Evolutionary Systems Biology.

By analyzing complex biological networks, I explore the nascent field of systems biology to address some of the most long-lasting and difficult questions in genetics and evolution. First, I study modular structure and test whether the modular organization in cellular function arises from modularity in the underlying molecular interaction networks. I show that although protein interaction networks are highly modular, there is little evidence to suggest that these network modules correspond to functional units or that they are evolutionarily conserved. I demonstrate that network modules can originate simply as a byproduct of gene duplication. Then, I investigate another systems level feature, redundancy, the evolutionary maintenance of which is puzzling. I infer that 37-47% of reactions are functionally redundant in E. coli and yeast metabolic networks, but the majority of them are preserved because they are efficiently used under different conditions or their loss causes an immediate fitness reduction. These results challenge the adaptive backup hypothesis and suggest that genetic robustness is likely an evolutionary byproduct. Subsequently, I study the genomic pattern of pleiotropy, another systems attribute of genes. A low level of pleiotropy is observed for the majority of genes in multiple species. A greater per-trait effect size is also observed for genes affecting more traits, which leads to the highest rate of adaptation for organisms of intermediate complexity. These findings suggest that pleiotropy not only allowed but may have also promoted the origin of complexity. Lastly, I apply the systems approach to study protein evolutionary rate. Simulating thousands of nutritional conditions using metabolic networks, I find that there is no condition or combination of conditions for which the gene importance correlates well with the observed gene evolutionary rate. It suggests that the weakness of the empirical correlation between gene importance and evolutionary rate is factual rather than artifactual. Together, my studies using systems approach deepen our understanding of the genetic systems and provide fresh perspectives on the fundamental characteristics of life.PhDEcology and Evolutionary BiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/77868/1/zcwang_1.pd