DOCSLIB.ORG

Assignment of Functional Impact on Genetic Data in Two Mouse Models of Affective Disorders

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Assignment of Functional Impact on Genetic Data in Two Mouse Models of Affective Disorders Assignment of functional impact on genetic data in two mouse models of affective disorders Dissertation Faculty of Biology Ludwig Maximilian University, Munich Regina Widner-Andrä December 14th 2011 Erstgutachter Prof. Dr. Rainer Landgraf Zweitgutachter Prof. Dr. Gisela Gruppe Tag der Abgabe: 14. Dezember 2011 Tag der mündlichen Prüfung: 8. Mai 2012 “Nothing in life is to be feared. It is only to be understood.” Marie Curie This dissertation is dedicated to my father, Gottfried Widner († February 2001). Table of contents Table of contents Table of contents ............................................................................................................. 1 1 Abstract .................................................................................................................... 7 2 Introduction .............................................................................................................. 9 2.1 The current concept of depression scale disorders ............................................ 9 2.2 Comorbidity of depression ............................................................................... 10 2.3 Generalized anxiety disorder ........................................................................... 11 2.4 Stress and reactivity of the hypothalamic-pituitary-adrenal axis ....................... 11 2.5 Genetics of depression and associated diseases ............................................ 13 2.6 Genome-wide association studies ................................................................... 14 2.7 Pharmacological therapy options for depression and associated diseases ...... 15 2.8 Psychopharmacotherapy of the future – a step towards personalized medicine? ................................................................................... 16 2.9 The use of animal models to unravel neurobiological underpinnings of depression and associated diseases ........................................................... 17 2.9.1 The HAB/LAB mouse model reflecting extremes in trait anxiety .................. 18 2.9.2 The stress reactivity mouse model .............................................................. 20 2.10 Technical progress in methods applied for the generation of transcriptome- and sequence-based genomic data ......................................... 22 2.11 Aim and scope of this study ............................................................................. 22 3 Animals, materials, and methods ............................................................................ 25 3.1 Experimental animals ...................................................................................... 25 3.1.1 Inbred mouse models .................................................................................. 25 3.1.2 Heterozygous Cofilin-1 knockout mice ........................................................ 25 3.1.3 C57BL/6 wild-type mice............................................................................... 26 3.1.4 CD-1 mice ................................................................................................... 26 3.2 Behavioral experiments ................................................................................... 26 3.2.1 Assessment of anxiety-related behavior ...................................................... 26 3.2.1.1 Open field test .................................................................................... 26 3.2.1.2 Elevated plus-maze test ..................................................................... 27 3.2.1.3 Dark-light box test .............................................................................. 28 3.2.2 Assessment of depression-like behavior ..................................................... 29 3.2.2.1 Tail suspension test ........................................................................... 29 3.2.2.2 Forced swim test ................................................................................ 30 3.2.3 Assessment of stress reactivity ................................................................... 31 3.2.4 Behavioral test batteries performed in this study ......................................... 32 1 Table of contents 3.2.4.1 Behavioral test battery conducted for phenotypic characterization of Cfl-1+/- vs. WT mice .............................................. 32 3.2.4.2 Behavioral test battery conducted for phenotypic characterization of an outbred population of CD-1 mice ............................................... 33 3.3 Sacrifice of animals ......................................................................................... 33 3.4 Dissection of embryos ..................................................................................... 34 3.5 Collection of brain and hippocampal tissue from embryonic and adult mice .... 34 3.6 Nucleic acid based methods ............................................................................ 34 3.6.1 RNA based methods ................................................................................... 34 3.6.1.1 Extraction of total RNA from hippocampal tissue ............................... 34 3.6.1.2 Control measures of RNA quality and determination of RNA concentration ............................................................................. 35 3.6.1.3 Reverse transcription of RNA into cDNA ............................................ 35 3.6.1.4 RNA amplification for array analysis .................................................. 36 3.6.1.5 Serial analysis of gene expression ..................................................... 