Genome-Wide Gene Expression Profiling and Mutation Analysis Of
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A Novel Approach to Identify Driver Genes Involved in Androgen-Independent Prostate Cancer
Schinke et al. Molecular Cancer 2014, 13:120 http://www.molecular-cancer.com/content/13/1/120 RESEARCH Open Access A novel approach to identify driver genes involved in androgen-independent prostate cancer Ellyn N Schinke1, Victor Bii1, Arun Nalla1, Dustin T Rae1, Laura Tedrick1, Gary G Meadows1 and Grant D Trobridge1,2* Abstract Background: Insertional mutagenesis screens have been used with great success to identify oncogenes and tumor suppressor genes. Typically, these screens use gammaretroviruses (γRV) or transposons as insertional mutagens. However, insertional mutations from replication-competent γRVs or transposons that occur later during oncogenesis can produce passenger mutations that do not drive cancer progression. Here, we utilized a replication-incompetent lentiviral vector (LV) to perform an insertional mutagenesis screen to identify genes in the progression to androgen-independent prostate cancer (AIPC). Methods: Prostate cancer cells were mutagenized with a LV to enrich for clones with a selective advantage in an androgen-deficient environment provided by a dysregulated gene(s) near the vector integration site. We performed our screen using an in vitro AIPC model and also an in vivo xenotransplant model for AIPC. Our approach identified proviral integration sites utilizing a shuttle vector that allows for rapid rescue of plasmids in E. coli that contain LV long terminal repeat (LTR)-chromosome junctions. This shuttle vector approach does not require PCR amplification and has several advantages over PCR-based techniques. Results: Proviral integrations were enriched near prostate cancer susceptibility loci in cells grown in androgen- deficient medium (p < 0.001), and five candidate genes that influence AIPC were identified; ATPAF1, GCOM1, MEX3D, PTRF, and TRPM4. -
Primate Specific Retrotransposons, Svas, in the Evolution of Networks That Alter Brain Function
Title: Primate specific retrotransposons, SVAs, in the evolution of networks that alter brain function. Olga Vasieva1*, Sultan Cetiner1, Abigail Savage2, Gerald G. Schumann3, Vivien J Bubb2, John P Quinn2*, 1 Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, U.K 2 Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK 3 Division of Medical Biotechnology, Paul-Ehrlich-Institut, Langen, D-63225 Germany *. Corresponding author Olga Vasieva: Institute of Integrative Biology, Department of Comparative genomics, University of Liverpool, Liverpool, L69 7ZB, [email protected] ; Tel: (+44) 151 795 4456; FAX:(+44) 151 795 4406 John Quinn: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK, [email protected]; Tel: (+44) 151 794 5498. Key words: SVA, trans-mobilisation, behaviour, brain, evolution, psychiatric disorders 1 Abstract The hominid-specific non-LTR retrotransposon termed SINE–VNTR–Alu (SVA) is the youngest of the transposable elements in the human genome. The propagation of the most ancient SVA type A took place about 13.5 Myrs ago, and the youngest SVA types appeared in the human genome after the chimpanzee divergence. Functional enrichment analysis of genes associated with SVA insertions demonstrated their strong link to multiple ontological categories attributed to brain function and the disorders. SVA types that expanded their presence in the human genome at different stages of hominoid life history were also associated with progressively evolving behavioural features that indicated a potential impact of SVA propagation on a cognitive ability of a modern human. -
1 UST College of Science Department of Biological Sciences
