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- All Subjects: Phylogenetics
- Creators: Maley, Carlo
- Creators: Scotch, Matthew
Description
The 2017-2018 Influenza season was marked by the death of 80,000 Americans: the highest flu-related death toll in a decade. Further, the yearly economic toll to the US healthcare system and society is on the order of tens of billions of dollars. It is vital that we gain a better understanding of the dynamics of influenza transmission in order to prevent its spread. Viral DNA sequences examined using bioinformatics methods offer a rich framework with which to monitor the evolution and spread of influenza for public health surveillance. To better understand the influenza epidemic during the severe 2017-2018 season, we established a passive surveillance system at Arizona State University’s Tempe Campus Health Services beginning in January 2018. From this system, nasopharyngeal samples screening positive for influenza were collected. Using these samples, molecular DNA sequences will be generated using a combined multiplex RT-PCR and NGS approach. Phylogenetic analysis will be used to infer the severity and temporal course of the 2017-2018 influenza outbreak on campus as well as the 2018-2019 flu season. Through this surveillance system, we will gain knowledge of the dynamics of influenza spread in a university setting and will use this information to inform public health strategies.
ContributorsMendoza, Lydia Marie (Author) / Scotch, Matthew (Thesis director) / Hogue, Brenda (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Phylogenetic analyses that were conducted in the past didn't have the ability or functionality to inform and implement useful public health decisions while using clustering. Models can be constructed to conduct any further analyses for the result of meaningful data to be used in the future of public health informatics. A phylogenetic tree is considered one of the best ways for researchers to visualize and analyze the evolutionary history of a certain virus. The focus of this study was to research HIV phylodynamic and phylogenetic methods. This involved identifying the fast growing HIV transmission clusters and rates for certain risk groups in the US. In order to achieve these results an HIV database was required to retrieve real-time data for implementation, alignment software for multiple sequence alignment, Bayesian analysis software for the development and manipulation of models, and graphical tools for visualizing the output from the models created. This study began by conducting a literature review on HIV phylogeographies and phylodynamics. Sequence data was then obtained from a sequence database to be run in a multiple alignment software. The sequence that was obtained was unaligned which is why the alignment was required. Once the alignment was performed, the same file was loaded into a Bayesian analysis software for model creation of a phylogenetic tree. When the model was created, the tree was edited in a tree visualization software for the user to easily interpret. From this study the output of the tree resulted the way it did, due to a distant homology or the mixing of certain parameters. For a further continuation of this study, it would be interesting to use the same aligned sequence and use different model parameter selections for the initial creation of the model to see how the output changes. This is because one small change for the model parameter could greatly affect the output of the phylogenetic tree.
ContributorsNandan, Meghana (Author) / Scotch, Matthew (Thesis director) / Liu, Li (Committee member) / Biomedical Informatics Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Bats (order Chiroptera) are the longest lived mammals for their size, with particularly extreme longevity evolving in the family Vespertilionidae, or vesper bats. Because of this, researchers have proposed using bats to study ageing and cancer suppression. Here, we study gene duplications across mammalian genomes and show that, similar to previous findings in elephants, bats have experienced duplications of the tumor suppressor gene TP53, including five genomic copies in the genome of the little brown bat (Myotis lucifugus) and two copies in Brandt's bat (Myotis brandtii). These species can live 37 and 41 years, respectively, despite having an adult body mass of only ~7 grams. We use evolutionary genetics and next generation sequencing approaches to show that positive selection has acted on the TP53 locus across bats, and two recently duplicated TP53 gene copies in the little brown bat are both highly conserved and expressed, suggesting they are functional. We also report an extraordinary genomic copy number expansion of the tumor suppressor gene FBXO31 in the common ancestor of vesper bats which accelerated in the Myotis lineage, leading to 34\u201457 copies and the expression of 20 functional FBXO31 homologs in Brandt's bat. As FBXO31 directs the degradation of MDM2, which is a negative regulator of TP53, we suggest that increased expression of both FBXO31 and TP53 may be related to an enhanced DNA-damage response to genotoxic stress brought on by long lifespans and rapid metabolic rates in bats.
ContributorsSchneider-Utaka, Aika Kunigunda (Author) / Maley, Carlo (Thesis director) / Wilson Sayres, Melissa (Committee member) / Tollis, Marc (Committee member) / School of Life Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Cancer is a problem of multicellularity, making it a problem across all species. This pervasiveness has led to much research into the defense and the pathology of the disease. Previously, studies have been limited in sample size, taxonomic breadth, and comparative methods to explain and understand the data available. Here, we have access to life history and cancer risk data of 17,563 individuals for 327 species, spanning across three monophyletic clades: Amphibians, Sauropsids, and Mammals. Comparative biology’s approach to cross-species cancer prevalence is crucial to the identification of species that are uniquely resistant to cancer as well as stratifying risk across a phylogeny based on the life history framework. Using the life history framework, alongside a multitude of life history data, was able to find that neoplasia prevalence increases with adult weight and longevity, but decreases with gestation time. It was also discovered that malignancy prevalence decreases with gestation time. Gestation and adult weight are also both significant predictors of neoplasia and malignancy prevalence when controlling for the other. On an evolutionary scale, cancer risk appears to be best described by sudden shifts in cancer prevalence followed by stabilizing selection of that trait. The understanding of increases and decreases of cancer risk across species could create better insight on human’s own cancer risk, as well as disease prevention in humans.
ContributorsMellon, Walker (Author) / Maley, Carlo (Thesis director) / Compton, Zachary (Committee member) / Mallo, Diego (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Economics (Contributor)
Created2022-12