Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
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- All Subjects: Genetics
Description
Abstract
Purpose—Use a framework of genetic knowledge to investigate the association between the genotypes of various genes with phenotypes, specifically the traits of elite athletes, in order to establish a personal opinion on their relevance to athletic performance.
Methods—Assemble and analyze selected published scientific studies on genotype and athletic performance and lastly to formulate a personal opinion on the value of genetic testing of athletes. ACTN3, ACE, MSTN, and apoE were the genes selected for analyses.
Results—Two genes, ACTN3 and ACE, showed a significant relationship of genotype to phenotypic traits related to athletic performance. ApoE did not demonstrate a phenotypic association with athletic performance, however it showed a correlation with injury susceptibility leading to traumatic brain injury (TBI). MSTN did not show a phenotypic association with athletic performance.
Conclusion—When considering the multifactorial nature of athletics, each sport must be investigated individually due to the different individual requirements. ACTN3 and ACE are the most widely studied genes, therefore, considerable data on their relevance to athletic performance was easily obtained and supported a relationship between genotype and athletic performance.
Purpose—Use a framework of genetic knowledge to investigate the association between the genotypes of various genes with phenotypes, specifically the traits of elite athletes, in order to establish a personal opinion on their relevance to athletic performance.
Methods—Assemble and analyze selected published scientific studies on genotype and athletic performance and lastly to formulate a personal opinion on the value of genetic testing of athletes. ACTN3, ACE, MSTN, and apoE were the genes selected for analyses.
Results—Two genes, ACTN3 and ACE, showed a significant relationship of genotype to phenotypic traits related to athletic performance. ApoE did not demonstrate a phenotypic association with athletic performance, however it showed a correlation with injury susceptibility leading to traumatic brain injury (TBI). MSTN did not show a phenotypic association with athletic performance.
Conclusion—When considering the multifactorial nature of athletics, each sport must be investigated individually due to the different individual requirements. ACTN3 and ACE are the most widely studied genes, therefore, considerable data on their relevance to athletic performance was easily obtained and supported a relationship between genotype and athletic performance.
ContributorsMinto, Jordan Taylor- Lloyd (Author) / Steele, Kelly (Thesis director) / Penton, C. Ryan (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Big Data Network Analysis of Genetic Variation and Gene Expression in Individuals with Breast Cancer
Description
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
Gle1 is an mRNP export mediator with major activity localized to the nuclear pore complex in eukaryotic cells. The protein's high preservation across vast phylogenetic distances allows us to approximate research on the properties of yeast Gle1 (yGle1) with those of human Gle1 (hGle1). Research at Vanderbilt University in 2016, which provides the research basis of this thesis, suggests that the coiled-coil domain of yGle1 is best crystallized in dicationic aqueous conditions of pH ~8.0 and 10\u201420% PEG 8000. Further exploration of crystallizable microconditions revealed a favorability toward lower pH and lower PEG concentration. Following the discovery of the protein's native crystallography conditions, a comprehensive meta-analysis of scientific literature on Gle1 was conducted on the association of Gle1 mutations with neuron disease.
ContributorsGaetano, Philip Pasquale (Author) / Foy, Joseph (Thesis director) / Dawson, T. Renee (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
With the rising data output and falling costs of Next Generation Sequencing technologies, research into data compression is crucial to maintaining storage efficiency and costs. High throughput sequencers such as the HiSeqX Ten can produce up to 1.8 terabases of data per run, and such large storage demands are even more important to consider for institutions that rely on their own servers rather than large data centers (cloud storage)1. Compression algorithms aim to reduce the amount of space taken up by large genomic datasets by encoding the most frequently occurring symbols with the shortest bit codewords and by changing the order of the data to make it easier to encode. Depending on the probability distribution of the symbols in the dataset or the structure of the data, choosing the wrong algorithm could result in a compressed file larger than the original or a poorly compressed file that results in a waste of time and space2. To test efficiency among compression algorithms for each file type, 37 open-source compression algorithms were used to compress six types of genomic datasets (FASTA, VCF, BCF, GFF, GTF, and SAM) and evaluated on compression speed, decompression speed, compression ratio, and file size using the benchmark test lzbench. Compressors that outpreformed the popular bioinformatics compressor Gzip (zlib -6) were evaluated against one another by ratio and speed for each file type and across the geometric means of all file types. Compressors that exhibited fast compression and decompression speeds were also evaluated by transmission time through variable speed internet pipes in scenarios where the file was compressed only once or compressed multiple times.
ContributorsHowell, Abigail (Author) / Cartwright, Reed (Thesis director) / Wilson Sayres, Melissa (Committee member) / Taylor, Jay (Committee member) / Barrett, The Honors College (Contributor)
Created2017-05
Description
My project focuses on the show swine industry and the different aspects that are involved in the process of raising show swine to be eventually used for breeding or harvested and prepared for meals that end up on people's dinner tables. I address areas of production and give an explanation of: swine genetics, swine breeding, swine show preparation, swine shows and harvesting. For the creative element of my thesis, I created a website with stories in each area of the swine production process. Each story includes personal experiences from various sources, visuals and video packages. The website was created to be engaging and esthetically pleasing to its readers. The intention of this project was to highlight the different elements, processes and stories of people who are involved in the breeding, showing and harvesting of pigs. The website can be found at thatpiggirl.weebly.com Keywords: show swine, breeding, genetics, pigs, swine industry, artificial insemination, harvesting, pig showing
ContributorsHyde, Shayla Nykohl (Author) / Chadha, Monica (Thesis director) / Maynard, Jeff (Committee member) / Walter Cronkite School of Journalism and Mass Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12