AuthorIgnacio Espinoza, Julio C.
AdvisorSullivan, Matthew B.
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
EmbargoRelease after 15-Jan-2016
AbstractViruses represent the most abundant biological entities on earth where, they are able to interact with all kingdoms of life. Yet their diversity, ecology and evolutionary aspects are only beginning to be fully elucidated, mainly due to technical limitations. The vast majority of the microbial world remains elusive to culture; more than 90% of genome sequenced viral isolates infect only 5 of the 54 prokaryotic phyla that are currently recognized. In contrast, viral metagenomics bypasses the need for cultures by directly sequencing fragmented genetic material of environmental viral communities. This dissertation uses viral metagenomics by applying well-tested bioinformatic protocols and expanding them to compare and contrast patterns of diversity, richness and specialization of large viral metagenomic datasets, in both local and global scales. First I demonstrate the utility of a functional-based perspective by adopting the protein cluster environment to estimate global viral diversity. Then, I use this PC approach to analyze metagenomes from two ecologically different environments, which by uncovering local gene specialization showcases the adequacy of a gene-centered workflow. Then I continue to expand upon this PC framework to study the Tara Oceans virome analyses of these data reveal patters of diversity that support a seed bank model. Finally, in search of a more meaningful ecological unit, I move from a gene-centered standpoint towards a population-based frame. We adopted a novel metagenomic technique that allowed me to uncover the discontinuity in the genomic sequence space, thus empirically defining a population. This final contribution will allow to sort and count viral communities, the first step to applying ecological and evolutionary theory.
Degree ProgramGraduate College
Molecular & Cellular Biology