Dmadere Week 9

Methods/Results

Analyzing and Interpreting STEM Results

1. Selected one of the profiles saved in the previous step for further interpretation of the data. Each member of the group selected their own significant profile to analyze.
   • Why did you select Profile #22? In other words, why was it interesting to you?

   - I selected Profile #22 because the cluster appeared very different from the rest of the clusters. Unlike the other clusters, this profile started out as a straight line, increased, and then slowly decreased. I wanted to analyze why this was occurring and get a better understanding of why this profile exhibits these qualities. When I clicked on the profile, I noticed that each colored line representing the genes started from 0 and stayed close until around the 60min time frame where it started to increase, and then decreased at the 90min time frame, which I also wanted to analyze further

   • How many genes belong to this profile?

   - There are 179 genes assigned to Profile 22.

   • How many genes were expected to belong to this profile?

   - There were 22.9 genes expected in this profile.

   • What is the p value for the enrichment of genes in this profile?

   - The p-value for the enrichment of genes in Profile 22 is 3.4E-98 and it is significant.

2. Opened the GO list file saved for Profile 22 in Excel. Filtered data by p-value < 0.05. Then filtered data by "Corrected P-Value" column to show the corrected p-values of < 0.05.
   • How many GO terms are associated with this profile at p < 0.05?

   -There are 25 GO terms associated with this profile at p < 0.05.

   • How many GO terms are associated with this profile with a corrected p value < 0.05?

   - There are 3 GO terms associated with Profile 22 with a corrected p-value < 0.05.

3. Selected the top 6 Gene Ontology terms from filtered list (p < 0.05 not corrected) and noted whether the same GO terms are showing up with multiple clusters.
   • Looked up the definitions for each of the terms at Gene Ontology Database. In your research presentation, will discuss the biological interpretation of these GO terms. In other words, why does the cell react to cold shock by changing the expression of genes associated with these GO terms? Also, what does this have to do with the transcription factor being deleted (for the groups working with deletion strain data)?

   -Cellular response to oxidative stress (GO:0034599): Any process that results in a change in state or activity of a cell (in terms of movement, secretion, enzyme production, gene expression, etc.) as a result of oxidative stress, a state often resulting from exposure to high levels of reactive oxygen species, e.g. superoxide anions, hydrogen peroxide (H2O2), and hydroxyl radicals. Source: GOC:mah

   - Cellular oxidant detoxification (GO:0098869): Any process carried out at the cellular level that reduces or removes the toxicity superoxide radicals or hydrogen peroxide. Source: GOC:vw, GOC:dos

   - Cytoplasm (GO:0005737): All of the contents of a cell excluding the plasma membrane and nucleus, but including other subcellular structures. Source: ISBN:0198547684

   - Oxidation-reduction process (GO:0055114): A metabolic process that results in the removal or addition of one or more electrons to or from a substance, with or without the concomitant removal or addition of a proton or protons. Source: GOC:rph, GOC:jh2, GOC:ecd, GOC:jid, GOC:dhl, GOC:mlg

   - Endocytosis (GO:0006897): A vesicle-mediated transport process in which cells take up external materials or membrane constituents by the invagination of a small region of the plasma membrane to form a new membrane-bounded vesicle. Source: ISBN:0716731363, ISBN:0198506732, GOC:mah

   - Actin Cortical Patch (GO:0030479): An endocytic patch that consists of an actin-containing structure found at the plasma membrane in cells; formed of networks of branched actin filaments that lie just beneath the plasma membrane and assemble, move, and disassemble rapidly. An example of this is the actin cortical patch found in Saccharomyces cerevisiae. Source: GOC:vw, PMID:16959963, GOC:mah, ISBN:0879693568, ISBN:0879693649

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

1. Opened the gene list in Excel for the one of the significant profiles from your stem analysis. Chose a cluster with a clear cold shock/recovery up/down or down/up pattern (Profile #22).
   • Copied the list of gene IDs onto clipboard.
2. Launch a web browser and go to the YEASTRACT Database
   • On the left panel of the window, clicked on the link to Rank by TF.
   • Pasted your list of genes from your cluster into the box labeled ORFs/Genes.
   • Checked the box for Check for all TFs.
   • Accepted the defaults for the Regulations Filter (Documented, DNA binding plus expression evidence)
   • Didn't apply a filter for "Filter Documented Regulations by environmental condition".
   • Ranked genes by TF using: The % of genes in the list and in YEASTRACT regulated by each TF.
   • Clicked on the Search button.
3. Questions:
   • In results window, 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 31 transcription factors that are significant.

   • Are CIN5, GLN3, and/or HAP4 on the list? If so, what is their "% in user set", "% in YEASTRACT", and "p value".

   - CIN5: User Set - 21.47%, YEASTRACT - 1.74%, P-value - 0.996

   - GLN3: User Set - 29.38%, YEASTRACT - 2.16%, P-value - 0.880

   - HAP4: User Set - 23.16%, YEASTRACT - 3.76%, P-value - 0.0019

4. Used YEASTRACT to assist with creating gene regulatory network
   • Selected "significant" transcription factors to run model. Used 17 transcription factors and included GLN3, HAP4, and CIN5 since they are the ones that are being studied in class as well as has a significance on the Profile.
   • Copied and pasted list of transcription factors identified from Gene Regulation Matrix into both "Transcription factors" field and the "Target ORF/Genes" field
   • Used "Regulations Filter" option of "Documents", "Only DNA binding evidence"
     • Clicked on "Generate" and saved Regulation Matrix to Desktop.

Data & Files

DM_dCIN5 Profile Gene Tables

DM_dCIN5 Profile GOlist Tables

DM_dCIN5 STEM Results Presentation

DM_dCIN5.txt

DM_dCIN5 Master Excel Sheet

Acknowledgements

Dmadere (talk) 20:10, 28 October 2019 (PDT)

References

• Assignment Page
• Gene Ontology
• STEM
• YEASTRACT