12Q14 Microdeletions
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High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model
Purdue University Purdue e-Pubs Department of Animal Sciences Faculty Department of Animal Sciences Publications 2016 High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model Chiao-Ling Lo Indiana University School of Medicine Amy C. Lossie Indiana University School of Medicine Tiebing Liang Indiana University School of Medicine Yunlong Liu Indiana University School of Medicine Xiaoling Xuei Indiana University School of Medicine See next page for additional authors Follow this and additional works at: http://docs.lib.purdue.edu/anscpubs Recommended Citation Lo C-L, Lossie AC, Liang T, Liu Y, Xuei X, Lumeng L, et al. (2016) High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model. PLoS Genet 12(8): e1006178. https://doi.org/10.1371/ journal.pgen.1006178 This document has been made available through Purdue e-Pubs, a service of the Purdue University Libraries. Please contact [email protected] for additional information. Authors Chiao-Ling Lo, Amy C. Lossie, Tiebing Liang, Yunlong Liu, Xiaoling Xuei, Lawrence Lumeng, Feng C. Zhou, and William M. Muir This article is available at Purdue e-Pubs: http://docs.lib.purdue.edu/anscpubs/19 RESEARCH ARTICLE High Resolution Genomic Scans Reveal Genetic Architecture Controlling Alcohol Preference in Bidirectionally Selected Rat Model Chiao-Ling Lo1,2, Amy C. Lossie1,3¤, Tiebing Liang1,4, Yunlong Liu1,5, Xiaoling Xuei1,6, Lawrence Lumeng1,4, Feng C. Zhou1,2,7*, William -
RUNNING HEAD: Low Homozygosity in Spanish Sheep
1 RUNNING HEAD: Low homozygosity in Spanish sheep 2 3 Low genome-wide homozygosity in eleven Spanish ovine breeds 4 5 M.G. Luigi 1, T.F. Cardoso 1, 2 , A. Martínez 3, A. Pons 4, L.A. Bermejo 5, J. Jordana 6, J.V. 6 Delgado 3, S. Adán 7, E. Ugarte 8, J. J. Arranz 9, J. Casellas 6 and M. Amills 1, 6 * 7 8 1Department of Animal Genetics, Centre for Research in Agricultural Genomics 9 (CRAG), CSIC-IRTA-UAB-UB, Campus Universitat Autònoma de Barcelona, 10 Bellaterra 08193, Spain; 2CAPES Foundation, Ministry of Education of Brazil, Brasilia 11 D. F., 70.040-020, Brazil; 3Departamento de Genética, Universidad de Córdoba, 12 Córdoba 14071, Spain; 4Unitat de Races Autòctones, Servei de Millora Agrària i 13 Pesquera (SEMILLA), Son Ferriol 07198, Spain; 5Departamento de Ingeniería, 14 Producción y Economía Agrarias, Universidad de La Laguna, 38071 La Laguna, 15 Tenerife, Spain; 6Departament de Ciència Animal i dels Aliments, Facultat de 16 Veterinària, Universitat Autònoma de Barcelona, Bellaterra 08193, Spain; 7Federación 17 de Razas Autóctonas de Galicia (BOAGA), Pazo de Fontefiz, 32152 Coles. Ourense, 18 Spain; 8Neiker-Tecnalia, Campus Agroalimentario de Arkaute, apdo 46 E-01080 19 Vitoria-Gazteiz (Araba), Spain; 9Departamento de Producción Animal, Universidad de 20 León, León 24071, Spain. 21 22 Corresponding author: Marcel Amills. Department of Animal Genetics, Centre for 23 Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus 24 Universitat Autònoma de Barcelona, Bellaterra 08193, Spain. Tel. 34 93 5636600. E- 25 mail: [email protected]. 26 Abstract 27 28 The population of Spanish sheep has decreased from 24 to 15 million heads in 29 the last 75 years due to multiple social and economic factors. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
GRIPAP1 / GRASP1 Antibody (N-Terminus) Goat Polyclonal Antibody Catalog # ALS14943
