Dbashour Week 14

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Electronic Notebook

Week 8 Corrections

  • put electronic notebook in the past tense.
  • switched the Bonferroni and B-H p value numbers
  • recorded number of replicates, number of NA replaced, and strain
  • updated summary paragraph
  • incorporated interpretation of p values of NSR1 and ADH1

Week 10 Corrections

  • put electronic notebook in the past tense.
  • added template
  • added summary paragraph
  • added stem worksheet
  • made name of powerpoint more specific with initials and strain name
  • added GO term references

Week 10 Continued

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. We will explore this using the YEASTRACT database.

  1. I opened the gene list in Excel for profile 45 of my stem analysis. I chose this cluster because it had a cold shock/recovery up/down or down/up pattern and it was one of the largest clusters.
    • I then copied the list of gene IDs onto my clipboard.
  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 my list of genes from my chosen cluster into the box labeled ORFs/Genes.
    • Check the box for Check for all TFs.
    • Accept the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
    • Do not apply a filter for "Filter Documented Regulations by environmental condition".
    • Rank genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
    • Click the Search button.
  3. Answer 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"?
    • There are 30 green or significant transcription factors.
      • I copied the table of results from the web page and pasted it into a new Excel workbook to preserve the results.
        • I upload the Excel file to Box and link to it below in the deliverables section of this wiki, naming it "Yeastract_Results_DB_Gene_hAPI.
        • My transcription factor is on the list. It's % in user set is 0.3085%, its % in yeastract is 0.1044%, and its p value is 1E-13.
  4. For the mathematical model and GRNsight, we need to define a gene regulatory network of transcription factors that regulate other transcription factors. We can use YEASTRACT to assist us with creating the network. We want to generate a network with approximately 15-30 transcription factors in it.
    • I chose 15 of the significant transcription factors on my list, adding HAP4 since it was not already on the list and CIN5. I chose these transcription factors among the rest because they are all significant and I kept in mind their % in user set, % in yeastract, and p value. All 15 TFs are listed below.
      • ACE2
      • CIN5
      • GLN3
      • HAP4
      • MSN2
      • PDR1
      • PDR3
      • SFP1
      • SWI5
      • UME6
      • YAP1
      • YHP1
      • YLR278C
      • YOX1
      • ZAP1
    • I then went to the link Generate Regulation Matrix on the yeastract database and copied and pasted the list of transcription factors above into both the "Transcription factors" field and the "Target ORF/Genes" field.
    • We are going to use the "Regulations Filter" options of "Documented", "Only DNA binding evidence"
      • Click the "Generate" button.
      • In the results window that appears, click on the link to the "Regulation matrix (Semicolon Separated Values (CSV) file)" that appears and save it to your Desktop. Rename this file with a meaningful name so that you can distinguish it from the other files you will generate.


Visualizing Your Gene Regulatory Networks with GRNsight

I will analyze the regulatory matrix files I generated above in Microsoft Excel and visualize them using GRNsight to determine which one will be appropriate to pursue further in the modeling.

  1. First I need to properly format the output files from YEASTRACT. I will repeat these steps for each of the three files I generated above.
    • Open the file in Excel. It will 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. Then went to the "Data" tab and selected "Text to columns". In the Wizard that appears, I selected "Delimited" and clicked "Next". In the next window, I selected "Semicolon", and clicked "Next". In the next window, leave the data format at "General", and click "Finish". This should now look 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 are connected to at least one of the other transcription factors by making sure that there is at least one "1" in a row or column for that transcription factor. If a factor is not connected to any other factor, it was deleted, making sure that I still had somewhere between 15 and 30 transcription factors in my network after this pruning.
      • I only delete the transcription factor if there are all zeros in its column AND all zeros in its row. You may find visualizing the matrix in GRNsight (below) can help you find these easily.
    • 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 you new worksheet and clicked on the A1 cell in the upper left. I selected "Paste special" from the "Home" tab. In the window that appears, I checked the box for "Transpose". This will paste your data with the columns transposed to rows and vice versa. This is necessary because we want the transcription factors that are the "regulatORS" across the top and the "regulatEES" along the side.
    • The labels for the genes in the columns and rows need to match. Thus, I deleted the "p" from each of the gene names in the columns. I 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 alphabatize 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.
      • Then I 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 it.
  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 has the "network" worksheet in it that I formatted above. If the file has been formatted properly, GRNsight should automatically create a graph of your network. I moved the nodes (genes) around until I got a layout that I liked and took a screenshot of the results and pasted it into my powerpoint presentation.

