Morris LMU Symposium Spring 2016

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Mathematical Modeling Shows that Gln3 Affects the Dynamics of the Gene Regulatory Network Controlling the Cold Shock Response in Saccharomyces cerevisiae

Tessa A. Morris, Kristen M. Horstmann, Brandon Klein, Ben G. Fitzpatrick, Kam D. Dahlquist Affiliations: Department of Biology, Loyola Marymount University

A gene regulatory network (GRN) consists of a set of transcription factors that regulate the level of expression of genes encoding other transcription factors. The dynamics of a GRN show how gene expression in the network changes over time. While the transcriptional regulation of the response to the environmental stress of heat shock in budding yeast, Saccharomyces cerevisiae, is well-understood, which transcription factors regulate the early response to cold shock is not fully understood. Thus, the focus of this study was to determine the GRN that controls the cold shock response in yeast and to model its dynamics. Microarray experiments were performed in the Dahlquist lab at various timepoints after cold shock (t=15, 30, and 60 minutes) to examine the gene expression patterns of both the wild type and mutant strains of yeast that had been deleted for the transcription factors Gln3. The microarray data were normalized using the limma package in R and a modified ANOVA was used to determine which genes had a log2 fold change significantly different than zero at any of the timepoints studied. The network based on the YEASTRACT database did not account for the large effect on the dynamics of several genes in the network due to the deletion of GLN3. In order to create a network structure that models the actual cellular conditions of cold shock, we have created a family of networks. This family of networks was created paring down a network with 35 genes one gene at a time to eventually create a network of 15 genes. From this method, we aim to uncover the gene regulatory network that controls the cold shock response in yeast. Our working code is available on the GRNmap page (http://kdahlquist.github.io/GRNmap/), and visualization of the network is available on GRNsight (http://dondi.github.io/GRNsight/).

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