Investigating the Effects of Copy Number Variants on Reading and Language Performance Alessandro Gialluisi1,2, Alessia Visconti3, Erik G
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Rare Modifier Variants Alter the Severity of Cardiovascular Disease in Pseudoxanthoma Elasticum
fcell-09-612581 June 8, 2021 Time: 11:34 # 1 BRIEF RESEARCH REPORT published: 08 June 2021 doi: 10.3389/fcell.2021.612581 Rare Modifier Variants Alter the Severity of Cardiovascular Disease in Pseudoxanthoma Elasticum: Identification of Novel Candidate Modifier Genes and Disease Pathways Through Mixture of Effects Analysis Eva Y. G. De Vilder1,2,3, Ludovic Martin4, Georges Lefthériotis5, Paul Coucke1,6, Filip Van Nieuwerburgh7 and Olivier M. Vanakker1,6* Edited by: 1 2 Svetlana Komarova, Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium, The Research Foundation – Flanders, Ghent, 3 4 McGill University, Canada Belgium, Department of Ophthalmology, Ghent University Hospital, Ghent, Belgium, Department of Dermatology, Angers University Hospital, Angers, France, 5 Department of Vascular Physiology and Sports Medicine, Angers University, Angers, Reviewed by: France, 6 Department of Biomolecular Medicine, Ghent University, Ghent, Belgium, 7 Department of Pharmaceutics, Carolina Beraldo Meloto, Laboratory of Pharmaceutical Biotechnology, Ghent University, Ghent, Belgium McGill University, Canada Koen van de Wetering, Thomas Jefferson University, Introduction: Pseudoxanthoma elasticum (PXE), an ectopic mineralization disorder United States caused by pathogenic ABCC6 variants, is characterized by skin, ocular and Jessica Bertrand, University Hospital Magdeburg, cardiovascular (CV) symptoms. Due to striking phenotypic variability without genotype- Germany phenotype correlations, modifier genes are thought to play a role in disease variability. *Correspondence: In this study, we evaluated the collective modifying effect of rare variants on the Olivier M. Vanakker [email protected] cardiovascular phenotype of PXE. Materials and Methods: Mixed effects of rare variants were assessed by Whole Exome Specialty section: This article was submitted to Sequencing in 11 PXE patients with an extreme CV phenotype (mild/severe). -
Genetic Variation Across the Human Olfactory Receptor Repertoire Alters Odor Perception
bioRxiv preprint doi: https://doi.org/10.1101/212431; this version posted November 1, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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 4.0 International license. Genetic variation across the human olfactory receptor repertoire alters odor perception Casey Trimmer1,*, Andreas Keller2, Nicolle R. Murphy1, Lindsey L. Snyder1, Jason R. Willer3, Maira Nagai4,5, Nicholas Katsanis3, Leslie B. Vosshall2,6,7, Hiroaki Matsunami4,8, and Joel D. Mainland1,9 1Monell Chemical Senses Center, Philadelphia, Pennsylvania, USA 2Laboratory of Neurogenetics and Behavior, The Rockefeller University, New York, New York, USA 3Center for Human Disease Modeling, Duke University Medical Center, Durham, North Carolina, USA 4Department of Molecular Genetics and Microbiology, Duke University Medical Center, Durham, North Carolina, USA 5Department of Biochemistry, University of Sao Paulo, Sao Paulo, Brazil 6Howard Hughes Medical Institute, New York, New York, USA 7Kavli Neural Systems Institute, New York, New York, USA 8Department of Neurobiology and Duke Institute for Brain Sciences, Duke University Medical Center, Durham, North Carolina, USA 9Department of Neuroscience, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA *[email protected] ABSTRACT The human olfactory receptor repertoire is characterized by an abundance of genetic variation that affects receptor response, but the perceptual effects of this variation are unclear. To address this issue, we sequenced the OR repertoire in 332 individuals and examined the relationship between genetic variation and 276 olfactory phenotypes, including the perceived intensity and pleasantness of 68 odorants at two concentrations, detection thresholds of three odorants, and general olfactory acuity. -
