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SFU Thesis Template Files Enabling systems-level analyses of the host response to infectious diseases in bovine and other mammalian species by Amir Bahram Khosravizadeh Foroushani M.Sc. (Computer Science), University of Texas at Dallas, 2009 Diplom Informatik, University of Tuebingen, 2003 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 Amir Bahram Khosravizadeh Foroushani 2014 SIMON FRASER UNIVERSITY Summer 2014 Approval Name: Amir Bahram Khosravizadeh Foroushani Degree: Doctor of Philosophy Title of Thesis: Enabling systems-level analyses of the host response to infectious diseases in bovine and other mammalian species Examining Committee: Chair: Dr. Mark A. Brockman Associate Professor, Faculty of Health Sciences // Dept of Molecular Biology and Biochemistry Dr. Fiona S.L. Brinkman Senior Supervisor Professor, Department of Molecular Biology and Biochemistry Dr. David J. Lynn Supervisor Group leader, Computational Biology, AGRIC,Teagasc, Ireland By video conference (Adelaide, Australia) Dr. Jack Chen Supervisor Professor, Department of Molecular Biology and Biochemistry Dr. Willie Davidson Supervisor Professor, Department of Molecular Biology and Biochemistry Dr. Lisa Craig Internal Examiner Associate Professor, Department of Molecular Biology and Biochemistry Dr. Paul Pavlidis External Examiner Associate Professor, Psychiatry University of British Columbia Date Defended/Approved: September 29, 2014 ii Partial Copyright Licence iii Abstract The innate immune response is a critical branch of immunity, providing a first line of defense against pathogens and shaping subsequent adaptive immune responses. The complexity of this system necessitates the application of systems-level approaches. InnateDB is an integrated web-accessible database and systems biology platform being developed to facilitate the systems level analysis of innate immunity pathways and networks. One of the aims of this thesis was to enhance InnateDB with bovine data, thereby providing a resource for investigation of this agriculturally important model organism. Using an orthology based approach, over 70% of InnateDB’s human protein- protein interactions (PPIs), and a similar fraction of human pathways were reconstructed in cow and integrated into InnateDB. Pathway analysis, the statistical association of observations at the molecular level with processes at a more systems level, plays a crucial role in the interpretation of high- throughput experimental datasets. A widely neglected challenge in pathway analysis relates to the handling of multifunctional genes. I therefore developed SIGORA, a novel pathway analysis method that identifies genes and gene-pairs that are unique signatures of a pathway and examines their over-representation in a given list of genes of interest (e.g. the list of differentially expressed genes in an infectious condition). With several biological datasets, SIGORA outperformed traditional methods, delivering biologically more plausible and relevant results. This was also reflected in significantly lower false positive rates for simulated datasets. An additional challenge in high-throughput dataset interpretation concerns the lack of functional annotation for many genes. The guilt by association (GBA) principle was applied in a conservative manner to a large tissue expression dataset (105 Tissues, 13000 genes) to infer gene functions from co-expression data. Overall, 180 previously un-annotated bovine genes were assigned a putative function by this approach. In 20% of the cases, the inferred function was additionally supported by literature in other species. iv microRNAs are emerging as important innate immune response regulators and as biomarkers of disease. Determining microRNA functions requires the identification of their targets, yet computational prediction of such targets is challenging. As part of a group investigating microRNA roles in bovine mastitis, I used a combination of prediction tools to compile a list of likely targets. Here, the overall emerging picture (including pathway enrichment) is consistent with our current understanding of this condition. Collectively this work provides new tools and insights that may more broadly be used to improve systems-based analysis of bovine and other mammalian responses. Keywords: Computational Biology; Bioinformatics; innate immunity; bovine infectious diseases; pathway analysis; miRNAs. v Dedication To Ebrahim, Fatemeh and Zaneta vi Acknowledgements I am very thankful for the invaluable guidance and contribution of my supervisory committee; Dr. Fiona Brinkman, Dr. David Lynn, Dr. Willie Davidson and Dr. Jack Chen. I would like to acknowledge all project collaborators at Teagasc, SFU, UBC and TCD, in particular Nathan Lawless, Peter Vegh, Karin Breuer, Matthew Laird, Geoffrey Winsor, Matthew Whiteside, Raymond Lo, Anastasia Sribnaia, Carol Chen as well as Dr. Bob Hancock, Dr. Cliona O'Farrelly and Dr. Mathew McCabe. I would also like to acknowledge Lakshmi Matukumalli and other members of the Bovine Gene Atlas project for providing the bovine tissue expression data. This work has been generously supported by a four year Walsh Fellowship Scheme from Teagasc and a Special Graduate Entrance Scholarship (SGES) from SFU. vii Table of Contents Approval .......................................................................................................................... ii Partial Copyright Licence ............................................................................................... iii Abstract .......................................................................................................................... iv Dedication ...................................................................................................................... vi Acknowledgements ....................................................................................................... vii Table of Contents .......................................................................................................... viii List of Tables ................................................................................................................. xiii List of Figures................................................................................................................xiv List of Acronyms ............................................................................................................xvi Glossary ...................................................................................................................... xviii Preface or Executive Summary or Introductory Image ...................................................xxi Chapter 1. Introduction ............................................................................................... 1 1.1. Burden of infectious disease ................................................................................... 1 1.2. The importance of infectious disease in cattle ........................................................ 2 1.2.1. Zoonotic diseases and emerging diseases .................................................. 2 1.2.2. Animal infectious diseases in a changing world ........................................... 4 1.3. The immune system ............................................................................................... 5 1.3.1. The innate immune system ......................................................................... 6 1.3.2. A glance at the complexity of the innate immune response ......................... 8 1.4. Systems level approaches and immunology ......................................................... 12 1.4.1. Types of systems studies .......................................................................... 13 Experimental systems immunology ........................................................... 14 Modeling & simulation based systems immunology .................................. 15 Quantitative models........................................................................................... 15 Box1: Modeling and simulation ................................................................. 15 Qualitative and rule based models .................................................................... 16 Box2: Networks and network analysis ....................................................... 18 A) Descriptive power of network representation ............................................. 18 B) Network analysis ......................................................................................... 18 1.4.2. Integrative systems biology ....................................................................... 19 1.5. Pathways, pathway databases and pathway analysis ........................................... 21 1.6. miRNAs as novel regulators of innate immunity .................................................... 23 1.6.1. Biogenesis ................................................................................................ 23 1.6.2. Function and relevance to innate immunity ............................................... 24 1.6.3. Computational prediction of miRNA targets ............................................... 27 Phylogenetic conservation: ....................................................................... 27 Genomic context: ...................................................................................... 28 Thermodynamic stability: .........................................................................
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