Why don't the modules dominate - Investigating the Structure of a Well-Known Modularity-Inducing Problem Domain

Wagner's modularity inducing problem domain is a key contribution to the study of the evolution of modularity, including both evolutionary theory and evolutionary computation. We study its behavior under classical genetic algorithms. Unlike what we seem to observe in nature, the emergence of modularity is highly conditional and dependent, for example, on the eagerness of search. In nature, modular solutions generally dominate populations, whereas in this domain, modularity, when it emerges, is a relatively rare variant. Emergence of modularity depends heavily on random fluctuations in the fitness function, with a randomly varied but unchanging fitness function, modularity evolved far more rarely. Interestingly, high-fitness non-modular solutions could frequently be converted into even-higher-fitness modular solutions by manually removing all inter-module edges. Despite careful exploration, we do not yet have a full explanation of why the genetic algorithm was unable to find these better solutions

Improving Scalability of Evolutionary Robotics with Reformulation

Creating systems that can operate autonomously in complex environments is a challenge for contemporary engineering techniques. Automatic design methods offer a promising alternative, but so far they have not been able to produce agents that outperform manual designs. One such method is evolutionary robotics. It has been shown to be a robust and versatile tool for designing robots to perform simple tasks, but more challenging tasks at present remain out of reach of the method. In this thesis I discuss and attack some problems underlying the scalability issues associated with the method. I present a new technique for evolving modular networks. I show that the performance of modularity-biased evolution depends heavily on the morphology of the robot’s body and present a new method for co-evolving morphology and modular control. To be able to reason about the new technique I develop reformulation framework: a general way to describe and reason about metaoptimization approaches. Within this framework I describe a new heuristic for developing metaoptimization approaches that is based on the technique for co-evolving morphology and modularity. I validate the framework by applying it to a practical task of zero-g autonomous assembly of structures with a fleet of small robots. Although this work focuses on the evolutionary robotics, methods and approaches developed within it can be applied to optimization problems in any domain

INVESTIGATING THE GENETIC BASIS OF AND PLASTICITY IN ECOLOGICALLY RELEVANT PHENOTYPES IN AFRICAN CICHLIDS

Understanding the generation of phenotypic variation by linking it to genetic variation has long been a focus of evolutionary biology; this framework has successfully been implemented in a variety of studies across the tree of life1,2. However, our understanding of the phenotype remains incomplete until we account for a myriad of interactions that influence the genotype-phenotype map, including interactions between traits (TxT), interactions between genes and the environment (GxE), as well as the ways in which various types of interactions are nested within and build upon one another (e.g., (TxT)xG). My dissertation aims to contribute to filling this gap by dissecting the interactions that influence variation in ecologically-relevant phenotypes in a model adaptive radiation: African cichlid fish. We utilize a stereotypical ecomorphological axis of variation, in which benthic fish scrape and bite prey off the rocky substrate while pelagic fish suction prey out of the water column3. Chapter 1 focuses predominantly on understanding the genetics that underlie variation across disparate anatomical units which relate to both the feeding and locomotive systems in these fish (i.e. a [[TxT]xG] interaction). We found that the genotype–phenotype map for fin shape is largely distinct from other morphological characters including body and craniofacial shape. These data suggest that key aspects of fin, body and jaw shape are genetically modular and that the coordinated evolution of these traits in cichlids is more likely due to common selective pressures than to pleiotropy or linkage. Chapter 2 dissects the genetics underlying those same anatomical units across environments, representing a more complex model of putative interactions (i.e. [[[TxT]xG]xE]). In more specific terms, this chapter aims to understand the genetic basis of phenotypic plasticity, We found a substantial degree of modularity in the plastic responses at both the morphological and genetic levels. In all, our data provide minimal support for the existence of global regulators of plasticity, serve as an important step toward further characterizing the genetic basis of plasticity in cichlids, and provide a list of candidate loci for future functional analyses. Chapter 3 delves more into a specific GxE interaction in craniofacial morphology, and for the first time in a vertebrate system tests the functional capacity of a signal transduction pathway to mediate the magnitude of a plastic response. We verify important roles for Hh signaling in this response, thus filling important gaps in the field. Together, my dissertation demonstrates how a broadly integrative approach to evolutionary biology can allow us to layer multiple lines of empirical evidence onto strong theoretical frameworks and further generate insights into the production and maintenance of real-world variation

The λ Red Proteins Promote Efficient Recombination between Diverged Sequences: Implications for Bacteriophage Genome Mosaicism

Genome mosaicism in temperate bacterial viruses (bacteriophages) is so great that it obscures their phylogeny at the genome level. However, the precise molecular processes underlying this mosaicism are unknown. Illegitimate recombination has been proposed, but homeologous recombination could also be at play. To test this, we have measured the efficiency of homeologous recombination between diverged oxa gene pairs inserted into λ. High yields of recombinants between 22% diverged genes have been obtained when the virus Red Gam pathway was active, and 100 fold less when the host Escherichia coli RecABCD pathway was active. The recombination editing proteins, MutS and UvrD, showed only marginal effects on λ recombination. Thus, escape from host editing contributes to the high proficiency of virus recombination. Moreover, our bioinformatics study suggests that homeologous recombination between similar lambdoid viruses has created part of their mosaicism. We therefore propose that the remarkable propensity of the λ-encoded Red and Gam proteins to recombine diverged DNA is effectively contributing to mosaicism, and more generally, that a correlation may exist between virus genome mosaicism and the presence of Red/Gam-like systems

Genetic Interactions and Gene-by-Environment Interactions in Evolution

The phenotypic effect of a mutation depends on both genetic interactions (G×G) and gene-by-environment interactions (G×E). G×G and G×E can distort the additive relationship between genotypes and phenotypes and complicate biological and biomedical studies. Understanding the patterns and mechanisms of these interactions is important for predicting evolutionary trajectories, designing plant and animal breeding strategies, detecting “missing heritability”, and guiding “personalized medicine”. In this thesis, I study how G×G and G×E affect mutational effects, including developing new methods and new models. Recent advancements in high-throughput DNA sequencing and high-throughput phenotyping provide powerful tools to study the relationships among genotypes, phenotypes, and the environment at unprecedented scales. Therefore, I take advantage of several published large datasets in my study, each containing hundreds to thousands of different genotypes of model organisms and their corresponding phenotypes in tens of environments. In Chapter 2, I report some general patterns of G×E and demonstrate the importance of considering potential environmental variations in mapping quantitative trait loci. In Chapter 3, I report how the environment affects diminishing returns epistasis and propose a modular life model to explain the patterns of diminishing returns. In Chapter 4, I propose and demonstrate that genetic dominance is a special case of diminishing returns epistasis. In Chapter 5, I report how and why the relationship between growth rate (r) and carrying capacity (K) in density-dependent population growth varies across environments. In Chapter 6, I demonstrate the existence of an intermediate optimal mating distance for hybrid performance in three model organisms. Overall, I find that large genomic and phenomic data are useful resources to address classical genetic questions, such as the origin of dominance (Chapter 4), the relationship between r and K (Chapter 5), and presence of an optimal mating distance (Chapter 6). The environment is a key player in the phenotypic effects of mutations, but it is also a high-dimension complex system that is hard to quantify. In this thesis, I define environment quality (Q) as the average fitness of many different genotypes measured in the environment. I demonstrate that Q is useful in studying how the environment affects additive (Chapter 3), interactive (Chapters 3 and 4), and pleiotropic mutational effects (Chapter 5). Many classical theories and models were developed based on observations made in a single environment, and they are often insufficient to explain across-environment observations. Studying across-environment effects provides valuable information for testing old models and for designing new models when old models fail. I conclude that studying G×G and G×E shed light on underlying biological mechanisms.PHDEcology and Evolutionary BiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144160/1/xinzhuw_1.pd

Open questions in the social lives of viruses

Social interactions among viruses occur whenever multiple viral genomes infect the same cells, hosts, or populations of hosts. Viral social interactions range from cooperation to conflict, occur throughout the viral world, and affect every stage of the viral lifecycle. The ubiquity of these social interactions means that they can determine the population dynamics, evolutionary trajectory, and clinical progression of viral infections. At the same time, social interactions in viruses raise new questions for evolutionary theory, providing opportunities to test and extend existing frameworks within social evolution. Many opportunities exist at this interface: Insights into the evolution of viral social interactions have immediate implications for our understanding of the fundamental biology and clinical manifestation of viral diseases. However, these opportunities are currently limited because evolutionary biologists only rarely study social evolution in viruses. Here, we bridge this gap by (1) summarizing the ways in which viruses can interact socially, including consequences for social evolution and evolvability; (2) outlining some open questions raised by viruses that could challenge concepts within social evolution theory; and (3) providing some illustrative examples, data sources, and conceptual questions, for studying the natural history of social viruses

Functional innovation from changes in protein domains and their combinations

Domains are the functional building blocks of proteins. In this work we discuss how domains can contribute to the evolution of new functions. Domains themselves can evolve through various mechanisms, altering their intrinsic function. Domains can also facilitate functional innovations by combining with other domains to make novel proteins. We discuss the mechanisms by which domain and domain combinations support functional innovations. We highlight interesting examples where changes in domain combination promote changes at the domain level

Neural Circuit Mechanisms Underlying Behavioral Evolution in Drosophila

Courtship rituals serve to reinforce reproductive barriers between closely related species. Several species in the Drosophila melanogaster subgroup exhibit pre-mating isolation due, in part, to the fact that D. melanogaster females produce 7,11-heptacosadiene (7,11-HD), a pheromone that promotes courtship in D. melanogaster males but suppresses it in D. simulans, D. yakuba, and D. erecta males. Here we compare pheromone-processing pathways across species to define how males endow 7,11-HD with the opposite behavioral valence to underlie species discrimination. We first show that D. melanogaster and D. simulans males detect 7,11-HD using the homologous peripheral sensory neurons, but this signal is differentially propagated to the P1 neurons that control courtship behavior. A change in the balance of excitation and inhibition onto courtship-promoting neurons transforms an excitatory pheromonal cue in D. melanogaster into an inhibitory one in D. simulans. Our results reveal how species-specific pheromone responses can emerge from conservation of peripheral detection mechanisms and diversification of central circuitry and suggest how evolution can exploit flexible circuit nodes to generate behavioral variation. To investigate if changes in the balance of excitation and inhibition at this node evolved repeatedly, we began characterizing the pheromone processing pathways in D. yakuba and D. erecta, two species we believe derived their aversion to 7,11-HD independently from D. simulans. This comparison provides a rare opportunity to explore the neural basis for parallel behavioral evolution. Finally, we observed differences in the olfactory and gustatory pathways D. melanogaster and D. simulans males use for sex discrimination. In males of both species, the male-specific volatile pheromone, cVA, activates a conserved sensory pathways and suppresses male courtship. However, 7-T, the major cuticular pheromone produced by all males in the D. melanogaster subgroup and by D. simulans females, plays a differential role in regulating male courtship across species – 7-T suppresses courtship in D. melanogaster males, but neither promotes nor inhibits courtship in D. simulans males. A difference in either detection of 7-T by peripheral sensory neurons or propagation of this signal to higher brain regions results in this pheromone activating courtship-suppressing mAL neurons in D. melanogaster males, but not D. simulans males. Together, these studies represent the first systematic comparison of neural circuits across Drosophila species and mark a new advance in the study of behavioral evolution by revealing how changes in central circuitry can alter discrete behaviors

The cichlid oral and pharyngeal jaws are evolutionarily and genetically coupled

Evolutionary constraints may significantly bias phenotypic change, while “breaking” from such constraints can lead to expanded ecological opportunity. Ray-finned fishes have broken functional constraints by developing two jaws (oral-pharyngeal), decoupling prey capture (oral jaw) from processing (pharyngeal jaw). It is hypothesized that the oral and pharyngeal jaws represent independent evolutionary modules and this facilitated diversification in feeding architectures. Here we test this hypothesis in African cichlids. Contrary to our expectation, we find integration between jaws at multiple evolutionary levels. Next, we document integration at the genetic level, and identify a candidate gene, smad7, within a pleiotropic locus for oral and pharyngeal jaw shape that exhibits correlated expression between the two tissues. Collectively, our data show that African cichlid evolutionary success has occurred within the context of a coupled jaw system, an attribute that may be driving adaptive evolution in this iconic group by facilitating rapid shifts between foraging habitats, providing an advantage in a stochastic environment such as the East African Rift-Valley

Directed evolution of an HIV-1 LTR specific recombinase for anti-retroviral therapy- a proof of concept study

The prospect of the work presented in this thesis has been to engineer Cre recombinase to recognize and recombine a sequence from an HIV-1 Long Terminal Repeat (LTR), characterize the recombination proficiency of the evolved recombinase in mammalian cells and explore the potential of the recombinase for a novel antiretroviral strategy