Expression Quantitative Trait Loci (Eqtls) Associated with Retrotransposons Demonstrate Their Modulatory Effect on the Transcriptome
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Detailed Characterization of Human Induced Pluripotent Stem Cells Manufactured for Therapeutic Applications
Stem Cell Rev and Rep DOI 10.1007/s12015-016-9662-8 Detailed Characterization of Human Induced Pluripotent Stem Cells Manufactured for Therapeutic Applications Behnam Ahmadian Baghbaderani 1 & Adhikarla Syama2 & Renuka Sivapatham3 & Ying Pei4 & Odity Mukherjee2 & Thomas Fellner1 & Xianmin Zeng3,4 & Mahendra S. Rao5,6 # The Author(s) 2016. This article is published with open access at Springerlink.com Abstract We have recently described manufacturing of hu- help determine which set of tests will be most useful in mon- man induced pluripotent stem cells (iPSC) master cell banks itoring the cells and establishing criteria for discarding a line. (MCB) generated by a clinically compliant process using cord blood as a starting material (Baghbaderani et al. in Stem Cell Keywords Induced pluripotent stem cells . Embryonic stem Reports, 5(4), 647–659, 2015). In this manuscript, we de- cells . Manufacturing . cGMP . Consent . Markers scribe the detailed characterization of the two iPSC clones generated using this process, including whole genome se- quencing (WGS), microarray, and comparative genomic hy- Introduction bridization (aCGH) single nucleotide polymorphism (SNP) analysis. We compare their profiles with a proposed calibra- Induced pluripotent stem cells (iPSCs) are akin to embryonic tion material and with a reporter subclone and lines made by a stem cells (ESC) [2] in their developmental potential, but dif- similar process from different donors. We believe that iPSCs fer from ESC in the starting cell used and the requirement of a are likely to be used to make multiple clinical products. We set of proteins to induce pluripotency [3]. Although function- further believe that the lines used as input material will be used ally identical, iPSCs may differ from ESC in subtle ways, at different sites and, given their immortal status, will be used including in their epigenetic profile, exposure to the environ- for many years or even decades. -
Gene Expression Analysis of Mevalonate Kinase Deficiency
International Journal of Environmental Research and Public Health Article Gene Expression Analysis of Mevalonate Kinase Deficiency Affected Children Identifies Molecular Signatures Related to Hematopoiesis Simona Pisanti * , Marianna Citro , Mario Abate , Mariella Caputo and Rosanna Martinelli * Department of Medicine, Surgery and Dentistry ‘Scuola Medica Salernitana’, University of Salerno, Via Salvatore Allende, 84081 Baronissi (SA), Italy; [email protected] (M.C.); [email protected] (M.A.); [email protected] (M.C.) * Correspondence: [email protected] (S.P.); [email protected] (R.M.) Abstract: Mevalonate kinase deficiency (MKD) is a rare autoinflammatory genetic disorder charac- terized by recurrent fever attacks and systemic inflammation with potentially severe complications. Although it is recognized that the lack of protein prenylation consequent to mevalonate pathway blockade drives IL1β hypersecretion, and hence autoinflammation, MKD pathogenesis and the molecular mechanisms underlaying most of its clinical manifestations are still largely unknown. In this study, we performed a comprehensive bioinformatic analysis of a microarray dataset of MKD patients, using gene ontology and Ingenuity Pathway Analysis (IPA) tools, in order to identify the most significant differentially expressed genes and infer their predicted relationships into biological processes, pathways, and networks. We found that hematopoiesis linked biological functions and pathways are predominant in the gene ontology of differentially expressed genes in MKD, in line with the observed clinical feature of anemia. We also provided novel information about the molecular Citation: Pisanti, S.; Citro, M.; Abate, M.; Caputo, M.; Martinelli, R. mechanisms at the basis of the hematological abnormalities observed, that are linked to the chronic Gene Expression Analysis of inflammation and to defective prenylation. -