36 3.6.2 DNA based methods ................................................................................... 37 3.6.2.1 DNA extraction from mouse tissue ..................................................... 37 3.6.2.2 Polymerase-chain reactions and gel electrophoresis ......................... 38 3.6.2.3 Gel electrophoresis ............................................................................ 39 3.6.2.4 Precipitation of cDNA ......................................................................... 39 3.6.2.5 Quantitative real-time PCR ................................................................ 40 3.6.2.6 Table of oligonucleotides ................................................................... 41 3.7 Protein based methods.................................................................................... 43 3.7.1 Mitochondrial proteomics ............................................................................ 43 3.7.1.1 Preparation of mitochondrial protein lysates ...................................... 43 3.7.1.2 Bradford assay .................................................................................. 44 3.7.1.3 Two-dimensional gel electrophoresis ................................................. 44 3.7.2 Cytochrome c immunoassay ....................................................................... 46 3.7.3 Cytochrome c oxidase staining ................................................................... 47 3.7.4 Quantification of plasma corticosterone via radioimmunoassays................. 48 3.8 Statistical and bioinformatical methods ............................................................ 49 3.8.1 Statistical analyses of microarray experiment ............................................. 49 3.8.1.1 Univariate analysis ............................................................................. 49 3.8.1.2 Multivariate analysis .......................................................................... 49 3.8.2 Statistical analyses of the SAGE experiment .............................................. 50 3.8.3 Cluster analyses of differentially regulated genes ....................................... 51 3.8.3.1 Database for annotation, visualization, and integrated discovery ....... 51 2 Table of contents 3.8.3.2 Gene ontology analyses ..................................................................... 51 3.8.4 High-density screening for single-nucleotide polymorphisms and detection of segmental copy number variants by means of the Jax Mouse Diversity Genotyping array ........................................................ 51 3.8.4.1 Detection of segmental copy number variation based on data from Jax Mouse Diversity Genotyping array ....................................... 52 3.8.5 Principle component analyses of phenotypic features ................................. 52 3.8.6 Calculation of association via WG-Permer .................................................. 53 3.8.7 Generation of CD-1 strain-specific haplotype map ...................................... 53 3.8.8 Statistical data analyses, graphical illustration, and common bioinformatical processes ............................................................................ 53 4 Results ................................................................................................................... 55 4.1 Gene expressional profiling of the SR mouse model........................................ 55 4.1.1 Differentially expressed genes according to univariate analysis of the microarray experiment ....................................................................... 55 4.1.2 Genes detected as differentially expressed in the SAGE experiment .......... 55 4.1.3 Overlapping pool of genes detected as differentially expressed in both gene expression profiling approaches ................................................. 55 4.1.4 Univariate vs. multivariate analysis of microarray data ................................ 56 4.1.5 Cluster
Load more

Recommended publications
  • Genome-Wide Analysis of Allele-Specific Expression Patterns in Seventeen Tissues of Korean Cattle (Hanwoo)
    animals Article Genome-Wide Analysis of Allele-Specific Expression Patterns in Seventeen Tissues of Korean Cattle (Hanwoo) Kyu-Sang Lim 1 , Sun-Sik Chang 2, Bong-Hwan Choi 3, Seung-Hwan Lee 4, Kyung-Tai Lee 3 , Han-Ha Chai 3, Jong-Eun Park 3 , Woncheoul Park 3 and Dajeong Lim 3,* 1 Department of Animal Science, Iowa State University, Ames, IA 50011, USA; [email protected] 2 Hanwoo Research Institute, National Institute of Animal Science, Rural Development Administration, Pyeongchang 25340, Korea; [email protected] 3 Animal Genomics and Bioinformatics Division, National Institute of Animal Science, Rural Development Administration, Wanju 55365, Korea; [email protected] (B.-H.C.); [email protected] (K.-T.L.); [email protected] (H.-H.C.); [email protected] (J.-E.P.); [email protected] (W.P.) 4 Division of Animal and Dairy Science, Chungnam National University, Daejeon 34134, Korea; [email protected] * Correspondence: [email protected] Received: 26 July 2019; Accepted: 23 September 2019; Published: 26 September 2019 Simple Summary: Allele-specific expression (ASE) is the biased allelic expression of genetic variants within the gene. Recently, the next-generation sequencing (NGS) technologies allowed us to detect ASE genes at a transcriptome-wide level. It is essential for the understanding of animal development, cellular programming, and the effect on their complexity because ASE shows developmental, tissue, or species-specific patterns. However, these aspects of ASE still have not been annotated well in farm animals and most studies were conducted mainly at the fetal stages. Hence, the current study focuses on detecting ASE genes in 17 tissues in adult cattle.
