph D. Dougherty*2,3,6 7 8 1Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. 9 Louis, MO, USA 10 2Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA 11 3Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA 12 4Department of Developmental Biology, Washington University School of Medicine, St. Louis, 13 MO, USA 14 5Department of Pathology and Immunology, Washington University School of Medicine, St. 15 Louis, MO, USA 16 6Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, 17 MO, USA 18 19 Contact: 20 Dr. Joseph Dougherty 21 Dougherty Lab, Department of Genetics 22 660 S. Euclid Ave, Campus Box 8232 23 St. Louis, MO 63110-1093 24 P: 314-286-0752 25 F: 314-362-7855 26 E: [email protected] 27 28 Number of Pages: 29 29 Number of Figures: 10 30 Number of Tables: 8 31 Abstract: 198 words 32 Introduction: 678 words 33 Discussion: 1373 34 35 CONFLICT OF INTEREST 36 37 JDD has received royalties related to TRAP in the past. No other authors declare a conflict of 38 interest. 39 40 ACKNOWLEDGEMENTS 41 42 We would like to thank M. Wong for Thy-1 mice, K. Monk, C. Weichselbaum and members of 43 the Dougherty lab for helpful comments, N. Pisat, N. Kopp, K. Sakers, and S. Pyfrom for training, 44 advice, and assistance. 1 45 ABSTRACT 46 47 Localized translation in neurites helps regulate synaptic strength and development. 48 Dysregulation of local translation is associated with many neurological disorders. However, due 49 to technical limitations, study of this phenomenon has largely been limited to brain regions 50 with laminar organization of dendrites such as the hippocampus or cerebellum. It has not been 51 examined in the cortex, a region of importance for most neurological disorders, where 52 dendrites of each neuronal population are densely intermingled with cell bodies of others. 53 Therefore, we have developed a novel method, SynapTRAP, which combines 54 synaptoneurosomal fractionation with Translating Ribosome Affinity Purification to identify 55 ribosome bound mRNA in processes of genetically defined cell types. We demonstrate 56 SynapTRAP’s efficacy and report local translation in the cortex of mice, where we identify a 57 subset of mRNAs that are translated in dendrites by neuronal ribosomes. These mRNAs have 58 disproportionately longer lengths, enrichment for FMRP binding and G-quartets, and their 59 genes are under greater evolutionary constraint in humans. In addition, we show that 60 alternative splicing likely regulates this phenomenon. Overall, SynapTRAP allows for rapid 61 isolation of cell-type specific localized translation and is applicable to classes of previously 62 inaccessible neuronal and non-neuronal cells in vivo. 63 64 65 SIGNIFICANCE STATEMENT 66 67 Instructions for making proteins are found in the genome, housed within the nucleus of each 68 cell. These are then copied as RNA and exported to manufacture new proteins. However, in the 69 brain, memory is thought to be encoded by strengthening individual connections (synapses) 70 between neurons far from the nucleus. Thus, to efficiently make new proteins specifically 71 where they are needed, neurons can transport RNAs to sites near synapses to locally produce 72 proteins. Importantly, several mutations that cause autism disrupt this process. It has been 73 assumed this process occurs in all brain regions, but has never been measured in the cortex. 74 We applied a newly developed method measure to study, for the first time, local translation in 75 cortical neurons. 76 77 INTRODUCTION 78 79 As all mRNA must come from a single cellular location (the nucleus) there is extensive post- 80 transcriptional regulation of RNA within cells, including localization of mRNA to specific 81 subcellular compartments. Localized translation of mRNA in specific subcellular compartments 82 allows more precise regulation of local protein concentrations, and thus modifies the functional 83 capacity of the compartment. A clear example exists in the nervous system where neurons 84 demonstrate remarkable capacity for regulated local translation with individual mRNAs 85 accumulating near activated synapses (Oswald Steward et al. 2014). Local translation in these 86 dendrites supports synaptic strengthening (Kang and Schuman 1996). While ultrastructural 87 evidence for localized translation in dendrites was first provided over thirty years ago (O. 2 88 Steward and Levy 1982), it is still not clear which mRNAs are translated in cortical neurites nor 89 how this translational profile changes across cell types. 90 91 In addition, several psychiatric diseases have been observed to have perturbations in neuronal 92 local translation. For example, Fragile X syndrome, an Autism Spectrum Disorder (ASD)-related 93 syndrome, and other ASD-associated disorders, are caused by mutations in known local 94 translational regulators (Kelleher and Bear 2008; Ronesi and Huber 2008). Interestingly, it has 95 been shown that the degree of translational perturbation in models of Fragile X can vary across 96 brain regions (Qin et al. 2005); however, it is unclear the extent to which local translation also 97 differs across cell types in response to disease, development, or activity. To study these kinds of 98 perturbations, a method is needed to enrich for both processes-localized and cell-type specific 99 mRNA. 100 101 Previously, studies have utilized cell-culture based methods for examining the RNAs found in 102 neurites in vitro (Poon et al. 2006; Taliaferro et al. 2016) in addition to physical methods (LCM 103 and manual dissection) to isolate processes of certain populations in vivo. In vivo, these 104 isolation techniques were limited to cell types with neurites that grow in a physical layer distant 105 from the cell body, including the CA1 synaptic neuropil of the hippocampus (Cajigas et al. 2012; 106 Poon et al. 2006; Ainsley et al. 2014; Zhong, Zhang, and Bloch 2006), and the Purkinje cell layer 107 of the cerebellum (Kratz et al. 2014). Likewise, a recent study was able to capture translating 108 mRNAs from retinal-geniculate axons because only retinal cells expressed the necessary tag 109 (Shigeoka et al. 2016). While valuable for assessing local translation in these limited neuronal 110 cell types, this approach is unable to assess localization in the intermingled dendrites of 111 neurons found in most regions of the brain, and provides no evidence as to whether the mRNAs 112 are on ribosomes, a prerequisite for local translation. The development of a method to isolate 113 the ribosome bound mRNAs from neurites of densely intermingled cells would allow analysis of 114 local translation across a larger number of cell types in the central nervous system (CNS). 115 116 Here, we describe SynapTRAP, a novel method that permits the harvesting of ribosomes from 117 the intermingled processes of specific cell types in vivo. This method combines subcellular 118 fractionation on a sucrose-percoll gradient with Translating Ribosome Affinity Purification 119 (TRAP) to identify ribosome bound mRNA from neurons in the synaptoneurosomal fraction 120 (SNF).
Recommended publications
  • Downloaded from [266]

