Genome-Wide Search for Signatures of Selection in Three Major Brazilian Locally Adapted Sheep Breeds
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Genome-Wide Association Study of Behavioral Disinhibition in a Selected Adolescent Sample Jaime Derringer *, Robin P. Corley
Genome-wide association study of behavioral disinhibition in a selected adolescent sample Jaime Derringer1*, Robin P. Corley2, Brett C. Haberstick2, Susan E. Young2, Brittany Demmitt2, Daniel P. Howrigan3, Robert M. Kirkpatrick4, William G. Iacono5, Matt McGue5, Matthew Keller2, Sandra Brown6, Susan Tapert6, Christian J. Hopfer7, Michael C. Stallings2, Thomas J. Crowley7, Soo Hyun Rhee2, Ken Krauter2, John K. Hewitt2, Matthew B. McQueen2 1 University of Illinois Urbana-Champaign, 2 University of Colorado Boulder, 3 Massachusetts General Hospital/Harvard Medical School, 4 Virginia Commonwealth University, 5 University of Minnesota, 6 University of California San Diego, 7 University of Colorado Denver * Corresponding Author: Jaime Derringer, [email protected], Department of Psychology, University of Illinois Urbana-Champaign, Champaign IL USA 61820 Behavioral disinhibition GWAS 2 Abstract Behavioral disinhibition (BD) is a quantitative measure designed to capture the heritable variation encompassing risky and impulsive behaviors. As a result, BD represents an ideal target for discovering genetic loci that predispose individuals to a wide range of antisocial behaviors and substance misuse that together represent a large cost to society as a whole. Published genome-wide association studies (GWAS) have examined specific phenotypes that fall under the umbrella of BD (e.g. alcohol dependence, conduct disorder); however no GWAS has specifically examined the overall BD construct. We conducted a GWAS of BD using a sample of 1,901 adolescents over-selected for characteristics that define high BD, such as substance and antisocial behavior problems, finding no individual locus that surpassed genome-wide significance. Although no single SNP was significantly associated with BD, restricted maximum likelihood analysis estimated that 49.3% of the variance in BD within the Caucasian sub-sample was accounted for by the genotyped SNPs (p=0.06). -
Molecular Characterization of Acute Myeloid Leukemia by Next Generation Sequencing: Identification of Novel Biomarkers and Targets of Personalized Therapies
Alma Mater Studiorum – Università di Bologna Dipartimento di Medicina Specialistica, Diagnostica e Sperimentale Dottorato di Ricerca in Oncologia, Ematologia e Patologia XXX Ciclo Settore Scientifico Disciplinare: MED/15 Settore Concorsuale:06/D3 Molecular characterization of acute myeloid leukemia by Next Generation Sequencing: identification of novel biomarkers and targets of personalized therapies Presentata da: Antonella Padella Coordinatore Prof. Pier-Luigi Lollini Supervisore: Prof. Giovanni Martinelli Esame finale anno 2018 Abstract Acute myeloid leukemia (AML) is a hematopoietic neoplasm that affects myeloid progenitor cells and it is one of the malignancies best studied by next generation sequencing (NGS), showing a highly heterogeneous genetic background. The aim of the study was to characterize the molecular landscape of 2 subgroups of AML patients carrying either chromosomal number alterations (i.e. aneuploidy) or rare fusion genes. We performed whole exome sequencing and we integrated the mutational data with transcriptomic and copy number analysis. We identified the cell cycle, the protein degradation, response to reactive oxygen species, energy