I GENETIC VARIATION in the DOMESTICATED DOG AS A
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Genome Sequence, Population History, and Pelage Genetics of the Endangered African Wild Dog (Lycaon Pictus) Michael G
Campana et al. BMC Genomics (2016) 17:1013 DOI 10.1186/s12864-016-3368-9 RESEARCH ARTICLE Open Access Genome sequence, population history, and pelage genetics of the endangered African wild dog (Lycaon pictus) Michael G. Campana1,2*, Lillian D. Parker1,2,3, Melissa T. R. Hawkins1,2,3, Hillary S. Young4, Kristofer M. Helgen2,3, Micaela Szykman Gunther5, Rosie Woodroffe6, Jesús E. Maldonado1,2 and Robert C. Fleischer1 Abstract Background: The African wild dog (Lycaon pictus) is an endangered African canid threatened by severe habitat fragmentation, human-wildlife conflict, and infectious disease. A highly specialized carnivore, it is distinguished by its social structure, dental morphology, absence of dewclaws, and colorful pelage. Results: We sequenced the genomes of two individuals from populations representing two distinct ecological histories (Laikipia County, Kenya and KwaZulu-Natal Province, South Africa). We reconstructed population demographic histories for the two individuals and scanned the genomes for evidence of selection. Conclusions: We show that the African wild dog has undergone at least two effective population size reductions in the last 1,000,000 years. We found evidence of Lycaon individual-specific regions of low diversity, suggestive of inbreeding or population-specific selection. Further research is needed to clarify whether these population reductions and low diversity regions are characteristic of the species as a whole. We documented positive selection on the Lycaon mitochondrial genome. Finally, we identified several candidate genes (ASIP, MITF, MLPH, PMEL) that may play a role in the characteristic Lycaon pelage. Keywords: Lycaon pictus, Genome, Population history, Selection, Pelage Background Primarily a hunter of antelopes, the African wild dog is a The African wild dog (Lycaon pictus) is an endangered highly distinct canine. -
Broad Poster Vivek
A novel computational method for finding regions with copy number abnormalities in cancer cells Vivek, Manuel Garber, and Mike Zody Broad Institute of MIT and Harvard, Cambridge, MA, USA Introduction Results Cancer can result from the over expression of oncogenes, genes which control and regulate cell growth. Sometimes oncogenes increase in 1 2 3 activity due to a specific genetic mutation called a translocation (Fig 1). SMAD4 – a gene known to be deleted in pancreatic COX10 – a gene deleted in cytochrome c oxidase AK001392 – a hereditary prostate cancer protein This translocation allows the oncogene to remain as active as its paired carcinoma deficiency, known to be related to cell proliferation gene. Amplification of this mutation can occur, thereby creating the proper conditions for uncontrolled cell growth; consequently, each Results from Analysis Program Results from Analysis Program Results from Analysis Program component of the translocation will amplify in similar quantities. In this mutation, the chromosomal region containing the oncogene displaces to Region 1 Region 2 R2 Region 1 Region 2 R2 Region 1 Region 2 R2 a region on another chromosome containing a gene that is expressed Chr18:47044749-47311978 Chr17:13930739-14654741 0.499070821478475 Chr17:13930739-14654741 Chr18:26861790-27072166 0.47355172850856 Chr17:12542326-13930738 Chr8:1789292-1801984 0.406208680312004 frequently. Actual region containing gene Actual region containing gene Actual region containing gene chr18: 45,842,214 - 48,514,513 chr17: 13,966,862 - 14,068,461 chr17: 12,542,326 - 13,930,738 Fig 1. Two chromosomal regions (abcdef and ghijk) are translocating to create two new regions (abckl and ghijedf). -
Manual Annotation and Analysis of the Defensin Gene Cluster in the C57BL
