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A Novel Gene Overexpression Plasmid Library and Its Application in Mapping Genetic Networks by Systematic Dosage Suppression

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A Novel Gene Overexpression Plasmid Library and Its Application in Mapping Genetic Networks by Systematic Dosage Suppression A Novel Gene Overexpression Plasmid Library and its application in Mapping Genetic Networks by Systematic Dosage Suppression by Leslie Joyce Magtanong A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of Molecular Genetics University of Toronto © Copyright by Leslie Joyce Magtanong 2011 A Novel Gene Overexpression Plasmid Library and its application in Mapping Genetic Networks by Systematic Dosage Suppression Leslie Joyce Magtanong Doctor of Philosophy Department of Molecular Genetics University of Toronto 2011 Abstract Increasing gene dosage provides a powerful means of probing gene function, as it tends to cause a gain-of-function effect due to increased gene activity. In the budding yeast, Saccharomyces cerevisiae, systematic gene overexpression studies have shown that in wild-type cells, overexpression of a small subset of genes results in an overt phenotype. However, examining the effects of gene overexpression in sensitized cells containing mutations in known genes is a powerful means for identifying functionally relevant genetic interactions. When a query mutant phenotype is rescued by gene overexpression, the genetic interaction is termed dosage suppression. I comprehensively investigated dosage suppression genetic interactions in yeast using three approaches. First, using one of two novel plasmid libraries cloned by two colleagues and myself, I systematically performed dosage suppression screens and identified over 130 novel dosage suppression genetic interactions for more than 25 essential yeast genes. The plasmid libraries, called the molecular barcoded yeast ORF (MoBY-ORF) 1.0 and 2.0, are designed to streamline dosage analysis by being compatible with high-throughput genomics technologies that can monitor plasmid representation, including barcode microarrays and next-generation sequencing methods. Second, I describe a detailed analysis of the novel dosage suppression interactions, as well as of literature-curated interactions, and show that the gene pairs exhibiting dosage suppression are often functionally related and can overlap with physical as well as negative genetic interactions. Third, I performed a systematic categorization of dosage suppression genetic ii interactions in yeast and show that the majority of the dosage suppression interactions can be assigned to one of four general mechanistic classifications. With this comprehensive analysis, I conclude that systematically identifying dosage suppression genetic interactions will allow for their integration into other genetic and physical interaction networks and should provide new insight into the global wiring diagram of the cell. iii Acknowledgments I have many people to thank for all of their support and encouragement throughout the years. First and foremost, I would like to thank my parents, Vic and Anita, my sisters, Lisa and Jill, and my husband, Scott Dixon, for their unconditional support during my time in Toronto. I also want to thank the professors, postdocs, and students who have provided valuable feedback and suggestions for my various experiments, presentations, and manuscripts. In particular, I acknowledge and am grateful to my supervisory committee, Drs. Brenda Andrews, Barbara Funnell, and Howard Lipshitz, who have been incredibly supportive of my research and abilities as a doctoral student. I thank the fellow graduate students who have contributed to my research. In particular, I thank Cheuk Hei Ho, who spearheaded the development of the MoBY-ORF plasmid libraries and gave me many helpful suggestions throughout my research; a postdoc, Sarah Barker, and the various technicians and summer students, all of whom were integral to the development of the MoBY-ORF plasmid libraries; Wei Jiao and Anastasia Baryshnikova, who did invaluable computational work for this project; and Sondra Bahr, a talented technician who made a significant contribution to the dosage suppression studies. Finally, I would like to thank my supervisor, Dr. Charlie Boone, whose intelligence and support for me will always be remembered. This work would not have been possible without assistance provided by members of the scientific community. In particular, I thank Andrew Smith, and Drs. Larry Heisler, Marinella Gibella, and Corey Nislow, who provided access to and assistance with their microarray facilities. I also thank the Natural Sciences and Engineering Research Council (NSERC), the Canadian Institutes of Health Research (CIHR), and the University of Toronto for financial support. iv Table of Contents Page Abstract ii Acknowledgments iv List of Tables ix List of Figures x List of Appendices xi List of Electronic Tables xii Chapter One: Introduction 1 1.1 General Introduction 2 1.2 Genetic Interactions 2 1.2.1 Negative Genetic Interactions 4 1.2.1.1 Complex Haploinsufficiency 4 1.2.2 Positive Genetic Interactions 5 1.2.3 Synthetic Dosage Effects: Lethality and Suppression 7 1.3 Investigating Genetic Interactions in S. cerevisiae in a Systematic 7 Manner 1.3.1 Development of Genome-wide Strain Collections 8 1.3.1.1 Loss-of-Function Strains: The Deletion Strain Collection 8 1.3.1.1.1 Barcoded strains and barcode microarrays 8 1.3.1.2 Essential Gene Strain Collections 13 1.3.1.2.1 tetO promoter collection 13 1.3.1.2.2 URA3-marked temperature-sensitive allele collection 15 1.3.1.2.3 DAmP allele collection 15 1.3.2 Gene overexpression 16 1.3.2.1 The Yeast Two-Hybrid S. cerevisiae ORF Array 17 1.3.2.2 The PCUP1-GST Library 21 1.3.2.3 The PGAL1/10-GST Library 21 1.3.2.4 The Movable ORF Library 22 1.3.2.5 The FLEXGene ORF Collection 23 1.3.2.6 The Yeast Genome Tiling Collection 23 v 1.3.2.7 Summary and Comparison of Various Existing Overexpression 24 Libraries 1.4 Systematic Identification of Genetic Interactions in Yeast 25 1.4.1 Synthetic Genetic Array (SGA) Analysis 25 1.4.1.1 Application of SGA to SDL analysis 27 1.4.1.2 Application of SGA to genetic mapping 27 1.4.1.3 Application of SGA to array-based high-content screening 27 1.4.2 Diploid-based Synthetic Lethal Analysis on Microarrays (dSLAM) 29 1.4.3 Genetic Interaction Mapping (GIM) 30 1.4.4 Summary of Genetic Interaction Mapping Strategies 30 1.5 Next-Generation Sequencing 31 1.6 Summary and Rationale 32 Chapter Two: The MoBY-ORF 1.0 Yeast Plasmid Library 34 2.1 Introduction 35 2.2 Results 35 2.2.1 Construction of a library of molecular barcoded yeast ORFs 35 2.2.2 Verification of constructed clones by sequencing 36 2.2.3 Assessment of clone function using temperature-sensitive mutants 39 2.2.4 Complementation cloning to identify drug-resistant mutants and 39 compound mode-of-action 2.3 Summary 39 2.4 Methods 40 2.4.1 Yeast Strains 40 2.4.2 Growth Media 40 2.4.3 Clone Construction and Analysis 40 2.4.4 Sequence Confirmation of the MoBY-ORF Collection Barcodes and 42 3’ ORF Junctions 2.4.5 Functional Complementation of Essential Genes 42 vi Chapter Three: Mapping Genetic Networks by Systematic Dosage 43 Suppression 3.1 Introduction 44 3.2 Results 46 3.2.1 Construction of the MoBY-ORF 2.0 plasmid library 46 3.2.2. Dosage suppression analysis of temperature-sensitive conditional 46 mutants Methods used to identify dosage suppressors 46 Description of results 53 3.2.3 An integrated dosage suppression genetic interaction network 57 Network overview 58 Identification of a genetic link between PKA signaling and the 58 kinetochore 3.2.4 Distribution of dosage suppressors across cellular processes 61 3.2.5. Overlap of dosage suppression interactions with protein-protein and 64 negative genetic network edges 3.2.6 Mechanistic categorization of dosage suppression interactions 64 Dosage suppression decision tree for categorizing dosage 64 suppression interactions Description of categories 64 3.3 Discussion 73 3.4 Methods 76 3.4.1 Growth media 76 3.4.2 Clone construction and analysis 76 3.4.3 Plasmid pool preparation 77 3.4.4 Cloning of dosage suppressors with the 2µ MoBY-ORF library 77 3.4.5 Yeast barcode microarray hybridization and data analysis 80 3.4.6 Empirical determination of raw barcode microarray intensity cutoff 80 for identification of candidate dosage suppressors 3.4.7 Assessing fitness of barcoded yeast strains by Illumina/Solexa 81 sequencing vii 3.4.8 Confirmation of candidate dosage suppressors and test for reciprocal 82 suppression 3.4.9 Overlap of dosage suppression genetic interactions with other types of 83 interactions 3.4.10 Analysis of functional relatedness 83 3.4.11 Identifying gene clusters in the integrated dosage suppression network 83 Chapter Four: Conclusions and Future Directions 84 4.1 General Overview 85 4.2 The MoBY-ORF gene overexpression libraries: present and future 85 applications 4.3 Dosage suppression genetic interaction networks: illuminating a new 88 facet of genetics 4.4 Understanding the mechanistic basis of dosage suppression 90 4.5 Concluding thoughts 92 Chapter Five: References 94 Chapter Six: Appendices 112 viii List of Tables Page 1.1 Overview of existing essential gene strain collections for S. cerevisiae 14 1.2 Overview of gene overexpression plasmid libraries for S. cerevisiae 18 3.2.1 Overlap of dosage suppression interactions with other types of 65 interactions 3.2.2 Distribution of dosage suppression gene pairs annotated in the 66 Saccharomyces Genome Database 3.2.3 Gene pairs tested for reciprocal suppression 71 3.2.4 Yeast strains used in this study 78 ix List of Figures Page 1.1 The barcoded kanMX cassette of the S. cerevisiae deletion collection 9 1.2 Barcode microarray method in yeast 11 1.3 Plasmid libraries in S. cerevisiae 19 2.2.1 Plasmid map of p5472 37 2.2.2 Construction of the MoBY-ORF library by homologous 38 recombination in yeast 3.2.1 Schematic of a plasmid in the MoBY-ORF 2.0 plasmid library 47 3.2.2 Plasmid map of p5476 48 3.2.3 MAGIC with the MoBY-ORF 1.0 plasmid library 49 3.2.4 Using the MoBY-ORF 2.0 library to identify candidate dosage 51 suppressors by barcode microarray 3.2.5 Empirical determination of raw barcode microarray intensity cutoff 54 for identification of candidate dosage suppressors 3.2.6 Dosage suppression genetic interaction network for S.
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