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Description
The technology expansion seen in the last decade for genomics research has permitted the generation of large-scale data sources pertaining to molecular biological assays, genomics, proteomics, transcriptomics and other modern omics catalogs. New methods to analyze, integrate and visualize these data types are essential to unveil relevant disease mechanisms. Towards

The technology expansion seen in the last decade for genomics research has permitted the generation of large-scale data sources pertaining to molecular biological assays, genomics, proteomics, transcriptomics and other modern omics catalogs. New methods to analyze, integrate and visualize these data types are essential to unveil relevant disease mechanisms. Towards these objectives, this research focuses on data integration within two scenarios: (1) transcriptomic, proteomic and functional information and (2) real-time sensor-based measurements motivated by single-cell technology. To assess relationships between protein abundance, transcriptomic and functional data, a nonlinear model was explored at static and temporal levels. The successful integration of these heterogeneous data sources through the stochastic gradient boosted tree approach and its improved predictability are some highlights of this work. Through the development of an innovative validation subroutine based on a permutation approach and the use of external information (i.e., operons), lack of a priori knowledge for undetected proteins was overcome. The integrative methodologies allowed for the identification of undetected proteins for Desulfovibrio vulgaris and Shewanella oneidensis for further biological exploration in laboratories towards finding functional relationships. In an effort to better understand diseases such as cancer at different developmental stages, the Microscale Life Science Center headquartered at the Arizona State University is pursuing single-cell studies by developing novel technologies. This research arranged and applied a statistical framework that tackled the following challenges: random noise, heterogeneous dynamic systems with multiple states, and understanding cell behavior within and across different Barrett's esophageal epithelial cell lines using oxygen consumption curves. These curves were characterized with good empirical fit using nonlinear models with simple structures which allowed extraction of a large number of features. Application of a supervised classification model to these features and the integration of experimental factors allowed for identification of subtle patterns among different cell types visualized through multidimensional scaling. Motivated by the challenges of analyzing real-time measurements, we further explored a unique two-dimensional representation of multiple time series using a wavelet approach which showcased promising results towards less complex approximations. Also, the benefits of external information were explored to improve the image representation.
ContributorsTorres Garcia, Wandaliz (Author) / Meldrum, Deirdre R. (Thesis advisor) / Runger, George C. (Thesis advisor) / Gel, Esma S. (Committee member) / Li, Jing (Committee member) / Zhang, Weiwen (Committee member) / Arizona State University (Publisher)
Created2011
Description
Well-established model systems exist in four out of the seven major classes of vertebrates. These include the mouse, chicken, frog and zebrafish. Noticeably missing from this list is a reptilian model organism for comparative studies between the vertebrates and for studies of biological processes unique to reptiles. To help fill

Well-established model systems exist in four out of the seven major classes of vertebrates. These include the mouse, chicken, frog and zebrafish. Noticeably missing from this list is a reptilian model organism for comparative studies between the vertebrates and for studies of biological processes unique to reptiles. To help fill in this gap the green anole lizard, Anolis carolinensis, is being adapted as a model organism. Despite the recent release of the complete genomic sequence of the A. carolinensis, the lizard lacks some resources to aid researchers in their studies. Particularly, the lack of transcriptomic resources for lizard has made it difficult to identify genes complete with alternative splice forms and untranslated regions (UTRs). As part of this work the genome annotation for A. carolinensis was improved through next generation sequencing and assembly of the transcriptomes from 14 different adult and embryonic tissues. This revised annotation of the lizard will improve comparative studies between vertebrates, as well as studies within A. carolinensis itself, by providing more accurate gene models, which provide the bases for molecular studies. To demonstrate the utility of the improved annotations and reptilian model organism, the developmental process of somitogenesis in the lizard was analyzed and compared with other vertebrates. This study identified several key features both divergent and convergent between the vertebrates, which was not previously known before analysis of a reptilian model organism. The improved genome annotations have also allowed for molecular studies of tail regeneration in the lizard. With the annotation of 3' UTR sequences and next generation sequencing, it is now possible to do expressional studies of miRNA and predict their mRNA target transcripts at genomic scale. Through next generation small RNA sequencing and subsequent analysis, several differentially expressed miRNAs were identified in the regenerating tail, suggesting miRNA may play a key role in regulating this process in lizards. Through miRNA target prediction several key biological pathways were identified as potentially under the regulation of miRNAs during tail regeneration. In total, this work has both helped advance A. carolinensis as model system and displayed the utility of a reptilian model system.
ContributorsEckalbar, Walter L (Author) / Kusumi, Kenro (Thesis advisor) / Huentelman, Matthew (Committee member) / Rawls, Jeffery (Committee member) / Wilson-Rawls, Norma (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Induced pluripotent stem cells (iPSCs) are an intriguing approach for neurological disease modeling, because neural lineage-specific cell types that retain the donors' complex genetics can be established in vitro. The statistical power of these iPSC-based models, however, is dependent on accurate diagnoses of the somatic cell donors; unfortunately, many neurodegenerative

