Psychomotor Retardation with a 1Q42.11–Q42.12 Deletion
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Proteomics Provides Insights Into the Inhibition of Chinese Hamster V79
www.nature.com/scientificreports OPEN Proteomics provides insights into the inhibition of Chinese hamster V79 cell proliferation in the deep underground environment Jifeng Liu1,2, Tengfei Ma1,2, Mingzhong Gao3, Yilin Liu4, Jun Liu1, Shichao Wang2, Yike Xie2, Ling Wang2, Juan Cheng2, Shixi Liu1*, Jian Zou1,2*, Jiang Wu2, Weimin Li2 & Heping Xie2,3,5 As resources in the shallow depths of the earth exhausted, people will spend extended periods of time in the deep underground space. However, little is known about the deep underground environment afecting the health of organisms. Hence, we established both deep underground laboratory (DUGL) and above ground laboratory (AGL) to investigate the efect of environmental factors on organisms. Six environmental parameters were monitored in the DUGL and AGL. Growth curves were recorded and tandem mass tag (TMT) proteomics analysis were performed to explore the proliferative ability and diferentially abundant proteins (DAPs) in V79 cells (a cell line widely used in biological study in DUGLs) cultured in the DUGL and AGL. Parallel Reaction Monitoring was conducted to verify the TMT results. γ ray dose rate showed the most detectable diference between the two laboratories, whereby γ ray dose rate was signifcantly lower in the DUGL compared to the AGL. V79 cell proliferation was slower in the DUGL. Quantitative proteomics detected 980 DAPs (absolute fold change ≥ 1.2, p < 0.05) between V79 cells cultured in the DUGL and AGL. Of these, 576 proteins were up-regulated and 404 proteins were down-regulated in V79 cells cultured in the DUGL. KEGG pathway analysis revealed that seven pathways (e.g. -
Chromosome Abnormalities in Two Patients with Features of Autosomal Dominant Robinow Syndrome
ß 2007 Wiley-Liss, Inc. American Journal of Medical Genetics Part A 143A:1790–1795 (2007) Research Letter Chromosome Abnormalities in Two Patients With Features of Autosomal Dominant Robinow Syndrome Juliana F. Mazzeu,1 Ana Cristina Krepischi-Santos,1 Carla Rosenberg,1 Karoly Szuhai,2 Jeroen Knijnenburg,2 Janneke M.M. Weiss,3 Irina Kerkis,1 Zan Mustacchi,4 Guilherme Colin,5 Roˆmulo Mombach,6 Rita de Ca´ssia M. Pavanello,1 Paulo A. Otto,1 and Angela M. Vianna-Morgante1* 1Centro de Estudos do Genoma Humano, Departamento de Gene´tica e Biologia Evolutiva, Instituto de Biocieˆncias, Universidade de Sa˜o Paulo, Sa˜o Paulo, Brazil 2Department of Molecular Cell Biology, Leiden University Medical Center, Leiden, The Netherlands 3Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands 4Hospital Infantil Darcy Vargas, Sa˜o Paulo, Brazil 5Departamento de Gene´tica Me´dica, Univille, Joinville, Brazil 6Centrinho Prefeito Luiz Gomes, Secretaria Municipal de Sau´de, Joinville, Brazil Received 13 April 2006; Accepted 13 December 2006 How to cite this article: Mazzeu JF, Krepischi-Santos AC, Rosenberg C, Szuhai K, Knijnenburg J, Weiss JMM, Kerkis I, Mustacchi Z, Colin G, Mombach R, Pavanello RM, Otto PA, Vianna-Morgante AM. 2007. Chromosome abnormalities in two patients with features of autosomal dominant Robinow syndrome. Am J Med Genet Part A 143A:1790–1795. To the Editor: Patient 1 Robinow syndrome [OMIM 180700] is characteriz- At age 3 4/12 years the girl was diagnosed as ed by fetal facies, mesomelic dwarfism, and hypo- affected by DRS (Fig. 1A). Detailed clinical examina- plastic genitalia. -
Revostmm Vol 10-4-2018 Ingles Maquetaciûn 1
108 ORIGINALS / Rev Osteoporos Metab Miner. 2018;10(4):108-18 Roca-Ayats N1, Falcó-Mascaró M1, García-Giralt N2, Cozar M1, Abril JF3, Quesada-Gómez JM4, Prieto-Alhambra D5,6, Nogués X2, Mellibovsky L2, Díez-Pérez A2, Grinberg D1, Balcells S1 1 Departamento de Genética, Microbiología y Estadística - Facultad de Biología - Universidad de Barcelona - Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER) - Instituto de Salud Carlos III (ISCIII) - Instituto de Biomedicina de la Universidad de Barcelona (IBUB) - Instituto de Investigación Sant Joan de Déu (IRSJD) - Barcelona (España) 2 Unidad de Investigación en Fisiopatología Ósea y Articular (URFOA); Instituto Hospital del Mar de Investigaciones Médicas (IMIM) - Parque de Salud Mar - Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES); Instituto de Salud Carlos III (ISCIII) - Barcelona (España) 3 Departamento de Genética, Microbiología y Estadística; Facultad de Biología; Universidad de Barcelona - Instituto de Biomedicina de la Universidad de Barcelona (IBUB) - Barcelona (España) 4 Unidad de Metabolismo Mineral; Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC); Hospital Universitario Reina Sofía - Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES); Instituto de Salud Carlos III (ISCIII) - Córdoba (España) 5 Grupo de Investigación en Enfermedades Prevalentes del Aparato Locomotor (GREMPAL) - Instituto de Investigación en Atención Primaria (IDIAP) Jordi Gol - Centro de Investigación -
35Th International Society for Animal Genetics Conference 7
35th INTERNATIONAL SOCIETY FOR ANIMAL GENETICS CONFERENCE 7. 23.16 – 7.27. 2016 Salt Lake City, Utah ABSTRACT BOOK https://www.asas.org/meetings/isag2016 INVITED SPEAKERS S0100 – S0124 https://www.asas.org/meetings/isag2016 epigenetic modifications, such as DNA methylation, and measuring different proteins and cellular metab- INVITED SPEAKERS: FUNCTIONAL olites. These advancements provide unprecedented ANNOTATION OF ANIMAL opportunities to uncover the genetic architecture GENOMES (FAANG) ASAS-ISAG underlying phenotypic variation. In this context, the JOINT SYMPOSIUM main challenge is to decipher the flow of biological information that lies between the genotypes and phe- notypes under study. In other words, the new challenge S0100 Important lessons from complex genomes. is to integrate multiple sources of molecular infor- T. R. Gingeras* (Cold Spring Harbor Laboratory, mation (i.e., multiple layers of omics data to reveal Functional Genomics, Cold Spring Harbor, NY) the causal biological networks that underlie complex traits). It is important to note that knowledge regarding The ~3 billion base pairs of the human DNA rep- causal relationships among genes and phenotypes can resent a storage devise encoding information for be used to predict the behavior of complex systems, as hundreds of thousands of processes that can go on well as optimize management practices and selection within and outside a human cell. This information is strategies. Here, we describe a multi-step procedure revealed in the RNAs that are composed of 12 billion for inferring causal gene-phenotype networks underly- nucleotides, considering the strandedness and allelic ing complex phenotypes integrating multi-omics data. content of each of the diploid copies of the genome. -
Oracle Health Sciences Omics Data Bank Programmer’S Guide Release 3.0.2.1 E35680-12
Oracle® Health Sciences Omics Data Bank Programmer’s Guide Release 3.0.2.1 E35680-12 March 2016 Oracle Health Sciences Omics Data Bank Programmer’s Guide Release 3.0.2.1 E35680-12 Copyright © 2013, 2016, Oracle and/or its affiliates. All rights reserved. This software and related documentation are provided under a license agreement containing restrictions on use and disclosure and are protected by intellectual property laws. Except as expressly permitted in your license agreement or allowed by law, you may not use, copy, reproduce, translate, broadcast, modify, license, transmit, distribute, exhibit, perform, publish, or display any part, in any form, or by any means. Reverse engineering, disassembly, or decompilation of this software, unless required by law for interoperability, is prohibited. The information contained herein is subject to change without notice and is not warranted to be error-free. If you find any errors, please report them to us in writing. If this is software or related documentation that is delivered to the U.S. Government or anyone licensing it on behalf of the U.S. Government, the following notice is applicable: U.S. GOVERNMENT END USERS: Oracle programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, delivered to U.S. Government end users are "commercial computer software" pursuant to the applicable Federal Acquisition Regulation and agency-specific supplemental regulations. As such, use, duplication, disclosure, modification, and adaptation of the programs, including any operating system, integrated software, any programs installed on the hardware, and/or documentation, shall be subject to license terms and license restrictions applicable to the programs. -
WO 2016/040794 Al 17 March 2016 (17.03.2016) P O P C T
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2016/040794 Al 17 March 2016 (17.03.2016) P O P C T (51) International Patent Classification: AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, C12N 1/19 (2006.01) C12Q 1/02 (2006.01) BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, C12N 15/81 (2006.01) C07K 14/47 (2006.01) DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JP, KE, KG, KN, KP, KR, (21) International Application Number: KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, PCT/US20 15/049674 MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, (22) International Filing Date: PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, 11 September 2015 ( 11.09.201 5) SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every (26) Publication Language: English kind of regional protection available): ARIPO (BW, GH, (30) Priority Data: GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, 62/050,045 12 September 2014 (12.09.2014) US TZ, UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, (71) Applicant: WHITEHEAD INSTITUTE FOR BIOMED¬ DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, ICAL RESEARCH [US/US]; Nine Cambridge Center, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, Cambridge, Massachusetts 02142-1479 (US). -
Integrated Analysis of DNA Methylation and Transcriptome Profiling of Polycystic Ovary Syndrome
2138 MOLECULAR MEDICINE REPORTS 21: 2138-2150, 2020 Integrated analysis of DNA methylation and transcriptome profiling of polycystic ovary syndrome LI LIU1, DONGYUN HE1, YANG WANG2 and MINJIA SHENG1 1Reproductive Medical Center, Department of Gynecology and Obstetrics, China‑Japan Union Hospital of Jilin University; 2Department of Dermatology, The Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, Jilin 130031, P.R. China Received December 17, 2018; Accepted July 30, 2019 DOI: 10.3892/mmr.2020.11005 Abstract. The present study aimed to identify potentially impor- Introduction tant biomarkers associated with polycystic ovary syndrome (PCOS) by integrating DNA methylation with transcriptome Polycystic ovary syndrome (PCOS) is a common reproduc- profiling. The transcription (E‑MTAB‑3768) and methylation tive disorder, affecting 5-20% of the reproductive-age female (E‑MTAB‑3777) datasets were retrieved from ArrayExpress. population worldwide (1,2). In addition, PCOS is associated Paired transcription and methylation profiling data of 10 cases with ovulatory dysfunction, abdominal adiposity, insulin of PCOS and 10 healthy controls were available for screening resistance, obesity, excessive androgen production and cardio- differentially expressed genes (DEGs) and differentially vascular risk