Copy Number Variation in Fetal Alcohol Spectrum Disorder

Total Page:16

File Type:pdf, Size:1020Kb

Copy Number Variation in Fetal Alcohol Spectrum Disorder Biochemistry and Cell Biology Copy number variation in fetal alcohol spectrum disorder Journal: Biochemistry and Cell Biology Manuscript ID bcb-2017-0241.R1 Manuscript Type: Article Date Submitted by the Author: 09-Nov-2017 Complete List of Authors: Zarrei, Mehdi; The Centre for Applied Genomics Hicks, Geoffrey G.; University of Manitoba College of Medicine, Regenerative Medicine Reynolds, James N.; Queen's University School of Medicine, Biomedical and Molecular SciencesDraft Thiruvahindrapuram, Bhooma; The Centre for Applied Genomics Engchuan, Worrawat; Hospital for Sick Children SickKids Learning Institute Pind, Molly; University of Manitoba College of Medicine, Regenerative Medicine Lamoureux, Sylvia; The Centre for Applied Genomics Wei, John; The Centre for Applied Genomics Wang, Zhouzhi; The Centre for Applied Genomics Marshall, Christian R.; The Centre for Applied Genomics Wintle, Richard; The Centre for Applied Genomics Chudley, Albert; University of Manitoba Scherer, Stephen W.; The Centre for Applied Genomics Is the invited manuscript for consideration in a Special Fetal Alcohol Spectrum Disorder Issue? : Keyword: Fetal alcohol spectrum disorder, FASD, copy number variations, CNV https://mc06.manuscriptcentral.com/bcb-pubs Page 1 of 354 Biochemistry and Cell Biology 1 Copy number variation in fetal alcohol spectrum disorder 2 Mehdi Zarrei,a Geoffrey G. Hicks,b James N. Reynolds,c,d Bhooma Thiruvahindrapuram,a 3 Worrawat Engchuan,a Molly Pind,b Sylvia Lamoureux,a John Wei,a Zhouzhi Wang,a Christian R. 4 Marshall,a Richard F. Wintle,a Albert E. Chudleye,f and Stephen W. Scherer,a,g 5 aThe Centre for Applied Genomics and Program in Genetics and Genome Biology, The Hospital 6 for Sick Children, Toronto, Ontario, Canada 7 bRegenerative Medicine Program, University of Manitoba, Winnipeg, Canada 8 cCentre for Neuroscience Studies, Queen's University, Kingston, Ontario, Canada. 9 dDepartment of Biomedical and MolecularDraft Sciences, Queen's University, Kingston, Ontario, 10 Canada 11 eDepartment of Pediatrics and Child Health, Max Rady College of Medicine, Rady Faculty of 12 Health Sciences, University of Manitoba, Winnipeg, Canada. 13 fDepartment of Biochemistry and Medical Genetics, Max Rady College of Medicine, Rady 14 Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada 15 gDepartment of Molecular Genetics and McLaughlin Centre, University of Toronto, Toronto, 16 Ontario, Canada 17 Corresponding authors: Stephen W. Scherer ([email protected]) and Albert E. 18 Chudley ([email protected]) 19 1 https://mc06.manuscriptcentral.com/bcb-pubs Biochemistry and Cell Biology Page 2 of 354 20 Abstract: Fetal alcohol spectrum disorder (FASD) is characterized by a combination of 21 neurological, developmental, and congenital defects that may occur as a consequence of prenatal 22 alcohol exposure. Earlier reports showed that large chromosomal anomalies may link to FASD. 23 Here, we examined the prevalence and types of copy number variations (CNVs) in FASD cases 24 previously diagnosed by a multidisciplinary FASD team in sites across Canada. We genotyped 25 95 children with FASD and 87 age-matched, typically developing controls on the Illumina 26 Human Omni2.5 SNP array platform. We compared their CNVs to those of 10,851 population 27 controls, in order to identify rare CNVs (<0.1% frequency), which may include large unbalanced 28 chromosomal abnormalities, that might be relevant to FASD. In 12/95 (13%) of the FASD cases, 29 rare CNVs were found that impact potentially clinically-relevant developmental genes, including 30 the CACNA1H involved in epilepsy andDraft autism, the 3q29 deletion disorder, and others. Our 31 results show that a subset of children diagnosed with FASD have chromosomal deletions and 32 duplications that may co-occur or explain the neurodevelopmental impairments in a diagnosed 33 cohort of FASD individuals. Children suspected to have FASD with or without sentinel facial 34 features of fetal alcohol syndrome and neurodevelopmental delays should potentially be 35 evaluated by a clinical geneticist and possibly have genetic investigations as appropriate to 36 exclude other etiologies. 