Mouse Glmn Conditional Knockout Project (CRISPR/Cas9)

Total Page:16

File Type:pdf, Size:1020Kb

Mouse Glmn Conditional Knockout Project (CRISPR/Cas9) https://www.alphaknockout.com Mouse Glmn Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Glmn conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Glmn gene (NCBI Reference Sequence: NM_133248 ; Ensembl: ENSMUSG00000029276 ) is located on Mouse chromosome 5. 19 exons are identified, with the ATG start codon in exon 2 and the TAA stop codon in exon 19 (Transcript: ENSMUST00000078021). Exon 6 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Glmn gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-326I10 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Mice homozygous for a gene trap allele exhibit complete embryonic lethality during organogenesis associated with growth retardation, delayed neural tube closure, incomplete embryo turning, pericardial effusion, disorganized yolk sac vascular plexus and head mesenchyme hypocellularity. Exon 6 starts from about 21.98% of the coding region. The knockout of Exon 6 will result in frameshift of the gene. The size of intron 5 for 5'-loxP site insertion: 1309 bp, and the size of intron 6 for 3'-loxP site insertion: 1302 bp. The size of effective cKO region: ~738 bp. The cKO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 5 6 7 19 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Glmn Homology arm cKO region loxP site Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. No significant tandem repeat is found in the dot plot matrix. So this region is suitable for PCR screening or sequencing analysis. Overview of the GC Content Distribution Window size: 300 bp Sequence 12 Summary: Full Length(7238bp) | A(30.35% 2197) | C(20.39% 1476) | T(27.37% 1981) | G(21.88% 1584) Note: The sequence of homologous arms and cKO region is analyzed to determine the GC content. No significant high GC-content region is found. So this region is suitable for PCR screening or sequencing analysis. Page 3 of 8 https://www.alphaknockout.com BLAT Search Results (up) QUERY SCORE START END QSIZE IDENTITY CHROM STRAND START END SPAN ----------------------------------------------------------------------------------------------- browser details YourSeq 3000 1 3000 3000 100.0% chr5 - 107574173 107577172 3000 browser details YourSeq 1535 1 1571 3000 99.0% chr14 + 120785586 120787159 1574 browser details YourSeq 1534 1 1575 3000 98.8% chr11 + 8325097 8326671 1575 browser details YourSeq 1530 1 1570 3000 98.8% chr16 - 8590493 8592062 1570 browser details YourSeq 1529 1 1569 3000 98.6% chr13 - 30273538 30275105 1568 browser details YourSeq 1529 1 1567 3000 98.7% chr11 - 93427768 93429333 1566 browser details YourSeq 1527 1 1571 3000 98.7% chr2 - 70072550 70074123 1574 browser details YourSeq 1527 1 1571 3000 98.6% chr14 - 76570907 76572477 1571 browser details YourSeq 1525 1 1561 3000 98.9% chr9 - 89321380 89322940 1561 browser details YourSeq 1525 1 1569 3000 98.6% chr9 - 37881875 37883443 1569 browser details YourSeq 1525 1 1574 3000 98.6% chr3 - 8654003 8655580 1578 browser details YourSeq 1525 1 1574 3000 98.5% chr3 + 158573588 158575162 1575 browser details YourSeq 1523 1 1571 3000 98.5% chr5 - 30693469 30695039 1571 browser details YourSeq 1523 1 1574 3000 98.5% chr3 - 97143338 97144911 1574 browser details YourSeq 1523 1 1572 3000 98.3% chr1 - 84967936 84969505 1570 browser details YourSeq 1523 1 1574 3000 98.5% chr1 - 35042749 35044322 1574 browser details YourSeq 1523 1 1572 3000 98.5% chr1 + 79688886 79690458 1573 browser details YourSeq 1522 1 1574 3000 98.5% chr11 - 12772475 12774057 1583 browser details YourSeq 