metabolism and biosynthetic process as the pathways mostly targeted by alterations in aneuploid AML. Moreover, we identified a 3-gene expression signature including RAD50, PLK1 and CDC20 that characterize this subgroup. Taking advantage of RNA sequencing we aimed at the discovery of novel and rare gene fusions. We detected 9 rare chimeric transcripts, of which partner genes were transcription factors (ZEB2, BCL11B and MAFK) or tumor suppressors (SAV1 and PUF60) rarely translocated across cancer types. Moreover, we detected cryptic events hiding the loss of NF1 and WT1, two recurrently altered genes in AML. Finally, we explored the oncogenic potential of the ZEB2-BCL11B fusion, which revealed no transforming ability in vitro. -
Misexpression of Cancer/Testis (Ct) Genes in Tumor Cells and the Potential Role of Dream Complex and the Retinoblastoma Protein Rb in Soma-To-Germline Transformation
Michigan Technological University Digital Commons @ Michigan Tech Dissertations, Master's Theses and Master's Reports 2019 MISEXPRESSION OF CANCER/TESTIS (CT) GENES IN TUMOR CELLS AND THE POTENTIAL ROLE OF DREAM COMPLEX AND THE RETINOBLASTOMA PROTEIN RB IN SOMA-TO-GERMLINE TRANSFORMATION SABHA M. ALHEWAT Michigan Technological University, [email protected] Copyright 2019 SABHA M. ALHEWAT Recommended Citation ALHEWAT, SABHA M., "MISEXPRESSION OF CANCER/TESTIS (CT) GENES IN TUMOR CELLS AND THE POTENTIAL ROLE OF DREAM COMPLEX AND THE RETINOBLASTOMA PROTEIN RB IN SOMA-TO- GERMLINE TRANSFORMATION", Open Access Master's Thesis, Michigan Technological University, 2019. https://doi.org/10.37099/mtu.dc.etdr/933 Follow this and additional works at: https://digitalcommons.mtu.edu/etdr Part of the Cancer Biology Commons, and the Cell Biology Commons MISEXPRESSION OF CANCER/TESTIS (CT) GENES IN TUMOR CELLS AND THE POTENTIAL ROLE OF DREAM COMPLEX AND THE RETINOBLASTOMA PROTEIN RB IN SOMA-TO-GERMLINE TRANSFORMATION By Sabha Salem Alhewati A THESIS Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE In Biological Sciences MICHIGAN TECHNOLOGICAL UNIVERSITY 2019 © 2019 Sabha Alhewati This thesis has been approved in partial fulfillment of the requirements for the Degree of MASTER OF SCIENCE in Biological Sciences. Department of Biological Sciences Thesis Advisor: Paul Goetsch. Committee Member: Ebenezer Tumban. Committee Member: Zhiying Shan. Department Chair: Chandrashekhar Joshi. Table of Contents List of figures .......................................................................................................................v -
The Pdx1 Bound Swi/Snf Chromatin Remodeling Complex Regulates Pancreatic Progenitor Cell Proliferation and Mature Islet Β Cell
Page 1 of 125 Diabetes The Pdx1 bound Swi/Snf chromatin remodeling complex regulates pancreatic progenitor cell proliferation and mature islet β cell function Jason M. Spaeth1,2, Jin-Hua Liu1, Daniel Peters3, Min Guo1, Anna B. Osipovich1, Fardin Mohammadi3, Nilotpal Roy4, Anil Bhushan4, Mark A. Magnuson1, Matthias Hebrok4, Christopher V. E. Wright3, Roland Stein1,5 1 Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 2 Present address: Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN 3 Department of Cell and Developmental Biology, Vanderbilt University, Nashville, TN 4 Diabetes Center, Department of Medicine, UCSF, San Francisco, California 5 Corresponding author: [email protected]; (615)322-7026 1 Diabetes Publish Ahead of Print, published online June 14, 2019 Diabetes Page 2 of 125 Abstract Transcription factors positively and/or negatively impact gene expression by