Gene Expression Microarray How to Analyze Your Own Genome Fall 2013

Transcription

1 Gene Expression Microarray How to Analyze Your Own Genome Fall 2013

2 Why Gene Expression? Genome- wide associabon mapping DNA sequence Disease or healthy? Molecular mechanism?

3 Why Gene Expression IdenBfying the genebc variabon that confers disease risk is not enough to decipher the molecular mechanisms of how the genebc variabon influence the disease: In medicine We need to determine which biological pathways and genes are involved in the disease process. The idenbfied pathways and genes can be a target for drug. In science Determining which pathways underlie the associabon between the genebc variabon and phenotype can provide insights on the funcbon of genes.

4 Microarrays for Molecular Biology DNA TranscripBon factor transcription Microarray for measuring gene expression levels mrna translation Proteins

5 Individuals What is gene expression? baseline expression Expression = acbvity level of gene in experiment genes gene Higher expression compared to baseline Lower expression compared to baseline

6 Microarray HybridizaEon Watson- Crick base pairing of complementary DNA sequences. Microarrays have tens of thousands of spots, each represenbng a piece of one gene, immobilized on a glass slide. The intensity (or intensity rabo) of each spot indicates the amount of labeled cdna hybridized, thus, represenbng the starbng mrna transcript abundance.

7 Hybridization and Scanning cdna arrays" - Prepare Cy3, Cy5-" labeled ss cdna" - Hybridize 600 ng of " labeled ss cdna to" glass slide array" - Scan"

8 Golub et al. (Science, 1999) One of the earliest work that demonstrated the feasibility of using only microarray gene expression data to determine cancer subtypes for pabents A stabsbcal model was learned to predict the labels for acute myeloid leukemia (ALL) and acute lymphoblasbc leukemia (AML) for each pabent given gene expression data Dataset used to learn the model consisted of 27 ALL and 11 AML pabents Tested the learned model on 20 ALL and 14 AML pabents and 29 out of 34 pabents were predicted to have correct cancer subtypes

9 Gene Expression Signature Can DisEnguish Cancer Types PaBents Genes that are informabve for predicbng cancer types

10 FDA Approves Gene- Based Breast Cancer MammaPrint is a DNA microarray- based test that measures the acbvity of 70 genes... The test measures each of these genes in a sample of a woman's breast- cancer tumor and then uses a specific formula to determine whether the pabent is deemed low risk or high risk for the spread of the cancer to another site. Test* *Washington Post, 2/06/2007

11 eqtl Mapping Expression quanbtabve trait locus (eqtl) mapping Data: SNPs and gene- expression data collected over many individuals Treats gene expressions as phenotypes and tries to discover the genebc basis of gene expression variability across individuals The genes whose expression levels are perturbed by the given genebc variabon are the most likely candidate for influencing the observed (clinical) phenotypes

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13 cis and trans eqtls cis eqtl: in genomes, the eqtl is located near the gene whose expression is affected by the eqtl. E.g., mutabons in the upstream of a gene influences the expression level of the gene trans eqtl: in genomes, the eqtl is located far away (or on a different chromosome) from the gene whose expression is affected by the eqtl. E.g., mutabons in the transcripbon factor gene can influence the expression level of the TF target genes.

14 Studying the GeneEc Basis of Diseases

15 Summary Microarray gene expression data can provide valuable insights on gene funcbons that may be hard to determine from DNA sequence alone. eqtl mapping can be used to idenbfy the genebc variabon that explains gene- expression variability. to determine the molecular mechanisms that are involved in disease processes.