Mutation of EMG1 Causing Bowen–Conradi Syndrome Results in Reduced Cell Proliferation Rates Concomitant with G2/M Arrest and 18S Rrna Processing Delay
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Analysis of Gene Expression Data for Gene Ontology
ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins. -
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. -
Pathogenic Variants in the DEAH-Box RNA Helicase DHX37 Are a Frequent Cause of 46,XY Gonadal Dysgenesis and 46,XY Testicular Regression Syndrome
ARTICLE © American College of Medical Genetics and Genomics Pathogenic variants in the DEAH-box RNA helicase DHX37 are a frequent cause of 46,XY gonadal dysgenesis and 46,XY testicular regression syndrome Ken McElreavey, PhD 1, Anne Jorgensen, PhD 2, Caroline Eozenou, PhD1, Tiphanie Merel, MSc1, Joelle Bignon-Topalovic, BSc1, Daisylyn Senna Tan, BSc3, Denis Houzelstein, PhD 1, Federica Buonocore, PhD 4, Nick Warr, PhD 5, Raissa G. G. Kay, PhD5, Matthieu Peycelon, MD, PhD 6,7,8, Jean-Pierre Siffroi, MD, PhD6, Inas Mazen, MD9, John C. Achermann, MD, PhD 4, Yuliya Shcherbak, MD10, Juliane Leger, MD, PhD11, Agnes Sallai, MD 12, Jean-Claude Carel, MD, PhD 11, Laetitia Martinerie, MD, PhD11, Romain Le Ru, MD13, Gerard S. Conway, MD, PhD14, Brigitte Mignot, MD15, Lionel Van Maldergem, MD, PhD 16, Rita Bertalan, MD, PhD17, Evgenia Globa, MD, PhD 18, Raja Brauner, MD, PhD19, Ralf Jauch, PhD 3, Serge Nef, PhD 20, Andy Greenfield, PhD5 and Anu Bashamboo, PhD1 Purpose: XY individuals with disorders/differences of sex devel- specifically associated with gonadal dysgenesis and TRS. opment (DSD) are characterized by reduced androgenization Consistent with a role in early testis development, DHX37 is caused, in some children, by gonadal dysgenesis or testis regression expressed specifically in somatic cells of the developing human during fetal development. The genetic etiology for most patients and mouse testis. with 46,XY gonadal dysgenesis and for all patients with testicular Conclusion: DHX37 pathogenic variants are a new cause of an regression syndrome (TRS) is unknown. autosomal dominant form of 46,XY DSD, including gonadal Methods: We performed exome and/or Sanger sequencing in 145 dysgenesis and TRS, showing that these conditions are part of a individuals with 46,XY DSD of unknown etiology including clinical spectrum. -
Inferring Biological Networks from Genome-Wide Transcriptional And
INFERRING BIOLOGICAL NETWORKS FROM GENOME-WIDE TRANSCRIPTIONAL AND FITNESS DATA By WAZEER MOHAMMAD VARSALLY 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 July 2013 I 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 In the last 15 years, the increased use of high throughput biology techniques such as genome-wide gene expression profiling, fitness profiling and protein interactomics has led to the generation of an extraordinary amount of data. The abundance of such diverse data has proven to be an essential foundation for understanding the complexities of molecular mechanisms and underlying pathways within a biological system. One approach of extrapolating biological information from this wealth of data has been through the use of reverse engineering methods to infer biological networks. This thesis demonstrates the capabilities and applications of such methodologies in identifying functionally enriched network modules in the yeast species Saccharomyces cerevisiae and Schizosaccharomyces pombe. This study marks the first time a mutual information based network inference approach has been applied to a set of specific genome-wide expression and fitness compendia, as well as the integration of these multi- level compendia. -
Number 9 September 2013