Induced pluripotent stem cells (iPSCs) are an intriguing approach for neurological disease modeling, because neural lineage-specific cell types that retain the donors' complex genetics can be established in vitro. The statistical power of these iPSC-based models, however, is dependent on accurate diagnoses of the somatic cell donors; unfortunately, many neurodegenerative diseases are commonly misdiagnosed in live human subjects. Postmortem histopathological examination of a donor's brain, combined with premortem clinical criteria, is often the most robust approach to correctly classify an individual as a disease-specific case or unaffected control. We describe the establishment of primary dermal fibroblasts cells lines from 28 autopsy donors. These fibroblasts were used to examine the proliferative effects of establishment protocol, tissue amount, biopsy site, and donor age. As proof-of-principle, iPSCs were generated from fibroblasts from a 75-year-old male, whole body donor, defined as an unaffected neurological control by both clinical and histopathological criteria. To our knowledge, this is the first study describing autopsy donor-derived somatic cells being used for iPSC generation and subsequent neural differentiation. This unique approach also enables us to compare iPSC-derived cell cultures to endogenous tissues from the same donor. We utilized RNA sequencing (RNA-Seq) to evaluate the transcriptional progression of in vitro-differentiated neural cells (over a timecourse of 0, 35, 70, 105 and 140 days), and compared this with donor-identical temporal lobe tissue. We observed in vitro progression towards the reference brain tissue, supported by (i) a significant increasing monotonic correlation between the days of our timecourse and the number of actively transcribed protein-coding genes and long intergenic non-coding RNAs (lincRNAs) (P < 0.05), consistent with the transcriptional complexity of the brain, (ii) an increase in CpG methylation after neural differentiation that resembled the epigenomic signature of the endogenous tissue, and (iii) a significant decreasing monotonic correlation between the days of our timecourse and the percent of in vitro to brain-tissue differences (P < 0.05) for tissue-specific protein-coding genes and all putative lincRNAs. These studies support the utility of autopsy donors' somatic cells for iPSC-based neurological disease models, and provide evidence that in vitro neural differentiation can result in physiologically progression.
ContributorsHjelm, Brooke E (Author) / Craig, David W. (Thesis advisor) / Wilson-Rawls, Norma J. (Thesis advisor) / Huentelman, Matthew J. (Committee member) / Mason, Hugh S. (Committee member) / Kusumi, Kenro (Committee member) / Arizona State University (Publisher)
Created2013
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Description
A single splice site mutation in the mitochondrial methionyl-tRNA formyltransferase (MTFMT) gene is described in three patients with mitochondrial disease from two unrelated families. Nuclear-encoded MTFMT localized to the mitochondria is responsible for the formylation of Met-tRNAMet necessary for the initiation of translation in the mitochondria. This mutation has been

