Johnson and O'Neil LMU Symposium 2016: Difference between revisions
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'''Evaluating Hap4's Role in the Gene Regulatory Network that Controls the Response to Cold Shock in ''Saccharomyces cerevisiae'' using GRNmap''' | '''Evaluating Hap4's Role in the Gene Regulatory Network that Controls the Response to Cold Shock in ''Saccharomyces cerevisiae'' using GRNmap''' | ||
Gene expression is regulated by proteins called transcription factors which can either repress or activate a gene’s transcriptional output. 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. A MATLAB software package called GRNmap uses ordinary differential equations to model the dynamics of medium-scale GRNs from budding yeast, ''Saccharomyces cerevisiae''. The program estimates production rates, expression thresholds, and regulatory weights for each transcription factor in the network based on DNA microarray data | Gene expression is regulated by proteins called transcription factors which can either repress or activate a gene’s transcriptional output. 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. A MATLAB software package called GRNmap uses ordinary differential equations to model the dynamics of medium-scale GRNs from budding yeast, ''Saccharomyces cerevisiae''. The program estimates production rates, expression thresholds, and regulatory weights for each transcription factor in the network based on DNA microarray data. Data were obtained from a yeast strain deleted for the Hap4 transcription factor which was subjected to cold shock at 13°C for 15, 30, and 60 minutes. A modified ANOVA showed that 1794 genes had a log<sub>2</sub> fold change significantly different than zero at any of the timepoints. These genes were then submitted to the YEASTRACT database to determine which transcription factors regulated them. From this we generated 32 candidate GRNs that ranged in size from 35 genes and 102 edges to 15 genes and 28 edges. We then estimated and compared the parameter values for production rates, expression thresholds, and regulatory weights for each of the GRNs. A comparison of the actual least squares error to the minimum theoretical least squares error allowed us to evaluate which size network explains the gene expression the best. From this analysis we have gained insight into Hap4's role in the gene regulatory network that controls the cold shock response in yeast. | ||
Required word count: 250 | Required word count: 250 | ||
Revision as of 16:32, 11 February 2016
Abstract Draft
Evaluating Hap4's Role in the Gene Regulatory Network that Controls the Response to Cold Shock in Saccharomyces cerevisiae using GRNmap
Gene expression is regulated by proteins called transcription factors which can either repress or activate a gene’s transcriptional output. 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. A MATLAB software package called GRNmap uses ordinary differential equations to model the dynamics of medium-scale GRNs from budding yeast, Saccharomyces cerevisiae. The program estimates production rates, expression thresholds, and regulatory weights for each transcription factor in the network based on DNA microarray data. Data were obtained from a yeast strain deleted for the Hap4 transcription factor which was subjected to cold shock at 13°C for 15, 30, and 60 minutes. A modified ANOVA showed that 1794 genes had a log2 fold change significantly different than zero at any of the timepoints. These genes were then submitted to the YEASTRACT database to determine which transcription factors regulated them. From this we generated 32 candidate GRNs that ranged in size from 35 genes and 102 edges to 15 genes and 28 edges. We then estimated and compared the parameter values for production rates, expression thresholds, and regulatory weights for each of the GRNs. A comparison of the actual least squares error to the minimum theoretical least squares error allowed us to evaluate which size network explains the gene expression the best. From this analysis we have gained insight into Hap4's role in the gene regulatory network that controls the cold shock response in yeast.
Required word count: 250
