New Insights Into Testicular Germ Cell Tumorigenesis from Gene Expression Profiling1

Total Page:16

File Type:pdf, Size:1020Kb

New Insights Into Testicular Germ Cell Tumorigenesis from Gene Expression Profiling1 [CANCER RESEARCH 62, 2359–2364, April 15, 2002] New Insights into Testicular Germ Cell Tumorigenesis from Gene Expression Profiling1 Rolf I. Skotheim, Outi Monni, Spyro Mousses, Sophie D. Fosså, Olli-P. Kallioniemi, Ragnhild A. Lothe,2 and Anne Kallioniemi Department of Genetics, Institute for Cancer Research [R. I. S., R. A. L.] and Department for Oncology and Radiotherapy [S. D. F.], The Norwegian Radium Hospital, N-0310 Oslo, Norway; Biomedicum Biochip Center, Biomedicum Helsinki, FIN-00290 Helsinki, Finland [O. M.]; Cancer Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland 20892 [O. M., S. M., O-P. K., A. K.]; and Laboratory of Cancer Genetics, Institute of Medical Technology, University of Tampere and Tampere University Hospital, FIN-33520 Tampere, Finland [A. K.] ABSTRACT teristic of virtually all TGCTs (4, 5). In addition, specific gains and losses from several other chromosomal regions have been described. 3 We have shown recently that about half of the human TGCTs reveal Although molecular studies have shown some genes to be altered at DNA copy number increases affecting two distinct regions on chromosome the DNA and/or expression levels in a limited number of TGCTs, the arm 17q. To identify potential target genes with elevated expressions attributable to the extra copies, we constructed a cDNA microarray target genes reflecting the nonrandom chromosomal aberrations re- containing 636 genes and expressed sequence tags from chromosome 17. main unknown (for a review of TGCT genetics, see Refs. 6 and 7). The expression patterns of 14 TGCTs, 1 carcinoma in situ, and 3 normal We have demonstrated recently by a genome-wide copy number testis samples were examined, all with known chromosome 17 copy num- analysis using CGH that sequences on chromosome arm 17q are bers. The growth factor receptor-bound protein 7 (GRB7) and junction frequently overrepresented in TGCTs, and two common regions of plakoglobin (JUP) were the two most highly overexpressed genes in the copy number increase were identified (8). Gain of the proximal TGCTs. GRB7 is tightly linked to ERBB2 and is coamplified and coex- region, 17q11–q21, is preferentially observed in nonseminomas, pressed with this gene in several cancer types. Interestingly, the expression whereas gain of the distal region, 17q24–qter, is common to all levels of ERBB2 were not elevated in the TGCTs, suggesting that GRB7 TGCTs (8). Nonrandom gain at 17q has also been reported in several might be the target for the increased DNA copy number in TGCTs. other cancer types (9–13). Because of the limited knowledge of altered gene expression in the devel- opment of TGCTs, we also examined the expression levels of 512 addi- To identify differentially expressed genes on chromosome 17 in tional genes located throughout the genome. Several genes novel to tes- TGCTs, we analyzed a series of TGCTs and normal testicular samples ticular tumorigenesis were consistently up- or down-regulated, including using a custom-made cDNA microarray with a comprehensive chro- POV1, MYCL1, MYBL2, MXI1, and DNMT2. Additionally, overexpression mosome 17 coverage (14). All analyzed tumors had been studied of the proto-oncogenes CCND2 and MYCN were confirmed from the previously by CGH, and thus, the expression profiles could be related literature. The overexpressions were for some of the target genes closely to the DNA copy numbers. The expression levels of 512 additional associated to either seminoma or nonseminoma TGCTs, and hierarchical genes mapping elsewhere in the genome, including many cancer- cluster analysis of the gene expression data effectively distinguished related genes, were also analyzed in the same set of TGCT samples. among the known histological subtypes. In summary, this focused func- tional genomic characterization of TGCTs has lead to the identification of new gene targets associated with a common genomic rearrangement as MATERIALS AND METHODS well as other genes with potential importance to testicular tumorigenesis. Tumor and Cell Line Samples. Eighteen testicular tissue samples were analyzed, including 8 pure seminomas, 6 nonseminomas, 1 carcinoma in situ INTRODUCTION (from the vicinity of a nonseminoma), and 3 normal samples. The tumors were selected from a series of primary TGCTs analyzed previously by CGH (8). TGCT3 is the most common malignancy among adolescent and Four of the 8 seminomas had gains at distal 17q, including the 17q24–qter young adult Caucasian males, and the incidence has been steadily region (Fig. 1A). The 6 nonseminomas (4 embryonal carcinomas and 2 im- increasing over the past 50 years (1, 2). TGCTs are classified into two mature teratomas) had large gains at chromosome 17, all including the 17q11– main histological subtypes, seminomas and nonseminomas, and there q21 region. The use of these samples in cDNA microarray experiments was are two models describing their development from carcinomas in situ approved by the Regional Committee for Medical Research Ethics in Norway and the NIH Office of Human Subjects Research. (3). Either both subtypes develop independently from carcinomas in A pool of two breast cancer cell lines, HBL100 and MDA-436 (American situ, or they develop as a continuum where seminomas may progress Type Culture Collection, Manassas, VA), was used as a common reference in further into nonseminomas. the cDNA microarray experiments. These cell lines were selected based on the TGCTs are generally in the triploid range, and isochromosome 12p facts that they show no increase in copy number at 17q and express most genes or gain of DNA sequences from chromosome arm 12p is a charac- on the cDNA microarray to some extent (10, 14). cDNA Microarray Experiments. The construction of the cDNA microar- Received 12/27/01; accepted 2/14/02. ray with comprehensive chromosome 17 coverage has been described previ- The costs of publication of this article were defrayed in part by the payment of page ously by Monni et al. (14). The microarray consisted of printed PCR products charges. This article must therefore be hereby marked advertisement in accordance with from 636 sequence-verified IMAGE cDNA clones (Research Genetics, Hunts- 18 U.S.C. Section 1734 solely to indicate this fact. ville, AL), including 201 known genes from the entire chromosome 17 and 435 1 Supported by the Research Council of Norway (to R. I. S.) and the Norwegian Cancer Society (to R. A. L.). ESTs from the 17q arm. An additional 512 sequence-verified IMAGE cDNA 2 To whom requests for reprints should be addressed, at Department of Genetics, clones were placed on the array, representing transcribed sequences located Institute for Cancer Research, The Norwegian Radium Hospital, N-0310 Oslo, Norway. elsewhere in the genome. Eighty-eight of these were housekeeping genes and Phone: 47-22934415; Fax: 47-22934440; E-mail: [email protected]. were used for calibration among the different experiments (15), 162 were a 3 The abbreviations used are: TGCT, testicular germ cell tumor; CCND2, cyclin D2; CGH, comparative genomic hybridization; DNMT2, DNA (cytosine-5)-methyltransferase 2; selection of known or putative cancer-related genes, and 262 were a collection ERBB2, v-erb-b2 avian erythroblastic leukemia viral oncogene homolog 2; EST, expressed of genes and ESTs from chromosome 10. sequence tag; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; GRB7, growth factor Preparation and printing of the cDNA clones on glass slides, probe prepa- receptor-bound protein 7; JUP, junction plakoglobin; LLGL2, lethal giant larvae (Drosophila) rations, hybridizations, and image generation and analyses were performed as homolog 2; MYBL2, B-Myb; MYCL1, L-Myc; MYCN, N-Myc; MXI1, MAX-interacting protein 1; PDE6G, phosphodiesterase 6G, cGMP-specific, rod, gamma; POV1, prostate cancer described (16). Briefly, mRNA was isolated from the test samples by using the overexpressed gene 1; RT-PCR, reverse transcription-PCR. Trizol reagent (Life Technologies, Inc., Rockville, MD) and oligo(dT)25 dyna- 2359 Downloaded from cancerres.aacrjournals.org on September 24, 2021. © 2002 American Association for Cancer Research. GENE EXPRESSION IN TESTICULAR GERM CELL TUMORS Fig. 1. Genetic changes in testicular germ cell tumors. A, genomic copy number gains on chromo- some 17 as seen by comparative genomic hybrid- ization. Each colored bar represents gain from the corresponding chromosome segment in the tumor indicated below. B, sample tree (dendrogram) from the hierarchical cluster analysis of 18 testicular samples. Letters below the dendrogram represent the tissue sources: N, normal testis; C, carcinoma in situ; I, immature teratoma; E, embryonal carci- noma, and S, seminoma. The vertical distances on the dendrogram reflect the relatedness of neighbor- ing samples. A gene expression map with pseudo- colors coding for the normalized ratios of up- and down-regulated genes in TGCTs located on chro- mosome 17 (C) and elsewhere in the genome (D)is shown. Transcribed sequences are presented in rows, and each experiment (cDNA sample) is shown in columns. Thus, each cell in the matrix represents the expression level of a single transcript in a single sample. Numbers in parentheses behind the ESTs provide the IMAGE clone ids. E, color coding for the normalized expression ratios (ex- pression relative to the average expressions in the three normal samples). beads (Dynal Biotech, Oslo, Norway) according to the manufacturers’ speci- data were hierarchically clustered by both gene and sample sides (501 clones fications. From the
Recommended publications
  • Bioinformatics Analysis of Weighted Genes in Diabetic Retinopathy
    Retina Bioinformatics Analysis of Weighted Genes in Diabetic Retinopathy Zhi-Peng You,1 Yu-Lan Zhang,1 Bing-Yang Li,1 Xin-Gen Zhu,2 and Ke Shi1 1Department of Ophthalmology, The Second Affiliated Hospital, Nanchang University, Nanchang, China 2Department of Neurosurgery, The Second Affiliated Hospital, Nanchang University, Nanchang, China Correspondence: Ke Shi, The Second PURPOSE. Intricate signaling networks and transcriptional regulators translate pathogen Affiliated Hospital of Nanchang Uni- recognition into defense responses. The aim of this study was to identify the weighted genes versity, No.1 Minde Road, Nanchang involved in diabetic retinopathy (DR) in different rodent models of diabetes. 330006, Jiangxi, People’s Republic of China; METHODS. We performed a gene coexpression analysis of publicly available microarray data, [email protected]. namely, the GSE19122 dataset from the Gene Expression Omnibus database. We conducted Z-PY and Y-LZ equally contributed to gene coexpression analysis on the microarray data to identify modules of functionally related the work. coexpressed genes that are differentially expressed in different rodent models. We leveraged a richly curated expression dataset and used weighted gene coexpression network analysis to Submitted: August 13, 2018 construct an undirected network. We screened 30 genes in the most closely related module. A Accepted: October 22, 2018 protein-protein interaction network was constructed for the genes in the most related module Citation: You Z-P, Zhang Y-L, Li B-Y, using the Search Tool for the Retrieval of Interacting Genes. Gene Ontology enrichment Zhu X-G, Shi K. Bioinformatics analysis analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were of weighted genes in diabetic reti- performed for the 30 genes.
    [Show full text]
  • Mouse Models of Inherited Retinal Degeneration with Photoreceptor Cell Loss
    cells Review Mouse Models of Inherited Retinal Degeneration with Photoreceptor Cell Loss 1, 1, 1 1,2,3 1 Gayle B. Collin y, Navdeep Gogna y, Bo Chang , Nattaya Damkham , Jai Pinkney , Lillian F. Hyde 1, Lisa Stone 1 , Jürgen K. Naggert 1 , Patsy M. Nishina 1,* and Mark P. Krebs 1,* 1 The Jackson Laboratory, Bar Harbor, Maine, ME 04609, USA; [email protected] (G.B.C.); [email protected] (N.G.); [email protected] (B.C.); [email protected] (N.D.); [email protected] (J.P.); [email protected] (L.F.H.); [email protected] (L.S.); [email protected] (J.K.N.) 2 Department of Immunology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand 3 Siriraj Center of Excellence for Stem Cell Research, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand * Correspondence: [email protected] (P.M.N.); [email protected] (M.P.K.); Tel.: +1-207-2886-383 (P.M.N.); +1-207-2886-000 (M.P.K.) These authors contributed equally to this work. y Received: 29 February 2020; Accepted: 7 April 2020; Published: 10 April 2020 Abstract: Inherited retinal degeneration (RD) leads to the impairment or loss of vision in millions of individuals worldwide, most frequently due to the loss of photoreceptor (PR) cells. Animal models, particularly the laboratory mouse, have been used to understand the pathogenic mechanisms that underlie PR cell loss and to explore therapies that may prevent, delay, or reverse RD. Here, we reviewed entries in the Mouse Genome Informatics and PubMed databases to compile a comprehensive list of monogenic mouse models in which PR cell loss is demonstrated.
    [Show full text]
  • GSKB: a Gene Set Database for Pathway Analysis in Mouse
    bioRxiv preprint doi: https://doi.org/10.1101/082511; this version posted October 24, 2016. 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 4.0 International license. GSKB: A gene set database for pathway analysis in mouse Liming Lai1, Jason Hennessey1, Valerie Bares1, Eun Woo Son1, Yuguang Ban1, Wei Wang1, Jianli Qi1, Gaixin Jiang1, Arthur Liberzon2, and Steven Xijin Ge1* 1Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA 2Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA * Corresponding author: Tel: +1-605-688-5845; Email: [email protected] ABSTRACT: Interpretation of high-throughput genomics data based on biological pathways constitutes a constant challenge, partly because of the lack of supporting pathway database. In this study, we created a functional genomics knowledgebase in mouse, which includes 33,261 pathways and gene sets compiled from 40 sources such as Gene Ontology, KEGG, GeneSetDB, PANTHER, microRNA and transcription factor target genes, etc. In addition, we also manually collected and curated 8,747 lists of differentially expressed genes from 2,526 published gene expression studies to enable the detection of similarity to previously reported gene expression signatures. These two types of data constitute a Gene Set Knowledgebase (GSKB), which can be readily used by various pathway analysis software such as gene set enrichment analysis (GSEA). Using our knowledgebase, we were able to detect the correct microRNA (miR-29) pathway that was suppressed using antisense oligonucleotides and confirmed its role in inhibiting fibrogenesis, which might involve upregulation of transcription factor SMAD3.
    [Show full text]
  • ABSTRACT Using a Bioinformatics Approach to Identify Genes That
    ABSTRACT Using a bioinformatics approach to identify genes that have possible candidacy of association with retinitis pigmentosa: GeneWeaver Natasha Lie Director: Erich J. Baker, Ph.D. Retinitis pigmentosa (RP) is a retinal degenerative disorder that affects about 1 in 3,000 people. The disease is genetic in cause, and currently there is no cure. The genetic cause of the disease may be contributed to one of several different genes, underscoring the complex genetic underpinnings of this disease. The information required to determine which genes are potentially causative for RP may exist, but it is difficult to determine which genes are most suitable for study because of the immense wealth and breadth of available information. In other words, large-scale heterogeneous species-specific data often obfuscates the true causative genetic background of RP. In this study we describe a method of identifying genes that may contribute to RP using the bioinformatics techniques of graph theory and database utilization. We report a potential ranked list of genes in which disruptions are likely causative of RP. APPROVED BY DIRECTOR OF HONORS THESIS: ___________________________________________________ Dr. Erich Baker, School of Engineering and Computer Science APPROVED BY THE HONORS PROGRAM: ______________________________________________ Dr. Elizabeth Corey, Director DATE: _________________________ USING A BIOINFORMATICS APPROACH TO IDENTIFY GENES THAT HAVE POSSIBLE CANDIDACY OF ASSOCIATION WITH RETINITIS PIGMENTOSA: GENEWEAVER A Thesis Submitted to the
    [Show full text]
  • Evolution and Expression of the Phosphodiesterase 6 Genes Unveils Vertebrate Novelty to Control Photosensitivity David Lagman, Ilkin E
    Lagman et al. BMC Evolutionary Biology (2016) 16:124 DOI 10.1186/s12862-016-0695-z RESEARCH ARTICLE Open Access Evolution and expression of the phosphodiesterase 6 genes unveils vertebrate novelty to control photosensitivity David Lagman, Ilkin E. Franzén, Joel Eggert, Dan Larhammar† and Xesús M. Abalo*† Abstract Background: Phosphodiesterase 6 (PDE6) is a protein complex that hydrolyses cGMP and acts as the effector of the vertebrate phototransduction cascade. The PDE6 holoenzyme consists of catalytic and inhibitory subunits belonging to two unrelated gene families. Rods and cones express distinct genes from both families: PDE6A and PDE6B code for the catalytic and PDE6G the inhibitory subunits in rods while PDE6C codes for the catalytic and PDE6H the inhibitory subunits in cones. We performed phylogenetic and comparative synteny analyses for both gene families in genomes from a broad range of animals. Furthermore, gene expression was investigated in zebrafish. Results: We found that both gene families expanded from one to three members in the two rounds of genome doubling (2R) that occurred at the base of vertebrate evolution. The PDE6 inhibitory subunit gene family appears to be unique to vertebrates and expanded further after the teleost-specific genome doubling (3R). We also describe a new family member that originated in 2R and has been lost in amniotes, which we have named pde6i. Zebrafish has retained two additional copies of the PDE6 inhibitory subunit genes after 3R that are highly conserved, have high amino acid sequence identity, are coexpressed in the same photoreceptor type as their amniote orthologs and, interestingly, show strikingly different daily oscillation in gene expression levels.
    [Show full text]
  • Integrative RNA-Seq and ATAC-Seq Analysis of Retinitis Pigmentosa Caused by PDE6 Mutation
    Integrative RNA-seq and ATAC-seq Analysis of Retinitis Pigmentosa Caused by PDE6 Mutation Wenrong Xu Kunming Medical University Yan Li Aliated Hospital of Yunnan University Xiaoxiao Feng Aliated Hospital of Yunnan University Libo Xiao Aliated Hospital of Yunnan University Lan Li The Aliated Calmette Hospital of Kunming Medical University Kangwei Jiao ( [email protected] ) Aliated Hospital of Yunnan University Research Article Keywords: ATAC-seq, RNA-seq, Retinitis pigmentosa, PARP1, retina tissues Posted Date: August 30th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-735055/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/12 Abstract Purpose: Inhibition of PARP1 could relieve PDE6 mutation-induced Retinitis pigmentosa (RP). However, the mechanism related with PARP1 overexpression in the RP has not been claried. We attempted to explore the potential regulatory mechanism related with PARP1 underlying RP. Methods: ATAC-seq and RNA-seq were preformed for retina tissues of C3H and rd1 mice. The differential expressed genes (DEGs) were identied, followed by PARP1-DEG coexpression network, and PPI network construction. GO-BP and pathway enrichment of DEGs of interest were performed by clusterproler software. The overlapped genes that might play regulatory role in PARP1 expression were mined by integrated analysis of RNA-seq and ATAC-seq data. Results: Total 1061 DEGs were identied between C3H and rd1 group. Co-expression network was constructed with 313 PARP1-gene coexpression pairs. The down-regulated DEGs were closely related with visual perception, light stimulus related biological process, while the up-regulated DEGs were signicantly enriched in phototransduction and PPAR signaling pathway.
    [Show full text]
  • Genomic Analyses of Early Responses to Radiation in Glioblastoma Reveal
    www.nature.com/scientificreports OPEN Genomic analyses of early responses to radiation in glioblastoma reveal new alterations at transcription, splicing, and translation levels Saket Choudhary1,5, Suzanne C. Burns2,5,6, Hoda Mirsafan1, Wenzheng Li1, Dat T. Vo4, Mei Qiao2, Xiufen Lei2, Andrew D. Smith1 & Luiz O. Penalva2,3 ✉ High-dose radiation is the main component of glioblastoma therapy. Unfortunately, radio-resistance is a common problem and a major contributor to tumor relapse. Understanding the molecular mechanisms driving response to radiation is critical for identifying regulatory routes that could be targeted to improve treatment response. We conducted an integrated analysis in the U251 and U343 glioblastoma cell lines to map early alterations in the expression of genes at three levels: transcription, splicing, and translation in response to ionizing radiation. Changes at the transcriptional level were the most prevalent response. Downregulated genes are strongly associated with cell cycle and DNA replication and linked to a coordinated module of expression. Alterations in this group are likely driven by decreased expression of the transcription factor FOXM1 and members of the E2F family. Genes involved in RNA regulatory mechanisms were afected at the mRNA, splicing, and translation levels, highlighting their importance in radiation-response. We identifed a number of oncogenic factors, with an increased expression upon radiation exposure, including BCL6, RRM2B, IDO1, FTH1, APIP, and LRIG2 and lncRNAs NEAT1 and FTX. Several of these targets have been previously implicated in radio- resistance. Therefore, antagonizing their efects post-radiation could increase therapeutic efcacy. Our integrated analysis provides a comprehensive view of early response to radiation in glioblastoma.
    [Show full text]
  • Downloaded from the Ensembl FTP Server (Ftp://Ftp.Ensembl.Org/Pub/Release-98/)
    Preussner et al. Genome Biology (2020) 21:186 https://doi.org/10.1186/s13059-020-02102-3 RESEARCH Open Access Splicing-accessible coding 3′UTRs control protein stability and interaction networks Marco Preussner1†, Qingsong Gao2†, Eliot Morrison3†, Olga Herdt1, Florian Finkernagel4, Michael Schumann5, Eberhard Krause5, Christian Freund3, Wei Chen6* and Florian Heyd1* * Correspondence: chenw@sustech. edu.cn; [email protected] Abstract † Marco Preussner, Qingsong Gao ′ ′ and Eliot Morrison contributed Background: 3 -Untranslated regions (3 UTRs) play crucial roles in mRNA metabolism, equally to this work. such as by controlling mRNA stability, translation efficiency, and localization. 6Department of Biology, South Intriguingly, in some genes the 3′UTR is longer than their coding regions, pointing to University of Science and ′ Technology of China, Shenzhen, additional, unknown functions. Here, we describe a protein-coding function of 3 Guangdong, China UTRs upon frameshift-inducing alternative splicing in more than 10% of human and 1Institute of Chemistry and mouse protein-coding genes. Biochemistry, Freie Universität Berlin, Laboratory of RNA Results: 3′UTR-encoded amino acid sequences show an enrichment of PxxP motifs Biochemistry, Takustrasse 6, 14195 and lead to interactome rewiring. Furthermore, an elevated proline content increases Berlin, Germany Full list of author information is protein disorder and reduces protein stability, thus allowing splicing-controlled available at the end of the article regulation of protein half-life. This could also act as a surveillance mechanism for erroneous skipping of penultimate exons resulting in transcripts that escape nonsense mediated decay. The impact of frameshift-inducing alternative splicing on disease development is emphasized by a retinitis pigmentosa-causing mutation leading to translation of a 3′UTR-encoded, proline-rich, destabilized frameshift-protein with altered protein-protein interactions.
    [Show full text]
  • Gene Expression in the Mouse Eye: an Online Resource for Genetics Using 103 Strains of Mice
    Molecular Vision 2009; 15:1730-1763 <http://www.molvis.org/molvis/v15/a185> © 2009 Molecular Vision Received 3 September 2008 | Accepted 25 August 2009 | Published 31 August 2009 Gene expression in the mouse eye: an online resource for genetics using 103 strains of mice Eldon E. Geisert,1 Lu Lu,2 Natalie E. Freeman-Anderson,1 Justin P. Templeton,1 Mohamed Nassr,1 Xusheng Wang,2 Weikuan Gu,3 Yan Jiao,3 Robert W. Williams2 (First two authors contributed equally to this work) 1Department of Ophthalmology and Center for Vision Research, Memphis, TN; 2Department of Anatomy and Neurobiology and Center for Integrative and Translational Genomics, Memphis, TN; 3Department of Orthopedics, University of Tennessee Health Science Center, Memphis, TN Purpose: Individual differences in patterns of gene expression account for much of the diversity of ocular phenotypes and variation in disease risk. We examined the causes of expression differences, and in their linkage to sequence variants, functional differences, and ocular pathophysiology. Methods: mRNAs from young adult eyes were hybridized to oligomer microarrays (Affymetrix M430v2). Data were embedded in GeneNetwork with millions of single nucleotide polymorphisms, custom array annotation, and information on complementary cellular, functional, and behavioral traits. The data include male and female samples from 28 common strains, 68 BXD recombinant inbred lines, as well as several mutants and knockouts. Results: We provide a fully integrated resource to map, graph, analyze, and test causes and correlations of differences in gene expression in the eye. Covariance in mRNA expression can be used to infer gene function, extract signatures for different cells or tissues, to define molecular networks, and to map quantitative trait loci that produce expression differences.
    [Show full text]
  • Clinical Phenotype of PDE6B-Associated Retinitis Pigmentosa
    International Journal of Molecular Sciences Article Clinical Phenotype of PDE6B-Associated Retinitis Pigmentosa Laura Kuehlewein 1,2,*, Ditta Zobor 1, Katarina Stingl 2,3 , Melanie Kempf 2,3, Fadi Nasser 1 , Antje Bernd 2, Saskia Biskup 4, Frans P.M. Cremers 5,6, Muhammad Imran Khan 5,6, Pascale Mazzola 7, Karin Schäferhoff 7, Tilman Heinrich 7,8, Tobias B. Haack 7,8, Bernd Wissinger 9, Eberhart Zrenner 1,10, Nicole Weisschuh 9 and Susanne Kohl 9 1 Institute for Ophthalmic Research, Centre for Ophthalmology, Eberhard Karls University Tübingen, 72076 Tübingen, Germany; [email protected] (D.Z.); [email protected] (F.N.); [email protected] (E.Z.) 2 University Eye Hospital, Centre for Ophthalmology, Eberhard Karls University Tübingen, 72076 Tübingen, Germany; [email protected] (K.S.); [email protected] (M.K.); [email protected] (A.B.) 3 Center for Rare Eye Diseases, Eberhard Karls University Tübingen, 72076 Tübingen, Germany 4 CeGaT GmbH, 72076 Tuebingen, Germany; [email protected] 5 Department of Human Genetics, Radboud University Medical Center, 6500 HB Nijmegen, The Netherlands; [email protected] (F.P.M.C.); [email protected] (M.I.K.) 6 Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 AJ Nijmegen, The Netherlands 7 Institute for Medical Genetics and Applied Genomics, University Hospital, Eberhard Karls University Tübingen, 72076 Tübingen, Germany; [email protected]
    [Show full text]
  • Towards Retinal Repair: Analysis of Photoreceptor Precursor Cells and Their Cell Surface Molecules
    Towards retinal repair: analysis of photoreceptor precursor cells and their cell surface molecules Ya-Ting Han University College London Institute of Child Health A thesis submitted for the degree of Philosophiae Doctor For the incredible cells that drive me here. ii Acknowledgements I would like to firstly thank my supervisor Prof. Jane Sowden for her consistent support, encouragement and advice throughout my PhD. I still remember when I just started my PhD and wanted some dendritic cells in a control experiment for some even not so exciting markers, Jane instantly contacted her colleagues to provide me these cells. Cases as such are countless. I have been encouraged to develop my own research ideas and Jane has always been supporting. It is through all these that I confidently and happily conducted my studies here. I am very happy that I chose the right supervisor. Thank you, Jane! I would also like to thank my secondary supervisor Prof. Robin Ali for his encouragements throughout, Dr. Janny Morgan for her advice during my PhD upgrade, Prof. Andy Copp, Prof. David Muller, Dr. Kenth Gustafsson, Dr. Andy Stoker, Dr. Juan-Pedro Martinez-Barbera, and Dr. Patrizia Ferretti for helpful discussion and advices. Thanks to Dr. Kevin Mills and Dr. Wendy Heywood for their supports with mass spectrometry, especially Wendy for her unlimited kind and generous help during all my time with mass spectrometry. Thanks to Dan who helped and advised me in molecular cloning. Thanks to Rachael who performed all the injections for cell transplantation. Thanks to Jorn who showed me the techniques when I just entered the lab and helped me with my first cell transplantation.
    [Show full text]
  • Eye Aging by Using Deep Learning to Predict Age from Fundus and Optical Coherence Tomography Images
    medRxiv preprint doi: https://doi.org/10.1101/2021.06.24.21259471; this version posted June 29, 2021. 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 4.0 International license . Identifying the genetic and non-genetic factors associated with accelerated eye aging by using deep learning to predict age from fundus and optical coherence tomography images Alan Le Goallec1,2, Samuel Diai1+, Sasha Collin1+, Théo Vincent1, Chirag J. Patel1* 1Department of Biomedical Informatics, Harvard Medical School, Boston, MA, 02115, USA 2Department of Systems, Synthetic and Quantitative Biology, Harvard University, Cambridge, MA, 02118, USA +Co-second authors *Corresponding author Contact information: Chirag J Patel [email protected] Abstract With age, eyesight declines and the vulnerability to age-related eye diseases such as glaucoma, cataract, macular degeneration and diabetic retinopathy increases. With the aging of the global population, the prevalence of these diseases is projected to increase, leading to reduced quality of life and increased healthcare cost. In the following, we built an eye age predictor by training convolutional neural networks to predict age from 175,000 eye fundus and optical coherence tomography images (R-Squared=83.6+-0.6%; root mean squared error=3.34+-0.07 years). We used attention maps to identify the features driving the eye age prediction. We defined accelerated eye aging as the difference between eye age and chronological age and performed a genome wide association study [GWAS] on this phenotype.
    [Show full text]