Several Fusion Genes Identified in a Spermatic Cord Leiomyoma With
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Analysis of Trans Esnps Infers Regulatory Network Architecture
Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2014 Anat Kreimer All rights reserved ABSTRACT Analysis of trans eSNPs infers regulatory network architecture Anat Kreimer eSNPs are genetic variants associated with transcript expression levels. The characteristics of such variants highlight their importance and present a unique opportunity for studying gene regulation. eSNPs affect most genes and their cell type specificity can shed light on different processes that are activated in each cell. They can identify functional variants by connecting SNPs that are implicated in disease to a molecular mechanism. Examining eSNPs that are associated with distal genes can provide insights regarding the inference of regulatory networks but also presents challenges due to the high statistical burden of multiple testing. Such association studies allow: simultaneous investigation of many gene expression phenotypes without assuming any prior knowledge and identification of unknown regulators of gene expression while uncovering directionality. This thesis will focus on such distal eSNPs to map regulatory interactions between different loci and expose the architecture of the regulatory network defined by such interactions. We develop novel computational approaches and apply them to genetics-genomics data in human. We go beyond pairwise interactions to define network motifs, including regulatory modules and bi-fan structures, showing them to be prevalent in real data and exposing distinct attributes of such arrangements. We project eSNP associations onto a protein-protein interaction network to expose topological properties of eSNPs and their targets and highlight different modes of distal regulation. -
The Molecular Genetic Architecture of Attention Deficit Hyperactivity Disorder
Molecular Psychiatry (2015) 20, 289–297 © 2015 Macmillan Publishers Limited All rights reserved 1359-4184/15 www.nature.com/mp EXPERT REVIEW The molecular genetic architecture of attention deficit hyperactivity disorder Z Hawi1, TDR Cummins1, J Tong1, B Johnson1, R Lau1, W Samarrai2 and MA Bellgrove1 Attention deficit hyperactivity disorder (ADHD) is a common childhood behavioral condition which affects 2–10% of school age children worldwide. Although the underlying molecular mechanism for the disorder is poorly understood, familial, twin and adoption studies suggest a strong genetic component. Here we provide a state-of-the-art review of the molecular genetics of ADHD incorporating evidence from candidate gene and linkage designs, as well as genome-wide association (GWA) studies of common single-nucleotide polymorphisms (SNPs) and rare copy number variations (CNVs). Bioinformatic methods such as functional enrichment analysis and protein–protein network analysis are used to highlight biological processes of likely relevance to the aetiology of ADHD. Candidate gene associations of minor effect size have been replicated across a number of genes including SLC6A3, DRD5, DRD4, SLC6A4, LPHN3, SNAP-25, HTR1B, NOS1 and GIT1. Although case-control SNP-GWAS have had limited success in identifying common genetic variants for ADHD that surpass critical significance thresholds, quantitative trait designs suggest promising associations with Cadherin13 and glucose–fructose oxidoreductase domain 1 genes. Further, CNVs mapped to glutamate receptor genes (GRM1, GRM5, GRM7 and GRM8) have been implicated in the aetiology of the disorder and overlap with bioinformatic predictions based on ADHD GWAS SNP data regarding enriched pathways. Although increases in sample size across multi-center cohorts will likely yield important new results, we advocate that this must occur in parallel with a shift away from categorical case-control approaches that view ADHD as a unitary construct, towards dimensional approaches that incorporate endophenotypes and statistical classification methods. -
CLASP2 Antibody Product Type
PRODUCT INFORMATION Product name: CLASP2 antibody Product type: Primary antibodies Description: Rabbit polyclonal to CLASP2 Immunogen:3 synthetic peptides (human) conjugated to KLH Reacts with:Hu, Ms Tested applications:ELISA, WB and IF GENE INFORMATION Gene Symbol: CLASP2 Gene Name:cytoplasmic linker associated protein 2 Ensembl ID:ENSG00000163539 Entrez GeneID:23122 GenBank Accession number:AB014527 Swiss-Prot:O75122 Molecular weight of CLASP2: 165.9 & 108.6kDa Function:Microtubule plus-end tracking protein that promotes the stabilization of dynamic microtubules. Involved in the nucleation of noncentrosomal microtubules originating from the trans-Golgi network (TGN). Required for the polarization of the cytoplasmic microtubule arrays in migrating cells towards the leading edge of the cell. May act at the cell cortex to enhance the frequency of rescue of depolymerizing microtubules by attaching their plus- ends to cortical platforms composed of ERC1 and PHLDB2. This cortical microtubule stabilizing activity is regulated at least in part by phosphatidylinositol 3-kinase signaling. Also performs a similar stabilizing function at the kinetochore which is essential for the bipolar alignment of chromosomes on the mitotic spindle. Acts as a mediator of ERBB2- dependent stabilization of microtubules at the cell cortex. Expected subcellular localization:Cytoplasm › cytoskeleton. Cytoplasm › cytoskeleton › microtubule organizing center › centrosome. Chromosome › centromere › kinetochore. Cytoplasm › cytoskeleton › spindle. Golgi apparatus. Golgi apparatus › trans-Golgi network. Cell membrane. Cell projection › ruffle membrane. Note: Localizes to microtubule plus ends. Localizes to centrosomes, kinetochores and the mitotic spindle from prometaphase. Subsequently localizes to the spindle midzone from anaphase and to the midbody from telophase. In migrating cells localizes to the plus ends of microtubules within the cell body and to the entire microtubule lattice within the lamella. -
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. -
An Interaction Map of Circulating Metabolites, Immune Gene Networks, and Their Genetic Regulation Artika P
Nath et al. Genome Biology (2017) 18:146 DOI 10.1186/s13059-017-1279-y RESEARCH Open Access An interaction map of circulating metabolites, immune gene networks, and their genetic regulation Artika P. Nath1,2, Scott C. Ritchie2,3, Sean G. Byars3,4, Liam G. Fearnley3,4, Aki S. Havulinna5,6, Anni Joensuu5, Antti J. Kangas7, Pasi Soininen7,8, Annika Wennerström5, Lili Milani9, Andres Metspalu9, Satu Männistö5, Peter Würtz7,10, Johannes Kettunen5,7,8,11, Emma Raitoharju12, Mika Kähönen13, Markus Juonala14,15, Aarno Palotie6,16,17,18, Mika Ala-Korpela7,8,11,19,20, Samuli Ripatti6,21, Terho Lehtimäki12, Gad Abraham2,3,4, Olli Raitakari22,23, Veikko Salomaa5, Markus Perola5,6,9 and Michael Inouye1,2,3,4* Abstract Background: Immunometabolism plays a central role in many cardiometabolic diseases. However, a robust map of immune-related gene networks in circulating human cells, their interactions with metabolites, and their genetic control is still lacking. Here, we integrate blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts (total N = 2168), including a subset of individuals with matched multi-omic data at 7-year follow-up. Results: We identify topologically replicable gene networks enrichedfordiverseimmunefunctions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules show complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, small molecules, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) reveal five modules with mQTLs that have both cis and trans effects. The strongest mQTL is in ARHGEF3 (rs1354034) and affects a module enriched for platelet function, independent of platelet counts. -
Mapping the Genetic Architecture of Gene Regulation in Whole Blood
Mapping the Genetic Architecture of Gene Regulation in Whole Blood Katharina Schramm1,2., Carola Marzi3,4,5., Claudia Schurmann6., Maren Carstensen7,8., Eva Reinmaa9,10, Reiner Biffar11, Gertrud Eckstein1, Christian Gieger12, Hans-Jo¨ rgen Grabe13, Georg Homuth6, Gabriele Kastenmu¨ ller14, Reedik Ma¨gi10, Andres Metspalu9,10, Evelin Mihailov10,15, Annette Peters2, Astrid Petersmann16, Michael Roden7,8,17, Konstantin Strauch12,18, Karsten Suhre14,19, Alexander Teumer6,UweVo¨ lker6, Henry Vo¨ lzke20, Rui Wang-Sattler3,4, Melanie Waldenberger3,4, Thomas Meitinger1,2,21, Thomas Illig22, Christian Herder7,8., Harald Grallert3,4,5., Holger Prokisch1,2*. 1 Institute of Human Genetics, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany, 2 Institute of Human Genetics, Technical University Munich, Mu¨nchen, Germany, 3 Research Unit of Molecular Epidemiology, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany, 4 Institute of Epidemiology II, Helmholtz Center Munich, German Research Center for Environmental Health, Neuherberg, Germany, 5 German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany, 6 Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine Greifswald, Greifswald, Germany, 7 Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Du¨sseldorf, Du¨sseldorf, Germany, 8 German Center for Diabetes Research (DZD e.V.), -
Redefining the Specificity of Phosphoinositide-Binding by Human
bioRxiv preprint doi: https://doi.org/10.1101/2020.06.20.163253; this version posted June 21, 2020. 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 4.0 International license. Redefining the specificity of phosphoinositide-binding by human PH domain-containing proteins Nilmani Singh1†, Adriana Reyes-Ordoñez1†, Michael A. Compagnone1, Jesus F. Moreno Castillo1, Benjamin J. Leslie2, Taekjip Ha2,3,4,5, Jie Chen1* 1Department of Cell & Developmental Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801; 2Department of Biophysics and Biophysical Chemistry, Johns Hopkins University School of Medicine, Baltimore, MD 21205; 3Department of Biophysics, Johns Hopkins University, Baltimore, MD 21218; 4Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205; 5Howard Hughes Medical Institute, Baltimore, MD 21205, USA †These authors contributed equally to this work. *Correspondence: [email protected]. bioRxiv preprint doi: https://doi.org/10.1101/2020.06.20.163253; this version posted June 21, 2020. 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 4.0 International license. ABSTRACT Pleckstrin homology (PH) domains are presumed to bind phosphoinositides (PIPs), but specific interaction with and regulation by PIPs for most PH domain-containing proteins are unclear. Here we employed a single-molecule pulldown assay to study interactions of lipid vesicles with full-length proteins in mammalian whole cell lysates. -
TRAK1 (NM 014965) Human Recombinant Protein – TP304282 | Origene
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for TP304282 TRAK1 (NM_014965) Human Recombinant Protein Product data: Product Type: Recombinant Proteins Description: Recombinant protein of human trafficking protein, kinesin binding 1 (TRAK1), transcript variant 2 Species: Human Expression Host: HEK293T Tag: C-Myc/DDK Predicted MW: 77.1 kDa Concentration: >50 ug/mL as determined by microplate BCA method Purity: > 80% as determined by SDS-PAGE and Coomassie blue staining Buffer: 25 mM Tris.HCl, pH 7.3, 100 mM glycine, 10% glycerol Preparation: Recombinant protein was captured through anti-DDK affinity column followed by conventional chromatography steps. Storage: Store at -80°C. Stability: Stable for 12 months from the date of receipt of the product under proper storage and handling conditions. Avoid repeated freeze-thaw cycles. RefSeq: NP_055780 Locus ID: 22906 UniProt ID: Q9UPV9, B7ZAE5 RefSeq Size: 4623 Cytogenetics: 3p22.1 RefSeq ORF: 2064 Synonyms: EIEE68; MILT1; OIP106 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. View online » ©2021 OriGene Technologies, Inc., 9620 Medical Center Drive, Ste 200, Rockville, MD 20850, US 1 / 2 TRAK1 (NM_014965) Human Recombinant Protein – TP304282 Summary: Involved in the regulation of endosome-to-lysosome trafficking, including endocytic trafficking of EGF-EGFR complexes and GABA-A receptors (PubMed:18675823). Involved in mitochondrial motility. When O-glycosylated, abolishes mitochondrial motility. Crucial for recruiting OGT to the mitochondrial surface of neuronal processes (PubMed:24995978). TRAK1 and RHOT form an essential protein complex that links KIF5 to mitochondria for light chain-independent, anterograde transport of mitochondria (By similarity).[UniProtKB/Swiss-Prot Function] Protein Families: Transcription Factors Product images: Coomassie blue staining of purified TRAK1 protein (Cat# TP304282). -
Mitoxplorer, a Visual Data Mining Platform To
mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dynamics and mutations Annie Yim, Prasanna Koti, Adrien Bonnard, Fabio Marchiano, Milena Dürrbaum, Cecilia Garcia-Perez, José Villaveces, Salma Gamal, Giovanni Cardone, Fabiana Perocchi, et al. To cite this version: Annie Yim, Prasanna Koti, Adrien Bonnard, Fabio Marchiano, Milena Dürrbaum, et al.. mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dy- namics and mutations. Nucleic Acids Research, Oxford University Press, 2020, 10.1093/nar/gkz1128. hal-02394433 HAL Id: hal-02394433 https://hal-amu.archives-ouvertes.fr/hal-02394433 Submitted on 4 Dec 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution| 4.0 International License Nucleic Acids Research, 2019 1 doi: 10.1093/nar/gkz1128 Downloaded from https://academic.oup.com/nar/advance-article-abstract/doi/10.1093/nar/gkz1128/5651332 by Bibliothèque de l'université la Méditerranée user on 04 December 2019 mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dynamics and mutations Annie Yim1,†, Prasanna Koti1,†, Adrien Bonnard2, Fabio Marchiano3, Milena Durrbaum¨ 1, Cecilia Garcia-Perez4, Jose Villaveces1, Salma Gamal1, Giovanni Cardone1, Fabiana Perocchi4, Zuzana Storchova1,5 and Bianca H. -
A Curated Database of Experimentally Identified Interaction Proteins Of
International Journal of Molecular Sciences Article OGT Protein Interaction Network (OGT-PIN): A Curated Database of Experimentally Identified Interaction Proteins of OGT Junfeng Ma 1,* , Chunyan Hou 2, Yaoxiang Li 1 , Shufu Chen 3 and Ci Wu 1 1 Lombardi Comprehensive Cancer Center, Department of Oncology, Georgetown University Medical Center, Washington, DC 20057, USA; [email protected] (Y.L.); [email protected] (C.W.) 2 Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; [email protected] 3 School of Engineering, Pennsylvania State University Behrend, Erie, PA 16563, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-202-6873802 Abstract: Interactions between proteins are essential to any cellular process and constitute the basis for molecular networks that determine the functional state of a cell. With the technical advances in recent years, an astonishingly high number of protein–protein interactions has been revealed. However, the interactome of O-linked N-acetylglucosamine transferase (OGT), the sole enzyme adding the O-linked β-N-acetylglucosamine (O-GlcNAc) onto its target proteins, has been largely undefined. To that end, we collated OGT interaction proteins experimentally identified in the past several decades. Rigorous curation of datasets from public repositories and O-GlcNAc-focused publications led to the identification of up to 929 high-stringency OGT interactors from multiple species studied (including Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Citation: Ma, J.; Hou, C.; Li, Y.; Chen, S.; Wu, C. OGT Protein Interaction Arabidopsis thaliana, and others). Among them, 784 human proteins were found to be interactors Network (OGT-PIN): A Curated of human OGT. -
SNP in Human ARHGEF3 Promoter Is Associated with Dnase
University of Groningen SNP in human ARHGEF3 promoter is associated with DNase hypersensitivity, transcript level and platelet function, and Arhgef3 KO mice have increased mean platelet volume Zou, Siying; Teixeira, Alexandra M.; Kostadima, Myrto; Astle, William J.; Radhakrishnan, Aparna; Simon, Lukas Mikolaj; Truman, Lucy; Fang, Jennifer S.; Hwa, John; Zhang, Ping-xia Published in: PLoS ONE DOI: 10.1371/journal.pone.0178095 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2017 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Zou, S., Teixeira, A. M., Kostadima, M., Astle, W. J., Radhakrishnan, A., Simon, L. M., ... Krause, D. S. (2017). SNP in human ARHGEF3 promoter is associated with DNase hypersensitivity, transcript level and platelet function, and Arhgef3 KO mice have increased mean platelet volume. PLoS ONE, 12(5), [e0178095]. https://doi.org/10.1371/journal.pone.0178095 Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. -
Gene Ontology Functional Annotations and Pleiotropy
Network based analysis of genetic disease associations Sarah Gilman Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2014 © 2013 Sarah Gilman All Rights Reserved ABSTRACT Network based analysis of genetic disease associations Sarah Gilman Despite extensive efforts and many promising early findings, genome-wide association studies have explained only a small fraction of the genetic factors contributing to common human diseases. There are many theories about where this “missing heritability” might lie, but increasingly the prevailing view is that common variants, the target of GWAS, are not solely responsible for susceptibility to common diseases and a substantial portion of human disease risk will be found among rare variants. Relatively new, such variants have not been subject to purifying selection, and therefore may be particularly pertinent for neuropsychiatric disorders and other diseases with greatly reduced fecundity. Recently, several researchers have made great progress towards uncovering the genetics behind autism and schizophrenia. By sequencing families, they have found hundreds of de novo variants occurring only in affected individuals, both large structural copy number variants and single nucleotide variants. Despite studying large cohorts there has been little recurrence among the genes implicated suggesting that many hundreds of genes may underlie these complex phenotypes. The question