BMC Genomics BioMed Central Research article Open Access Manual annotation and analysis of the defensin gene cluster in the C57BL/6J mouse reference genome Clara Amid*†1, Linda M Rehaume*†2, Kelly L Brown2,3, James GR Gilbert1, Gordon Dougan1, Robert EW Hancock2 and Jennifer L Harrow1 Address: 1Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, 2University of British Columbia, Centre for Microbial Disease & Immunity Research, 2259 Lower Mall, Vancouver, BC, V6T 1Z4, Canada and 3Department of Rheumatology and Inflammation Research, Göteborg University, Guldhedsgatan 10, S-413 46 Göteborg, Sweden Email: Clara Amid* - [email protected]; Linda M Rehaume* - [email protected]; Kelly L Brown - [email protected]; James GR Gilbert - [email protected]; Gordon Dougan - [email protected]; Robert EW Hancock - [email protected]; Jennifer L Harrow - [email protected] * Corresponding authors †Equal contributors Published: 15 December 2009 Received: 15 May 2009 Accepted: 15 December 2009 BMC Genomics 2009, 10:606 doi:10.1186/1471-2164-10-606 This article is available from: http://www.biomedcentral.com/1471-2164/10/606 © 2009 Amid et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: Host defense peptides are a critical component of the innate immune system. Human alpha- and beta-defensin genes are subject to copy number variation (CNV) and historically the organization of mouse alpha-defensin genes has been poorly defined. -
Supporting Online Material
1 2 3 4 5 6 7 Supplementary Information for 8 9 Fractalkine-induced microglial vasoregulation occurs within the retina and is altered early in diabetic 10 retinopathy 11 12 *Samuel A. Mills, *Andrew I. Jobling, *Michael A. Dixon, Bang V. Bui, Kirstan A. Vessey, Joanna A. Phipps, 13 Ursula Greferath, Gene Venables, Vickie H.Y. Wong, Connie H.Y. Wong, Zheng He, Flora Hui, James C. 14 Young, Josh Tonc, Elena Ivanova, Botir T. Sagdullaev, Erica L. Fletcher 15 * Joint first authors 16 17 Corresponding author: 18 Prof. Erica L. Fletcher. Department of Anatomy & Neuroscience. The University of Melbourne, Grattan St, 19 Parkville 3010, Victoria, Australia. 20 Email: [email protected] ; Tel: +61-3-8344-3218; Fax: +61-3-9347-5219 21 22 This PDF file includes: 23 24 Supplementary text 25 Figures S1 to S10 26 Tables S1 to S7 27 Legends for Movies S1 to S2 28 SI References 29 30 Other supplementary materials for this manuscript include the following: 31 32 Movies S1 to S2 33 34 35 36 1 1 Supplementary Information Text 2 Materials and Methods 3 Microglial process movement on retinal vessels 4 Dark agouti rats were anaesthetized, injected intraperitoneally with rhodamine B (Sigma-Aldrich) to label blood 5 vessels and retinal explants established as described in the main text. Retinal microglia were labelled with Iba-1 6 and imaging performed on an inverted confocal microscope (Leica SP5). Baseline images were taken for 10 7 minutes, followed by the addition of PBS (10 minutes) and then either fractalkine or fractalkine + candesartan 8 (10 minutes) using concentrations outlined in the main text. -
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. -
32-12012: Human Beta Defensin-3 Description Product
9853 Pacific Heights Blvd. Suite D. San Diego, CA 92121, USA Tel: 858-263-4982 Email: [email protected] 32-12012: Human Beta Defensin-3 Gene : DEFB103A Gene ID : 414325 Uniprot ID : P81534 Alternative Name : DEFB-3, Beta-defensin 3, Defensin, beta 103, Defensin-like protein Description Source: Genetically modified E.coli. Predicted MW: Monomer, 5.2 kDa (45 aa) Beta-Defensin 3 (BD-3), also known as DEFB-3, is a member of the defensin class of antimicrobial peptides. Beta defensins exert host defense responses against viruses, bacteria, and fungi through the binding and permeabilizing of microbial membranes. BD-3 expression is stimulated by interferon-gamma and is an important molecule during adaptive immunity. BD-3 functions to activate monocytes and mast cells, and has antibacterial functions towards Gram-negative and Gram-positive bacteria. Further, BD-3 blocks human immunodeficiency virus type 1 (HIV-1) replication through the downregulation of the HIV-1 co-receptor, CXCR4. Product Info Amount : 20 µg / 100 µg Purification : Reducing and Non-Reducing SDS PAGE at >= 95% Lyophilized from a sterile (0.2 micron) filtered aqueous solution containing 0.1% Trifluoroacetic Content : Acid (TFA) Sterile water at 0.1 mg/mL Storage condition : Store at -20°C Amino Acid : GIINTLQKYY CRVRGGRCAV LSCLPKEEQI GKCSTRGRKC CRRKK Application Note Endotoxin: Less than 0.1 ng/µg (1 IEU/µg) as determined by LAL test. Centrifuge vial before opening, Suspend the product by gently pipetting the above recommended solution down the sides of the vial. DO NOT VORTEX. Allow several minutes for complete reconstitution. For prolonged storage, dilute to working aliquots in a 0.1% BSA solution, store at -80°C and avoid repeat freeze thaws. -
Mapping DNA Structural Variation in Dogs
Downloaded from genome.cshlp.org on October 3, 2021 - Published by Cold Spring Harbor Laboratory Press Resource Mapping DNA structural variation in dogs Wei-Kang Chen,1,4 Joshua D. Swartz,1,4,5 Laura J. Rush,2 and Carlos E. Alvarez1,3,6 1Center for Molecular and Human Genetics, The Research Institute at Nationwide Children’s Hospital, Columbus, Ohio 43205, USA; 2Department of Veterinary Biosciences, The Ohio State University, Columbus, Ohio 43210, USA; 3Department of Pediatrics, The Ohio State University College of Medicine, Columbus, Ohio 43210, USA DNA structural variation (SV) comprises a major portion of genetic diversity, but its biological impact is unclear. We propose that the genetic history and extraordinary phenotypic variation of dogs make them an ideal mammal in which to study the effects of SV on biology and disease. The hundreds of existing dog breeds were created by selection of extreme morphological and behavioral traits. And along with those traits, each breed carries increased risk for different diseases. We used array CGH to create the first map of DNA copy number variation (CNV) or SV in dogs. The extent of this variation, and some of the gene classes affected, are similar to those of mice and humans. Most canine CNVs affect genes, including disease and candidate disease genes, and are thus likely to be functional. We identified many CNVs that may be breed or breed class specific. Cluster analysis of CNV regions showed that dog breeds tend to group according to breed classes. Our combined findings suggest many CNVs are (1) in linkage disequilibrium with flanking sequence, and (2) associated with breed-specific traits. -
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Supplementary Figure S1. Results of flow cytometry analysis, performed to estimate CD34 positivity, after immunomagnetic separation in two different experiments. As monoclonal antibody for labeling the sample, the fluorescein isothiocyanate (FITC)- conjugated mouse anti-human CD34 MoAb (Mylteni) was used. Briefly, cell samples were incubated in the presence of the indicated MoAbs, at the proper dilution, in PBS containing 5% FCS and 1% Fc receptor (FcR) blocking reagent (Miltenyi) for 30 min at 4 C. Cells were then washed twice, resuspended with PBS and analyzed by a Coulter Epics XL (Coulter Electronics Inc., Hialeah, FL, USA) flow cytometer. only use Non-commercial 1 Supplementary Table S1. Complete list of the datasets used in this study and their sources. GEO Total samples Geo selected GEO accession of used Platform Reference series in series samples samples GSM142565 GSM142566 GSM142567 GSM142568 GSE6146 HG-U133A 14 8 - GSM142569 GSM142571 GSM142572 GSM142574 GSM51391 GSM51392 GSE2666 HG-U133A 36 4 1 GSM51393 GSM51394 only GSM321583 GSE12803 HG-U133A 20 3 GSM321584 2 GSM321585 use Promyelocytes_1 Promyelocytes_2 Promyelocytes_3 Promyelocytes_4 HG-U133A 8 8 3 GSE64282 Promyelocytes_5 Promyelocytes_6 Promyelocytes_7 Promyelocytes_8 Non-commercial 2 Supplementary Table S2. Chromosomal regions up-regulated in CD34+ samples as identified by the LAP procedure with the two-class statistics coded in the PREDA R package and an FDR threshold of 0.5. Functional enrichment analysis has been performed using DAVID (http://david.abcc.ncifcrf.gov/) -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Predicting Gene Ontology Biological Process from Temporal Gene Expression Patterns Astrid Lægreid,1,4 Torgeir R
