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MICROARRAYS D’EXPRESSIÓ ESTUDI DE REGULADORS DE LA TRANSCRIPCIÓ DE LA FAMILIA trxG. M. Corominas : [email protected] Spotted microarrays rely on delivery technologies to place biologic material (purified cDNA, oligonucleotides) onto allocated locations of the chip.

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slide1

MICROARRAYS D’EXPRESSIÓ

ESTUDI DE REGULADORS DE LA

TRANSCRIPCIÓ DE LA FAMILIA trxG

M. Corominas: [email protected]

slide2

Spotted microarrays rely on delivery technologies to place biologic material (purified cDNA, oligonucleotides) onto allocated locations of the chip.

(competitive hybridization: Cy3vsCy5)

slide3

- 90% amplification

- Single product in most PCRs

10,000

3,000

21,226

5,148

2,000

1,000

21,226

5,148

2,000

10,000

3,000

1,000

10,000

3,000

21,226

5,148

2,000

Direct PCR from

Bacterial Growth

1,000

21,226

5,148

2,000

10,000

3,000

Analysis of PCR results

by electrophoresis

Spotting on

slide

1,000

Production of cDNA chips

17 plates from the Berkeley Drosophila Gene Collection

with 384 wells (clones) each.

Aprox. 5000 genes in total

slide4

Operon D. melanogaster Array

16416 spots

14593 70mer probes representing 13664 genes and 17899 transcripts

POSITIVE CONTROLS

  • 10 A. thaliana oligos (TIGR spikes) - each printed 4 times by pin = 640 spots
  • 12 D. melanogaster oligos - each printed 17 times = 204 spots

NEGATIVE CONTROLS

  • 12 Randomly Generated Negative Controls – printed several times = 188 spots
  • 352 Empty spots
  • 449 Buffer spots
hybridization of chips

RNA Extraction

mRNA

mRNA

Cy5 test sample

Cy3 control sample

Hybridize Slide

Hybridization of Chips

mutant flies (ash2)

wild-type flies

Fluorescent

Labelling

slide7

532 nm

635nm

-Integrate Data

-Filter Data

-Adjust dye bias

-Calculate Ratios

-Adjust Data

-Set Thresholds

Scanning of Chips

Scan Slide

fluorescent intensities for

each cDNA, spot or gene

fluorescent intensities for

each cDNA, spot or gene

GenePix

slide8

Operon D. melanogaster Array

16416 spots

14593 70mer probes representing 13664 genes and 17899 transcripts

POSITIVE CONTROLS

  • 10 A. thaliana oligos (TIGR spikes) - each printed 4 times by pin = 640 spots
  • 12 D. melanogaster oligos - each printed 17 times = 204 spots

NEGATIVE CONTROLS

  • 12 Randomly Generated Negative Controls – printed several times = 188 spots
  • 352 Empty spots
  • 449 Buffer spots

(hybridized with aRNA ISOash2I1 vs ISO)

slide9

Amplification Test:

totalRNA vs aRNA log2ratios

Correlation coef = 0.94

tigr spike in mix
TIGR spike-in Mix

We can use the spikes to assess quality of experiment and analysis

On chip: 10 A. thaliana oligos spotted 64 times each (4 times by pin)

To add to labeling reaction: In vitro synthesized RNA from each

gene at different proportions and quantities:

For Amplification experiments

we use the spikes diluted 1:500

tigr spikes ma plot from an experiment with total rna
TIGR spikes MA plot from an experiment with total RNA

Experimental procedure and analysis seems good

(spikes fall where expected)

bad spots filtering
“Bad” Spots Filtering
  • Is the process in which spots that don’t look right are
  • discarded according to different criteria

GenePix discards data according to internal filters like:

x % pixels > Median Background intensity

Convert Data 3.33 to further filter data.

Spots were flagged as OK if:

medianFx > mBx +/- XSD

  • Spots must pass filtering for both channels
adjusting ratios
Adjusting Ratios
  • A Ratio measures how much sample cDNA over control
  • cDNA we have of a given gene. This is:
  • Ratio = Intensity sample / Intensity control
  • Different measures for the ratios:
    • Ratio of Medians
    • Ratio of Means
    • Regression Ratio
  • Log (base 2) the ratios :
    • Makes variation of intensities and ratios of intensitiesmore  independent of absolute magnitude.
    • Gives a more realistic sense of variation.
slide14

Therefore:

  • a Normal distribution
  • with mean (all log2 Ratio ) = 0
  • We expect:
    • few genes upregulated
    • few genes downregulated
    • most genes unchanged (log2 Ratio = 0)
  • Draw distribution of Ratios and check mean:
    • if really not N: filter bad spots better
          • try to Normalize (mean = 0; SD = 1)
          • discard experiment
    • if close to N: adjust mean (product or sum)
          • Normalize (0; 1)
multiple experiment comparison

Norm log Ratio of Medians

Experiment 1

Experiment 3

Experiment 2

Experiment 4

7

6

5

4

% Genes in Class

3

2

1

0

4

-7

0.7

1.8

2.9

5.1

6.2

-1.5

-5.9

-4.8

-3.7

-2.6

-0.4

log Ratio of Medians Class

Multiple Experiment Comparison
analysis layout

2 TIFF images (Cy3 & Cy5)

GAL file (gene matrix)

Input

GenePix Pro 4.0 Image analysis

ANALYSIS LAYOUT

Output

1 GPR file for experiment

Input

TIGR Express Converter 1.4.1

Output

1 MEV file for experiment

slide17

1 MEV file for experiment (total=5)

Input

TIGR MIDAS

  • Each experiment analyzed independently
  • Background filter applied
  • Normalization applied: Lowess (LOC) for each experiment independently

Input

EXCEL & TIGR MEV

  • Spike-in, negative and positive control Check
  • MA Plots
  • Experiment Comparison (Scatter Plots)
  • Relevant Genes Finding
slide18

Controls and Quality assesment

- Sequencing of some clones from the Collection plates

- RT-PCR of some genes in a semiquantitative way

- in situ hybridization

- Western Blot

- inmunolocalization

- Northern Blot

- Clonal Analysis

classification according to go gene ontology
Classification according to GO (Gene Ontology)
  • Gene Ontology is a “controlled vocabulary that can be
  • applied to all eukaryotes “. Each gene product is classi-
  • fied in one or more categories.
  • Is distribution of missexpressed genes significantly
  • different from the one of our initial set of genes?
  • maybe trxG genes act predominantly upon a group
  • of genes of similar function or pathway?
slide24

Departament de Genètica:

Florenci Serras

Montserrat Corominas

Isabel Almudí

Mireia Angulo

Sergi Beltran

Cristina Pallarès

Miguel Pignatelli

Adrià Punset

Marta Sesé

CRG-UPF-IMIM

Roderic Guigó

Enrique Blanco

Plataforma de Transcriptòmica

Parc Científic- SCT-UB

Lídia Sevilla

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