recruiting coregulatory factors, which interact through protein-protein binding. Here we demonstrate that mouse pancreas size and islet β cell function are controlled by the ATP-dependent Swi/Snf chromatin remodeling coregulatory complex that physically associates with Pdx1, a diabetes- linked transcription factor essential to pancreatic morphogenesis and adult islet-cell function and maintenance. Early embryonic deletion of just the Swi/Snf Brg1 ATPase subunit reduced multipotent pancreatic progenitor cell proliferation and resulted in pancreas hypoplasia. In contrast, removal of both Swi/Snf ATPase subunits, Brg1 and Brm, was necessary to compromise adult islet β cell activity, which included whole animal glucose intolerance, hyperglycemia and impaired insulin secretion. Notably, lineage-tracing analysis revealed Swi/Snf-deficient β cells lost the ability to produce the mRNAs for insulin and other key metabolic genes without effecting the expression of many essential islet-enriched transcription factors. -
JNK Activation of BIM Promotes Hepatic Oxidative Stress, Steatosis and Insulin Resistance in Obesity
Page 1 of 62 Diabetes JNK activation of BIM promotes hepatic oxidative stress, steatosis and insulin resistance in obesity. Sara A. Litwak1, Lokman Pang1,2, Sandra Galic1, Mariana Igoillo-Esteve3, William J. Stanley1,2, Jean-Valery Turatsinze3, Kim Loh1, Helen E. Thomas1,2, Arpeeta Sharma4, Eric Trepo5,6, Christophe Moreno5,6, Daniel J. Gough7,8, Decio L. Eizirik3, Judy B. de Haan4, Esteban N. Gurzov1,2,a 1St Vincent’s Institute of Medical Research, Melbourne, Australia. 2Department of Medicine, St. Vincent’s Hospital, The University of Melbourne, Melbourne, Australia. 3ULB Center for Diabetes Research, Université Libre de Bruxelles (ULB), Brussels, Belgium. 4Oxidative Stress Laboratory, Basic Science Division, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia. 5CUB Hôpital Erasme, Université Libre de Bruxelles (ULB), Belgium. 6Laboratory of experimental Gastroenterology, Université Libre de Bruxelles (ULB), Belgium. 7Hudson Institute of Medical Research, Clayton, VIC, Australia. 8Department of Molecular and Translational Science, Monash University, Clayton, Vic, Australia. aPresent address, to where correspondence and reprint requests should be addressed: Dr Esteban N. Gurzov ULB Center for Diabetes Research Université Libre de Bruxelles Campus Erasme, Route de Lennik 808, B-1070-Brussels-Belgium Phone: +32 2 5556242 Fax: +32 2 5556239 Email: [email protected] Disclosure statement: The authors declare no conflict of interest Running Title: BIM regulates lipid metabolism in hepatocytes. 1 Diabetes Publish Ahead of Print, published online September 19, 2017 Diabetes Page 2 of 62 ABSTRACT The BCL-2 family are crucial regulators of the mitochondrial pathway of apoptosis in normal physiology and disease. Besides their role in cell death, BCL-2 proteins have been implicated in the regulation of mitochondrial oxidative phosphorylation and cellular metabolism. -
Us 2018 / 0305689 A1
US 20180305689A1 ( 19 ) United States (12 ) Patent Application Publication ( 10) Pub . No. : US 2018 /0305689 A1 Sætrom et al. ( 43 ) Pub . Date: Oct. 25 , 2018 ( 54 ) SARNA COMPOSITIONS AND METHODS OF plication No . 62 /150 , 895 , filed on Apr. 22 , 2015 , USE provisional application No . 62/ 150 ,904 , filed on Apr. 22 , 2015 , provisional application No. 62 / 150 , 908 , (71 ) Applicant: MINA THERAPEUTICS LIMITED , filed on Apr. 22 , 2015 , provisional application No. LONDON (GB ) 62 / 150 , 900 , filed on Apr. 22 , 2015 . (72 ) Inventors : Pål Sætrom , Trondheim (NO ) ; Endre Publication Classification Bakken Stovner , Trondheim (NO ) (51 ) Int . CI. C12N 15 / 113 (2006 .01 ) (21 ) Appl. No. : 15 /568 , 046 (52 ) U . S . CI. (22 ) PCT Filed : Apr. 21 , 2016 CPC .. .. .. C12N 15 / 113 ( 2013 .01 ) ; C12N 2310 / 34 ( 2013. 01 ) ; C12N 2310 /14 (2013 . 01 ) ; C12N ( 86 ) PCT No .: PCT/ GB2016 /051116 2310 / 11 (2013 .01 ) $ 371 ( c ) ( 1 ) , ( 2 ) Date : Oct . 20 , 2017 (57 ) ABSTRACT The invention relates to oligonucleotides , e . g . , saRNAS Related U . S . Application Data useful in upregulating the expression of a target gene and (60 ) Provisional application No . 62 / 150 ,892 , filed on Apr. therapeutic compositions comprising such oligonucleotides . 22 , 2015 , provisional application No . 62 / 150 ,893 , Methods of using the oligonucleotides and the therapeutic filed on Apr. 22 , 2015 , provisional application No . compositions are also provided . 62 / 150 ,897 , filed on Apr. 22 , 2015 , provisional ap Specification includes a Sequence Listing . SARNA sense strand (Fessenger 3 ' SARNA antisense strand (Guide ) Mathew, Si Target antisense RNA transcript, e . g . NAT Target Coding strand Gene Transcription start site ( T55 ) TY{ { ? ? Targeted Target transcript , e . -
Differential Expression Gene Symbol Upregulated
Table S1. 1658 differential expressed genes with P-value < 0.05 in myeloid dendritic cells patients with all ergies compared to healthy controls. Differential Gene Symbol Expression Upregulated KIAA1217, RP11-111M22.2, RP11-21M24.2, FAM221B, TRIM9, CNKSR3, LRIT3, (N=771) RP11-26J3.1, RP11-708J19.1, RPS3AP35, AC096574.4, RBPMS, JPH3, RASGRF1, RP11-118E18.4, TPPP, KCNJ9, ARMC12, TUBB8P7, KCND3, CTD-2083E4.4, SLCO5A1, EGLN3, NOS3, RPS3AP40, OR10A4, AC007551.2, RP11-110I1.12, ZNF732, RP4-800G7.3, RNFT2, SFXN2, SEPT5, UFSP1, KRT8P26, RP11- 634H22.1, RP11-357G3.1, CTC-487M23.5, RP11-804H8.6, ROPN1L, E2F2, RP11- 983P16.4, SOX12, KRTAP16-1, FAM188B, TTC28, CTB-66B24.1, PLS1, SHF, ESR1, SOCS2, MNS1, GPR55, RP11-1020A11.2, C4orf32, BHLHE22, RP11- 63E5.6, SIGLEC15, FGFBP3, AP000692.10, CTD-2357A8.3, RP1-102E24.6, ZC4H2, AC074367.1, WDR86-AS1, YPEL1, HOXB-AS1, RP3-522P13.2, OR7E47P, AC068039.4, NUDT8, IBA57, PPP1R3G, CACNB3, KB-1460A1.1, IQCJ-SCHIP1-AS1, CRHR2, CD27-AS1, RP11-368J22.2, MANSC4, FITM2, AC002467.7, RPS5P2, SNHG17, GCAT, C10orf91, CTB-61M7.1, ATP8A2P2, RP11-50E11.2, TFAP4, CTD-2060C23.1, MED9, RP11-583F2.1, GAPDHP62, RN7SL801P, CYB5RL, ALG14, IGLV5-52, AC106801.1, RP11-403A21.3, LAD1, EARS2, NEURL3, DUSP14, RP11-116K4.1, PKNOX1, RP11-248J23.5, ZNF730, PSMF1, PINLYP, HOXA10, PTMAP8, RNLS, NANOGP7, FOXD1, AIFM2, KCNJ14, AC114730.8, RP11-804H8.5, C1orf109, PANK1, RPL32P26, RP11- 528A10.2, KL, METTL21B, CTD-2186M15.1, UBE3D, SMARCA5-AS1, SCARF2, AC000003.2, AC013470.6, PEX10, LRP11, ACTBP14, RP11-93B14.5, MIR1182, LIMCH1, IFI27L1, FSTL3, -
48 14 5 5 4 9 Hsa-Mir-5001-5P -4.18 -4.18 N/A
Total Total 8mer 7mer-m8 7mer-A1 6mer Cumulative weighted Aggregate Target gene Representative transcript Gene name 3P-seq tags + 5 Representative miRNA context++ sites sites sites sites sites context++ score PCT score GIPC3 ENST00000322315.5 GIPC PDZ domain containing family, member 3 48 14 5 5 4 9 hsa-miR-5001-5p -4.18 -4.18 N/A GNG13 ENST00000248150.4 guanine nucleotide binding protein (G protein), gamma 13 5 7 0 7 0 0 hsa-miR-4498 -2.21 -2.21 N/A EVC ENST00000382674.2 Ellis van Creveld syndrome 165 15 0 15 0 1 hsa-miR-4498 -2.1 -2.1 N/A MAM domain containing glycosylphosphatidylinositol MDGA1 ENST00000297153.7 240 7 3 3 1 5 