Specific, Gene Expression Signatures in HIV-1 Infection1
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Qingsheng Li Publications Papers in the Biological Sciences 2009 Microarray Analysis of Lymphatic Tissue Reveals Stage- Specific, Gene Expression Signatures in HIV-1 Infection1 Qingsheng Li University of Minnesota, [email protected] Anthony J. Smith University of Minnesota Timothy W. Schacker University of Minnesota John V. Carlis University of Minnesota Lijie Duan University of Minnesota See next page for additional authors Follow this and additional works at: https://digitalcommons.unl.edu/biosciqingshengli Li, Qingsheng; Smith, Anthony J.; Schacker, Timothy W.; Carlis, John V.; Duan, Lijie; Reilly, Cavan S.; and Haase, Ashley T., "Microarray Analysis of Lymphatic Tissue Reveals Stage- Specific, Gene Expression Signatures in HIV-1 Infection1" (2009). Qingsheng Li Publications. 8. https://digitalcommons.unl.edu/biosciqingshengli/8 This Article is brought to you for free and open access by the Papers in the Biological Sciences at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Qingsheng Li Publications by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. Authors Qingsheng Li, Anthony J. Smith, Timothy W. Schacker, John V. Carlis, Lijie Duan, Cavan S. Reilly, and Ashley T. Haase This article is available at DigitalCommons@University of Nebraska - Lincoln: https://digitalcommons.unl.edu/ biosciqingshengli/8 NIH Public Access Author Manuscript J Immunol. Author manuscript; available in PMC 2013 January 23. Published in final edited form as: J Immunol. 2009 August 1; 183(3): 1975–1982. doi:10.4049/jimmunol.0803222. Microarray Analysis of Lymphatic Tissue Reveals Stage- Specific, Gene Expression Signatures in HIV-1 Infection1 $watermark-text $watermark-text $watermark-text Qingsheng Li2,*, Anthony J. -
BMC Genomics Biomed Central
BMC Genomics BioMed Central Research article Open Access Genomic analysis of the chromosome 15q11-q13 Prader-Willi syndrome region and characterization of transcripts for GOLGA8E and WHCD1L1 from the proximal breakpoint region Yong-hui Jiang*1, Kekio Wauki1,3, Qian Liu1, Jan Bressler1, Yanzhen Pan1, Catherine D Kashork1,2, Lisa G Shaffer1,2 and Arthur L Beaudet1 Address: 1Departments of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA, 2Signature Genomics Laboratories, LLC, 120 North Pine Street, Suite 242C, Spokane, WA 99202, USA and 3Shinshu University School of Medicine, Dept of Medical Genetics, 3-1-1 Asahi, Nagano, Matsumoto 390-8621, Japan Email: Yong-hui Jiang* - [email protected]; Kekio Wauki - [email protected]; Qian Liu - [email protected]; Jan Bressler - [email protected]; Yanzhen Pan - [email protected]; Catherine D Kashork - [email protected]; Lisa G Shaffer - [email protected]; Arthur L Beaudet - [email protected] * Corresponding author Published: 28 January 2008 Received: 20 September 2007 Accepted: 28 January 2008 BMC Genomics 2008, 9:50 doi:10.1186/1471-2164-9-50 This article is available from: http://www.biomedcentral.com/1471-2164/9/50 © 2008 Jiang et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract Background: Prader-Willi syndrome (PWS) is a neurobehavioral disorder characterized by neonatal hypotonia, childhood obesity, dysmorphic features, hypogonadism, mental retardation, and behavioral problems. -
For Peer Review 19 20 21 22 23 24 Pamela Doo, B.A
