Supporting Information for Proteomics DOI 10.1002/Pmic.200500648
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Bayesian Hierarchical Modeling of High-Throughput Genomic Data with Applications to Cancer Bioinformatics and Stem Cell Differentiation
BAYESIAN HIERARCHICAL MODELING OF HIGH-THROUGHPUT GENOMIC DATA WITH APPLICATIONS TO CANCER BIOINFORMATICS AND STEM CELL DIFFERENTIATION by Keegan D. Korthauer A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Statistics) at the UNIVERSITY OF WISCONSIN–MADISON 2015 Date of final oral examination: 05/04/15 The dissertation is approved by the following members of the Final Oral Committee: Christina Kendziorski, Professor, Biostatistics and Medical Informatics Michael A. Newton, Professor, Statistics Sunduz Kele¸s,Professor, Biostatistics and Medical Informatics Sijian Wang, Associate Professor, Biostatistics and Medical Informatics Michael N. Gould, Professor, Oncology © Copyright by Keegan D. Korthauer 2015 All Rights Reserved i in memory of my grandparents Ma and Pa FL Grandma and John ii ACKNOWLEDGMENTS First and foremost, I am deeply grateful to my thesis advisor Christina Kendziorski for her invaluable advice, enthusiastic support, and unending patience throughout my time at UW-Madison. She has provided sound wisdom on everything from methodological principles to the intricacies of academic research. I especially appreciate that she has always encouraged me to eke out my own path and I attribute a great deal of credit to her for the successes I have achieved thus far. I also owe special thanks to my committee member Professor Michael Newton, who guided me through one of my first collaborative research experiences and has continued to provide key advice on my thesis research. I am also indebted to the other members of my thesis committee, Professor Sunduz Kele¸s,Professor Sijian Wang, and Professor Michael Gould, whose valuable comments, questions, and suggestions have greatly improved this dissertation. -
Supplemental Table S1
Entrez Gene Symbol Gene Name Affymetrix EST Glomchip SAGE Stanford Literature HPA confirmed Gene ID Profiling profiling Profiling Profiling array profiling confirmed 1 2 A2M alpha-2-macroglobulin 0 0 0 1 0 2 10347 ABCA7 ATP-binding cassette, sub-family A (ABC1), member 7 1 0 0 0 0 3 10350 ABCA9 ATP-binding cassette, sub-family A (ABC1), member 9 1 0 0 0 0 4 10057 ABCC5 ATP-binding cassette, sub-family C (CFTR/MRP), member 5 1 0 0 0 0 5 10060 ABCC9 ATP-binding cassette, sub-family C (CFTR/MRP), member 9 1 0 0 0 0 6 79575 ABHD8 abhydrolase domain containing 8 1 0 0 0 0 7 51225 ABI3 ABI gene family, member 3 1 0 1 0 0 8 29 ABR active BCR-related gene 1 0 0 0 0 9 25841 ABTB2 ankyrin repeat and BTB (POZ) domain containing 2 1 0 1 0 0 10 30 ACAA1 acetyl-Coenzyme A acyltransferase 1 (peroxisomal 3-oxoacyl-Coenzyme A thiol 0 1 0 0 0 11 43 ACHE acetylcholinesterase (Yt blood group) 1 0 0 0 0 12 58 ACTA1 actin, alpha 1, skeletal muscle 0 1 0 0 0 13 60 ACTB actin, beta 01000 1 14 71 ACTG1 actin, gamma 1 0 1 0 0 0 15 81 ACTN4 actinin, alpha 4 0 0 1 1 1 10700177 16 10096 ACTR3 ARP3 actin-related protein 3 homolog (yeast) 0 1 0 0 0 17 94 ACVRL1 activin A receptor type II-like 1 1 0 1 0 0 18 8038 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 1 0 0 0 0 19 8751 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 1 0 0 0 0 20 8728 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 1 0 0 0 0 21 81792 ADAMTS12 ADAM metallopeptidase with thrombospondin type 1 motif, 12 1 0 0 0 0 22 9507 ADAMTS4 ADAM metallopeptidase with thrombospondin type 1 -
ANKRD11 Gene Ankyrin Repeat Domain 11
ANKRD11 gene ankyrin repeat domain 11 Normal Function The ANKRD11 gene provides instructions for making a protein called ankyrin repeat domain 11 (ANKRD11). As its name suggests, this protein contains multiple regions called ankyrin domains; proteins with these domains help other proteins interact with each other. The ANKRD11 protein interacts with certain proteins called histone deacetylases, which are important for controlling gene activity. Through these interactions, ANKRD11 affects when genes are turned on and off. For example, ANKRD11 brings together histone deacetylases and other proteins called p160 coactivators. This association regulates the ability of p160 coactivators to turn on gene activity. ANKRD11 may also enhance the activity of a protein called p53, which controls the growth and division (proliferation) and the self-destruction (apoptosis) of cells. The ANKRD11 protein is found in nerve cells (neurons) in the brain. During embryonic development, ANKRD11 helps regulate the proliferation of these cells and development of the brain. Researchers speculate that the protein may also be involved in the ability of neurons to change and adapt over time (plasticity), which is important for learning and memory. ANKRD11 may function in other cells in the body and appears to be involved in normal bone development. Health Conditions Related to Genetic Changes KBG syndrome Several ANKRD11 gene mutations have been found to cause KBG syndrome, a condition characterized by large upper front teeth and other unusual facial features, skeletal abnormalities, and intellectual disability. Most of these mutations lead to an abnormally short ANKRD11 protein, which likely has little or no function. Reduction of this protein's function is thought to underlie the signs and symptoms of the condition. -
New York Chapter American College of Physicians Annual
New York Chapter American College of Physicians Annual Scientific Meeting Poster Presentations Saturday, October 12, 2019 Westchester Hilton Hotel 699 Westchester Avenue Rye Brook, NY New York Chapter American College of Physicians Annual Scientific Meeting Medical Student Clinical Vignette 1 Medical Student Clinical Vignette Adina Amin Medical Student Jessy Epstein, Miguel Lacayo, Emmanuel Morakinyo Touro College of Osteopathic Medicine A Series of Unfortunate Events - A Rare Presentation of Thoracic Outlet Syndrome Venous thoracic outlet syndrome, formerly known as Paget-Schroetter Syndrome, is a condition characterized by spontaneous deep vein thrombosis of the upper extremity. It is a very rare syndrome resulting from anatomical abnormalities of the thoracic outlet, causing thrombosis of the deep veins draining the upper extremity. This disease is also called “effort thrombosis― because of increased association with vigorous and repetitive upper extremity activities. Symptoms include severe upper extremity pain and swelling after strenuous activity. A 31-year-old female with a history of vascular thoracic outlet syndrome, two prior thrombectomies, and right first rib resection presented with symptoms of loss of blood sensation, dull pain in the area, and sharp pain when coughing/sneezing. When the patient had her first blood clot, physical exam was notable for swelling, venous distension, and skin discoloration. The patient had her first thrombectomy in her right upper extremity a couple weeks after the first clot was discovered. Thrombolysis with TPA was initiated, and percutaneous mechanical thrombectomy with angioplasty of the axillary and subclavian veins was performed. Almost immediately after the thrombectomy, the patient had a rethrombosis which was confirmed by ultrasound. -
New Resources for Transcription Analysis and Genome Fugu
