<p>Hydrogen peroxide is used by animals and plants to deter the growth of microbial invaders by inflicting DNA lesions, protein oxidation and lipid membrane modifications. Pathogens protect themselves with enzymes and scavenging proteins. This study investigated population genetic, biochemical and genetic aspects of peroxide survival in <i>Saccharomyces cerevisiae </i> to address its importance for yeast biology and fungal pathogenicity.</p><p>Population genetic analyses of DNA sequences from five loci from 103 strains encompassing the known ecological spectrum of <i>S. cerevisiae</i> show that it is a recombining species with three divergent subgroups, which are associated with soil, fruit, and vineyards. Clinical isolates cluster with fruit isolates but are significantly more resistant to peroxide. Clinical isolates are genetically diverse, indicating multiple origins of the pathogenic lifestyle and eliminating the possibility that peroxide resistance is due to shared ancestry rather than it's importance for than its importance in colonizing the host.</p><p>Biochemical aspects of peroxide survival were studied in a resistant (high-survival) clinical isolate, a sensitive (low-survival) laboratory strain and their hybrid. Catalase activity and expression levels are indistinguishable among strains. Co-culture assays and growth curve records indicate that a secreted factor improves survival of the laboratory strain and that the phenotypic difference is most pronounced during exponential growth, excluding mechanisms of the General Stress Response effective during stationary phase. Semi-quantitative expression profiles of stress response candidate genes do not differ, suggesting a novel resistance mechanism.</p><p>To elucidate the genetic basis of peroxide survival, the hybrid was sporulated and 200 F1 segregants phenotyped and genotyped for oxidative stress candidate genes. Peroxide survival is a dominant quantitative trait and not linked to catalase, peroxidase or superoxide dismutase genes. 1,246 backcross segregants were phenotyped and 93 segregants selectively genotyped using microarrays. A 14-gene locus on chromosome XVI displayed marker-trait association. One gene, <i>RDS2</i>, encodes a zinc cluster protein acting as a regulator of drug sensitivity and contains a non-synonymous polymorphism whose exchange between the parental strains results a 15% decrease in survival in the clinical strain.</p><p>This work establishes a novel function for <i>RDS2</i> in oxidative stress response and demonstrates the effect a quantitative trait nucleotide has on a clinically relevant phenotype.</p> / Dissertation

Thesis (Ph.D.)--Mississippi State University. Department of Plant and Soil Sciences. / Title from title screen. Includes bibliographical references.

Increasingly, individual variation is being recognized as an important influence on behavioral evolution. Sources of variation are therefore an important target for research into the development, evolution, and function of behavior. By providing information about the timescale on which individuals are responsive to their environment, patterns of within-individual variation can shed light on function of behavioral variation. Here, I wanted to understand the function of behavioral variation and the genetic and environmental sources of variation in behavior. First, I test the hypotheses that variation in begging signals nestling hunger, need, or quality. Hunger is a short-term response to food deprivation, while need and quality give long-term information about fitness benefits of gaining more food and fitness potential, respectively. Second, I test the hypotheses that variation in begging is due to genetic, permanent environment, common environmental, and maternal effects. I test these hypotheses in the begging behavior of western bluebirds (Sialia mexicana), making repeated measurements across the nestling period. I show that begging behavior is consistent across the nestling period, and that nestling begging intensity increases with food deprivation. Nestlings fed during a given parental visit beg at higher intensity than nestmates, and on average wait longer since their last meal compared to individuals who were not fed in the same visit. These results support the hypothesis that variation in nestling begging signals hunger. I also show that responsiveness to food deprivation is negatively related to condition, but this effect is not consistent across the nestling period. Finally, variation in begging is produced by a common environmental effect that is correlated through time, suggesting that begging is strongly influenced by the nest environment. Together, these results indicate that variation in begging signals short-term changes in hunger and that environmental effects dominate the production of variation in begging.

Life history theory assumes that correlations among fitness-related life history traits should be negative among individuals, reflecting resource allocation constraints among traits such as growth and reproduction. These traits trade off because they cannot be simultaneously maximized in individuals facing finite resource acquisition. Positive correlations among traits that are expected to be negative (e.g. between energetically costly traits) have been regularly observed, however, and have usually been ascribed to genetic or resource acquisition differences. In the freshwater zooplankton Cladoceran Daphnia, positive correlations have been particularly well documented even when genetic and environmental variation have been controlled. The sign of these correlations represent a problem for life history theory, which is underpinned by the notion of universal and unavoidable costs associated with investing in a given trait. It has been suggested, however, that costs vary with environment and thus can change the sign of a correlation. A change in correlation sign over an environmental gradient may indicate that the assumed universality of costs and constraints are not as universal as expected by life history theory. Few life history experiments have examined traits in multiple environments, and fewer have done so while controlling resource acquisition and genetic variation. Here I ask whether the positive genetic correlations among somatic growth rate, egg production rate, and longevity are present in the face of equal ingestion, clonal individuals, and a finely resolved gradient of food quality, an environmental factor that frequently affects Daphnia. I partition trait covariation into genetic and residual, or environmental, sources. All resulting genetic correlations were non-significant. Residual correlations trended from significantly positive to negative between longevity and growth rate and remained near zero between longevity and egg rate. The residual correlation between growth and reproduction, two expensive traits, displayed significantly positive residual correlations across the food quality gradient remained significantly positive. Given the experimental controls in place, I suggest that differences in individual ontogeny may give rise to differential resource utilization or assimilation efficiency. This may be a mechanism for differential resource acquisition in the absence of ingestion variation. Additionally, the different ways genetic and residual correlations change over an environmental gradient may provide insight on one manner by which genotypes might coexist and provide a candidate explanation for the second paradox of the plankton. / Thesis (Master, Biology) -- Queen's University, 2014-03-31 07:01:21.774

As genomic sequencing technologies continue to advance, researchers are furthering their understanding of the relationships between genetic variants and expressed traits (Hirschhorn and Daly, 2005). However, missing data can significantly limit the power of a genetic study. Here, the use of a regularized generalized linear model, denoted GLMNET is proposed to impute missing genotypes. The method aimed to address certain limitations of earlier regression approaches in regards to genotype imputation, particularly multicollinearity among predictors. The performance of GLMNET-based method is compared to the performance of the phase-based method fastPHASE. Two simulation settings were evaluated: a sparse-missing model, and a small-panel expan- sion model. The sparse-missing model simulated a scenario where SNPs were missing in a random fashion across the genome. In the small-panel expansion model, a set of test individuals that were only genotyped at a small subset of the SNPs of the large panel. Each imputation method was tested in the context of two data-sets: Canadian Holstein cattle data and human HapMap CEU data. Although the proposed method was able to perform with high accuracy (>90% in all simulations), fastPHASE per- formed with higher accuracy (>94%). However, the new method, which was coded in R, was able to impute genotypes with better time efficiency than fastPHASE and this could be further improved by optimizing in a compiled language.

<p>Despite high vaccination rates and effective adaptive immune responses from the part of infected individuals, influenza A viruses cause significant morbidity and mortality annually. This is due to influenza's rapid antigenic evolution, whereby continual mutations occurring in epitope regions of the virus's hemagglutinin protein result in the diminishment of long-term antibody recognition, in a process that has been termed `antigenic drift'. Although it is clear that antigenic drift enables previously infected individuals to become reinfected, the mechanism that is responsible for influenza's antigenic drift is still under debate. As recently as 2009, a new hypothesis of antigenic drift was put forward that argues that binding avidity changes in the viral hemagglutinin result in antigenic drift as a side effect. This hypothesis stands in contrast to the traditionally accepted hypothesis that mutations in epitope regions are positively selected for their ability to evade immune recognition. This thesis focuses on the use of epidemiological models and empirical data analysis to explore different hypotheses of antigenic drift. </p><p>In the first chapter, I am asking what effects on antigenic drift rate would be produced under the new hypothesis. I mathematically formulate the hypothesis that antigenic drift is simply a side effect of cellular receptor binding avidity changes that occur as the virus is transmitted between individuals of different immune status levels. I then use this formulation to explore how influenza's rate of antigenic drift depends on different epidemiological factors, including host contact rate, host lifespan, and the duration of infection. Finally, I use the model to assess alternative vaccination strategies by the impact they have on rates of antigenic drift and therewith rates of disease incidence/</p><p>In the second chapter, I critically evaluate the binding avidity hypothesis by comparing predictions of the hypothesis against empirical data. I first use a `phylodynamic' extension of the model presented in the first chapter to determine whether the hypothesis is consistent with the ladderlike phylogeny of influenza's hemagglutinin protein. I then use viral sequence data and metadata to determine whether older aged individuals (with a higher number of previous infections) harbor viruses with higher binding avidity than younger aged individuals (with a lower number of previous infections), a prediction made by the binding avidity hypothesis. Finally, I perform a phylogenetic analysis to determine how rapidly binding avidity changes occur. From these analyses, I conclude that the binding avidity hypothesis is not well supported by empirical data.</p><p>In the third chapter, I develop an integrated viral life cycle model, in which viral replication depends on three viral phenotypes: receptor binding avidity, neuraminidase activity, and antigenicity. This integrated model recognizes that receptor binding avidity changes will influence viral replication, but also allows for antigenic evolution to be brought about directly by epitope changes. I first use this model to show how the evolutionary dynamics of these phenotypes are dependent on one another and how antigenic drift can be interpreted within this framework. I then return to some of the questions addressed in the first chapter to ask how different epidemiological factors impact influenza's rate of antigenic drift.</p><p>Together, these three chapters highlight the importance of viral phenotypes other than antigenicity in contributing to influenza's antigenic evolution, and, more generally, the importance of computational and mathematical research in understanding constraints on viral adaptation.</p> / Dissertation

While the use of microbial model systems in experimental evolution has made great contributions to our understanding of evolutionary processes, technological limitations and the problems of transparency they cause continue to inhibit their use in understanding even the most basic evolutionary phenomena. Conventional mathematical models are too constraining in that the range of genotypes and fitnesses must be designated at the outset, and so such models cannot be used to describe truly open-ended systems. In this thesis, I use Artificial Life technology to investigate patterns and mechanisms of evolution over short and long periods of time in a simulated chemostat-type system. The system may be rendered completely transparent, and is "open" in that genotypes with unique sequences and fitness arise unpredictably through mutation and selection. / The results demonstrate that Artificial Life technology is an open-ended, yet tractable system that may be used satisfactorily to investigate problems that he beyond the reach of current theory and biotechnology. (Abstract shortened by UMI.)

<p>Many factors, including gene networks, developmental processes, and the environment mediate the link between the activity of genes and complex phenotypes in higher organisms. While genetic variants are the raw material for evolution, these other factors are critical for determining which variants are actually exposed to natural selection. In this dissertation, I describe three projects in which I investigate how developmental mechanisms and the environment interact to shape phenotypic variation. In each project, I use gene expression as a window into the activity of genes, and as a tool to measure variation in and among developmental mechanisms. Two projects are experimental, focusing on early development in sea urchins, and how environmental stress caused by climate change impacts the expression of genetic variation in phenotypic traits. In these projects, I explicitly incorporate information about the biochemical functions of genes and how they interact in development, and test how such mechanisms shape the impact of genetic and environmental perturbations to development. The third project is methodological, in which I propose a unified statistical framework for inferring previously unknown developmental constraints that may underlie gene expression phenotypes. Together, these projects demonstrate that an understanding of developmental mechanisms can enhance our understanding of the processes that shape variation in populations, and can help predict the biological effects of climate change.</p> / Dissertation

The use of molecular markers to identify quantitative trait loci ( QTL ) affecting economically important traits has become a key approach in animal genetics, both for understanding the genetic basis of these traits and to help design novel breeding programs. The general goal of the present work was to map QTL for economically important traits in beef cattle. Because of the practical limitations of phenotypic selection for meat quality, these traits are ideal candidates for the use of marker - assisted selection. Thus, the thesis specifically focused on carcass and beef quality traits. Six half - sib families were generated by mating six Limousin x Jersey crossbred sires to purebred Jersey or Limousin cows, producing 784 backcross progeny ( 366 and 418 progeny in Australia and New Zealand, respectively ). The six crossbred sires and all the backcross progeny were genotyped for 285 microsatellite markers ( on average 189 informative loci per sire family ) spread across the 29 bovine autosomes. A large number of traits were recorded on backcross progeny. In the first phase of the research, a single - QTL model based on regression interval mapping was used to map QTL for a wide range of economically important traits in the beef industry. Chromosome - wise significant evidence for linkage was found on BTA12 ( P < 0.01 ) and BTA16 ( P < 0.05 ) for age at puberty. Thirteen QTL were found to affect calving ease related traits ( birth weight, pelvic area and gestation length ). BTA11, 14 and 22 were most significant linkage groups affecting calving ease traits. Several genomic regions were linked to the carcass and beef quality traits. The results revealed a major QTL on BTA2 close to the map position of myostatin gene, affecting yield, carcass fatness and beef quality traits. In the second phase, the pleiotropic effects of a myostatin functional SNP on beef traits were studied. There was no association between this myostatin variant and birth weight and growth traits. However, the variant decreased overall fatness, increased muscle mass and improved meat tenderness, thus providing an intermediate and more useful phenotype than the more severe double - muscling phenotype caused by a major deletion in the myostatin gene described by others. In the third phase, a multiple marker analysis approach in the framework of the mixed - effects model was developed, allowing all markers of the entire genome to be included in the analysis simultaneously. Further, exploiting a factor analytic covariance structure for modeling trait by marker or family by marker interaction terms, the approach was extended to the multi - trait and multiple family situations. The simulation study showed that modeling multiple phenotypes and multiple families in a single linkage analysis simultaneously can markedly increase the power to detect QTL, compared to modeling each phenotype or family separately. Finally, the multi - trait multiple QTL approach developed herein was applied to map QTL influencing carcass and meat quality traits. Several pleoitropic QTL and also traitspecific QTL affecting beef traits were mapped, resulting in a useful resource from which fine mapping can be launched for subsequent gene discovery and marker - assisted selection. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?DB=local&Search_Arg=koshkoih+thesis+adelaide&Search_Code=GKEY%5E*&SL=None&CNT=50 / Thesis (Ph.D.)--University of Adelaide, School of Agriculture, Food and Wine, 2007.

The aims of this study were to develop a genetic linkage map of perennial ryegrass, identify quantitative trait loci (QTL) for herbage and seed production traits, and to identify DNA markers associated with QTL for use in marker-assisted selection (MAS). Major traits identified for herbage production were leaf elongation rate (LER), leaf lamina length (LL), tiller number (TN) and tiller weight (TW), and for increased seed production were seed yield per head (SdYH), reproductive tiller number (RT), reproductive tillers with matured heads (TMH), florets per head (FH), spikelets per head (SH), florets per spikelet (FS), floret site utilization (FSU) and seed weight (TSW). A genetic linkage map spanning 582 centimorgans (cM) was constructed with EST-SSR (simple sequence repeat markers derived from expressed sequence tags) and used to identify QTL for herbage dry weight (DW) and seed yield per plant (SdYP), and their key component traits. Significant genotype by environment effects were encountered for herbage yield, with fewer QTL identified in spring than in autumn. For some traits, ranking of genotypes differed greatly between seasons and different QTL were identified. QTL for DW were identified on linkage groups (Lg) 1 and 6. The QTL on Lg 6 co-located with QTL for TN, while that on Lg 1 co-located with LER and LL. Markers at Lg 1 QTL (qDW-03-1.1) may be more useful for increasing herbage production by MAS because selection for high LER and long LL has been suggested to increase herbage production in perennial ryegrass. QTL for SdYP were identified on Lg 2 and Lg 6. The QTL on Lg 6 co-located with QTL for SdYH, FSU and TSW, while that on Lg 2 co-located with FH, SH and FS. For seed production, markers at Lg 6 QTL (qSdYP-03-6) may be very useful because this QTL co-located with QTL for SdYH, FSU and TSW, and SdYH has been identified previously as a key selection criterion for increasing seed yield. Marker-trait validation confirmed markers pps0495 and pps0698 identified by QTL analysis to be potentially useful for selecting for fast leaf appearance and long LL, respectively, in perennial ryegrass.