1522 1 1574 3000 98.5% chr4 + 88566757 88568333 1577 browser details YourSeq 1522 1 1570 3000 98.5% chr2 + 17474072 17475641 1570 Note: The 3000 bp section upstream of Exon 6 is BLAT searched against the genome. No significant similarity is found. BLAT Search Results (down) QUERY SCORE START END QSIZE IDENTITY CHROM STRAND START END SPAN ----------------------------------------------------------------------------------------------- browser details YourSeq 3000 1 3000 3000 100.0% chr5 - 107570435 107573434 3000 browser details YourSeq 190 2177 2864 3000 88.3% chr12 + 104799576 104907315 107740 browser details YourSeq 163 2611 2913 3000 86.4% chr19 + 37709742 37710050 309 browser details YourSeq 158 2595 2893 3000 83.0% chr17 - 83053910 83054222 313 browser details YourSeq 155 2620 2944 3000 89.5% chr12 + 13014984 13015308 325 browser details YourSeq 146 2635 2913 3000 84.5% chr4 - 117956126 117956401 276 browser details YourSeq 139 2635 2913 3000 81.2% chr2 + 165335620 165335925 306 browser details YourSeq 139 2595 2944 3000 84.2% chr11 + 61379476 61379814 339 browser details YourSeq 135 2221 2862 3000 87.7% chr18 - 24175261 24470380 295120 browser details YourSeq 133 2663 2942 3000 89.9% chr2 - 131677275 131677594 320 browser details YourSeq 132 2663 2955 3000 87.8% chr18 - 60510187 60510809 623 browser details YourSeq 132 2620 2890 3000 88.9% chr1 + 13676625 13676920 296 browser details YourSeq 131 2663 2944 3000 88.7% chr9 + 106534205 106534508 304 browser details YourSeq 130 2595 2865 3000 82.9% chr9 - 55249906 55250305 400 browser details YourSeq 130 2608 2944 3000 84.0% chr14 - 121372798 121373136 339 browser details YourSeq 129 2698 2946 3000 92.2% chr1 + 36713757 36714027 271 browser details YourSeq 127 2642 2940 3000 88.3% chr15 + 87985046 87985343 298 browser details YourSeq 122 2672 2913 3000 90.7% chr8 + 4366911 4367186 276 browser details YourSeq 121 2621 2863 3000 93.0% chr3 - 56091952 56244146 152195 browser details YourSeq 121 2676 2939 3000 89.6% chr10 + 42918431 42918982 552 Note: The 3000 bp section downstream of Exon 6 is BLAT searched against the genome. No significant similarity is found. Page 4 of 8 https://www.alphaknockout.com Gene and protein information: Glmn glomulin, FKBP associated protein [ Mus musculus (house mouse) ] Gene ID: 170823, updated on 12-Aug-2019 Gene summary Official Symbol Glmn provided by MGI Official Full Name glomulin, FKBP associated protein provided by MGI Primary source MGI:MGI:2141180 See related Ensembl:ENSMUSG00000029276 Gene type protein coding RefSeq status VALIDATED Organism Mus musculus Lineage Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Eutheria; Euarchontoglires; Glires; Rodentia; Myomorpha; Muroidea; Muridae; Murinae; Mus; Mus Also known as Fap48; Fap68; AW227515; 9330160J16Rik Expression Broad expression in CNS E11.5 (RPKM 4.4), CNS E18 (RPKM 3.9) and 20 other tissues See more Orthologs human all Genomic context Location: 5; 5 E5 See Glmn in Genome Data Viewer Exon count: 20 Annotation release Status Assembly Chr Location 108 current GRCm38.p6 (GCF_000001635.26) 5 NC_000071.6 (107548962..107597888, complement) Build 37.2 previous assembly MGSCv37 (GCF_000001635.18) 5 NC_000071.5 (107977986..108026907, complement) Chromosome 5 - NC_000071.6 Page 5 of 8 https://www.alphaknockout.com Transcript information: This gene has 8 transcripts Gene: Glmn ENSMUSG00000029276 Description glomulin, FKBP associated protein [Source:MGI Symbol;Acc:MGI:2141180] Gene Synonyms 9330160J16Rik, Fap48, Fap68 Location Chromosome 5: 107,548,967-107,597,888 reverse strand. GRCm38:CM000998.2 About this gene This gene has 8 transcripts (splice variants), 261 