Morris LMU Symposium Spring 2016: Difference between revisions

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Affiliations: Department of Biology, Loyola Marymount University
Affiliations: Department of Biology, Loyola Marymount University


A gene regulatory network (GRN) consists of a set of transcription factors that regulate the expression of genes encoding other transcription factors. The dynamics of a GRN show how gene expression in the network changes over time. The focus of this study was to determine the GRN that controls the cold shock response in budding yeast, ''Saccharomyces cerevisiae'', and to model its dynamics. Microarray experiments were performed in the Dahlquist lab to measure gene expression after 15, 30, and 60 minutes of cold shock for both the wild type strain and a strain deleted for the transcription factor Gln3. These data were used as input to a MATLAB software package called GRNmap, which uses ordinary differential equations to model the dynamics of a medium-scale gene regulatory network. The program estimates production rates, expression thresholds, and regulatory weights for each transcription factor in the network using a penalized least squares approach. A modified ANOVA showed that xxx genes (xx%) had a log<sub>2</sub> fold change significantly different than zero with an adjusted p value of < 0.05 at at least one timepoint for the Gln3 deletion strain. These genes were submitted to the YEASTRACT database to determine the transcription factors that regulate them. From this, a family of xxx GRNs ranging from xx genes and xx edges to xx genes and xx edges was generated. Parameter values, production rates, regulatory weights, and expression thresholds were compared for each of these GRNs. From the modeling of the network families, we have observed that the presence of absence of Gln3 affects the dynamics of the gene regulatory network controlling the cold shock response in yeast.  
A gene regulatory network (GRN) consists of a set of transcription factors that regulate the expression of genes encoding other transcription factors. The dynamics of a GRN show how gene expression in the network changes over time. The focus of this study was to determine the GRN that controls the cold shock response in budding yeast, ''Saccharomyces cerevisiae'', and to model its dynamics. Microarray experiments were performed in the Dahlquist lab to measure gene expression after 15, 30, and 60 minutes of cold shock for both the wild type strain and a strain deleted for the transcription factor Gln3. These data were used as input to a MATLAB software package called GRNmap, which uses ordinary differential equations to model the dynamics of a medium-scale gene regulatory network. The program estimates production rates, expression thresholds, and regulatory weights for each transcription factor in the network using a penalized least squares approach. A modified ANOVA showed that xxx genes (xx%) had a log<sub>2</sub> fold change significantly different than zero with an adjusted p value of < 0.05 for at least one timepoint for the Gln3 deletion strain. These genes were submitted to the YEASTRACT database to determine the transcription factors that regulate them. From this, a family of xxx GRNs ranging from xx genes and xx edges to xx genes and xx edges was generated. Parameter values, production rates, regulatory weights, and expression thresholds were compared for each of these GRNs. From the modeling of the network families, we have observed that the presence of absence of Gln3 affects the dynamics of the gene regulatory network controlling the cold shock response in yeast.  


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Revision as of 12:32, 12 February 2016

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 expression of genes encoding other transcription factors. The dynamics of a GRN show how gene expression in the network changes over time. The focus of this study was to determine the GRN that controls the cold shock response in budding yeast, Saccharomyces cerevisiae, and to model its dynamics. Microarray experiments were performed in the Dahlquist lab to measure gene expression after 15, 30, and 60 minutes of cold shock for both the wild type strain and a strain deleted for the transcription factor Gln3. These data were used as input to a MATLAB software package called GRNmap, which uses ordinary differential equations to model the dynamics of a medium-scale gene regulatory network. The program estimates production rates, expression thresholds, and regulatory weights for each transcription factor in the network using a penalized least squares approach. A modified ANOVA showed that xxx genes (xx%) had a log2 fold change significantly different than zero with an adjusted p value of < 0.05 for at least one timepoint for the Gln3 deletion strain. These genes were submitted to the YEASTRACT database to determine the transcription factors that regulate them. From this, a family of xxx GRNs ranging from xx genes and xx edges to xx genes and xx edges was generated. Parameter values, production rates, regulatory weights, and expression thresholds were compared for each of these GRNs. From the modeling of the network families, we have observed that the presence of absence of Gln3 affects the dynamics of the gene regulatory network controlling the cold shock response in yeast.

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