    [Show full text]
  • Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?
    Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement.
    [Show full text]
  • Supporting Information
    Supporting Information Collin et al. 10.1073/pnas.1220864110 SI Materials and Methods Mutation Analysis of PASK and ZNF408. The two candidate variants Human Subjects. A detailed clinical description of familial exudative that were left after linkage and exome analysis were analyzed in vitreoretinopathy (FEVR) family W05-215 has been reported family W05-215 with Sanger sequencing of exon 6 of proline- previously (1), and clinical details of the affected individuals alanine-rich ste20-related kinase (PASK) and exon 5 of zinc studied using next-generation sequencing (NGS) (III:5 and V:2) finger protein 408 (ZNF408). Primer sequences are available are summarized below. Eight affected individuals, three un- on request. The presence of these two changes in additional affected individuals, and three spouses participated in the ge- Dutch FEVR probands and 110 control individuals was ana- netic analysis (Fig. S1A). After linkage and exome sequencing lyzed via restriction fragment length polymorphism analysis, analysis were performed, three additional affected relatives using AflIII for the c.791dup change in PASK and SfaNI for the (IV:10, IV:11, and V:7) were sampled. Clinical details of the c.1363C>T change in ZNF408. All exons and intron–exon two individuals with FEVR from family W05-220 (IV:3 and boundaries of ZNF408 were amplified under standard PCR V:2) are summarized below. Furthermore, 132 individuals with conditions using primers that are available on request. Sanger FEVR (8 from The Netherlands, 64 from the United Kingdom, sequence analysis was performed with the ABI PRISM Big Dye 55 from Japan, and 5 from Switzerland) participated in this Terminator Cycle Sequencing V2.0 Ready Reaction Kit and study, along with 110 ethnically matched Dutch and 191 eth- an ABI PRISM 3730 DNA analyzer (Applied Biosystems).
    [Show full text]
  • Contribution of Heritability and Epigenetic Factors to Skeletal Muscle Mass Variation in United Kingdom Twins
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Queen Mary Research Online ORIGINAL ARTICLE Downloaded from https://academic.oup.com/jcem/article-abstract/101/6/2450/2804789 by St Bartholomew's & the Royal London School of Medicine and Denistry user on 29 October 2019 Contribution of Heritability and Epigenetic Factors to Skeletal Muscle Mass Variation in United Kingdom Twins Gregory Livshits, Fei Gao, Ida Malkin, Maria Needhamsen, Yudong Xia, Wei Yuan, Christopher G. Bell, Kirsten Ward, Yuan Liu, Jun Wang,* Jordana T. Bell,* and Tim D. Spector* Department of Twin Research and Genetic Epidemiology (G.L., M.N., W.Y., C.G.B., K.W., J.T.B., T.D.S.), King’s College London, London SE1 7EH, United Kingdom; Human Population Biology Research Unit (G.L., I.M.), Department of Anatomy and Anthropology, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel; Beijing Genomics Institute-Shenzhen (F.G., Y.X., Y.L., J.W.), Shenzhen 518083, China; King Abdulaziz University (J.W.), Jeddah 22254, Saudi Arabia; and Department of Biology (J.W.) and The Novo Nordisk Foundation Center for Basic Metabolic Research (J.W.), University of Copenhagen, Copenhagen DK-2200, Denmark Context: Skeletal muscle mass (SMM) is one of the major components of human body composition, with deviations from normal values often leading to sarcopenia. Objective: Our major aim was to conduct a genome-wide DNA methylation study in an attempt to identify potential genomic regions associated with SMM. Design: This was a mixed cross-sectional and longitudinal study.
    [Show full text]
  • Identification of Hub Genes Associated with Hepatocellular Carcinoma Prognosis by Bioinformatics Analysis
    Journal of Cancer Therapy, 2021, 12, 186-207 https://www.scirp.org/journal/jct ISSN Online: 2151-1942 ISSN Print: 2151-1934 Identification of Hub Genes Associated with Hepatocellular Carcinoma Prognosis by Bioinformatics Analysis Xi Zhang*, Xiaojun Luo*, Wenbin Liu, Ai Shen# Department of Hepatobiliary and Pancreatic Tumor Center, Chongqing University Cancer Hospital, Chongqing, China How to cite this paper: Zhang, X., Luo, Abstract X.J., Liu, W.B. and Shen, A. (2021) Identi- fication of Hub Genes Associated with He- Objective: This study aimed to identify hub genes that are associated with patocellular Carcinoma Prognosis by Bio- hepatocellular carcinoma (HCC) prognosis by bioinformatics analysis. Me- informatics Analysis. Journal of Cancer The- thods: Data were collected from the Gene Expression Omnibus (GEO) and rapy, 12, 186-207. https://doi.org/10.4236/jct.2021.124019 The Cancer Genome Atlas (TCGA) liver HCC datasets. The robust rank ag- gregation algorithm was used in integrating the data on differentially expressed Received: March 23, 2021 genes (DEGs). Online databases DAVID 6.8 and REACTOME were used for Accepted: April 26, 2021 gene ontology and pathway enrichment analysis. R software version 3.5.1, Cy- Published: April 29, 2021 toscape, and Kaplan-Meier plotter were used to identify hub genes. Results: Copyright © 2021 by author(s) and Six GEO datasets and the TCGA liver HCC dataset were included in this Scientific Research Publishing Inc. analysis. A total of 151 upregulated and 245 downregulated DEGs were iden- This work is licensed under the Creative tified. The upregulated DEGs most significantly enriched in the functional Commons Attribution International License (CC BY 4.0).
    [Show full text]
  • Genome-Wide Association Study in 2,046 Participants Drawn from a Population-Based Study
    www.nature.com/scientificreports OPEN Variants in NEB and RIF1 genes on chr2q23 are associated with skeletal muscle index in Koreans: genome‑wide association study Kyung Jae Yoon1,2,3,4, Youbin Yi1, Jong Geol Do1, Hyung‑Lae Kim5, Yong‑Taek Lee1,2* & Han‑Na Kim2,4* Although skeletal muscle plays a crucial role in metabolism and infuences aging and chronic diseases, little is known about the genetic variations with skeletal muscle, especially in the Asian population. We performed a genome‑wide association study in 2,046 participants drawn from a population‑based study. Appendicular skeletal muscle mass was estimated based on appendicular lean soft tissue measured with a multi‑frequency bioelectrical impedance analyzer and divided by height squared to derive the skeletal muscle index (SMI). After conducting quality control and imputing the genotypes, we analyzed 6,391,983 autosomal SNPs. A genome‑wide signifcant association was found for the intronic variant rs138684936 in the NEB and RIF1 genes (β = 0.217, p = 6.83 × 10–9). These two genes are next to each other and are partially overlapped on chr2q23. We conducted extensive functional annotations to gain insight into the directional biological implication of signifcant genetic variants. A gene‑based analysis identifed the signifcant TNFSF9 gene and confrmed the suggestive association of the NEB gene. Pathway analyses showed the signifcant association of regulation of multicellular organism growth gene‑set and the suggestive associations of pathways related to skeletal system development or skeleton morphogenesis with SMI. In conclusion, we identifed a new genetic locus on chromosome 2 for SMI with genome‑wide signifcance.