Atlas of Genetics and Cytogenetics in Oncology and Haematology OPEN ACCESS JOURNAL INIST -CNRS Volume 17 - Number 9 September 2013 The PDF version of the Atlas of Genetics and Cytogenetics in Oncology and Haematology is a reissue of the original articles published in collaboration with the Institute for Scientific and Technical Information (INstitut de l’Information Scientifique et Technique - INIST) of the French National Center for Scientific Research (CNRS) on its electronic publishing platform I-Revues. Online and PDF versions of the Atlas of Genetics and Cytogenetics in Oncology and Haematology are hosted by INIST-CNRS. Atlas of Genetics and Cytogenetics in Oncology and Haematology OPEN ACCESS JOURNAL INIST -CNRS Scope The Atlas of Genetics and Cytogenetics in Oncology and Haematology is a peer reviewed on-line journal in open access, devoted to genes, cytogenetics, and clinical entities in cancer, and cancer-prone diseases. It presents structured review articles ("cards") on genes, leukaemias, solid tumours, cancer-prone diseases, more traditional review articles on these and also on surrounding topics ("deep insights"), case reports in hematology, and educational items in the various related topics for students in Medicine and in Sciences. Editorial correspondance Jean-Loup Huret Genetics, Department of Medical Information, University Hospital F-86021 Poitiers, France tel +33 5 49 44 45 46 or +33 5 49 45 47 67 [email protected] or [email protected] Staff Mohammad Ahmad, Mélanie Arsaban, Marie-Christine Jacquemot-Perbal, Vanessa Le Berre, Anne Malo, Carol Moreau, Catherine Morel-Pair, Laurent Rassinoux, Alain Zasadzinski. Philippe Dessen is the Database Director, and Alain Bernheim the Chairman of the on-line version (Gustave Roussy Institute – Villejuif – France). -
Supporting Information
Supporting Information Friedman et al. 10.1073/pnas.0812446106 SI Results and Discussion intronic miR genes in these protein-coding genes. Because in General Phenotype of Dicer-PCKO Mice. Dicer-PCKO mice had many many cases the exact borders of the protein-coding genes are defects in additional to inner ear defects. Many of them died unknown, we searched for miR genes up to 10 kb from the around birth, and although they were born at a similar size to hosting-gene ends. Out of the 488 mouse miR genes included in their littermate heterozygote siblings, after a few weeks the miRBase release 12.0, 192 mouse miR genes were found as surviving mutants were smaller than their heterozygote siblings located inside (distance 0) or in the vicinity of the protein-coding (see Fig. 1A) and exhibited typical defects, which enabled their genes that are expressed in the P2 cochlear and vestibular SE identification even before genotyping, including typical alopecia (Table S2). Some coding genes include huge clusters of miRNAs (in particular on the nape of the neck), partially closed eyelids (e.g., Sfmbt2). Other genes listed in Table S2 as coding genes are [supporting information (SI) Fig. S1 A and C], eye defects, and actually predicted, as their transcript was detected in cells, but weakness of the rear legs that were twisted backwards (data not the predicted encoded protein has not been identified yet, and shown). However, while all of the mutant mice tested exhibited some of them may be noncoding RNAs. Only a single protein- similar deafness and stereocilia malformation in inner ear HCs, coding gene that is differentially expressed in the cochlear and other defects were variable in their severity. -
393LN V 393P 344SQ V 393P Probe Set Entrez Gene
