ingest cdrApp 2018-06-13T15:38:07.014Z 51cd2fe2-3fd7-401f-a923-a97bc3db68a2 modifyDatastreamByValue RELS-EXT fedoraAdmin 2018-06-13T16:04:55.559Z Setting exclusive relation addDatastream MD_TECHNICAL fedoraAdmin 2018-06-13T16:05:06.826Z Adding technical metadata derived by FITS addDatastream MD_FULL_TEXT fedoraAdmin 2018-06-13T16:05:34.497Z Adding full text metadata extracted by Apache Tika modifyDatastreamByValue RELS-EXT fedoraAdmin 2018-06-13T16:05:57.544Z Setting exclusive relation modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-07-16T21:09:56.905Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-07-18T16:44:12.479Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-08-22T15:25:03.974Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-09-28T18:14:01.086Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-10-12T17:04:13.846Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2019-03-22T20:24:40.414Z Paul Maurizio Author Curriculum in Bioinformatics and Computational Biology School of Medicine MODELING THE HOST GENETIC DETERMINANTS OF INFLUENZA VIRUS PATHOGENESIS IN MICE The persistent threat of infection has contributed to variation in mortality and survival, shaping mammalian genomes throughout history. Genetic variation that now exists controls infection outcomes, although the specific genes and variants are not well known. Common methods for genome-wide mapping often assume predominantly additive genetic action, for reasons of power and simplicity. However, non-additive effects may arise from mutations in critical pathways, such as those that regulate the host resistance to influenza A virus. Notably, complex, non-additive genetic architecture is difficult to characterize in human studies, and certain effects may remain elusive except in model organisms, such as mice. Thus, the identification of novel non-additive genetic effects in host-pathogen interactions is an area of open research, and this dissertation focuses specifically on understanding the role of dominance, parent-of-origin, and additive genetic variation the host control of influenza infection. In this research, I use experimental crosses of inbred strains of mice, both standard and recombinant inbreds, to introduce genetic diversity and increase levels of heterozygosity. Using replicable, genetically diverse populations, I model and characterize genetic variation that controls the host pathogenic response to influenza. In Chapter 1, I provide a basic introduction for influenza virus, diallels, and reciprocal cross breeding designs for genetic studies, and I review systems and statistical genetics analysis with recombinant inbred strains known as the Collaborative Cross. In Chapter 2, I describe the genetic architecture of the host response to influenza in a diallel, and the dissection of Mx1 subspecies-specific dominance. In Chapter 3, I describe novel parent-of-origin effects on pathology and on gene regulation in the response to influenza in F1 reciprocal cross mice. Chapter 4 covers the discovery of a novel genomic locus that controls pathology of influenza infection in the lung, via quantitative trait locus mapping in Collaborative Cross F1 mice. I conclude in Chapter 5 with a recap and future directions. In summary, this work provides a path forward for interrogating and understanding the complex genetic architecture of genome-wide contributions to host pathology following influenza infection, using quantitative, statistical, and systems approaches in inbred and hybrid mice. Spring 2018 2018 Genetics Virology Bioinformatics Bayesian mixed model, Collaborative Cross, diallel, multiple imputation, parent-of-origin, treatment response eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Bioinformatics and Computational Biology Mark Heise Thesis advisor William Valdar Thesis advisor Terrence Furey Thesis advisor Fernando Pardo-Manuel de Villena Thesis advisor Ralph Baric Thesis advisor Jeremy Purvis Thesis advisor text Paul Maurizio Author Curriculum in Bioinformatics and Computational Biology School of Medicine MODELING THE HOST GENETIC DETERMINANTS OF INFLUENZA VIRUS PATHOGENESIS IN MICE The persistent threat of infection has contributed to variation in mortality and survival, shaping mammalian genomes throughout history. Genetic variation that now exists controls infection outcomes, although the specific genes and variants are not well known. Common methods for genome-wide mapping often assume predominantly additive genetic action, for reasons of power and simplicity. However, non-additive effects may arise from mutations in critical pathways, such as those that regulate the host resistance to influenza A virus. Notably, complex, non-additive genetic architecture is difficult to characterize in human studies, and certain effects may remain elusive except in model organisms, such as mice. Thus, the identification of novel non-additive genetic effects in host-pathogen interactions is an area of open research, and this dissertation focuses specifically on understanding the role of dominance, parent-of-origin, and additive genetic variation the host control of influenza infection. In this research, I use experimental crosses of inbred strains of mice, both standard and recombinant inbreds, to introduce genetic diversity and increase levels of heterozygosity. Using replicable, genetically diverse populations, I model and characterize genetic variation that controls the host pathogenic response to influenza. In Chapter 1, I provide a basic introduction for influenza virus, diallels, and reciprocal cross breeding designs for genetic studies, and I review systems and statistical genetics analysis with recombinant inbred strains known as the Collaborative Cross. In Chapter 2, I describe the genetic architecture of the host response to influenza in a diallel, and the dissection of Mx1 subspecies-specific dominance. In Chapter 3, I describe novel parent-of-origin effects on pathology and on gene regulation in the response to influenza in F1 reciprocal cross mice. Chapter 4 covers the discovery of a novel genomic locus that controls pathology of influenza infection in the lung, via quantitative trait locus mapping in Collaborative Cross F1 mice. I conclude in Chapter 5 with a recap and future directions. In summary, this work provides a path forward for interrogating and understanding the complex genetic architecture of genome-wide contributions to host pathology following influenza infection, using quantitative, statistical, and systems approaches in inbred and hybrid mice. Spring 2018 2018 Genetics Virology Bioinformatics Bayesian mixed model, Collaborative Cross, diallel, multiple imputation, parent-of-origin, treatment response eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Bioinformatics and Computational Biology Mark Heise Thesis advisor William Valdar Thesis advisor Terrence Furey Thesis advisor Fernando Pardo-Manuel de Villena Thesis advisor Ralph Baric Thesis advisor Jeremy Purvis Thesis advisor text Paul Maurizio Author Curriculum in Bioinformatics and Computational Biology School of Medicine MODELING THE HOST GENETIC DETERMINANTS OF INFLUENZA VIRUS PATHOGENESIS IN MICE The persistent threat of infection has contributed to variation in mortality and survival, shaping mammalian genomes throughout history. Genetic variation that now exists controls infection outcomes, although the specific genes and variants are not well known. Common methods for genome-wide mapping often assume predominantly additive genetic action, for reasons of power and simplicity. However, non-additive effects may arise from mutations in critical pathways, such as those that regulate the host resistance to influenza A virus. Notably, complex, non-additive genetic architecture is difficult to characterize in human studies, and certain effects may remain elusive except in model organisms, such as mice. Thus, the identification of novel non-additive genetic effects in host-pathogen interactions is an area of open research, and this dissertation focuses specifically on understanding the role of dominance, parent-of-origin, and additive genetic variation the host control of influenza infection. In this research, I use experimental crosses of inbred strains of mice, both standard and recombinant inbreds, to introduce genetic diversity and increase levels of heterozygosity. Using replicable, genetically diverse populations, I model and characterize genetic variation that controls the host pathogenic response to influenza. In Chapter 1, I provide a basic introduction for influenza virus, diallels, and reciprocal cross breeding designs for genetic studies, and I review systems and statistical genetics analysis with recombinant inbred strains known as the Collaborative Cross. In Chapter 2, I describe the genetic architecture of the host response to influenza in a diallel, and the dissection of Mx1 subspecies-specific dominance. In Chapter 3, I describe novel parent-of-origin effects on pathology and on gene regulation in the response to influenza in F1 reciprocal cross mice. Chapter 4 covers the discovery of a novel genomic locus that controls pathology of influenza infection in the lung, via quantitative trait locus mapping in Collaborative Cross F1 mice. I conclude in Chapter 5 with a recap and future directions. In summary, this work provides a path forward for interrogating and understanding the complex genetic architecture of genome-wide contributions to host pathology following influenza infection, using quantitative, statistical, and systems approaches in inbred and hybrid mice. Spring 2018 2018 Genetics Virology Bioinformatics Bayesian mixed model, Collaborative Cross, diallel, multiple imputation, parent-of-origin, treatment response eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Bioinformatics and Computational Biology Mark Heise Thesis advisor William Valdar Thesis advisor Terrence Furey Thesis advisor Fernando Pardo-Manuel de Villena Thesis advisor Ralph Baric Thesis advisor Jeremy Purvis Thesis advisor text Paul Maurizio Author Curriculum in Bioinformatics and Computational Biology School of Medicine MODELING THE HOST GENETIC DETERMINANTS OF INFLUENZA VIRUS PATHOGENESIS IN MICE The persistent threat of infection has contributed to variation in mortality and survival, shaping mammalian genomes throughout history. Genetic variation that now exists controls infection outcomes, although the specific genes and variants are not well known. Common methods for genome-wide mapping often assume predominantly additive genetic action, for reasons of power and simplicity. However, non-additive effects may arise from mutations in critical pathways, such as those that regulate the host resistance to influenza A virus. Notably, complex, non-additive genetic architecture is difficult to characterize in human studies, and certain effects may remain elusive except in model organisms, such as mice. Thus, the identification of novel non-additive genetic effects in host-pathogen interactions is an area of open research, and this dissertation focuses specifically on understanding the role of dominance, parent-of-origin, and additive genetic variation the host control of