Date of Award
Master of Science (MS)
Computational Engineering and Science
Why sexual reproduction and recombination are prevalent among living organisms is one of the most intriguing questions in biology. It has been studied extensively from a multitude of perspectives ranging from multi-locus population genetics models, in-vivo and more recently in-silico systems. The analysis of complex metabolic networks in living organisms reveals that they can be decomposed into several functionally distinct sub-groups, called modules. This property of modular organization has been accepted as a general organizational feature of biological networks, and has important consequences for the evolution of biologically complex features through different combinations of simpler functions. In this light it has been shown that sexual populations can develop a form of modularity on the genetic level, called mixability, where alleles are selected for their ability to function under a wide variety of genetic contexts, much like a module.
However the functional implications of mixability still remain to be seen. We wish to assess whether mixability can develop in a simplified model of populations undergoing evolution for increased biological complexity through the construction of their genomes into simple metabolic chains. We modelled the fitness and growth of complexity in sexual and asexual populations in the presence of recurrent mutations which increase the ability of genes to interact with one another. Our results show that mixability is selected for in sexual populations when genetic diversity is high and under certain conditions gives sexual populations a competitive edge over asexual populations through increased genetic complexity. This provides a starting point for examining the effect of mixability upon growing genetic networks and its role in influencing larger scale modularity, which thus far has not been significantly explored.
Bundalovic-Torma, Cedoljub, "THE EFFECT OF SEX AND MIXABILITY ON THE EVOLUTION OF AN IDEALIZED GENETIC NETWORK" (2010). Open Access Dissertations and Theses. Paper 4221.
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