Chromosome 21 Leading Edge Gene Set
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SAN TA C RUZ BI OTEC HNOL OG Y, INC . DIP2A (L-16): sc-67555 BACKGROUND APPLICATIONS DIP2A (Disco-interacting protein 2 homolog A), also known as DIP2, is a 1,571 DIP2A (L-16) is recommended for detection of DIP2A of human origin by amino acid nuclear protein. It is one of three human homologs (DIP2A, DIP2B Western Blotting (starting dilution 1:200, dilution range 1:100-1:1000), and DIP2C) of the Drosophila dip2 (disconnected-interacting protein 2) protein. immunoprecipitation [1-2 µg per 100-500 µg of total protein (1 ml of cell In Drosophila , dip2 interacts with disco, a protein required for neuronal con - lysate)], immunofluorescence (starting dilution 1:50, dilution range 1:50- nections in the visual systems of larvae and adults. The closest vertebrate 1:500) and solid phase ELISA (starting dilution 1:30, dilution range 1:30- homologs to disco are the basonuclin genes. In mice, DIP2 homologs show 1:3000). restricted expression to the brain. This suggests that, similar to the function DIP2A (L-16) is also recommended for detection of DIP2A, also designated of Drosphila dip2, vertebrate DIP2 homologs may play a role in the develop - Disco-interacting protein 2 homolog A, in additional species, including ment of the nervous system. Expressed ubiquitously with highest expression canine. in the brain, DIP2A is thought to function in signaling throughout the central nervous system by providing positional clues for axon patterning and pathfind - Suitable for use as control antibody for DIP2A siRNA (h): sc-62212, DIP2A ing . Four isoforms of DIP2A exist due to alternative splicing events. -
A Regulator of Aldosterone Synthesis in Human Adrenocortical Tissues
S J A FELIZOLA and others PCP4: a regulator of aldosterone 52:2 159–167 Research synthesis PCP4: a regulator of aldosterone synthesis in human adrenocortical tissues Saulo J A Felizola, Yasuhiro Nakamura, Yoshikiyo Ono1, Kanako Kitamura, Kumi Kikuchi1, Yoshiaki Onodera, Kazue Ise, Kei Takase2, Akira Sugawara3, Namita Hattangady4, William E Rainey4, Fumitoshi Satoh1 and Hironobu Sasano Department of Pathology, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, Correspondence Miyagi 980-8575, Japan should be addressed 1Division of Nephrology, Endocrinology and Vascular Medicine, Tohoku University Hospital, Sendai, Japan to Y Nakamura Departments of 2Diagnostic Radiology 3Molecular Endocrinology, Tohoku University Graduate School of Medicine, Email 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8575, Japan yasu-naka@ 4Department of Physiology and Medicine, University of Michigan, Ann Arbor, Michigan, USA patholo2.med.tohoku.ac.jp Abstract Purkinje cell protein 4 (PCP4) is a calmodulin (CaM)-binding protein that accelerates calcium Key Words association and dissociation with CaM. It has been previously detected in aldosterone- " Purkinje cell protein 4 (PCP4) producing adenomas (APA), but details on its expression and function in adrenocortical " adrenal cortex tissues have remained unknown. Therefore, we performed the immunohistochemical " aldosterone analysis of PCP4 in the following tissues: normal adrenal (NA; nZ15), APA (nZ15), cortisol- " calmodulin (CaM) producing adenomas (nZ15), and idiopathic hyperaldosteronism cases (IHA; nZ5). APA " CYP11B2 samples (nZ45) were also submitted to quantitative RT-PCR of PCP4, CYP11B1, and CYP11B2, Journal of Molecular Endocrinology as well as DNA sequencing for KCNJ5 mutations. Transient transfection analysis using PCP4 siRNA was also performed in H295R adrenocortical carcinoma cells, following ELISA analysis, and CYP11B2 luciferase assays were also performed after PCP4 vector transfection in order to study the regulation of PCP4 protein expression. -
A Comparative Analysis of Transcribed Genes in the Mouse Hypothalamus and Neocortex Reveals Chromosomal Clustering
A comparative analysis of transcribed genes in the mouse hypothalamus and neocortex reveals chromosomal clustering Wee-Ming Boon*, Tim Beissbarth†, Lavinia Hyde†, Gordon Smyth†, Jenny Gunnersen*, Derek A. Denton*‡, Hamish Scott†, and Seong-Seng Tan* *Howard Florey Institute, University of Melbourne, Parkville 3052, Australia; and †Genetics and Bioinfomatics Division, Walter and Eliza Hall Institute of Medical Research, Royal Parade, Parkville 3050, Australia Contributed by Derek A. Denton, August 26, 2004 The hypothalamus and neocortex are subdivisions of the mamma- representing all of the genes that are expressed (qualitative and lian forebrain, and yet, they have vastly different evolutionary quantitative) in the hypothalamus and neocortex under standard histories, cytoarchitecture, and biological functions. In an attempt conditions. to define these attributes in terms of their genetic activity, we have In the current study, we describe the use of the Serial Analysis compared their genetic repertoires by using the Serial Analysis of of Gene Expression (SAGE) database, which allows simulta- Gene Expression database. From a comparison of 78,784 hypothal- neous detection of the expression levels of the entire genome amus tags with 125,296 neocortical tags, we demonstrate that each without a priori knowledge of gene sequences (13). SAGE takes structure possesses a different transcriptional profile in terms of advantage of the fact that a small sequence tag taken from a gene ontological characteristics and expression levels. Despite its defined position within the transcript is sufficient to identify the more recent evolutionary history, the neocortex has a more com- gene (from known cDNA or EST sequences), and up to 40 tags plex pattern of gene activity. -
Genome Wide Association Study of Response to Interval and Continuous Exercise Training: the Predict‑HIIT Study Camilla J
Williams et al. J Biomed Sci (2021) 28:37 https://doi.org/10.1186/s12929-021-00733-7 RESEARCH Open Access Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study Camilla J. Williams1†, Zhixiu Li2†, Nicholas Harvey3,4†, Rodney A. Lea4, Brendon J. Gurd5, Jacob T. Bonafglia5, Ioannis Papadimitriou6, Macsue Jacques6, Ilaria Croci1,7,20, Dorthe Stensvold7, Ulrik Wislof1,7, Jenna L. Taylor1, Trishan Gajanand1, Emily R. Cox1, Joyce S. Ramos1,8, Robert G. Fassett1, Jonathan P. Little9, Monique E. Francois9, Christopher M. Hearon Jr10, Satyam Sarma10, Sylvan L. J. E. Janssen10,11, Emeline M. Van Craenenbroeck12, Paul Beckers12, Véronique A. Cornelissen13, Erin J. Howden14, Shelley E. Keating1, Xu Yan6,15, David J. Bishop6,16, Anja Bye7,17, Larisa M. Haupt4, Lyn R. Grifths4, Kevin J. Ashton3, Matthew A. Brown18, Luciana Torquati19, Nir Eynon6 and Jef S. Coombes1* Abstract Background: Low cardiorespiratory ftness (V̇O2peak) is highly associated with chronic disease and mortality from all causes. Whilst exercise training is recommended in health guidelines to improve V̇O2peak, there is considerable inter-individual variability in the V̇O2peak response to the same dose of exercise. Understanding how genetic factors contribute to V̇O2peak training response may improve personalisation of exercise programs. The aim of this study was to identify genetic variants that are associated with the magnitude of V̇O2peak response following exercise training. Methods: Participant change in objectively measured V̇O2peak from 18 diferent interventions was obtained from a multi-centre study (Predict-HIIT). A genome-wide association study was completed (n 507), and a polygenic predictor score (PPS) was developed using alleles from single nucleotide polymorphisms= (SNPs) signifcantly associ- –5 ated (P < 1 10 ) with the magnitude of V̇O2peak response. -
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. -
The 50Th Anniversary of the Discovery of Trisomy 21: the Past, Present, and Future of Research and Treatment of Down Syndrome
REVIEW The 50th anniversary of the discovery of trisomy 21: The past, present, and future of research and treatment of Down syndrome Andre´Me´garbane´, MD, PhD1,2, Aime´ Ravel, MD1, Clotilde Mircher, MD1, Franck Sturtz, MD, PhD1,3, Yann Grattau, MD1, Marie-Odile Rethore´, MD1, Jean-Maurice Delabar, PhD4, and William C. Mobley, MD, PhD5 Abstract: Trisomy 21 or Down syndrome is a chromosomal disorder HISTORICAL REVIEW resulting from the presence of all or part of an extra Chromosome 21. Clinical description It is a common birth defect, the most frequent and most recognizable By examining artifacts from the Tumaco-La Tolita culture, form of mental retardation, appearing in about 1 of every 700 newborns. which existed on the border between current Colombia and Although the syndrome had been described thousands of years before, Ecuador approximately 2500 years ago, Bernal and Briceno2 it was named after John Langdon Down who reported its clinical suspected that certain figurines depicted individuals with Tri- description in 1866. The suspected association of Down syndrome with somy 21, making these potteries the earliest evidence for the a chromosomal abnormality was confirmed by Lejeune et al. in 1959. existence of the syndrome. Martinez-Frias3 identified the syn- Fifty years after the discovery of the origin of Down syndrome, the term drome in a terra-cotta head from the Tolteca culture of Mexico “mongolism” is still inappropriately used; persons with Down syn- in 500 patients with AD in which the facial features of Trisomy drome are still institutionalized. Health problems associated with that 21 are clearly displayed. -
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, -
Enzyme DHRS7
Toward the identification of a function of the “orphan” enzyme DHRS7 Inauguraldissertation zur Erlangung der Würde eines Doktors der Philosophie vorgelegt der Philosophisch-Naturwissenschaftlichen Fakultät der Universität Basel von Selene Araya, aus Lugano, Tessin Basel, 2018 Originaldokument gespeichert auf dem Dokumentenserver der Universität Basel edoc.unibas.ch Genehmigt von der Philosophisch-Naturwissenschaftlichen Fakultät auf Antrag von Prof. Dr. Alex Odermatt (Fakultätsverantwortlicher) und Prof. Dr. Michael Arand (Korreferent) Basel, den 26.6.2018 ________________________ Dekan Prof. Dr. Martin Spiess I. List of Abbreviations 3α/βAdiol 3α/β-Androstanediol (5α-Androstane-3α/β,17β-diol) 3α/βHSD 3α/β-hydroxysteroid dehydrogenase 17β-HSD 17β-Hydroxysteroid Dehydrogenase 17αOHProg 17α-Hydroxyprogesterone 20α/βOHProg 20α/β-Hydroxyprogesterone 17α,20α/βdiOHProg 20α/βdihydroxyprogesterone ADT Androgen deprivation therapy ANOVA Analysis of variance AR Androgen Receptor AKR Aldo-Keto Reductase ATCC American Type Culture Collection CAM Cell Adhesion Molecule CYP Cytochrome P450 CBR1 Carbonyl reductase 1 CRPC Castration resistant prostate cancer Ct-value Cycle threshold-value DHRS7 (B/C) Dehydrogenase/Reductase Short Chain Dehydrogenase Family Member 7 (B/C) DHEA Dehydroepiandrosterone DHP Dehydroprogesterone DHT 5α-Dihydrotestosterone DMEM Dulbecco's Modified Eagle's Medium DMSO Dimethyl Sulfoxide DTT Dithiothreitol E1 Estrone E2 Estradiol ECM Extracellular Membrane EDTA Ethylenediaminetetraacetic acid EMT Epithelial-mesenchymal transition ER Endoplasmic Reticulum ERα/β Estrogen Receptor α/β FBS Fetal Bovine Serum 3 FDR False discovery rate FGF Fibroblast growth factor HEPES 4-(2-Hydroxyethyl)-1-Piperazineethanesulfonic Acid HMDB Human Metabolome Database HPLC High Performance Liquid Chromatography HSD Hydroxysteroid Dehydrogenase IC50 Half-Maximal Inhibitory Concentration LNCaP Lymph node carcinoma of the prostate mRNA Messenger Ribonucleic Acid n.d. -
Role of Phytochemicals in Colon Cancer Prevention: a Nutrigenomics Approach
Role of phytochemicals in colon cancer prevention: a nutrigenomics approach Marjan J van Erk Promotor: Prof. Dr. P.J. van Bladeren Hoogleraar in de Toxicokinetiek en Biotransformatie Wageningen Universiteit Co-promotoren: Dr. Ir. J.M.M.J.G. Aarts Universitair Docent, Sectie Toxicologie Wageningen Universiteit Dr. Ir. B. van Ommen Senior Research Fellow Nutritional Systems Biology TNO Voeding, Zeist Promotiecommissie: Prof. Dr. P. Dolara University of Florence, Italy Prof. Dr. J.A.M. Leunissen Wageningen Universiteit Prof. Dr. J.C. Mathers University of Newcastle, United Kingdom Prof. Dr. M. Müller Wageningen Universiteit Dit onderzoek is uitgevoerd binnen de onderzoekschool VLAG Role of phytochemicals in colon cancer prevention: a nutrigenomics approach Marjan Jolanda van Erk Proefschrift ter verkrijging van graad van doctor op gezag van de rector magnificus van Wageningen Universiteit, Prof.Dr.Ir. L. Speelman, in het openbaar te verdedigen op vrijdag 1 oktober 2004 des namiddags te vier uur in de Aula Title Role of phytochemicals in colon cancer prevention: a nutrigenomics approach Author Marjan Jolanda van Erk Thesis Wageningen University, Wageningen, the Netherlands (2004) with abstract, with references, with summary in Dutch ISBN 90-8504-085-X ABSTRACT Role of phytochemicals in colon cancer prevention: a nutrigenomics approach Specific food compounds, especially from fruits and vegetables, may protect against development of colon cancer. In this thesis effects and mechanisms of various phytochemicals in relation to colon cancer prevention were studied through application of large-scale gene expression profiling. Expression measurement of thousands of genes can yield a more complete and in-depth insight into the mode of action of the compounds. -
Genetic Analysis of Over One Million People Identifies 535 New Loci Associated with Blood 2 Pressure Traits
1 Genetic analysis of over one million people identifies 535 new loci associated with blood 2 pressure traits. 3 4 Table of Contents 5 SUPPLEMENTARY TABLES LEGENDS……………………………………………………………………………….…….3 6 SUPPLEMENTARY FIGURES LEGENDS ........................................................................................ 6 7 SUPPLEMENTARY METHODS ................................................................................................... 10 8 1. UK Biobank data .................................................................................................................................... 10 9 2. UKB Quality Control ............................................................................................................................... 10 10 3. Phenotypic data ..................................................................................................................................... 11 11 4. UKB analysis ........................................................................................................................................... 11 12 5. Genomic inflation and confounding ....................................................................................................... 12 13 6. International Consortium for Blood Pressure (ICBP) GWAS .................................................................... 12 14 7. Meta-analyses of discovery datasets ..................................................................................................... 13 15 8. Linkage Disequilibrium calculations ...................................................................................................... -
V45n4a03.Pdf
Montoya JC/et al/Colombia Médica - Vol. 45 Nº4 2014 (Oct-Dec) Colombia Médica colombiamedica.univalle.edu.co Original Article Global differential expression of genes located in the Down Syndrome Critical Region in normal human brain Expresión diferencial global de genes localizados en la Región Crítica del Síndrome de Down en el cerebro humano normal Julio Cesar Montoya1,3, Dianora Fajardo2, Angela Peña2 , Adalberto Sánchez1, Martha C Domínguez1,2, José María Satizábal1, Felipe García-Vallejo1,2 1 Department of Physiological Sciences, School of Basic Sciences, Faculty of Health, Universidad del Valle. 2 Laboratory of Molecular Biology and Pathogenesis LABIOMOL. Universidad del Valle, Cali, Colombia. 3 Faculty of Basic Sciences, Universidad Autónoma de Occidente, Cali, Colombia. Montoya JC , Fajardo D, Peña A , Sánchez A, Domínguez MC, Satizábal JM, García-Vallejo F.. Global differential expression of genes located in the Down Syndrome Critical Region in normal human brain. Colomb Med. 2014; 45(4): 154-61. © 2014 Universidad del Valle. This is an Open Access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Article history Abstract Resumen Background: The information of gene expression obtained from Introducción: La información de la expresión de genes consignada Received: 2 July 2014 Revised: 10 November 2014 databases, have made possible the extraction and analysis of data en bases de datos, ha permitido extraer y analizar información acerca Accepted: 19 December 2014 related with several molecular processes involving not only in procesos moleculares implicados tanto en la homeostasis cerebral y su brain homeostasis but its disruption in some neuropathologies; alteración en algunas neuropatologías. -
NICU Gene List Generator.Xlsx
Neonatal Crisis Sequencing Panel Gene List Genes: A2ML1 - B3GLCT A2ML1 ADAMTS9 ALG1 ARHGEF15 AAAS ADAMTSL2 ALG11 ARHGEF9 AARS1 ADAR ALG12 ARID1A AARS2 ADARB1 ALG13 ARID1B ABAT ADCY6 ALG14 ARID2 ABCA12 ADD3 ALG2 ARL13B ABCA3 ADGRG1 ALG3 ARL6 ABCA4 ADGRV1 ALG6 ARMC9 ABCB11 ADK ALG8 ARPC1B ABCB4 ADNP ALG9 ARSA ABCC6 ADPRS ALK ARSL ABCC8 ADSL ALMS1 ARX ABCC9 AEBP1 ALOX12B ASAH1 ABCD1 AFF3 ALOXE3 ASCC1 ABCD3 AFF4 ALPK3 ASH1L ABCD4 AFG3L2 ALPL ASL ABHD5 AGA ALS2 ASNS ACAD8 AGK ALX3 ASPA ACAD9 AGL ALX4 ASPM ACADM AGPS AMELX ASS1 ACADS AGRN AMER1 ASXL1 ACADSB AGT AMH ASXL3 ACADVL AGTPBP1 AMHR2 ATAD1 ACAN AGTR1 AMN ATL1 ACAT1 AGXT AMPD2 ATM ACE AHCY AMT ATP1A1 ACO2 AHDC1 ANK1 ATP1A2 ACOX1 AHI1 ANK2 ATP1A3 ACP5 AIFM1 ANKH ATP2A1 ACSF3 AIMP1 ANKLE2 ATP5F1A ACTA1 AIMP2 ANKRD11 ATP5F1D ACTA2 AIRE ANKRD26 ATP5F1E ACTB AKAP9 ANTXR2 ATP6V0A2 ACTC1 AKR1D1 AP1S2 ATP6V1B1 ACTG1 AKT2 AP2S1 ATP7A ACTG2 AKT3 AP3B1 ATP8A2 ACTL6B ALAS2 AP3B2 ATP8B1 ACTN1 ALB AP4B1 ATPAF2 ACTN2 ALDH18A1 AP4M1 ATR ACTN4 ALDH1A3 AP4S1 ATRX ACVR1 ALDH3A2 APC AUH ACVRL1 ALDH4A1 APTX AVPR2 ACY1 ALDH5A1 AR B3GALNT2 ADA ALDH6A1 ARFGEF2 B3GALT6 ADAMTS13 ALDH7A1 ARG1 B3GAT3 ADAMTS2 ALDOB ARHGAP31 B3GLCT Updated: 03/15/2021; v.3.6 1 Neonatal Crisis Sequencing Panel Gene List Genes: B4GALT1 - COL11A2 B4GALT1 C1QBP CD3G CHKB B4GALT7 C3 CD40LG CHMP1A B4GAT1 CA2 CD59 CHRNA1 B9D1 CA5A CD70 CHRNB1 B9D2 CACNA1A CD96 CHRND BAAT CACNA1C CDAN1 CHRNE BBIP1 CACNA1D CDC42 CHRNG BBS1 CACNA1E CDH1 CHST14 BBS10 CACNA1F CDH2 CHST3 BBS12 CACNA1G CDK10 CHUK BBS2 CACNA2D2 CDK13 CILK1 BBS4 CACNB2 CDK5RAP2