orthologues, is a member of 1 Ensembl protein family and is associated with 9 phenotypes. Transcripts Name Transcript ID bp Protein Translation ID Biotype CCDS UniProt Flags Glmn- ENSMUST00000078021.12 2015 596aa ENSMUSP00000077168.6 Protein coding CCDS19505 Q8BZM1 TSL:1 201 GENCODE basic APPRIS P1 Glmn- ENSMUST00000082121.8 1945 596aa ENSMUSP00000080766.2 Protein coding CCDS19505 Q8BZM1 TSL:1 202 GENCODE basic APPRIS P1 Glmn- ENSMUST00000100949.9 1759 532aa ENSMUSP00000098509.3 Protein coding CCDS51587 Q3T9A5 TSL:1 203 GENCODE basic Glmn- ENSMUST00000124140.1 593 100aa ENSMUSP00000123224.1 Protein coding - D3Z0L3 CDS 3' 204 incomplete TSL:5 Glmn- ENSMUST00000124546.7 2042 97aa ENSMUSP00000122129.1 Nonsense mediated - D6RGR3 TSL:5 205 decay Glmn- ENSMUST00000137939.7 676 No - Retained intron - - TSL:2 206 protein Glmn- ENSMUST00000148505.7 815 No - lncRNA - - TSL:5 208 protein Glmn- ENSMUST00000143113.1 417 No - lncRNA - - TSL:5 207 protein Page 6 of 8 https://www.alphaknockout.com 68.92 kb Forward strand 107.54Mb 107.56Mb 107.58Mb 107.60Mb Genes Gm42669-201 >protein coding Rpap2-202 >protein coding (Comprehensive set... Gm42669-202 >protein coding Rpap2-203 >protein coding 1700028K03Rik-201 >protein coding Rpap2-204 >protein coding 1700028K03Rik-206 >protein coding Rpap2-207 >lncRNA 1700028K03Rik-205 >protein coding Rpap2-201 >protein coding 1700028K03Rik-204 >lncRNA Rpap2-205 >protein coding 1700028K03Rik-202 >protein coding Rpap2-208 >protein coding 1700028K03Rik-203 >retained intron Rpap2-206 >protein coding Contigs AC134411.7 > < AC117574.7 Genes (Comprehensive set... < Glmn-201protein coding < Glmn-203protein coding < Glmn-206retained intron < Glmn-208lncRNA < Glmn-202protein
Recommended publications
  • Pathway-Based Genome-Wide Association Analysis of Coronary Heart Disease Identifies Biologically Important Gene Sets
    European Journal of Human Genetics (2012) 20, 1168–1173 & 2012 Macmillan Publishers Limited All rights reserved 1018-4813/12 www.nature.com/ejhg ARTICLE Pathway-based genome-wide association analysis of coronary heart disease identifies biologically important gene sets Lisa de las Fuentes1,4, Wei Yang2,4, Victor G Da´vila-Roma´n1 and C Charles Gu*,2,3 Genome-wide association (GWA) studies of complex diseases including coronary heart disease (CHD) challenge investigators attempting to identify relevant genetic variants among hundreds of thousands of markers being tested. A selection strategy based purely on statistical significance will result in many false negative findings after adjustment for multiple testing. Thus, an integrated analysis using information from the learned genetic pathways, molecular functions, and biological processes is desirable. In this study, we applied a customized method, variable set enrichment analysis (VSEA), to the Framingham Heart Study data (404 467 variants, n ¼ 6421) to evaluate enrichment of genetic association in 1395 gene sets for their contribution to CHD. We identified 25 gene sets with nominal Po0.01; at least four sets are previously known for their roles in CHD: vascular genesis (GO:0001570), fatty-acid biosynthetic process (GO:0006633), fatty-acid metabolic process (GO:0006631), and glycerolipid metabolic process (GO:0046486). Although the four gene sets include 170 genes, only three of the genes contain a variant ranked among the top 100 in single-variant association tests of the 404 467 variants tested. Significant enrichment for novel gene sets less known for their importance to CHD were also identified: Rac 1 cell-motility signaling pathway (h_rac1 Pathway, Po0.001) and sulfur amino-acid metabolic process (GO:0000096, Po0.001).
