JP Feb 04 16

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Julia Preziosi

Big Picture Questions:

1. What do we want out of our research ; what would be a perfect outcome? How would we get there?

What's triggered in the first step of the postprandial organ increase cascade in the small intestine. A gene or combination of genes which is/are differentially regulated after feeding. Comparing pre- and postprandial gene normalized expressions. Narrowing the differentially expressed genes by process. Narrow by what's present in other research at what time points. We don't know if the gene we want continues expression the whole time of digestion (regulation) or just triggers an initial response. We don't know if the process turns a gene off to allow the response, or turns a gene on.

Need to figure out what kinds of genes / what biological function is important - transporter? DNA modifier? Cell signaling pathways; ligand and receptor. Could be that ligand and receptor already produced. G protein activates mRNA transcription production for expressed genes - triggered by transcription activator (is it already there or is G protein initiating cascade that turns on keystone transcription factor, turns on a whole bunch more. Proteins involved in uptake ___(source)___ that lead to size growth? Lipid uptake?

  • Transcript for transcription factor (hormone responsive (extracellular or protein binding inside -> transcription factor (consequence seen only))).

2. What are we going to do with each of our 12 data sets to evaluate & treat it later?

We have normalized data. We need to analyze differential expression. We need to confirm that we can find intestine specific genes in all 6 samples. Serosa v Mucosa specific?

Validate if we sampled as expected - are the 6 samples comparable? Look for housekeeping genes specific to small intestine, mucosa.

Determine which tissue type is present in our sample. What is the dendigram telling us? Threshold of grouping. "Limit data to interesting genes" in the DESeq - what did this do? Only shows us differently expressed genes. Separate out statistically interesting from biologically interesting. (Does the DESeq throw out ones that are present in one condition and absent in another, or call them 0 expressed). Ask for the transcription factors first, then look at expression. Gene ontology terms.

Correlation: Figure from Feb 02 16; what variables could we correlate? Plot points x y axis and do a regression, find correlation coefficient (R^2) - how well does the line explain the relationship between the data, how well do the points fit? Slope shows positive / negative / no correlation.

We can correlate one gene to another, to see which groups respond similarly. Change together.