Blueprint Genetics Congenital Disorders of Glycosylation Panel
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The Diversity of Dolichol-Linked Precursors to Asn-Linked Glycans Likely Results from Secondary Loss of Sets of Glycosyltransferases
The diversity of dolichol-linked precursors to Asn-linked glycans likely results from secondary loss of sets of glycosyltransferases John Samuelson*†, Sulagna Banerjee*, Paula Magnelli*, Jike Cui*, Daniel J. Kelleher‡, Reid Gilmore‡, and Phillips W. Robbins* *Department of Molecular and Cell Biology, Boston University Goldman School of Dental Medicine, 715 Albany Street, Boston, MA 02118-2932; and ‡Department of Biochemistry and Molecular Biology, University of Massachusetts Medical School, Worcester, MA 01665-0103 Contributed by Phillips W. Robbins, December 17, 2004 The vast majority of eukaryotes (fungi, plants, animals, slime mold, to N-glycans of improperly folded proteins, which are retained in and euglena) synthesize Asn-linked glycans (Alg) by means of a the ER by conserved glucose-binding lectins (calnexin͞calreticulin) lipid-linked precursor dolichol-PP-GlcNAc2Man9Glc3. Knowledge of (13). Although the Alg glycosyltransferases in the lumen of ER this pathway is important because defects in the glycosyltrans- appear to be eukaryote-specific, archaea and Campylobacter sp. ferases (Alg1–Alg12 and others not yet identified), which make glycosylate the sequon Asn and͞or contain glycosyltransferases dolichol-PP-glycans, lead to numerous congenital disorders of with domains like those of Alg1, Alg2, Alg7, and STT3 (1, 14–16). glycosylation. Here we used bioinformatic and experimental Protists, unicellular eukaryotes, suggest three notable exceptions methods to characterize Alg glycosyltransferases and dolichol- to the N-linked glycosylation path described in yeast and animals PP-glycans of diverse protists, including many human patho- (17). First, the kinetoplastid Trypanosoma cruzi (cause of Chagas gens, with the following major conclusions. First, it is demon- myocarditis), fails to glucosylate the dolichol-PP-linked precursor strated that common ancestry is a useful method of predicting and so makes dolichol-PP-GlcNAc2Man9 (18). -
Physical Interactions Between the Alg1, Alg2, and Alg11 Mannosyltransferases of the Endoplasmic Reticulum
Glycobiology vol. 14 no. 6 pp. 559±570, 2004 DOI: 10.1093/glycob/cwh072 Advance Access publication on March 24, 2004 Physical interactions between the Alg1, Alg2, and Alg11 mannosyltransferases of the endoplasmic reticulum Xiao-Dong Gao2, Akiko Nishikawa1, and Neta Dean1 begins on the cytosolic face of the ER, where seven sugars (two N-acetylglucoseamines and five mannoses) are added 1Department of Biochemistry and Cell Biology, Institute for Cell and Developmental Biology, State University of New York, Stony Brook, sequentially to dolichyl phosphate on the outer leaflet of NY 11794-5215, and 2Research Center for Glycoscience, National the ER, using nucleotide sugar donors (Abeijon and Institute of Advanced Industrial Science and Technology, Tsukuba Hirschberg, 1992; Perez and Hirschberg, 1986; Snider and Downloaded from https://academic.oup.com/glycob/article/14/6/559/638968 by guest on 30 September 2021 Central 6, 1-1 Higashi, Tsukuba 305-8566, Japan Rogers, 1984). After a ``flipping'' or translocation step, the Received on January 26, 2004; revised on March 2, 2004; accepted on last seven sugars (four mannoses and three glucoses) are March 2, 2004 added within the lumen of the ER, using dolichol-linked sugar donors (Burda and Aebi, 1999). Once assembled, the The early steps of N-linked glycosylation involve the synthesis oligosaccharide is transferred from the lipid to nascent of a lipid-linked oligosaccharide, Glc3Man9GlcNAc2-PP- protein in a reaction catalyzed by oligosaccharyltransferase. dolichol, on the endoplasmic reticulum (ER) membrane. After removal of terminal glucoses and a single mannose, Prior to its lumenal translocation and transfer to nascent nascent glycoproteins bearing the N-linked Man8GlcNAc2 glycoproteins, mannosylation of Man5GlcNAc2-PP-dolichol core can exit the ER to the Golgi, where this core may is catalyzed by the Alg1, Alg2, and Alg11 mannosyltrans- undergo further carbohydrate modifications. -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
Autism Multiplex Family with 16P11.2P12.2 Microduplication Syndrome in Monozygotic Twins and Distal 16P11.2 Deletion in Their Brother
European Journal of Human Genetics (2012) 20, 540–546 & 2012 Macmillan Publishers Limited All rights reserved 1018-4813/12 www.nature.com/ejhg ARTICLE Autism multiplex family with 16p11.2p12.2 microduplication syndrome in monozygotic twins and distal 16p11.2 deletion in their brother Anne-Claude Tabet1,2,3,4, Marion Pilorge2,3,4, Richard Delorme5,6,Fre´de´rique Amsellem5,6, Jean-Marc Pinard7, Marion Leboyer6,8,9, Alain Verloes10, Brigitte Benzacken1,11,12 and Catalina Betancur*,2,3,4 The pericentromeric region of chromosome 16p is rich in segmental duplications that predispose to rearrangements through non-allelic homologous recombination. Several recurrent copy number variations have been described recently in chromosome 16p. 16p11.2 rearrangements (29.5–30.1 Mb) are associated with autism, intellectual disability (ID) and other neurodevelopmental disorders. Another recognizable but less common microdeletion syndrome in 16p11.2p12.2 (21.4 to 28.5–30.1 Mb) has been described in six individuals with ID, whereas apparently reciprocal duplications, studied by standard cytogenetic and fluorescence in situ hybridization techniques, have been reported in three patients with autism spectrum disorders. Here, we report a multiplex family with three boys affected with autism, including two monozygotic twins carrying a de novo 16p11.2p12.2 duplication of 8.95 Mb (21.28–30.23 Mb) characterized by single-nucleotide polymorphism array, encompassing both the 16p11.2 and 16p11.2p12.2 regions. The twins exhibited autism, severe ID, and dysmorphic features, including a triangular face, deep-set eyes, large and prominent nasal bridge, and tall, slender build. The eldest brother presented with autism, mild ID, early-onset obesity and normal craniofacial features, and carried a smaller, overlapping 16p11.2 microdeletion of 847 kb (28.40–29.25 Mb), inherited from his apparently healthy father. -
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. -
Linkage Analysis in 15 Families, Physical And
European Journal of Human Genetics (2002) 11, 145 – 154 ª 2002 Nature Publishing Group All rights reserved 1018 – 4813/02 $25.00 www.nature.com/ejhg ARTICLE Familial juvenile hyperuricaemic nephropathy (FJHN): linkage analysis in 15 families, physical and transcriptional characterisation of the FJHN critical region on chromosome 16p11.2 and the analysis of seven candidate genes Blanka Stibu˚ rkova´1, Jacek Majewski2, Katerˇina Hodanˇova´1, Lenka Ondrova´1, Marke´ta Jerˇa´bkova´1, Marie Zika´nova´1, Petr Vylet’al1, Ivan Sˇebesta3, Anthony Marinaki4, Anne Simmonds4, Gert Matthijs5, Jean-Pierre Fryns5, Rosa Torres6, Juan Garcı´a Puig7, Jurg Ott2 and Stanislav Kmoch*,1 1Center for Integrated Genomics, Institute for Inherited Metabolic Disorders, Charles University 1st School of Medicine and General Faculty Hospital Prague, Czech Republic; 2Laboratory of Statistical Genetics, Rockefeller University, New York, NY, USA; 3Department of Clinical Biochemistry, Charles University 1st School of Medicine and General Faculty Hospital Prague, Czech Republic; 4Purine Research Unit, GKT, Guy’s Hospital, London, UK; 5Center for Human Genetics, University of Leuven, Leuven, Belgium; 6Department of Clinical Biochemistry, La Paz Hospital, Madrid, Spain; 7Division of Internal Medicine, La Paz Hospital, Madrid, Spain Familial juvenile hyperuricaemic nephropathy (FJHN) is an autosomal dominant renal disease characterised by juvenile onset of hyperuricaemia, gouty arthritis, and progressive renal failure at an early age. Recent studies in four kindreds showed linkage of a gene for FJHN to the same genomic interval on chromosome 16p11.2, where the gene for the phenotypically similar medullary cystic disease type 2 (MCKD2) has been localised. In this study we performed linkage analysis in additional 15 FJHN families. -
Yeast Genome Gazetteer P35-65