    [Show full text]
  • Supporting Information
    Supporting Information Pouryahya et al. SI Text Table S1 presents genes with the highest absolute value of Ricci curvature. We expect these genes to have significant contribution to the network’s robustness. Notably, the top two genes are TP53 (tumor protein 53) and YWHAG gene. TP53, also known as p53, it is a well known tumor suppressor gene known as the "guardian of the genome“ given the essential role it plays in genetic stability and prevention of cancer formation (1, 2). Mutations in this gene play a role in all stages of malignant transformation including tumor initiation, promotion, aggressiveness, and metastasis (3). Mutations of this gene are present in more than 50% of human cancers, making it the most common genetic event in human cancer (4, 5). Namely, p53 mutations play roles in leukemia, breast cancer, CNS cancers, and lung cancers, among many others (6–9). The YWHAG gene encodes the 14-3-3 protein gamma, a member of the 14-3-3 family proteins which are involved in many biological processes including signal transduction regulation, cell cycle pro- gression, apoptosis, cell adhesion and migration (10, 11). Notably, increased expression of 14-3-3 family proteins, including protein gamma, have been observed in a number of human cancers including lung and colorectal cancers, among others, suggesting a potential role as tumor oncogenes (12, 13). Furthermore, there is evidence that loss Fig. S1. The histogram of scalar Ricci curvature of 8240 genes. Most of the genes have negative scalar Ricci curvature (75%). TP53 and YWHAG have notably low of p53 function may result in upregulation of 14-3-3γ in lung cancer Ricci curvatures.
    [Show full text]
  • Emery and Rimoin's Principles and Practice Of
    9 Disorders of the Venous System Pascal Brouillard,1 Nisha Limaye,1 Laurence M. Boon,1,2 Miikka Vikkula1,3 1Human Molecular Genetics, de Duve Institute, Université catholique de Louvain, Brussels, Belgium, 2Center for Vascular Anomalies, Division of Plastic Surgery, Cliniques Universitaires St-Luc, Université catholique de Louvain, Brussels, Belgium, 3Walloon Excellence in Lifesciences and Biotechnology (WELBIO), Université catholique de Louvain, Brussels, Belgium 9.1 INTRODUCTION hemangioma) and more slow-growing vascular malfor- mations. The latter are subcategorized according to the The vasculature is the first organ system to develop during type(s) of vessel(s) altered [5–7] into capillary, venous, embryogenesis, delivering nutrients, growth factors, and arteriovenous, lymphatic, and combined malformations. oxygen to tissues and removing wastes. It is made up of four major types of vessels: arteries, capillaries, veins, and lymphatic vessels, all of which have a single layer of endo- 9.2 THE VENOUS SYSTEM thelial cells (ECs) forming the innermost layer. In blood Veins collect CO2-rich blood from the capillary net- vessels, the endothelial tubes are supported by a layer of work and contain about 75%–80% of the total volume of vascular smooth muscle cells (vSMCs) and/or pericytes blood in the body. They have larger lumens than arteries, (together called mural cells) of variable thickness. A base- with thinner, less muscular walls. Venous flow is passive, ment membrane separates the endothelial and vSMC essentially mediated by physical movements of the body layers, with an extracellular matrix (ECM) of fibrous and and the aspirating effect exerted by the heart. The pres- elastic proteins and carbohydrate polymers forming the ence of valves ensures correct orientation of blood flow.