hsa-miR-5001-5p -2.05 -2.11 N/A anchor 1 KLK4 ENST00000324041.1 kallikrein-related peptidase 4 5 9 0 9 0 0 hsa-miR-4498 -1.77 -1.77 N/A OLFML2A ENST00000288815.5 olfactomedin-like 2A 155 9 4 4 1 1 hsa-miR-4498 -1.77 -1.77 N/A SDK2 ENST00000392650.3 sidekick cell adhesion molecule 2 8 5 3 2 0 2 hsa-miR-4498 -1.74 -1.74 N/A NKIRAS2 ENST00000462043.2 NFKB inhibitor interacting Ras-like 2 9685 4 1 3 0 1 hsa-miR-5001-5p -1.71 -1.71 N/A OSBP2 ENST00000382310.3 oxysterol binding protein 2 485 6 2 4 0 0 hsa-miR-5001-5p -1.64 -1.66 N/A SNPH ENST00000381873.3 syntaphilin 13 5 2 2 1 1 hsa-miR-4498 -1.61 -1.61 N/A SPN ENST00000360121.3 sialophorin 5 3 2 0 1 3 hsa-miR-5001-5p -1.58 -1.58 N/A PER2 ENST00000254658.3 period circadian clock 2 106 4 2 1 1 3 hsa-miR-4498 -1.57 -1.57 N/A FLJ27365 ENST00000360737.3 hsa-mir-4763 74 5 2 3 0 3 hsa-miR-4498 -1.5 -1.54 N/A UDP-Gal:betaGlcNAc beta 1,3-galactosyltransferase, B3GALT5 ENST00000380620.4 -
The Cancer Genome Atlas Dataset-Based Analysis of Aberrantly Expressed Genes by Geneanalytics in Thymoma Associated Myasthenia Gravis: Focusing on T Cells
2323 Original Article The Cancer Genome Atlas dataset-based analysis of aberrantly expressed genes by GeneAnalytics in thymoma associated myasthenia gravis: focusing on T cells Jianying Xi1#, Liang Wang1#, Chong Yan1, Jie Song1, Yang Song2, Ji Chen2, Yongjun Zhu2, Zhiming Chen2, Chun Jin3, Jianyong Ding3, Chongbo Zhao1,4 1Department of Neurology, 2Department of Thoracic Surgery, Huashan Hospital, Fudan University, Shanghai 200040, China; 3Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai 200030, China; 4Department of Neurology, Jing’an District Centre Hospital of Shanghai, Fudan University, Shanghai 200040, China Contributions: (I) Conception and design: J Xi, L Wang, C Zhao; (II) Administrative support: J Xi, L Wang, C Zhao; (III) Provision of study materials or patients: Y Song, Y Zhu, J Chen, Z Chen, C Jin, J Ding; (IV) Collection and assembly of data: C Jin, J Ding; (V) Data analysis and interpretation: C Yan, J Song; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors. #These authors contributed equally to this work. Correspondence to: Chongbo Zhao. Department of Neurology, Huashan Hospital, Fudan University, Shanghai 200040, China. Email: [email protected]. Background: Myasthenia gravis (MG) is a group of autoimmune disease which could be accompanied by thymoma. Many differences have been observed between thymoma-associated MG (TAMG) and non-MG thymoma (NMG). However, the molecular difference between them remained unknown. This study aimed to explore the differentially expressed genes (DEGs) between the two categories and to elucidate the possible pathogenesis of TAMG further. Methods: DEGs were calculated using the RNA-Sequencing data from 11 TAMG and 10 NMG in The Cancer Genome Atlas (TCGA) database. -
Supplemental Figure 1
A BCD6 35 80 1.0 3 Thr Ala 0.4 Thr Ala 30 0.8 60 4 0.3 2 25 0.6 40 20 0.2 0.4 1 2 20 intake(g)Food Body weight(g) 15 0.1 0.2 Serum TSH (ng/ml) T4 plasmaT4 levels (ng/ml) plasma levelsT3 (ng/ml) 1/V 10 0.0 0 0.0 0 5 10 15 Thr Ala Thr Ala Thr Ala -1.0 -0.5 0.5 1.0 1.5 2.0 Thr Ala Thr Ala Age (weeks) 1/[T4] (nM) dark light (fmols/min/mg ptn) (fmols/min/mg -1 Ala Thr IKMN O Femur 16.5 0.55 1100 0.24 E F 16.0 1050 0.22 G H 0.50 Thr92‐D2 15.5 1000 0.20 Ala92‐D2 0.45 15.0 950 0.18 (mgHAcm-3) Femur volume 0.40 14.5 900 0.16 Cortical thickness Femur length (mm) length Femur Bone MineralDensity 14.0 0.35 850 0.14 Thr Ala Thr Ala Thr Ala Thr Ala JLPQR Vertebrae 4.6 5.5 0.070 0.35 4.4 5.0 0.065 0.30 **P<0.01 0.060 4.2 *** 4.5 0.055 0.25 4.0 4.0 0.050 0.20 3.8 3.5 Trabecular number 0.045 Trabecular spacing Trabecular thickness Vertebral height (mm) height Vertebral 3.6 3.0 0.040 0.15 Thr Ala Thr Ala Thr Ala Thr Ala Figure S1: Additional phenotype of the Ala92‐Dio2 mouse. -
