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The advent of big data analytics tools and frameworks has allowed for a plethora of new approaches to research and analysis, making data sets that were previously too large or complex more accessible and providing methods to collect, store, and investigate non-traditional data. These tools are starting to be applied

The advent of big data analytics tools and frameworks has allowed for a plethora of new approaches to research and analysis, making data sets that were previously too large or complex more accessible and providing methods to collect, store, and investigate non-traditional data. These tools are starting to be applied in more creative ways, and are being used to improve upon traditional computation methods through distributed computing. Statistical analysis of expression quantitative trait loci (eQTL) data has classically been performed using the open source tool PLINK - which runs on high performance computing (HPC) systems. However, progress has been made in running the statistical analysis in the ecosystem of the big data framework Hadoop, resulting in decreased run time, reduced storage footprint, reduced job micromanagement and increased data accessibility. Now that the data can be more readily manipulated, analyzed and accessed, there are opportunities to use the modularity and power of Hadoop to further process the data. This project focuses on adding a component to the data pipeline that will perform graph analysis on the data. This will provide more insight into the relation between various genetic differences in individuals with breast cancer, and the resulting variation - if any - in gene expression. Further, the investigation will look to see if there is anything to be garnered from a perspective shift; applying tools used in classical networking contexts (such as the Internet) to genetically derived networks.
ContributorsRandall, Jacob Christopher (Author) / Buetow, Kenneth (Thesis director) / Meuth, Ryan (Committee member) / Almalih, Sara (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description

Agassiz’s desert tortoise (Gopherus agassizii) is a long-lived species native to the Mojave Desert and is listed as threatened under the US Endangered Species Act. To aid conservation efforts for preserving the genetic diversity of this species, we generated a whole genome reference sequence with an annotation based on dee

Agassiz’s desert tortoise (Gopherus agassizii) is a long-lived species native to the Mojave Desert and is listed as threatened under the US Endangered Species Act. To aid conservation efforts for preserving the genetic diversity of this species, we generated a whole genome reference sequence with an annotation based on deep transcriptome sequences of adult skeletal muscle, lung, brain, and blood. The draft genome assembly for G. agassizii has a scaffold N50 length of 252 kbp and a total length of 2.4 Gbp. Genome annotation reveals 20,172 protein-coding genes in the G. agassizii assembly, and that gene structure is more similar to chicken than other turtles. We provide a series of comparative analyses demonstrating (1) that turtles are among the slowest-evolving genome-enabled reptiles, (2) amino acid changes in genes controlling desert tortoise traits such as shell development, longevity and osmoregulation, and (3) fixed variants across the Gopherus species complex in genes related to desert adaptations, including circadian rhythm and innate immune response. This G. agassizii genome reference and annotation is the first such resource for any tortoise, and will serve as a foundation for future analysis of the genetic basis of adaptations to the desert environment, allow for investigation into genomic factors affecting tortoise health, disease and longevity, and serve as a valuable resource for additional studies in this species complex.

Data Availability: All genomic and transcriptomic sequence files are available from the NIH-NCBI BioProject database (accession numbers PRJNA352725, PRJNA352726, and PRJNA281763). All genome assembly, transcriptome assembly, predicted protein, transcript, genome annotation, repeatmasker, phylogenetic trees, .vcf and GO enrichment files are available on Harvard Dataverse (doi:10.7910/DVN/EH2S9K).

ContributorsTollis, Marc (Author) / DeNardo, Dale F (Author) / Cornelius, John A (Author) / Dolby, Greer A (Author) / Edwards, Taylor (Author) / Henen, Brian T. (Author) / Karl, Alice E. (Author) / Murphy, Robert W. (Author) / Kusumi, Kenro (Author)
Created2017-05-31
Description
Cancer is a disease which can affect all animals across the tree of life. Certain species have undergone natural selection to reduce or prevent cancer. Mechanisms to block cancer may include, among others, a species possessing additional paralogues of tumor suppressor genes, or decreasing the number of oncogenes within their

Cancer is a disease which can affect all animals across the tree of life. Certain species have undergone natural selection to reduce or prevent cancer. Mechanisms to block cancer may include, among others, a species possessing additional paralogues of tumor suppressor genes, or decreasing the number of oncogenes within their genome. To understand cancer prevention patterns across species, I developed a bioinformatic pipeline to identify copies of 545 known tumor suppressor genes and oncogenes across 63 species of mammals. I used phylogenetic regressions to test for associations between cancer gene copy numbers and a species’ life history. I found a significant association between cancer gene copies and species’ longevity quotient. Additional paralogues of tumor suppressor genes and oncogenes is not solely dependent on body size, but rather the balance between body size and longevity. Additionally, there is a significance association between life history traits and genes that are both germline and somatic tumor suppressor genes. The bioinformatic pipeline identified large tumor suppressor gene and oncogene copy numbers in the naked mole rat (Heterocephalus glaber), armadillo (Dasypus novemcinctus), and the two-fingered sloth (Choloepus hoffmanni). These results suggest that increased paralogues of tumor suppressor genes and oncogenes are these species’ modes of cancer resistance.
ContributorsSchneider-Utaka, Aika Kunigunda (Author) / Maley, Carlo C (Thesis advisor) / Wilson, Melissa A. (Committee member) / Tollis, Marc (Committee member) / Arizona State University (Publisher)
Created2019