Downloaded from genome.cshlp.org on July 6, 2011 - Published by Cold Spring Harbor Laboratory Press Fugu ESTs: New Resources for Transcription Analysis and Genome Annotation Melody S. Clark, Yvonne J.K. Edwards, Dan Peterson, et al. Genome Res. 2003 13: 2747-2753 Access the most recent version at doi:10.1101/gr.1691503 References This article cites 51 articles, 26 of which can be accessed free at: http://genome.cshlp.org/content/13/12/2747.full.html#ref-list-1 Article cited in: http://genome.cshlp.org/content/13/12/2747.full.html#related-urls Email alerting Receive free email alerts when new articles cite this article - sign up in the box at the service top right corner of the article or click here To subscribe to Genome Research go to: http://genome.cshlp.org/subscriptions Cold Spring Harbor Laboratory Press Downloaded from genome.cshlp.org on July 6, 2011 - Published by Cold Spring Harbor Laboratory Press Resource Fugu ESTs: New Resources for Transcription Analysis and Genome Annotation Melody S. Clark,1,7,8 Yvonne J.K. Edwards,1 Dan Peterson,2 Sandra W. Clifton,2 Amanda J. Thompson,1 Masahide Sasaki,3 Yutaka Suzuki,3 Kiyoshi Kikuchi,5,6 Shugo Watabe,5 Koichi Kawakami,4 Sumio Sugano,3 Greg Elgar,1 and Stephen L. Johnson2 1MRC Rosalind Franklin Centre for Genomics Research, (formerly known as the MRC UK HGMP Resource Centre), Genome Campus, Hinxton, Cambridge, CB10 1SB, UK; 2Department of Genetics, Washington University Medical School, St Louis, Missouri 63110, USA; 3The Institute of Medical Science, The University of Tokyo, Shirokanedai, -
Supplementary Materials For
www.sciencemag.org/cgi/content/full/science.1230422/DC1 Supplementary Materials for Genomic Diversity and Evolution of the Head Crest in the Rock Pigeon Michael D. Shapiro,* Zev Kronenberg, Cai Li, Eric T. Domyan, Hailin Pan, Michael Campbell, Hao Tan, Chad D. Huff, Haofu Hu, Anna I. Vickrey, Sandra C. A. Nielsen, Sydney A. Stringham, Hao Hu, Eske Willerslev, M. Thomas P. Gilbert, Mark Yandell, Guojie Zhang, Jun Wang* *To whom correspondence should be addressed. E-mail: [email protected] (M.D.S.); [email protected] (J.W.) Published 31 January 2013 on Science Express DOI: 10.1126/science.1230422 This PDF file includes: Materials and Methods Supplementary Text Figs. S1 to S27 Tables S1 to S28 References (26–72) Materials and Methods Genome assembly The DNA sample for sequencing of the reference genome was extracted from blood obtained from a single, male Danish Tumbler, bred by Anders and Hans Ove Christiansen (Danmarks Racedueforeninger, Næstved, Denmark). This breed was chosen because it is an old breed that is believed to have changed little in recent history. Seven paired-end sequencing libraries were constructed, with insert sizes of 170 bp, 500 bp, 800 bp, 2 kb, 5 kb, 10 kb and 20 kb. The libraries were sequenced using Illumina HiSeq2000 platform, yielding a total of 127.17 Gb raw data (Table S1). The raw sequences were filtered for low quality, adapter sequence, paired-end read overlap, and PCR duplicates. We also performed an error correction step on the raw reads before assembling. Filtering and error correction resulted in 81.57 Gb of clean data for genome assembly with the genome with SOAPdenovo (26). -
Role of Cornification and Triglyceride Synthesis Genes
Gillespie et al. BMC Genomics 2013, 14:169 http://www.biomedcentral.com/1471-2164/14/169 RESEARCH ARTICLE Open Access Transcriptome analysis of pigeon milk production – role of cornification and triglyceride synthesis genes Meagan J Gillespie1,2*, Tamsyn M Crowley1,3, Volker R Haring1, Susanne L Wilson1, Jennifer A Harper1, Jean S Payne1, Diane Green1, Paul Monaghan1, John A Donald2, Kevin R Nicholas3 and Robert J Moore1 Abstract Background: The pigeon crop is specially adapted to produce milk that is fed to newly hatched young. The process of pigeon milk production begins when the germinal cell layer of the crop rapidly proliferates in response to prolactin, which results in a mass of epithelial cells that are sloughed from the crop and regurgitated to the young. We proposed that the evolution of pigeon milk built upon the ability of avian keratinocytes to accumulate intracellular neutral lipids during the cornification of the epidermis. However, this cornification process in the pigeon crop has not been characterised. Results: We identified the epidermal differentiation complex in the draft pigeon genome scaffold and found that, like the chicken, it contained beta-keratin genes. These beta-keratin genes can be classified, based on sequence similarity, into several clusters including feather, scale and claw keratins. The cornified cells of the pigeon crop express several cornification-associated genes including cornulin, S100-A9 and A16-like, transglutaminase 6-like and the pigeon ‘lactating’ crop-specific annexin cp35. Beta-keratins play an important role in ‘lactating’ crop, with several claw and scale keratins up-regulated. Additionally, transglutaminase 5 and differential splice variants of transglutaminase 4 are up-regulated along with S100-A10. -
Supp Table 1.Pdf
Upregulated genes in Hdac8 null cranial neural crest cells fold change Gene Symbol Gene Title 134.39 Stmn4 stathmin-like 4 46.05 Lhx1 LIM homeobox protein 1 31.45 Lect2 leukocyte cell-derived chemotaxin 2 31.09 Zfp108 zinc finger protein 108 27.74 0710007G10Rik RIKEN cDNA 0710007G10 gene 26.31 1700019O17Rik RIKEN cDNA 1700019O17 gene 25.72 Cyb561 Cytochrome b-561 25.35 Tsc22d1 TSC22 domain family, member 1 25.27 4921513I08Rik RIKEN cDNA 4921513I08 gene 24.58 Ofa oncofetal antigen 24.47 B230112I24Rik RIKEN cDNA B230112I24 gene 23.86 Uty ubiquitously transcribed tetratricopeptide repeat gene, Y chromosome 22.84 D8Ertd268e DNA segment, Chr 8, ERATO Doi 268, expressed 19.78 Dag1 Dystroglycan 1 19.74 Pkn1 protein kinase N1 18.64 Cts8 cathepsin 8 18.23 1500012D20Rik RIKEN cDNA 1500012D20 gene 18.09 Slc43a2 solute carrier family 43, member 2 17.17 Pcm1 Pericentriolar material 1 17.17 Prg2 proteoglycan 2, bone marrow 17.11 LOC671579 hypothetical protein LOC671579 17.11 Slco1a5 solute carrier organic anion transporter family, member 1a5 17.02 Fbxl7 F-box and leucine-rich repeat protein 7 17.02 Kcns2 K+ voltage-gated channel, subfamily S, 2 16.93 AW493845 Expressed sequence AW493845 16.12 1600014K23Rik RIKEN cDNA 1600014K23 gene 15.71 Cst8 cystatin 8 (cystatin-related epididymal spermatogenic) 15.68 4922502D21Rik RIKEN cDNA 4922502D21 gene 15.32 2810011L19Rik RIKEN cDNA 2810011L19 gene 15.08 Btbd9 BTB (POZ) domain containing 9 14.77 Hoxa11os homeo box A11, opposite strand transcript 14.74 Obp1a odorant binding protein Ia 14.72 ORF28 open reading -
Epigenetics Page 1
Epigenetics esiRNA ID Gene Name Gene Description Ensembl ID HU-13237-1 ACTL6A actin-like 6A ENSG00000136518 HU-13925-1 ACTL6B actin-like 6B ENSG00000077080 HU-14457-1 ACTR1A ARP1 actin-related protein 1 homolog A, centractin alpha (yeast) ENSG00000138107 HU-10579-1 ACTR2 ARP2 actin-related protein 2 homolog (yeast) ENSG00000138071 HU-10837-1 ACTR3 ARP3 actin-related protein 3 homolog (yeast) ENSG00000115091 HU-09776-1 ACTR5 ARP5 actin-related protein 5 homolog (yeast) ENSG00000101442 HU-00773-1 ACTR6 ARP6 actin-related protein 6 homolog (yeast) ENSG00000075089 HU-07176-1 ACTR8 ARP8 actin-related protein 8 homolog (yeast) ENSG00000113812 HU-09411-1 AHCTF1 AT hook containing transcription factor 1 ENSG00000153207 HU-15150-1 AIRE autoimmune regulator ENSG00000160224 HU-12332-1 AKAP1 A kinase (PRKA) anchor protein 1 ENSG00000121057 HU-04065-1 ALG13 asparagine-linked glycosylation 13 homolog (S. cerevisiae) ENSG00000101901 HU-13552-1 ALKBH1 alkB, alkylation repair homolog 1 (E. coli) ENSG00000100601 HU-06662-1 ARID1A AT rich interactive domain 1A (SWI-like) ENSG00000117713 HU-12790-1 ARID1B AT rich interactive domain 1B (SWI1-like) ENSG00000049618 HU-09415-1 ARID2 AT rich interactive domain 2 (ARID, RFX-like) ENSG00000189079 HU-03890-1 ARID3A AT rich interactive domain 3A (BRIGHT-like) ENSG00000116017 HU-14677-1 ARID3B AT rich interactive domain 3B (BRIGHT-like) ENSG00000179361 HU-14203-1 ARID3C AT rich interactive domain 3C (BRIGHT-like) ENSG00000205143 HU-09104-1 ARID4A AT rich interactive domain 4A (RBP1-like) ENSG00000032219 HU-12512-1 ARID4B AT rich interactive domain 4B (RBP1-like) ENSG00000054267 HU-12520-1 ARID5A AT rich interactive domain 5A (MRF1-like) ENSG00000196843 HU-06595-1 ARID5B AT rich interactive domain 5B (MRF1-like) ENSG00000150347 HU-00556-1 ASF1A ASF1 anti-silencing function 1 homolog A (S. -
Identification of TMEM131L As a Novel Regulator of Thymocyte Proliferation in Humans
Identification of TMEM131L as a Novel Regulator of Thymocyte Proliferation in Humans This information is current as Nesrine Maharzi, Véronique Parietti, Elisabeth Nelson, of September 25, 2021. Simona Denti, Macarena Robledo-Sarmiento, Niclas Setterblad, Aude Parcelier, Marika Pla, François Sigaux, Jean Claude Gluckman and Bruno Canque J Immunol 2013; 190:6187-6197; Prepublished online 20 May 2013; Downloaded from doi: 10.4049/jimmunol.1300400 http://www.jimmunol.org/content/190/12/6187 Supplementary http://www.jimmunol.org/content/suppl/2013/05/21/jimmunol.130040 http://www.jimmunol.org/ Material 0.DC1 References This article cites 44 articles, 20 of which you can access for free at: http://www.jimmunol.org/content/190/12/6187.full#ref-list-1 Why The JI? Submit online. by guest on September 25, 2021 • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2013 by The American Association of Immunologists, -
Silkworm Z Chromosome Is Enriched in Testis-Specific Genes
Supporting Information http://www.genetics.org/cgi/content/full/genetics.108.099994/DC1 Silkworm Z Chromosome is Enriched in Testis-Specific Genes K. P. Arunkumar, Kazuei Mita and J. Nagaraju Copyright © 2009 by the Genetics Society of America DOI: 10.1534/genetics.108.099994 2 SI K. Arunkumar et al. File S1 Gene Ontology annotation GO annotation generates a dynamic controlled vocabulary that can be applied to all organisms, even while knowledge of gene and protein roles in cells is still accumulating and changing. To this end, the Seqdblite FASTA sequence flat file was downloaded from the GO database. By running BLAST against Seqdblite, closest homologue was identified. From BLAST output, molecular functions, biological processes and cellular localisation were parsed by building an in-house GO database in MySQL from the GO-term-database flat file, downloaded from Gene Ontology Database Downloads (http://www.godatabase.org/dev/). The Perl-DBI was used to interface with MySQL, to extract the parent terms of each individual GO term that are obtained by parsing BLAST output. The output was then represented graphically. All ESTs were assigned a biological process, molecular function and cellular component using Gene Ontology (GO) database. The closest annotated homologue in the GO database was used for assigning these categories. The results of the GO annotation are graphically represented in Figures S1-3. Many of the gene products were found to be localized in cell (42%). In cell, gene products were predominant in intracellular region (78%) which comprised of localizations in intracellular organelle (38%) and cytoplasm (29%). The other localizations were organelle (29%) followed by protein complex (18%) (Figure S1). -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of