Matching Items (2)
133485-Thumbnail Image.png

A protocol for Resolving Indeterminate Blood Phenotypes in Rhesus (Macaca mulatta) and Cynomolgus Macaques (M. fascicularis)

Description
Rhesus (Macaca mulatta) and cynomolgus (M. fascicularis) macaques are the most commonly used nonhuman primate models in biomedical research. It is therefore critical to correctly infer each study animal's ABO blood group phenotype to prevent fatal transfusion- and transplantation-induced immune responses. While most macaques can be efficiently and accurately phenotyped…

Rhesus (Macaca mulatta) and cynomolgus (M. fascicularis) macaques are the most commonly used nonhuman primate models in biomedical research. It is therefore critical to correctly infer each study animal's ABO blood group phenotype to prevent fatal transfusion- and transplantation-induced immune responses. While most macaques can be efficiently and accurately phenotyped using a DNA-based assay, we have identified some animals that are unable to be classified as type A, B, or AB and therefore exhibit an indeterminate phenotype. The purpose of this study was to develop a protocol for resolving indeterminate blood group phenotypes and consequently determine if these animals do indeed belong to an O blood phenotype. We attempted both direct and cloning-based sequencing of 21 animals phenotyped as A, B, AB, or indeterminate in order to assess variation at the functional mutation site in exon 7 of the macaque ABO gene. Although direct-from-PCR Sanger sequencing was unable to generate reliable sequence results, our cloned plasmid protocol yielded high quality sequences consistent with known blood group-specific alleles and as such can be used to identify informative polymorphisms at this locus.
ContributorsVizor, Choice Popsira (Author) / Kanthaswamy, Sreetharan (Thesis director) / Oldt, Robert (Committee member) / Department of Information Systems (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05

Data Analytics to Identify the Genetic Basis for Resilience to Temperature Stress in Soybeans

Description
This paper explores the ability to predict yields of soybeans based on genetics and environmental factors. Based on the biology of soybeans, it has been shown that yields are best when soybeans grow within a certain temperature range. The event a soybean is exposed to temperature outside their accepted range…

This paper explores the ability to predict yields of soybeans based on genetics and environmental factors. Based on the biology of soybeans, it has been shown that yields are best when soybeans grow within a certain temperature range. The event a soybean is exposed to temperature outside their accepted range is labeled as an instance of stress. Currently, there are few models that use genetic information to predict how crops may respond to stress. Using data provided by an agricultural business, a model was developed that can categorically label soybean varieties by their yield response to stress using genetic data. The model clusters varieties based on their yield production in response to stress. The clustering criteria is based on variance distribution and correlation. A logistic regression is then fitted to identify significant gene markers in varieties with minimal yield variance. Such characteristics provide a probabilistic outlook of how certain varieties will perform when planted in different regions. Given changing global climate conditions, this model demonstrates the potential of using data to efficiently develop and grow crops adjusted to climate changes.
ContributorsDean, Arlen (Co-author) / Ozcan, Ozkan (Co-author) / Travis, Daniel (Co-author) / Gel, Esma (Thesis director) / Armbruster, Dieter (Committee member) / Parry, Sam (Committee member) / Industrial, Systems and Operations Engineering Program (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05