Microarray hybridization Usually comparative – Ratio between two samples Examples – Tumor vs. normal tissue – Drug treatment vs. no treatment – Embryo.

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Presentation transcript:

Microarray hybridization Usually comparative – Ratio between two samples Examples – Tumor vs. normal tissue – Drug treatment vs. no treatment – Embryo vs. adult mRNA cDNA DNA microarray samples

2. Spotting DNA on the chip

Capillary action on contact Apply small droplets on contact Pin stamps DNA on contact Spray droplets under pressure Types of printing pins

Synthesis of High Density Oligonucleotide Arrays by Photolithography/Photochemistry

Comparisons of microarrays

Scanning of microarrays Confocal laser scanning microscopy Laser beam excites each spot of DNA Amount of fluorescence detected Different lasers used for different wavelengths – Cy3 – Cy5 laser detection

Spotting of PCR amplified clones using MicroGrid II 610

Hybridization of target with spotted slides by GeneTAC Hybstation Quantification of Cy3 & Cy5 labeled target using Nanodrop

Control and water Stressed Cotton plants RNA Isolation cDNA Library construction PCR amplification of clones Spotting of slides with PCR amplified clones using MicroGrid II 610 Preparation of Cy3 and Cy5 labeled TARGET Hybridization of target with spotted slides by GeneTAC Hybstation Scanning of slides by GeneTAC UC4X4 Slide Image after hybridization

4.1 Scanning & capturing images

Image files of hybridized slide in both Cy3 and Cy5 channels Up-regulated Down-regulated Co-expressed

Scanning Hybridized Microarray Laser 2Laser 1 Monochrome pictures combined Emission Excitation (two-color arrays)

Image Segmentation Scanned Image Numerical Data Segmentation Software

Results given as ratios Images use colors: Cy3 = Green Cy5 = red Yellow – Yellow is equal intensity or no change in expression Analysis of hybridization

Intensity-dependent bias A M = log(Cy3/Cy5) Low intensities M<0: Cy3<Cy5 High intensities M>0: Cy3>Cy5 * Global normalization cannot remove intensity-dependent biases

A We expect the M vs A plot to look like: M = log(Cy3/Cy5)

LOWESS (Locally Weighted Scatterplot Smoothing) Local linear regression model Tri-cube weight function Least Squares Estimated values of log 2 (Cy5/Cy3) as function of log 10 (Cy3*Cy5)

Heat map of Affymetrix 430 V2.0 GeneChip data