393LN v 393P 344SQ v 393P Entrez fold fold probe set Gene Gene Symbol Gene cluster Gene Title p-value change p-value change chemokine (C-C motif) ligand 21b /// chemokine (C-C motif) ligand 21a /// chemokine (C-C motif) ligand 21c 1419426_s_at 18829 /// Ccl21b /// Ccl2 1 - up 393 LN only (leucine) 0.0047 9.199837 0.45212 6.847887 nuclear factor of activated T-cells, cytoplasmic, calcineurin- 1447085_s_at 18018 Nfatc1 1 - up 393 LN only dependent 1 0.009048 12.065 0.13718 4.81 RIKEN cDNA 1453647_at 78668 9530059J11Rik1 - up 393 LN only 9530059J11 gene 0.002208 5.482897 0.27642 3.45171 transient receptor potential cation channel, subfamily 1457164_at 277328 Trpa1 1 - up 393 LN only A, member 1 0.000111 9.180344 0.01771 3.048114 regulating synaptic membrane 1422809_at 116838 Rims2 1 - up 393 LN only exocytosis 2 0.001891 8.560424 0.13159 2.980501 glial cell line derived neurotrophic factor family receptor alpha 1433716_x_at 14586 Gfra2 1 - up 393 LN only 2 0.006868 30.88736 0.01066 2.811211 1446936_at --- --- 1 - up 393 LN only --- 0.007695 6.373955 0.11733 2.480287 zinc finger protein 1438742_at 320683 Zfp629 1 - up 393 LN only 629 0.002644 5.231855 0.38124 2.377016 phospholipase A2, 1426019_at 18786 Plaa 1 - up 393 LN only activating protein 0.008657 6.2364 0.12336 2.262117 1445314_at 14009 Etv1 1 - up 393 LN only ets variant gene 1 0.007224 3.643646 0.36434 2.01989 ciliary rootlet coiled- 1427338_at 230872 Crocc 1 - up 393 LN only coil, rootletin 0.002482 7.783242 0.49977 1.794171 expressed sequence 1436585_at 99463 BB182297 1 - up 393 -
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 -
An Integrative Genomic Analysis of the Longshanks Selection Experiment for Longer Limbs in Mice
bioRxiv preprint doi: https://doi.org/10.1101/378711; this version posted August 19, 2018. 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 Title: 2 An integrative genomic analysis of the Longshanks selection experiment for longer limbs in mice 3 Short Title: 4 Genomic response to selection for longer limbs 5 One-sentence summary: 6 Genome sequencing of mice selected for longer limbs reveals that rapid selection response is 7 due to both discrete loci and polygenic adaptation 8 Authors: 9 João P. L. Castro 1,*, Michelle N. Yancoskie 1,*, Marta Marchini 2, Stefanie Belohlavy 3, Marek 10 Kučka 1, William H. Beluch 1, Ronald Naumann 4, Isabella Skuplik 2, John Cobb 2, Nick H. 11 Barton 3, Campbell Rolian2,†, Yingguang Frank Chan 1,† 12 Affiliations: 13 1. Friedrich Miescher Laboratory of the Max Planck Society, Tübingen, Germany 14 2. University of Calgary, Calgary AB, Canada 15 3. IST Austria, Klosterneuburg, Austria 16 4. Max Planck Institute for Cell Biology and Genetics, Dresden, Germany 17 Corresponding author: 18 Campbell Rolian 19 Yingguang Frank Chan 20 * indicates equal contribution 21 † indicates equal contribution 22 Abstract: 23 Evolutionary studies are often limited by missing data that are critical to understanding the 24 history of selection. Selection experiments, which reproduce rapid evolution under controlled 25 conditions, are excellent tools to study how genomes evolve under strong selection. Here we 1 bioRxiv preprint doi: https://doi.org/10.1101/378711; this version posted August 19, 2018. -
A Master Autoantigen-Ome Links Alternative Splicing, Female Predilection, and COVID-19 to Autoimmune Diseases
bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454526; this version posted August 4, 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 4.0 International license. A Master Autoantigen-ome Links Alternative Splicing, Female Predilection, and COVID-19 to Autoimmune Diseases Julia Y. Wang1*, Michael W. Roehrl1, Victor B. Roehrl1, and Michael H. Roehrl2* 1 Curandis, New York, USA 2 Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, USA * Correspondence: [email protected] or [email protected] 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.07.30.454526; this version posted August 4, 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 4.0 International license. Abstract Chronic and debilitating autoimmune sequelae pose a grave concern for the post-COVID-19 pandemic era. Based on our discovery that the glycosaminoglycan dermatan sulfate (DS) displays peculiar affinity to apoptotic cells and autoantigens (autoAgs) and that DS-autoAg complexes cooperatively stimulate autoreactive B1 cell responses, we compiled a database of 751 candidate autoAgs from six human cell types. At least 657 of these have been found to be affected by SARS-CoV-2 infection based on currently available multi-omic COVID data, and at least 400 are confirmed targets of autoantibodies in a wide array of autoimmune diseases and cancer. -
