GV Exercise.2

Find Biomarkers for a given context

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| GV Exercise.3 ]
last edit: October 31, 2014

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AIM: From a given context to be analyzed by quantitative PCR (QPCR) in your lab, identify good biological markers (positive controls) and good reference genes (negative controls) for your future experiment, based on a low variance in similar biological conditions.

We do not have a gene list but we know the biological context

By limiting the background set to a relevant biological topic, we expect to find slightly different probes with RefGenes than when considering the whole database. The expression profile of these probes may vary in the whole biome but are relatively stable within the biological model of interest. The same approach can be used to find tissue specific or cancer type specific markers

Please keep in mind that:

• Probes identified here are only valid for the selected context and dependent on the public data used in GV (better results when exp# is higher)
• The user should always validate such candidate control probes before using them in costly experiments.

step#1: create different sample subsets relevant to the system under study

We create first 3 sample selections to analyze gene expression under oxidative stress at different levels of stringency.

• a very-specific sample-set: methyl viologen samples present in the database as a relevant subset to illustrate the 'oxydative stress' => {Methyl viologen is a herbicide that gives rise to superoxide anion in light}
• a broader sample-set: all oxidative study samples in the database
• the full Ath database context (as in ex1)

Create an Arabidopsis thaliana sample-set for methyl viologen from the 'experiment titles'

Create an Arabidopsis thaliana sample-set for oxidative from the 'experiment titles'

You can also be more specific and create an Arabidopsis thaliana sample-set for oxidative as a 'condition'

Create a full Arabidopsis thaliana sample-set

You should now have a sample selection like below

Counts will vary upon time with new additions to the GV database

step#2 search for specific probes within sample sets with the Gene perturbation search tool

Using the requested sample selections, use the Gene perturbation tool to discover probes with strong differential expression under oxidative stress

Search up to 10 markers showing at least 4 fold change UP in the Methyl Viologen samples

Search up to 10 markers showing at least 4 fold change DOWN in the Methyl Viologen samples

Search up to 100 markers showing at least 2 fold change UP in the Methyl Viologen samples

Search up to 10 markers showing at least 2 fold change UP for late oxidative stress in the oxidative-stress samples

Search up to 10 markers showing at least 2 fold change UP for late oxidative stress in whole Ath database samples

Collapse all definitions and use the search box to locate the oxidative lines

Note in the last case that the same markers may be differentially regulated in any other condition present in the sample group. We of course expect some overlap between the different stress conditions.

From each obtained result-set, create a new gene selection with the found markers using the new button and name the three lists as below

We have now identified defined context specific biomarkers for which we need matching reference probes.

step#3: run Condition Search on the Ath.Me-Viologen_4xUR under Ath.all context

Identify other conditions where the selected markers LSU1 is differentially expressed with at least 3x contrast and 0.001 confidence. Note the color of the LSU1 expression in two groups of conditions.

try it first

A quick Pubmed search returned that LSU1 is involved in sensing Sulfur deprivation .

We see here that LSU1 gets up-regulated in absence of sulfur and is strongly down-regulated in specific circadian clock experiment. Such finding can often be used to build hypotheses for wet lab experiments

step#4: run RefGenes on each sample/gene selection combination

As in Exercise#1, create Refgene sets from each gene selection and feed-back these references against the different sample selections defined above.

The aim of the experiment is to control

• wether defining references against a very limited and biased sample set (methyl viologen) identifies probes showing stable expression outside of this context.
• wether probes defined based on a very broad context (full Ath) are still qualitatively good references for a very specific sample set.

Please answer these yourself and start appreciating the power of GV when the correct questions are asked.

Download the exercise file

Try it by yourself before expanding on the right!

You need here to play with samples selections and Refgene-defined gene selections in the Search Condition perturbation tool

• download the file and open it from within genevestigator File Load Workspace link

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References:

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[ Main_Page | Genevestigator_training | Analyze_public_microarray_data_using_Genevestigator | GV Exercise.1 |
| GV Exercise.3 ]