A single splice site mutation in the mitochondrial methionyl-tRNA formyltransferase (MTFMT) gene is described in three patients with mitochondrial disease from two unrelated families. Nuclear-encoded MTFMT localized to the mitochondria is responsible for the formylation of Met-tRNAMet necessary for the initiation of translation in the mitochondria. This mutation has been associated with mitochondrial disease (oxidative phosphorylation deficiencies due to a decreased expression of MTFMT), Leigh syndrome, and developmental delay. However, there is significant phenotypic variation between patients, which is not uncommon in mitochondrial disease. Though the variation was not clearly elucidated through analysis of gene expression, this data supported two potential gene modifiers as well as proposed an alternative energy producing pathway in the cell—glutamine metabolism. This nonsynonymous mutation at site c.626C>T generates a splicing suppressor in the coding region on exon 4 resulting exon skipping in almost all transcripts in homozygotes during splicing. It is hypothesized that antisense oligotherapy will be effective in rescuing this mutation by inhibiting the splice silencer and promoting exon inclusion as well as an increased expression of MTFMT protein in affected patients. Patient fibroblast cells were treated with MTFMT Oligo 3, which was shown to be promising in previous experiments. Real-Time qPCR was used to measure mRNA expression showing a significant up-regulation of wild-type MTFMT with treatment. In order to test whether this therapy increases mitochondrial function as well, three mitochondrial functional assays measuring superoxide species in the mitochondria, the mitochondrial membrane potential, and calcium uptake in the mitochondria were tested for optimization of results. Success has been shown in the measurement of superoxide species and mitochondrial membrane potential in patient cells without treatment. Oligotherapy will hopefully be considered as a viable therapeutic option in the future as further testing is conducted and perfected.
ContributorsMoskowitz, Abby Mae (Author) / Huentelman, Matt (Thesis director) / Schrauwen, Isabelle (Committee member) / Rangasamy, Sampath (Committee member) / School of Human Evolution and Social Change (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
One of the newest technologies available for agricultural use is the sequencing of the bovine genome and the identification of specific genes that would ensure favorable physical traits in the herd. An easy way for this technology to be utilized is in the milking herds of dairies, the herd has

One of the newest technologies available for agricultural use is the sequencing of the bovine genome and the identification of specific genes that would ensure favorable physical traits in the herd. An easy way for this technology to be utilized is in the milking herds of dairies, the herd has already been bred for specific traits and any change due to a genomic influence would be easily seen. Dairy cattle are commonly bred through artificial insemination, and this would be a perfect place for the genomic programs to prove themselves. In order to determine the attitudes of local dairymen toward genomics, I designed and administered a survey to gauge their opinions. The survey was given to a meeting of the United Dairymen of Arizona at their Tempe offices. The survey covered the current breeding methods used by the dairies, the desired attributes in a milking herd and a breeding program, and a place for the dairymen to give their own opinions on genomics. The results indicated that the dairymen are interested of using genomics, but they are unsure of the cost. Dairymen are often looking for new methods to increase their milk production and herd value, but are reluctant to pay a high amount. One recommendation is for these dairymen to utilize bulls that have had their genome analyzed when they are breeding their cows. This would allow the dairymen to see the effects and benefits of genomics on their herd without the dairymen having to front the large start up cost for their own genomic program.
ContributorsCooley, Haley Rayanne (Author) / Grebitus, Carola (Thesis director) / Schmitz, Troy (Committee member) / Morrison School of Agribusiness (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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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

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
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Description
Valley Fever, also known as coccidioidomycosis, is a respiratory disease that affects 10,000 people annually, primarily in Arizona and California. Due to a lack of gene annotation, diagnosis and treatment of Valley Fever is severely limited. In turn, gene annotation efforts are also hampered by incomplete genome sequencing. We intend

Valley Fever, also known as coccidioidomycosis, is a respiratory disease that affects 10,000 people annually, primarily in Arizona and California. Due to a lack of gene annotation, diagnosis and treatment of Valley Fever is severely limited. In turn, gene annotation efforts are also hampered by incomplete genome sequencing. We intend to use proteogenomic analysis to reannotate the Coccidioides posadasii str. Silveira genome from protein-level data. Protein samples extracted from both phases of Silveira were fragmented into peptides, sequenced, and compared against databases of known and predicted proteins sequences, as well as a de novo six-frame translation of the genome. 288 unique peptides were located that did not match a known Silveira annotation, and of those 169 were associated with another Coccidioides strain. Additionally, 17 peptides were found at the boundary of, or outside of, the current gene annotation comprising four distinct clusters. For one of these clusters, we were able to calculate a lower bound and an estimate for the size of the gap between two Silveira contigs using the Coccidioides immitis RS transcript associated with that cluster's peptides \u2014 these predictions were consistent with the current annotation's scaffold structure. Three peptides were associated with an actively translated transposon, and a putative active site was located within an intact LTR retrotransposon. We note that gene annotation is necessarily hindered by the quality and level of detail in prior genome sequencing efforts, and recommend that future studies involving reannotation include additional sequencing as well as gene annotation via proteogenomics or other methods.
ContributorsSherrard, Andrew (Author) / Lake, Douglas (Thesis director) / Grys, Thomas (Committee member) / Mitchell, Natalie (Committee member) / Computing and Informatics Program (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Studying human genetic variation opens the possibility of understanding the details of population migrations, how humans develop and function, and why they get sick. To fully understand these things, genetic variation must be comprehensively characterized across globally diverse human populations and evolutionary knowledge can be used to inform studies of

Studying human genetic variation opens the possibility of understanding the details of population migrations, how humans develop and function, and why they get sick. To fully understand these things, genetic variation must be comprehensively characterized across globally diverse human populations and evolutionary knowledge can be used to inform studies of disease. In my dissertation I use computational methods to study human genetic variation. Each of my dissertation chapters focuses on a unique topic in the field of human evolutionary genetics. In the first chapter, I present PopInf, a computational pipeline to visualize principal components analysis output and assign ancestry to samples with unknown genetic ancestry, given a reference population panel of known origins. This pipeline facilitates visualization and identification of genetic ancestry across samples, so that this ancestry can be accounted for in studies of health and disease risk. In the next chapter, I investigate factors that shape patterns of genetic variation within and among four small-scale pastoral populations in northern Kenya. I find that geography predominantly shapes patterns of genetic variation in northern Kenyan human populations. In the next chapter, I investigate the extent to which Neanderthal introgression impacts liver cancer etiology. I find a pattern of overall enrichment of somatic mutations on Neanderthal introgressed haplotypes. Finally, through simulations, I investigate the effects of standard autosomal versus sex chromosome complement-informed alignment, variant calling and variant filtering strategies on variants called on the human sex chromosomes. I show that aligning to a reference genome informed on the sex chromosome complement of samples improves variant calling on the sex chromosome compared to aligning to a default reference, and variant calling is improved in males when calling the sex chromosomes haploid rather than diploid and when using haploid-based thresholds for filtering variants on the sex chromosomes. I provide recommendations for alignment, variant calling and filtering on the sex chromosomes based on these findings.
ContributorsOill, Angela Maria (Author) / Wilson, Melissa A (Thesis advisor) / Stone, Anne C (Thesis advisor) / Buetow, Kenneth H (Committee member) / Mathew, Sarah (Committee member) / Pfeifer, Susanne P (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Speciation, or the process by which one population diverges into multiple populations that can no longer interbreed with each other, has brought about the incredible diversity of life. Mechanisms underlying this process can be more visible in the early stages of the speciation process. The mechanisms that restrict gene flow

Speciation, or the process by which one population diverges into multiple populations that can no longer interbreed with each other, has brought about the incredible diversity of life. Mechanisms underlying this process can be more visible in the early stages of the speciation process. The mechanisms that restrict gene flow in highly mobile species with no absolute barriers to dispersal, especially marine species, are understudied. Similarly, human impacts are reshaping ecosystems globally, and we are only just beginning to understand the implications of these rapid changes on evolutionary processes. In this dissertation, I investigate patterns of speciation and evolution in two avian clades: a genus of widespread tropical seabirds (boobies, genus Sula), and two congeneric passerine species in an urban environment (cardinals, genus Cardinalis). First, I explore the prevalence of gene flow across land barriers within species and between sympatric species in boobies. I found widespread evidence of gene flow over all land barriers and between 3 species pairs. Next, I compared the effects of urbanization on the spatial distributions of two cardinal species, pyrrhuloxia (Cardinalis sinuatus) and northern cardinals (Cardinalis cardinalis), in Tucson, Arizona. I found that urbanization has different effects on the spatial distributions of two closely related species that share a similar environmental niche, and I identified environmental variables that might be driving this difference. Then I tested for effects of urbanization on color and size traits of these two cardinal species. In both of these species, urbanization has altered traits involved in signaling, heat tolerance, foraging, and maneuverability. Finally, I tested for evidence of selection on the urban populations of both cardinal species and found evidence of both parallel selection and introgression between the species, as well as selection on different genes in each species. The functions of the genes that experienced positive selection suggest that light at night, energetics, and air pollution may have acted as strong selective pressures on these species in the past. Overall, my dissertation emphasizes the role of introgression in the speciation process, identifies environmental stressors faced by wildlife in urban environments, and characterizes their evolutionary responses to those stressors.
ContributorsJackson, Daniel Nelson (Author) / McGraw, Kevin J (Thesis advisor) / Amdam, Gro (Committee member) / Sweazea, Karen (Committee member) / Taylor, Scott (Committee member) / Arizona State University (Publisher)
Created2023
Description
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