gazetteer Metabolism 35 tRNA modification mitochondrial transport amino-acid metabolism other tRNA-transcription activities vesicular transport (Golgi network, etc.) nitrogen and sulphur metabolism mRNA synthesis peroxisomal transport nucleotide metabolism mRNA processing (splicing) vacuolar transport phosphate metabolism mRNA processing (5’-end, 3’-end processing extracellular transport carbohydrate metabolism and mRNA degradation) cellular import lipid, fatty-acid and sterol metabolism other mRNA-transcription activities other intracellular-transport activities biosynthesis of vitamins, cofactors and RNA transport prosthetic groups other transcription activities Cellular organization and biogenesis 54 ionic homeostasis organization and biogenesis of cell wall and Protein synthesis 48 plasma membrane Energy 40 ribosomal proteins organization and biogenesis of glycolysis translation (initiation,elongation and cytoskeleton gluconeogenesis termination) organization and biogenesis of endoplasmic pentose-phosphate pathway translational control reticulum and Golgi tricarboxylic-acid pathway tRNA synthetases organization and biogenesis of chromosome respiration other protein-synthesis activities structure fermentation mitochondrial organization and biogenesis metabolism of energy reserves (glycogen Protein destination 49 peroxisomal organization and biogenesis and trehalose) protein folding and stabilization endosomal organization and biogenesis other energy-generation activities protein targeting, sorting and translocation vacuolar and lysosomal -
Bioinformatics Analyses of Genomic Imprinting
Bioinformatics Analyses of Genomic Imprinting Dissertation zur Erlangung des Grades des Doktors der Naturwissenschaften der Naturwissenschaftlich-Technischen Fakultät III Chemie, Pharmazie, Bio- und Werkstoffwissenschaften der Universität des Saarlandes von Barbara Hutter Saarbrücken 2009 Tag des Kolloquiums: 08.12.2009 Dekan: Prof. Dr.-Ing. Stefan Diebels Berichterstatter: Prof. Dr. Volkhard Helms Priv.-Doz. Dr. Martina Paulsen Vorsitz: Prof. Dr. Jörn Walter Akad. Mitarbeiter: Dr. Tihamér Geyer Table of contents Summary________________________________________________________________ I Zusammenfassung ________________________________________________________ I Acknowledgements _______________________________________________________II Abbreviations ___________________________________________________________ III Chapter 1 – Introduction __________________________________________________ 1 1.1 Important terms and concepts related to genomic imprinting __________________________ 2 1.2 CpG islands as regulatory elements ______________________________________________ 3 1.3 Differentially methylated regions and imprinting clusters_____________________________ 6 1.4 Reading the imprint __________________________________________________________ 8 1.5 Chromatin marks at imprinted regions___________________________________________ 10 1.6 Roles of repetitive elements ___________________________________________________ 12 1.7 Functional implications of imprinted genes _______________________________________ 14 1.8 Evolution and parental conflict ________________________________________________ -
Congenital Disorders of Glycosylation from a Neurological Perspective
brain sciences Review Congenital Disorders of Glycosylation from a Neurological Perspective Justyna Paprocka 1,* , Aleksandra Jezela-Stanek 2 , Anna Tylki-Szyma´nska 3 and Stephanie Grunewald 4 1 Department of Pediatric Neurology, Faculty of Medical Science in Katowice, Medical University of Silesia, 40-752 Katowice, Poland 2 Department of Genetics and Clinical Immunology, National Institute of Tuberculosis and Lung Diseases, 01-138 Warsaw, Poland; [email protected] 3 Department of Pediatrics, Nutrition and Metabolic Diseases, The Children’s Memorial Health Institute, W 04-730 Warsaw, Poland; [email protected] 4 NIHR Biomedical Research Center (BRC), Metabolic Unit, Great Ormond Street Hospital and Institute of Child Health, University College London, London SE1 9RT, UK; [email protected] * Correspondence: [email protected]; Tel.: +48-606-415-888 Abstract: Most plasma proteins, cell membrane proteins and other proteins are glycoproteins with sugar chains attached to the polypeptide-glycans. Glycosylation is the main element of the post- translational transformation of most human proteins. Since glycosylation processes are necessary for many different biological processes, patients present a diverse spectrum of phenotypes and severity of symptoms. The most frequently observed neurological symptoms in congenital disorders of glycosylation (CDG) are: epilepsy, intellectual disability, myopathies, neuropathies and stroke-like episodes. Epilepsy is seen in many CDG subtypes and particularly present in the case of mutations -
We Consider the Ordinary Differential Equation Model of the Metal Rolling
We consider the ordinary differential equation model of the metal rolling process defined in K. Gal- kowski, E. Rogers, W. Paszke and D. H. Owens, Linear repetitive process control theory applied to a physical example, Int. J. Appl. Comput. Sci., 13 (2003), 87-99. In order to do that, we firstly define the Ore algebra formed by the derivative D w.r.t. time t and by the shift operator S acting on the discrete variable k which denotes the pass number. > Alg1 := DefineOreAlgebra(diff=[D,t], dual_shift=[S,k], polynom=[t,k], > comm=[lambda,lambda1,lambda2,M]): The system matrix is defined by: > R1 := evalm([[D^2+lambda/M-(lambda/lambda1)*D^2*S-(lambda/M)*S, > lambda/(M*lambda2)]]); λ λ D2 S λ S λ R1 := D2 + − − M λ1 M M λ2 Then, the system is defined by the following equation > ApplyMatrix(R1, [y(t,k), FM(t,k)], Alg1)[1,1]=0; (λ y(t, k) λ1 λ2 − λ y(t, k − 1) λ1 λ2 + D1, 1(y)(t, k) M λ1 λ2 − λ D1, 1(y)(t, k − 1) M λ2 + λ FM(t, k) λ1)/(M λ1 λ2) = 0 which corresponds to (4) of the previously quoted paper. Let us check the structural properties of the previous system (e.g., controllability, parametrizability, flatness). > R1_adj := Involution(R1, Alg1): It is known that the Alg1 -module associated with the matrix R1 is torsion-free iff the first extension module of the Alg1 -module associated with R1 adj with values in Alg1 is 0. We compute this extension module by using Exti: > Ext1 := Exti(R1_adj, Alg1, 1); Ext1 := [ 1 , M λ D2 S λ2 − M D2 λ1 λ2 + λ S λ1 λ2 − λ λ1 λ2 −λ λ1 , −λ λ1 ] M D2 λ1 λ2 − M λ D2 S λ2 + λ λ1 λ2 − λ S λ1 λ2 As the first matrix Ext1 [1] is an identity matrix, we obtain that the Alg1 -module associated with R1 is torsion-free, and thus, the corresponding system is controllable and parametrizable. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Current Trends in Gene Recovery Mediated by the CRISPR-Cas System Hyeon-Ki Jang 1, Beomjong Song2,Gue-Hohwang1 and Sangsu Bae 1
Jang et al. Experimental & Molecular Medicine (2020) 52:1016–1027 https://doi.org/10.1038/s12276-020-0466-1 Experimental & Molecular Medicine REVIEW ARTICLE Open Access Current trends in gene recovery mediated by the CRISPR-Cas system Hyeon-Ki Jang 1, Beomjong Song2,Gue-HoHwang1 and Sangsu Bae 1 Abstract The CRISPR-Cas system has undoubtedly revolutionized the genome editing field, enabling targeted gene disruption, regulation, and recovery in a guide RNA-specific manner. In this review, we focus on currently available gene recovery strategies that use CRISPR nucleases, particularly for the treatment of genetic disorders. Through the action of DNA repair mechanisms, CRISPR-mediated DNA cleavage at a genomic target can shift the reading frame to correct abnormal frameshifts, whereas DNA cleavage at two sites, which can induce large deletions or inversions, can correct structural abnormalities in DNA. Homology-mediated or homology-independent gene recovery strategies that require donor DNAs have been developed and widely applied to precisely correct mutated sequences in genes of interest. In contrast to the DNA cleavage-mediated gene correction methods listed above, base-editing tools enable base conversion in the absence of donor DNAs. In addition, CRISPR-associated transposases have been harnessed to generate a targeted knockin, and prime editors have been developed to edit tens of nucleotides in cells. Here, we introduce currently developed gene recovery strategies and discuss the pros and cons of each. 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; Introduction differs from that of the endogenous gene2. Furthermore, Human genetic disorders, often associated with severe the mutated endogenous gene, which is malfunctional and pathological phenotypes, are caused by genomic aberra- potentially cytotoxic, might still be transcribed.