Introduction to microarray technology and data analysis
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1 Introduction to microarray technology and data analysis Aron C. Eklund Cancer Systems Biology group Center for Biological Sequence Analysis Technical University of Denmark Introduction to Systems Biology February 11, 2013
2 Learning objectives 1. Describe a gene expression microarray and what it measures 2. Explain the steps needed to generate gene expression microarray data 4. Describe at least one application of a gene expression microarray 5. Use R at a basic level 6. Explain and calculate a log2 ratio 7. Explain and calculate a P value using the t test
3 Expression of a gene Transcription Translation DNA mrna Protein gene expression = how much of a certain mrna is present protein expression = how much of a certain protein is present
4 Why do we want to measure gene expression 1. Research setting - inference of the function of a gene - understanding gene regulation - biomarker discovery 2. Clinical diagnostics - predictive biomarkers for cancer - identifying cancers of unknown primary
5 The DNA microarray Thousands to millions of DNA spots in a few square centimeters Cartridge Glass slide a. b.
6 The gene expression microarray a. Labeled target RNA made from a biological sample Specific hybridization between a complementary probe and target detected by fluorescence DNA probe attached to the microarray substrate expression profile
7 Sequence-specific hybridization 5 -CTTGACACCCAGCTGGTCCTGTGGATGGGAGCGGT-3 3 -GTGGGTCGACCAGGACACCTACCCT-5 Probe Target mrna Substrate 5 -TAGCACACCCCGCTGCTCCTGTGGTCCCAAATGCA-3 X 3 -GTGGGTCGACCAGGACACCTACCCT-5 other mrna
8 Gene expression matrix Samples Genes 100.CEL.gz 103.CEL.gz 104.CEL.gz 105.CEL.gz 106.CEL.gz DDR RFC HSPA PAX GUCA1A UBA THRA PTPN CCL CYP2E EPHB ESRRA CYP2A GAS MMP TRADD FNTB PLD which values can be compared here?
9 The process Biological specimen Expression data
10 SAMPLE Two color labeled cdna (mostly outdated simple approach!) CONTROL mrna mrna cdna cdna Cy5-cDNA Cy3-cDNA
11 The Eberwine Protocol SAMPLE 42 C 2 h + Reverse Transcriptase RNA ssdna T7 70 C 10 min 16 C 2 h + RNase H + Polymerase clean up dsdna T7 pol 37 C 6 h dsdna arna + Biotin-labeled nucleotides
12 Affymetrix fluidics station and scanner Hybridize, incubate, rinse Scan
13 Image processing and normalization
14 Normalized expression matrix Samples Genes 100.CEL.gz 103.CEL.gz 104.CEL.gz 105.CEL.gz 106.CEL.gz DDR RFC HSPA PAX GUCA1A UBA THRA PTPN CCL CYP2E EPHB ESRRA CYP2A GAS MMP TRADD FNTB PLD now what?
15 What is the question? Typically, we use microarrays to compare between groups: Disease vs. normal Drug treatment vs. control Disease A vs. Disease B Good prognosis vs. bad prognosis
16 Comparing a gene between two groups MBNL fold change log2 ratio P value (Studentʼs t test) HD N
17 There are many other ways to analyze microarray data 0.00 scanner origin PCC BPE4 BPLE3 BPLE2 BPLER2 BPE3 BPE2 BPLE4 BPLER3 BPLER4 OCE1 FNE1 OCE2 FNE2 OCLER1 FNLER1 OCLE1 FNLE1 OCLE2 OCLER2 FNLE2 FNLER2 HMLE3 HMLER3 HME3 HME2 HME4 HMLER4 HMLE2 HMLE4 HMLER2
18 Individual probe response on microarrays Log scale Natural scale Log intensity Intensity Log concentration (pm) Concentration (pm) D. Skvortsov et al., (2007) NAR
19 Microarray data: what do the numbers mean 1. No calibration: Expression values cannot be readily translated into concentration 2. Response curves are not parallel: Comparison between one gene and another gene is almost meaningless 3. Noisy at low levels (on the log scale): Fold changes can be misleading. 4. Saturation at high levels: Cannot detect changes
20 Evolution of gene expression (mrna) measurements s - Northern blot - one gene at a time, not very accurate s - Quantitative reverse transcriptase polymerase chain reaction (RT-PCR) - one gene at a time, very accurate 3. mid-1990s - DNA microarray - many genes at a time, medium accuracy 4. Late 2000s - RNA-seq - all genes, high accuracy?
21 Other applications of microarrays (in general) DNA microarray - Gene expression - Genotyping (SNP profile) - DNA profiling (CGH, copy number) - ChIP-Chip Protein microarrays Tissue microarrays Cellular microarrays Compound microarrays
22 About the exercises
23 The data set in the exercise Genome-wide expression profiling of human blood reveals biomarkers for Huntington's disease. Borovecki F, Lovrecic L, Zhou J, Jeong H, Then F, Rosas HD, Hersch SM, Hogarth P, Bouzou B, Jensen RV, Krainc D. Proc Natl Acad Sci U S A Aug 2;102(31): samples: - 14 normal - 5 presymptomatic - 12 symptomatic Affymetrix HG-U133A arrays Huntingon s disease: - neurological disorder - polyglutamine expansion in the huntingtin gene Why search for marker of disease progression (not diagnosis)? - assess treatment efficacy - surrogate endpoint in drug trials
24 Practicalities
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Introduction to microarray technology and data analysis Aron C. Eklund eklund@cbs.dtu.dk Cancer Systems Biology group Center for Biological Sequence Analysis Technical University of Denmark Introduction
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