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- Genre: Doctoral Dissertation
Description
The Cape Floral Region (CFR) in southwestern South Africa is one of the most diverse in the world, with >9,000 plant species, 70% of which are endemic, in an area of only ~90,000 km2. Many have suggested that the CFR's heterogeneous environment, with respect to landscape gradients, vegetation, rainfall, elevation, and soil fertility, is responsible for the origin and maintenance of this biodiversity. While studies have struggled to link species diversity with these features, no study has attempted to associate patterns of gene flow with environmental data to determine how CFR biodiversity evolves on different scales. Here, a molecular population genetic data is presented for a widespread CFR plant, Leucadendron salignum, across 51 locations with 5-kb of chloroplast (cpDNA) and 6-kb of unlinked nuclear (nuDNA) DNA sequences in a dataset of 305 individuals. In the cpDNA dataset, significant genetic structure was found to vary on temporal and spatial scales, separating Western and Eastern Capes - the latter of which appears to be recently derived from the former - with the highest diversity in the heart of the CFR in a central region. A second study applied a statistical model using vegetation and soil composition and found fine-scale genetic divergence is better explained by this landscape resistance model than a geographic distance model. Finally, a third analysis contrasted cpDNA and nuDNA datasets, and revealed very little geographic structure in the latter, suggesting that seed and pollen dispersal can have different evolutionary genetic histories of gene flow on even small CFR scales. These three studies together caution that different genomic markers need to be considered when modeling the geographic and temporal origin of CFR groups. From a greater perspective, the results here are consistent with the hypothesis that landscape heterogeneity is one driving influence in limiting gene flow across the CFR that can lead to species diversity on fine-scales. Nonetheless, while this pattern may be true of the widespread L. salignum, the extension of this approach is now warranted for other CFR species with varying ranges and dispersal mechanisms to determine how universal these patterns of landscape genetic diversity are.
ContributorsTassone, Erica (Author) / Verrelli, Brian C (Thesis advisor) / Dowling, Thomas (Committee member) / Cartwright, Reed (Committee member) / Rosenberg, Michael S. (Committee member) / Wojciechowski, Martin (Committee member) / Arizona State University (Publisher)
Created2013
Description
Understanding the diversity, evolutionary relationships, and geographic distribution of species is foundational knowledge in biology. However, this knowledge is lacking for many diverse lineages of the tree of life. This is the case for the desert stink beetles in the tribe Amphidorini LeConte, 1862 (Coleoptera: Tenebrionidae) – a lineage of arid-adapted flightless beetles found throughout western North America. Four interconnected studies that jointly increase our knowledge of this group are presented. First, the darkling beetle fauna of the Algodones sand dunes in southern California is examined as a case study to explore the scientific practice of checklist creation. An updated list of the species known from this region is presented, with a critical focus on material now made available through digitization and global aggregation. This part concludes with recommendations for future biodiversity checklist authors. Second, the psammophilic genus Trogloderus LeConte, 1879 is revised. Six new species are described, and the first, multi-gene phylogeny for the genus is inferred. In addition, historical biogeographic reconstructions along with novel hypotheses of speciation patterns within the Intermountain Region are given. In particular, the Kaibab Plateau and Kaiparowitz Formation are found to have promoted speciation on the Colorado Plateau. The Owens Valley and prehistoric Bouse Embayment are similarly hypothesized to drive species diversification in southern California. Third, a novel phylogenomic analysis for the tribe Amphidorini is presented, based on 29 de novo partial transcriptomes. Three putative ortholog sets were discovered and analyzed to infer the relationships between species groups and genera. The existing classification of the tribe is found to be highly inadequate, though the earliest-diverging relationships within the tribe are still in question. Finally, the new phylogenetic framework is used to provide a genus-level revision for the Amphidorini, which previously contained six valid genera and 253 valid species. This updated classification includes more than 100 taxonomic changes and results in the revised tribe consisting of 16 genera, with three being described as new to science.
ContributorsJohnston, Murray Andrew (Author) / Franz, Nico M (Thesis advisor) / Cartwright, Reed (Committee member) / Taylor, Jesse (Committee member) / Pigg, Kathleen (Committee member) / Arizona State University (Publisher)
Created2018
Description
Invasive salmonellosis caused by Salmonella enterica serovar Typhimurium ST313 is a major health crisis in sub-Saharan Africa, with multidrug resistance and atypical clinical presentation challenging current treatment regimens and resulting in high mortality. Moreover, the increased risk of spreading ST313 pathovars worldwide is of major concern, given global public transportation networks and increased populations of immunocompromised individuals (as a result of HIV infection, drug use, cancer therapy, aging, etc). While it is unclear as to how Salmonella ST313 strains cause invasive disease in humans, it is intriguing that the genomic profile of some of these pathovars indicates key differences between classic Typhimurium (broad host range), but similarities to human-specific typhoidal Salmonella Typhi and Paratyphi. In an effort to advance fundamental understanding of the pathogenesis mechanisms of ST313 in humans, I report characterization of the molecular genetic, phenotypic and virulence profiles of D23580 (a representative ST313 strain). Preliminary studies to characterize D23580 virulence, baseline stress responses, and biochemical profiles, and in vitro infection profiles in human surrogate 3-D tissue culture models were done using conventional bacterial culture conditions; while subsequent studies integrated a range of incrementally increasing fluid shear levels relevant to those naturally encountered by D23580 in the infected host to understand the impact of biomechanical forces in altering these characteristics. In response to culture of D23580 under these conditions, distinct differences in transcriptional biosignatures, pathogenesis-related stress responses, in vitro infection profiles and in vivo virulence in mice were observed as compared to those of classic Salmonella pathovars tested.
Collectively, this work represents the first characterization of in vivo virulence and in vitro pathogenesis properties of D23580, the latter using advanced human surrogate models that mimic key aspects of the parental tissue. Results from these studies highlight the importance of studying infectious diseases using an integrated approach that combines actions of biological and physical networks that mimic the host-pathogen microenvironment and regulate pathogen responses.
Collectively, this work represents the first characterization of in vivo virulence and in vitro pathogenesis properties of D23580, the latter using advanced human surrogate models that mimic key aspects of the parental tissue. Results from these studies highlight the importance of studying infectious diseases using an integrated approach that combines actions of biological and physical networks that mimic the host-pathogen microenvironment and regulate pathogen responses.
ContributorsYang, Jiseon (Author) / Nickerson, Cheryl A. (Thesis advisor) / Chang, Yung (Committee member) / Stout, Valerie (Committee member) / Ott, C Mark (Committee member) / Roland, Kenneth (Committee member) / Barrila, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015
Description
This thesis introduces new techniques for clustering distributional data according to their geometric similarities. This work builds upon the optimal transportation (OT) problem that seeks global minimum cost for matching distributional data and leverages the connection between OT and power diagrams to solve different clustering problems. The OT formulation is based on the variational principle to differentiate hard cluster assignments, which was missing in the literature. This thesis shows multiple techniques to regularize and generalize OT to cope with various tasks including clustering, aligning, and interpolating distributional data. It also discusses the connections of the new formulation to other OT and clustering formulations to better understand their gaps and the means to close them. Finally, this thesis demonstrates the advantages of the proposed OT techniques in solving machine learning problems and their downstream applications in computer graphics, computer vision, and image processing.
ContributorsMi, Liang (Author) / Wang, Yalin (Thesis advisor) / Chen, Kewei (Committee member) / Karam, Lina (Committee member) / Li, Baoxin (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2020
Description
Next-generation sequencing is a powerful tool for detecting genetic variation. How-ever, it is also error-prone, with error rates that are much larger than mutation rates.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.
ContributorsOrr, Adam James (Author) / Cartwright, Reed (Thesis advisor) / Wilson, Melissa (Committee member) / Kusumi, Kenro (Committee member) / Taylor, Jesse (Committee member) / Pfeifer, Susanne (Committee member) / Arizona State University (Publisher)
Created2020