SNP Genotypes of Olfactory Receptor Genes Associated with Olfactory Ability in German Shepherd Dogs
SHORT COMMUNICATION doi: 10.1111/age.12389 SNP genotypes of olfactory receptor genes associated with olfactory ability in German Shepherd dogs † ‡ – M. Yang*, G.-J. Geng , W. Zhang , L. Cui§, H.-X. Zhang and J.-L. Zheng‡ † *Police-dog Technology Department, National Police University of China, Shenyang, Liaoning 110034, China. Technology Department, ‡ Shenyang Traffic Police Detachment, Shenyang, Liaoning 110001, China. Forensic Medicine Department, National Police University of China, Shenyang, Liaoning 110854, China. §Document Inspection Department, National Police University of China, Shenyang, Liaoning – 110854, China. Mark Inspection Department, National Police University of China, Shenyang, Liaoning 110854, China. Summary To find out the relationship between SNP genotypes of canine olfactory receptor genes and olfactory ability, 28 males and 20 females from German Shepherd dogs in police service were scored by odor detection tests and analyzed using the Beckman GenomeLab SNPstream. The representative 22 SNP loci from the exonic regions of 12 olfactory receptor genes were investigated, and three kinds of odor (human, ice drug and trinitrotoluene) were detected. The results showed that the SNP genotypes at the OR10H1-like:c.632C>T, OR10H1-like:c.770A>T, OR2K2-like:c.518G>A, OR4C11-like: c.511T>G and OR4C11-like:c.692G>A loci had a statistically significant effect on the scenting abilities (P < 0.001). The kind of odor influenced the performances of the dogs (P < 0.001). In addition, there were interactions between genotype and the kind of odor at the following loci: OR10H1-like:c.632C>T, OR10H1-like:c.770A>T, OR4C11-like:c.511T>G and OR4C11-like:c.692G>A(P< 0.001). -
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, -
Journal of Pediatric Gastroenterology and Nutrition, Publish Ahead of Print
Journal of Pediatric Gastroenterology and Nutrition, Publish Ahead of Print DOI : 10.1097/MPG.0000000000002462 Serologic, but not genetic, markers are associated with impaired anthropometrics at diagnosis of pediatric Crohn’s disease Authors: Sara K. Naramore, MD1, William E. Bennett, Jr., MD, MS1,2, Guanglong Jiang, MS3,4, Subra Kugathasan, MD5, Lee A. Denson, MD6, Jeffrey S. Hyams, MD7, Steven J. Steiner, MD1, and PRO-KIIDS Research Group8† 1Department of Pediatrics, Division of Pediatric Gastroenterology, Hepatology, and Nutrition, Indiana University School of Medicine, Indianapolis, IN 2Department of Pediatrics, Division of Pediatric and Adolescent Comparative Effectiveness Research, Indiana University School of Medicine, Indianapolis, IN 3Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 4Department of BioHealth Informatics, Indiana University-Purdue University−Indianapolis, Indianapolis, IN 5Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 6Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 7Department of Pediatrics, Connecticut Children’s Medical Center, Hartford, CT 8PRO-KIIDS Research Group, New York, NY †Membership of the PRO-KIIDS Research Group is listed in the Acknowledgements. Principal Investigator and Corresponding Author: Sara Naramore, MD Department of Pediatrics Indiana University School of Medicine Riley Hospital for Children ____________________________________________________ This is the author's manuscript of the article published in final edited form as: Naramore, S. K., Bennett, W. E. J., Jiang, G., Kugathasan, S., Denson, L. A., Hyams, J. S., … Group, and P.-K. R. (2019). Serologic, but not Genetic, Markers are Associated with Impaired Anthropometrics at Diagnosis of Pediatric Crohn’s Disease. Journal of Pediatric Gastroenterology and Nutrition, Publish Ahead of Print. -
Genome-Wide Association Study Identifies Loci for Arterial Stiffness
www.nature.com/scientificreports OPEN Genome-wide association study identifes loci for arterial stifness index in 127,121 UK Biobank Received: 1 February 2019 Accepted: 5 June 2019 participants Published: xx xx xxxx Kenneth Fung1, Julia Ramírez 2, Helen R. Warren2,3, Nay Aung 1, Aaron M. Lee1, Evan Tzanis2,3, Stefen E. Petersen 1,3 & Patricia B. Munroe2,3 Arterial stifness index (ASI) is a non-invasive measure of arterial stifness using infra-red fnger sensors (photoplethysmography). It is a well-suited measure for large populations as it is relatively inexpensive to perform, and data can be acquired within seconds. These features raise interest in using ASI as a tool to estimate cardiovascular disease risk as prior work demonstrates increased arterial stifness is associated with elevated systolic blood pressure, and ASI is predictive of cardiovascular disease and mortality. We conducted genome-wide association studies (GWASs) for ASI in 127,121 UK Biobank participants of European-ancestry. Our primary analyses identifed variants at four loci reaching genome-wide signifcance (P < 5 × 10−8): TEX41 (rs1006923; P = 5.3 × 10−12), FOXO1 (rs7331212; P = 2.2 × 10−11), C1orf21 (rs1930290, P = 1.1 × 10−8) and MRVI1 (rs10840457, P = 3.4 × 10−8). Gene- based testing revealed three signifcant genes, the most signifcant gene was COL4A2 (P = 1.41 × 10−8) encoding type IV collagen. Other candidate genes at associated loci were also involved in smooth muscle tone regulation. Our fndings provide new information for understanding the development of arterial stifness. Arterial stifness measures have been reported as independent markers of vascular ageing1,2, hypertension3,4, car- diovascular disease (CVD)5,6 and mortality6,7. -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US). -
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 -
(A) TCGA-LUAD, (B) TCGA-LUSC, (C) Database from Rizvi H, Et Al
Figure S1. The correlations of TMB value between panel sequencing and WES in published databases. (A) TCGA-LUAD, (B) TCGA-LUSC, (C) Database from Rizvi H, et al. J Clin Oncol, 2018;36. Abbreviations: TMB, tumor mutational burden; TCGA, The Cancer Genome Atlas; LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; WES, wholeexome sequencing A B C 1 / 3 Figure S2. The comparison of multi-region tTMB among different NSCLC subtypes. Abbreviations: TMB, tumor mutational burden; tTMB, tissue TMB 2 / 3 Figure S3. The comparisons and overlaps of tumor-derived mutational profiles among tumor tissues in each region and the corresponding ctDNA. The P0XX was the patient No. shown at the top. Each tumor region (T1, T2, T3…) with plasma (P) were arranged in the x axis. ctDNA was isolated from plasma (more details in Supplementary Methods). Right y axis displayed tumor-derived mutational profiles in detail. The detected mutations were shown in red, while undetected cases were shown in gray. 3 / 3 P001 P004 P005 P006 P007 P009 P015 P018 KRAS.p.G12C ATG9B.p.R298C MORC1.p.G97V MLH1.p.L658V EGFR.p.L747_E749del SPTA1.p.S444C VAV1.p.R548W TP53.p.Y163C BAX.p.E41G CSMD3.p.H1455Y FAT1.p.R4481L CHI3L1.p.G37S DDR2.p.R478C APC.p.E2184K EPOR.p.R45P PTCH2.p.E854K TENM3.p.S44I EGFR.p.L858R U2AF1.p.S34F STK11.p.I238F MAEL.c.703.1G.C PIK3CA.p.R108H MSH6.p.S1340C EGFR.p.E746_A750del TSC1.p.R779. FLT1.p.K37E XRCC1.p.E455Q TP53.c.443.2A.C EGFR.p.A750P PPEF1.p.R348Q NTRK3.p.D208E TP53.p.Q105_S110delinsP DNMT3A.p.F563I NF1.p.A1228T CDK13.p.K852Nfs.23 POLR3B.c.1102.3_1102.2delTA COL6A6.p.P1542S MYD88.p.L265P FLT4.p.A601V TERT.c..58.u3403C.A ACIN1.p.K1047N ERBB2.p.G746delinsVC PRKCD.p.G210V EPHA3.p.T519M NOTCH1.p.Q2361. -