Stella Modulates Transcriptional and Endogenous Retrovirus Programs
Stella modulates transcriptional and endogenous retrovirus programs during maternal-to-zygotic transition Yun Huang1,7 , Jong Kyoung Kim2,6,7, Dang Vinh Do1, Caroline Lee1, Christopher A. Penfold1, Jan J. Zylicz1, John C. Marioni2,3,5, Jamie A. Hackett1,4,8, M. Azim Surani1,8 1 Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Tennis Court Road, Cambridge CB2 1QN, UK; Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK 2 European Molecular Biology Laboratory – European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge CB10 1SD, UK 3 Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SA, UK 4 Present Address: European Molecular Biology Laboratory (EMBL) - Monterotondo, via Ramarini 32, 00015 Rome, Italy 5 Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge CB2 0RE, UK 6 Department of New Biology, DGIST, Daegu, 42988, Republic of Korea 7 Co-first authors 8 Co-corresponding authors [email protected] [email protected] 1 1 Abstract 2 3 The maternal-to-zygotic transition (MZT) marks the period when the embryonic genome is 4 activated and acquires control of development. Maternally inherited factors play a key role in 5 this critical developmental process, which occurs at the 2-cell stage in mice. We investigated 6 the function of the maternally inherited factor Stella (encoded by Dppa3) using single- 7 cell/embryo approaches. We show that loss of maternal Stella results in widespread 8 transcriptional mis-regulation and a partial failure of MZT. Strikingly, activation of 9 endogenous retroviruses (ERVs) is significantly impaired in Stella maternal/zygotic knockout 10 embryos, which in turn leads to a failure to upregulate chimeric transcripts. -
The Ribosomopathy Paradox
FEBS Letters 588 (2014) 1491–1500 journal homepage: www.FEBSLetters.org Review Diverse diseases from a ubiquitous process: The ribosomopathy paradox ⇑ Joy Armistead a, Barbara Triggs-Raine a,b, a Department of Biochemistry and Medical Genetics, The University of Manitoba, 745 Bannatyne Ave., Winnipeg, MB R3E 0J9, Canada b The Manitoba Institute of Child Health, 715 McDermot Ave., Winnipeg, MB R3E 3P4, Canada article info abstract Article history: Collectively, the ribosomopathies are caused by defects in ribosome biogenesis. Although these dis- Received 9 January 2014 orders encompass deficiencies in a ubiquitous and fundamental process, the clinical manifestations Revised 8 March 2014 are extremely variable and typically display tissue specificity. Research into this paradox has offered Accepted 12 March 2014 fascinating new insights into the role of the ribosome in the regulation of mRNA translation, cell Available online 19 March 2014 cycle control, and signaling pathways involving TP53, MYC and mTOR. Several common features Edited by Ulrike Kutay of ribosomopathies such as small stature, cancer predisposition, and hematological defects, point to how these diverse diseases may be related at a molecular level. Ó 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved. Keywords: Ribosomopathy Ribosome biogenesis Tissue specificity IRES elements 1. Introduction through cleavage and modification events, ensuring equimolar amounts of these rRNA species. The 5S rRNA is transcribed inde- The ribosomopathies are a diverse group of disorders which, pendently by RNA polymerase III in the nucleoplasm, undergoing despite their heterogeneity at a clinical level, affect the same its own maturation pathway before re-importation into the biochemical process.