Human Genetics Page 2 of 51 1 2 3 control critera. 4 5 6 The call rate threshold for samples was ≥90%. We have added a statement to this effect in the 7 Methods. 8 9 4. No rationale provided for selection of individuals for sequencing. For example, why were all 10 11 individuals in Family 1 sequenced but only the offspring in family 3? 12 13 We selected the individuals within each family that were likely to be the most informative in 14 sequencing studies. For example, the phenotypes of the parents in family 3 are unknown, 15 sequencing data is unlikely to be of additional benefit, as we would be unable to determine 16 whether variants of interest co-segregate with the phenotype. We have added a section in the 17 18 Methods outlining theseFor choices. Peer Review 19 20 5. “…several [of the coding variants] were associated with the major haplotype of interest in 21 one of the three families”. It would be helpful to know how many variants were associated 22 with the haplotype of interest, without having to go to the Supplemental Table. 23 24 25 We have added this information in the text of the Results section and have highlighted these 26 variants in grey in Supplemental Table 3. 27 28 We hope that these revisions are satisfactory, and submit the revised manuscript for your 29 consideration for publication. 30 31 32 Thank you very much, 33 34 35 36 37 38 39 40 41 42 Carol A. Mathews, MD 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Page 3 of 51 Human Genetics 1 2 3 Genomewide Linkage Analysis in Costa Rican Families Implicates Chromosome 15q14 as a 4 5 6 Candidate Region for OCD 7 8 9 Jessica Ross, M.D. -
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 ...................................................... -
Supplemental Figures
Control #1 Control #2 Control #3 83972 #1 83972 #2 83972 #3 CFT073 #1 CFT073 #2 CFT073 #3 Log-intensity ratios (M-values) ratios Log-intensity Log-intensity averages (A-values) Supplemental Figure 1. MA-plots showing normalized raw data using cross- correlation. The data was found to be of high quality with high replicate correlation (correlation>0.98) and with no systematic bias. A 83972 B CFT073 Supplemental Figure 2. Inversely regulated gene networks generated by IPA. The five inversely regulated genes belonged to one functional network in which HSPA6, FOSB and RN7SK interact with TATA box binding protein (TBP), a general transcription factor required for RNA polymerase II activity. The ABU strain 83972 (A) suppressed FOSB and other genes in this network while the CFT073 strain (B) enhanced their expression. 83972 also suppressed RGS4, a negative regulator of G-protein-coupled receptor-induced signaling and IFIT1, a gene of the type I IFN signaling pathway essential for the antibacterial effector response. A No of affected Network genes Score Top functions genes BAIAP2, BANP, BRIX1, Caspase, CTNNB1, Cyclin A, DACH1, Infection Mechanisms, EMP1, EPHA4, FGFBP1, GADD45G, HES1, HIST2H2BE, IgG, Infectious Disease, IL12, Interferon α, Jnk, MAVS, MDM2, NFkB, NOD1, P38 MAPK, 51 24 Endocrine System PDCD4, PELI2, PEMT, Ras homolog, TFAP2A, TLR5, Development and TNFRSF10D, UBC, Ubiquitin, VANGL2, VARS, Vegf, ZC3HAV1 Function AHCTF1, AKR1C2, ALOX5AP, ARL4A, BAMBI, BAZ2B, Bcl9- Cbp/p300-Ctnnb1-Lef/Tcf, BRF2, CA9, Ca2+, CNN2, CRIP1, Small Molecule -
Insights Into Dispersed Duplications and Complex Structural Mutations
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.03.235358; this version posted August 10, 2020. 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. Insights into dispersed duplications and complex structural mutations from whole genome sequencing 706 families Christopher W. Whelan1,2,3*, Robert E. Handsaker1,2,3, Giulio Genovese1,2,3, Seva Kashin1,2,3, Monkol Lek4, Jason Hughes5, Joshua McElwee6, Michael Lenardo7, Daniel MacArthur3,8,9, Steven A. McCarroll1,2,3* 1Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA 2Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA 3Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA 4Department of Genetics, Yale School of Medicine, New Haven, Connecticut 06520, USA 5Foundation