37 Key words: Fetal alcohol spectrum disorder, FASD, copy number variations, CNV. 38 Résumé: [will be translated into French by the journal translator] 39 Mots-clés: Fetal alcohol spectrum disorder, FASD, copy number variations, CNV. 2 https://mc06.manuscriptcentral.com/bcb-pubs Page 3 of 354 Biochemistry and Cell Biology 40 Introduction 41 Fetal alcohol spectrum disorder (FASD) is an umbrella term for a group of alcohol-related 42 disorders, characterizing the full range of damage from prenatal alcohol exposure (Chudley et al. 43 2005). It comprises fetal alcohol syndrome (FAS), partial FAS, alcohol-related 44 neurodevelopmental disorders, and alcohol-related birth defects, which are congenital anomalies 45 that can include growth deficits, facial dysmorphism, and/or malformations in multiple 46 physiological systems (Abdelmalik et al. 2013; Chudley et al. 2005; Douzgou et al. 2012; 47 Popova et al. 2016). FASD is also associated with numerous co-morbid neurodevelopmental 48 disorders, including intellectual disabilities, microcephaly, autism spectrum disorder (ASD), and 49 attention deficit hyperactivity disorder (Abdelmalik et al. 2013; Douzgou et al. 2012; Weyrauch 50 et al. 2017). Draft 51 The reported incidence of FASD is 0.2 to 3.0 per 1,000 live births for most countries (Douzgou 52 et al. 2012). However, an incidence of up to 89.2 per 1,000 births was reported in regions of 53 South Africa where wine production is abundant (May et al. 2007). A recent review of the 54 global prevalence of FASD in children and youth reported a prevalence of 7.7 per 1000 55 population (95% CI, 4.9-11.7 per 1000 population). The highest rate was reported by the World 56 Health Organization European region with 19.8 per 1000 population, (95% CI, 14.1-28 per 1000 57 population)(Lange et al. 2017). 58 It is well established in the medical community that not all children exposed to alcohol 59 prenatally develop FASD (Abel 1995; Stoler 1999). This indicates that factors other than 60 prenatal alcohol exposure also contribute to FASD aetiology. The impact of the genetic 61 variations to the aetiology of FASD has been studied in animal models (reviewed in (Eberhart 62 and Parnell 2016; McCarthy and Eberhart 2014)). However, genetic studies on human are 3 https://mc06.manuscriptcentral.com/bcb-pubs Biochemistry and Cell Biology Page 4 of 354 63 restricted to case reports with large chromosomal anomalies (Stoler 1999) and twin studies 64 (Chasnoff 1985). For example, association of trisomy 21 or ring chromosome 6 with FASD has 65 been reported (Bingol et al. 1987; Muller et al. 1993; Romke et al. 1987). Large chromosomal 66 anomalies such as 22q11.2 microdeletion and microduplication, and 1q21 microduplications, 67 among others, were reported in 9% (7/90) of cases with FASD in a UK cohort (Douzgou et al. 68 2012). A retrospective study of younger and older siblings of patients with FAS clearly indicated 69 a greatly increased risk of FAS in younger siblings if an older sibling had been diagnosed with 70 FAS (Abel 1988). The contribution of CNVs to the aetiology of neurodevelopmental disorders 71 (Gazzellone et al. 2016; Lionel et al. 2011; Oskoui et al. 2015; Pinto et al. 2014; Pinto et al. 72 2010; Zarrei et al. 2017a), including those that may be comorbid with FASD (Popova et al. 73 2016), has been well documented. However,Draft until the current study, a genome-wide CNV 74 analysis in FASD cases had not been performed. 75 Our objective was to assess the role of CNVs and chromosomal abnormalities, at a genome- 76 wide level, in a clinically well-defined collection of individuals with FASD, to further define 77 genomic risk contribution in this common disorder. 78 Materials and methods 79 Participants 80 Ninety-five children diagnosed with FASD and eighty-seven aged-matched, typically 81 developing controls as internal control were recruited through the NeuroDevNet Canadian FASD 82 study cohort (Portales-Casamar et al. 2016; Reynolds et al. 2011) and the majority of clinical 83 centers used the Canadian FASD Guidelines for diagnosis (Chudley et al. 2005). Siblings of 84 some probands, if consented, were also recruited for this study (Table S1). Our FASD cases have 4 https://mc06.manuscriptcentral.com/bcb-pubs Page 5 of 354 Biochemistry and Cell Biology 85 a sex ratio of 0.73 (male: 40; female: 55; Table S1; 0.85 in internal controls). Research Ethics 86 Board approval was obtained from each participating centre, and all caregivers and participants 87 provided written informed consent. Saliva samples were collected from the children. Details of 88 saliva collection and storage is provided elsewhere (Portales-Casamar et al. 2016). 89 Genotyping, CNV calling, and detection of rare variants 90 DNA extracted from saliva using standard protocols was genotyped on two Illumina Human 91 Omni2.5 SNP array platforms (Omni2.5m-Quad; n=132 and Omni2.5m-8; n=50) at The Centre 92 for Applied Genomics in Toronto according to the manufacturer’s protocol. Relevant microarray 93 data are deposited in the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo/; 94 GSE102650). Quality control and ancestryDraft assessment procedures were as described previously 95 (Gazzellone et al. 2016; Oskoui et al. 2015). Ancestry was determined using PLINK v1.07 96 (Purcell et al. 2007). 97 CNV calling was performed as previously described with slight modifications (Oskoui et al. 98 2015). In brief, three CNV calling algorithms were used for both cases and internal controls: i.e. 99 iPattern (Pinto et al. 2011), PennCNV (Wang et al. 2007), and QuantiSNP (Colella et al. 2007). 100 We then analyzed “stringent” CNVs, those detected by at least two methods. Detecting large 101 CNVs particularly sex chromosomal aneuploidies is challenging (Oskoui et al. 2015). Hence, 102 these large CNVs are sometimes fragmented. If found, they were merged and their identity 103 confirmed by examining the probe density and B allele frequencies in the region.
Recommended publications
  • 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.
    [Show full text]
  • Autism Multiplex Family with 16P11.2P12.2 Microduplication Syndrome in Monozygotic Twins and Distal 16P11.2 Deletion in Their Brother
    European Journal of Human Genetics (2012) 20, 540–546 & 2012 Macmillan Publishers Limited All rights reserved 1018-4813/12 www.nature.com/ejhg ARTICLE Autism multiplex family with 16p11.2p12.2 microduplication syndrome in monozygotic twins and distal 16p11.2 deletion in their brother Anne-Claude Tabet1,2,3,4, Marion Pilorge2,3,4, Richard Delorme5,6,Fre´de´rique Amsellem5,6, Jean-Marc Pinard7, Marion Leboyer6,8,9, Alain Verloes10, Brigitte Benzacken1,11,12 and Catalina Betancur*,2,3,4 The pericentromeric region of chromosome 16p is rich in segmental duplications that predispose to rearrangements through non-allelic homologous recombination. Several recurrent copy number variations have been described recently in chromosome 16p. 16p11.2 rearrangements (29.5–30.1 Mb) are associated with autism, intellectual disability (ID) and other neurodevelopmental disorders. Another recognizable but less common microdeletion syndrome in 16p11.2p12.2 (21.4 to 28.5–30.1 Mb) has been described in six individuals with ID, whereas apparently reciprocal duplications, studied by standard cytogenetic and fluorescence in situ hybridization techniques, have been reported in three patients with autism spectrum disorders. Here, we report a multiplex family with three boys affected with autism, including two monozygotic twins carrying a de novo 16p11.2p12.2 duplication of 8.95 Mb (21.28–30.23 Mb) characterized by single-nucleotide polymorphism array, encompassing both the 16p11.2 and 16p11.2p12.2 regions. The twins exhibited autism, severe ID, and dysmorphic features, including a triangular face, deep-set eyes, large and prominent nasal bridge, and tall, slender build. The eldest brother presented with autism, mild ID, early-onset obesity and normal craniofacial features, and carried a smaller, overlapping 16p11.2 microdeletion of 847 kb (28.40–29.25 Mb), inherited from his apparently healthy father.
    [Show full 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.