European Patent Office of Opposition to That Patent, in Accordance with the Implementing Regulations
(19) TZZ Z_T (11) EP 2 884 280 B1 (12) EUROPEAN PATENT SPECIFICATION (45) Date of publication and mention (51) Int Cl.: of the grant of the patent: G01N 33/566 (2006.01) 09.05.2018 Bulletin 2018/19 (21) Application number: 13197310.9 (22) Date of filing: 15.12.2013 (54) Method for evaluating the scent performance of perfumes and perfume mixtures Verfahren zur Bewertung des Duftverhaltens von Duftstoffen und Duftstoffmischungen Procédé d’evaluation de senteur performance du parfums et mixtures de parfums (84) Designated Contracting States: (56) References cited: AL AT BE BG CH CY CZ DE DK EE ES FI FR GB WO-A2-03/091388 GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR • BAGHAEI KAVEH A: "Deorphanization of human olfactory receptors by luciferase and Ca-imaging (43) Date of publication of application: methods.",METHODS IN MOLECULAR BIOLOGY 17.06.2015 Bulletin 2015/25 (CLIFTON, N.J.) 2013, vol. 1003, 19 June 2013 (2013-06-19), pages229-238, XP008168583, ISSN: (73) Proprietor: Symrise AG 1940-6029 37603 Holzminden (DE) • KAVEH BAGHAEI ET AL: "Olfactory receptors coded by segregating pseudo genes and (72) Inventors: odorants with known specific anosmia.", 33RD • Hatt, Hanns ANNUAL MEETING OF THE ASSOCIATION FOR 44789 Bochum (DE) CHEMORECEPTION, 1 April 2011 (2011-04-01), • Gisselmann, Günter XP055111507, 58456 Witten (DE) • TOUHARA ET AL: "Deorphanizing vertebrate • Ashtibaghaei, Kaveh olfactory receptors: Recent advances in 44801 Bochum (DE) odorant-response assays", NEUROCHEMISTRY • Panten, Johannes INTERNATIONAL, PERGAMON PRESS, 37671 Höxter (DE) OXFORD, GB, vol. -
Qt4vh1p2c4 Nosplash E372185
Copyright 2014 by Janine Micheli-Jazdzewski ii Dedication I would like to dedicate this thesis to Rock, who is not with us anymore, TR, General Jack D. Ripper, and Page. Thank you for sitting with me while I worked for countless hours over the years. iii Acknowledgements I would like to express my special appreciation and thanks to my advisor Dr. Deanna Kroetz, you have been a superb mentor for me. I would like to thank you for encouraging my research and for helping me to grow as a research scientist. Your advice on both research, as well as on my career have been priceless. I would also like to thank my committee members, Dr. Laura Bull, Dr. Steve Hamilton and Dr. John Witte for guiding my research and expanding my knowledge on statistics, genetics and clinical phenotypes. I also want to thank past and present members of my laboratory for their support and help over the years, especially Dr. Mike Baldwin, Dr. Sveta Markova, Dr. Ying Mei Liu and Dr. Leslie Chinn. Thanks are also due to my many collaborators that made this research possible including: Dr. Eric Jorgenson, Dr. David Bangsberg, Dr. Taisei Mushiroda, Dr. Michiaki Kubo, Dr. Yusuke Nakamura, Dr. Jeffrey Martin, Joel Mefford, Dr. Sarah Shutgarts, Dr. Sulggi Lee and Dr. Sook Wah Yee. A special thank you to the RIKEN Center for Genomic Medicine that generously performed the genome-wide genotyping for these projects. Thanks to Dr. Steve Chamow, Dr. Bill Werner, Dr. Montse Carrasco, and Dr. Teresa Chen who started me on the path to becoming a scientist.