Arrays

1
Arrays How do they work ? What are they ?
2
Arrays are inverted Northerns
quantitate
Extract target RNA
3
Probe preparation
Acquire or Generate probes All the genes you
want
Spot
4
Hybridise Scan
5
Arrays How do you make them ?
6
Arrayers
7
Pins
Pin type blunt, ring, quill, coated.. Breaking
bending, sticking Consistency of spots
coffee-cup, splash, drip Contamination
carry-over, dust, hairs, crystals. Etc etc.
8
Slides

• Cracking
• Splitting
• Exfoliating
• Fluorescing
• Coatings - Hydrophobic, hydrophilic, correctly
  aged poly-lysine (a bit of an art)
• Home-made vs bought (cost of internal vs
  external quality control.
• Scan before coating, scan after coating, scan
  after arraying, scan after hyb-ing all part of QC
• Etcetc...

9
RNA Quality control
10
What it looks like
Before processing, we have a LOT of spots
11
Example Hybridisation
After processing, we have a LOT of objective data
12
What biological questions can you answer with
arrays ?
13
Sorting out gene families
microarray
5 hormone response gene family members In
different experiments
14
What goes on the slide ?
One choice would be Amplifications of cDNAs
chosen by partial sequence (ESTs)
15
However ..
THE ARABIDOPSIS GENOME INITIATIVE Nature 408,
(2000)
16
Apart from wholesale duplication
Gene families ( of members as a proportion of
the genome)

• Conservation between genes
• 37 of genes are highly conserved
• (TBLASTX Elt10-30)
• 10 more are partially conserved
• (TBLASTX Elt10-5)

17
ESTs have inherent problems
18

• Better solutions
• GSTs (gene specific tags)
• Oligo arrays
• Affymetrix genechips

19
Selection of Expression Probes
3
5
Sequence
Probes
Perfect Match Mismatch
Chip
20
AffymetrixWafer and Chip Format
5 - 50 µm
5 - 50 µm
Millions of identical oligonucleotide probes per
feature
49 - 400 chips/wafer
1.28cm
up to 3,000,000 features/chip
21
Photolithographic Synthesis
Lamp
Mask
Chip
22
Synthesis of Ordered Oligonucleotide Arrays
23
Procedures for Target Preparation
Fragment (heat, Mg2)
IVT (Biotin-UTP Biotin-CTP)
AAAA
RNA
Wash Stain
Scan
cDNA
Hybridise (16 hours)
24
GeneChip Expression AnalysisHybridization and
Staining
Array
25
Bioinformatics How do you display the data from
arrays to make sense of it ?
26
Problems with arraying
29
70
27
Primary Analysis(Analysing the raw spot
intensities)

• Ratios of intensities
• Comparing the intensity to the control channel
• Logged intensities
• Makes variation of intensities and ratios of
  intensities more independent of absolute
  magnitude
• Normalised or standardised data
• Removes systematic variations in experiments.

28
Data Normalization - Allows for data comparison

• Scaling Factor (linear) normalization
• - Global or selected gene set
• - Works well when data quality metrics are
  consistent
• - Weakness assumes error is uniform across all
  genes
• Non-linear
• - Can provide higher precision, especially at
  the extremes
• - Requires selected gene (invariant) set
• - Weakness gives false confidence in poor data

29
Secondary Analysis(Analysing intensity ratios
across whole slide, gene expression histories)

• scatter plot of array data e.g.
• log Cy5 vs. log Cy3
• Separate Affy chips

Not normalized
Normalized
30
Secondary Analysis(Analysing intensity ratios
across whole slide, gene expression histories)
Gene expression history how has my favourite
gene been expressed in all experiments in the
database
31
Standards allow Storage of Data
Minimum Information About a Microarray Experiment
(MIAME) http//www.mged.org

• Experimental design time course, dose
  response, normal vs. treated
• Array description description of array which
  physical copy used
• Description of sample growth conditions, dev.
  stage, labelling
• Hybridisation conditions wash procedure,
  time, concentration
• Measurements scanning hardware software
• Normalisation controls housekeeping genes,
  spiking controls

32
Tertiary Analysis(e.g. Clustering)

• Clustering of genes based on similar expression
  profiles
• Several techniques have been applied to array
  data
• Hierarchical clustering
• Non-hierarchical clustering methods
• Principle Component Analysis K-means
  clustering

33
Which software should I use ?
free
free
34
An Expression Roadmap to Wood formation
Bark Phloem Cambium
Xylem
Division Expansion 2nd
cell-wall
35
Differential expression patterns
36
Lignin biosynthesis
C4H EC1.14.13.11
COMT EC2.1.1.68
F5H EC1.14.13.-
COMT EC2.1.1.68
PAL EC4.3.1.5
C3H
4CL
4CL
4CL
4CL
EC4.1.1.28
EC3.2.1.21
4CL EC6.2.1.12
Coumarine
CCoAOMT EC2.1.1.104
CCoAOMT EC2.1.1.104
CCoA-3H
CCR
CCR
CCR
EC1.14.11.9
CCR EC1.2.1.44
F5H EC1.14.13.-
Flavonoids
CAD
CAD
Fold Change
COMT EC2.1.1.68
F5H EC1.14.13.-
CAD EC1.1.1.195
15 4 3 2 1.5 11 1.5 2 3
4 15
Transport
Anionic Peroxidases EC1.11.1.7
Polymerisation
C
D
E
A
B
Laccase EC1.10.3.2
Dirigent-like
L I G N I N
37
Amniotic membrane for Ocular surface
reconstruction
Oligo array
2D protein
38
Caution !
These are just CLUES !!