Medicine, Cambridge, Massachusetts 02141, USA 6Nimbus Therapeutics, Cambridge, Massachusetts 02139, USA 7Clinical Genomics Program, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA. 8Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston 02114, MA, USA 9Centre for Population Genomics, Murdoch Children’s Research Institute, Melbourne, Victoria, Australia * Corresponding Author E-mail: [email protected] (C.W.W), [email protected] (S.A.M.) Abstract Two intriguing forms of genome structural variation (SV) – dispersed duplications, and de novo rearrangements of complex, multi-allelic loci – have long escaped genomic analysis. We describe a new 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.03.235358; this version posted August 10, 2020. -
1 Supplementary Material Figure S1. Volcano Plot of Differentially
Supplementary material Figure S1. Volcano Plot of differentially expressed genes between preterm infants fed own mother’s milk (OMM) or pasteurized donated human milk (DHM). Table S1. The 10 most representative biological processes filtered for enrichment p- value in preterm infants. Biological Processes p-value Quantity of DEG* Transcription, DNA-templated 3.62x10-24 189 Regulation of transcription, DNA-templated 5.34x10-22 188 Transport 3.75x10-17 140 Cell cycle 1.03x10-13 65 Gene expression 3.38x10-10 60 Multicellular organismal development 6.97x10-10 86 1 Protein transport 1.73x10-09 56 Cell division 2.75x10-09 39 Blood coagulation 3.38x10-09 46 DNA repair 8.34x10-09 39 Table S2. Differential genes in transcriptomic analysis of exfoliated epithelial intestinal cells between preterm infants fed own mother’s milk (OMM) and pasteurized donated human milk (DHM). Gene name Gene Symbol p-value Fold-Change (OMM vs. DHM) (OMM vs. DHM) Lactalbumin, alpha LALBA 0.0024 2.92 Casein kappa CSN3 0.0024 2.59 Casein beta CSN2 0.0093 2.13 Cytochrome c oxidase subunit I COX1 0.0263 2.07 Casein alpha s1 CSN1S1 0.0084 1.71 Espin ESPN 0.0008 1.58 MTND2 ND2 0.0138 1.57 Small ubiquitin-like modifier 3 SUMO3 0.0037 1.54 Eukaryotic translation elongation EEF1A1 0.0365 1.53 factor 1 alpha 1 Ribosomal protein L10 RPL10 0.0195 1.52 Keratin associated protein 2-4 KRTAP2-4 0.0019 1.46 Serine peptidase inhibitor, Kunitz SPINT1 0.0007 1.44 type 1 Zinc finger family member 788 ZNF788 0.0000 1.43 Mitochondrial ribosomal protein MRPL38 0.0020 1.41 L38 Diacylglycerol -
Targeting Cancer Cell Metabolism with Mitochondria- Immobilized Phosphorescent Cyclometalated Iridium(III) Complexes
Electronic Supplementary Material (ESI) for Chemical Science. This journal is © The Royal Society of Chemistry 2016 Electronic Supplementary Information Targeting cancer cell metabolism with mitochondria- immobilized phosphorescent cyclometalated iridium(III) complexes Jian-Jun Cao,a Cai-Ping Tan,*a Mu-He Chen,a Na Wu,a De-Yang Yao,b Xing-Guo Liu,b Liang-Nian Jia and Zong-Wan Mao*a a MOE Key Laboratory of Bioinorganic and Synthetic Chemistry, School of Chemistry and Chemical Engineering, Sun Yat-Sen University, Guangzhou 510275 (P. R. China). E-mail: [email protected]; [email protected] b Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, South China Institute for Stem Cell Biology and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, People's Republic of China. S1 Table of Contents Experimental section Materials and measurements…………..........………………………..…………..…..………..……..S5 Synthesis and characterization…………..........………………………..……………..…….………..S5 Crystallographic structure determination…………..........………………………..…….……………S7 Stability studies of complex 2…………..........………………………..……………………..………S7 Cell lines and culture conditions…………..........………………………..……………..……………S8 Cytotoxicity assay…………..........………………………..……………..…………………………..S8 Co-culture of A549 cells and LO2 cells…………..........………………………..…….…………….S8 Lipophilicity…………..........………………………..……………..……………………………...…S8 ICP-MS measurement …………..........………………………..……………..……………………...S9 -