    [Show full text]
  • Supplementary Table S1. Prioritization of Candidate FPC Susceptibility Genes by Private Heterozygous Ptvs
    Supplementary Table S1. Prioritization of candidate FPC susceptibility genes by private heterozygous PTVs Number of private Number of private Number FPC patient heterozygous PTVs in heterozygous PTVs in tumors with somatic FPC susceptibility Hereditary cancer Hereditary Gene FPC kindred BCCS samples mutation DNA repair gene Cancer driver gene gene gene pancreatitis gene ATM 19 1 - Yes Yes Yes Yes - SSPO 12 8 1 - - - - - DNAH14 10 3 - - - - - - CD36 9 3 - - - - - - TET2 9 1 - - Yes - - - MUC16 8 14 - - - - - - DNHD1 7 4 1 - - - - - DNMT3A 7 1 - - Yes - - - PKHD1L1 7 9 - - - - - - DNAH3 6 5 - - - - - - MYH7B 6 1 - - - - - - PKD1L2 6 6 - - - - - - POLN 6 2 - Yes - - - - POLQ 6 7 - Yes - - - - RP1L1 6 6 - - - - - - TTN 6 5 4 - - - - - WDR87 6 7 - - - - - - ABCA13 5 3 1 - - - - - ASXL1 5 1 - - Yes - - - BBS10 5 0 - - - - - - BRCA2 5 6 1 Yes Yes Yes Yes - CENPJ 5 1 - - - - - - CEP290 5 5 - - - - - - CYP3A5 5 2 - - - - - - DNAH12 5 6 - - - - - - DNAH6 5 1 1 - - - - - EPPK1 5 4 - - - - - - ESYT3 5 1 - - - - - - FRAS1 5 4 - - - - - - HGC6.3 5 0 - - - - - - IGFN1 5 5 - - - - - - KCP 5 4 - - - - - - LRRC43 5 0 - - - - - - MCTP2 5 1 - - - - - - MPO 5 1 - - - - - - MUC4 5 5 - - - - - - OBSCN 5 8 2 - - - - - PALB2 5 0 - Yes - Yes Yes - SLCO1B3 5 2 - - - - - - SYT15 5 3 - - - - - - XIRP2 5 3 1 - - - - - ZNF266 5 2 - - - - - - ZNF530 5 1 - - - - - - ACACB 4 1 1 - - - - - ALS2CL 4 2 - - - - - - AMER3 4 0 2 - - - - - ANKRD35 4 4 - - - - - - ATP10B 4 1 - - - - - - ATP8B3 4 6 - - - - - - C10orf95 4 0 - - - - - - C2orf88 4 0 - - - - - - C5orf42 4 2 - - - -
    [Show full text]
  • Plasma Membrane Ion Channels and Epithelial to Mesenchymal Transition in Cancer Cells
    2311 I Azimi and G R Monteith Ion channels and EMT 23:11 R517–R525 Review in cancer Plasma membrane ion channels and epithelial to mesenchymal transition in cancer cells Iman Azimi1,2,3 and Gregory R Monteith1,2,3 Correspondence should be addressed 1 The School of Pharmacy, The University of Queensland, Brisbane, Queensland, Australia to G R Monteith 2 Mater Research Institute, The University of Queensland, Brisbane, Queensland, Australia Email 3 Translational Research Institute, Brisbane, Queensland, Australia [email protected] Abstract A variety of studies have suggested that epithelial to mesenchymal transition (EMT) Key Words may be important in the progression of cancer in patients through metastasis and/or f calcium therapeutic resistance. A number of pathways have been investigated in EMT in cancer f cell signalling cells. Recently, changes in plasma membrane ion channel expression as a consequence f intracellular signalling of EMT have been reported. Other studies have identified specific ion channels able to f metastasis regulate aspects of EMT induction. The utility of plasma membrane ion channels as targets for pharmacological modulation make them attractive for therapeutic approaches to target EMT. In this review, we provide an overview of some of the key plasma membrane ion channel types and highlight some of the studies that are beginning to define changes in plasma membrane ion channels as a consequence of EMT and also their possible roles in Endocrine-Related Cancer Endocrine-Related Cancer Endocrine-Related EMT induction. (2016) 23, R517–R525 Introduction Epithelial to mesenchymal transition (EMT) refers to the treatment of the primary tumour are often feasible process whereby epithelial cells which typically exhibit (e.g.
