Loss-Of-Function of the Ciliopathy Protein Cc2d2a Disorganizes The
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An EMT-Primary Cilium-GLIS2 Signaling Axis Regulates Mammogenesis and Claudin-Low Breast Tumorigenesis
bioRxiv preprint doi: https://doi.org/10.1101/2020.12.29.424695; this version posted December 29, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 An EMT-primary cilium-GLIS2 signaling axis regulates mammogenesis 2 and claudin-low breast tumorigenesis 3 4 5 6 7 Molly M. Wilson1, Céline Callens2, Matthieu Le Gallo3,4, Svetlana Mironov2, Qiong Ding5, 8 Amandine Salamagnon2, Tony E. Chavarria1, Abena D. Peasah6, Arjun Bhutkar1, Sophie 9 Martin3,4, Florence Godey3,4, Patrick Tas3,4, Anton M. Jetten8, Jane E. Visvader7, Robert A. 10 Weinberg9, Massimo Attanasio5, Claude Prigent2, Jacqueline A. Lees1, Vincent J Guen2* 11 12 13 14 1Koch Institute for Integrative Cancer Research and Department of Biology, Massachusetts 15 Institute of Technology, Cambridge, MA, USA. 16 2Institut de Génétique et Développement de Rennes - Centre National de la Recherche 17 Scientifique, Rennes, France. 18 3INSERM U1242, Rennes 1 University, Rennes, France. 19 4Centre de Lutte Contre le Cancer Eugène Marquis, Rennes, France. 20 5Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, IA, 21 USA. 22 6Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 23 USA. 24 7Stem Cells and Cancer Division, The Walter and Eliza Hall Institute of Medical Research and 25 Department of Medical Biology, The University of Melbourne, Parkville, Victoria, Australia. 26 8Cell Biology Section, Division of Intramural Research, National Institute of Environmental Health 27 Sciences, National Institutes of Health, Research Triangle Park, NC, USA. 28 9MIT Department of Biology and the Whitehead Institute, Cambridge, MA, USA. -
A Trafficome-Wide Rnai Screen Reveals Deployment of Early and Late Secretory Host Proteins and the Entire Late Endo-/Lysosomal V
bioRxiv preprint doi: https://doi.org/10.1101/848549; this version posted November 19, 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 The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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 4.0 International license. 1 A trafficome-wide RNAi screen reveals deployment of early and late 2 secretory host proteins and the entire late endo-/lysosomal vesicle fusion 3 machinery by intracellular Salmonella 4 5 Alexander Kehl1,4, Vera Göser1, Tatjana Reuter1, Viktoria Liss1, Maximilian Franke1, 6 Christopher John1, Christian P. Richter2, Jörg Deiwick1 and Michael Hensel1, 7 8 1Division of Microbiology, University of Osnabrück, Osnabrück, Germany; 2Division of Biophysics, University 9 of Osnabrück, Osnabrück, Germany, 3CellNanOs – Center for Cellular Nanoanalytics, Fachbereich 10 Biologie/Chemie, Universität Osnabrück, Osnabrück, Germany; 4current address: Institute for Hygiene, 11 University of Münster, Münster, Germany 12 13 Running title: Host factors for SIF formation 14 Keywords: siRNA knockdown, live cell imaging, Salmonella-containing vacuole, Salmonella- 15 induced filaments 16 17 Address for correspondence: 18 Alexander Kehl 19 Institute for Hygiene 20 University of Münster 21 Robert-Koch-Str. 4148149 Münster, Germany 22 Tel.: +49(0)251/83-55233 23 E-mail: [email protected] 24 25 or bioRxiv preprint doi: https://doi.org/10.1101/848549; this version posted November 19, 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 4.0 International license. -
Identification of Expression Qtls Targeting Candidate Genes For
ISSN: 2378-3648 Salleh et al. J Genet Genome Res 2018, 5:035 DOI: 10.23937/2378-3648/1410035 Volume 5 | Issue 1 Journal of Open Access Genetics and Genome Research RESEARCH ARTICLE Identification of Expression QTLs Targeting Candidate Genes for Residual Feed Intake in Dairy Cattle Using Systems Genomics Salleh MS1,2, Mazzoni G2, Nielsen MO1, Løvendahl P3 and Kadarmideen HN2,4* 1Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark Check for 2Department of Bio and Health Informatics, Technical University of Denmark, Lyngby, Denmark updates 3Department of Molecular Biology and Genetics-Center for Quantitative Genetics and Genomics, Aarhus University, AU Foulum, Tjele, Denmark 4Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark *Corresponding author: Kadarmideen HN, Department of Applied Mathematics and Computer Science, Technical University of Denmark, DK-2800, Kgs. Lyngby, Denmark, E-mail: [email protected] Abstract body weight gain and net merit). The eQTLs and biological pathways identified in this study improve our understanding Background: Residual feed intake (RFI) is the difference of the complex biological and genetic mechanisms that de- between actual and predicted feed intake and an important termine FE traits in dairy cattle. The identified eQTLs/genet- factor determining feed efficiency (FE). Recently, 170 can- ic variants can potentially be used in new genomic selection didate genes were associated with RFI, but no expression methods that include biological/functional information on quantitative trait loci (eQTL) mapping has hitherto been per- SNPs. formed on FE related genes in dairy cows. In this study, an integrative systems genetics approach was applied to map Keywords eQTLs in Holstein and Jersey cows fed two different diets to eQTL, RNA-seq, Genotype, Data integration, Systems improve identification of candidate genes for FE. -
WO 2016/040794 Al 17 March 2016 (17.03.2016) P O P C T
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2016/040794 Al 17 March 2016 (17.03.2016) P O P C T (51) International Patent Classification: AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, C12N 1/19 (2006.01) C12Q 1/02 (2006.01) BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, C12N 15/81 (2006.01) C07K 14/47 (2006.01) DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JP, KE, KG, KN, KP, KR, (21) International Application Number: KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, PCT/US20 15/049674 MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, (22) International Filing Date: PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, 11 September 2015 ( 11.09.201 5) SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every (26) Publication Language: English kind of regional protection available): ARIPO (BW, GH, (30) Priority Data: GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, 62/050,045 12 September 2014 (12.09.2014) US TZ, UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, (71) Applicant: WHITEHEAD INSTITUTE FOR BIOMED¬ DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, ICAL RESEARCH [US/US]; Nine Cambridge Center, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, Cambridge, Massachusetts 02142-1479 (US). -
Genome-Wide Association Study of Brain Amyloid Deposition As Measured by Pittsburgh Compound-B (Pib)-PET Imaging
Molecular Psychiatry (2021) 26:309–321 https://doi.org/10.1038/s41380-018-0246-7 ARTICLE Genome-wide association study of brain amyloid deposition as measured by Pittsburgh Compound-B (PiB)-PET imaging 1,2 3,4 5 1 3,4 1 Qi Yan ● Kwangsik Nho ● Jorge L. Del-Aguila ● Xingbin Wang ● Shannon L. Risacher ● Kang-Hsien Fan ● 6,7 8 7,9 6,7,8 1 Beth E. Snitz ● Howard J. Aizenstein ● Chester A. Mathis ● Oscar L. Lopez ● F. Yesim Demirci ● 1 6,7,8 3,4 Eleanor Feingold ● William E. Klunk ● Andrew J. Saykin ● for the Alzheimer’s Disease Neuroimaging 5 1,7,8 Initiative (ADNI) ● Carlos Cruchaga ● M. Ilyas Kamboh Received: 1 December 2017 / Accepted: 31 July 2018 / Published online: 25 October 2018 © The Author(s) 2018. This article is published with open access Abstract Deposition of amyloid plaques in the brain is one of the two main pathological hallmarks of Alzheimer’s disease (AD). Amyloid positron emission tomography (PET) is a neuroimaging tool that selectively detects in vivo amyloid deposition in the brain and is a reliable endophenotype for AD that complements cerebrospinal fluid biomarkers with regional information. We measured in vivo amyloid deposition in the brains of ~1000 subjects from three collaborative AD centers and ADNI 11 1234567890();,: 1234567890();,: using C-labeled Pittsburgh Compound-B (PiB)-PET imaging followed by meta-analysis of genome-wide association studies, first to our knowledge for PiB-PET, to identify novel genetic loci for this endophenotype. The APOE region showed the most significant association where several SNPs surpassed the genome-wide significant threshold, with APOE*4 being most significant (P-meta = 9.09E-30; β = 0.18). -
Product Size GOT1 P00504 F CAAGCTGT
Table S1. List of primer sequences for RT-qPCR. Gene Product Uniprot ID F/R Sequence(5’-3’) name size GOT1 P00504 F CAAGCTGTCAAGCTGCTGTC 71 R CGTGGAGGAAAGCTAGCAAC OGDHL E1BTL0 F CCCTTCTCACTTGGAAGCAG 81 R CCTGCAGTATCCCCTCGATA UGT2A1 F1NMB3 F GGAGCAAAGCACTTGAGACC 93 R GGCTGCACAGATGAACAAGA GART P21872 F GGAGATGGCTCGGACATTTA 90 R TTCTGCACATCCTTGAGCAC GSTT1L E1BUB6 F GTGCTACCGAGGAGCTGAAC 105 R CTACGAGGTCTGCCAAGGAG IARS Q5ZKA2 F GACAGGTTTCCTGGCATTGT 148 R GGGCTTGATGAACAACACCT RARS Q5ZM11 F TCATTGCTCACCTGCAAGAC 146 R CAGCACCACACATTGGTAGG GSS F1NLE4 F ACTGGATGTGGGTGAAGAGG 89 R CTCCTTCTCGCTGTGGTTTC CYP2D6 F1NJG4 F AGGAGAAAGGAGGCAGAAGC 113 R TGTTGCTCCAAGATGACAGC GAPDH P00356 F GACGTGCAGCAGGAACACTA 112 R CTTGGACTTTGCCAGAGAGG Table S2. List of differentially expressed proteins during chronic heat stress. score name Description MW PI CC CH Down regulated by chronic heat stress A2M Uncharacterized protein 158 1 0.35 6.62 A2ML4 Uncharacterized protein 163 1 0.09 6.37 ABCA8 Uncharacterized protein 185 1 0.43 7.08 ABCB1 Uncharacterized protein 152 1 0.47 8.43 ACOX2 Cluster of Acyl-coenzyme A oxidase 75 1 0.21 8 ACTN1 Alpha-actinin-1 102 1 0.37 5.55 ALDOC Cluster of Fructose-bisphosphate aldolase 39 1 0.5 6.64 AMDHD1 Cluster of Uncharacterized protein 37 1 0.04 6.76 AMT Aminomethyltransferase, mitochondrial 42 1 0.29 9.14 AP1B1 AP complex subunit beta 103 1 0.15 5.16 APOA1BP NAD(P)H-hydrate epimerase 32 1 0.4 8.62 ARPC1A Actin-related protein 2/3 complex subunit 42 1 0.34 8.31 ASS1 Argininosuccinate synthase 47 1 0.04 6.67 ATP2A2 Cluster of Calcium-transporting -
Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ...................................................... -
Nucleic Acids Research, 2009, Vol
Published online 2 June 2009 Nucleic Acids Research, 2009, Vol. 37, No. 14 4587–4602 doi:10.1093/nar/gkp425 An integrative genomics approach identifies Hypoxia Inducible Factor-1 (HIF-1)-target genes that form the core response to hypoxia Yair Benita1, Hirotoshi Kikuchi2, Andrew D. Smith3, Michael Q. Zhang3, Daniel C. Chung2 and Ramnik J. Xavier1,2,* 1Center for Computational and Integrative Biology, 2Gastrointestinal Unit, Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 and 3Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA Received April 20, 2009; Revised May 6, 2009; Accepted May 8, 2009 ABSTRACT the pivotal mediators of the cellular response to hypoxia is hypoxia-inducible factor (HIF), a transcription factor The transcription factor Hypoxia-inducible factor 1 that contains a basic helix-loop-helix motif as well as (HIF-1) plays a central role in the transcriptional PAS domain. There are three known members of the response to oxygen flux. To gain insight into HIF family (HIF-1, HIF-2 and HIF-3) and all are a/b the molecular pathways regulated by HIF-1, it is heterodimeric proteins. HIF-1 was the first factor to be essential to identify the downstream-target genes. cloned and is the best understood isoform (1). HIF-3 is We report here a strategy to identify HIF-1-target a distant relative of HIF-1 and little is currently known genes based on an integrative genomic approach about its function and involvement in oxygen homeosta- combining computational strategies and experi- sis. -
Study of Urine Extracellular Vesicles-Derived Protein Biomarkers for the Non-Invasive Monitoring of Kidney-Transplanted Patients
ADVERTIMENT. Lʼaccés als continguts dʼaquesta tesi queda condicionat a lʼacceptació de les condicions dʼús establertes per la següent llicència Creative Commons: http://cat.creativecommons.org/?page_id=184 ADVERTENCIA. El acceso a los contenidos de esta tesis queda condicionado a la aceptación de las condiciones de uso establecidas por la siguiente licencia Creative Commons: http://es.creativecommons.org/blog/licencias/ WARNING. The access to the contents of this doctoral thesis it is limited to the acceptance of the use conditions set by the following Creative Commons license: https://creativecommons.org/licenses/?lang=en Study of urine extracellular vesicles-derived protein biomarkers for the non-invasive monitoring of kidney- transplanted patients Laura Carreras Planella Doctoral thesis Badalona, 20th October 2020 Thesis directors: Francesc Enric Borràs Serres, PhD Maria Isabel Troya Saborido, PhD 2 PhD programme in Advanced Immunology Department of Cellular Biology, Physiology and Immunology Universitat Autònoma de Barcelona Study of urine extracellular vesicles-derived protein biomarkers for the non-invasive monitoring of kidney-transplanted patients Estudi de biomarcadors proteics derivats de vesícules extracel·lulars de la orina per la monitorització no invasiva de pacients trasplantats de ronyó Thesis presented by Laura Carreras Planella to qualify for the PhD degree in Advanced Immunology by the Universitat Autònoma de Barcelona The presented work has been performed in the ReMAR-IVECAT group at the Germans Trias i Pujol Health Sciences Research Institute (IGTP) under the supervision of Dr. Francesc Enric Borràs Serres, as tutor and co-director, and Dr. Maria Isabel Troya Saborido as co-director. 3 Laura Carreras was sponsored by the Spanish Government with an FPU grant (“Formación de Personal Universitario”, FPU17/01444) and by La Fundació Cellex during the development of the PhD project. -
1 Supplementary Materials Common Genetic Variants
Supplementary Materials Common Genetic Variants Modulate Pathogen-Sensing Responses in Human Dendritic Cells Mark N. Lee, Chun Ye, Alexandra-Chloé Villani, Towfique Raj, Weibo Li, Thomas M. Eisenhaure, Selina H. Imboywa, Portia I. Chipendo, F. Ann Ran, Kamil Slowikowski, Lucas D. Ward, Khadir Raddassi, Cristin McCabe, Michelle H. Lee, Irene Y. Frohlich, David A. Hafler, Manolis Kellis, Soumya Raychaudhuri, Feng Zhang, Barbara E. Stranger, Christophe O. Benoist, Philip L. De Jager, Aviv Regev*, Nir Hacohen* *Corresponding authors. E-mail: [email protected] (A.R.); [email protected] (N.H.) This PDF file includes: Materials and Methods Supplementary Text Figs. S1 to S5 Captions for tables S1 to S11 References (46-72) Other Supplementary Materials for this manuscript includes the following: Tables S1 to S11 as zipped archive: Table S1. Samples. Table S2. Differential expression analysis. Table S3. Gene signature set. Table S4. cis-eQTLs and cis-reQTLs from pooled analysis. Table S5. Imputation meta-analysis. Table S6. Conditioning. Table S7. ChIP-Seq enrichment. Table S8. Trans-eQTLs and trans-reQTLs from pooled analysis. Table S9. Trans-eQTLs and trans-reQTLs from pooled analysis (only cis considered). Table S10. rs12805435 trans. Table S11. GWAS. 1 Materials and Methods Study subjects Donors were recruited from the Boston community as part of the Phenogenetic Project and ImmVar Consortium, and gave written informed consent for the studies. Individuals were excluded if they had a history of inflammatory disease, autoimmune disease, chronic metabolic disorders or chronic infectious disorders. For the microarray study, 30 healthy human donors were recruited. Donors were between 19 and 49 years of age; 15 were male and 15 were female; 18 were Caucasian, 6 were African-American and 6 were Asian; 12 provided a serial replicate blood sample (i.e. -
