Gene Expression Analysis Gabor T. Marth Department of Biology, Boston College BI420 – Introduction to Bioinformatics

Gene expression

Why study gene expression? at different developmental stages? in cells of different tissues? at different time points in the same cell? cells under different environmental conditions? between normal and cancerous cells? Which genes are active

What are expression microarrays?

Expression microarrays – “physical appearance”

Microarray construction

cDNA preparation

Expression assay

Expression microarray movie DNA microarray chip animation:

Chip readout – absolute expression and ratio

Chip readout – relative transcription

Chip readout – example

Time course experiments Experiment: measuring gene expression as oxygen gets depleted in yeast grown in a closed container

Time course data

Data analysis – normalization balance fluorescent intensities of two dyes adjust for differences in experimental conditions

Normalization

Log2 transformation Double or half expression now has the same magnitude

Clustering – intro Why: if the expression pattern for gene B is similar to gene A, maybe they are involved in the same or related pathway How: Re-order expression vectors in the data set so that similar patterns are together

Clustering – numerical

Clustering – visual

Hierarchical clustering: pair-wise similarity

Hierarchical clustering: cluster construction

Clustering – large example

Next two classes Chapter 7. Chapter 8.

Application of microarrays: classification of cancers

Microarrays to detect genome copy #

Protein identification Protein separation by 2D gel eletrophoresis

Protein identification mass spectrometry

Protein function identification protein chips: identification of proteins that bind specific chemicals

Thanks Olga Troyanskaya, Ph.D. Department of Computer Science Lewis-Sigler Institute for Integrative Genomics Princeton University Expression informatics slides courtesy of: