Microarray Gene Analysis Coursework Questions and Answers

Gene microarray systems and readout

You do not need to use RStudio to answer Any of the following coursework questions.

 

(i.) Gene microarray systems comprise either “one colour” or “spotted” arrays. State which of these approaches can be used to study two samples simultaneously on the same microarray (1 mark).

 

What readout results from this array approach? (1 mark) 

 

The following Table appears in a research publication showing data for 4 genes from a one-colour microarray experiment where the authors have compared a drug responsive control cancer cell line A with a drug resistant cell line B: 

 

(ii.) Explain what is meant by the term “probeset” (Column 4 in the Table) in the one-colour microarray procedure. (4 marks)

 

(iii.) Use the open-access resource Gene Cards to determine the three missing gene descriptions in Column 9 of the Table. (3 marks)

 

(iv.) The researchers used biological triplicate samples from each of the two cancer cell lines to generate the mean intensity data for the Table (Columns 1, 2). How does a biological replicate differ from a technical replicate?  (2 marks)

 

(v.) What Quality Control (QC) step can be performed to view such triplicate array data in order to check it is of a good enough standard for differential expression analysis? (1 mark)

 

(vi.) State the two processes that are used to correct microarray raw intensity data in order to eliminate non-biological differences (such as  brightness bias or spatial bias) between microarrays and to allow graphical display of non-skewed expression data within a manageable scale. (2 marks)

 

(vii.) Using their microarray intensity data the researchers obtained the list of genes in the Table  that were differentially-expressed between the two cell lines by using a statistical test to generate a p value for every gene, as well as by analysing their fold increase.

 

Give an example of a statistical test that is applicable to compare gene expression in these two cell lines using their triplicate intensity data (1 mark).

 

Why is it very important to adjust p value results for multiple testing in microarray analysis? (2 marks)

 

 Provide a named example of such a  value correction approach (1 mark).

 

(viii.) In this instance, the absolute fold changes in gene expression have been displayed in Column 6 of the Table, but why do bioinformaticians often prefer to display fold change as a log2 value? (2 marks)

 

(ix.) Using all the various data provided in the Table, state which genes you consider to be convincingly altered in expression in the drug resistant cell line and explain why.  (4 marks)

 

(x.) State a laboratory technique that could be used to explore whether any of these genes had an important function in drug resistant growth using cell line B. (1 mark)

 

(i.) Clustering of gene microarray data using bioinformatic tools such as Morpheus and studying the associated dendrograms are often used when profiling clinical or experimental cancer samples.

 

What is clustering (1 mark)  and what is a dendrogram? (1 mark)

 

(ii.) What step should initially be performed with microarray data before clustering so that the clustering results are more manageable and easier to view?  (1 mark)

 

(iii.) The following Heatmap shows the expression levels of 10 genes (A-J) in lung cancer samples from six patients. The Heatmap colour scale runs from bright red (high expression), through black, down to bright green (low expression).

 

What evidence is there that these expression data have undergone clustering?  (2 marks)

 

What does the sample dendrogram tell us about tumours 1-6?  (3 marks)

 

State 2 ways in which the large coloured ”blocks” of genes (e.g.  the cluster of genes A-F) displayed on the heatmap could be useful to cancer biologists or clinicians. (2 marks).