Immediately following a gene duplication event, if both gene copies are to be fixed into a species’ genome there is a period of enhanced selection acting on either one or both duplicates (paralogs) that results in some extent of functional divergence. However, as redundancy among extant duplicates is thought to confer genomic robustness, a consequent question is: how much functional overlap exists between duplicates that are retained over long spans of evolutionary time? To examine this issue I determined the extent of shared protein interactions and protein complex membership for paralogous gene pairs resulting from an ancient Whole Genome Duplication (WGD) event in yeast, finding retained functional overlap to be substantial among this group. Surprisingly however, I found paralogs existing within the same complex tended to maintain greater disparities in expression, suggesting the existence of previously proposed “transcriptional back-up” mechanisms. To test both for existence of such mechanisms and for any phenotypic manifestation of their shared functional overlap I surveyed for the presence of aggravating genetic interactions between 399 WGD-resultant paralog pairs. While these paralogs exhibited a high frequency (~30%) of epistasis, observed genetic interactions were not predictable based on protein interaction overlap. Further, exposure to a limited number of stressors confirmed that additional instances of epistasis were only observable under alternate conditions. As only a small number of stress conditions were tested, the high frequency of genetic interactions reported appears to be a minimum estimate of the true extent of epistasis among WGD paralogs, potentially explaining the lack of overlap with protein interaction data. As it is impossible to survey an infinite condition space, Synthetic Genetic Array (SGA) screening of yeast strains carrying double-deletions of paralog pairs was used to assess functional redundancy among a group of the remaining non-epistatic paralog pairs. The resulting interactions demonstrated functional relationships in non-epistatic paralogs only obvious upon ablation of both duplicates, suggesting that these interactions had initially been masked through redundant function. These findings ultimately suggest an advantage to retained functional overlap among whole genome duplicates that is capable of being stably maintained through millions of years of evolutionary time.

Immediately following a gene duplication event, if both gene copies are to be fixed into a species’ genome there is a period of enhanced selection acting on either one or both duplicates (paralogs) that results in some extent of functional divergence. However, as redundancy among extant duplicates is thought to confer genomic robustness, a consequent question is: how much functional overlap exists between duplicates that are retained over long spans of evolutionary time? To examine this issue I determined the extent of shared protein interactions and protein complex membership for paralogous gene pairs resulting from an ancient Whole Genome Duplication (WGD) event in yeast, finding retained functional overlap to be substantial among this group. Surprisingly however, I found paralogs existing within the same complex tended to maintain greater disparities in expression, suggesting the existence of previously proposed “transcriptional back-up” mechanisms. To test both for existence of such mechanisms and for any phenotypic manifestation of their shared functional overlap I surveyed for the presence of aggravating genetic interactions between 399 WGD-resultant paralog pairs. While these paralogs exhibited a high frequency (~30%) of epistasis, observed genetic interactions were not predictable based on protein interaction overlap. Further, exposure to a limited number of stressors confirmed that additional instances of epistasis were only observable under alternate conditions. As only a small number of stress conditions were tested, the high frequency of genetic interactions reported appears to be a minimum estimate of the true extent of epistasis among WGD paralogs, potentially explaining the lack of overlap with protein interaction data. As it is impossible to survey an infinite condition space, Synthetic Genetic Array (SGA) screening of yeast strains carrying double-deletions of paralog pairs was used to assess functional redundancy among a group of the remaining non-epistatic paralog pairs. The resulting interactions demonstrated functional relationships in non-epistatic paralogs only obvious upon ablation of both duplicates, suggesting that these interactions had initially been masked through redundant function. These findings ultimately suggest an advantage to retained functional overlap among whole genome duplicates that is capable of being stably maintained through millions of years of evolutionary time.

Gene regulatory networks are dynamic and continuously remodelled in response to internal and external stimuli. To understand how these networks alter cellular phenotype in response towards specific challenges, my first project sought to develop a methodology to explore how the strength of genetic interactions changes according to environmental context. Defined as sensitivity-based epistasis, the results obtained using this methodology were compared to those generated under the conventional fitness-based approach. By integrating this information with gene expression profiles and physical interaction datasets, we demonstrate that sensitivity-based epistasis specifically highlights genetic interactions with a dynamic component. Having investigated how an external stimulus regulates network dynamics, we next sought to understand of how genome positioning impacts transcription kinetics. This feat was accomplished by cloning two gene-reporter constructs, representing contrasting promoter architectures, across 128 loci along chromosome III in S.Cerevisiae. By comparing expression and noise measurements for promoters with “covered” and “open” chromatin structures against a stochastic model for eukaryotic gene expression, we demonstrate that while promoter structure regulates burst frequency (the rate of promoter activation), positional effects in turn appear to primarily modulate burst size (the number of mRNA produced per gene activation event). By integrating these datasets with information describing global chromatin structure, we suggest that the acetylation state of chromatin regulates burst size across the genome. Interestingly, this hypothesis is further supported by nicotinamide-mediated inhibition of Sir2 which would appear to modulate burst size globally across the genome.

Resolving the genetic and mechanistic bases of complex biological behaviors remains a central challenge in the post-genomic era. Among these is the emergence of interspecies cooperation, a feature common across levels of biological organization. Of the numerous examples afforded by nature, microbes arguably provide the greatest ability to connect underlying genotypes to cooperative phenotypes.

Evaluating the evolutionary role of mutations depends on an understanding of their major properties, including their rate of origin, U, and the distribution of their fitness effects, f(s). While substantial effort has been put into measuring these properties, most studies have only examined their distributions in a single context. In nature, spontaneous mutations are likely to experience heterogeneity in genetic and environmental context, and this could lead to variation in both U and f(s). My thesis investigates the changes in U and f(s) with different genetic and environmental factors in Drosophila melanogaster, in order to elucidate the nature of context-associated variation in mutational properties. Examination of condition-dependent variation in DNA repair showed that high and low conditioned individuals differ in the use of alternative repair pathways. This could ultimately lead to variance in their heritable mutation rates. However, the assumption that condition dependence in repair arises solely due to a presumed trade-off between accuracy and the energetic costs associated with different repair pathways is too simplistic. Instead, physiological considerations appear to mediate condition-dependent changes in DNA repair. Measurements of selection on individual mutations across different genetic and environment contexts showed that context-associated changes in mutational fitness effects are common. I found that heterogeneity in fitness effects across different environments result in changes to the overall mean and variance of f(s). This does not, however, seem attributable to the degree of ‘adaptedness’ of a population to a particular environment (a prediction generated by previous theoretical analysis). On the other hand, f(s) appears to be relatively robust to differences among genotypes, with epistasis averaging close to zero. This finding suggests that genetic and environmental perturbations may affect mutations differently. Overall, my thesis represents the most rigorous empirical investigation to date of the conceptual and theoretical predictions regarding the nature of context-dependent heterogeneity in U and f(s) for multicellular eukaryotes.

Taking the advantage of the high-throughput Single Nucleotide Polymorphism (SNP) genotyping technology, Genome-Wide Association Studies (GWASs) are regarded holding promise for unravelling complex relationships between genotype and phenotype. GWASs aim to identify genetic variants associated with disease by assaying and analyzing hundreds of thousands of SNPs. Traditional single-locus-based and two-locus-based methods have been standardized and led to many interesting findings. Recently, a substantial number of GWASs indicate that, for most disorders, joint genetic effects (epistatic interaction) across the whole genome are broadly existing in complex traits. At present, identifying high-order epistatic interactions from GWASs is computationally and methodologically challenging. My dissertation research focuses on the problem of searching genome-wide association with considering three frequently encountered scenarios, i.e. one case one control, multi-cases multi-controls, and Linkage Disequilibrium (LD) block structure. For the first scenario, we present a simple and fast method, named DCHE, using dynamic clustering. Also, we design two methods, a Bayesian inference based method and a heuristic method, to detect genome-wide multi-locus epistatic interactions on multiple diseases. For the last scenario, we propose a block-based Bayesian approach to model the LD and conditional disease association simultaneously. Experimental results on both synthetic and real GWAS datasets show that the proposed methods improve the detection accuracy of disease-specific associations and lessen the computational cost compared with current popular methods.

Gene regulatory networks are dynamic and continuously remodelled in response to internal and external stimuli. To understand how these networks alter cellular phenotype in response towards specific challenges, my first project sought to develop a methodology to explore how the strength of genetic interactions changes according to environmental context. Defined as sensitivity-based epistasis, the results obtained using this methodology were compared to those generated under the conventional fitness-based approach. By integrating this information with gene expression profiles and physical interaction datasets, we demonstrate that sensitivity-based epistasis specifically highlights genetic interactions with a dynamic component. Having investigated how an external stimulus regulates network dynamics, we next sought to understand of how genome positioning impacts transcription kinetics. This feat was accomplished by cloning two gene-reporter constructs, representing contrasting promoter architectures, across 128 loci along chromosome III in S.Cerevisiae. By comparing expression and noise measurements for promoters with “covered” and “open” chromatin structures against a stochastic model for eukaryotic gene expression, we demonstrate that while promoter structure regulates burst frequency (the rate of promoter activation), positional effects in turn appear to primarily modulate burst size (the number of mRNA produced per gene activation event). By integrating these datasets with information describing global chromatin structure, we suggest that the acetylation state of chromatin regulates burst size across the genome. Interestingly, this hypothesis is further supported by nicotinamide-mediated inhibition of Sir2 which would appear to modulate burst size globally across the genome.

Evaluating the evolutionary role of mutations depends on an understanding of their major properties, including their rate of origin, U, and the distribution of their fitness effects, f(s). While substantial effort has been put into measuring these properties, most studies have only examined their distributions in a single context. In nature, spontaneous mutations are likely to experience heterogeneity in genetic and environmental context, and this could lead to variation in both U and f(s). My thesis investigates the changes in U and f(s) with different genetic and environmental factors in Drosophila melanogaster, in order to elucidate the nature of context-associated variation in mutational properties. Examination of condition-dependent variation in DNA repair showed that high and low conditioned individuals differ in the use of alternative repair pathways. This could ultimately lead to variance in their heritable mutation rates. However, the assumption that condition dependence in repair arises solely due to a presumed trade-off between accuracy and the energetic costs associated with different repair pathways is too simplistic. Instead, physiological considerations appear to mediate condition-dependent changes in DNA repair. Measurements of selection on individual mutations across different genetic and environment contexts showed that context-associated changes in mutational fitness effects are common. I found that heterogeneity in fitness effects across different environments result in changes to the overall mean and variance of f(s). This does not, however, seem attributable to the degree of ‘adaptedness’ of a population to a particular environment (a prediction generated by previous theoretical analysis). On the other hand, f(s) appears to be relatively robust to differences among genotypes, with epistasis averaging close to zero. This finding suggests that genetic and environmental perturbations may affect mutations differently. Overall, my thesis represents the most rigorous empirical investigation to date of the conceptual and theoretical predictions regarding the nature of context-dependent heterogeneity in U and f(s) for multicellular eukaryotes.

Thesis (Ph. D. in Human Genetics)--Vanderbilt University, May 2009. / Title from title screen. Includes bibliographical references.

Gene regulatory networks are dynamic and continuously remodelled in response to internal and external stimuli. To understand how these networks alter cellular phenotype in response towards specific challenges, my first project sought to develop a methodology to explore how the strength of genetic interactions changes according to environmental context. Defined as sensitivity-based epistasis, the results obtained using this methodology were compared to those generated under the conventional fitness-based approach. By integrating this information with gene expression profiles and physical interaction datasets, we demonstrate that sensitivity-based epistasis specifically highlights genetic interactions with a dynamic component. Having investigated how an external stimulus regulates network dynamics, we next sought to understand of how genome positioning impacts transcription kinetics. This feat was accomplished by cloning two gene-reporter constructs, representing contrasting promoter architectures, across 128 loci along chromosome III in S.Cerevisiae. By comparing expression and noise measurements for promoters with “covered” and “open” chromatin structures against a stochastic model for eukaryotic gene expression, we demonstrate that while promoter structure regulates burst frequency (the rate of promoter activation), positional effects in turn appear to primarily modulate burst size (the number of mRNA produced per gene activation event). By integrating these datasets with information describing global chromatin structure, we suggest that the acetylation state of chromatin regulates burst size across the genome. Interestingly, this hypothesis is further supported by nicotinamide-mediated inhibition of Sir2 which would appear to modulate burst size globally across the genome.