factors (3). However, the genetic mechanisms methylated genes (DMGs). Genes with a negative correlation of PCOS remain largely unknown, since the etiology of the between expression levels and methylation levels were retained disease is very complex and affected both by genomic and by correlation analysis to construct a protein-protein interaction environmental factors. Therefore, an improved understanding (PPI) network. Subsequently, functional and pathway enrich- of the genetic mechanisms of PCOS may provide novel insights ment analyses were performed to identify genes in the PPI into the treatment and diagnosis of PCOS (4). -
Link Between Short Tandem Repeats and Translation Initiation Site Selection Masoud Arabfard1,2, Kaveh Kavousi2*, Ahmad Delbari3 and Mina Ohadi3*
Arabfard et al. Human Genomics (2018) 12:47 https://doi.org/10.1186/s40246-018-0181-3 PRIMARY RESEARCH Open Access Link between short tandem repeats and translation initiation site selection Masoud Arabfard1,2, Kaveh Kavousi2*, Ahmad Delbari3 and Mina Ohadi3* Abstract Background: Despite their vast biological implication, the relevance of short tandem repeats (STRs)/microsatellites to the protein-coding gene translation initiation sites (TISs) remains largely unknown. Methods: We performed an Ensembl-based comparative genomics study of all annotated orthologous TIS-flanking sequences in human and 46 other species across vertebrates, on the genomic DNA and cDNA platforms (755,956 TISs), aimed at identifying human-specific STRs in this interval. The collected data were used to examine the hypothesis of a link between STRs and TISs. BLAST was used to compare the initial five amino acids (excluding the initial methionine), codons of which were flanked by STRs in human, with the initial five amino acids of all annotated proteins for the orthologous genes in other vertebrates (total of 5,314,979 pair-wise TIS comparisons on the genomic DNA and cDNA platforms) in order to compare the number of events in which human-specific and non-specific STRs occurred with homologous and non-homologous TISs (i.e., ≥ 50% and < 50% similarity of the five amino acids). Results: We detected differential distribution of the human-specific STRs in comparison to the overall distribution of STRs on the genomic DNA and cDNA platforms (Mann Whitney U test p =1.4×10−11 and p <7.9×10−11, respectively). We also found excess occurrence of non-homologous TISs with human-specific STRs and excess occurrence of homologous TISs with non-specific STRs on both platforms (p < 0.00001). -
Agricultural University of Athens
ΓΕΩΠΟΝΙΚΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΑΘΗΝΩΝ ΣΧΟΛΗ ΕΠΙΣΤΗΜΩΝ ΤΩΝ ΖΩΩΝ ΤΜΗΜΑ ΕΠΙΣΤΗΜΗΣ ΖΩΙΚΗΣ ΠΑΡΑΓΩΓΗΣ ΕΡΓΑΣΤΗΡΙΟ ΓΕΝΙΚΗΣ ΚΑΙ ΕΙΔΙΚΗΣ ΖΩΟΤΕΧΝΙΑΣ ΔΙΔΑΚΤΟΡΙΚΗ ΔΙΑΤΡΙΒΗ Εντοπισμός γονιδιωματικών περιοχών και δικτύων γονιδίων που επηρεάζουν παραγωγικές και αναπαραγωγικές ιδιότητες σε πληθυσμούς κρεοπαραγωγικών ορνιθίων ΕΙΡΗΝΗ Κ. ΤΑΡΣΑΝΗ ΕΠΙΒΛΕΠΩΝ ΚΑΘΗΓΗΤΗΣ: ΑΝΤΩΝΙΟΣ ΚΟΜΙΝΑΚΗΣ ΑΘΗΝΑ 2020 ΔΙΔΑΚΤΟΡΙΚΗ ΔΙΑΤΡΙΒΗ Εντοπισμός γονιδιωματικών περιοχών και δικτύων γονιδίων που επηρεάζουν παραγωγικές και αναπαραγωγικές ιδιότητες σε πληθυσμούς κρεοπαραγωγικών ορνιθίων Genome-wide association analysis and gene network analysis for (re)production traits in commercial broilers ΕΙΡΗΝΗ Κ. ΤΑΡΣΑΝΗ ΕΠΙΒΛΕΠΩΝ ΚΑΘΗΓΗΤΗΣ: ΑΝΤΩΝΙΟΣ ΚΟΜΙΝΑΚΗΣ Τριμελής Επιτροπή: Aντώνιος Κομινάκης (Αν. Καθ. ΓΠΑ) Ανδρέας Κράνης (Eρευν. B, Παν. Εδιμβούργου) Αριάδνη Χάγερ (Επ. Καθ. ΓΠΑ) Επταμελής εξεταστική επιτροπή: Aντώνιος Κομινάκης (Αν. Καθ. ΓΠΑ) Ανδρέας Κράνης (Eρευν. B, Παν. Εδιμβούργου) Αριάδνη Χάγερ (Επ. Καθ. ΓΠΑ) Πηνελόπη Μπεμπέλη (Καθ. ΓΠΑ) Δημήτριος Βλαχάκης (Επ. Καθ. ΓΠΑ) Ευάγγελος Ζωίδης (Επ.Καθ. ΓΠΑ) Γεώργιος Θεοδώρου (Επ.Καθ. ΓΠΑ) 2 Εντοπισμός γονιδιωματικών περιοχών και δικτύων γονιδίων που επηρεάζουν παραγωγικές και αναπαραγωγικές ιδιότητες σε πληθυσμούς κρεοπαραγωγικών ορνιθίων Περίληψη Σκοπός της παρούσας διδακτορικής διατριβής ήταν ο εντοπισμός γενετικών δεικτών και υποψηφίων γονιδίων που εμπλέκονται στο γενετικό έλεγχο δύο τυπικών πολυγονιδιακών ιδιοτήτων σε κρεοπαραγωγικά ορνίθια. Μία ιδιότητα σχετίζεται με την ανάπτυξη (σωματικό βάρος στις 35 ημέρες, ΣΒ) και η άλλη με την αναπαραγωγική -
Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ...................................................... -
Multiethnic Genome-Wide Association Study of Diabetic Retinopathy Using Liability Threshold Modeling of Duration of Diabetes and Glycemic Control
Diabetes Volume 68, February 2019 441 Multiethnic Genome-Wide Association Study of Diabetic Retinopathy Using Liability Threshold Modeling of Duration of Diabetes and Glycemic Control Samuela Pollack,1 Robert P. Igo Jr.,2 Richard A. Jensen,3 Mark Christiansen,3 Xiaohui Li,4 Ching-Yu Cheng,5,6 Maggie C.Y. Ng,7,8 Albert V. Smith,9 Elizabeth J. Rossin,10 Ayellet V. Segrè,10 Samaneh Davoudi,10 Gavin S. Tan,5,6 Yii-Der Ida Chen,4 Jane Z. Kuo,4,11 Latchezar M. Dimitrov,7,8 Lynn K. Stanwyck,10 Weihua Meng,12 S. Mohsen Hosseini,13 Minako Imamura,14,15,16 Darryl Nousome,17 Jihye Kim,18 Yang Hai,4 Yucheng Jia,4 Jeeyun Ahn,19 Aaron Leong,20 Kaanan Shah,21 Kyu Hyung Park,22 Xiuqing Guo,4 Eli Ipp,23 Kent D. Taylor,4 Sharon G. Adler,24 John R. Sedor,25,26,27 Barry I. Freedman,28 Family Investigation of Nephropathy and Diabetes-Eye Research Group, DCCT/EDIC Research Group, I-Te Lee,29,30,31 Wayne H.-H. Sheu,29,30,31,32 Michiaki Kubo,33 Atsushi Takahashi,34,35 Samy Hadjadj,36,37,38,39 Michel Marre,40,41,42 David-Alexandre Tregouet,43,44 Roberta Mckean-Cowdin,17,45 Rohit Varma,17,45 Mark I. McCarthy,46,47,48 Leif Groop,49 Emma Ahlqvist,49 Valeriya Lyssenko,49,50 Elisabet Agardh,49 Andrew Morris,51 Alex S.F. Doney,52 Helen M. Colhoun,53 Iiro Toppila,54,55,56 Niina Sandholm,54,55,56 Per-Henrik Groop,54,55,56,57 Shiro Maeda,14,15,16 Craig L. -
Introduction
ent INTRODUCTION When we consider a protein (or gene), one of the most fundamental questions is what other proteins are related. Biological sequences often occur in families. These fam ilies may consist of related genes within an organism (paralogs), sequences within a population (e.g., polymorphic variants), or genes in other species (ortho logs). Sequences diverge from each other for reasons such as duplication within a genome or speciation leading to the existence of orthologs. We have studied pairwise comparisons of two protein (or DNA) sequences (Chapter 3), and we have also seen multiple related sequences in the form of profiles or as the output of a BLAST or other database search (Chapters 4 and 5). We will also explore multiple sequence alignments in the context of molecular phylogeny (Chapter 7), protein domains (Chap ter 10), and protein structure (Chapter 11). In this chapter, we consider the general problem of multiple sequence alignment from three perspectives. First, we describe five approaches to making multiple sequence alignments from a group of homologous sequences of interest. Second, we discuss multiple alignment of genomic DNA. This is typically a comparative genomics problem of aligning large chromosomal regions from different species. Third, we explore databases ofmultiply aligned sequences, such as Pfam, the protein family database. While multiple sequence alignment is commonly performed for bo th protein and D NA sequences, most databases consist of protein families only. Nucleotides corresponding to coding regions are typically less well conserved than Bioinformatics and Functional Genomics, Second Edition. By [onathan Pevsner Copyright © 2009 John Wiley & Sons, Inc. 179 180 MULTIPLE SEQUEN CE ALIGNMENT proteins because of the degeneracy of the genetic code.