Analysis of the Impact of Population Copy Number Variation in Introns
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ASSESSING DIAGNOSTIC and THERAPEUTIC TARGETS in OBESITY- ASSOCIATED LIVER DISEASES Noemí Cabré Casares
ASSESSING DIAGNOSTIC AND THERAPEUTIC TARGETS IN OBESITY- ASSOCIATED LIVER DISEASES Noemí Cabré Casares ADVERTIMENT. L'accés als continguts d'aquesta tesi doctoral i la seva utilització ha de respectar els drets de la persona autora. Pot ser utilitzada per a consulta o estudi personal, així com en activitats o materials d'investigació i docència en els termes establerts a l'art. 32 del Text Refós de la Llei de Propietat Intel·lectual (RDL 1/1996). Per altres utilitzacions es requereix l'autorització prèvia i expressa de la persona autora. En qualsevol cas, en la utilització dels seus continguts caldrà indicar de forma clara el nom i cognoms de la persona autora i el títol de la tesi doctoral. No s'autoritza la seva reproducció o altres formes d'explotació efectuades amb finalitats de lucre ni la seva comunicació pública des d'un lloc aliè al servei TDX. Tampoc s'autoritza la presentació del seu contingut en una finestra o marc aliè a TDX (framing). Aquesta reserva de drets afecta tant als continguts de la tesi com als seus resums i índexs. ADVERTENCIA. El acceso a los contenidos de esta tesis doctoral y su utilización debe respetar los derechos de la persona autora. Puede ser utilizada para consulta o estudio personal, así como en actividades o materiales de investigación y docencia en los términos establecidos en el art. 32 del Texto Refundido de la Ley de Propiedad Intelectual (RDL 1/1996). Para otros usos se requiere la autorización previa y expresa de la persona autora. En cualquier caso, en la utilización de sus contenidos se deberá indicar de forma clara el nombre y apellidos de la persona autora y el título de la tesis doctoral. -
Frontiers in Integrative Genomics and Translational Bioinformatics
BioMed Research International Frontiers in Integrative Genomics and Translational Bioinformatics Guest Editors: Zhongming Zhao, Victor X. Jin, Yufei Huang, Chittibabu Guda, and Jianhua Ruan Frontiers in Integrative Genomics and Translational Bioinformatics BioMed Research International Frontiers in Integrative Genomics and Translational Bioinformatics Guest Editors: Zhongming Zhao, Victor X. Jin, Yufei Huang, Chittibabu Guda, and Jianhua Ruan Copyright © òýÔ Hindawi Publishing Corporation. All rights reserved. is is a special issue published in “BioMed Research International.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Contents Frontiers in Integrative Genomics and Translational Bioinformatics, Zhongming Zhao, Victor X. Jin, Yufei Huang, Chittibabu Guda, and Jianhua Ruan Volume òýÔ , Article ID Þò ¥ÀÔ, ç pages Building Integrated Ontological Knowledge Structures with Ecient Approximation Algorithms, Yang Xiang and Sarath Chandra Janga Volume òýÔ , Article ID ýÔ ò, Ô¥ pages Predicting Drug-Target Interactions via Within-Score and Between-Score, Jian-Yu Shi, Zun Liu, Hui Yu, and Yong-Jun Li Volume òýÔ , Article ID ç ýÀç, À pages RNAseq by Total RNA Library Identies Additional RNAs Compared to Poly(A) RNA Library, Yan Guo, Shilin Zhao, Quanhu Sheng, Mingsheng Guo, Brian Lehmann, Jennifer Pietenpol, David C. Samuels, and Yu Shyr Volume òýÔ , Article ID âòÔçý, À pages Construction of Pancreatic Cancer Classier Based on SVM Optimized by Improved FOA, Huiyan Jiang, Di Zhao, Ruiping Zheng, and Xiaoqi Ma Volume òýÔ , Article ID ÞÔýòç, Ôò pages OperomeDB: A Database of Condition-Specic Transcription Units in Prokaryotic Genomes, Kashish Chetal and Sarath Chandra Janga Volume òýÔ , Article ID çÔòÔÞ, Ôý pages How to Choose In Vitro Systems to Predict In Vivo Drug Clearance: A System Pharmacology Perspective, Lei Wang, ChienWei Chiang, Hong Liang, Hengyi Wu, Weixing Feng, Sara K. -
