Understanding the Evolution of Gene Expression from a Regulatory Network Perspective

evolution of gene expression;transcriptional regulatory network;Ecology and Evolutionary Biology;Science;Molecular, Cellular, and Developmental Biology

Yang, BingZhang, Jianzhi ;

University of Michigan

关键词: evolution of gene expression;    transcriptional regulatory network;    Ecology and Evolutionary Biology;    Science;    Molecular, Cellular, and Developmental Biology;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/138702/ypauling_1.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

The evolution of transcriptional regulation has been demonstrated to be a major contributor to phenotypic evolution.One important step in transcriptional regulation is the interaction between transcription factors and their target genes, the organization of which is represented by the Transcriptional Regulatory Network (TRN).Recent studies have shown that structural properties within a TRN provide important information for understanding how different transcriptional patterns are formed in many biological systems.However, it is less clear whether or not those structural properties are also informative in understanding the evolution of transcriptional patterns.In this thesis, I examined the question of whether the number of connections for a gene in a TRN was associated with observed gene expression differences by combining published datasets from multiple related Drosophila species.Specifically, I found that increasing number of regulators (in-degree) for a gene was associated with decreasing differences in gene expression and cis regulation.Meanwhile, I found no significant relationship between the number of targets (out-degree) for a transcription factor and differences in gene expression.To assess the generality of the conclusions from Drosophila species, I inferred a whole-genome transcriptional regulatory network in Saccharomyces cerevisiae and combined it with published gene expression datasets involving multiple Saccharomyces species to examine the relationship between in-degree/out-degree and differences in gene expression.I found that increasing in-degree was associated with increasing differences in gene expression between two strains of S. cerevisiae, but no significant relationship between in-degree and differences in gene expression was detected in all comparisons between two diverged Saccharomyces species.These two studies suggest that whether and how the number of interactions for a gene within a TRN could impact the evolution of the transcription level might depend on the biological system under consideration.Finally, I examined whether and how existing genetic variants that disrupted transcriptional regulation of a yeast gene TDH3 could influence how random mutations change its expression, by introducing random mutations into 8 yeast strains each carrying a single genetic variant responsible for altering the expression level of TDH3 and quantifying both the mean expression level and expression noise for resulting mutagenized cells in each of the 8 genetic backgrounds.I found that the lab strain BY was less sensitive to random mutations on the mean expression level, compared to other genotypes carrying genetic variants.Also, I found that relationships between effects of random mutations on the mean level of expression and expression noise depend on the existing genetic variants.In addition, I found that the sensitivity to random mutations on mean level of expression was positively correlated with the expression noise for strains carrying genetic variants in the TDH3 promoter.This study demonstrates that various aspects of how random mutations alter the expression of a single gene are modified by existing genetic changes that disrupt the transcriptional regulation.. Taken together, my thesis work demonstrates that the transcriptional regulatory network provides an informative context to study the evolution of gene expression, in the sense that both the process of the accumulation of genetic variations and formation of the ultimate evolutionary patterns are potentially affected by the interactions within the network.