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- All Subjects: Genetics
- Genre: Academic theses
- Creators: Lemery, Kathryn
- Creators: Rosenberg, Michael S.
- Member of: ASU Electronic Theses and Dissertations
- Resource Type: Text
Description
The purpose of the current study was to use structural equation modeling-based quantitative genetic models to characterize latent genetic and environmental influences on proneness to three discrete negative emotions in middle childhood, according to mother-report, father-report and in-home observation. One primary aim was to test the extent to which covariance among the three emotions could be accounted for by a single, common genetically- and environmentally-influenced negative emotionality factor. A second aim was to examine the extent to which different reporters appeared to be tapping into the same genetically- and environmentally-influenced aspects of each emotion. According to mother- and father-report, moderate to high genetic influences were evident for all emotions, with mother- and father-report of fear and father-report of anger showing the highest heritability. Significant common environmental influences were also found for mother-report of anger and sadness in both univariate and multivariate models. For observed emotion, anger was moderately heritable with no evidence for common environmental variance, but sadness, object fear and social fear all showed modest to moderate common environmental influences and no significant genetic variance. In addition, cholesky decompositions examining genetic and environmental influences across reporter suggested that despite considerable overlap between mother-report and father-report, there was also reporter-specific variance on anger, sadness, and fear. Specifically, there were significant common environmental influences on mother-report of anger- and sadness that were not shared with father-report, and genetic influences on father-report of sadness and fear that were not shared with mother-report. In-home observations were not highly correlated enough with parent-report to support multivariate analysis for any emotion. Finally, according to both mother- and father-report, a single set of genetic and environmental influences was sufficient to account for covariance among all three negative emotions. However, fear was primarily explained by genetic influences not shared with other emotions, and anger also showed considerable emotion-specific genetic variance. In both cases, findings support the value of a more emotion-specific approach to temperament, and highlight the need to consider distinctions as well as commonalities across emotions, reporters and situations.
ContributorsClifford, Sierra (Author) / Lemery, Kathryn (Thesis advisor) / Shiota, Michelle (Committee member) / Eisenberg, Nancy (Committee member) / Arizona State University (Publisher)
Created2013
Description
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
Understanding how interpersonal relationships, such as parenting and sibling relationships, may contribute to early sleep development is important, as early sleep dysregulation has been shown to impact later sleep behavior (Sadeh & Anders, 1993), as well as cognitive and behavioral functioning (Gregory et al., 2006; Soffer-Dudek et al., 2011). In addition, twin studies provide an optimal opportunity to estimate genetic and environmental contributions to parenting, sibling relationships and child sleep, as they are influenced by both genetic and contextual factors. As such, the current thesis examined whether parental punitive discipline and sibling conflict were associated with child sleep duration, dysregulation and daytime sleepiness at 12 months, 30 months, and five years in a longitudinal sample of young twins recruited through birth records (Lemery-Chalfant et al., 2013). Mixed model regression analyses and quantitative behavioral genetic models (univariate and bivariate) were conducted to explore bidirectional relations and estimate genetic and environmental contributions to parental punitive punishment, sibling conflict and child sleep parameters. Sleep duration and dysregulation showed stability over time. Parental punitive discipline did not predict concurrent or future sleep parameters, nor were there bidirectional relations between punitive discipline and child sleep behaviors. Greater sibling conflict at five years was associated with shorter concurrent child sleep duration and greater daytime sleepiness, suggesting that sibling conflict may be a critical interpersonal stressor that negatively impacts child sleep. Shared environmental factors also accounted for the greatest proportion of the covariance between sibling conflict and sleep duration and daytime sleepiness at five years. These findings hold promise for sleep and sibling interaction interventions, including educating parents about fostering positive sibling relations and teaching caregivers to utilize specific parenting behaviors that may encourage better child sleep behaviors (e.g., establishing bedtime routines). Future studies should aim to understand the nuances of associations between family relationships (like punitive discipline and sibling conflict) and child sleep, as well as other explore person- and family-level factors, such as child negative emotions and parenting, that may influence associations between family relationships and child sleep.
ContributorsBreitenstein, Reagan Styles (Author) / Doane, Leah D (Thesis advisor) / Lemery, Kathryn (Committee member) / Bradley, Robert (Committee member) / Arizona State University (Publisher)
Created2015
Description
The current study examined the unique influence of emotional childhood abuse on positive and negative aspects of different types of social relationships (e.g., family, spouse/partner, and friends) in midlife and whether genetic variations of the oxytocin receptor gene (OXTR) moderated these associations. Genetic variations in OXTR are measured by single-nucleotide polymorphisms (SNPs), which have been the most substantially studied prospects for explaining individual differences in socio-behavioral phenotypes. Specifically, an SNP, rs53576, involving a guanine (G) to adenine (A) substitution located in the third intron of the OXTR has been associated with fundamental aspects of social processes and behaviors. Compared to A carriers, individuals homozygous for the G allele have enhanced social competencies and tend to elicit more positive responses from social partners, consequently increasing the overall quality of social relationships across the lifespan. However, the G allele of the OXTR has also been associated with greater social sensitivity. In the current study, conducted among a sample of 614 adults in midlife, it was shown that emotional childhood abuse was significantly associated with having less supportive and more strained relationships in midlife. Regarding supportive family relationships, the effect of emotional childhood abuse was moderated by the OXTR rs53576 polymorphism. Specifically, under conditions of more emotional abuse in childhood, individuals homozygous for the G allele had more supportive family relationships in midlife compared to A carriers. Overall, the findings suggest that genetic variations of OXTR rs53576 may be an important candidate in understanding the development of social relationship functioning within the context of negative early life experiences.
ContributorsEbbert, Ashley Marie (Author) / Infurna, Frank (Thesis advisor) / Corbin, William (Committee member) / Lemery, Kathryn (Committee member) / Luthar, Suniya (Committee member) / Arizona State University (Publisher)
Created2018
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 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
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 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.
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
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