10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 GRIPAP1 / GRASP1 Antibody (N-Terminus) Goat Polyclonal Antibody Catalog # ALS14943 Specification GRIPAP1 / GRASP1 Antibody (N-Terminus) - Product Information Application IHC Primary Accession Q4V328 Reactivity Human Host Goat Clonality Polyclonal Calculated MW 96kDa KDa GRIPAP1 / GRASP1 Antibody (N-Terminus) - Additional Information Gene ID 56850 Anti-GRIPAP1 / GRASP1 antibody IHC of Other Names human brain, cortex. GRIP1-associated protein 1, GRASP-1, GRIPAP1, KIAA1167 Target/Specificity Human GRIPAP1 / GRASP1. This antibody is expected to recognize both reported isoforms (as represented by NP_064522.3; NP_997555.1) Reconstitution & Storage Store at -20°C. Minimize freezing and thawing. Precautions GRIPAP1 / GRASP1 Antibody (N-Terminus) is for research use only and not for use in Anti-GRIPAP1 / GRASP1 antibody IHC of diagnostic or therapeutic procedures. human tonsil. GRIPAP1 / GRASP1 Antibody (N-Terminus) GRIPAP1 / GRASP1 Antibody (N-Terminus) - Protein Information - References Bechtel S.,et al.BMC Genomics Name GRIPAP1 (HGNC:18706) 8:399-399(2007). Ross M.T.,et al.Nature 434:325-337(2005). Synonyms KIAA1167 Hirosawa M.,et al.DNA Res. 6:329-336(1999). Function Lubec G.,et al.Submitted (DEC-2008) to Regulates the endosomal recycling back to UniProtKB. the neuronal plasma membrane, possibly Holt L.J.,et al.Nucleic Acids Res. by connecting early and late recycling 28:72-72(2000). endosomal domains and promoting Page 1/2 10320 Camino Santa Fe, Suite G San Diego, CA 92121 Tel: 858.875.1900 Fax: 858.622.0609 segregation of recycling endosomes from early endosomal membranes. -
Mutation Analysis of Genes Within the Dynactin Complex in a Cohort of Hereditary Peripheral Neuropathies
Clin Genet 2016: 90: 127–133 © 2015 John Wiley & Sons A/S. Printed in Singapore. All rights reserved Published by John Wiley & Sons Ltd CLINICAL GENETICS doi: 10.1111/cge.12712 Original Article Mutation analysis of genes within the dynactin complex in a cohort of hereditary peripheral neuropathies a a Tey S., Ahmad-Annuar A., Drew A.P., Shahrizaila N., Nicholson G.A., S. Tey , A. Ahmad-Annuar , Kennerson M.L. Mutation analysis of genes within the dynactin complex in A.P. Drewb, N. Shahrizailac, , a cohort of hereditary peripheral neuropathies. G.A. Nicholsonb d and Clin Genet 2016: 90: 127–133. © John Wiley & Sons A/S. Published by M.L. Kennersonb,d John Wiley & Sons Ltd, 2015 aDepartment of Biomedical Science, The cytoplasmic dynein–dynactin genes are attractive candidates for Faculty of Medicine, University of Malaya, b neurodegenerative disorders given their functional role in retrograde Kuala Lumpur, Malaysia, Northcott transport along neurons. The cytoplasmic dynein heavy chain (DYNC1H1) Neuroscience Laboratory, ANZAC Research Institute, and Sydney Medical gene has been implicated in various neurodegenerative disorders, and School, University of Sydney, Sydney, dynactin 1 (DCTN1) genes have been implicated in a wide spectrum of Australia, cDepartment of Medicine, disorders including motor neuron disease, Parkinson’s disease, spinobulbar Faculty of Medicine, University of Malaya, muscular atrophy and hereditary spastic paraplegia. However, the Kuala Lumpur, Malaysia, and dMolecular involvement of other dynactin genes with inherited peripheral neuropathies Medicine Laboratory, Concord Hospital, (IPN) namely, hereditary sensory neuropathy, hereditary motor neuropathy Sydney, Australia and Charcot–Marie–Tooth disease is under reported. We screened eight genes; DCTN1-6 and ACTR1A and ACTR1B in 136 IPN patients using Key words: Charcot–Marie–Tooth – whole-exome sequencing and high-resolution melt (HRM) analysis. -
FARE2021WINNERS Sorted by Institute
FARE2021WINNERS Sorted By Institute Swati Shah Postdoctoral Fellow CC Radiology/Imaging/PET and Neuroimaging Characterization of CNS involvement in Ebola-Infected Macaques using Magnetic Resonance Imaging, 18F-FDG PET and Immunohistology The Ebola (EBOV) virus outbreak in Western Africa resulted in residual neurologic abnormalities in survivors. Many case studies detected EBOV in the CSF, suggesting that the neurologic sequelae in survivors is related to viral presence. In the periphery, EBOV infects endothelial cells and triggers a “cytokine stormâ€. However, it is unclear whether a similar process occurs in the brain, with secondary neuroinflammation, neuronal loss and blood-brain barrier (BBB) compromise, eventually leading to lasting neurological damage. We have used in vivo imaging and post-necropsy immunostaining to elucidate the CNS pathophysiology in Rhesus macaques infected with EBOV (Makona). Whole brain MRI with T1 relaxometry (pre- and