    [Show full text]
  • Loss of 18Q22.3 Involving the Carboxypeptidase of Glutamate-Like Gene Is Associated with Poor Prognosis in Resected Pancreatic Cancer
    Published OnlineFirst November 29, 2011; DOI: 10.1158/1078-0432.CCR-11-1903 Clinical Cancer Imaging, Diagnosis, Prognosis Research Loss of 18q22.3 Involving the Carboxypeptidase of Glutamate-like Gene Is Associated with Poor Prognosis in Resected Pancreatic Cancer Jih-Hsiang Lee1, Elisa Giovannetti4, Jin-Hyeok Hwang1,5, Iacopo Petrini1, Qiuyan Wang1, Johannes Voortman1,4, Yonghong Wang2, Seth M. Steinberg3, Niccola Funel6, Paul S. Meltzer2, Yisong Wang1, and Giuseppe Giaccone1 Abstract Purposes: Pancreatic cancer is the fourth leading cause of cancer-related death, and studies on the clinical relevance of its genomic imbalances are warranted. Experimental Design: Recurrent copy number alterations of cytobands and genes were analyzed by array comparative genomic hybridization (aCGH) in 44 resected pancreatic cancer specimens. Prognostic markers identified by aCGH were validated by PCR gene copy number assay in an independent validation cohort of 61 resected pancreatic cancers. The functions of gene identified were evaluated by proliferation, cell cycle, and migration assays in pancreatic cancer cells. Results: We showed recurrent copy number gains and losses in the first cohort. Loss of 18q22.3 was significantly associated with short-term overall survival in the first cohort (P ¼ 0.019). This cytoband includes the carboxypeptidase of glutamate-like (CPGL) gene. CPGL gene deletion was associated with shorter overall survival in the validation cohort (P ¼ 0.003). CPGL deletion and mutations of TP53 or Kras seem to be independent events. A Cox model analysis of the two cohorts combined showed that loss of 18q22.3/deletion of the CPGL gene was an independent poor prognostic factor for overall survival (HR ¼ 2.72, P ¼ 0.0007).
    [Show full text]
  • Supplementary Methods
    Heterogeneous Contribution of Microdeletions in the Development of Common Generalized and Focal epilepsies. SUPPLEMENTARY METHODS Epilepsy subtype extended description. Genetic Gereralized Epilepsy (GGE): Features unprovoked tonic and/or clonic seizures, originated inconsistently at some focal point within the brain that rapidly generalizes engaging bilateral distributed spikes and waves discharges on the electroencephalogram. This generalization can include cortical and sub cortical structures but not necessarily the entire cortex[1]. GGE is the most common group of epilepsies accounting for 20% of all cases[2]. It is characterized by an age-related onset and a strong familial aggregation and heritability which allows the assumption of a genetic cause. Although genetic associations have been identified, a broad spectrum of causes is acknowledged and remains largely unsolved [3]. Rolandic Epilepsy (RE): Commonly known also as Benign Epilepsy with Centrotemporal Spikes (BECTS), hallmarks early onset diagnosis (mean onset = 7 years old) with brief, focal hemifacial or oropharyngeal sensorimotor seizures alongside speech arrest and secondarily generalized tonic– clonic seizures, which mainly occur during sleep[4]. Rolandic epilepsy features a broad spectrum of less benign related syndromes called atypical Rolandic epilepsy (ARE), including benign partial epilepsy (ABPE), Landau–Kleffner syndrome(LKS) and epileptic encephalopathy with continuous spike-and-waves during sleep (CSWSS)[5]. Together they are the most common childhood epilepsy with a prevalence of 0.2–0.73/1000 (i.e. _1/2500)[6]. Adult Focal Epilepsy (AFE). Focal epilepsy is characterized by sporadic events of seizures originated within a specific brain region and restricted to one hemisphere. Although they can exhibit more than one network of wave discharges on the electroencephalogram, and different degrees of spreading, they feature a consistent site of origin.
    [Show full text]
  • Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
    Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A.
    [Show full text]
  • Looking for Missing Proteins in the Proteome Of
    Looking for Missing Proteins in the Proteome of Human Spermatozoa: An Update Yves Vandenbrouck, Lydie Lane, Christine Carapito, Paula Duek, Karine Rondel, Christophe Bruley, Charlotte Macron, Anne Gonzalez de Peredo, Yohann Coute, Karima Chaoui, et al. To cite this version: Yves Vandenbrouck, Lydie Lane, Christine Carapito, Paula Duek, Karine Rondel, et al.. Looking for Missing Proteins in the Proteome of Human Spermatozoa: An Update. Journal of Proteome Research, American Chemical Society, 2016, 15 (11), pp.3998-4019. 10.1021/acs.jproteome.6b00400. hal-02191502 HAL Id: hal-02191502 https://hal.archives-ouvertes.fr/hal-02191502 Submitted on 19 Mar 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Journal of Proteome Research 1 2 3 Looking for missing proteins in the proteome of human spermatozoa: an 4 update 5 6 Yves Vandenbrouck1,2,3,#,§, Lydie Lane4,5,#, Christine Carapito6, Paula Duek5, Karine Rondel7, 7 Christophe Bruley1,2,3, Charlotte Macron6, Anne Gonzalez de Peredo8, Yohann Couté1,2,3, 8 Karima Chaoui8, Emmanuelle Com7, Alain Gateau5, AnneMarie Hesse1,2,3, Marlene 9 Marcellin8, Loren Méar7, Emmanuelle MoutonBarbosa8, Thibault Robin9, Odile Burlet- 10 Schiltz8, Sarah Cianferani6, Myriam Ferro1,2,3, Thomas Fréour10,11, Cecilia Lindskog12,Jérôme 11 1,2,3 7,§ 12 Garin , Charles Pineau .