UST College of Science Department of Biological Sciences 1 Pharmacogenomics of Myofascial Pain Syndrome An Undergraduate Thesis Submitted to the Department of Biological Sciences College of Science University of Santo Tomas In Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Biology Jose Marie V. Lazaga Marc Llandro C. Fernandez May 2021 UST College of Science Department of Biological Sciences 2 PANEL APPROVAL SHEET This undergraduate research manuscript entitled: Pharmacogenomics of Myofascial Pain Syndrome prepared and submitted by Jose Marie V. Lazaga and Marc Llandro C. Fernandez, was checked and has complied with the revisions and suggestions requested by panel members after thorough evaluation. This final version of the manuscript is hereby approved and accepted for submission in partial fulfillment of the requirements for the degree of Bachelor of Science in Biology. Noted by: Asst. Prof. Marilyn G. Rimando, PhD Research adviser, Bio/MicroSem 602-603 Approved by: Bio/MicroSem 603 panel member Bio/MicroSem 603 panel member Date: Date: UST College of Science Department of Biological Sciences 3 DECLARATION OF ORIGINALITY We hereby affirm that this submission is our own work and that, to the best of our knowledge and belief, it contains no material previously published or written by another person nor material to which a substantial extent has been accepted for award of any other degree or diploma of a university or other institute of higher learning, except where due acknowledgement is made in the text. We also declare that the intellectual content of this undergraduate research is the product of our work, even though we may have received assistance from others on style, presentation, and language expression. -
Predicting Gene Ontology Biological Process from Temporal Gene Expression Patterns Astrid Lægreid,1,4 Torgeir R
Methods Predicting Gene Ontology Biological Process From Temporal Gene Expression Patterns Astrid Lægreid,1,4 Torgeir R. Hvidsten,2 Herman Midelfart,2 Jan Komorowski,2,3,4 and Arne K. Sandvik1 1Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, N-7489 Trondheim, Norway; 2Department of Information and Computer Science, Norwegian University of Science and Technology, N-7491 Trondheim, Norway; 3The Linnaeus Centre for Bioinformatics, Uppsala University, SE-751 24 Uppsala, Sweden The aim of the present study was to generate hypotheses on the involvement of uncharacterized genes in biological processes. To this end,supervised learning was used to analyz e microarray-derived time-series gene expression data. Our method was objectively evaluated on known genes using cross-validation and provided high-precision Gene Ontology biological process classifications for 211 of the 213 uncharacterized genes in the data set used. In addition,new roles in biological process were hypothesi zed for known genes. Our method uses biological knowledge expressed by Gene Ontology and generates a rule model associating this knowledge with minimal characteristic features of temporal gene expression profiles. This model allows learning and classification of multiple biological process roles for each gene and can predict participation of genes in a biological process even though the genes of this class exhibit a wide variety of gene expression profiles including inverse coregulation. A considerable number of the hypothesized new roles for known genes were confirmed by literature search. In addition,many biological process roles hypothesi zed for uncharacterized genes were found to agree with assumptions based on homology information. -
Role and Regulation of the P53-Homolog P73 in the Transformation of Normal Human Fibroblasts
Role and regulation of the p53-homolog p73 in the transformation of normal human fibroblasts Dissertation zur Erlangung des naturwissenschaftlichen Doktorgrades der Bayerischen Julius-Maximilians-Universität Würzburg vorgelegt von Lars Hofmann aus Aschaffenburg Würzburg 2007 Eingereicht am Mitglieder der Promotionskommission: Vorsitzender: Prof. Dr. Dr. Martin J. Müller Gutachter: Prof. Dr. Michael P. Schön Gutachter : Prof. Dr. Georg Krohne Tag des Promotionskolloquiums: Doktorurkunde ausgehändigt am Erklärung Hiermit erkläre ich, dass ich die vorliegende Arbeit selbständig angefertigt und keine anderen als die angegebenen Hilfsmittel und Quellen verwendet habe. Diese Arbeit wurde weder in gleicher noch in ähnlicher Form in einem anderen Prüfungsverfahren vorgelegt. Ich habe früher, außer den mit dem Zulassungsgesuch urkundlichen Graden, keine weiteren akademischen Grade erworben und zu erwerben gesucht. Würzburg, Lars Hofmann Content SUMMARY ................................................................................................................ IV ZUSAMMENFASSUNG ............................................................................................. V 1. INTRODUCTION ................................................................................................. 1 1.1. Molecular basics of cancer .......................................................................................... 1 1.2. Early research on tumorigenesis ................................................................................. 3 1.3. Developing -