influenza infection. In this research, I use experimental crosses of inbred strains of mice, both standard and recombinant inbreds, to introduce genetic diversity and increase levels of heterozygosity. Using replicable, genetically diverse populations, I model and characterize genetic variation that controls the host pathogenic response to influenza. In Chapter 1, I provide a basic introduction for influenza virus, diallels, and reciprocal cross breeding designs for genetic studies, and I review systems and statistical genetics analysis with recombinant inbred strains known as the Collaborative Cross. In Chapter 2, I describe the genetic architecture of the host response to influenza in a diallel, and the dissection of Mx1 subspecies-specific dominance. In Chapter 3, I describe novel parent-of-origin effects on pathology and on gene regulation in the response to influenza in F1 reciprocal cross mice. Chapter 4 covers the discovery of a novel genomic locus that controls pathology of influenza infection in the lung, via quantitative trait locus mapping in Collaborative Cross F1 mice. I conclude in Chapter 5 with a recap and future directions. In summary, this work provides a path forward for interrogating and understanding the complex genetic architecture of genome-wide contributions to host pathology following influenza infection, using quantitative, statistical, and systems approaches in inbred and hybrid mice. Spring 2018 2018 Genetics Virology Bioinformatics Bayesian mixed model, Collaborative Cross, diallel, multiple imputation, parent-of-origin, treatment response eng Doctor of Philosophy Dissertation Bioinformatics and Computational Biology Mark Heise Thesis advisor William Valdar Thesis advisor Terrence Furey Thesis advisor Fernando Pardo-Manuel Pardo-Pardo-Manuel de Villena Thesis advisor Ralph S. Baric Thesis advisor Jeremy Purvis Thesis advisor text University of North Carolina at Chapel Hill Degree granting institution Paul Maurizio Creator Curriculum in Bioinformatics and Computational Biology School of Medicine MODELING THE HOST GENETIC DETERMINANTS OF INFLUENZA VIRUS PATHOGENESIS IN MICE The persistent threat of infection has contributed to variation in mortality and survival, shaping mammalian genomes throughout history. Genetic variation that now exists controls infection outcomes, although the specific genes and variants are not well known. Common methods for genome-wide mapping often assume predominantly additive genetic action, for reasons of power and simplicity. However, non-additive effects may arise from mutations in critical pathways, such as those that regulate the host resistance to influenza A virus. Notably, complex, non-additive genetic architecture is difficult to characterize in human studies, and certain effects may remain elusive except in model organisms, such as mice. Thus, the identification of novel non-additive genetic effects in host-pathogen interactions is an area of open research, and this dissertation focuses specifically on understanding the role of dominance, parent-of-origin, and additive genetic variation the host control of influenza infection. In this research, I use experimental crosses of inbred strains of mice, both standard and recombinant inbreds, to introduce genetic diversity and increase levels of heterozygosity. Using replicable, genetically diverse populations, I model and characterize genetic variation that controls the host pathogenic response to influenza. In Chapter 1, I provide a basic introduction for influenza virus, diallels, and reciprocal cross breeding designs for genetic studies, and I review systems and statistical genetics analysis with recombinant inbred strains known as the Collaborative Cross. In Chapter 2, I describe the genetic architecture of the host response to influenza in a diallel, and the dissection of Mx1 subspecies-specific dominance. In Chapter 3, I describe novel parent-of-origin effects on pathology and on gene regulation in the response to influenza in F1 reciprocal cross mice. Chapter 4 covers the discovery of a novel genomic locus that controls pathology of influenza infection in the lung, via quantitative trait locus mapping in Collaborative Cross F1 mice. I conclude in Chapter 5 with a recap and future directions. In summary, this work provides a path forward for interrogating and understanding the complex genetic architecture of genome-wide contributions to host pathology following influenza infection, using quantitative, statistical, and systems approaches in inbred and hybrid mice. Genetics Virology Bioinformatics Bayesian mixed model; Collaborative Cross; diallel; multiple imputation; parent-of-origin; treatment response eng Doctor of Philosophy Dissertation Bioinformatics and Computational Biology Mark Heise Thesis advisor William Valdar Thesis advisor Terrence Furey Thesis advisor Fernando Pardo-Manuel Pardo-Pardo-Manuel de Villena Thesis advisor Ralph S. Baric Thesis advisor Jeremy Purvis Thesis advisor text University of North Carolina at Chapel Hill Degree granting institution 2018 2018-05 Paul Maurizio Author Curriculum in Bioinformatics and Computational Biology School of Medicine MODELING THE HOST GENETIC DETERMINANTS OF INFLUENZA VIRUS PATHOGENESIS IN MICE The persistent threat of infection has contributed to variation in mortality and survival, shaping mammalian genomes throughout history. Genetic variation that now exists controls infection outcomes, although the specific genes and variants are not well known. Common methods for genome-wide mapping often assume predominantly additive genetic action, for reasons of