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Wound healing is a complex tissue response that requires a coordinated interplay of multiple cells in orchestrated biological processes to restore the skin's barrier function post-injury. Proteolytic enzymes, in particular matrix metalloproteinases (MMPs), contribute to all phases of the healing process by regulating immune cell influx, clearing out the extracellular

Wound healing is a complex tissue response that requires a coordinated interplay of multiple cells in orchestrated biological processes to restore the skin's barrier function post-injury. Proteolytic enzymes, in particular matrix metalloproteinases (MMPs), contribute to all phases of the healing process by regulating immune cell influx, clearing out the extracellular matrix (ECM), and remodeling scar tissue. As a result of these various functions in the healing of skin wounds, uncontrolled activities of MMPs are associated with impaired wound healing. The MMP gene family consists of a highly conserved set of genes. Deleterious mutations in MMP genes cause developmental phenotypes that affect the heart, skeleton, and immune system response. The availability of contiguous draft genomes of non-model organisms enables the study of gene families through analysis of synteny and sequence identity. My project is aimed at conducting a comparative genomic analysis of the MMP gene family from the genomes of 29 tetrapod species—with an emphasis on reptiles. Results regarding the similarities and differences among MMP protein sequences can be further investigated to shed light on the causes which give rise to various adaptive mutations for specific species groups.
ContributorsYu, Alexander (Author) / Kusumi, Kenro (Thesis director) / Dolby, Greer (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2022-12
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Structural Equation Modeling (SEM) is a multivariate analysis methodology that could potentially be utilized to examine the barrier effect that river systems have on genetic differentiation. In this project, river systems are split into the variables of Daily Average Discharge, Average River Width, and Seasonality measurements and regressed onto the

Structural Equation Modeling (SEM) is a multivariate analysis methodology that could potentially be utilized to examine the barrier effect that river systems have on genetic differentiation. In this project, river systems are split into the variables of Daily Average Discharge, Average River Width, and Seasonality measurements and regressed onto the genetic differentiation, measured as Fst. This data was collected from the USGS database (U.S. Geological Survey, 2020), sequencing files from differing literature, or Google Earth measurements. Different Structural Equation Modeling models are used to model different system structures as well as compare it to more traditional methodologies like Generalized Linear Modeling and Generalized Linear Mixed Modeling. Ultimately results were limited by the small sample size, however, interesting patterns still emerged from the models. The SE models indicate that Discharge plays a primary role in the genetic differentiation of adjacent river populations. In addition to this, the results demonstrate how quantification of indirect effects, particularly those relating to discharge, give more informative interpretations than traditional multivariate statistics alone. These findings prompt further investigations into this potential methodology.

ContributorsMaag, Garett (Author) / Dolby, Greer A. (Thesis advisor) / Kusumi, Kenro (Thesis advisor) / Stokes, Maya F. (Committee member) / Barly, Anthony (Committee member) / Arizona State University (Publisher)
Created2023