1. Genomica Funcional Dr. Víctor Treviño vtrevino@itesm.mx A7-421
Microarrays - Microarreglos 1

2. Functional Genomics Technologies
Transcriptomics
Proteomics
Metabolomics
Genomics
SNP (Single Nucleotide Polymorphisms)
CNV (Copy Number Variation, CGH)
Epigenomics

3. Microarrays
Technology that provides measurments of thousands of molecules in the same experiment and reasonable prices and precision
Generally in the size of a typical microscope slide (75 x 25 mm (3" X 1") and about 1.0 mm thick)

4. Microarrays
Affymetrix
Spotted
Illumina
Google Images

5. Microarrays – Probe Production
(2) Litography (Affymetrix)
(1) Spotted
InkJey (Spotted-Like)
(3) Optical Fiber (Illumina)

6. Microarray Technologies “Images”
Affymetrix - 1 dye
Spotted/InkJet Arrays two-dyes
Illumina

7. Microarray – Hibridisation Principle
Microarrays Bioinformatics, Dov Stekel, Cambridge, 2003

8. Microarray Repositories

9. Microarrays – What can be done with data?
Differential Expression
Unsupervised Classification
Biomarker detection
Identifying genes related to survival times
Regression Analysis
Gene Copy Number and Comparative Genomic Hibridization
Epigenetics and Methylation
Genetic Polymorphisms and SNP's
Chromatin Immuno-Precipitation On-Chip
Pathogen Detection …

10. Microarrays – Sample Size ????
α is the probability of a false-positive result
1−β is the power to detect a difference of size δ in gene expression on the log base 2 scale
τg σg + (representing a sum of biological and technical is the variation in expression for gene g across the different arrays)
Bioinformatics in Cancer and Cancer Theraphy – Gordon – Humana

11. Microarray Applications
Microarray Technology Through Applications, F. Falciani, Taylor & Francis 2007

12. Differential Expression
Gene 1
Gene 2
Gene 3 .
Gene N
Class A
Samples
Class B
Normal Tissue,
Cancer A,
Untreated,
Reference, …
Tumour Tissue,
Cancer B,
Treated,
Strains,
Differential Expression
Positive
Negative
Samples A B
Gene Selection
µ=d
Expression Level 
p-value  FDR  q-Value

13. Biomarker Discovery Biomarker Detection Gene Selection Positive
Negative
Samples
Class A
Class B
µ=d
Gene Selection
Expression Level 
Gene 1
Gene 2
Gene 3 .
Gene N
Class A
Samples
Class B
Normal Tissue,
Cancer A,
Untreated,
Reference, …
Tumour Tissue,
Cancer B,
Treated,
Strains,

14. Unsupervised Classification
Unsupervised Sample Classification
Expression
Low
Co-Expressed
Genes
High 1 2 3 4 5 6 7 8 9
Figure 4. Unsupervised classification and detection of co-expressed genes. A. Double-Hierarchical clustering of gene expression values (heatmap), in rows by genes, and in columns by samples. Similar samples generate cluster easily identified. For example, the expression of samples AC is similar between them and different from the rest. Co-expressed genes forms tight and small culsters. A selected cluster framed by a dotted lines is shown in B. B. Hierarchical generation of clusters from a selected group of genes in A.
A C G B H E D I K M L
Samples

15. Regression: Gene Association to outcome
Univariate linear Regression
Regression: Gene Association to outcome
Positive
Negative
Gene Selection
Dependent Variable 
Gene Expression 
Slope ≠ 0
Slope = 0
Gene 1
Gene 2
Gene 3 .
Gene N
Class A
Samples
Class B
Normal Tissue,
Cancer A,
Untreated,
Reference, …
Tumour Tissue,
Cancer B,
Treated,
Strains,
ai = 0
ai ≠ 0

16. Regression: Gene Association to outcome
(Optional)
Gene Interactions
Intercept
Gene i
Multivariate Linear
Regression: Gene Association to outcome
Positive
Negative
Gene Selection
Dependent Variable 
Gene Expression 
Slope ≠ 0
Slope = 0
Gene 1
Gene 2
Gene 3 .
Gene N
Class A
Samples
Class B
Normal Tissue,
Cancer A,
Untreated,
Reference, …
Tumour Tissue,
Cancer B,
Treated,
Strains,

17. Genes Associated to Survival Times and Risk
h-Hazard, x-Genes
β-Coefficients
Multivariate Non-Linear Regression
Cox Proportional Hazard
Gene 1
Gene 2
Gene 3 .
Gene N
Class A
Samples
Class B
Normal Tissue,
Cancer A,
Untreated,
Reference, …
Tumour Tissue,
Cancer B,
Treated,
Strains,
Genes Associated to Survival Times and Risk
Positive
Negative
Gene Selection +
Kaplan-Meier Plot
Time 
Hazard
1.0
0.0

18. Chromatin Immuno-Precipitation (ChIP-on-Chip) Identificación de Sitios de Unión (Binding Sites)
Precipitation of
Antibody-TF-DNA
complex
Fusion of
Tag sequence
into TF gene
Labelling of
precipitated
DNA
Microarray
Hybridisation
Incubation
DNA-Tagged TF
Transcription Factor
Tag
Antibody
against
tag peptide
Microarray Technology Through Applications, F. Falciani, Taylor & Francis 2007

19. CpG Methylation Detección de Sitios Metilados/NoMetiladosX
Unmethylated Fraction
Hypermethylated Fraction
Sample
Control
Cleavage with
methylation-sensitive
restriction enzyme
TasI Csp6I
CpG specific
Adaptor Ligation
cleavage with
McrBC
Adaptor-specific
amplification
Unmethylated fraction
Hypermetylation fraction
Cy5
(red)
Cy3
(green)
Microarray

20. SNP - Single Nucleotide Polymorphisms Detección de Mutaciones Puntuales
Labelling
Detection
Hybridisation
AA CG CC …
SNP1
SNP2
SNP3 3' T G C 5'
Products of 1nt primer
extension (in solution)
Capture A GC CG +
Transcribed RNA
+ reverse transcriptase
A^C TA
C^A
Extension
ddNTPs
(one labelled)
(1nt)
Labelled ddNTPs
PCR products
+ DNA polymerase a b c

21. Pathogen/Parasites Detection
(1) ACGGCTAGTCACAAC...
(2) GCTAGTCACAACCCA...
(3) GCTAGTCCGGCACAG...
...
Sample
Spotted
Hybridized
(1)
(2)
(3)

22. “Tiling” Arrays Usan sondas a todo lo largo del genoma DNA Genómico
“Sin-Traslape”
DNA Genómico
Sondas
“Con-Traslape”

23. Tiling-Arrays – CGH Comparative Genomic Hybridization
Compra DNA Genómico de varios tipos de células/tejidos/especies

24. Tiling-Arrays  Metyl-DNA immunoprecipitation (Detección de Sitios Metilados/NoMetilados)

25. Tiling-Arrays – DNAseI Detección de Sitios Expuestos (Heterochromatin)

26. miRNA - Arrays

27. miRNA microarray procedure
FIGURE 1.Overview of the miRNA microarray procedure. RNA species smaller than ~40 nt are purified by a rapid electrophoretic gel fractionation method. miRNAs are 3′-end labeled with poly(A) polymerase, amine-modified nucleotides, and amine-reactive dyes. The fluorescently labeled miRNAs are hybridized to a glass slide on which miRNA-specific DNA oligonucleotide probes have been arrayed. Microarrays are processed and analyzed using standard equipment, scanner, and software. A representative result from a scanned microarray is shown in B.
RNA species smaller than ~40 nt are purified by a rapid electrophoretic gel fractionation method
Microarrays are processed and analyzed using standard equipment, scanner, and software
Copyright 2005 by RNA Society
SHINGARA J et al. RNA 2005;11:

28. Other Microarrays
Microarray Technology Through Applications, F. Falciani, Taylor & Francis 2007

29. Antibodies Microarrays
Microarray Technology Through Applications, F. Falciani, Taylor & Francis 2007

30. Protein Microarrays
Microarray Technology Through Applications, F. Falciani, Taylor & Francis 2007

31. Carbohydrate Microarray

32. Small-Molecule Microarrays