C12) United States Patent (IO) Patent No.: US 10,774,349 B2 San Et Al
I1111111111111111 1111111111 111111111111111 IIIII IIIII IIIII IIIIII IIII IIII IIII US010774349B2 c12) United States Patent (IO) Patent No.: US 10,774,349 B2 San et al. (45) Date of Patent: Sep.15,2020 (54) ALPHA OMEGA BIFUNCTIONAL FATTY 9/1029 (2013.01); C12N 9/13 (2013.01); ACIDS C12N 9/16 (2013.01); C12N 9/88 (2013.01); C12N 9/93 (2013.01) (71) Applicant: William Marsh Rice University, (58) Field of Classification Search Houston, TX (US) None See application file for complete search history. (72) Inventors: Ka-Yiu San, Houston, TX (US); Dan Wang, Houston, TX (US) (56) References Cited (73) Assignee: William Marsh Rice University, U.S. PATENT DOCUMENTS Houston, TX (US) 9,994,881 B2 * 6/2018 Gonzalez . Cl2N 9/0006 2016/0090576 Al 3/2016 Garg et al. ( *) Notice: Subject to any disclaimer, the term ofthis patent is extended or adjusted under 35 FOREIGN PATENT DOCUMENTS U.S.C. 154(b) by 152 days. WO W02000075343 12/2000 (21) Appl. No.: 15/572,099 WO W02016179572 11/2016 (22) PCT Filed: May 7, 2016 OTHER PUBLICATIONS (86) PCT No.: PCT/US2016/031386 Choi, K. H., R. J. Heath, and C. 0. Rock. 2000. 13-Ketoacyl-acyl carrier protein synthase III (FabH) is a determining factor in § 371 (c)(l), branched-chain fatty acid biosynthesis. J. Bacteriol. 182:365-370. (2) Date: Nov. 6, 2017 He, X., and K. A. Reynolds. 2002. Purification, characterization, and identification of novel inhibitors of the beta-ketoacyl-acyl (87) PCT Pub. No.: WO2016/179572 carrier protein synthase III (FabH) from Staphylococcus aureus. -
The Molecular Karyotype of 25 Clinical-Grade Human Embryonic Stem Cell Lines Received: 07 August 2015 1 1 2 3,4 Accepted: 27 October 2015 Maurice A
www.nature.com/scientificreports OPEN The Molecular Karyotype of 25 Clinical-Grade Human Embryonic Stem Cell Lines Received: 07 August 2015 1 1 2 3,4 Accepted: 27 October 2015 Maurice A. Canham , Amy Van Deusen , Daniel R. Brison , Paul A. De Sousa , 3 5 6 5 7 Published: 26 November 2015 Janet Downie , Liani Devito , Zoe A. Hewitt , Dusko Ilic , Susan J. Kimber , Harry D. Moore6, Helen Murray3 & Tilo Kunath1 The application of human embryonic stem cell (hESC) derivatives to regenerative medicine is now becoming a reality. Although the vast majority of hESC lines have been derived for research purposes only, about 50 lines have been established under Good Manufacturing Practice (GMP) conditions. Cell types differentiated from these designated lines may be used as a cell therapy to treat macular degeneration, Parkinson’s, Huntington’s, diabetes, osteoarthritis and other degenerative conditions. It is essential to know the genetic stability of the hESC lines before progressing to clinical trials. We evaluated the molecular karyotype of 25 clinical-grade hESC lines by whole-genome single nucleotide polymorphism (SNP) array analysis. A total of 15 unique copy number variations (CNVs) greater than 100 kb were detected, most of which were found to be naturally occurring in the human population and none were associated with culture adaptation. In addition, three copy-neutral loss of heterozygosity (CN-LOH) regions greater than 1 Mb were observed and all were relatively small and interstitial suggesting they did not arise in culture. The large number of available clinical-grade hESC lines with defined molecular karyotypes provides a substantial starting platform from which the development of pre-clinical and clinical trials in regenerative medicine can be realised. -
Dual Proteome-Scale Networks Reveal Cell-Specific Remodeling of the Human Interactome
bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 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. Dual Proteome-scale Networks Reveal Cell-specific Remodeling of the Human Interactome Edward L. Huttlin1*, Raphael J. Bruckner1,3, Jose Navarrete-Perea1, Joe R. Cannon1,4, Kurt Baltier1,5, Fana Gebreab1, Melanie P. Gygi1, Alexandra Thornock1, Gabriela Zarraga1,6, Stanley Tam1,7, John Szpyt1, Alexandra Panov1, Hannah Parzen1,8, Sipei Fu1, Arvene Golbazi1, Eila Maenpaa1, Keegan Stricker1, Sanjukta Guha Thakurta1, Ramin Rad1, Joshua Pan2, David P. Nusinow1, Joao A. Paulo1, Devin K. Schweppe1, Laura Pontano Vaites1, J. Wade Harper1*, Steven P. Gygi1*# 1Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA. 2Broad Institute, Cambridge, MA, 02142, USA. 3Present address: ICCB-Longwood Screening Facility, Harvard Medical School, Boston, MA, 02115, USA. 4Present address: Merck, West Point, PA, 19486, USA. 5Present address: IQ Proteomics, Cambridge, MA, 02139, USA. 6Present address: Vor Biopharma, Cambridge, MA, 02142, USA. 7Present address: Rubius Therapeutics, Cambridge, MA, 02139, USA. 8Present address: RPS North America, South Kingstown, RI, 02879, USA. *Correspondence: [email protected] (E.L.H.), [email protected] (J.W.H.), [email protected] (S.P.G.) #Lead Contact: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
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. -
A Clinicopathological and Molecular Genetic Analysis of Low-Grade Glioma in Adults
A CLINICOPATHOLOGICAL AND MOLECULAR GENETIC ANALYSIS OF LOW-GRADE GLIOMA IN ADULTS Presented by ANUSHREE SINGH MSc A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy Brain Tumour Research Centre Research Institute in Healthcare Sciences Faculty of Science and Engineering University of Wolverhampton November 2014 i DECLARATION This work or any part thereof has not previously been presented in any form to the University or to any other body whether for the purposes of assessment, publication or for any other purpose (unless otherwise indicated). Save for any express acknowledgments, references and/or bibliographies cited in the work, I confirm that the intellectual content of the work is the result of my own efforts and of no other person. The right of Anushree Singh to be identified as author of this work is asserted in accordance with ss.77 and 78 of the Copyright, Designs and Patents Act 1988. At this date copyright is owned by the author. Signature: Anushree Date: 30th November 2014 ii ABSTRACT The aim of the study was to identify molecular markers that can determine progression of low grade glioma. This was done using various approaches such as IDH1 and IDH2 mutation analysis, MGMT methylation analysis, copy number analysis using array comparative genomic hybridisation and identification of differentially expressed miRNAs using miRNA microarray analysis. IDH1 mutation was present at a frequency of 71% in low grade glioma and was identified as an independent marker for improved OS in a multivariate analysis, which confirms the previous findings in low grade glioma studies. -