    [Show full text]
  • Gene Expression Profiling in Hepatocellular Carcinoma: Upregulation of Genes in Amplified Chromosome Regions
    Modern Pathology (2008) 21, 505–516 & 2008 USCAP, Inc All rights reserved 0893-3952/08 $30.00 www.modernpathology.org Gene expression profiling in hepatocellular carcinoma: upregulation of genes in amplified chromosome regions Britta Skawran1, Doris Steinemann1, Anja Weigmann1, Peer Flemming2, Thomas Becker3, Jakobus Flik4, Hans Kreipe2, Brigitte Schlegelberger1 and Ludwig Wilkens1,2 1Institute of Cell and Molecular Pathology, Hannover Medical School, Hannover, Germany; 2Institute of Pathology, Hannover Medical School, Hannover, Germany; 3Department of Visceral and Transplantation Surgery, Hannover Medical School, Hannover, Germany and 4Institute of Virology, Hannover Medical School, Hannover, Germany Cytogenetics of hepatocellular carcinoma and adenoma have revealed gains of chromosome 1q as a significant differentiating factor. However, no studies are available comparing these amplification events with gene expression. Therefore, gene expression profiling was performed on tumours cytogenetically well characterized by array-based comparative genomic hybridisation. For this approach analysis was carried out on 24 hepatocellular carcinoma and 8 hepatocellular adenoma cytogenetically characterised by array-based comparative genomic hybridisation. Expression profiles of mRNA were determined using a genome-wide microarray containing 43 000 spots. Hierarchical clustering analysis branched all hepatocellular adenoma from hepatocellular carcinoma. Significance analysis of microarray demonstrated 722 dysregulated genes in hepatocellular carcinoma. Gene set enrichment analysis detected groups of upregulated genes located in chromosome bands 1q22–42 seen also as the most frequently gained regions by comparative genomic hybridisation. Comparison of significance analysis of microarray and gene set enrichment analysis narrowed down the number of dysregulated genes to 18, with 7 genes localised on 1q22 (SCAMP3, IQGAP3, PYGO2, GPATC4, ASH1L, APOA1BP, and CCT3). In hepatocellular adenoma 26 genes in bands 11p15, 11q12, and 12p13 were upregulated.
    [Show full text]
  • Genome-Wide Loss of Heterozygosity and Copy Number Analysis in Melanoma Using High-Density Single-Nucleotide Polymorphism Arrays Mitchell Stark and Nicholas Hayward
    Research Article Genome-Wide Loss of Heterozygosity and Copy Number Analysis in Melanoma Using High-Density Single-Nucleotide Polymorphism Arrays Mitchell Stark and Nicholas Hayward Oncogenomics Laboratory, Queensland Institute of Medical Research, Herston, Queensland, Australia Abstract Conventional chromosome-based comparative genomic hybridiza- Although a number of genes related to melanoma develop- tion (CGH) has been used to study melanomas of different subtypes ment have been identified through candidate gene screening (4–7), and a limited number of studies have looked at array-based approaches, few studies have attempted to conduct such CGH (aCGH) in murine (8), swine (9), and human (2, 10) mela- analyses on a genome-wide scale. Here we use Illumina 317K nomas. The latter studies have led to the identification of CDK4, whole-genome single-nucleotide polymorphism arrays to CCND1, and KIT amplifications in a subset of malignant melanoma. define a comprehensive allelotype of melanoma based on loss Although aCGH is adequate for detecting high level amplifica- of heterozygosity (LOH) and copy number changes in a panel tions and homozygous deletions (HD), it grossly underestimates of 76 melanoma cell lines. In keeping with previous reports, the level of LOH (11). In contrast, the use of high-density single- we found frequent LOH on chromosome arms 9p (72%), 10p nucleotide polymorphism (SNP) arrays has proved to be a superior approach to defining genome-wide LOH and copy number changes (55%), 10q (55%), 9q (49%), 6q (43%), 11q (43%), and 17p (41%). Tumor suppressor genes (TSGs) can be identified in a wide range of tumor types (e.g., refs.
    [Show full text]
  • Gene Modules Associated with Human Diseases Revealed by Network
    bioRxiv preprint doi: https://doi.org/10.1101/598151; this version posted June 15, 2019. 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. Gene modules associated with human diseases revealed by network analysis Shisong Ma1,2*, Jiazhen Gong1†, Wanzhu Zuo1†, Haiying Geng1, Yu Zhang1, Meng Wang1, Ershang Han1, Jing Peng1, Yuzhou Wang1, Yifan Wang1, Yanyan Chen1 1. Hefei National Laboratory for Physical Sciences at the Microscale, School of Life Sciences, University of Science and Technology of China, Hefei, Anhui 230027, China 2. School of Data Science, University of Science and Technology of China, Hefei, Anhui 230027, China * To whom correspondence should be addressed. Email: [email protected] † These authors contribute equally. 1 bioRxiv preprint doi: https://doi.org/10.1101/598151; this version posted June 15, 2019. 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. ABSTRACT Despite many genes associated with human diseases have been identified, disease mechanisms often remain elusive due to the lack of understanding how disease genes are connected functionally at pathways level. Within biological networks, disease genes likely map to modules whose identification facilitates etiology studies but remains challenging. We describe a systematic approach to identify disease-associated gene modules.
    [Show full text]
  • Tobacco Smoking Induces Metabolic Reprogramming of Renal Cell Carcinoma
    Tobacco smoking induces metabolic reprogramming of renal cell carcinoma James Reigle, … , Jarek Meller, Maria F. Czyzyk-Krzeska J Clin Invest. 2020. https://doi.org/10.1172/JCI140522. Clinical Medicine In-Press Preview Metabolism Oncology Graphical abstract Find the latest version: https://jci.me/140522/pdf September 10, 2020 Tobacco smoking induces metabolic reprogramming of renal cell carcinoma James Reigle1,2,3*, Dina Secic1,4*, Jacek Biesiada5*, Collin Wetzel1,6*, Behrouz Shamsaei5, Johnson Chu1, Yuanwei Zang1,7, Xiang Zhang8, Nicholas J. Talbot1, Megan E. Bischoff1, Yongzhen Zhang1,7, Charuhas V. Thakar9,10, Krishnanath Gaitonde9,11, Abhinav Sidana11, Hai Bui10, John T. Cunningham1, Qing Zhang12, Laura S. Schmidt13,14, W. Marston Linehan13, Mario Medvedovic2,5, David R. Plas1, Julio A. Landero Figueroa4,15#, Jarek Meller2,3,5,15,16#, Maria F. Czyzyk-Krzeska1,10,15# 1Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA 2Department of Biomedical Informatics, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA 3Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA 4Agilent Metallomics Center of the Americas, Department of Chemistry, University of Cincinnati College of Arts and Science, Cincinnati, OH 45221, USA 5Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA 6Rieveschl Laboratories for Mass
    [Show full text]
  • GLYAT (N-12): Sc-83833
    SAN TA C RUZ BI OTEC HNOL OG Y, INC . GLYAT (N-12): sc-83833 BACKGROUND PRODUCT GLYAT (glycine-N-acyltransferase), also known as GAT, CAT, HRP-1(CLP), Each vial contains 200 µg IgG in 1.0 ml of PBS with < 0.1% sodium azide Acyl-CoA:glycine N-acyltransferase (AAc) or ACGNAT, is a 296 amino acid and 0.1% gelatin. mitochondrial acyltransferase that conjugates glycine to acyl-CoA sub strates. Blocking peptide available for competition studies, sc-83833 P, (100 µg Existing as two alternatively spliced isoforms, GLYAT may participate in peptide in 0.5 ml PBS containing < 0.1% sodium azide and 0.2% BSA). detoxification of endogenous and xenobiotic acyl-CoA and is expressed in human liver at peak levels from 18 months to 40 years. Children under seven APPLICATIONS months express only five to forty percent of liver GLYAT specific activity, thereby functioning with a lower ability to detoxify their system of certain GLYAT (N-12) is recommended for detection of GLYAT of human origin drugs and xenobiotics. A member of the glycine N-acyltransferase family, by Western Blotting (starting dilution 1:200, dilution range 1:100-1:1000), GLYAT is encoded by a gene located on human chromosome 11, which hous es immunoprecipitation [1-2 µg per 100-500 µg of total protein (1 ml of cell over 1,400 genes and comprises nearly 4% of the human genome. Jervell lysate)], immunofluorescence (starting dilution 1:50, dilution range 1:50- and Lange-Nielsen syndrome, Jacobsen syndrome, Niemann-Pick disease, 1:500) and solid phase ELISA (starting dilution 1:30, dilution range 1:30- hereditary angioedema and Smith-Lemli-Opitz syndrome are associated with 1:3000).
    [Show full text]
  • Genetic Variations in Connection
    Genetic variations in connection Citation for published version (APA): Cirillo, E. (2019). Genetic variations in connection: understanding the effects of Single Nucleotide Polymorphisms in their biological context. ProefschriftMaken Maastricht. https://doi.org/10.26481/dis.20190118ec Document status and date: Published: 01/01/2019 DOI: 10.26481/dis.20190118ec Document Version: Publisher's PDF, also known as Version of record Please check the document version of this publication: • A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.
    [Show full text]