Mitochondrial Genetics
Mitochondrial genetics Patrick Francis Chinnery and Gavin Hudson* Institute of Genetic Medicine, International Centre for Life, Newcastle University, Central Parkway, Newcastle upon Tyne NE1 3BZ, UK Introduction: In the last 10 years the field of mitochondrial genetics has widened, shifting the focus from rare sporadic, metabolic disease to the effects of mitochondrial DNA (mtDNA) variation in a growing spectrum of human disease. The aim of this review is to guide the reader through some key concepts regarding mitochondria before introducing both classic and emerging mitochondrial disorders. Sources of data: In this article, a review of the current mitochondrial genetics literature was conducted using PubMed (http://www.ncbi.nlm.nih.gov/pubmed/). In addition, this review makes use of a growing number of publically available databases including MITOMAP, a human mitochondrial genome database (www.mitomap.org), the Human DNA polymerase Gamma Mutation Database (http://tools.niehs.nih.gov/polg/) and PhyloTree.org (www.phylotree.org), a repository of global mtDNA variation. Areas of agreement: The disruption in cellular energy, resulting from defects in mtDNA or defects in the nuclear-encoded genes responsible for mitochondrial maintenance, manifests in a growing number of human diseases. Areas of controversy: The exact mechanisms which govern the inheritance of mtDNA are hotly debated. Growing points: Although still in the early stages, the development of in vitro genetic manipulation could see an end to the inheritance of the most severe mtDNA disease. Keywords: mitochondria/genetics/mitochondrial DNA/mitochondrial disease/ mtDNA Accepted: April 16, 2013 Mitochondria *Correspondence address. The mitochondrion is a highly specialized organelle, present in almost all Institute of Genetic Medicine, International eukaryotic cells and principally charged with the production of cellular Centre for Life, Newcastle energy through oxidative phosphorylation (OXPHOS). -
Circular RNA Expression in Human Hematopoietic Cells Is Widespread
bioRxiv preprint doi: https://doi.org/10.1101/300293; this version posted April 12, 2018. 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. Circular RNA expression in human hematopoietic cells is widespread and cell-type specific Benoit P Nicolet1, Sander Engels1, Francesca Aglialoro1, Emile van den Akker1, Marieke von Lindern1 and Monika C Wolkers1,* 1 Department of Hematopoiesis, Sanquin Research and Landsteiner Laboratory, Academic Medical Centre (AMC), University of Amsterdam, Amsterdam, The Netherlands. * To whom correspondence should be addressed. M. Wolkers, Sanquin Research Department of Hematopoiesis, Plesmanlaan 125, 1066 CX Amsterdam, The Netherlands. Tel: +31-20-5127003; Fax: +31- 20-5123474; Email: [email protected]. bioRxiv preprint doi: https://doi.org/10.1101/300293; this version posted April 12, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. ABSTRACT Hematopoietic stem cells differentiate into a broad range of specialized blood cells. This process is tightly regulated and depends on transcription factors, micro-RNAs, and long non-coding RNAs. Recently, also circular RNA (circRNA) were found to regulate cellular processes. Their expression pattern and their identity is however less well defined. Here, we provide the first comprehensive analysis of circRNA expression in human hematopoietic progenitors, and in differentiated lymphoid and myeloid cells. We here show that the expression of circRNA is cell-type specific, and increases upon maturation. circRNA splicing variants can also be cell-type specific. -
Identification of Differentially Expressed Genes and Pathways in Mice Exposed to Mixed Field Neutron/Photon Radiation Constantinos G