    Downloaded from [266]

    Patterns of DNA methylation on the human X chromosome and use in analyzing X-chromosome inactivation by Allison Marie Cotton B.Sc., The University of Guelph, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2012 © Allison Marie Cotton, 2012 Abstract The process of X-chromosome inactivation achieves dosage compensation between mammalian males and females. In females one X chromosome is transcriptionally silenced through a variety of epigenetic modifications including DNA methylation. Most X-linked genes are subject to X-chromosome inactivation and only expressed from the active X chromosome. On the inactive X chromosome, the CpG island promoters of genes subject to X-chromosome inactivation are methylated in their promoter regions, while genes which escape from X- chromosome inactivation have unmethylated CpG island promoters on both the active and inactive X chromosomes. The first objective of this thesis was to determine if the DNA methylation of CpG island promoters could be used to accurately predict X chromosome inactivation status. The second objective was to use DNA methylation to predict X-chromosome inactivation status in a variety of tissues. A comparison of blood, muscle, kidney and neural tissues revealed tissue-specific X-chromosome inactivation, in which 12% of genes escaped from X-chromosome inactivation in some, but not all, tissues. X-linked DNA methylation analysis of placental tissues predicted four times higher escape from X-chromosome inactivation than in any other tissue. Despite the hypomethylation of repetitive elements on both the X chromosome and the autosomes, no changes were detected in the frequency or intensity of placental Cot-1 holes.
  • Delineation of Key Regulatory Elements Identifies Points Of