power and simplicity. However, non-additive effects may arise from mutations in critical pathways, such as those that regulate the host resistance to influenza A virus. Notably, complex, non-additive genetic architecture is difficult to characterize in human studies, and certain effects may remain elusive except in model organisms, such as mice. Thus, the identification of novel non-additive genetic effects in host-pathogen interactions is an area of open research, and this dissertation focuses specifically on understanding the role of dominance, parent-of-origin, and additive genetic variation the host control of influenza infection. In this research, I use experimental crosses of inbred strains of mice, both standard and recombinant inbreds, to introduce genetic diversity and increase levels of heterozygosity. Using replicable, genetically diverse populations, I model and characterize genetic variation that controls the host pathogenic response to influenza. In Chapter 1, I provide a basic introduction for influenza virus, diallels, and reciprocal cross breeding designs for genetic studies, and I review systems and statistical genetics analysis with recombinant inbred strains known as the Collaborative Cross. In Chapter 2, I describe the genetic architecture of the host response to influenza in a diallel, and the dissection of Mx1 subspecies-specific dominance. In Chapter 3, I describe novel parent-of-origin effects on pathology and on gene regulation in the response to influenza in F1 reciprocal cross mice. Chapter 4 covers the discovery of a novel genomic locus that controls pathology of influenza infection in the lung, via quantitative trait locus mapping in Collaborative Cross F1 mice. I conclude in Chapter 5 with a recap and future directions. In summary, this work provides a path forward for interrogating and understanding the complex genetic architecture of genome-wide contributions to host pathology following influenza infection, using quantitative, statistical, and systems approaches in inbred and hybrid mice. Spring 2018 2018 Genetics Virology Bioinformatics Bayesian mixed model, Collaborative Cross, diallel, multiple imputation, parent-of-origin, treatment response eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Bioinformatics and Computational Biology Mark Heise Thesis advisor William Valdar Thesis advisor Terrence Furey Thesis advisor Fernando Pardo-Manuel Pardo-Pardo-Manuel de Villena Thesis advisor Ralph S. Baric Thesis advisor Jeremy Purvis Thesis advisor text Paul Maurizio Creator Curriculum in Bioinformatics and Computational Biology School of Medicine The persistent threat of infection has contributed to variation in mortality and survival, shaping mammalian genomes throughout history. Genetic variation that now exists controls infection outcomes, although the specific genes and variants are not well known. Common methods for genome-wide mapping often assume predominantly additive genetic action, for reasons of power and simplicity. However, non-additive effects may arise from mutations in critical pathways, such as those that regulate the host resistance to influenza A virus. Notably, complex, non-additive genetic architecture is difficult to characterize in human studies, and certain effects may remain elusive except in model organisms, such as mice. Thus, the identification of novel non-additive genetic effects in host-pathogen interactions is an area of open research, and this dissertation focuses specifically on understanding the role of dominance, parent-of-origin, and additive genetic variation the host control of influenza infection. In this research, I use experimental crosses of inbred strains of mice, both standard and recombinant inbreds, to introduce genetic diversity and increase levels of heterozygosity. Using replicable, genetically diverse populations, I model and characterize genetic variation that controls the host pathogenic response to influenza. In Chapter 1, I provide a basic introduction for influenza virus, diallels, and reciprocal cross breeding designs for genetic studies, and I review systems and statistical genetics analysis with recombinant inbred strains known as the Collaborative Cross. In Chapter 2, I describe the genetic architecture of the host response to influenza in a diallel, and the dissection of Mx1 subspecies-specific dominance. In Chapter 3, I describe novel parent-of-origin effects on pathology and on gene regulation in the response to influenza in F1 reciprocal cross mice. Chapter 4 covers the discovery of a novel genomic locus that controls pathology of influenza infection in the lung, via quantitative trait locus mapping in Collaborative Cross F1 mice. I conclude in Chapter 5 with a recap and future directions. In summary, this work provides a path forward for interrogating and understanding the complex genetic architecture of genome-wide contributions to host pathology following influenza infection, using quantitative, statistical, and systems approaches in inbred and hybrid mice. 2018-05 2018 Genetics Virology Bioinformatics Bayesian mixed model; Collaborative Cross; diallel; multiple imputation; parent-of-origin; treatment response eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Mark Heise Thesis advisor William Valdar Thesis advisor Terrence Furey Thesis advisor Fernando Pardo-Manuel Pardo-Pardo-Manuel de Villena Thesis advisor Ralph S. Baric Thesis advisor Jeremy Purvis Thesis advisor text Maurizio_unc_0153D_17631.pdf uuid:5b50b9a5-25a7-48db-9df2-1a3232eac863 2020-06-13T00:00:00 2018-04-11T12:47:48Z proquest application/pdf 12174456