post-contrast) and FDG-PET were performed to monitor the progression of disease in two cohorts of EBOV infected macaques from baseline to terminal endpoint (day 5-6). Post-necropsy, multiplex fluorescence immunohistochemical (MF-IHC) staining for various cellular markers in the thalamus and brainstem was performed. Serial blood and CSF samples were collected to assess disease progression. The linear mixed effect model was used for statistical analysis. Post-infection, we first detected EBOV in the serum (day 3) and CSF (day 4) with dramatic increases until euthanasia. The standard uptake values of FDG-PET relative to whole brain uptake (SUVr) in the midbrain, pons, and thalamus increased significantly over time (p<0.01) and positively correlated with blood viremia (p≤0.01). -
GRIP1 Gene Glutamate Receptor Interacting Protein 1
GRIP1 gene glutamate receptor interacting protein 1 Normal Function The GRIP1 gene provides instructions for making a protein that is able to attach (bind) to other proteins and is important for moving (targeting) proteins to the correct location in cells. For example, the GRIP1 protein targets two proteins called FRAS1 and FREM2 to the correct region of the cell so that they can form a group of proteins known as the FRAS/FREM complex. This complex is found in the thin, sheet-like structures ( basement membranes) that separate and support the cells of many tissues. The complex is particularly important during development before birth. One of its roles is to anchor the top layer of skin by connecting the basement membrane of the top layer to the layer of skin below. The FRAS/FREM complex is also involved in the proper development of certain other organs and tissues, including the kidneys, although the mechanism is unclear. In addition, the GRIP1 protein targets necessary proteins to the junctions (synapses) between nerve cells (neurons) in the brain where cell-to-cell communication occurs. GRIP1 may also be involved in the development of neurons. Health Conditions Related to Genetic Changes Fraser syndrome At least two GRIP1 gene mutations have been found to cause Fraser syndrome; these mutations are involved in a small percentage of cases of this condition. Fraser syndrome affects development before birth and is characterized by eyes that are completely covered by skin (cryptophthalmos), fusion of the skin between the fingers and toes (cutaneous syndactyly), and abnormalities of the kidneys and other organs and tissues. -
GRIP1 Regulates Synaptic Plasticity and Learning and Memory
GRIP1 regulates synaptic plasticity and learning and memory Han L. Tana,1, Shu-Ling Chiua,b,1, Qianwen Zhua,1, and Richard L. Huganira,2 aSolomon H. Snyder Department of Neuroscience and Kavli Neuroscience Discovery Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205; and bInstitute of Cellular and Organismic Biology, Academia Sinica, 11529 Taipei, Taiwan Contributed by Richard L. Huganir, August 18, 2020 (sent for review July 15, 2020; reviewed by Lin Mei and Peter Penzes) Hebbian plasticity is a key mechanism for higher brain functions, plasticity. For example, synapse-associated protein (SAP97) directly such as learning and memory. This form of synaptic plasticity primarily binds the GluA1 subunit and may promote AMPAR trafficking and involves the regulation of synaptic α-amino-3-hydroxy-5-methyl-4-isoxa- LTP (11–13). Protein interacting with C-kinase 1 (PICK1), a zolepropionic acid receptor (AMPAR) abundance and properties, whereby GluA2 subunit-binding protein, functions to remove AMPAR AMPARs are inserted into synapses during long-term potentiation (LTP) from synapses and causes internalization of synaptic AMPARs, or removed during long-term depression (LTD). The molecular mecha- and deficits in Hebbian plasticity have been reported in PICK1 nisms underlying AMPAR trafficking remain elusive, however. Here we mutant mice (14, 15). show that glutamate receptor interacting protein 1 (GRIP1), an AMPAR- Glutamate receptor interacting protein (GRIP1) is a scaf- binding protein shown to regulate the trafficking and synaptic targeting folding protein that has seven postsynaptic density 95/discs large/ of AMPARs, is required for LTP and learning and memory. GRIP1 is zona occludens (PDZ) domains (16, 17). -
Downloaded Per Proteome Cohort Via the Web- Site Links of Table 1, Also Providing Information on the Deposited Spectral Datasets
www.nature.com/scientificreports OPEN Assessment of a complete and classifed platelet proteome from genome‑wide transcripts of human platelets and megakaryocytes covering platelet functions Jingnan Huang1,2*, Frauke Swieringa1,2,9, Fiorella A. Solari2,9, Isabella Provenzale1, Luigi Grassi3, Ilaria De Simone1, Constance C. F. M. J. Baaten1,4, Rachel Cavill5, Albert Sickmann2,6,7,9, Mattia Frontini3,8,9 & Johan W. M. Heemskerk1,9* Novel platelet and megakaryocyte transcriptome analysis allows prediction of the full or theoretical proteome of a representative human platelet. Here, we integrated the established platelet proteomes from six cohorts of healthy subjects, encompassing 5.2 k proteins, with two novel genome‑wide transcriptomes (57.8 k mRNAs). For 14.8 k protein‑coding transcripts, we assigned the proteins to 21 UniProt‑based classes, based on their preferential intracellular localization and presumed function. This classifed transcriptome‑proteome profle of platelets revealed: (i) Absence of 37.2 k genome‑ wide transcripts. (ii) High quantitative similarity of platelet and megakaryocyte transcriptomes (R = 0.75) for 14.8 k protein‑coding genes, but not for 3.8 k RNA genes or 1.9 k pseudogenes (R = 0.43–0.54), suggesting redistribution of mRNAs upon platelet shedding from megakaryocytes. (iii) Copy numbers of 3.5 k proteins that were restricted in size by the corresponding transcript levels (iv) Near complete coverage of identifed proteins in the relevant transcriptome (log2fpkm > 0.20) except for plasma‑derived secretory proteins, pointing to adhesion and uptake of such proteins. (v) Underrepresentation in the identifed proteome of nuclear‑related, membrane and signaling proteins, as well proteins with low‑level transcripts. -
A Different View on DNA Amplifications Indicates Frequent, Highly Complex, and Stable Amplicons on 12Q13-21 in Glioma
A Different View on DNA Amplifications Indicates Frequent, Highly Complex, and Stable Amplicons on 12q13-21 in Glioma Ulrike Fischer,1 Andreas Keller,3 Petra Leidinger,1 Stephanie Deutscher,1 Sabrina Heisel,1 Steffi Urbschat,2 Hans-Peter Lenhof,3 and Eckart Meese1 Departments of 1Human Genetics and 2Neurosurgery, Saarland University, Homburg/Saar, Germany and 3Center for Bioinformatics, Saarland University, Saarbru¨cken, Germany Abstract Introduction To further understand the biological significance of DNA amplification does not occur in normal human cells amplifications for glioma development and recurrencies, but in multidrug-resistant cells and in tumor cells. Numerous we characterized amplicon frequency and size in studies described gene amplification in various human tumors low-grade glioma and amplicon stability in vivo in by cytogenetic and molecular genetic means. The breakage- recurring glioblastoma. We developed a 12q13-21 fusion-bridge cycle (1) is the most popular model to explain amplicon–specific genomic microarray and a intrachromosomal amplifications and many amplified structures bioinformatics amplification prediction tool to analyze like mixed ladders that were found in homogeneously staining amplicon frequency, size, and maintenance in 40 glioma regions (2). The ‘‘episome model’’ proposes that episomes samples including 16 glioblastoma, 10 anaplastic result from excision of small circular DNA that enlarges by astrocytoma, 7 astrocytoma WHO grade 2, and 7 overreplication or recombination until it becomes cytogeneti- pilocytic astrocytoma. Whereas previous studies cally visible as double minute chromosomes (3). Recent results reported two amplified subregions, we found a more of Tanaka et al. (4) showthat large palindromic sequences were complex situation with many amplified subregions. present in human cancers and the location of palindromes in the Analyzing 40 glioma, we found that all analyzed cancer genome serves as a structural platform to support glioblastoma and the majority of pilocytic astrocytoma, subsequent gene amplification. -
Gain-Of-Function Glutamate Receptor Interacting Protein 1 Variants Alter Glua2 Recycling and Surface Distribution in Patients with Autism
Gain-of-function glutamate receptor interacting protein 1 variants alter GluA2 recycling and surface distribution in patients with autism Rebeca Mejiasa, Abby Adamczyka, Victor Anggonob,c, Tejasvi Niranjana,d, Gareth M. Thomasb,c, Kamal Sharmab,c, Cindy Skinnere, Charles E. Schwartze, Roger E. Stevensone, M. Daniele Fallinf, Walter Kaufmanng,h, Mikhail Pletnikovb,h, David Vallea, Richard L. Huganirb,c,1, and Tao Wanga,1 aMcKusick-Nathans Institute of Genetic Medicine and Department of Pediatrics, bDepartment of Neuroscience, cThe Howard Hughes Medical Institute, dPredoctoral Training Program in Human Genetics, and hDepartment of Psychiatry and Behavioral Sciences, The Johns Hopkins University School of Medicine, Baltimore, MD 21205; eGreenwood Genetic Center, Greenwood, SC 29646; fDepartment of Epidemiology, The Johns Hopkins University School of Public Health, Baltimore, MD 21205; and gThe Kennedy Krieger Institute, Baltimore, MD 21205 Contributed by Richard L. Huganir, February 14, 2011 (sent for review December 13, 2010) Glutamate receptor interacting protein 1 (GRIP1) is a neuronal ceptor targeting and localization to the postsynaptic membrane scaffolding protein that interacts directly with the C termini of and for activity-dependent synaptic reorganization of AMPA glutamate receptors 2/3 (GluA2/3) via its PDZ domains 4 to 6 (PDZ4– receptors (16, 20). 6). We found an association (P < 0.05) of a SNP within the PDZ4-6 genomic region with autism by genotyping autistic patients (n = Results 480) and matched controls (n = 480). Parallel sequencing identified We identified an association (P = 0.048) of a common SNP five rare missense variants within or near PDZ4–6 only in the au- (rs7397862) in intron 15 of GRIP1 within the region encoding tism cohort, resulting in a higher cumulative mutation load (P = PDZ4–6 (exons 12–16) in a case-control study of autism (n = 0.032). -
Phenotype Informatics
Freie Universit¨atBerlin Department of Mathematics and Computer Science Phenotype informatics: Network approaches towards understanding the diseasome Sebastian Kohler¨ Submitted on: 12th September 2012 Dissertation zur Erlangung des Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.) am Fachbereich Mathematik und Informatik der Freien Universitat¨ Berlin ii 1. Gutachter Prof. Dr. Martin Vingron 2. Gutachter: Prof. Dr. Peter N. Robinson 3. Gutachter: Christopher J. Mungall, Ph.D. Tag der Disputation: 16.05.2013 Preface This thesis presents research work on novel computational approaches to investigate and characterise the association between genes and pheno- typic abnormalities. It demonstrates methods for organisation, integra- tion, and mining of phenotype data in the field of genetics, with special application to human genetics. Here I will describe the parts of this the- sis that have been published in peer-reviewed journals. Often in modern science different people from different institutions contribute to research projects. The same is true for this thesis, and thus I will itemise who was responsible for specific sub-projects. In chapter 2, a new method for associating genes to phenotypes by means of protein-protein-interaction networks is described. I present a strategy to organise disease data and show how this can be used to link diseases to the corresponding genes. I show that global network distance measure in interaction networks of proteins is well suited for investigat- ing genotype-phenotype associations. This work has been published in 2008 in the American Journal of Human Genetics. My contribution here was to plan the project, implement the software, and finally test and evaluate the method on human genetics data; the implementation part was done in close collaboration with Sebastian Bauer.