    Delineation of Key Regulatory Elements Identifies Points Of

    DELINEATION OF KEY REGULATORY ELEMENTS IDENTIFIES POINTS OF VULNERABILITY IN THE MITOGEN-ACTIVATED SIGNALING NETWORK SUPPLEMENTARY MATERIALS List of contents Supplementary Figures with legends 1. Figure S1: Distribution of primary siRNA screen data, and standardization of assay procedure. 2. Figure S2: Scatter plot of screen data. 3. Figure S3: Functional relevance of the identified targets and Calculation of residence time from PDT and cell cycle distribution. 4. Figure S4: FACS profiles for ABL1 and AKT1. Table for data in Figure 5B. 5. Figure S5: Venn diagram showing the results of the comparative analysis of other screen results 6. Figure S6: Dose response profiles for the AKT1 + ABL1 inhibitor combination for CH1, list of the 14 cell lines and their description, effect of ABL1+AKT1 inhibitor combination on increase in apoptotic cells and G1 arrest in 14 cell lines, effects of CHEK1 inhibitor on combination C1,C2 on 4 cell lines. Supplementary Tables 1. Table S1: siRNA screen results for targeted kinases and phosphatases. 2. Table S2: Gene expression status of the validated hits. 3. Table S3: Role played by identified RNAi hits in regulation of cell cycle, the effect on PDTs along with phase-specific RTs. 4. Table S4: List of molecules classified as cell cycle targets. 5. Table S5: High confidence network used for graph theory analysis. 6. Table S6: Occurrences of nodes in shortest path networks. 7. Table S7: Network file used as SNAVI background. 8. Table S8: Classification of nodes present in modules according to specificity. Legends for tables Supplementary Experimental Procedures References Figure S1 A 450 400 G1 S 350 G2 300 250 200 150 100 50 Distribution of molecules Distribution 0 -6-4-20246 Z-score 350 200 400 G1 S 300 G2 150 300 250 200 100 200 150 100 50 100 Distribution of molecules 50 0 0 0 -4 -2 0 2 4 -4-20246 -4-20246 Z-score B PLK1 GAPDH PLCg BTK PLCg CDC2A PLCg CHEK1 PLCg MET Distribution profiles of complete primary screen and western blots showing knockdown efficiency.
  • Sex-Chromosome Dosage Effects on Gene Expression in Humans

    Sex-Chromosome Dosage Effects on Gene Expression in Humans

    Sex-chromosome dosage effects on gene expression in humans Armin Raznahana,1, Neelroop N. Parikshakb,c, Vijay Chandrand, Jonathan D. Blumenthala, Liv S. Clasena, Aaron F. Alexander-Blocha, Andrew R. Zinne,f, Danny Wangsag, Jasen Wiseh, Declan G. M. Murphyi, Patrick F. Boltoni, Thomas Riedg, Judith Rossj, Jay N. Gieddk, and Daniel H. Geschwindb,c aDevelopmental Neurogenomics Unit, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892; bNeurogenetics Program, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095; cCenter for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, CA 90095; dDepartment of Pediatrics, School of Medicine, University of Florida, Gainesville, FL 32610; eMcDermott Center for Human Growth and Development, University of Texas Southwestern Medical School, Dallas, TX 75390; fDepartment of Internal Medicine, University of Texas Southwestern Medical School, Dallas, TX 75390; gGenetics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892; hQiagen, Frederick, MD 21703; iInstitute of Psychiatry, Psychology and Neuroscience, King’s College London, University of London, London WC1B 5DN, United Kingdom; jDepartment of Pediatrics, Thomas Jefferson University, Philadelphia, PA 19107; and kDepartment of Psychiatry, University of California, San Diego, La Jolla, CA 92093 Edited by James A. Birchler, University of Missouri,
  • View Board for Human Subjects Research