Molecular Genetics of Phosphate Homeostasis
TECHNISCHE UNIVERSITÄT MÜNCHEN FAKULTÄT WISSENSCHAFTSZENTRUM WEIHENSTEPHAN FÜR ERNÄHRUNG, LANDNUTZUNG UND UMWELT LEHRSTUHL FÜR TIERZUCHT Molecular Genetics of Phosphate Homeostasis Susanne Beate Diener Vollständiger Abdruck der von der Fakultät Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt der Technischen Universität München zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften genehmigten Dissertation. Vorsitzender: Univ.-Prof. Dr. Michael W. Pfaffl Prüfer der Dissertation: 1. Univ.-Prof. Dr. Hans-Rudolf Fries 2. apl. Prof. Dr. Walter Just (Universität Ulm) Die Dissertation wurde am 12. März 2015 bei der Technischen Universität München eingereicht und durch die Fakultät Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt am 09. Juni 2015 angenommen. To my parents. SUMMARY SUMMARY Phosphate homeostasis is crucial for manifold physiological processes ranging from cellular signalling to bone mineralisation. It is maintained by a complex network that involves several factors and organs. Within the so-called bone-kidney axis, bone-derived fibroblast growth factor 23 (FGF23) has emerged as the key regulator of systemic phosphate turnover. It controls, through activating FGF receptor (FGFR)/Klotho complexes in the kidney, renal phosphate handling and vitamin D metabolism. If the body’s phosphate balance is disturbed, hypo- and hyperphosphatemic disorders can arise. Although several genes directly implicated in monogenic phosphate balance disorders have already been identified, the pathophysiology is still incompletely understood and many open questions remain to be elucidated. The first part of this thesis focused on a next-generation sequencing (NGS)-based strategy to identify novel potential disease genes in human hypophosphatemia. 11 unrelated families with unknown genetic cause of phosphate wasting were analysed. However, no novel variants which seem to be of pathogenic relevance in at least two unrelated patients could be detected by exome sequencing. -
INSTITUTO CARLOS CHAGAS Doutorado Em Biociências E Biotecnologia
INSTITUTO CARLOS CHAGAS Doutorado em Biociências e Biotecnologia CARACTERIZAÇÃO FUNCIONAL DE DZIP1 EM CÉLULAS DE LINHAGEM HELA E CÉLULAS-TRONCO DERIVADAS DE TECIDO ADIPOSO HUMANO PATRÍCIA SHIGUNOV CURITIBA/PR 2013 INSTITUTO CARLOS CHAGAS Pós-Graduação em Biociências e Biotecnologia Patrícia Shigunov CARACTERIZAÇÃO FUNCIONAL DE DZIP1 EM CÉLULAS DE LINHAGEM HELA E CÉLULAS-TRONCO DERIVADAS DE TECIDO ADIPOSO HUMANO Tese apresentada ao Instituto Carlos Chagas como parte dos requisitos para obtenção do título de Doutora em Biociências e Biotecnologia. Orientadores: Prof. Dr. Bruno Dallagiovanna Prof. Dr. Alejandro Correa CURITIBA/PR 2013 ii iii iv Ao meu companheiro Eduardo, Á minha amada Íris, Aos meus pais e irmãos. v AGRADECIMENTOS Ao meu esposo, Eduardo Cezar Santos, agradeço o companheirismo, paciência e compreensão. Aos meus pais, Claudinéia e Nicolau Shigunov, pelo amor incondicional e por sempre terem acreditado em mim. À minha irmã, Vanessa Shigunov, pela amizade e apoio. Ao Dr. Bruno Dalagiovanna por orientar minha formação científica desde a iniciação científica ao doutoramento. Agradeço por toda a sabedoria transmitida nesse período e pela amizade. Aos membros da banca examinadora: Dr. Samuel Goldenberg, Dr. Giordano Calloni e Dra. Lysangela Ronalte Alves pela revisão criteriosa do presente trabalho. Ao Dr. Marco Stimamiglio pelo suporte nas plataformas de citometria e microscopia confocal. Ao Dr. Jose Sotelo-Silveira pelos ensinamentos nas análises de microarranjo de DNA. Aos Dr. Fabricio Marchini e Dr. Michel Batista pelo suporte na plataforma de proteômica. À todos do Laboratório de Biologia Básica de Células-Tronco: Dr. Alejandro Correa Dominguez, Crisciele Kuligovski, Dra. Alessandra Melo de Aguiar, Andressa Vaz Schittini, Dra. Ana Paula Abud, Dra.