Emmatyrnauer Week 14

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Electronic notebook for the continuation of Week 10 Data Analysis

Using YEASTRACT to Infer which Transcription Factors Regulate a Cluster of Genes

In the previous analysis using STEM, we found a number of gene expression profiles (aka clusters) which grouped genes based on similarity of gene expression changes over time. The implication is that these genes share the same expression pattern because they are regulated by the same (or the same set) of transcription factors. I explored this using the YEASTRACT database.

  1. I opened the gene list in Excel for the one of the significant profiles from my stem analysis (profile 45). I chose this cluster because it has a clear cold shock/recovery up/down pattern. It is also a large cluster.
    • I copied the list of gene IDs from my clipboard (C6:C585).
  2. I launched a web browser and went to the YEASTRACT database.
    • On the left panel of the window, I clicked on the link to Rank by TF.
    • I pasted the list of genes from the cluster (profile 45) into the box labeled ORFs/Genes.
    • I checked the box for Check for all TFs.
    • I accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
    • I did not apply a filter for "Filter Documented Regulations by environmental condition".
    • I ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
    • I clicked the Search button.
  3. I answered the following questions:
    • In the results window that appears, the p values colored green are considered "significant", the ones colored yellow are considered "borderline significant" and the ones colored pink are considered "not significant". How many transcription factors are green or "significant"?
      • 23 transcription factors are green/significant
    • I copied the table of results from the web page and pasted it into a new Excel workbook to preserve the results.
      • I uploaded the Excel file to wiki linked to it here: Media:Yeastract_profile45results_preserved_emmat.xlsx.
      • Is your transcription factor on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value". (Note: I didn't answer this because I was assigned the wt strain).
  4. For the mathematical model and GRNsight, I needed to define a gene regulatory network of transcription factors that regulatde other transcription factors. I used YEASTRACT to assist me with creating the network. I wanted to generate a network with approximately 15-30 transcription factors in it.
    • I selected from this list of "significant" transcription factors, which ones I was going to use to run the model. I used these transcription factors and added GLN3 because it was not already in my list. Justification: I chose all of the significant transcription factors from profile 45 because there were less than 30 and this would provide extra transcription factors for the network just in case some did not have connections to any of the others. List of transcription factors: ACE2, ARG80, GAT3, GCR2, GLN3, HAP4, INO4, MIG2, MSN2, NDT80, PDR3, SFP1, STB5, SUT1, UME6, YAP1, YHP1, YLR278C, and YOX1
    • I went back to the YEASTRACT database and followed the link to Generate Regulation Matrix.
    • I copied and pasted the list of transcription factors I identified into both the "Transcription factors" field and the "Target ORF/Genes" field. I had to delete the spaces before each of the names for the regulatory network to generate properly.
    • I used the "Regulations Filter" options of "Documented", "Only DNA binding evidence"
      • I clicked the "Generate" button.
      • In the results window that appeared, I clicked on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appeared and saved it to my Desktop. I renamed this file to "RegulationMatrix_yeastract_week10etf"

Visualizing My Gene Regulatory Network with GRNsight

I analyzed the regulatory matrix file I generated above in Microsoft Excel and visualized it using GRNsight.

  1. First I needed to properly format the output file from YEASTRACT.
    • I opened the file in Excel. It did not open properly in Excel because a semicolon was used as the column delimiter instead of a comma. To fix this, I selected the entire Column A. I then went to the "Data" tab and selected "Text to columns". In the Wizard that appeared, I selected "Delimited" and clicked "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, I left the data format at "General", and clicked "Finish". This now looked like a table with the names of the transcription factors across the top and down the first column and all of the zeros and ones distributed throughout the rows and columns. This is called an "adjacency matrix." If there is a "1" in the cell, that means there is a connection between the trancription factor in that row with that column.
    • I saved this file in Microsoft Excel workbook format (.xlsx).
    • I checked to see that all of the transcription factors in the matrix were connected to at least one of the other transcription factors by making sure that there was at least one "1" in a row or column for that transcription factor. If a factor was not connected to any other factor, I deleted its row and column from the matrix ( RIM101 and ASG1 were deleted). I made sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning (19).
      • I only deleted the transcription factor if there were all zeros in its column AND all zeros in its row.
    • For this adjacency matrix to be usable in GRNmap (the modeling software) and GRNsight (the visualization software), I needed to transpose the matrix. I inserted a new worksheet into my Excel file and named it "network". I went back to the previous sheet and selected the entire matrix and copied it. I went to my new worksheet and clickeded on the A1 cell in the upper left. I selected "Paste special" from the "Home" tab. In the window that appeared, I checked the box for "Transpose". This pasted my data with the columns transposed to rows and vice versa. This is necessary because I wanteded the transcription factors that were the "regulatORS" across the top and the "regulatEES" along the side.
    • The labels for the genes in the columns and rows needed to match. Thus, I deleted the "p" from each of the gene names in the columns. I also adjusted the case of the labels to make them all upper case.
    • In cell A1, I copied and pasted the text "rows genes affected/cols genes controlling".
    • Finally, for ease of working with the adjacency matrix in Excel, I wanted to alphabetize the gene labels both across the top and side.
      • I selected the area of the entire adjacency matrix.
      • I clicked the Data tab and clicked the custom sort button.
      • I sorted Column A alphabetically, being sure to exclude the header row.
      • I then sorted row 1 from left to right, excluding cell A1. In the Custom Sort window, I clicked on the options button and selected sort left to right, excluding column 1.
    • I named the worksheet containing my organized adjacency matrix "network" and Saved.
  2. Now I visualized what these gene regulatory networks look like with the GRNsight software.
    • I went to the GRNsight home page.
    • I selected the menu item File > Open and selected the regulation matrix .xlsx file that had the "network" worksheet in it that I formatted above. GRNsight automatically created a graph of my network. I moved the nodes (genes) around until you got a layout that I liked and took a screenshot of the results. I pasted it into my PowerPoint presentation from week 10 and uploaded a new version of the powerpoint including this screenshot to wiki: Media:Wt_profileimage_presentation_emmat.pptx

Conclusion

For the assignment this week, I used the YEASTRACT database to determine the connection between the regulation of different genes from the profile 45 genelist of the wild type microarray data. Yeastract allowed me to identify similarities in the expression pattern (through transcription factors) of the different genes. From profile 45, 23 transcription factors were identified as significant (these transcription factors regulated the most genes in the genelist of profile 45). I then used YEASTRACT to generate a regulation matrix of the 23 transcription factors--i also added GLN3 per the instructions. Finally, I made some adjustments to this regulation matrix (which was downloaded as a CSV file) to allow for it to be readable by GRNsight. I opened it in GRNsight which generated a graph of my network. This network graphically depicted the connections between the different genes.

Acknowledgements

  1. Dr. Dahlquist for teaching and assisting me with the data analysis
  2. The data analyst guild for assisting with the data analysis
  3. I copied and modified the instructions from the Week 10 assignment page.

While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source. Emmatyrnauer (talk) 19:38, 4 December 2017 (PST)

References

  1. LMU BioDB 2017. (2017). Week 10. Retrieved December 4, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10
  2. YEASTRACT. Retrieved December 4, 2017, from http://www.yeastract.com/formgenerateregulationmatrix.php
  3. GRNsight (2017) Retrieved December 4, 2017, from http://dondi.github.io/GRNsight/

Links

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