Abschlussbericht Für Vorhaben 3609S30013
Ressortforschungsberichte zur kerntechnischen Sicherheit und zum Strahlenschutz Untersuchungen zum Zusammenwirken umweltbedingter Risikofaktoren mit genetischen und weiteren endogenen Faktoren bei der Entstehung von Leukämie im Kindesalter Teilvorhaben 1; Pilotstudie: Sequenzierung und bioinformatische Auswertung - Vorhaben 3611S70014 Auftragnehmer: Universitätsklinikum Schleswig-Holstein - Campus Kiel M. Stanulla A. Borkhardt C. Eckert J. Korbel M. Schrappe M.-L. Yaspo A. Franke Das Vorhaben wurde mit Mitteln des Bundesministeriums für Umwelt, Naturschutz, Bau und Reaktorsicherheit (BMUB) und im Auftrag des Bundesamtes für Strahlenschutz (BfS) durchgeführt. Dieser Band enthält einen Ergebnisbericht eines vom Bundesamt für Strahlenschutz im Rahmen der Ressortforschung des BMUB (UFOPLAN) in Auftrag gegebenen Untersuchungsvorhabens. Verantwortlich für den Inhalt sind allein die Autoren. Das BfS übernimmt keine Gewähr für die Richtigkeit, die Genauigkeit und Vollständigkeit der Angaben sowie die Beachtung privater Rechte Dritter. Der Auftraggeber behält sich alle Rechte vor. Insbesondere darf dieser Bericht nur mit seiner Zustimmung ganz oder teilweise vervielfältigt werden. Der Bericht gibt die Auffassung und Meinung des Auftragnehmers wieder und muss nicht mit der des BfS übereinstimmen. BfS-RESFOR-103/15 Bitte beziehen Sie sich beim Zitieren dieses Dokumentes immer auf folgende URN: urn:nbn:de:0221-2015012912280 Salzgitter, Januar 2015 - 1 - Untersuchungen zum Zusammenwirken umweltbedingter Risikofaktoren mit genetischen und weiteren -
You Can Check If Genes Are Captured by the Agilent Sureselect V5 Exome
IIHG Clinical Exome Sequencing Test Gene Coverage • Whole Exome Sequencing is a targeted capture platform which does not capture the entire exome. Regions not captured by the exome will not be analyzed. o Please note, it is important to understand the absence of a reportable variant in a given gene does not mean there are not pathogenic variants in that gene. • Data sensitivity and specificity for exome testing is variable as gene coverage is not uniform throughout the exome. • The Agilent SureSelect XT Human All Exon v5 kit captures ~98% of Refseq coding base pairs, and >94% of the captured coding bases in the exome are covered at our depth-of-coverage minimum threshold (30 reads). • All test reports include the following information: o Regions of the Symptom Candidate Gene List which were not captured by the current exome capture platform. o Regions of the Symptom Candidate Gene List which were not sequenced to a sufficient depth of coverage to make a clinical diagnosis. • You can check if genes are captured by the Agilent Agilent SureSelect v5 exome capture, and how well those genes are typically covered here. • Explanations for the headings; • Symbol: Gene symbol • Chr: Chromosome • % Captured: the minimum portion of the gene captured by the Agilent SureSelect XT Human All Exon v5 kit. This includes all transcripts for a given gene. o 100.00% = the entire gene is captured o 0.00% = none of the gene is captured • % Covered: the minimum portion of the gene that has at least 30x average coverage when sequenced on the Illumina HiSeq2000 with 100 base pair (bp) paired-end reads for eight CEPH samples.