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Building mathematical models and examining the compatibility of their theoretical predictions with empirical data are important for our understanding of evolution. The rapidly increasing amounts of genomic data on polymorphisms greatly motivate evolutionary biologists to find targets of positive selection. Although intensive mathematical and statistical studies for characterizing signatures of

Building mathematical models and examining the compatibility of their theoretical predictions with empirical data are important for our understanding of evolution. The rapidly increasing amounts of genomic data on polymorphisms greatly motivate evolutionary biologists to find targets of positive selection. Although intensive mathematical and statistical studies for characterizing signatures of positive selection have been conducted to identify targets of positive selection, relatively little is known about the effects of other evolutionary forces on signatures of positive selection. In this dissertation, I investigate the effects of various evolutionary factors, including purifying selection and population demography, on signatures of positive selection. Specifically, the effects on two highly used methods for detecting positive selection, one by Wright's Fst and its analogues and the other by footprints of genetic hitchhiking, are investigated. In Chapters 2 and 3, the effect of purifying selection on Fst is studied. The results show that purifying selection intensity greatly affects Fst by modulating allele frequencies across populations. The footprints of genetic hitchhiking in a geographically structured population are studied in Chapter 4. The results demonstrate that footprints of genetic hitchhiking are significantly influenced by geographic structure, which may help scientists to infer the origin and spread of the beneficial allele. In Chapter 5, the stochastic dynamics of a hitchhiking allele are studied using the diffusion process of genetic hitchhiking conditioned on the fixation of the beneficial allele. Explicit formulae for the conditioned two-locus diffusion process of genetic hitchhiking are derived and stochastic aspects of genetic hitchhiking are investigated. The results in this dissertation show that it is essential to model the interaction of neutral and selective forces for correct identification of the targets of positive selection.
ContributorsMaruki, Takahiro (Author) / Kim, Yuseob (Thesis advisor) / Taylor, Jesse E (Thesis advisor) / Greenwood, Priscilla E (Committee member) / Hedrick, Philip W (Committee member) / Rosenberg, Michael S. (Committee member) / Arizona State University (Publisher)
Created2011
Description
The ability to tolerate bouts of oxygen deprivation varies tremendously across the animal kingdom. Adult humans from different regions show large variation in tolerance to hypoxia; additionally, it is widely known that neonatal mammals are much more tolerant to anoxia than their adult counterparts, including in humans. Drosophila melanogaster are

The ability to tolerate bouts of oxygen deprivation varies tremendously across the animal kingdom. Adult humans from different regions show large variation in tolerance to hypoxia; additionally, it is widely known that neonatal mammals are much more tolerant to anoxia than their adult counterparts, including in humans. Drosophila melanogaster are very anoxia-tolerant relative to mammals, with adults able to survive 12 h of anoxia, and represent a well-suited model for studying anoxia tolerance. Drosophila live in rotting, fermenting media and a result are more likely to experience environmental hypoxia; therefore, they could be expected to be more tolerant of anoxia than adults. However, adults have the capacity to survive anoxic exposure times ~8 times longer than larvae. This dissertation focuses on understanding the mechanisms responsible for variation in survival from anoxic exposure in the genetic model organism, Drosophila melanogaster, focused in particular on effects of developmental stage (larval vs. adults) and within-population variation among individuals.

Vertebrate studies suggest that surviving anoxia requires the maintenance of ATP despite the loss of aerobic metabolism in a manner that prevents a disruption of ionic homeostasis. Instead, the abilities to maintain a hypometabolic state with low ATP and tolerate large disturbances in ionic status appear to contribute to the higher anoxia tolerance of adults. Furthermore, metabolomics experiments support this notion by showing that larvae had higher metabolic rates during the initial 30 min of anoxia and that protective metabolites were upregulated in adults but not larvae. Lastly, I investigated the genetic variation in anoxia tolerance using a genome wide association study (GWAS) to identify target genes associated with anoxia tolerance. Results from the GWAS also suggest mechanisms related to protection from ionic and oxidative stress, in addition to a protective role for immune function.
ContributorsCampbell, Jacob B (Author) / Harrison, Jon F. (Thesis advisor) / Gadau, Juergen (Committee member) / Call, Gerald B (Committee member) / Sweazea, Karen L (Committee member) / Rosenberg, Michael S. (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Isolation-by-distance is a specific type of spatial genetic structure that arises when parent-offspring dispersal is limited. Many natural populations exhibit localized dispersal, and as a result, individuals that are geographically near each other will tend to have greater genetic similarity than individuals that are further apart. It is important to

Isolation-by-distance is a specific type of spatial genetic structure that arises when parent-offspring dispersal is limited. Many natural populations exhibit localized dispersal, and as a result, individuals that are geographically near each other will tend to have greater genetic similarity than individuals that are further apart. It is important to identify isolation-by-distance because it can impact the statistical analysis of population samples and it can help us better understand evolutionary dynamics. For this dissertation I investigated several aspects of isolation-by-distance. First, I looked at how the shape of the dispersal distribution affects the observed pattern of isolation-by-distance. If, as theory predicts, the shape of the distribution has little effect, then it would be more practical to model isolation-by-distance using a simple dispersal distribution rather than replicating the complexities of more realistic distributions. Therefore, I developed an efficient algorithm to simulate dispersal based on a simple triangular distribution, and using a simulation, I confirmed that the pattern of isolation-by-distance was similar to other more realistic distributions. Second, I developed a Bayesian method to quantify isolation-by-distance using genetic data by estimating Wright’s neighborhood size parameter. I analyzed the performance of this method using simulated data and a microsatellite data set from two populations of Maritime pine, and I found that the neighborhood size estimates had good coverage and low error. Finally, one of the major consequences of isolation-by-distance is an increase in inbreeding. Plants are often particularly susceptible to inbreeding, and as a result, they have evolved many inbreeding avoidance mechanisms. Using a simulation, I determined which mechanisms are more successful at preventing inbreeding associated with isolation-by-distance.
ContributorsFurstenau, Tara N (Author) / Cartwright, Reed A (Thesis advisor) / Rosenberg, Michael S. (Committee member) / Taylor, Jesse (Committee member) / Wilson-Sayres, Melissa (Committee member) / Arizona State University (Publisher)
Created2015
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Description
In species with highly heteromorphic sex chromosomes, the degradation of one of the sex chromosomes can result in unequal gene expression between the sexes (e.g., between XX females and XY males) and between the sex chromosomes and the autosomes. Dosage compensation is a process whereby genes on the sex chromosomes

In species with highly heteromorphic sex chromosomes, the degradation of one of the sex chromosomes can result in unequal gene expression between the sexes (e.g., between XX females and XY males) and between the sex chromosomes and the autosomes. Dosage compensation is a process whereby genes on the sex chromosomes achieve equal gene expression which prevents deleterious side effects from having too much or too little expression of genes on sex chromsomes. The green anole is part of a group of species that recently underwent an adaptive radiation. The green anole has XX/XY sex determination, but the content of the X chromosome and its evolution have not been described. Given its status as a model species, better understanding the green anole genome could reveal insights into other species. Genomic analyses are crucial for a comprehensive picture of sex chromosome differentiation and dosage compensation, in addition to understanding speciation.

In order to address this, multiple comparative genomics and bioinformatics analyses were conducted to elucidate patterns of evolution in the green anole and across multiple anole species. Comparative genomics analyses were used to infer additional X-linked loci in the green anole, RNAseq data from male and female samples were anayzed to quantify patterns of sex-biased gene expression across the genome, and the extent of dosage compensation on the anole X chromosome was characterized, providing evidence that the sex chromosomes in the green anole are dosage compensated.

In addition, X-linked genes have a lower ratio of nonsynonymous to synonymous substitution rates than the autosomes when compared to other Anolis species, and pairwise rates of evolution in genes across the anole genome were analyzed. To conduct this analysis a new pipeline was created for filtering alignments and performing batch calculations for whole genome coding sequences. This pipeline has been made publicly available.
ContributorsRupp, Shawn Michael (Author) / Wilson Sayres, Melissa A (Thesis advisor) / Kusumi, Kenro (Committee member) / DeNardo, Dale (Committee member) / Arizona State University (Publisher)
Created2016
Description
Leprosy and tuberculosis are age-old diseases that have tormented mankind and left behind a legacy of fear, mutilation, and social stigmatization. Today, leprosy is considered a Neglected Tropical Disease due to its high prevalence in developing countries, while tuberculosis is highly endemic in developing countries and rapidly re-emerging in several

Leprosy and tuberculosis are age-old diseases that have tormented mankind and left behind a legacy of fear, mutilation, and social stigmatization. Today, leprosy is considered a Neglected Tropical Disease due to its high prevalence in developing countries, while tuberculosis is highly endemic in developing countries and rapidly re-emerging in several developed countries. In order to eradicate these diseases effectively, it is necessary to understand how they first originated in humans and whether they are prevalent in nonhuman hosts which can serve as a source of zoonotic transmission. This dissertation uses a phylogenomics approach to elucidate the evolutionary histories of the pathogens that cause leprosy and tuberculosis, Mycobacterium leprae and the M. tuberculosis complex, respectively, through three related studies. In the first study, genomes of M. leprae strains that infect nonhuman primates were sequenced and compared to human M. leprae strains to determine their genetic relationships. This study assesses whether nonhuman primates serve as a reservoir for M. leprae and whether there is potential for transmission of M. leprae between humans and nonhuman primates. In the second study, the genome of M. lepraemurium (which causes leprosy in mice, rats, and cats) was sequenced to clarify its genetic relationship to M. leprae and other mycobacterial species. This study is the first to sequence the M. lepraemurium genome and also describes genes that may be important for virulence in this pathogen. In the third study, an ancient DNA approach was used to recover M. tuberculosis genomes from human skeletal remains from the North American archaeological record. This study informs us about the types of M. tuberculosis strains present in post-contact era North America. Overall, this dissertation informs us about the evolutionary histories of these pathogens and their prevalence in nonhuman hosts, which is not only important in an anthropological context but also has significant implications for disease eradication and wildlife conservation.
ContributorsHonap, Tanvi Prasad (Author) / Stone, Anne C (Thesis advisor) / Rosenberg, Michael S. (Thesis advisor) / Clark-Curtiss, Josephine E (Committee member) / Krause, Johannes (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Rapid advancements in genomic technologies have increased our understanding of rare human disease. Generation of multiple types of biological data including genetic variation from genome or exome, expression from transcriptome, methylation patterns from epigenome, protein complexity from proteome and metabolite information from metabolome is feasible. "Omics" tools provide comprehensive view

Rapid advancements in genomic technologies have increased our understanding of rare human disease. Generation of multiple types of biological data including genetic variation from genome or exome, expression from transcriptome, methylation patterns from epigenome, protein complexity from proteome and metabolite information from metabolome is feasible. "Omics" tools provide comprehensive view into biological mechanisms that impact disease trait and risk. In spite of available data types and ability to collect them simultaneously from patients, researchers still rely on their independent analysis. Combining information from multiple biological data can reduce missing information, increase confidence in single data findings, and provide a more complete view of genotype-phenotype correlations. Although rare disease genetics has been greatly improved by exome sequencing, a substantial portion of clinical patients remain undiagnosed. Multiple frameworks for integrative analysis of genomic and transcriptomic data are presented with focus on identifying functional genetic variations in patients with undiagnosed, rare childhood conditions. Direct quantitation of X inactivation ratio was developed from genomic and transcriptomic data using allele specific expression and segregation analysis to determine magnitude and inheritance mode of X inactivation. This approach was applied in two families revealing non-random X inactivation in female patients. Expression based analysis of X inactivation showed high correlation with standard clinical assay. These findings improved understanding of molecular mechanisms underlying X-linked disorders. In addition multivariate outlier analysis of gene and exon level data from RNA-seq using Mahalanobis distance, and its integration of distance scores with genomic data found genotype-phenotype correlations in variant prioritization process in 25 families. Mahalanobis distance scores revealed variants with large transcriptional impact in patients. In this dataset, frameshift variants were more likely result in outlier expression signatures than other types of functional variants. Integration of outlier estimates with genetic variants corroborated previously identified, presumed causal variants and highlighted new candidate in previously un-diagnosed case. Integrative genomic approaches in easily attainable tissue will facilitate the search for biomarkers that impact disease trait, uncover pharmacogenomics targets, provide novel insight into molecular underpinnings of un-characterized conditions, and help improve analytical approaches that use large datasets.
ContributorsSzelinger, Szabolcs (Author) / Craig, David W. (Thesis advisor) / Kusumi, Kenro (Thesis advisor) / Narayan, Vinodh (Committee member) / Rosenberg, Michael S. (Committee member) / Huentelman, Matthew J (Committee member) / Arizona State University (Publisher)
Created2015