Summary of what you need to turn in for the individual Week 10 assignment

  1. Your individual journal page should have an electronic lab notebook recording your work. This includes the detailed methods specific to your analysis, your result files, the answers to any questions posed in the protocol above, a scientific conclusion, and the acknowledgments and references sections. Don't forget your paragraph which is a biological interpretation of your stem results.
  2. Upload your updated Excel spreadsheet to the wiki that has today's manipulations in it. Use the same filename as before so that the download link that you already (previous versions will still be available in the history).
  3. Append the screenshots of the stem results to the PowerPoint presentation that contains the p value table that you created for the Week 8 assignments. Each slide in the presentation should have a meaningful title that describes the main message of the slide.
  4. Zip together all of the tab-delimited text files that you created for and from stem and upload them to the wiki.
    • the file that was saved from your original spreadsheet that you used to run stem
    • each of the genelist and GOlist files for each of your significant profiles.
  5. Write a paragraph-length conclusion for this week's exercise.

Deliverables

DGLN3 ANOVA/Stem
DGLN3 ppt Dina
DGLN3 Gene List and GO list
Yeastract TF List
GRNmap dGLN3 input
GRNmap dGLN3 output

Summary

This week, I continued the methods for the Week 10 assignment, with the goal of retrieving a network model that can be put into GRNsight and visualized. I created both a black and white version as well as a colored version, with the help of Dr. Dahlquist, that shows the magnitude and direction of the expression in the network. I did this by choosing profile 45 to interpret and analyze and found a list of transcription factors associated with this profile through the website YEASTRACT database. This list is what I used for the network. Once the .xlsx file was ready and completed, I inputted it into GRNsight and received a network model in black and white. Then Dr. Dahlquist assisted in fixing my files to be formatted in a way that will make it usable in GRNsight in color as opposed to black and white. These input and output files are located in the deliverables of this wiki and screenshots of the network can be found in the powerpoint of this wiki.

Acknowledgements

  1. Recieved help from both Dondi and Dr. Dahlquist from feedback given and instructions given in class.
  2. Copied and modified the instructions from Week 8 and Week 10 as well as retrieved deliverable file from Week 8
  3. Texted the data analyst group chat for questions

While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.
Dbashour (talk) 13:20, 9 December 2017 (PST)

References

  1. Dahlquist, K. D., Dionisio, J. D. N., Fitzpatrick, B. G., Anguiano, N. A., Varshneya, A., Southwick, B. J., & Samdarshi, M. (2016). GRNsight: a web application and service for visualizing models of small-to medium-scale gene regulatory networks. PeerJ Computer Science, 2, e85.
  2. LMU BioDB 2017. (2017). Week 14. Retrieved November 28, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_14
  3. LMU BioDB 2017. (2017). Week 8. Retrieved November 29, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_8
  4. LMU BioDB 2017. (2017). Week 10. Retrieved November 29, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10
  5. Teixeira, M. C., Monteiro, P. T., Guerreiro, J. F., Gonçalves, J. P., Mira, N. P., dos Santos, S. C., ... & Madeira, S. C. (2013). The YEASTRACT database: an upgraded information system for the analysis of gene and genomic transcription regulation in Saccharomyces cerevisiae. Nucleic acids research, 42(D1), D161-D166.

Dina Bashoura

Biological Databases Homepage

List of Assignments

List of Individual Journal Entries

List of Shared Journal Entries

List of Final Assignments

List of Team Journal Assignments

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