Emmatyrnauer Week 15

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Electronic Notebook

In week 14 I produced a gene regulatory network utilizing Yeastract and GRNsight. However, this regulatory network was too large. To trim the network, I removed transcription factors one by one, each time visualizing the newly trimmed list in GRNsight. I had to visualize the trimmed network in GRNsight to ensure that there were no loose ends/floating transcription factors (i.e. transcription factors that were not connected to any others in the network). The process of removal is documented in Media: REGULATIONMATRIXFINAL_ET.zip, with the final version being #5 (this media file has also been linked to on Emmatyrnauer Week 14 as it allowed Dr. Dahlquist to check over the network and provide me with the initial unweighted input file for GRNsight ( 17-genes_39-edges_teamINT_Sigmoid_estimation.xlsx) on my user talk page. When opened in GRNsight, this input file produced Figure 1. In this figure, you are able to visualize the presence of interactions between genes. However, the nature of these interactions cannot be understood. That is, the magnitude of the interactions and whether or not they are induction or repression. So, Matlab was utilized to create a weighted network file (within Media:GRNsight_inputoutput_excelandimages.zip‎) as well as individual .jpg images for each gene (Media:Emmat_gene_jpg_matlab.zip). The output matrix file was opened in GRNsight and produced Figure 2. Pink arrows indicate induction/upregulation while blue lines with bars indicate repression/downregulation. It appears that most interactions are repression of other genes and that MSN2 is largely responsible for inhibiting many of the genes belonging to this network. Furthermore, some genes are regulated by one gene while others are regulated by multiple (Fig. 2). It is also notable that some of the genes that are repressed, are also induced (Fig. 2). This suggests a form of very specific regulation where the cell may be sensitive to subtle changes in expression of these genes. As a result, the cell utilizes differing pathways for their regulation.

Figure 1. Unweighted network
Figure 2. Weighted network

Acknowledgements

  1. Lights, Camera, InterACTION! for collaboration in the creation of the group presentation and paper.
  2. Dr. Dahlquist for assisting in the alteration of the significant genes excel spreadsheet to create an input file for Matlab (including the deletion and insertion of genes).
  3. Yeastract for determining the most significant transcription factors in profile 45 of wild type data.
  4. Matlab for creating the output file which was used to create weighted gene regulation map.
  5. GRNsight for generation of gene map (both weighted and unweighted).
  6. While I worked with the people and programs noted above, this individual journal entry was completed by me and not copied from another source.

References

  1. YEASTRACT. Retrieved December 7, 2017, from http://www.yeastract.com/formgenerateregulationmatrix.php
  2. GRNsight (2017) Retrieved December 7, 2017, from http://dondi.github.io/GRNsight/
  3. Matlab. Retrieved December 7, 2017, from LMU's computer lab (https://www.mathworks.com/products/matlab.html)


Links

  1. My User Page
  2. List of Assignments
  3. List of Journal Entries
  4. List of Shared Journal Entries
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