Differential Gene Regulation in Fibroblasts in Co-Culture with Keratinocytes and Head and Neck SCC Cells
ANTICANCER RESEARCH 35: 3253-3266 (2015) Differential Gene Regulation in Fibroblasts in Co-culture with Keratinocytes and Head and Neck SCC Cells MALIN HAKELIUS1, DANIEL SAIEPOUR1, HANNA GÖRANSSON2, KRISTOFER RUBIN3, BENGT GERDIN1 and DANIEL NOWINSKI1 Departments of 1Surgical Sciences, Plastic Surgery and 3Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden; 2Array Facility, Department of Medical Sciences, Uppsala University, Uppsala, Sweden Abstract. Background: While carcinoma-associated growth. In cancers, this microenvironment, or tumor stroma, fibroblasts (CAFs) support tumorigenesis, normal tissue constitutes the backbone of the tumor and is essential for the fibroblasts suppress tumor progression. Mechanisms behind cohesiveness of the tumor tissue the tumor’s ability to thrive conversion of fibroblasts into a CAF phenotype are largely (1). This stroma has considerable similarities with that of unrevealed. Materials and Methods: Transwell co-cultures non-malignant repair processes that are characterized by with fibroblasts in collagen gels and squamous-cell activation of fibroblasts and neoformation of stromal tissue, carcinoma (SCC) cells or normal oral keratinocytes (NOKs) which has led to the concept of a tumor as a "wound that in inserts. Differences in fibroblast global gene expression never heals" (2). were analyzed using Affymetrix arrays and subsequent A fibroblast phenotype characterized by expression of functional annotation and cluster analysis, as well as gene alpha-smooth muscle actin (SMA), platelet-derived growth set enrichment analysis were performed. Results: There were factor receptor-beta (PDGFR-β) and the pericyte marker 52 up-regulated and 30 down-regulated transcript IDs neuron glial antigen 2 (NG2) is regarded as a key cell in the (>2-fold, p<0.05) in fibroblasts co-cultured with SCC tumor stroma (3). -
Data Set 1. Biological Analysis of the Genes Found to Be Significant in the Endotoxin Study
Data Set 1. Biological analysis of the genes found to be significant in the endotoxin study. Pages 2 – 105: Q values, gene names and annotation on the genes significant at FDR = 0.1%. Pages 106 – 127: Global functional analysis of the down-regulated genes. Pages 128 – 169: Global functional analysis of the up-regulated genes. Probe Set q-value Direction Gene Annotation 117_at 9.60E-05 up HSPA6 heat shock 70kDa protein 6 (HSP70B') 1405_i_at 2.00E-06 down CCL5 chemokine (C-C motif) ligand 5 PRP8 pre-mRNA processing factor 8 200000_s_at 2.50E-05 down PRPF8 homolog (yeast) PRP8 pre-mRNA processing factor 8 200000_s_at 0.000712 down PRPF8 homolog (yeast) 200001_at 0.000658 down CAPNS1 calpain, small subunit 1 200002_at 2.00E-06 down RPL35 ribosomal protein L35 200002_at 2.00E-06 down RPL35 ribosomal protein L35 200003_s_at 1.10E-05 down RPL28 ribosomal protein L28 200003_s_at 1.10E-05 down RPL28 ribosomal protein L28 eukaryotic translation initiation factor 3, 200005_at 2.00E-06 down EIF3S7 subunit 7 zeta, 66/67kDa eukaryotic translation initiation factor 3, 200005_at 2.00E-06 down EIF3S7 subunit 7 zeta, 66/67kDa Parkinson disease (autosomal 200006_at 4.70E-05 down PARK7 recessive, early onset) 7 Parkinson disease (autosomal 200006_at 8.70E-05 down PARK7 recessive, early onset) 7 200008_s_at 5.40E-05 up GDI2 GDP dissociation inhibitor 2 200008_s_at 0.000361 up GDI2 GDP dissociation inhibitor 2 200009_at 0.000171 down GDI2 GDP dissociation inhibitor 2 200010_at 2.00E-06 down RPL11 ribosomal protein L11 200010_at 2.00E-06 down RPL11 ribosomal