Functional Genomics and Proteomics of the Cellular Osmotic Stress
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Chapter 14: Functional Genomics Learning Objectives
Chapter 14: Functional Genomics Learning objectives Upon reading this chapter, you should be able to: ■ define functional genomics; ■ describe the key features of eight model organisms; ■ explain techniques of forward and reverse genetics; ■ discuss the relation between the central dogma and functional genomics; and ■ describe proteomics-based approaches to functional genomics. Outline : Functional genomics Introduction Relation between genotype and phenotype Eight model organisms E. coli; yeast; Arabidopsis; C. elegans; Drosophila; zebrafish; mouse; human Functional genomics using reverse and forward genetics Reverse genetics: mouse knockouts; yeast; gene trapping; insertional mutatgenesis; gene silencing Forward genetics: chemical mutagenesis Functional genomics and the central dogma Approaches to function; Functional genomics and DNA; …and RNA; …and protein Proteomic approaches to functional genomics CASP; protein-protein interactions; protein networks Perspective Albert Blakeslee (1874–1954) studied the effect of altered chromosome numbers on the phenotype of the jimson-weed Datura stramonium, a flowering plant. Introduction: Functional genomics Functional genomics is the genome-wide study of the function of DNA (including both genes and non-genic regions), as well as RNA and proteins encoded by DNA. The term “functional genomics” may apply to • the genome, transcriptome, or proteome • the use of high-throughput screens • the perturbation of gene function • the complex relationship of genotype and phenotype Functional genomics approaches to high throughput analyses Relationship between genotype and phenotype The genotype of an individual consists of the DNA that comprises the organism. The phenotype is the outward manifestation in terms of properties such as size, shape, movement, and physiology. We can consider the phenotype of a cell (e.g., a precursor cell may develop into a brain cell or liver cell) or the phenotype of an organism (e.g., a person may have a disease phenotype such as sickle‐cell anemia). -
Masterpath: Network Analysis of Functional Genomics Screening Data
MasterPATH: network analysis of functional genomics screening data Natalia Rubanova, Guillaume Pinna, Jeremie Kropp, Anna Campalans, Juan Pablo Radicella, Anna Polesskaya, Annick Harel-Bellan, Nadya Morozova To cite this version: Natalia Rubanova, Guillaume Pinna, Jeremie Kropp, Anna Campalans, Juan Pablo Radicella, et al.. MasterPATH: network analysis of functional genomics screening data. BMC Genomics, BioMed Central, 2020, 21 (1), pp.632. 10.1186/s12864-020-07047-2. hal-02944249 HAL Id: hal-02944249 https://hal.archives-ouvertes.fr/hal-02944249 Submitted on 26 Nov 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Rubanova et al. BMC Genomics (2020) 21:632 https://doi.org/10.1186/s12864-020-07047-2 METHODOLOGY ARTICLE Open Access MasterPATH: network analysis of functional genomics screening data Natalia Rubanova1,2,3* , Guillaume Pinna4, Jeremie Kropp1, Anna Campalans5,6,7, Juan Pablo Radicella5,6,7, Anna Polesskaya8, Annick Harel-Bellan1 and Nadya Morozova1,4 Abstract Background: Functional genomics employs several experimental approaches to investigate gene functions. High- throughput techniques, such as loss-of-function screening and transcriptome profiling, allow to identify lists of genes potentially involved in biological processes of interest (so called hit list). -
Exploring Functional Pairing Between Surface Glycoconjugates And
Exploring functional pairing between surface PNAS PLUS glycoconjugates and human galectins using programmable glycodendrimersomes Qi Xiaoa, Anna-Kristin Ludwigb, Cecilia Romanòc, Irene Buzzaccheraa,d,e,f, Samuel E. Shermana, Maria Vetroc, Sabine Vértesyb, Herbert Kaltnerb, Ellen H. Reedg, Martin Möllerd,e, Christopher J. Wilsonf, Daniel A. Hammerg,h, Stefan Oscarsonc, Michael L. Kleini,1, Hans-Joachim Gabiusb, and Virgil Perceca,1 aRoy & Diana Vagelos Laboratories, Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104-6323; bInstitute of Physiological Chemistry, Faculty of Veterinary Medicine, Ludwig-Maximilians-University, 80539 Munich, Germany; cCentre for Synthesis and Chemical Biology, University College Dublin, Dublin 4, Ireland; dDWI − Leibniz Institute for Interactive Materials, RWTH Aachen University, 52074 Aachen, Germany; eInstitute of Technical and Macromolecular Chemistry, RWTH Aachen University, 52074 Aachen, Germany; fNovioSense B.V., 6534 AT Nijmegen, The Netherlands; gDepartment of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104-6321; hDepartment of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, PA 19104-6391; and iInstitute of Computational Molecular Science, Temple University, Philadelphia, PA 19122 Contributed by Michael L. Klein, January 4, 2018 (sent for review November 16, 2017; reviewed by Timothy J. Deming and Yoshiko Miura) Precise translation of glycan-encoded information into cellular lection process are not yet defined quantitatively. Confronted with activity depends critically on highly specific functional pairing the combination of natural glycan complexity and the result of between glycans and their human lectin counter receptors. Sulfo- evolutionary structure diversification within a lectin family, the glycolipids, such as sulfatides, are important glycolipid components ultimate experimental strategy would seem to require full glycome of the biological membranes found in the nervous and immune and lectin network analysis. -
OSTF1 (AT9G4): Sc-517418
SAN TA C RUZ BI OTEC HNOL OG Y, INC . OSTF1 (AT9G4): sc-517418 BACKGROUND PRODUCT OSTF1 (osteoclast-stimulating factor 1) is a 214 amino acid cytoplasmic pro - Each vial contains 100 µg IgG 2a kappa light chain in 1.0 ml of PBS with tein that contains 3 ANK repeats and one SH3 domain. The SH3 domain < 0.1% sodium azide and 0.1% gelatin. mediates interaction of OSTF1 with SMN. In addition to SMN, OSTF1 inter - acts with Src and FAS-L. In osteoclasts, OSTF1 is thought to induce bone APPLICATIONS resorption most likely through a signaling cascade that results in the secre - OSTF1 (AT9G4) is recommended for detection of OSTF1 of mouse, rat and tion of factors that enhance osteoclast formation and activity. The gene that human origin by Western Blotting (starting dilution 1:200, dilution range encdoes OSTF1 consists of almost 59,000 bases and maps to human chro mo - 1:100-1:1000), immunoprecipitation [1-2 µg per 100-500 µg of total protein some 9q21.13. Housing over 900 genes, chromosome 9 comprises nearly 4% (1 ml of cell lysate)], immunofluorescence (starting dilution 1:50, dilution of the human genome. Hereditary hemorrhagic telangiectasia, which is char - range 1:50-1:500), flow cytometry (1 µg per 1 x 10 6 cells) and solid phase acterized by harmful vascular defects, and familial dysautonomia, are both ELISA (starting dilution 1:30, dilution range 1:30-1:3000). associated with chromosome 9. Notably, chromosome 9 encompasses the largest interferon family gene cluster. Suitable for use as control antibody for OSTF1 siRNA (h): sc-92800, OSTF1 siRNA (m): sc-151336, OSTF1 shRNA Plasmid (h): sc-92800-SH, OSTF1 REFERENCES shRNA Plasmid (m): sc-151336-SH, OSTF1 shRNA (h) Lentiviral Particles: sc-92800-V and OSTF1 shRNA (m) Lentiviral Particles: sc-151336-V. -
The Economic Impact and Functional Applications of Human Genetics and Genomics
The Economic Impact and Functional Applications of Human Genetics and Genomics Commissioned by the American Society of Human Genetics Produced by TEConomy Partners, LLC. Report Authors: Simon Tripp and Martin Grueber May 2021 TEConomy Partners, LLC (TEConomy) endeavors at all times to produce work of the highest quality, consistent with our contract commitments. However, because of the research and/or experimental nature of this work, the client undertakes the sole responsibility for the consequence of any use or misuse of, or inability to use, any information or result obtained from TEConomy, and TEConomy, its partners, or employees have no legal liability for the accuracy, adequacy, or efficacy thereof. Acknowledgements ASHG and the project authors wish to thank the following organizations for their generous support of this study. Invitae Corporation, San Francisco, CA Regeneron Pharmaceuticals, Inc., Tarrytown, NY The project authors express their sincere appreciation to the following indi- viduals who provided their advice and input to this project. ASHG Government and Public Advocacy Committee Lynn B. Jorde, PhD ASHG Government and Public Advocacy Committee (GPAC) Chair, President (2011) Professor and Chair of Human Genetics George and Dolores Eccles Institute of Human Genetics University of Utah School of Medicine Katrina Goddard, PhD ASHG GPAC Incoming Chair, Board of Directors (2018-2020) Distinguished Investigator, Associate Director, Science Programs Kaiser Permanente Northwest Melinda Aldrich, PhD, MPH Associate Professor, Department of Medicine, Division of Genetic Medicine Vanderbilt University Medical Center Wendy Chung, MD, PhD Professor of Pediatrics in Medicine and Director, Clinical Cancer Genetics Columbia University Mira Irons, MD Chief Health and Science Officer American Medical Association Peng Jin, PhD Professor and Chair, Department of Human Genetics Emory University Allison McCague, PhD Science Policy Analyst, Policy and Program Analysis Branch National Human Genome Research Institute Rebecca Meyer-Schuman, MS Human Genetics Ph.D. -
The Effect of Bovine Galectin-1, a Conceptus Secretory Protein, on the Endometrial Transcriptome
Graduate Theses, Dissertations, and Problem Reports 2019 The Effect of Bovine Galectin-1, a Conceptus Secretory Protein, on the Endometrial Transcriptome Lindsay Faye Grose West Virginia University, [email protected] Follow this and additional works at: https://researchrepository.wvu.edu/etd Part of the Beef Science Commons, Dairy Science Commons, Genetics Commons, Large or Food Animal and Equine Medicine Commons, and the Other Physiology Commons Recommended Citation Grose, Lindsay Faye, "The Effect of Bovine Galectin-1, a Conceptus Secretory Protein, on the Endometrial Transcriptome" (2019). Graduate Theses, Dissertations, and Problem Reports. 4088. https://researchrepository.wvu.edu/etd/4088 This Thesis is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Thesis in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Thesis has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact [email protected]. The Effect of Bovine Galectin-1, a Conceptus Secretory Protein, on the Endometrial Transcriptome Lindsay Faye Grose Thesis submitted to the Davis College of Agriculture, Natural Resources and Design at West Virginia University in partial fulfillment of the requirements for the degree of Master of Science in Reproductive Physiology Daniel J. -
Recognition of Microbial Glycans by Soluble Human Lectins
Available online at www.sciencedirect.com ScienceDirect Recognition of microbial glycans by soluble human lectins 3 1 1,2 Darryl A Wesener , Amanda Dugan and Laura L Kiessling Human innate immune lectins that recognize microbial glycans implicated in the regulation of microbial colonization and can conduct microbial surveillance and thereby help prevent in protection against infection. Seminal research on the infection. Structural analysis of soluble lectins has provided acute response to bacterial infection led to the identifica- invaluable insight into how these proteins recognize their tion of secreted factors that include C-reactive protein cognate carbohydrate ligands and how this recognition gives (CRP) and mannose-binding lectin (MBL) [1,3]. Both rise to biological function. In this opinion, we cover the CRP and MBL can recognize carbohydrate antigens on structural features of lectins that allow them to mediate the surface of pathogens, including Streptococcus pneumo- microbial recognition, highlighting examples from the collectin, niae and Staphylococcus aureus and then promote comple- Reg protein, galectin, pentraxin, ficolin and intelectin families. ment-mediated opsonization and cell killing [4]. Since These analyses reveal how some lectins (e.g., human intelectin- these initial observations, other lectins have been impli- 1) can recognize glycan epitopes that are remarkably diverse, cated in microbial recognition. Like MBL some of these yet still differentiate between mammalian and microbial proteins are C-type lectins, while others are members of glycans. We additionally discuss strategies to identify lectins the ficolin, pentraxin, galectin, or intelectin families. that recognize microbial glycans and highlight tools that Many of the lectins that function in microbial surveillance facilitate these discovery efforts. -
Human Lectins, Their Carbohydrate Affinities and Where to Find Them
biomolecules Review Human Lectins, Their Carbohydrate Affinities and Where to Review HumanFind Them Lectins, Their Carbohydrate Affinities and Where to FindCláudia ThemD. Raposo 1,*, André B. Canelas 2 and M. Teresa Barros 1 1, 2 1 Cláudia D. Raposo * , Andr1 é LAQVB. Canelas‐Requimte,and Department M. Teresa of Chemistry, Barros NOVA School of Science and Technology, Universidade NOVA de Lisboa, 2829‐516 Caparica, Portugal; [email protected] 12 GlanbiaLAQV-Requimte,‐AgriChemWhey, Department Lisheen of Chemistry, Mine, Killoran, NOVA Moyne, School E41 of ScienceR622 Co. and Tipperary, Technology, Ireland; canelas‐ [email protected] NOVA de Lisboa, 2829-516 Caparica, Portugal; [email protected] 2* Correspondence:Glanbia-AgriChemWhey, [email protected]; Lisheen Mine, Tel.: Killoran, +351‐212948550 Moyne, E41 R622 Tipperary, Ireland; [email protected] * Correspondence: [email protected]; Tel.: +351-212948550 Abstract: Lectins are a class of proteins responsible for several biological roles such as cell‐cell in‐ Abstract:teractions,Lectins signaling are pathways, a class of and proteins several responsible innate immune for several responses biological against roles pathogens. such as Since cell-cell lec‐ interactions,tins are able signalingto bind to pathways, carbohydrates, and several they can innate be a immuneviable target responses for targeted against drug pathogens. delivery Since sys‐ lectinstems. In are fact, able several to bind lectins to carbohydrates, were approved they by canFood be and a viable Drug targetAdministration for targeted for drugthat purpose. delivery systems.Information In fact, about several specific lectins carbohydrate were approved recognition by Food by andlectin Drug receptors Administration was gathered for that herein, purpose. plus Informationthe specific organs about specific where those carbohydrate lectins can recognition be found by within lectin the receptors human was body. -
Human Functional Genomics Project Begins Unraveling Links Between
Human Functional Genomics Project Begins Unraveling Links Between Genes, Immune Response Jul 28, 2016 | Elizabeth Newbern Premium NEW YORK (GenomeWeb) – Earlier this month, researchers involved in the Human Functional Genomics Project (HFGP) published data on the relationship between genetics and human cytokine response in Nature Medicine. The data was derived from a first cohort, the 200 Functional Genomics project, and the researchers plan to publish more data from this cohort in Nature Medicine in August. In addition, the HFGP just finished collecting patient data from a second cohort made up of 500 healthy individuals from Western Europe and aptly named the 500 Functional Genomics project, late last year. The HFGP researchers also recently finished collecting data from their LifeLines-deep cohort, made up of 1,600 healthy individuals from Western Europe. The researchers are assessing and analyzing the 500 FG and LifeLines-deep data now and hope to publish preliminary results at the end of this year, Mihai Netea, member of the HFGP's scientific advisory board and professor of the Radboud Center for Infectious Diseases (RCI) in the Netherlands, told GenomeWeb. They also finished recruitment and started data collection for their 300 Functional Genomics project, which is a cohort of 300 obese individuals, he added. The human immune system is composed of a complex network of organs, tissues, cells, and molecules and has evolved to both protect the host against infections and to play roles in immune surveillance. However, it has previously been unclear what role genetics plays in influencing cytokine responses in health and disease. The HFGP researchers aim to find out more about the role of genetics in immune response by characterizing and better understanding variation in human response through the use of various omics analyses — genomic, transcriptomic, metabolomic, and microbiomic — and in-depth functional phenotyping. -
Tesis Andrea Flores UAM.Pdf
¿Qué somos y cómo realizaremos eso que somos? Octavio Paz, Nobel Prize of Literature 1980 “Te enterramos ayer. Ayer te enterramos. Te echamos tierra ayer. Quedaste en la tierra ayer. Estás rodeada de tierra desde ayer. Arriba y abajo y a los lados, por tus pies y por tu cabeza, está la tierra desde ayer. Te metimos en la tierra, te tapamos con tierra ayer. Perteneces a la tierra desde ayer. Ayer te enterramos en la tierra, ayer". Jaime Sabines. DEDICO ESTA TESIS A MI ABUE, POR SER MI PIEDRA DE TOQUE Y LA MUJER QUE MÁS HE ADMIRADO Cecilia Caballero Jiménez (1924 -2014) ACKNOWLEDGEMENTS To all my lab -mates in the Department of Physical and Chemical Biology (CIB) , for your company through the years. To Antonio, for your guidance. To the people at the Institute of Chemistry (UNAM), for receiving me as part of your group. To all the people in the Glycopharm Marie Curi e ITN, for your inspiration in my scientific research, I wish to have an everlasting relation with you. To my students, for your admiration and your will to never stop learning. To my best friends , scattered around the globe, I love you . To Sandy and Silvi a in particular. To my siblings, and my nephew and niece, Alan and Talia. For your presence in my life. I love you deeply. And to all that were a part of my path in the obtention of this PhD, para ustedes . OUTLINE OUTLINE List of abbreviations ..……………………………………………………... v Glosary ………..…….………………… …………………………………... vi ABSTRACT ………………………………………………………………. ix RESUMEN ………………………………………………………………... xi INTRODUCTION ……………………………… ………………………... 1 1. CELL GLYCOSYLATION …….………….. -
The Landscape of Human Mutually Exclusive Splicing
bioRxiv preprint doi: https://doi.org/10.1101/133215; this version posted May 2, 2017. 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-ND 4.0 International license. The landscape of human mutually exclusive splicing Klas Hatje1,2,#,*, Ramon O. Vidal2,*, Raza-Ur Rahman2, Dominic Simm1,3, Björn Hammesfahr1,$, Orr Shomroni2, Stefan Bonn2§ & Martin Kollmar1§ 1 Group of Systems Biology of Motor Proteins, Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Göttingen, Germany 2 Group of Computational Systems Biology, German Center for Neurodegenerative Diseases, Göttingen, Germany 3 Theoretical Computer Science and Algorithmic Methods, Institute of Computer Science, Georg-August-University Göttingen, Germany § Corresponding authors # Current address: Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland $ Current address: Research and Development - Data Management (RD-DM), KWS SAAT SE, Einbeck, Germany * These authors contributed equally E-mail addresses: KH: [email protected], RV: [email protected], RR: [email protected], DS: [email protected], BH: [email protected], OS: [email protected], SB: [email protected], MK: [email protected] - 1 - bioRxiv preprint doi: https://doi.org/10.1101/133215; this version posted May 2, 2017. 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. -
High-Throughput Automated Microfluidic Sample Preparation for Accurate Microbial Genomics
High-throughput automated microfluidic sample preparation for accurate microbial genomics The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Kim, Soohong et al. “High-Throughput Automated Microfluidic Sample Preparation for Accurate Microbial Genomics.” Nature Communications 8 (2017): 13919. © 2017 Macmillan Publishers Limited As Published http://dx.doi.org/10.1038/ncomms13919 Publisher Nature Publishing Group Version Final published version Citable link http://hdl.handle.net/1721.1/108270 Terms of Use Creative Commons Attribution 4.0 International License Detailed Terms http://creativecommons.org/licenses/by/4.0/ ARTICLE Received 14 Oct 2016 | Accepted 11 Nov 2016 | Published 27 Jan 2017 DOI: 10.1038/ncomms13919 OPEN High-throughput automated microfluidic sample preparation for accurate microbial genomics Soohong Kim1,2, Joachim De Jonghe1,3, Anthony B. Kulesa1,2, David Feldman1,4, Tommi Vatanen1,5, Roby P. Bhattacharyya1,6, Brittany Berdy7, James Gomez1, Jill Nolan1, Slava Epstein7 & Paul C. Blainey1,2 Low-cost shotgun DNA sequencing is transforming the microbial sciences. Sequencing instruments are so effective that sample preparation is now the key limiting factor. Here, we introduce a microfluidic sample preparation platform that integrates the key steps in cells to sequence library sample preparation for up to 96 samples and reduces DNA input requirements 100-fold while maintaining or improving data quality. The general-purpose microarchitecture we demonstrate supports workflows with arbitrary numbers of reaction and clean-up or capture steps. By reducing the sample quantity requirements, we enabled low-input (B10,000 cells) whole-genome shotgun (WGS) sequencing of Mycobacterium tuberculosis and soil micro-colonies with superior results.