In Vivo Dual RNA-Seq Analysis Reveals the Basis for Differential Tissue Tropism of Clinical Isolates of Streptococcus Pneumoniae
In Vivo Dual RNA-Seq Analysis Reveals the Basis for Differential Tissue Tropism of Clinical Isolates of Streptococcus pneumoniae Vikrant Minhas,1,4 Rieza Aprianto,2,4 Lauren J. McAllister,1 Hui Wang,1 Shannon C. David,1 Kimberley T. McLean,1 Iain Comerford,3 Shaun R. McColl,3 James C. Paton,1,5,6,* Jan-Willem Veening,2,5 and Claudia Trappetti,1,5 Supplementary Information Supplementary Table 1. Pneumococcal differential gene expression in the lungs 6 h post-infection, 9-47-Ear vs 9-47M. Genes with fold change (FC) greater than 2 and p < 0.05 are shown. FC values highlighted in blue = upregulated in 9-47-Ear, while values highlighted in red = upregulated in 9- 47M. Locus tag in 9-47- Product padj FC Ear Sp947_chr_00844 Sialidase B 3.08E-10 313.9807 Sp947_chr_02077 hypothetical protein 4.46E-10 306.9412 Sp947_chr_00842 Sodium/glucose cotransporter 2.22E-09 243.4822 Sp947_chr_00841 N-acetylneuraminate lyase 4.53E-09 227.7963 scyllo-inositol 2-dehydrogenase Sp947_chr_00845 (NAD(+)) 4.36E-09 221.051 Sp947_chr_00848 hypothetical protein 1.19E-08 202.7867 V-type sodium ATPase catalytic subunit Sp947_chr_00853 A 1.29E-06 100.5411 Sp947_chr_00846 Beta-glucoside kinase 3.42E-06 98.18951 Sp947_chr_00855 V-type sodium ATPase subunit D 8.34E-06 85.94879 Sp947_chr_00851 V-type sodium ATPase subunit C 2.50E-05 72.46612 Sp947_chr_00843 hypothetical protein 2.17E-05 65.97758 Sp947_chr_00839 HTH-type transcriptional regulator RpiR 3.09E-05 61.28171 Sp947_chr_00854 V-type sodium ATPase subunit B 1.32E-06 50.86992 Sp947_chr_00120 hypothetical protein 3.00E-04 -
Genes in a Refined Smith-Magenis Syndrome Critical Deletion Interval on Chromosome 17P11.2 and the Syntenic Region of the Mouse
Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Article Genes in a Refined Smith-Magenis Syndrome Critical Deletion Interval on Chromosome 17p11.2 and the Syntenic Region of the Mouse Weimin Bi,1,6 Jiong Yan,1,6 Paweł Stankiewicz,1 Sung-Sup Park,1,7 Katherina Walz,1 Cornelius F. Boerkoel,1 Lorraine Potocki,1,3 Lisa G. Shaffer,1 Koen Devriendt,4 Małgorzata J.M. Nowaczyk,5 Ken Inoue,1 and James R. Lupski1,2,3,8 Departments of 1Molecular & Human Genetics, 2Pediatrics, Baylor College of Medicine, 3Texas Children’s Hospital, Houston, Texas 77030, USA; 4Centre for Human Genetics, University Hospital Gasthuisberg, Catholic University of Leuven, B-3000 Leuven, Belgium; 5Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Ontario L8S 4J9, Canada Smith-Magenis syndrome (SMS) is a multiple congenital anomaly/mental retardation syndrome associated with behavioral abnormalities and sleep disturbance. Most patients have the same ∼4 Mb interstitial genomic deletion within chromosome 17p11.2. To investigate the molecular bases of the SMS phenotype, we constructed BAC/PAC contigs covering the SMS common deletion interval and its syntenic region on mouse chromosome 11. Comparative genome analysis reveals the absence of all three ∼200-kb SMS-REP low-copy repeats in the mouse and indicates that the evolution of SMS-REPs was accompanied by transposition of adjacent genes. Physical and genetic map comparisons in humans reveal reduced recombination in both sexes. Moreover, by examining the deleted regions in SMS patients with unusual-sized deletions, we refined the minimal Smith-Magenis critical region (SMCR) to an ∼1.1-Mb genomic interval that is syntenic to an ∼1.0-Mb region in the mouse. -