    View Board for Human Subjects Research

    BMC Medical Genetics BioMed Central G4Research article Open Access Expression profiling of clonal lymphocyte cell cultures from Rett syndrome patients Ivan J Delgado1,4, Dong Sun Kim1,5, Karen N Thatcher2, Janine M LaSalle2 and Ignatia B Van den Veyver*1,3 Address: 1Department of Obstetrics and Gynecology, Baylor College of Medicine, Houston, TX, USA, 2Medical Microbiology and Immunology and Rowe Program in Human Genetics, School of Medicine, University of California, Davis, CA, USA, 3Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA, 4Senior Scientist, Identigene Inc., 5615 Kirby, Suite 800 Houston, TX 77005, USA and 5Assistant Professor, Department of Anatomy, School of Medicine, Kyungpook National University, South Korea Email: Ivan J Delgado - [email protected]; Dong Sun Kim - [email protected]; Karen N Thatcher - [email protected]; Janine M LaSalle - [email protected]; Ignatia B Van den Veyver* - [email protected] * Corresponding author Published: 21 July 2006 Received: 25 October 2005 Accepted: 21 July 2006 BMC Medical Genetics 2006, 7:61 doi:10.1186/1471-2350-7-61 This article is available from: http://www.biomedcentral.com/1471-2350/7/61 © 2006 Delgado et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: More than 85% of Rett syndrome (RTT) patients have heterozygous mutations in the X-linked MECP2 gene which encodes methyl-CpG-binding protein 2, a transcriptional repressor that binds methylated CpG sites.
  • Infection-Derived Lipids Elicit an Immune Deficiency Circuit In

    Infection-Derived Lipids Elicit an Immune Deficiency Circuit In

    ARTICLE Received 12 May 2016 | Accepted 22 Dec 2016 | Published 14 Feb 2017 DOI: 10.1038/ncomms14401 OPEN Infection-derived lipids elicit an immune deficiency circuit in arthropods Dana K. Shaw1, Xiaowei Wang1, Lindsey J. Brown1,w, Adela S. Oliva Cha´vez1, Kathryn E. Reif2,w, Alexis A. Smith3, Alison J. Scott4, Erin E. McClure1, Vishant M. Boradia1, Holly L. Hammond1, Eric J. Sundberg5, Greg A. Snyder5, Lei Liu6, Kathleen DePonte6, Margarita Villar7, Massaro W. Ueti2, Jose´ de la Fuente7,8, Robert K. Ernst1,4, Utpal Pal3, Erol Fikrig6,9 & Joao H.F. Pedra1 The insect immune deficiency (IMD) pathway resembles the tumour necrosis factor receptor network in mammals and senses diaminopimelic-type peptidoglycans present in Gram-negative bacteria. Whether unidentified chemical moieties activate the IMD signalling cascade remains unknown. Here, we show that infection-derived lipids 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoglycerol (POPG) and 1-palmitoyl-2-oleoyl diacylglycerol (PODAG) stimulate the IMD pathway of ticks. The tick IMD network protects against colonization by three distinct bacteria, that is the Lyme disease spirochete Borrelia burgdorferi and the rickettsial agents Anaplasma phagocytophilum and A. marginale. Cell signalling ensues in the absence of transmembrane peptidoglycan recognition proteins and the adaptor molecules Fas-associated protein with a death domain (FADD) and IMD. Conversely, biochemical interactions occur between x-linked inhibitor of apoptosis protein (XIAP), an E3 ubiquitin ligase, and the E2 conjugating enzyme Bendless. We propose the existence of two functionally distinct IMD networks, one in insects and another in ticks. 1 Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA.
  • A Network Inference Approach to Understanding Musculoskeletal

    A Network Inference Approach to Understanding Musculoskeletal

    A NETWORK INFERENCE APPROACH TO UNDERSTANDING MUSCULOSKELETAL DISORDERS by NIL TURAN A thesis submitted to The University of Birmingham for the degree of Doctor of Philosophy College of Life and Environmental Sciences School of Biosciences The University of Birmingham June 2013 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT Musculoskeletal disorders are among the most important health problem affecting the quality of life and contributing to a high burden on healthcare systems worldwide. Understanding the molecular mechanisms underlying these disorders is crucial for the development of efficient treatments. In this thesis, musculoskeletal disorders including muscle wasting, bone loss and cartilage deformation have been studied using systems biology approaches. Muscle wasting occurring as a systemic effect in COPD patients has been investigated with an integrative network inference approach. This work has lead to a model describing the relationship between muscle molecular and physiological response to training and systemic inflammatory mediators. This model has shown for the first time that oxygen dependent changes in the expression of epigenetic modifiers and not chronic inflammation may be causally linked to muscle dysfunction.
  • Single Cell Analysis Reveals X Chromosome Upregulation Is Not

    Single Cell Analysis Reveals X Chromosome Upregulation Is Not

    bioRxiv preprint doi: https://doi.org/10.1101/2021.07.18.452817; this version posted July 19, 2021. 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 Single cell analysis reveals X chromosome upregulation is not global and 2 primarily belongs to ancestral genes in pre-gastrulation embryos 3 Naik C H, Chandel D, and Gayen S* 4 Department of Molecular Reproduction, Development and Genetics, Indian Institute of Science, 5 Bangalore-560012, India. 6 *Correspondence: [email protected] 7 8 Abstract 9 Recent studies have provided substantial evidence supporting Ohno's hypothesis that 10 upregulation of active X chromosome genes balances the dosage of X-linked gene expression 11 relative to autosomal genes. However, the dynamics of X-chromosome upregulation (XCU) 12 during early development remain poorly Pre-gastrulation embryos E6.50 13 understood. Here, we have profiled the E6.25 E5.5 14 dynamics of XCU in different lineages of 15 female pre-gastrulation mouse embryos at 16 single cell level through allele-specific single 17 cell RNA-seq analysis. We found dynamic 18 XCU upon initiation of random X- Epiblast cells 19 chromosome inactivation (XCI) in epiblast Onset of Random X-inactivation 20 cells and cells of extraembryonic lineages, 21 which undergo imprinted XCI, also harbored 22 upregulated active-X chromosome. On the 23 other hand, the extent of XCU remains 24 controversial till date.
  • Functional Non-Coding Polymorphism in an EPHA2 Promoter PAX2

    Functional Non-Coding Polymorphism in an EPHA2 Promoter PAX2

    www.nature.com/scientificreports OPEN Functional non-coding polymorphism in an EPHA2 promoter PAX2 binding site Received: 10 March 2017 Accepted: 4 August 2017 modifes expression and alters the Published: xx xx xxxx MAPK and AKT pathways Xiaoyin Ma1,2, Zhiwei Ma2, Xiaodong Jiao2 & J. Fielding Hejtmancik 2 To identify possible genetic variants infuencing expression of EPHA2 (Ephrin-receptor Type-A2), a tyrosine kinase receptor that has been shown to be important for lens development and to contribute to both congenital and age related cataract when mutated, the extended promoter region of EPHA2 was screened for variants. SNP rs6603883 lies in a PAX2 binding site in the EPHA2 promoter region. The C (minor) allele decreased EPHA2 transcriptional activity relative to the T allele by reducing the binding afnity of PAX2. Knockdown of PAX2 in human lens epithelial (HLE) cells decreased endogenous expression of EPHA2. Whole RNA sequencing showed that extracellular matrix (ECM), MAPK-AKT signaling pathways and cytoskeleton related genes were dysregulated in EPHA2 knockdown HLE cells. Taken together, these results indicate a functional non-coding SNP in EPHA2 promoter afects PAX2 binding and reduces EPHA2 expression. They further suggest that decreasing EPHA2 levels alters MAPK, AKT signaling pathways and ECM and cytoskeletal genes in lens cells that could contribute to cataract. These results demonstrate a direct role for PAX2 in EPHA2 expression and help delineate the role of EPHA2 in development and homeostasis required for lens transparency. Cataract is an opacity of the crystalline lens1. Hereditary cataract can occur at or near birth, usually as a Mendelian trait, or as individual ages, as a multifactorial trait infuenced by multiple genes and environmental factors.
  • 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
  • Role of Maternal Sin3a in Reprogramming Gene Expression During Mouse Preimplantation Development

    Role of Maternal Sin3a in Reprogramming Gene Expression During Mouse Preimplantation Development

    University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2016 Role Of Maternal Sin3a In Reprogramming Gene Expression During Mouse Preimplantation Development Richard A. Jimenez University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Developmental Biology Commons, and the Genetics Commons Recommended Citation Jimenez, Richard A., "Role Of Maternal Sin3a In Reprogramming Gene Expression During Mouse Preimplantation Development" (2016). Publicly Accessible Penn Dissertations. 2366. https://repository.upenn.edu/edissertations/2366 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/2366 For more information, please contact [email protected]. Role Of Maternal Sin3a In Reprogramming Gene Expression During Mouse Preimplantation Development Abstract In mouse, the maternal-to-zygotic transition entails a dramatic reprogramming of gene expression during the course of zygotic genome activation, which is essential for continued development beyond the 2-cell stage. Superimposed on zygotic genome activation and reprogramming of gene expression is formation of a chromatin-mediated transcriptionally repressive state that promotes repression of genes at the 2-cell stage. Experimentally inducing global histone hyperacetylation relieves this repression and histone deacetylase 1 (HDAC1) is the major HDAC involved in the development of this transcriptionally repressive state. Because SIN3A is essential
  • Sex-Chromosome Dosage Effects on Gene Expression in Humans

    Sex-Chromosome Dosage Effects on Gene Expression in Humans

    Sex-chromosome dosage effects on gene expression in humans Armin Raznahana,1, Neelroop N. Parikshakb,c, Vijay Chandrand, Jonathan D. Blumenthala, Liv S. Clasena, Aaron F. Alexander-Blocha, Andrew R. Zinne,f, Danny Wangsag, Jasen Wiseh, Declan G. M. Murphyi, Patrick F. Boltoni, Thomas Riedg, Judith Rossj, Jay N. Gieddk, and Daniel H. Geschwindb,c aDevelopmental Neurogenomics Unit, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892; bNeurogenetics Program, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095; cCenter for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, CA 90095; dDepartment of Pediatrics, School of Medicine, University of Florida, Gainesville, FL 32610; eMcDermott Center for Human Growth and Development, University of Texas Southwestern Medical School, Dallas, TX 75390; fDepartment of Internal Medicine, University of Texas Southwestern Medical School, Dallas, TX 75390; gGenetics Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892; hQiagen, Frederick, MD 21703; iInstitute of Psychiatry, Psychology and Neuroscience, King’s College London, University of London, London WC1B 5DN, United Kingdom; jDepartment of Pediatrics, Thomas Jefferson University, Philadelphia, PA 19107; and kDepartment of Psychiatry, University of California, San Diego, La Jolla, CA 92093 Edited by James A. Birchler, University of Missouri,
  • High Expression of the Sd Synthase B4GALNT2 Associates with Good

    High Expression of the Sd Synthase B4GALNT2 Associates with Good

    cells Article High Expression of the Sda Synthase B4GALNT2 Associates with Good Prognosis and Attenuates Stemness in Colon Cancer Michela Pucci y, Inês Gomes Ferreira y, Martina Orlandani, Nadia Malagolini, Manuela Ferracin and Fabio Dall’Olio * Department of Experimental, Diagnostic and Specialty Medicine (DIMES), General Pathology Building, University of Bologna, Via San Giacomo 14, Via San Giacomo 14, 40126 Bologna, Italy; [email protected] (M.P.); [email protected] (I.G.F.); [email protected] (M.O.); [email protected] (N.M.); [email protected] (M.F.) * Correspondence: [email protected]; Tel.: +39-051-2094704 These authors have equal contribution. y Received: 25 February 2020; Accepted: 7 April 2020; Published: 11 April 2020 Abstract: Background: The carbohydrate antigen Sda and its biosynthetic enzyme B4GALNT2 are highly expressed in normal colonic mucosa but are down-regulated to a variable degree in colon cancer tissues. Here, we investigated the clinical and biological importance of B4GALNT2 in colon cancer. Methods: Correlations of B4GALNT2 mRNA with clinical data were obtained from The Cancer Genome Atlas (TCGA) database; the phenotypic and transcriptomic changes induced by B4GALNT2 were studied in LS174T cells transfected with B4GALNT2 cDNA. Results: TCGA data indicate that patients with high B4GALNT2 expression in cancer tissues display longer survival than non-expressers. In LS174T cells, expression of B4GALNT2 did not affect the ability to heal a scratch wound or to form colonies in standard growth conditions but markedly reduced the growth in soft agar, the tridimensional (3D) growth as spheroids, and the number of cancer stem cells, indicating a specific effect of B4GALNT2 on the growth in poor adherence and stemness.