Broustas et al. BMC Genomics (2018) 19:504 https://doi.org/10.1186/s12864-018-4884-6 RESEARCHARTICLE Open Access Identification of differentially expressed genes and pathways in mice exposed to mixed field neutron/photon radiation Constantinos G. Broustas1* , Andrew D. Harken2, Guy Garty2 and Sally A. Amundson1 Abstract Background: Radiation exposure due to the detonation of an improvised nuclear device remains a major security concern. Radiation from such a device involves a combination of photons and neutrons. Although photons will make the greater contribution to the total dose, neutrons will certainly have an impact on the severity of the exposure as they have high relative biological effectiveness. Results: We investigated the gene expression signatures in the blood of mice exposed to 3 Gy x-rays, 0.75 Gy of neutrons, or to mixed field photon/neutron with the neutron fraction contributing 5, 15%, or 25% of a total 3 Gy radiation dose. Gene ontology and pathway analysis revealed that genes involved in protein ubiquitination pathways were significantly overrepresented in all radiation doses and qualities. On the other hand, eukaryotic initiation factor 2 (EIF2) signaling pathway was identified as one of the top 10 ranked canonical pathways in neutron, but not pure x-ray, exposures. In addition, the related mTOR and regulation of EIF4/p70S6K pathways were also significantly underrepresented in the exposures with a neutron component, but not in x-ray radiation. The majority of the changed genes in these pathways belonged to the ribosome biogenesis and translation machinery and included several translation initiation factors (e.g. Eif2ak4, Eif3f), as well as 40S and 60S ribosomal subunits (e.g. -
Systems-Level Identification of PKA-Dependent Signaling In
Systems-level identification of PKA-dependent PNAS PLUS signaling in epithelial cells Kiyoshi Isobea, Hyun Jun Junga, Chin-Rang Yanga,J’Neka Claxtona, Pablo Sandovala, Maurice B. Burga, Viswanathan Raghurama, and Mark A. Kneppera,1 aEpithelial Systems Biology Laboratory, Systems Biology Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892-1603 Edited by Peter Agre, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, and approved August 29, 2017 (received for review June 1, 2017) Gproteinstimulatoryα-subunit (Gαs)-coupled heptahelical receptors targets are as yet unidentified. Some of the known PKA targets regulate cell processes largely through activation of protein kinase A are other protein kinases and phosphatases, meaning that PKA (PKA). To identify signaling processes downstream of PKA, we de- activation is likely to result in indirect changes in protein phos- leted both PKA catalytic subunits using CRISPR-Cas9, followed by a phorylation manifest as a signaling network, the details of which “multiomic” analysis in mouse kidney epithelial cells expressing the remain unresolved. To identify both direct and indirect targets of Gαs-coupled V2 vasopressin receptor. RNA-seq (sequencing)–based PKA in mammalian cells, we used CRISPR-Cas9 genome editing transcriptomics and SILAC (stable isotope labeling of amino acids in to introduce frame-shifting indel mutations in both PKA catalytic cell culture)-based quantitative proteomics revealed a complete loss subunit genes (Prkaca and Prkacb), thereby eliminating PKA-Cα of expression of the water-channel gene Aqp2 in PKA knockout cells. and PKA-Cβ proteins. This was followed by use of quantitative SILAC-based quantitative phosphoproteomics identified 229 PKA (SILAC-based) phosphoproteomics to identify phosphorylation phosphorylation sites. -
Anti-ADD3 / Gamma Adducin Antibody (ARG66528)
Product datasheet [email protected] ARG66528 Package: 100 μg anti-ADD3 / gamma Adducin antibody Store at: -20°C Summary Product Description Rabbit Polyclonal antibody recognizes ADD3 / gamma Adducin Tested Reactivity Hu, Ms Predict Reactivity Rat Tested Application WB Host Rabbit Clonality Polyclonal Isotype IgG Target Name ADD3 / gamma Adducin Antigen Species Human Immunogen Synthetic peptide within aa. 400-480 of Human ADD3 / gamma Adducin. Conjugation Un-conjugated Alternate Names Gamma-adducin; ADDL; Adducin-like protein 70 Application Instructions Application table Application Dilution WB 1:500 - 1:2000 Application Note * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 79 kDa Observed Size 75 kDa Properties Form Liquid Purification Affinity purification with immunogen. Buffer PBS, 0.02% Sodium azide, 50% Glycerol and 0.5% BSA. Preservative 0.02% Sodium azide Stabilizer 50% Glycerol and 0.5% BSA Concentration 1 mg/ml Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot and store at -20°C. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening. The antibody solution should be gently mixed before use. www.arigobio.com 1/2 Note For laboratory research only, not for drug, diagnostic or other use. Bioinformation Gene Symbol ADD3 Gene Full Name adducin 3 (gamma) Background Adducins are heteromeric proteins composed of different subunits referred to as adducin alpha, beta and gamma. The three subunits are encoded by distinct genes and belong to a family of membrane skeletal proteins involved in the assembly of spectrin-actin network in erythrocytes and at sites of cell- cell contact in epithelial tissues. -
Pulling the Hood Off Genetic Susceptibility to Hypertensive
EDITORIAL www.jasn.org Pulling the Hood off Genetic Rodent genetic models may provide opportunities to ad- dress these challenges and identify mechanisms by which Susceptibility to Hypertensive HRD arises. This is especially so when genetic risk arises from natural genetic variation that can reveal the involvement Renal Disease of genes or mechanisms not previously anticipated to partic- ipate in disease. Opportunities beyond the reach of human Isha S. Dhande 1 and Peter A. Doris1 population genetics include reduced genetic complexity be- 1 Center for Human Genetics, Brown Foundation Institute of Molecular cause the maternal and paternal autosomes in inbred rodent Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas models are genetically identical. Both selective breeding and targeted genetic modification can be performed in model or- JASN 31: ccc–ccc, 2020. fi doi: https://doi.org/10.1681/ASN.2020020139 ganisms to investigate speci c genetic variation. These ap- proaches include low-resolution replacement of an entire chromosome (consomic line) or a chromosomal segment The effect of elevated BP on morbidity and mortality is not (congenic line) from a rodent strain that lacks disease suscep- uniformly distributed across the hypertensive population. tibility. Higher resolution obtained by targeted gene deletion Susceptibility to progressive hypertensive renal disease and replacement of single genes are also important tools after (HRD) is influenced by heritable factors: the occurrence of the potential target has been refined. Several useful rat models family members who have experienced ESKD is a robust pre- of HRD have been identified that result from natural genetic dictor of risk1,2 and provides the rationale for large-scale pop- variation. -
Dynamic Changes of Muscle Insulin Sensitivity After Metabolic Surgery
ARTICLE https://doi.org/10.1038/s41467-019-12081-0 OPEN Dynamic changes of muscle insulin sensitivity after metabolic surgery Sofiya Gancheva1,2,3,11, Meriem Ouni 3,4,11, Tomas Jelenik2,3, Chrysi Koliaki1,2,3,5, Julia Szendroedi1,2,3, Frederico G.S. Toledo6, Daniel F. Markgraf 2,3, Dominik H. Pesta 2,3, Lucia Mastrototaro2,3, Elisabetta De Filippo2,3, Christian Herder 1,2,3, Markus Jähnert 3,4, Jürgen Weiss3,7, Klaus Strassburger 3,8, Matthias Schlensak9, Annette Schürmann 3,4,10,12 & Michael Roden 1,2,3,12 1234567890():,; The mechanisms underlying improved insulin sensitivity after surgically-induced weight loss are still unclear. We monitored skeletal muscle metabolism in obese individuals before and over 52 weeks after metabolic surgery. Initial weight loss occurs in parallel with a decrease in muscle oxidative capacity and respiratory control ratio. Persistent elevation of intramyocel- lular lipid intermediates, likely resulting from unrestrained adipose tissue lipolysis, accom- panies the lack of rapid changes in insulin sensitivity. Simultaneously, alterations in skeletal muscle expression of genes involved in calcium/lipid metabolism and mitochondrial function associate with subsequent distinct DNA methylation patterns at 52 weeks after surgery. Thus, initial unfavorable metabolic changes including insulin resistance of adipose tissue and skeletal muscle precede epigenetic modifications of genes involved in muscle energy metabolism and the long-term improvement of insulin sensitivity. 1 Division of Endocrinology and Diabetology, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany. 2 Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University, Düsseldorf, Germany. 3 German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany.