DOCSLIB.ORG

Computational Studies of the Genome Dynamics of Mammalian Transposable Elements and Their Relationships to Genes

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

COMPUTATIONAL STUDIES OF THE GENOME DYNAMICS OF MAMMALIAN TRANSPOSABLE ELEMENTS AND THEIR RELATIONSHIPS TO GENES by Ying Zhang M.Sc., Katholieke Universiteit Leuven (BELGIUM), 2004 B.E., Harbin Institute of Technology (CHINA), 1993 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE STUDIES (Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) May, 2012 © Ying Zhang, 2012 Abstract Sequences derived from transposable elements (TEs) comprise nearly 40 - 50% of the genomic DNA of most mammalian species, including mouse and human. However, what impact they may exert on their hosts is an intriguing question. Originally considered as merely genomic parasites or “selfish DNA”, these mobile elements show their detrimental effects through a variety of mechanisms, from physical DNA disruption to epigenetic regulation. On the other hand, evidence has been mounting to suggest that TEs sometimes may also play important roles by participating in essential biological processes in the host cell. The dual-roles of TE-host interactions make it critical for us to understand the relationship between TEs and the host, which may ultimately help us to better understand both normal cellular functions and disease. This thesis encompasses my three genome-wide computational studies of TE-gene dynamics in mammals. In the first, I identified high levels of TE insertional polymorphisms among inbred mouse strains, and systematically analyzed their distributional features and biological effects, through mining tens of millions of mouse genomic DNA sequences. In the second, I examined the properties of TEs located in introns, and identified key factors, such as the distance to the intron-exon boundary, insertional orientation, and proximity to splice sites, that influence the probability that TEs will be retained in genes. In the third, a study specifically focused on genes with extremely high or low TE content in three mammalian species, I showed associations between TE density and the function/conservation of genes, as well as the relevance of chromatin state to TE accumulation in genes. ii While most of my results clearly support the idea that today’s TE distribution pattern is an outcome of natural selection or genetic drift during evolution, the final part of my work, which compares TE density to chromatin state in embryonic stem cells, suggests that traces of the initial integration preference of TEs still exist. Taken together, these results demonstrated the effects of both initial TE integration and natural selection in shaping the landscape of today’s mammalian genomes and, most importantly, shed light on the roles of mobile elements in evolution. iii Preface A version of Chapter 2 has been published: Ying Zhang, Irina A. Maksakova, Liane Gagnier, Louie N. van de Lagemaat, Dixie L. Mager (2008). “Genome-wide assessments reveal extremely high levels of polymorphism of two active families of mouse endogenous retroviral elements.” PLoS Genet 4(2): e1000007. I designed all the computational methods for identifying mouse ERV polymorphisms, performed most computational data analyses, and wrote sections of the paper. I.A.M. and L.G. performed all the biological experiments for Figure 2.5 and 2.7, L.N.v.d.L. analyzed the data in Figure 2.6, D.L.M and I.A.M. wrote sections of the paper. A version of Chapter 3 has been published: Ying Zhang, Mark T. Romanish, Dixie L. Mager (2011). “Distributions of transposable elements reveal hazardous zones in Mammalian introns.” PLoS Comput Biol 7(5): e1002046. I designed and performed all the computational data analyses, and wrote sections of the paper. M.T.R. performed the biological experiments for Figure 2.8. D.L.M and M.T.R. wrote sections of the paper. A version of Chapter 4 has been published: Ying Zhang and Dixie L. Mager (2012). “Gene properties and chromatin state influence the accumulation of transposable elements in genes.” PLoS One 7(1): e30158. I designed and performed all the computational data analyses, and wrote the paper. D.L.M corrected and revised the paper. The mouse work was covered by Animal Care Certificate A09-0372 issued by the UBC Animal Care Committee. iv Table of Contents Abstract .................................................................................................................................... ii Preface ..................................................................................................................................... iv Table of Contents .................................................................................................................... v List of Tables .......................................................................................................................... xi List of Figures ........................................................................................................................ xii Acknowledgements ............................................................................................................... xv Chapter 1: Introduction ........................................................................................................ 1 1.1 Mammalian Transposable Elements ..................................................................... 2 1.1.1 Long interspersed nucleotide elements (LINEs) ................................................... 6 1.1.2 Short interspersed nucleotide elements (SINEs) ................................................... 7 1.1.3 Long terminal repeat (LTR) retrotransposons ...................................................... 8 1.1.4 DNA transposons ................................................................................................ 10 1.2 Distribution of TEs in Mammalian Genomes .................................................... 11 1.2.1 TE distribution and the local G/C content .......................................................... 12 1.2.2 TE orientation bias in genes ................................................................................ 13 1.2.3 TE density within genes ...................................................................................... 14 1.3 Initial Integration Site Preference of TEs ........................................................... 15 1.3.1 Integration site preference of retroviruses and ERVs ......................................... 16 1.3.2 Integration site preference of other TEs .............................................................. 19 1.4 Activity and Polymorphism of TEs in Mammals ............................................... 20 1.4.1 TE activity and polymorphism in humans .......................................................... 21 v 1.4.2 TE activity and polymorphism in mice ............................................................... 24 1.4.3 TE activity and polymorphism in other mammals .............................................. 26 1.5 Effects of TE Integration in the Host Genome ................................................... 29 1.5.1 TE-mediated physical damage at the DNA level ................................................ 29 1.5.2 Transcriptional influence of TE sequences on host genes .................................. 32 1.5.3 Epigenetic Effects of TEs ................................................................................... 36 1.6 Transposable Elements and Host Evolution....................................................... 39 1.6.1 TEs vs. the host genome: an everlasting battle ................................................... 39 1.6.2 TE exaptation: turning “junk” into “gold” .......................................................... 43 1.7 Thesis Objectives ................................................................................................... 47 Chapter 2: Identification and Investigation of ERV Polymorphisms in Mice ............... 50 2.1 Background ........................................................................................................... 51 2.2 Results and Discussion .......................................................................................... 53 2.2.1 Prevalence of ETn/MusDs and IAPs in different strains .................................... 53 2.2.2 Identification and frequency of polymorphic ERVs ........................................... 54 2.2.3 Genic distribution patterns of the youngest ERVs are distinct from older elements .......................................................................................................................... 57 2.2.4 Confirmation of polymorphic ERVs in gene introns .......................................... 58 2.2.5 Potential gene expression effects mediated by polymorphic ERVs ................... 63 2.3 Concluding Remarks ............................................................................................ 71 2.4 Materials and Methods ......................................................................................... 72 2.4.1 Source data .......................................................................................................... 72 2.4.2 Design of ERV probes and detection of ERVs in the assembled B6 genome .... 73 vi 2.4.3 Detection of ERV insertions in test strains ......................................................... 74 2.4.4 Determining the polymorphism status of ERVs present in B6 or in the test strains .............................................................................................................................75 2.4.5 B6 trace sampling
Recommended publications
  • Genetic Analysis of Retinopathy in Type 1 Diabetes

    Genetic Analysis of Retinopathy in Type 1 Diabetes

    Genetic Analysis of Retinopathy in Type 1 Diabetes by Sayed Mohsen Hosseini A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Institute of Medical Science University of Toronto © Copyright by S. Mohsen Hosseini 2014 Genetic Analysis of Retinopathy in Type 1 Diabetes Sayed Mohsen Hosseini Doctor of Philosophy Institute of Medical Science University of Toronto 2014 Abstract Diabetic retinopathy (DR) is a leading cause of blindness worldwide. Several lines of evidence suggest a genetic contribution to the risk of DR; however, no genetic variant has shown convincing association with DR in genome-wide association studies (GWAS). To identify common polymorphisms associated with DR, meta-GWAS were performed in three type 1 diabetes cohorts of White subjects: Diabetes Complications and Control Trial (DCCT, n=1304), Wisconsin Epidemiologic Study of Diabetic Retinopathy (WESDR, n=603) and Renin-Angiotensin System Study (RASS, n=239). Severe (SDR) and mild (MDR) retinopathy outcomes were defined based on repeated fundus photographs in each study graded for retinopathy severity on the Early Treatment Diabetic Retinopathy Study (ETDRS) scale. Multivariable models accounted for glycemia (measured by A1C), diabetes duration and other relevant covariates in the association analyses of additive genotypes with SDR and MDR. Fixed-effects meta- analysis was used to combine the results of GWAS performed separately in WESDR, ii RASS and subgroups of DCCT, defined by cohort and treatment group. Top association signals were prioritized for replication, based on previous supporting knowledge from the literature, followed by replication in three independent white T1D studies: Genesis-GeneDiab (n=502), Steno (n=936) and FinnDiane (n=2194).
  • Hearing Aging Is 14.1±0.4% GWAS-Heritable

    Hearing Aging Is 14.1±0.4% GWAS-Heritable

    medRxiv preprint doi: https://doi.org/10.1101/2021.07.05.21260048; this version posted July 7, 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 . Predicting age from hearing test results with machine learning reveals the genetic and environmental factors underlying accelerated auditory aging Alan Le Goallec1,2+, Samuel Diai1+, 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-first authors *Corresponding author Contact information: Chirag J Patel [email protected] Abstract With the aging of the world population, age-related hearing loss (presbycusis) and other hearing disorders such as tinnitus become more prevalent, leading to reduced quality of life and social isolation. Unveiling the genetic and environmental factors leading to age-related auditory disorders could suggest lifestyle and therapeutic interventions to slow auditory aging. In the following, we built the first machine learning-based hearing age predictor by training models to predict chronological age from hearing test results (root mean squared error=7.10±0.07 years; R-Squared=31.4±0.8%). We defined hearing age as the prediction outputted by the model on unseen samples, and accelerated auditory aging as the difference between a participant’s hearing age and age. We then performed a genome wide association study [GWAS] and found that accelerated hearing aging is 14.1±0.4% GWAS-heritable.
  • Lineage-Specific Evolution of the Vertebrate Otopetrin Gene Family Revealed by Comparative Genomic Analyses

    Lineage-Specific Evolution of the Vertebrate Otopetrin Gene Family Revealed by Comparative Genomic Analyses

    Hurle et al. BMC Evolutionary Biology 2011, 11:23 http://www.biomedcentral.com/1471-2148/11/23 RESEARCHARTICLE Open Access Lineage-specific evolution of the vertebrate Otopetrin gene family revealed by comparative genomic analyses Belen Hurle1, Tomas Marques-Bonet2,3, Francesca Antonacci3, Inna Hughes4, Joseph F Ryan1, NISC Comparative Sequencing Program1,5, Evan E Eichler3, David M Ornitz6, Eric D Green1,5* Abstract Background: Mutations in the Otopetrin 1 gene (Otop1) in mice and fish produce an unusual bilateral vestibular pathology that involves the absence of otoconia without hearing impairment. The encoded protein, Otop1, is the only functionally characterized member of the Otopetrin Domain Protein (ODP) family; the extended sequence and structural preservation of ODP proteins in metazoans suggest a conserved functional role. Here, we use the tools of sequence- and cytogenetic-based comparative genomics to study the Otop1 and the Otop2-Otop3 genes and to establish their genomic context in 25 vertebrates. We extend our evolutionary study to include the gene mutated in Usher syndrome (USH) subtype 1G (Ush1g), both because of the head-to-tail clustering of Ush1g with Otop2 and because Otop1 and Ush1g mutations result in inner ear phenotypes. Results: We established that OTOP1 is the boundary gene of an inversion polymorphism on human chromosome 4p16 that originated in the common human-chimpanzee lineage more than 6 million years ago. Other lineage- specific evolutionary events included a three-fold expansion of the Otop genes in Xenopus tropicalis and of Ush1g in teleostei fish. The tight physical linkage between Otop2 and Ush1g is conserved in all vertebrates.
  • Ccdc80 and Ccdc80-L1: Identification and Functional Analysis of Two Novel Genes Involved in Zebrafish (Danio Rerio) Development

    Ccdc80 and Ccdc80-L1: Identification and Functional Analysis of Two Novel Genes Involved in Zebrafish (Danio Rerio) Development

    UNIVERSITÀ DEGLI STUDI DI MILANO SCUOLA DI DOTTORATO IN SCIENZE BIOLOGICHE E MOLECOLARI DIPARTIMENTO DI BIOLOGIA DOTTORATO DI RICERCA IN BIOLOGIA CELLULARE E MOLECOLARE XXIV CICLO ccdc80 and ccdc80-l1: Identification and Functional Analysis of Two Novel Genes Involved in Zebrafish (Danio rerio) Development settori scientifico/disciplinari: BIO/06; BIO/11 Tesi di dottorato di Chiara Brusegan R08215 TUTOR: prof. Franco Cotelli COORDINATORE DEL DOTTORATO: prof. Martino Bolognesi A.A. 2010/2011 Index Part I 1. Abstract 1 2. State of the art 2 2.1 Motility of the zebrafish embryo 2 2.2 Muscle formation 3 2.3 Neural differentiation 6 2.4 Identification of zebrafish ccdc80 genes 9 3. Aim of the project 13 4. Materials and Methods 14 4.1 Zebrafish lines and maintenance 14 4.2 Sequence analysis 14 4.3 RT-PCR 15 4.4 Synthesis of probes for whole mount in situ hybridization (WISH) 16 4.5 Whole-mount in situ hybridization 17 4.6 Immunohistochemistry 17 4.7 Histological sections 18 4.8 Injections 18 4.9 Cyclopamine treatment 19 4.10 Statistical analysis 19 5. Results 20 5.1 Identification of ccdc80 homologs in the genome of zebrafish 20 5.2.1 ccdc80 expression profiling 22 5.2.2 ccdc80-loss- and gain-of-function affects somitogenesis in vivo 23 5.2.3 ccdc80 is involved in somitogenesis, but not in the development of the notochord 25 5.2.4 ccdc80 is positively regulated by the Hedgehog pathway 26 5.3.1 ccdc80-l1 expression profiling 27 5.3.2 ccdc80-l1 knocked-down embryos displayed impaired motility 29 5.3.3 ccdc80-l1 loss of function does not affect somitogenesis nor muscle pioneers and adaxial cells formation 30 5.3.4 analysis of neurogenesis of primary motoneurons in ccdc80-l1 morphants 32 5.3.5 Also ccdc80-l1 expression is positively regulated by the Hedgehog pathway 35 5.4.1 ccdc80 expression is not regulated by ccdc80-l1, nor vice versa 37 6.
  • Whole-Genome Microarray Detects Deletions and Loss of Heterozygosity of Chromosome 3 Occurring Exclusively in Metastasizing Uveal Melanoma

    Whole-Genome Microarray Detects Deletions and Loss of Heterozygosity of Chromosome 3 Occurring Exclusively in Metastasizing Uveal Melanoma

    Anatomy and Pathology Whole-Genome Microarray Detects Deletions and Loss of Heterozygosity of Chromosome 3 Occurring Exclusively in Metastasizing Uveal Melanoma Sarah L. Lake,1 Sarah E. Coupland,1 Azzam F. G. Taktak,2 and Bertil E. Damato3 PURPOSE. To detect deletions and loss of heterozygosity of disease is fatal in 92% of patients within 2 years of diagnosis. chromosome 3 in a rare subset of fatal, disomy 3 uveal mela- Clinical and histopathologic risk factors for UM metastasis noma (UM), undetectable by fluorescence in situ hybridization include large basal tumor diameter (LBD), ciliary body involve- (FISH). ment, epithelioid cytomorphology, extracellular matrix peri- ϩ ETHODS odic acid-Schiff-positive (PAS ) loops, and high mitotic M . Multiplex ligation-dependent probe amplification 3,4 5 (MLPA) with the P027 UM assay was performed on formalin- count. Prescher et al. showed that a nonrandom genetic fixed, paraffin-embedded (FFPE) whole tumor sections from 19 change, monosomy 3, correlates strongly with metastatic death, and the correlation has since been confirmed by several disomy 3 metastasizing UMs. Whole-genome microarray analy- 3,6–10 ses using a single-nucleotide polymorphism microarray (aSNP) groups. Consequently, fluorescence in situ hybridization were performed on frozen tissue samples from four fatal dis- (FISH) detection of chromosome 3 using a centromeric probe omy 3 metastasizing UMs and three disomy 3 tumors with Ͼ5 became routine practice for UM prognostication; however, 5% years’ metastasis-free survival. to 20% of disomy 3 UM patients unexpectedly develop metas- tases.11 Attempts have therefore been made to identify the RESULTS. Two metastasizing UMs that had been classified as minimal region(s) of deletion on chromosome 3.12–15 Despite disomy 3 by FISH analysis of a small tumor sample were found these studies, little progress has been made in defining the key on MLPA analysis to show monosomy 3.
  • Dual Proteome-Scale Networks Reveal Cell-Specific Remodeling of the Human Interactome

    Dual Proteome-Scale Networks Reveal Cell-Specific Remodeling of the Human Interactome

    bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Dual Proteome-scale Networks Reveal Cell-specific Remodeling of the Human Interactome Edward L. Huttlin1*, Raphael J. Bruckner1,3, Jose Navarrete-Perea1, Joe R. Cannon1,4, Kurt Baltier1,5, Fana Gebreab1, Melanie P. Gygi1, Alexandra Thornock1, Gabriela Zarraga1,6, Stanley Tam1,7, John Szpyt1, Alexandra Panov1, Hannah Parzen1,8, Sipei Fu1, Arvene Golbazi1, Eila Maenpaa1, Keegan Stricker1, Sanjukta Guha Thakurta1, Ramin Rad1, Joshua Pan2, David P. Nusinow1, Joao A. Paulo1, Devin K. Schweppe1, Laura Pontano Vaites1, J. Wade Harper1*, Steven P. Gygi1*# 1Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA. 2Broad Institute, Cambridge, MA, 02142, USA. 3Present address: ICCB-Longwood Screening Facility, Harvard Medical School, Boston, MA, 02115, USA. 4Present address: Merck, West Point, PA, 19486, USA. 5Present address: IQ Proteomics, Cambridge, MA, 02139, USA. 6Present address: Vor Biopharma, Cambridge, MA, 02142, USA. 7Present address: Rubius Therapeutics, Cambridge, MA, 02139, USA. 8Present address: RPS North America, South Kingstown, RI, 02879, USA. *Correspondence: [email protected] (E.L.H.), [email protected] (J.W.H.), [email protected] (S.P.G.) #Lead Contact: [email protected] bioRxiv preprint doi: https://doi.org/10.1101/2020.01.19.905109; this version posted January 19, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder.
  • Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2

    Supplementary Table 3 Complete List of RNA-Sequencing Analysis of Gene Expression Changed by ≥ Tenfold Between Xenograft and Cells Cultured in 10%O2

    Supplementary Table 3 Complete list of RNA-Sequencing analysis of gene expression changed by ≥ tenfold between xenograft and cells cultured in 10%O2 Expr Log2 Ratio Symbol Entrez Gene Name (culture/xenograft) -7.182 PGM5 phosphoglucomutase 5 -6.883 GPBAR1 G protein-coupled bile acid receptor 1 -6.683 CPVL carboxypeptidase, vitellogenic like -6.398 MTMR9LP myotubularin related protein 9-like, pseudogene -6.131 SCN7A sodium voltage-gated channel alpha subunit 7 -6.115 POPDC2 popeye domain containing 2 -6.014 LGI1 leucine rich glioma inactivated 1 -5.86 SCN1A sodium voltage-gated channel alpha subunit 1 -5.713 C6 complement C6 -5.365 ANGPTL1 angiopoietin like 1 -5.327 TNN tenascin N -5.228 DHRS2 dehydrogenase/reductase 2 leucine rich repeat and fibronectin type III domain -5.115 LRFN2 containing 2 -5.076 FOXO6 forkhead box O6 -5.035 ETNPPL ethanolamine-phosphate phospho-lyase -4.993 MYO15A myosin XVA -4.972 IGF1 insulin like growth factor 1 -4.956 DLG2 discs large MAGUK scaffold protein 2 -4.86 SCML4 sex comb on midleg like 4 (Drosophila) Src homology 2 domain containing transforming -4.816 SHD protein D -4.764 PLP1 proteolipid protein 1 -4.764 TSPAN32 tetraspanin 32 -4.713 N4BP3 NEDD4 binding protein 3 -4.705 MYOC myocilin -4.646 CLEC3B C-type lectin domain family 3 member B -4.646 C7 complement C7 -4.62 TGM2 transglutaminase 2 -4.562 COL9A1 collagen type IX alpha 1 chain -4.55 SOSTDC1 sclerostin domain containing 1 -4.55 OGN osteoglycin -4.505 DAPL1 death associated protein like 1 -4.491 C10orf105 chromosome 10 open reading frame 105 -4.491
  • C3orf70 Is Involved in Neural and Neurobehavioral Development

    C3orf70 Is Involved in Neural and Neurobehavioral Development

    pharmaceuticals Article C3orf70 Is Involved in Neural and Neurobehavioral Development Yoshifumi Ashikawa 1, Takashi Shiromizu 1, Koki Miura 1, Yuka Adachi 1, Takaaki Matsui 2, Yasumasa Bessho 2, Toshio Tanaka 3 and Yuhei Nishimura 1,* 1 Department of Integrative Pharmacology, Mie University Graduate School of Medicine, Tsu, Mie 514-8507, Japan; [email protected] (Y.A.); [email protected] (T.S.); [email protected] (K.M.); [email protected] (Y.A.) 2 Gene Regulation Research, Graduate School of Biological Sciences, Nara Institute of Science and Technology, Takayama, Nara 630-0192, Japan; [email protected] (T.M.); [email protected] (Y.B.) 3 Department of Systems Pharmacology, Mie University Graduate School of Medicine, Tsu, Mie 514-8507, Japan; [email protected] * Correspondence: [email protected] Received: 10 October 2019; Accepted: 15 October 2019; Published: 16 October 2019 Abstract: Neurogenesis is the process by which undifferentiated progenitor cells develop into mature and functional neurons. Defects in neurogenesis are associated with neurodevelopmental and neuropsychiatric disorders; therefore, elucidating the molecular mechanisms underlying neurogenesis can advance our understanding of the pathophysiology of these disorders and facilitate the discovery of novel therapeutic targets. In this study, we performed a comparative transcriptomic analysis to identify common targets of the proneural transcription factors Neurog1/2 and Ascl1 during neurogenesis of human and mouse stem cells. We successfully identified C3orf70 as a novel common target gene of Neurog1/2 and Ascl1 during neurogenesis. Using in situ hybridization, we demonstrated that c3orf70a and c3orf70b, two orthologs of C3orf70, were expressed in the midbrain and hindbrain of zebrafish larvae.
  • A Single-Cell Transcriptomic Landscape of Primate Arterial Aging

    A Single-Cell Transcriptomic Landscape of Primate Arterial Aging

    ARTICLE https://doi.org/10.1038/s41467-020-15997-0 OPEN A single-cell transcriptomic landscape of primate arterial aging Weiqi Zhang 1,2,3,4,5,13, Shu Zhang6,7,13, Pengze Yan3,8,13, Jie Ren7,9,13, Moshi Song3,5,8, Jingyi Li2,3,8, Jinghui Lei4, Huize Pan2,3, Si Wang3,5,8, Xibo Ma3,10, Shuai Ma2,3,8, Hongyu Li2,3, Fei Sun2,3, Haifeng Wan3,5,11, ✉ ✉ ✉ Wei Li 3,5,11, Piu Chan4, Qi Zhou3,5,11, Guang-Hui Liu 2,3,4,5,8 , Fuchou Tang 6,7,9,12 & Jing Qu 3,5,11 Our understanding of how aging affects the cellular and molecular components of the vas- 1234567890():,; culature and contributes to cardiovascular diseases is still limited. Here we report a single-cell transcriptomic survey of aortas and coronary arteries in young and old cynomolgus monkeys. Our data define the molecular signatures of specialized arteries and identify eight markers discriminating aortic and coronary vasculatures. Gene network analyses characterize tran- scriptional landmarks that regulate vascular senility and position FOXO3A, a longevity- associated transcription factor, as a master regulator gene that is downregulated in six subtypes of monkey vascular cells during aging. Targeted inactivation of FOXO3A in human vascular endothelial cells recapitulates the major phenotypic defects observed in aged monkey arteries, verifying FOXO3A loss as a key driver for arterial endothelial aging. Our study provides a critical resource for understanding the principles underlying primate arterial aging and contributes important clues to future treatment of age-associated vascular disorders. 1 CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.
  • 1 Supporting Information for a Microrna Network Regulates

    1 Supporting Information for a Microrna Network Regulates

    Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia.
  • High-Density Single Nucleotide Polymorphism Array Defines Novel Stage and Location-Dependent Allelic Imbalances in Human Bladder Tumors

    High-Density Single Nucleotide Polymorphism Array Defines Novel Stage and Location-Dependent Allelic Imbalances in Human Bladder Tumors

    ResearchResearch Article Article High-Density Single Nucleotide Polymorphism Array Defines Novel Stage and Location-Dependent Allelic Imbalances in Human Bladder Tumors Karen Koed,1,3 Carsten Wiuf,4 Lise-Lotte Christensen,1 Friedrik P. Wikman,1 Karsten Zieger,1,2 Klaus Møller,2 Hans von der Maase,3 and Torben F. Ørntoft1 Molecular Diagnostic Laboratory, 1Departments of Clinical Biochemistry, 2Urology, and 3Oncology, Aarhus University Hospital; and 4Bioinformatics Research Center, Aarhus University, Aarhus, Denmark Abstract In the case of noninvasive Ta transitional cell carcinomas, this Bladder cancer is a common disease characterized by multiple includes loss of chromosome 9, or parts of it, as well as 1q+ and loss recurrences and an invasive disease course in more than 10% of the Y chromosome in males (2, 5). In invasive tumors, many of patients. It is of monoclonal or oligoclonal origin and alterations have been reported to be more or less common: 1pÀ, genomic instability has been shown at certain loci. We used a 2qÀ,4qÀ,5qÀ,8pÀ, À9, 10qÀ, 11pÀ,11qÀ, 1q+, 2p+, 5p+, 8q+, 10,000 single nucleotide polymorphism (SNP) array with an 11q13+, 17q+, and 20q+ (2, 6–8). It has been suggested that these lost average of 2,700 heterozygous SNPs to detect allelic imbalances or gained regions harbor tumor suppressor genes and oncogenes, (AI) in 37 microdissected bladder tumors from 17 patients. respectively. However, the large chromosomal areas involved often Eight tumors represented upstaging from Ta to T1, eight from contain many genes, making meaningful predictions of the T1 to T2+, and one from Ta to T2+.
  • Relevance Network Between Chemosensitivity and Transcriptome in Human Hepatoma Cells1

    Relevance Network Between Chemosensitivity and Transcriptome in Human Hepatoma Cells1

    Vol. 2, 199–205, February 2003 Molecular Cancer Therapeutics 199 Relevance Network between Chemosensitivity and Transcriptome in Human Hepatoma Cells1 Masaru Moriyama,2 Yujin Hoshida, topoisomerase II ␤ expression, whereas it negatively Motoyuki Otsuka, ShinIchiro Nishimura, Naoya Kato, correlated with expression of carboxypeptidases A3 Tadashi Goto, Hiroyoshi Taniguchi, and Z. Response to nimustine was associated with Yasushi Shiratori, Naohiko Seki, and Masao Omata expression of superoxide dismutase 2. Department of Gastroenterology, Graduate School of Medicine, Relevance networks identified several negative University of Tokyo, Tokyo 113-8655 [M. M., Y. H., M. O., N. K., T. G., H. T., Y. S., M. O.]; Cellular Informatics Team, Computational Biology correlations between gene expression and resistance, Research Center, Tokyo 135-0064 [S. N.]; and Department of which were missed by hierarchical clustering. Our Functional Genomics, Graduate School of Medicine, Chiba University, results suggested the necessity of systematically Chiba 260-8670 [N. S.], Japan evaluating the transporting systems that may play a major role in resistance in hepatoma. This may provide Abstract useful information to modify anticancer drug action in Generally, hepatoma is not a chemosensitive tumor, hepatoma. and the mechanism of resistance to anticancer drugs is not fully elucidated. We aimed to comprehensively Introduction evaluate the relationship between chemosensitivity and Hepatoma is a major cause of death even in developed gene expression profile in human hepatoma cells, by countries, and its incidence is increasing (1). Despite the using microarray analysis, and analyze the data by progress of therapeutic technique (2), the efficacy of radical constructing relevance networks. therapy is hampered by frequent recurrence and advance of In eight hepatoma cell lines (HLE, HLF, Huh7, Hep3B, the tumor (3).