    [Show full text]
  • Genetic and Chemical Modifiers of EGFR Dependence in Non- Small Cell Lung Cancer
    Genetic and Chemical Modifiers of EGFR Dependence in Non- Small Cell Lung Cancer The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Sharifnia, Tanaz. 2014. Genetic and Chemical Modifiers of EGFR Dependence in Non-Small Cell Lung Cancer. Doctoral dissertation, Harvard University. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:11745725 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Genetic and Chemical Modifiers of EGFR Dependence in Non-Small Cell Lung Cancer A dissertation presented by Tanaz Sharifnia to The Division of Medical Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Biological and Biomedical Sciences Harvard University Cambridge, Massachusetts December 2013 © 2013 Tanaz Sharifnia All rights reserved. Dissertation Advisor: Professor Matthew Meyerson Tanaz Sharifnia Genetic and Chemical Modifiers of EGFR Dependence in Non-Small Cell Lung Cancer ABSTRACT The term ‘oncogene addiction’ has been used to describe the phenomenon whereby tumor cells exhibit singular reliance on an oncogene or oncogenic pathway for their survival, despite the accumulation of multiple genetic lesions. In non-small cell lung cancer (NSCLC), this principle is perhaps best exemplified with the finding that epidermal growth factor receptor (EGFR) mutations predict response to EGFR-targeted therapies and thus represent a dependency in the subset of tumors harboring these alterations.
    [Show full text]
  • Genetic Syndromes with Vascular Malformations – Update on Molecular Background and Diagnostics
    State of the art paper Genetics Genetic syndromes with vascular malformations – update on molecular background and diagnostics Adam Ustaszewski1,2, Joanna Janowska-Głowacka2, Katarzyna Wołyńska2, Anna Pietrzak3, Magdalena Badura-Stronka2 1Institute of Human Genetics, Polish Academy of Sciences, Poznan, Poland Corresponding author: 2Department of Medical Genetics, Poznan University of Medical Sciences, Poznan, Adam Ustaszewski Poland Institute of Human Genetics 3Department of Neurology, Poznan University of Medical Sciences, Poznan, Poland Polish Academy of Sciences 32 Strzeszynska St Submitted: 19 April 2018; Accepted: 9 September 2018 60-479 Poznan, Poland Online publication: 25 February 2020 Phone: +48 61 65 79 223 E-mail: adam.ustaszewski@ Arch Med Sci 2021; 17 (4): 965–991 igcz.poznan.pl DOI: https://doi.org/10.5114/aoms.2020.93260 Copyright © 2020 Termedia & Banach Abstract Vascular malformations are present in a great variety of congenital syn- dromes, either as the predominant or additional feature. They pose a major challenge to the clinician: due to significant phenotype overlap, a precise diagnosis is often difficult to obtain, some of the malformations carry a risk of life threatening complications and, for many entities, treatment is not well established. To facilitate their recognition and aid in differentiation, we present a selection of notable congenital disorders of vascular system development, distinguishing between the heritable germinal and sporadic somatic mutations as their causes. Clinical features, genetic background and comprehensible description of molecular mechanisms is provided for each entity. Key words: arteriovenous malformation, vascular malformation, capillary malformation, venous malformation, arterial malformation, lymphatic malformation. Introduction Congenital vascular malformations (VMs) are disorders of vascular architecture development.
    [Show full text]
  • The Effect of Phototherapy on Cancer Predisposition Genes of Diabetic and Normal Human Skin Fibroblasts
    Hindawi BioMed Research International Volume 2017, Article ID 7604861, 9 pages https://doi.org/10.1155/2017/7604861 Research Article The Effect of Phototherapy on Cancer Predisposition Genes of Diabetic and Normal Human Skin Fibroblasts Pongsathorn Chotikasemsri,1 Boonsin Tangtrakulwanich,2 and Surasak Sangkhathat3 1 Biomedical Engineering Institute, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand 2Department of Orthopedic Surgery and Physical Medicine, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand 3Department of Surgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, Thailand Correspondence should be addressed to Pongsathorn Chotikasemsri; [email protected] Received 3 October 2016; Accepted 19 February 2017; Published 12 March 2017 Academic Editor: Tokuya Omi Copyright © 2017 Pongsathorn Chotikasemsri et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The purpose of this study was to investigate whether LED light at different wavelengths affects the expression profile of 143cancer predisposition genes in both diabetic and normal human fibroblasts. In this study, both diabetic and normal fibroblast cell lines were 2 cultured and irradiated with red (635 nm), green (520 nm), and blue (465 nm) LED light for 10 minutes at 0.67 J/cm each. After that, mRNA from all cell lines was extracted for microarray analysis. We found that green light activates EPHB2, KIT, ANTXR2, ESCO2, MSR1, EXT1, TSC1, KIT, NF1, BUB1B, FANCD2, EPCAM, FANCD2, NF, DIS3L2, and RET in normal fibroblast cells, while blue and red light can upregulate RUNX1, PDGFRA, EHBP1, GPC3, AXIN2, KDR, GLMN, MSMB, EPHB2, MSR1, KIT, FANCD2, BMPR1A, BUB1B, PDE11A, and RET.