Methods Predicting Gene Ontology Biological Process From Temporal Gene Expression Patterns Astrid Lægreid,1,4 Torgeir R. Hvidsten,2 Herman Midelfart,2 Jan Komorowski,2,3,4 and Arne K. Sandvik1 1Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, N-7489 Trondheim, Norway; 2Department of Information and Computer Science, Norwegian University of Science and Technology, N-7491 Trondheim, Norway; 3The Linnaeus Centre for Bioinformatics, Uppsala University, SE-751 24 Uppsala, Sweden The aim of the present study was to generate hypotheses on the involvement of uncharacterized genes in biological processes. To this end,supervised learning was used to analyz e microarray-derived time-series gene expression data. Our method was objectively evaluated on known genes using cross-validation and provided high-precision Gene Ontology biological process classifications for 211 of the 213 uncharacterized genes in the data set used. In addition,new roles in biological process were hypothesi zed for known genes. Our method uses biological knowledge expressed by Gene Ontology and generates a rule model associating this knowledge with minimal characteristic features of temporal gene expression profiles. This model allows learning and classification of multiple biological process roles for each gene and can predict participation of genes in a biological process even though the genes of this class exhibit a wide variety of gene expression profiles including inverse coregulation. A considerable number of the hypothesized new roles for known genes were confirmed by literature search. In addition,many biological process roles hypothesi zed for uncharacterized genes were found to agree with assumptions based on homology information. -
Role of Amylase in Ovarian Cancer Mai Mohamed University of South Florida, [email protected]
University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School July 2017 Role of Amylase in Ovarian Cancer Mai Mohamed University of South Florida, [email protected] Follow this and additional works at: http://scholarcommons.usf.edu/etd Part of the Pathology Commons Scholar Commons Citation Mohamed, Mai, "Role of Amylase in Ovarian Cancer" (2017). Graduate Theses and Dissertations. http://scholarcommons.usf.edu/etd/6907 This Dissertation is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Role of Amylase in Ovarian Cancer by Mai Mohamed A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Pathology and Cell Biology Morsani College of Medicine University of South Florida Major Professor: Patricia Kruk, Ph.D. Paula C. Bickford, Ph.D. Meera Nanjundan, Ph.D. Marzenna Wiranowska, Ph.D. Lauri Wright, Ph.D. Date of Approval: June 29, 2017 Keywords: ovarian cancer, amylase, computational analyses, glycocalyx, cellular invasion Copyright © 2017, Mai Mohamed Dedication This dissertation is dedicated to my parents, Ahmed and Fatma, who have always stressed the importance of education, and, throughout my education, have been my strongest source of encouragement and support. They always believed in me and I am eternally grateful to them. I would also like to thank my brothers, Mohamed and Hussien, and my sister, Mariam. I would also like to thank my husband, Ahmed. -
Angiopoietin 4 (ANGPT4) (NM 015985) Human Untagged Clone Product Data
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 SC304373 Angiopoietin 4 (ANGPT4) (NM_015985) Human Untagged Clone Product data: Product Type: Expression Plasmids Product Name: Angiopoietin 4 (ANGPT4) (NM_015985) Human Untagged Clone Tag: Tag Free Symbol: ANGPT4 Synonyms: ANG3; ANG4 Vector: pCMV6-XL5 E. coli Selection: Ampicillin (100 ug/mL) Cell Selection: None 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 / 3 Angiopoietin 4 (ANGPT4) (NM_015985) Human Untagged Clone – SC304373 Fully Sequenced ORF: >OriGene sequence for NM_015985 edited CAGGCAAGCCTGGCCACTGTTGGCTGCAGCAGGACATCCCAGGCACAGCCCCTAGGGCTC TGAGCAGACATCCCTCGCCATTGACACATCTTCAGATGCTCTCCCAGCTAGCCATGCTGC AGGGCAGCCTCCTCCTTGTGGTTGCCACCATGTCTGTGGCTCAACAGACAAGGCAGGAGG CGGATAGGGGCTGCGAGACACTTGTAGTCCAGCACGGCCACTGTAGCTACACCTTCTTGC TGCCCAAGTCTGAGCCCTGCCCTCCGGGGCCTGAGGTCTCCAGGGACTCCAACACCCTCC AGAGAGAATCACTGGCCAACCCACTGCACCTGGGGAAGTTGCCCACCCAGCAGGTGAAAC AGCTGGAGCAGGCACTGCAGAACAACACGCAGTGGCTGAAGAAGCTAGAGAGGGCCATCA AGACGATCTTGAGGTCGAAGCTGGAGCAGGTCCAGCAGCAAATGGCCCAGAATCAGACGG CCCCCATGCTAGAGCTGGGCACCAGCCTCCTGAACCAGACCACTGCCCAGATCCGCAAGC TGACCGACATGGAGGCTCAGCTCCTGAACCAGACATCAAGAATGGATGCCCAGATGCCAG AGACCTTTCTGTCCACCAACAAGCTGGAGAACCAGCTGCTGCTACAGAGGCAGAAGCTCC AGCAGCTTCAGGGCCAAAACAGCGCGCTCGAGAAGCGGTTGCAGGCCCTGGAGACCAAGC