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The University of Chicago Genetic Services Laboratories
The University of Chicago Genetic Services Laboratories 5841 S. Maryland Ave., Rm. G701, MC 0077, Chicago, Illinois 60637 Toll Free: (888) UC GENES (888) 824 3637 Local: (773) 834 0555 FAX: (773) 702 9130 [email protected] dnatesting.uchicago.edu. CLIA #: 14D0917593 CAP #: 18827-49 Next Generation Sequencing Panel for Early Infantile Epileptic Encephalopathy Clinical Features and Molecular Genetics: Early infantile epileptic encephalopathy (EIEE), also known as Ohtahara syndrome, is a severe form of epilepsy characterized by frequent tonic spasms with onset in the first months of life. EEG reveals suppression-burst patterns, characterized by high- voltage bursts alternating with almost flat suppression phases. Seizures are medically intractable with evolution to West syndrome at 3-6 months of age and then Lennox-Gastaut syndrome at 1-3 years of age. EIEE represents approximately 1% of all epilepsies occuring in children less than 15 years of age (1). Patients have severe developmental delay and poor prognosis. The diagnostic workup of EIEEs remains challenging because of frequent difficulties in defining etiologies. Acquired structural abnormalities like hypoxic-ischemic insults and isolated cortical malformations, which represent the most common causes of epileptic encelphalopathy in infancy should be excluded first (2). Our EIEE Panel includes sequence analysis of all 15 genes listed below, and deletion/duplication analysis of the 12 genes listed in bold below. Early Infantile Epileptic Encephalopathy Panel ARHGEF9 KCNQ2 PNKP SLC2A1 ARX MAGI2 SCN1A SPTAN1 CDKL5 PCDH19 SCN2A STXBP1 GRIN2A PLCB1 SLC25A22 Gene / Condition Clinical Features and Molecular Pathology ARHGEF9 The ARHGEF9 gene encodes the protein collybistin, which is a brain-specific protein involved in EIEE8 inhibitory synaptogenesis (3). -
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. -
Figure S1. Representative Report Generated by the Ion Torrent System Server for Each of the KCC71 Panel Analysis and Pcafusion Analysis
Figure S1. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. A Figure S1. Continued. Representative report generated by the Ion Torrent system server for each of the KCC71 panel analysis and PCaFusion analysis. (A) Details of the run summary report followed by the alignment summary report for the KCC71 panel analysis sequencing. (B) Details of the run summary report for the PCaFusion panel analysis. B Figure S2. Comparative analysis of the variant frequency found by the KCC71 panel and calculated from publicly available cBioPortal datasets. For each of the 71 genes in the KCC71 panel, the frequency of variants was calculated as the variant number found in the examined cases. Datasets marked with different colors and sample numbers of prostate cancer are presented in the upper right. *Significantly high in the present study. Figure S3. Seven subnetworks extracted from each of seven public prostate cancer gene networks in TCNG (Table SVI). Blue dots represent genes that include initial seed genes (parent nodes), and parent‑child and child‑grandchild genes in the network. Graphical representation of node‑to‑node associations and subnetwork structures that differed among and were unique to each of the seven subnetworks. TCNG, The Cancer Network Galaxy. Figure S4. REVIGO tree map showing the predicted biological processes of prostate cancer in the Japanese. Each rectangle represents a biological function in terms of a Gene Ontology (GO) term, with the size adjusted to represent the P‑value of the GO term in the underlying GO term database. -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
Table of Contents Neurology.Org/Ng Online ISSN: 2376-7839 Volume 3, Number 3, June 2017
Table of Contents Neurology.org/ng Online ISSN: 2376-7839 Volume 3, Number 3, June 2017 THE HELIX e151 HSP and deafness: Neurocristopathy caused by e157 Collaboration, workshops, and symposia a novel mosaic SOX10 mutation S.M. Pulst S. Donkervoort, D. Bharucha-Goebel, P. Yun, Y. Hu, P. Mohassel, A. Hoke, W.M. Zein, D. Ezzo, A.M. Atherton, A.C. Modrcin, M. Dasouki, A.R. Foley, and C.G. Bönnemann EDITORIAL e159 ARHGEF9 mutations cause a specific recognizable X-linked intellectual disability e155 Genetic analysis of age at onset variation in syndrome spinocerebellar ataxia type 2 P. Striano and F. Zara K.P. Figueroa, H. Coon, N. Santos, L. Velazquez, Companion article, e148 L.A. Mederos, and S.M. Pulst ARTICLES e158 Previously unrecognized behavioral phenotype in e148 ARHGEF9 disease: Phenotype clarification and Gaucher disease type 3 genotype-phenotype correlation M. Abdelwahab, M. Potegal, E.G. Shapiro, and M.Alber,V.M.Kalscheuer,E.Marco,E.Sherr, I. Nestrasil G. Lesca, M. Till, G. Gradek, A. Wiesener, C. Korenke, S. Mercier, F. Becker, T. Yamamoto, S.W. Scherer, C.R. Marshall, S. Walker, U.R. Dutta, A.B. Dalal, e160 Intramyocellular lipid excess in the mitochondrial V. Suckow, P. Jamali, K. Kahrizi, H. Najmabadi, and disorder MELAS: MRS determination at 7T B.A. Minassian S. Golla, J. Ren, C.R. Malloy, and J.M. Pascual Editorial, e159 e149 Clinicopathologic and molecular spectrum of CLINICAL/SCIENTIFIC NOTES RNASEH1-related mitochondrial disease e147 Camptocormia and shuffling gait due to a novel E. Bugiardini, O.V. Poole, A. Manole, A.M. Pittman, MT-TV mutation: Diagnostic pitfalls A. -
A Database of Gene Regulatory Network Models Across Human Conditions
bioRxiv preprint doi: https://doi.org/10.1101/2021.06.18.448997; this version posted June 18, 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. GRAND: A database of gene regulatory network models across human conditions Marouen Ben Guebila1†, Camila M Lopes-Ramos1†, Deborah Weighill1,7, Abhijeet Rajendra Sonawane2, Rebekka Burkholz1, Behrouz Shamsaei3, John Platig4, Kimberly Glass1,4, Marieke L Kuijjer5,6, John Quackenbush1,4,*. 1Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA. 2Center for Interdisciplinary Cardiovascular Sciences, Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA. 3Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA. 4Channing Division of Network Medicine, Department of Medicine, Harvard Medical School and Brigham and Women’s Hospital 5Center for Molecular Medicine Norway, Faculty of Medicine, University of Oslo, Norway 6Leiden University Medical Center, Leiden, the Netherlands 7Current address: UNC Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA † Joint Authors. * To whom correspondence should be addressed. Email: [email protected]. 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.06.18.448997; this version posted June 18, 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. -
Supplemental Information
Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig. -
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 -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
A Worldwide Map of Swine Short Tandem Repeats and Their
Wu et al. Genet Sel Evol (2021) 53:39 https://doi.org/10.1186/s12711-021-00631-4 Genetics Selection Evolution RESEARCH ARTICLE Open Access A worldwide map of swine short tandem repeats and their associations with evolutionary and environmental adaptations Zhongzi Wu1, Huanfa Gong1, Mingpeng Zhang1, Xinkai Tong1, Huashui Ai1, Shijun Xiao1, Miguel Perez‑Enciso2,3, Bin Yang1* and Lusheng Huang1* Abstract Background: Short tandem repeats (STRs) are genetic markers with a greater mutation rate than single nucleotide polymorphisms (SNPs) and are widely used in genetic studies and forensics. However, most studies in pigs have focused only on SNPs or on a limited number of STRs. Results: This study screened 394 deep‑sequenced genomes from 22 domesticated pig breeds/populations world‑ wide, wild boars from both Europe and Asia, and numerous outgroup Suidaes, and identifed a set of 878,967 poly‑ morphic STRs (pSTRs), which represents the largest repository of pSTRs in pigs to date. We found multiple lines of evidence that pSTRs in coding regions were afected by purifying selection. The enrichment of trinucleotide pSTRs in coding sequences (CDS), 5′UTR and H3K4me3 regions suggests that trinucleotide STRs serve as important com‑ ponents in the exons and promoters of the corresponding genes. We demonstrated that, compared to SNPs, pSTRs provide comparable or even greater accuracy in determining the breed identity of individuals. We identifed pSTRs that showed signifcant population diferentiation between domestic pigs and wild boars in Asia and Europe. We also observed that some pSTRs were signifcantly associated with environmental variables, such as average annual tem‑ perature or altitude of the originating sites of Chinese indigenous breeds, among which we identifed loss‑of‑function and/or expanded STRs overlapping with genes such as AHR, LAS1L and PDK1. -
Mutation P.R356Q in the Collybistin Phosphoinositide Binding Site Is Associated with Mild Intellectual Disability
ORIGINAL RESEARCH published: 12 March 2019 doi: 10.3389/fnmol.2019.00060 Mutation p.R356Q in the Collybistin Phosphoinositide Binding Site Is Associated With Mild Intellectual Disability Tzu-Ting Chiou 1, Philip Long 2, Alexandra Schumann-Gillett 3, Venkateswarlu Kanamarlapudi 4, Stefan A. Haas 5, Kirsten Harvey 2, Megan L. O’Mara 3, Angel L. De Blas 1, Vera M. Kalscheuer 6 and Robert J. Harvey 7,8* 1Department of Physiology and Neurobiology, University of Connecticut, Storrs, CT, United States, 2Department of Pharmacology, UCL School of Pharmacy, London, United Kingdom, 3Research School of Chemistry, The Australian National University, Canberra, ACT, Australia, 4Institute of Life Science, School of Medicine, Swansea University, Singleton Park, Swansea, United Kingdom, 5Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany, 6Group Development and Disease, Max Planck Institute for Molecular Genetics, Berlin, Germany, 7School of Health and Sport Sciences, University of the Sunshine Coast, Sippy Downs, QLD, Australia, 8Sunshine Coast Health Institute, Birtinya, QLD, Australia The recruitment of inhibitory GABAA receptors to neuronal synapses requires a complex interplay between receptors, neuroligins, the scaffolding protein gephyrin and the GDP-GTP exchange factor collybistin (CB). Collybistin is regulated by protein-protein interactions at the N-terminal SH3 domain, which can bind neuroligins 2/4 and the Edited by: Verena Tretter, GABAAR a2 subunit. Collybistin also harbors a RhoGEF domain which mediates Medical University of Vienna, Austria interactions with gephyrin and catalyzes GDP-GTP exchange on Cdc42. Lastly, Reviewed by: collybistin has a pleckstrin homology (PH) domain, which binds phosphoinositides, Hans Michael Maric, Universität Würzburg, Germany such as phosphatidylinositol 3-phosphate (PI3P/PtdIns3P) and phosphatidylinositol Yuchio Yanagawa, 4-monophosphate (PI4P/PtdIns4P). -
Target Gene Gene Description Validation Diana Miranda
Supplemental Table S1. Mmu-miR-183-5p in silico predicted targets. TARGET GENE GENE DESCRIPTION VALIDATION DIANA MIRANDA MIRBRIDGE PICTAR PITA RNA22 TARGETSCAN TOTAL_HIT AP3M1 adaptor-related protein complex 3, mu 1 subunit V V V V V V V 7 BTG1 B-cell translocation gene 1, anti-proliferative V V V V V V V 7 CLCN3 chloride channel, voltage-sensitive 3 V V V V V V V 7 CTDSPL CTD (carboxy-terminal domain, RNA polymerase II, polypeptide A) small phosphatase-like V V V V V V V 7 DUSP10 dual specificity phosphatase 10 V V V V V V V 7 MAP3K4 mitogen-activated protein kinase kinase kinase 4 V V V V V V V 7 PDCD4 programmed cell death 4 (neoplastic transformation inhibitor) V V V V V V V 7 PPP2R5C protein phosphatase 2, regulatory subunit B', gamma V V V V V V V 7 PTPN4 protein tyrosine phosphatase, non-receptor type 4 (megakaryocyte) V V V V V V V 7 EZR ezrin V V V V V V 6 FOXO1 forkhead box O1 V V V V V V 6 ANKRD13C ankyrin repeat domain 13C V V V V V V 6 ARHGAP6 Rho GTPase activating protein 6 V V V V V V 6 BACH2 BTB and CNC homology 1, basic leucine zipper transcription factor 2 V V V V V V 6 BNIP3L BCL2/adenovirus E1B 19kDa interacting protein 3-like V V V V V V 6 BRMS1L breast cancer metastasis-suppressor 1-like V V V V V V 6 CDK5R1 cyclin-dependent kinase 5, regulatory subunit 1 (p35) V V V V V V 6 CTDSP1 CTD (carboxy-terminal domain, RNA polymerase II, polypeptide A) small phosphatase 1 V V V V V V 6 DCX doublecortin V V V V V V 6 ENAH enabled homolog (Drosophila) V V V V V V 6 EPHA4 EPH receptor A4 V V V V V V 6 FOXP1 forkhead box P1 V