    [Show full text]
  • A Framework to Identify Contributing Genes In
    A framework to identify contributing genes in patients with Phelan-McDermid syndrome Anne-Claude Tabet, Thomas Rolland, Marie Ducloy, Jonathan Levy, Julien Buratti, Alexandre Mathieu, Damien Haye, Laurence Perrin, Céline Dupont, Sandrine Passemard, et al. To cite this version: Anne-Claude Tabet, Thomas Rolland, Marie Ducloy, Jonathan Levy, Julien Buratti, et al.. A frame- work to identify contributing genes in patients with Phelan-McDermid syndrome. npj Genomic Medicine, Springer Nature, 2019, 4 (1), pp.16. 10.1038/s41525-019-0090-y. hal-02347889 HAL Id: hal-02347889 https://hal.archives-ouvertes.fr/hal-02347889 Submitted on 16 Dec 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. bioRxiv preprint doi: https://doi.org/10.1101/117978; this version posted March 18, 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. A framework to identify modifier genes in patients
    [Show full text]
  • Identification of Candidate Biomarkers and Pathways Associated with Type 1 Diabetes Mellitus Using Bioinformatics Analysis
    bioRxiv preprint doi: https://doi.org/10.1101/2021.06.08.447531; this version posted June 9, 2021. 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. Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karnataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2021.06.08.447531; this version posted June 9, 2021. 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. Abstract Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were then performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway.
    [Show full text]
  • Single Cell Derived Clonal Analysis of Human Glioblastoma Links
    SUPPLEMENTARY INFORMATION: Single cell derived clonal analysis of human glioblastoma links functional and genomic heterogeneity ! Mona Meyer*, Jüri Reimand*, Xiaoyang Lan, Renee Head, Xueming Zhu, Michelle Kushida, Jane Bayani, Jessica C. Pressey, Anath Lionel, Ian D. Clarke, Michael Cusimano, Jeremy Squire, Stephen Scherer, Mark Bernstein, Melanie A. Woodin, Gary D. Bader**, and Peter B. Dirks**! ! * These authors contributed equally to this work.! ** Correspondence: [email protected] or [email protected]! ! Supplementary information - Meyer, Reimand et al. Supplementary methods" 4" Patient samples and fluorescence activated cell sorting (FACS)! 4! Differentiation! 4! Immunocytochemistry and EdU Imaging! 4! Proliferation! 5! Western blotting ! 5! Temozolomide treatment! 5! NCI drug library screen! 6! Orthotopic injections! 6! Immunohistochemistry on tumor sections! 6! Promoter methylation of MGMT! 6! Fluorescence in situ Hybridization (FISH)! 7! SNP6 microarray analysis and genome segmentation! 7! Calling copy number alterations! 8! Mapping altered genome segments to genes! 8! Recurrently altered genes with clonal variability! 9! Global analyses of copy number alterations! 9! Phylogenetic analysis of copy number alterations! 10! Microarray analysis! 10! Gene expression differences of TMZ resistant and sensitive clones of GBM-482! 10! Reverse transcription-PCR analyses! 11! Tumor subtype analysis of TMZ-sensitive and resistant clones! 11! Pathway analysis of gene expression in the TMZ-sensitive clone of GBM-482! 11! Supplementary figures and tables" 13" "2 Supplementary information - Meyer, Reimand et al. Table S1: Individual clones from all patient tumors are tumorigenic. ! 14! Fig. S1: clonal tumorigenicity.! 15! Fig. S2: clonal heterogeneity of EGFR and PTEN expression.! 20! Fig. S3: clonal heterogeneity of proliferation.! 21! Fig.
    [Show full text]