    [Show full text]
  • HSP90-Incorporating Chaperome Networks As Biosensor for Disease-Related Pathways in Patient- Specific Midbrain Dopamine Neurons
    ARTICLE DOI: 10.1038/s41467-018-06486-6 OPEN HSP90-incorporating chaperome networks as biosensor for disease-related pathways in patient- specific midbrain dopamine neurons Sarah Kishinevsky1,2,3,4, Tai Wang3, Anna Rodina3, Sun Young Chung1,2, Chao Xu3, John Philip5, Tony Taldone3, Suhasini Joshi3, Mary L. Alpaugh3,14, Alexander Bolaender3, Simon Gutbier6, Davinder Sandhu7, Faranak Fattahi1,2, Bastian Zimmer1,2, Smit K. Shah3, Elizabeth Chang5, Carmen Inda3,15, John Koren 3rd3,16, Nathalie G. Saurat1,2, Marcel Leist 6, Steven S. Gross7, Venkatraman E. Seshan8, Christine Klein9, Mark J. Tomishima1,2,10, Hediye Erdjument-Bromage11,12, Thomas A. Neubert 11,12, Ronald C. Henrickson5, 1234567890():,; Gabriela Chiosis3,13 & Lorenz Studer1,2 Environmental and genetic risk factors contribute to Parkinson’s Disease (PD) pathogenesis and the associated midbrain dopamine (mDA) neuron loss. Here, we identify early PD pathogenic events by developing methodology that utilizes recent innovations in human pluripotent stem cells (hPSC) and chemical sensors of HSP90-incorporating chaperome networks. We show that events triggered by PD-related genetic or toxic stimuli alter the neuronal proteome, thereby altering the stress-specific chaperome networks, which produce changes detected by chemical sensors. Through this method we identify STAT3 and NF-κB signaling activation as examples of genetic stress, and phospho-tyrosine hydroxylase (TH) activation as an example of toxic stress-induced pathways in PD neurons. Importantly, pharmacological inhibition of the stress chaperome network reversed abnormal phospho- STAT3 signaling and phospho-TH-related dopamine levels and rescued PD neuron viability. The use of chemical sensors of chaperome networks on hPSC-derived lineages may present a general strategy to identify molecular events associated with neurodegenerative diseases.
    [Show full text]
  • Combinatorial Immune and Stress Response, Cytoskeleton and Signal
    Journal of Hazardous Materials 378 (2019) 120778 Contents lists available at ScienceDirect Journal of Hazardous Materials journal homepage: www.elsevier.com/locate/jhazmat Combinatorial immune and stress response, cytoskeleton and signal transduction effects of graphene and triphenyl phosphate (TPP) in mussel T Mytilus galloprovincialis ⁎ ⁎ Xiangjing Menga,c, Fei Lia, , Xiaoqing Wanga,c, Jialin Liua, Chenglong Jia,b, Huifeng Wua,b, a CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research (YIC), Chinese Academy of Sciences (CAS), Shandong Key Laboratory of Coastal Environmental Processes, YICCAS, Yantai 264003, PR China b Laboratory for Marine Fisheries Science and Food Production Processes, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, PR China c University of Chinese Academy of Sciences, Beijing 100049, PR China GRAPHICAL ABSTRACT ARTICLE INFO ABSTRACT Keywords: Owing to its unique surface properties, graphene can absorb environmental pollutants, thereby affecting their Joint effects environmental behavior. Triphenyl phosphate (TPP) is a highly produced flame retardant. However, the toxi- Graphene cities of graphene and its combinations with contaminants remain largely unexplored. In this work, we in- Triphenyl phosphate (TPP) vestigated the toxicological effects of graphene and TPP to mussel Mytilus galloprovincialis. Results indicated that Toxicity graphene could damage the digestive gland tissues, but no significant changes were found in
    [Show full text]
  • Genomic Approach in Idiopathic Intellectual Disability Maria De Fátima E Costa Torres
    ESTUDOS DE 8 01 PDPGM 2 CICLO Genomic approach in idiopathic intellectual disability Maria de Fátima e Costa Torres D Autor. Maria de Fátima e Costa Torres D.ICBAS 2018 Genomic approach in idiopathic intellectual disability Genomic approach in idiopathic intellectual disability Maria de Fátima e Costa Torres SEDE ADMINISTRATIVA INSTITUTO DE CIÊNCIAS BIOMÉDICAS ABEL SALAZAR FACULDADE DE MEDICINA MARIA DE FÁTIMA E COSTA TORRES GENOMIC APPROACH IN IDIOPATHIC INTELLECTUAL DISABILITY Tese de Candidatura ao grau de Doutor em Patologia e Genética Molecular, submetida ao Instituto de Ciências Biomédicas Abel Salazar da Universidade do Porto Orientadora – Doutora Patrícia Espinheira de Sá Maciel Categoria – Professora Associada Afiliação – Escola de Medicina e Ciências da Saúde da Universidade do Minho Coorientadora – Doutora Maria da Purificação Valenzuela Sampaio Tavares Categoria – Professora Catedrática Afiliação – Faculdade de Medicina Dentária da Universidade do Porto Coorientadora – Doutora Filipa Abreu Gomes de Carvalho Categoria – Professora Auxiliar com Agregação Afiliação – Faculdade de Medicina da Universidade do Porto DECLARAÇÃO Dissertação/Tese Identificação do autor Nome completo _Maria de Fátima e Costa Torres_ N.º de identificação civil _07718822 N.º de estudante __ 198600524___ Email institucional [email protected] OU: [email protected] _ Email alternativo [email protected] _ Tlf/Tlm _918197020_ Ciclo de estudos (Mestrado/Doutoramento) _Patologia e Genética Molecular__ Faculdade/Instituto _Instituto de Ciências
    [Show full text]
  • CREB-Dependent Transcription in Astrocytes: Signalling Pathways, Gene Profiles and Neuroprotective Role in Brain Injury
    CREB-dependent transcription in astrocytes: signalling pathways, gene profiles and neuroprotective role in brain injury. Tesis doctoral Luis Pardo Fernández Bellaterra, Septiembre 2015 Instituto de Neurociencias Departamento de Bioquímica i Biologia Molecular Unidad de Bioquímica y Biologia Molecular Facultad de Medicina CREB-dependent transcription in astrocytes: signalling pathways, gene profiles and neuroprotective role in brain injury. Memoria del trabajo experimental para optar al grado de doctor, correspondiente al Programa de Doctorado en Neurociencias del Instituto de Neurociencias de la Universidad Autónoma de Barcelona, llevado a cabo por Luis Pardo Fernández bajo la dirección de la Dra. Elena Galea Rodríguez de Velasco y la Dra. Roser Masgrau Juanola, en el Instituto de Neurociencias de la Universidad Autónoma de Barcelona. Doctorando Directoras de tesis Luis Pardo Fernández Dra. Elena Galea Dra. Roser Masgrau In memoriam María Dolores Álvarez Durán Abuela, eres la culpable de que haya decidido recorrer el camino de la ciencia. Que estas líneas ayuden a conservar tu recuerdo. A mis padres y hermanos, A Meri INDEX I Summary 1 II Introduction 3 1 Astrocytes: physiology and pathology 5 1.1 Anatomical organization 6 1.2 Origins and heterogeneity 6 1.3 Astrocyte functions 8 1.3.1 Developmental functions 8 1.3.2 Neurovascular functions 9 1.3.3 Metabolic support 11 1.3.4 Homeostatic functions 13 1.3.5 Antioxidant functions 15 1.3.6 Signalling functions 15 1.4 Astrocytes in brain pathology 20 1.5 Reactive astrogliosis 22 2 The transcription
    [Show full text]
  • 1 SUPPLEMENTARY APPENDIX Canakinumab Reverses Overexpression of Inflammatory Response Genes in Tumor Necrosis Factor Receptor−
    SUPPLEMENTARY APPENDIX Canakinumab Reverses Overexpression of Inflammatory Response Genes in Tumor Necrosis Factor Receptor−Associated Periodic Syndrome Rebecca Torene,1 Nanguneri Nirmala,1 Laura Obici,2 Marco Cattalini,3 Vincent Tormey,4 Roberta Caorsi,5 Sandrine Starck-Schwertz,6 Martin Letzkus,6 Nicole Hartmann,6 Ken Abrams,7 Helen Lachmann,8 Marco Gattorno5 1Novartis Institutes for Biomedical Research, Cambridge, MA, USA; 2Amyloid Centre, IRCCS Policlinico San Matteo, Pavia, Italy; 3Pediatric Clinic, University of Brescia and Spedali Civili, Brescia, Italy; 4Galway University Hospitals, Galway, Ireland; 5G Gaslini Institute, Genova, Italy; 6Novartis Institutes for Biomedical Research, Basel Switzerland; 7Novartis Pharmaceuticals Corp., East Hanover, NJ, USA; 8University College London Medical School, London, UK 1 METHODS Identification of Differentially Expressed Genes To identify differentially expressed genes, samples were included in a linear regression model using the LIMMA package in R, with visit number and array batch as factors. Pairwise comparisons between different visits were performed to determine the differentially expressed genes using subject as the random effect. TRAPS patients at baseline were also contrasted with healthy volunteers. Differential expression was defined using a maximum Benjamini-Hochberg corrected P-value cutoff of 0.05 and a minimum 2-fold change in either direction. Because neutrophil counts were previously observed to decline during canakinumab treatment, the potential interaction between changes in neutrophil counts and changes in gene expression changes were evaluated. An analysis of variance (ANOVA) was first used to determine changes in neutrophil counts with canakinumab treatment across the visits at baseline, Day 15, and Day 113, and then Pearson’s correlation was used to determine whether differentially expressed genes correlated with the relative neutrophil count.
    [Show full text]
  • Supplementary Figures and Tables
    Supplementary Information for FKBP4 connects mTORC2 and PI3K to activate the PDK1/Akt-dependent cell proliferation signaling in breast cancer Alain Mangé, Etienne Coyaud, Caroline Desmetz, Benoit Béganton, Peter Coopman, Brian Raught, Jérôme Solassol Corresponding author: Alain Mangé, IRCM – INSERM U1194, 208 rue des Apothicaires, 34298 MONTPELLIER CEDEX 5. Tel: (33)467612412, Fax: (33)467339590, [email protected] This PDF file includes: • Figs. S1, S2 and S3 • Tables S1, S2 1 Figure and Table legends Fig. S1. FKBP4 knockdown impairs cell growth and proliferation in two ER/PR-positive cell lines, MCF-7 (A) and T47D (B), and one triple-negative cell line, MDA-MB-436 (C). The cell proliferation rate was determined by cell count every day during 6 days. Data are based on 3 independent experiments. Results are shown as mean ± SEM. * P<0.05; ** P<0.01; *** P<0.001. Fig. S2. BioID workflow chart. Fig. S3. Effect of single FKBP4 siRNAs on the phosphorylation of Akt at Ser473. MDA-MB-231 cells, transfected with negative control or 4 single FKBP4 siRNAs (constitutive of the SMARTpool used in the study), were serum deprived overnight and stimulated with 10% FCS for 1 h. Cell lysates were analyzed by immunoblotting. The phosphorylation of Akt was examined using the antibody indicated. Table S1. FKBP4 BioID-based interactome. The proteins identified are from two biological replicates and two technical replicates. Total spectral count (sum of the spectral identified from the four MS runs), and the corresponding SAINT score is specified. Table S2. FKBP4 FLAG tag-based IP-MS interactome. The proteins identified are from two biological replicates and two technical replicates.
    [Show full text]