Large Meta-Analysis of Genome-Wide Association Studies
medRxiv preprint doi: https://doi.org/10.1101/2020.10.01.20200659; this version posted October 4, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Large meta-analysis of genome-wide association studies expands knowledge of the genetic etiology of Alzheimer’s disease and highlights potential translational opportunities Céline Bellenguez1,*,#, Fahri Küçükali2,3,4*, Iris Jansen5,6*, Victor Andrade7,8*, Sonia Morenau- Grau9,10,*, Najaf Amin11,12, Benjamin Grenier-Boley1, Anne Boland13, Luca Kleineidam7,8, Peter Holmans14, Pablo Garcia9,10, Rafael Campos Martin7, Adam Naj15,16, Yang Qiong17, Joshua C. Bis18, Vincent Damotte1, Sven Van der Lee5,6,19, Marcos Costa1, Julien Chapuis1, Vilmentas Giedraitis20, María Jesús Bullido10,21, Adolfo López de Munáin10,22, Jordi Pérez- Tur10,23, Pascual Sánchez-Juan10,24, Raquel Sánchez-Valle25, Victoria Álvarez26, Pau Pastor27, Miguel Medina10,28, Jasper Van Dongen2,3,4, Christine Van Broeckhoven2,3,4, Rik Vandenberghe29,30, Sebastiaan Engelborghs31,32, Gael Nicolas33, Florence Pasquier34, Olivier Hanon35, Carole Dufouil36, Claudine Berr37, Stéphanie Debette36, Jean-François Dartigues36, Gianfranco Spalletta38, Benedetta Nacmias39,40, Vincenzo Solfrezzi41, Barbara Borroni42, Lucio Tremolizzo43, Davide Seripa44, Paolo Caffarra45, Antonio Daniele46,47, Daniela Galimberti48,49, Innocenzo Rainero50, Luisa Benussi51, Alesio Squassina52, Patrizia Mecoci53, Lucilla Parnetti54, Carlo Masullo55, Beatrice Arosio56, John Hardy57, Simon Mead58, Kevin Morgan59, Clive Holmes60, Patrick Kehoe61, Bob Woods62, EADB, Charge, ADGC, Jin Sha15,16, Yi Zhao15,63, Chien-Yueh Lee15,63, Pavel P. -
Meta-Analysis of Genetic Association with Diagnosed Alzheimer's Disease Identifies Novel Risk Loci and Implicates Abeta, Tau, Immunity and Lipid Processing
bioRxiv preprint doi: https://doi.org/10.1101/294629; this version posted April 4, 2018. 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-ND 4.0 International license. Meta-analysis of genetic association with diagnosed Alzheimer's disease identifies novel risk loci and implicates Abeta, Tau, immunity and lipid processing Kunkle BW+*1, Grenier-Boley B+2,3,4, Sims R5, Bis JC6, Naj AC7, Boland A8, Vronskaya M5, van der Lee SJ9, Amlie- Wolf A10, Bellenguez C2,3,4, Frizatti A5, Chouraki V2,11, Martin ER1,12, Sleegers K13,14, Badarinarayan N5, Jakobsdottir J15, Hamilton-Nelson KL1, Aloso R8, Raybould R5, Chen Y10, Kuzma AB10, Hiltunen M17,18, Morgan T5, Ahmad S9, Vardarajan BN19-21, Epelbaum J22, Hoffmann P23,24,25, Boada M26, Beecham GW1,12, Garnier JG8, Harold D27, Fitzpatrick AL28,29, Valladares O10, Moutet ML8, Gerrish A5, Smith AV30,31, Qu L10, Bacq D8, Denning N5, Jian X32, Zhao Y10, Zompo MD33, Fox NC34, Grove ML23, Choi SH16, Mateo I35, Hughes JT36, Adams HH9, Malamon J10, Garcia FS36, Patel Y37, Brody JA6, Dombroski B10, Naranjo MCD36, Daniilidou M38, Eiriksdottir G15, Mukherjee S39, Wallon D40,41, Uphill J42, Aspelund T15,43, Cantwell LB10, Garzia F8, Galimberti D44, Hofer E45,46, Butkiewics M47, Fin B8, Scarpini E44, Sarnowski C16, Bush W47, Meslage S8, Kornhuber J48, White CC49, Song Y47, Barber RC50, Engelborghs S51,52, Pichler S53, Voijnovic D9, Adams PM54, Vandenberghe -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase