DOCSLIB.ORG

Computational Ortholog Prediction: Evaluating Use Cases and Improving High-Throughput Performance

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Computational Ortholog Prediction: Evaluating Use Cases and Improving High-Throughput Performance by Matthew Daratha Whiteside B.Sc., (Hons., Bioinformatics), University of Waterloo, 2006 Thesis Submitted In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in the Department of Molecular Biology and Biochemistry Faculty of Science © Matthew Daratha Whiteside 2013 SIMON FRASER UNIVERSITY Spring 2013 Approval Name: Matthew Daratha Whiteside Degree: Doctor of Philosophy Title of Thesis: Computational Ortholog Prediction: Evaluating Use Cases and Improving High-Throughput Performance Examining Committee: Chair: Dr. Ralph Pantophlet Assistant Professor, Faculty of Health Sciences Dr. Fiona S.L. Brinkman Senior Supervisor Professor, Department of Molecular Biology and Biochemistry Dr. Jack Chen Supervisor Associate Professor, Department of Molecular Biology and Biochemistry Dr. Margo M. Moore Supervisor Professor, Department of Biological Sciences Dr. Ryan D. Morin Internal Examiner Assistant Professor, Department of Molecular Biology and Biochemistry Dr. Rosemary J. Redfield External Examiner Professor, Department of Zoology University of British Columbia Date Defended/Approved: March 8th, 2013 ii Partial Copyright Licence iii Abstract Orthologs are genes that diverged from an ancestral gene when the species diverged. High-throughput computational methods for ortholog prediction are a key component of many computational biology analyses. A fundamental premise in these analyses is that orthologs (when predicted correctly) are functionally equivalent and can be used to transfer gene annotations across species. Currently, many existing ortholog prediction methods generate a sizeable number of incorrect ortholog predictions, especially in cases of complex gene evolution. My thesis examines the functional equivalence hypothesis further and presents one solution that increases the precision of ortholog prediction. To examine the use of orthologs in computational analysis, I conducted and evaluated three projects that employ ortholog prediction in distinct ways. In these projects, orthologs were used to (1) identify conserved, unique genes in metazoan species, (2) validate predicted gene regulatory modules in Pseudomonas aeruginosa, and (3) construct a transcriptional regulatory network in Aspergillus fumigatus. I identified factors affecting ortholog prediction in these specific use cases, demonstrating how successive gene duplications, incomplete genomes and rapid evolution of gene regulation can impact the results for such analyses. To improve ortholog prediction, I evaluated and augmented an existing method called Ortholuge. Ortholuge is a computational method that increases the precision of ortholog prediction in a high-throughput setting. I evaluated the performance of Ortholuge, showing that its approach of classifying orthologs based on their relative phylogenetic divergence does identify orthologs that are more functionally equivalent. I compared Ortholuge to contemporary methods QuartetS and OMA, and showed that Ortholuge consistently identifies functionally-equivalent orthologs across a range of taxonomic distances. I also further developed Ortholuge’s functionality by reducing run-time, increasing accuracy and improving usability through a number of modifications. Lastly, to make Ortholuge results available to the research community, I developed a database of Ortholuge ortholog predictions for bacteria and archaea species. This online iv database provides high-level visualization of orthologs and the ability to easily run complex queries to retrieve genes that are shared or unique between specified taxa. Overall, this work contributes an enhanced method for precise high-throughput ortholog identification and increases our understanding of the functional equivalences between orthologs. Keywords: Orthology; Comparative Genomics; Bioinformatics; Phylogenomics; Evolution v Dedication Aan mijn liefde Joske. Dank u voor jou eeuwige steun. Je geeft me de moed om mijn dromen te volgen. vi Acknowledgements I would like to thank the many people who have helped me in the completion of my PhD thesis. The first is my senior supervisor, Dr. Fiona Brinkman. You have my sincerest gratitude. Thank you for this opportunity, which has taught me so much. My PhD has been more than an education; it has been a life changing experience. I would like to thank past and present members of the Brinkman lab. You have made this experience truly unforgettable. Thank you so much for your support and shared laughs during these past six years. I am very thankful for the invaluable guidance and contribution of my supervisory committee; Dr. Margo Moore and Dr. Jack Chen. I would like to acknowledge all project collaborators. Your help and the opportunities you have provided me have made this work possible. I would like to extend thanks to: • Drs. Jinko Graham and Brad McNeney, Jeong Eun Min – OL.locfdr Project • Drs. Melissa Frederic and Michel Leroux – Metazoan Project • Dr. Margo Moore, Linda Pinto and Jason Catterson – Aspergillus fumigatus Iron-Limitation Project • Geoff Winsor and Matthew Laird – OrtholugeDB Project Thank you to the funding agencies: the Michael Smith Foundation for Health Research and Simon Fraser University for their financial support during my PhD. Finally, I would like to thank my family. Without your support and encouragement, none of this would be possible. vii Table of Contents Approval .............................................................................................................................ii Partial Copyright Licence .................................................................................................. iii Abstract .............................................................................................................................iv Dedication .........................................................................................................................vi Acknowledgements .......................................................................................................... vii Table of Contents ............................................................................................................ viii List of Tables .................................................................................................................... xii List of Figures.................................................................................................................. xiii List of Acronyms ...............................................................................................................xv Glossary .......................................................................................................................... xvi 1. Introduction to Homology and Comparative Genomics ..................................... 1 1.1. Gene Evolution and Its Impact on Gene Function ................................................... 2 1.1.1. Overview of the Mechanisms of Gene Evolution .......................................... 2 1.1.2. Definition of Orthology and Paralogy ............................................................ 3 1.1.3. Correspondence between Mode of Gene Evolution and Functional Divergence ................................................................................................... 5 Fates of Genes after Duplication .................................................................. 6 Neofunctionalization ..................................................................................... 7 Subfunctionalization ..................................................................................... 7 1.2. Detection of Orthologs ............................................................................................. 8 1.2.1. Phylogenetic Tree-based Detection of Orthologs ......................................... 8 1.2.2. Graph-based Detection of Orthologs ............................................................ 9 1.2.3. Hybrid Approaches ..................................................................................... 10 1.2.4. Resolving Complex Ortholog Relationships ............................................... 11 Detection of In-paralogs ............................................................................. 11 Grouping Orthologs from Multiple Species ................................................. 11 1.3. Factors Affecting Ortholog Prediction Accuracy ..................................................... 14 Gene Loss and Incomplete Genomes ........................................................ 14 Gene Fusion and Fission ........................................................................... 15 Issues Identifying the Nearest Neighbour with the BLAST Algorithm ........ 15 Horizontal Gene Transfer ........................................................................... 16 1.4. Improving Ortholog Prediction ................................................................................ 16 1.4.1. Review of Existing Strategies for Improved Ortholog Prediction ................ 16 Phylogenetic-based Ortholog Prediction without a Species Tree .............. 16 Overcoming Limitations of the BLAST algorithm in Identifying the Nearest Neighbour ............................................................................... 17 A Domain-Centric Approach ....................................................................... 17 Synteny .....................................................................................................
Recommended publications
  • Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy Revisited Genotype-Phenotype Correlations of All Published Cases

    Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy Revisited Genotype-Phenotype Correlations of All Published Cases

    VIEWS AND REVIEWS OPEN ACCESS Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy revisited Genotype-phenotype correlations of all published cases Georgia Xiromerisiou, MD, PhD, Chrysoula Marogianni, MD, MSc, Katerina Dadouli, MSc, Correspondence Christina Zompola, MD, Despoina Georgouli, MD, MSc, Antonios Provatas, MD, PhD, Dr. Xiromerisiou [email protected] Aikaterini Theodorou, MD, Paschalis Zervas, MD, Christina Nikolaidou, MD, Stergios Stergiou, MD, Panagiotis Ntellas, MD, Maria Sokratous, MD, MSc, Pantelis Stathis, MD, PhD, Georgios P. Paraskevas, MD, PhD, Anastasios Bonakis, MD, PhD, Konstantinos Voumvourakis, MD, PhD, Christos Hadjichristodoulou, MD, PhD, Georgios M. Hadjigeorgiou, MD, PhD, and Georgios Tsivgoulis, MD, PhD Neurol Genet 2020;6:e434. doi:10.1212/NXG.0000000000000434 Abstract Objective The aim of this study was to evaluate the correlation between the various NOTCH3 mutations and their clinical and genetic profile, along with the presentation of a novel mutation in a patient. Methods Here, we describe the phenotype of a patient with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) harboring a novel mutation. We also performed an extensive literature research for NOTCH3 mutations published since the identification of the gene and performed a systematic review of all published cases with NOTCH3 mutations. We evaluated the mutation pathogenicity in a great number of patients with detailed clinical and genetic evaluation and investigated the possible phenotype-genotype correlations. Results Our patient harbored a novel mutation in the NOTCH3 gene, the c.3084 G > C, corresponding to the aminoacidic substitution p.Trp1028Cys, presenting with seizures as the first neurologic manifestation. We managed to find a correlation between the pathogenicity of mutations, severity of the phenotype, and age at onset of CADASIL.
  • Genome-Wide Analysis of LRR-RLK Gene Family in Four Gossypium Species and Expression Analysis During Cotton Development and Stress Responses

    Genome-Wide Analysis of LRR-RLK Gene Family in Four Gossypium Species and Expression Analysis During Cotton Development and Stress Responses

    G C A T T A C G G C A T genes Article Genome-Wide Analysis of LRR-RLK Gene Family in Four Gossypium Species and Expression Analysis during Cotton Development and Stress Responses Ruibin Sun 1, Shaohui Wang 1, Dan Ma 1 and Chuanliang Liu 1,2,* 1 State Key Laboratory of Cotton Biology, Institute of Cotton Research, Chinese Academy of Agricultural Sciences, Anyang 455000, China; [email protected] (R.S.); [email protected] (S.W.); [email protected] (D.M.) 2 Zhengzhou Research Base, State Key Laboratory of Cotton Biology, Zhengzhou University, Zhengzhou 450066, China * Correspondence: [email protected] Received: 30 September 2018; Accepted: 26 November 2018; Published: 29 November 2018 Abstract: Leucine-rich repeat receptor-like kinases (LRR-RLKs) have been reported to play important roles in plant growth, development, and stress responses. However, no comprehensive analysis of this family has been performed in cotton (Gossypium spp.), which is an important economic crop that suffers various stresses in growth and development. Here we conducted a comprehensive analysis of LRR-RLK family in four Gossypium species (Gossypium arboreum, Gossypium barbadense, Gossypium hirsutum, and Gossypium raimondii). A total of 1641 LRR-RLK genes were identified in the four Gossypium species involved in our study. The maximum-likelihood phylogenetic tree revealed that all the LRR-RLK genes were divided into 21 subgroups. Exon-intron organization structure of LRR-RLK genes kept relatively conserved within subfamilies and between Arabidopsis and Gossypium genomes. Notably, subfamilies XI and XII were found dramatically expanded in Gossypium species. Tandem duplication acted as an important mechanism in expansion of the Gossypium LRR-RLK gene family.
  • How Chaotic Is Genome Chaos?

    How Chaotic Is Genome Chaos?

    cancers Review How Chaotic Is Genome Chaos? James A. Shapiro Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL 60637, USA; [email protected] Simple Summary: Cancer genomes can undergo major restructurings involving many chromosomal locations at key stages in tumor development. This restructuring process has been designated “genome chaos” by some authors. In order to examine how chaotic cancer genome restructuring may be, the cell and molecular processes for DNA restructuring are reviewed. Examination of the action of these processes in various cancers reveals a degree of specificity that indicates genome restructuring may be sufficiently reproducible to enable possible therapies that interrupt tumor progression to more lethal forms. Abstract: Cancer genomes evolve in a punctuated manner during tumor evolution. Abrupt genome restructuring at key steps in this evolution has been called “genome chaos.” To answer whether widespread genome change is truly chaotic, this review (i) summarizes the limited number of cell and molecular systems that execute genome restructuring, (ii) describes the characteristic signatures of DNA changes that result from activity of those systems, and (iii) examines two cases where genome restructuring is determined to a significant degree by cell type or viral infection. The conclusion is that many restructured cancer genomes display sufficiently unchaotic signatures to identify the cellular systems responsible for major oncogenic transitions, thereby identifying possible targets for therapies to inhibit tumor progression to greater aggressiveness. Keywords: DNA break repair; alternative end-joining (alt-EJ); chromothripsis; chromoplexy; chro- Citation: Shapiro, J.A. How Chaotic moanasynthesis; retrotransposition; target-primed reverse transcription (TPRT); immunoglobulin Is Genome Chaos? Cancers 2021, 13, VDJ joining; class switch recombination (CSR); human papillomavirus (HPV) 1358.
  • On the Role of Chromosomal Rearrangements in Evolution

    On the Role of Chromosomal Rearrangements in Evolution

    On the role of chromosomal rearrangements in evolution: Reconstruction of genome reshuffling in rodents and analysis of Robertsonian fusions in a house mouse chromosomal polymorphism zone by Laia Capilla Pérez A thesis submitted for the degree of Doctor of Philosophy in Animal Biology Supervisors: Dra. Aurora Ruiz-Herrera Moreno and Dr. Jacint Ventura Queija Institut de Biotecnologia i Biomedicina (IBB) Departament de Biologia Cel·lular, Fisiologia i Immunologia Departament de Biologia Animal, Biologia Vegetal i Ecologia Universitat Autònoma de Barcelona Supervisor Supervisor PhD candidate Aurora Ruiz-Herrera Moreno Jacint Ventura Queija Laia Capilla Pérez Bellaterra, 2015 A la mare Al pare Al mano “Visto a la luz de la evolución, la biología es, quizás, la ciencia más satisfactoria e inspiradora. Sin esa luz, se convierte en un montón de hechos varios, algunos de ellos interesantes o curiosos, pero sin formar ninguna visión conjunta.” Theodosius Dobzhansky “La evolución es tan creativa. Por eso tenemos jirafas.” Kurt Vonnegut This thesis was supported by grants from: • Ministerio de Economía y Competitividad (CGL2010-15243 and CGL2010- 20170). • Generalitat de Catalunya, GRQ 1057. • Ministerio de Economía y Competitividad. Beca de Formación de Personal Investigador (FPI) (BES-2011-047722). • Ministerio de Economía y Competitividad. Beca para la realización de estancias breves (EEBB-2011-07350). Covers designed by cintamontserrat.blogspot.com INDEX Abstract 15-17 Acronyms 19-20 1. GENERAL INTRODUCTION 21-60 1.1 Chromosomal rearrangements
  • The Biocyc Collection of Microbial Genomes and Metabolic Pathways Peter D

    The Biocyc Collection of Microbial Genomes and Metabolic Pathways Peter D

    Briefings in Bioinformatics, 2017, 1–9 doi: 10.1093/bib/bbx085 Paper Downloaded from https://academic.oup.com/bib/advance-article-abstract/doi/10.1093/bib/bbx085/4084231 by guest on 02 May 2019 The BioCyc collection of microbial genomes and metabolic pathways Peter D. Karp, Richard Billington, Ron Caspi, Carol A. Fulcher, Mario Latendresse, Anamika Kothari, Ingrid M. Keseler, Markus Krummenacker, Peter E. Midford, Quang Ong, Wai Kit Ong, Suzanne M. Paley and Pallavi Subhraveti Corresponding author: Peter D. Karp, Bioinformatics Research Group, SRI International, 333 Ravenswood Ave, AE206, Menlo Park, CA 94025, USA. E-mail: [email protected] Abstract BioCyc.org is a microbial genome Web portal that combines thousands of genomes with additional information inferred by computer programs, imported from other databases and curated from the biomedical literature by biologist curators. BioCyc also provides an extensive range of query tools, visualization services and analysis software. Recent advances in BioCyc in- clude an expansion in the content of BioCyc in terms of both the number of genomes and the types of information available for each genome; an expansion in the amount of curated content within BioCyc; and new developments in the BioCyc soft- ware tools including redesigned gene/protein pages and metabolite pages; new search tools; a new sequence-alignment tool; a new tool for visualizing groups of related metabolic pathways; and a facility called SmartTables, which enables biolo- gists to perform analyses that previously would have required a programmer’s assistance. Key words: genome databases; microbial genome databases; metabolic pathway databases Peter Karp is the Director of the SRI Bioinformatics Research Group (BRG).
  • Biological Capacities Clearly Define a Major Subdivision in Domain Bacteria 4 5 Raphaël Méheust+,1,2, David Burstein+,1,3,8, Cindy J

    Biological Capacities Clearly Define a Major Subdivision in Domain Bacteria 4 5 Raphaël Méheust+,1,2, David Burstein+,1,3,8, Cindy J

    bioRxiv preprint doi: https://doi.org/10.1101/335083; this version posted May 30, 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. 1 Research article 2 3 Biological capacities clearly define a major subdivision in Domain Bacteria 4 5 Raphaël Méheust+,1,2, David Burstein+,1,3,8, Cindy J. Castelle1,2,4 and Jillian F. Banfield1,2,4,5,6,7,*,# 6 7 1Department of Earth and Planetary Science, University of California, Berkeley, Berkeley, CA, USA 8 2Innovative Genomics Institute, Berkeley, CA, USA 9 3 California Institute for Quantitative Biosciences (QB3), University of California Berkeley, CA USA 10 4Chan Zuckerberg Biohub, San Francisco, CA, USA 11 5University of Melbourne, Melbourne, VIC, Australia 12 6Lawrence Berkeley National Laboratory, Berkeley, CA, USA 13 7Department of Environmental Science, Policy and Management, University of California, Berkeley, 14 Berkeley, CA, USA 15 8Present address: School of Molecular and Cell Biology and Biotechnology, George S. Wise Faculty of 16 Life Sciences, Tel Aviv University, Tel Aviv, Israel 17 +These authors contributed equally to this work 18 *Correspondence: [email protected] 19 #Lead Contact 20 21 Resume 22 Phylogenetic analyses separate candidate phyla radiation (CPR) bacteria from other bacteria, but 23 the degree to which their proteomes are distinct remains unclear. Here, we leveraged a proteome 24 database that includes sequences from thousands of uncultivated organisms to identify protein 25 families and examine their organismal distributions. We focused on widely distributed protein 26 families that co-occur in genomes, as they likely foundational for metabolism.
  • Hundreds of Novel Composite Genes and Chimeric Genes with Bacterial

    Hundreds of Novel Composite Genes and Chimeric Genes with Bacterial

    Hundreds of novel composite genes and chimeric genes with bacterial origins contributed to haloarchaeal evolution Raphaël Méheust, Andrew Watson, Francois-Joseph Lapointe, R. Thane Papke, Philippe Lopez, Eric Bapteste To cite this version: Raphaël Méheust, Andrew Watson, Francois-Joseph Lapointe, R. Thane Papke, Philippe Lopez, et al.. Hundreds of novel composite genes and chimeric genes with bacterial origins contributed to haloarchaeal evolution. Genome Biology, BioMed Central, 2018, 19, pp.75. 10.1186/s13059-018- 1454-9. hal-01830047 HAL Id: hal-01830047 https://hal.sorbonne-universite.fr/hal-01830047 Submitted on 4 Jul 2018 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. Distributed under a Creative Commons Attribution| 4.0 International License Méheust et al. Genome Biology (2018) 19:75 https://doi.org/10.1186/s13059-018-1454-9 RESEARCH Open Access Hundreds of novel composite genes and chimeric genes with bacterial origins contributed to haloarchaeal evolution Raphaël Méheust1, Andrew K. Watson1, François-Joseph Lapointe3, R. Thane Papke2, Philippe Lopez1 and Eric Bapteste1* Abstract Background: Haloarchaea, a major group of archaea, are able to metabolize sugars and to live in oxygenated salty environments. Their physiology and lifestyle strongly contrast with that of their archaeal ancestors.
  • Psortm: a Bacterial and Archaeal Protein Subcellular Localization Prediction Tool for Metagenomics Data Michael A

    Psortm: a Bacterial and Archaeal Protein Subcellular Localization Prediction Tool for Metagenomics Data Michael A

    Bioinformatics, 36(10), 2020, 3043–3048 doi: 10.1093/bioinformatics/btaa136 Advance Access Publication Date: 28 February 2020 Original Paper Sequence analysis PSORTm: a bacterial and archaeal protein subcellular localization prediction tool for metagenomics data Michael A. Peabody1,†, Wing Yin Venus Lau1,†, Gemma R. Hoad1,2, Baofeng Jia1, Finlay Maguire3, Kristen L. Gray1, Robert G. Beiko3 and Fiona S. L. Brinkman1,* 1Department of Molecular Biology and Biochemistry, 2Research Computing Group, Simon Fraser University, Burnaby, BC V5A 1S6, Canada and 3Department of Computer Science, Dalhousie University, Halifax, NS B3H 4R2, Canada *To whom correspondence should be addressed. †The authors wish it to be known that these authors contributed equally. Associate Editor: Yann Ponty Received on July 3, 2019; revised on January 23, 2020; editorial decision on February 19, 2020; accepted on February 25, 2020 Abstract Motivation: Many methods for microbial protein subcellular localization (SCL) prediction exist; however, none is readily available for analysis of metagenomic sequence data, despite growing interest from researchers studying microbial communities in humans, agri-food relevant organisms and in other environments (e.g. for identification of cell-surface biomarkers for rapid protein-based diagnostic tests). We wished to also identify new markers of water quality from freshwater samples collected from pristine versus pollution-impacted watersheds. Results: We report PSORTm, the first bioinformatics tool designed for prediction of diverse bacterial and archaeal protein SCL from metagenomics data. PSORTm incorporates components of PSORTb, one of the most precise and widely used protein SCL predictors, with an automated classification by cell envelope. An evaluation using 5-fold cross-validation with in silico-fragmented sequences with known localization showed that PSORTm maintains PSORTb’s high precision, while sensitivity increases proportionately with metagenomic sequence fragment length.
  • Role of ECDYSONELESS in ERBB2/HER2 Mediated Breast Oncogenesis

    Role of ECDYSONELESS in ERBB2/HER2 Mediated Breast Oncogenesis

    University of Nebraska Medical Center DigitalCommons@UNMC Theses & Dissertations Graduate Studies Spring 5-7-2016 Role of ECDYSONELESS in ERBB2/HER2 Mediated Breast Oncogenesis Shalis A. Ammons University of Nebraska Medical Center Follow this and additional works at: https://digitalcommons.unmc.edu/etd Part of the Biology Commons, and the Cancer Biology Commons Recommended Citation Ammons, Shalis A., "Role of ECDYSONELESS in ERBB2/HER2 Mediated Breast Oncogenesis" (2016). Theses & Dissertations. 107. https://digitalcommons.unmc.edu/etd/107 This Dissertation is brought to you for free and open access by the Graduate Studies at DigitalCommons@UNMC. It has been accepted for inclusion in Theses & Dissertations by an authorized administrator of DigitalCommons@UNMC. For more information, please contact [email protected]. ROLE OF ECDYSONELESS IN ERBB2/HER2 MEDIATED BREAST ONCOGENESIS By Shalis Ammons A DISSERTATION Presented to the Faculty of the University of Nebraska Graduate College in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Genetics, Cell Biology & Anatomy Graduate Program Under the supervision of Professor Vimla Band University of Nebraska Medical Center Omaha, Nebraska April, 2016 Supervisory Committee: Karen Gould, Ph.D Kay-Uwe Wagner, Ph.D Hamid Band, Ph.D Kaustubh Datta, Ph.D ROLE OF ECDYSONELESS IN ERBB2/HER2 MEDIATED BREAST ONCOGENESIS By Shalis Ammons University of Nebraska Medical Center, 2016 Advisor: Vimla Band, PhD Breast cancer is the second leading cause of cancer related deaths in women in the United States. The human Epidermal Growth Factor 2 (ErbB2) gene amplification and/or receptor overexpression subtype of breast cancer accounts for 25% of all breast cancers.
  • Genes of Innate Immunity and Their Significance in Evolutionary Ecology of Free Livings Rodents Alena Fornuskova

    Genes of Innate Immunity and Their Significance in Evolutionary Ecology of Free Livings Rodents Alena Fornuskova

    Genes of innate immunity and their significance in evolutionary ecology of free livings rodents Alena Fornuskova To cite this version: Alena Fornuskova. Genes of innate immunity and their significance in evolutionary ecology of free livings rodents. Populations and Evolution [q-bio.PE]. Université Montpellier II - Sciences et Tech- niques du Languedoc; Masarykova univerzita (Brno, République tchèque), 2013. English. NNT : 2013MON20103. tel-01021258 HAL Id: tel-01021258 https://tel.archives-ouvertes.fr/tel-01021258 Submitted on 9 Jul 2014 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. UNIVERSITE•MONTPELLIER•II•• SCIENCES•ET•TECHNIQUES•DU•LANGUEDOC•• FACULTE•DES•SCIENCES• • and• • MASARYK•UNIVERSITY,•BRNO• FACULTY•OF•SCIENCE• • THESIS•• • To•obtain•doctoral•degree• • Formation•doctorale :•Biologie•de•l'évolution•et•écologie• • Ecole•Doctorale :•Systèmes•Intégrés•en•Biologie,•Agronomie,•Géosciences,•Hydrosciences, • Environnement,•SIBAGHE• • • Presented•and•defended•publicly• • AUTHOR:•Alena•Fornuskova• • • GENES•OF•INNATE•IMMUNITY•AND•THEIR•SIGNIFICANCE•IN•
  • GLP1/GLP1 Receptors

    GLP1/GLP1 Receptors

    J-L HWANG and others Evolution of GLP1 and GLP1 52:3 T15–T27 Thematic Review receptor MOLECULAR EVOLUTION OF GPCRS GLP1/GLP1 receptors Correspondence Jong-Ik Hwang, Seongsik Yun, Mi Jin Moon, Cho Rong Park and Jae Young Seong should be addressed to J Y Seong Graduate School of Medicine, Korea University, Seoul 136-705, Republic of Korea Email [email protected] Abstract Glucagon-like peptide 1 (GLP1) is an intestinal incretin that regulates glucose homeostasis Key Words through stimulation of insulin secretion from pancreatic b-cells and inhibits appetite by " evolution acting on the brain. Thus, it is a promising therapeutic agent for the treatment of type 2 " exon diabetes mellitus and obesity. Studies using synteny and reconstructed ancestral " GLP1 chromosomes suggest that families for GLP1 and its receptor (GLP1R) have emerged through " GLP1R two rounds (2R) of whole genome duplication and local gene duplications before and after " G protein-coupled receptor 2R. Exon duplications have also contributed to the expansion of the peptide family " genome members. Specific changes in the amino acid sequence following exon/gene/genome " gene duplications have established distinct yet related peptide and receptor families. These " duplication specific changes also confer selective interactions between GLP1 and GLP1R. In this review, we present a possible macro (genome level)- and micro (gene/exon level)-evolution mechanisms of GLP1 and GLP1R, which allows them to acquire selective interactions between this ligand–receptor pair. This information may provide critical insight for the Journal of Molecular development of potent therapeutic agents targeting GLP1R. Endocrinology Journal of Molecular Endocrinology (2014) 52, T15–T27 Introduction Glucagon-like peptide 1 (GLP1) is a gastrointestinal 1990).
  • Pathway Tools Version 24.0: Integrated Software for Pathway/Genome Informatics and Systems Biology

    Pathway Tools Version 24.0: Integrated Software for Pathway/Genome Informatics and Systems Biology

    Pathway Tools version 24.0: Integrated Software for Pathway/Genome Informatics and Systems Biology Peter D. Karp∗, Suzanne M. Paley, Peter E. Midford, Markus Krummenacker, Richard Billington, Anamika Kothari, Wai Kit Ong, Pallavi Subhraveti, Ingrid M. Keseler, and Ron Caspi Bioinformatics Research Group, SRI International 333 Ravenswood Ave, Menlo Park, CA 94025 [email protected] ∗To whom correspondence should be addressed. arXiv:1510.03964v4 [q-bio.GN] 12 Nov 2020 1 Abstract Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence align- ments, a genome-variant analyzer, and comparative-genomics operations. It offers metabolic- informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, pre- diction of reaction atom mappings, and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of reg- ulatory interactions. The software creates and manages a type of organism-specific database called a Pathway/Genome Database (PGDB), which the software enables database curators to interactively edit. It supports web publishing of PGDBs and provides a large number of query, visualization, and omics-data analysis tools. Scientists around the world have created more than 35,000 PGDBs by using Pathway Tools, many of which are curated databases for important model organisms. Those PGDBs can be exchanged using a peer-to-peer database- sharing system called the PGDB Registry. Biographical Note Dr. Peter Karp is the Director of the Bioinformatics Research Group at SRI International. He received the PhD degree in Computer Science from Stanford University.