Microarray and functional genomics Wenjing Tao University of Missouri.

Microarray and functional genomics

Wenjing Tao

University of Missouri

Microarray: high through-put whole genome approach

Microarray is a tool for analyzing gene expression that consists of a small membrane or glass slide containing samples of many genes arranged in a regular pattern

48 grids, with 31k probes

Each grid contain 650 probes

Microarray terminology

• Feature - an array element

• Probe - a feature corresponding to a defined sequence (immobilized on a solid surface in an ordered array)

• Target - a pool of nucleic acids of unknown sequence

- Find the genes and assign them functions

- Predict protein structures and functions

- Reconstruct metabolic, signaling, and other pathways

- Reconstruct informational networks

- Link genotype to phenotype

- Use genotype/phenotype to predict relevant outcome

- Cross- species comparisons

Microarray provides the opportunities

Kinds of array features

Synthetic oligonucleotides:

Affymetrix genechip

Long oligo array

PCR products from:

Cloned cDNAs

Genomic DNA

cDNA & oligonucleotide arrays

100-300 m spot 20-25 mers

Schulze and Downward, 2001 Nat Cell Biol 3, 190

Target2

Target1

RNART

RT

Labeling withFlouresent dye

ORFs or ESTs

Design long oligoes

Microtiter plate Microarray slides

• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •

HybridizationScan

cDNA and long oligo array experiment

Affymetrix GeneChip

GREEN represents Reference DNA hybridized to the target DNA.

RED represents Test DNA hybridized to the target DNA.

YELLOW represents a combination of Test and Reference DNA hybridized equally to the target DNA.

BLACK represents areas where neither the Reference nor Test DNA hybridized to the target DNA.

Fluorescent microarrays are composed of a combined two false color laser scanned images

Image file post-processing• Single slide normalization – GenePix Pro 4.1

• Slide-slide and dye-swap comparison – TMEV & MIDAS • Cross-slides quality evaluation - GeneSpring + R script for CV filter• Mixed linear model analysis of Variance to identify significant differentially expressed genes – R or SAS program• Data Analysis in the Post-Genomic Era (gene annotation, ontology and pathway analysis– KOG, COG, KEGG, TAIR, Onto-Tools, GenMapp…• Data validation – qPCR or Northern blot

Whole genome approaches to biological questions

• Gene expression

• Gene variation

• Gene function

NSF-DB1-0211842, PI: Henry Nguyen

Functional Genomics of Root Growth and Root Signaling under drought

http://rootgenomics.missouri.edu/prgc/research.html

Drought-stress inducible genes and their possible functions in stress tolerance and response.

Yamaguchi-Shinozaki et al. JIRCAS Working Report, 2002

Dr. Henry Nguyen’s lab, Plant Sciences, University of Missouri

Characterize the transcript profiles of apical and basal regions of the root

growth zone under water deficit condition using maize long oligonucleitide arrays

To identify genes contributing to root growth maintenance under water deficit condition

To determine genes responsible for progressive inhibition of root elongation under water-deficit condition

To compare the differential gene expression in root region of progressive inhibition of root elongation under water stress with the normal growth deceleration in well-watered root region

Objectives

WW48 WS48

1

2

3

4

1

2

3

4

1

2

3456

Pair-wise comparison of maize root segments using oligo array

Characterization of the maize long oligo array

• Maize oligo array, printed at the University of Arizona, contains 56,311 70-mer oligonucleotide probes, including >30,000 identifiable unique maize genes. 16,915 oligoes do not have any annotation.

• 70-mer oligonucleotides in conjunction with Operon Qiagen based on the TIGR Maize Database

WS/WW=Cy5/Cy3 WS/WW=Cy3/Cy5

Dye Swap

Slides feature and dye-swap experiment

1. Channel A intensity vs. channel B intensity

2. Log channel A intensity vs. log channel B intensity

3. R-I

4. Z-score histogram5. Box plot

Two-color microarray data feature

Flip dye consistency checking

- processed data count: 27852 (only slides A)- pre-filtering corr. coeff: 0.11360581- post-filtering data count: 26747- confidence factor: 0.9647781- dispersion factor: 0.035401408

Summary of the evaluation of replicates (technique & biological)

• ~50,000 of the 56,311 genes have intensity >200 (at least one channel).

• Confidence of dye-swap is > 96%• 99.9% confidence limit was estimated by testing

the coefficient of variance (CV) for replicates

Mixed linear model analysis of two color microarray data- producing lists of differentially expressed

genes with low false discovery rates To obtain accurate and precise estimates of gene expression values

between treatment and control, analyze gene effects with a simultaneous consideration of all blocking factors, a linear mixed ANOVA model is applied:

There are two processes:

First, global mixed model was applied:

Log2(singal values) = treat + dye + treat*dye + tech_reps_effect + array_effect (within treat*dye and tech_reps_effect)

Second, take residual values from the first model and then apply this model for individual gene:

Residuals = treat + dye + tech_reps_effects + array(within tech_reps_effects)

POORLY CHARACTERIZED - 6%

METABOLISM - 11%

INFORMATION STORAGE AND PROCESSING - 4%

CELLULAR PROCESSES AND SIGNALING 10%

NOT ASSIGNED – 69%

Gene function categorization of significantly differentially expressed

genes

KOG analysis

RNA processing and modification

16%

Chromatin structure and

dynamics13%

Translation, ribosomal

structure and biogenesis

23%

Transcription34%

Replication, recombination and

repair14%

Information storage and processing

Energy production and

conversion15%

Amino acid transport and

metabolism14%

Nucleotide transport and

metabolism5%

Carbohydrate transport and

metabolism18%

Inorganic ion transport and

metabolism16%

Secondary metabolites

biosynthesis, transport and

catabolism14%

Lipid transport and metabolism

14%Coenzyme

transport and metabolism

4%

Metabolites

Posttranslational modification, protein turnover, chaperones

30%

Signal transduction mechanisms

31%

Intracellular trafficking, secretion, and vesicular

transport11%

Defense mechanisms8%

Extracellular structures1%

Nuclear structure1%

Cytoskeleton6% Cell

wall/membrane/envelope biogenesis

9%

Cell motility0%

Cell cycle control, cell division, chromosome

partitioning3%

CELLULAR PROCESSES AND SIGNALING

Summary

• Microarray is a high through-put tool to identify novel genes

• We have identified 19 hundred drought response and root growth maintenance related genes

• Combining functional analysis we would find drought stress tolerance related pathways and genes

• This knowledge will lead to novel approaches for improving drought tolerance in maize.