| Genes show different expression variation and growth fitness when responding to various environment conditions. Many studies have focused on identifying factors influencing such differences, especially in the studies of essential genes versus viable genes. Nonetheless, the need to obtain a more complete understanding of factors and their interactions influencing expression variation and fitness pleiotropy (growth defect upon gene deletion) remains a challenge.;In this dissertation, a systematic analysis on factors that affect expression variation and pleiotropy as well as their inter-relationship have been conducted using S. cerevisiae as a model. For S. cerevisiae, high-throughput technologies produce many genome-wide data, such as protein interaction, regulatory network, gene deletion, etc. With availability of such data, it was found that TATA-box and the number of TFs (transcription factors) are the most important factors influencing expression variation among four different factors: protein interaction degree, toxicity degree (the number of DNA-damaging conditions that the growth rate of the yeast deletion strain is significantly affected), TATA box, the number of TFs. In addition, the number of TFs regulating a gene was found to be an important factor influencing expression variation for both TATA-containing and non-TATA-containing genes, but with different association strength. Moreover, expression variation was significantly negatively correlated with toxicity degree only for TATA-containing genes.;Fitness pleiotropy is a measurement of the gene's importance to fitness. Two important measurements: (1) if the gene product is central in a protein interaction network, and (2) if the gene is more likely to be chromatin regulated (defined as CRE) were found to significantly affect a gene's fitness pleiotropy. Although a significant negative association between fitness pleiotropy and gene expression variation was identified, study showed that CRE could be considered as the key underlying latent variable that controls both fitness pleiotropy and expression variation resulting in their correlation.;These findings highlight the significance of both gene regulation and protein interaction networks in influencing the gene expression variation and fitness pleiotropy. Moreover, distinct mechanisms may influence gene expression variation in TATA-containing and non-TATA-containing genes, provides new insights into the mechanisms that underlie the evolution of gene expression. |
