normal carcinome inflammation

carcinomenormal

inflammation

1964

DKFZ Genomics Activities

MolTools Partners

Anthony BrookesKarolinska Institute

Olli KallioniemiVTT Technical Research Centre

Mike TaussigBabraham Institute

Ed SouthernOGT

Andres, MetspaluEstonian Biocentre

Arvydas JanulaitisFermentas UAB

Ivo GutCentre National de Génotypage Jörg Hoheisel

Peter LichterAnnemarie PoustkaDKFZ

Jörn KochAarhus University

Hans LehrachMax Planck Institute

Ove ÖhmanÅmic

Ulf LandegrenUppsala University

EU

Marc ZabeauMethexis Genomics

Dolores CahillRoyal College of Surgeons

George ChurchHarvard University, USA

Marcus Beierfebit biotech

Basic Level of Functional Analysis

DNA RNA ProteinDNA RNA ProteinTranscription ExpressionMethylation

LocalisationStructure SplicingModificationInteractionOrganisation

RNAiSNPs CombinationStructure

Copy number

DegradationComposition

Enzymatic activity

Epigenetics Platform

• The Human Epigenome Project• Characterisation of DNA-methylation patterns

in tumours• MolTools: Advanced molecular tools for

array-based analyses• Amplification- and label-free SNP-analysis

EU

Nanotechnology

Systematic-Methodological Platform Epigenetics

DKFZ:Jörg Hoheisel (Coordination,

Chip Technologies)Frank Lyko (Epigenetics)Herman-Josef Gröne (Tumour bank)

Bonn UniversityAndreas Waha (Chip Technologies)

University of SaarbrückenJörn WalterInternational University BremenAlbert JeltschMPI for Molecular Genetics, BerlinRichard ReinhardIMB JenaAlbert Platzer

Transcriptional Profiling

gene 1 gene 2 gene 3

cDNA microarray

sample 1 sample 2RNA

scanned image

Transcriptional Profiling Projects

ManMouseDrosophila melanogasterArabidopsis thalianaSaccharomyces cerevisiaeHydractinia echinata

Bacillus subtilisTrypanosoma bruceiNeurospora crassaPseudomonas putidaRhizobium meliloti

EU

EU

EU

In Situ Synthesised Oligonucleotide MicroarrayN. crassa Microarray

Aign & Hoheisel (2003) Fungal Genet. Biol. 40, 225-233.

Mask-Free Control of Oligonucleotide Synthesis

Light

Amidites

Digital micromirror system

Photolabile protection group

1. 2. 3.

1. Molecules bound to glass surface

2. Cleavage of protection groups at illuminated spots

3. Condensation of amiditesresults in oligomer elongation

Chip-Based Analyses

On-chipenzymatic reaction

e.g. primer extension

5´

dTTP dGTP dCTP

GTCGG5´

CGATCGG5´

TGCTAGCC

TGGTA

AC

C

dATP5´

3´3´

hybridisation ofwildtype target

wtwt mt

mt

DNA-polymerase

analysis in solution; on-chip molecule separation

GCTATTGACCA...

tag 15´

ACC

tag 25´

ACCGCTA...


wtwt mt

mt

Detection via tag sequencesDirect hybridisation

GGCTAGCAT3´


wtwt mt

mt

GGCTGGCAT3´

CCGATCGTA

3´

5´

CG

GTT

CA

TA

3´

5´

mismatch versus full-matchdiscrimination

ZIP-Code Array vs. Gene-Specific Array

oligo-dTor

gene-specificprimer

template specificprimer extension and labelling

template DNA or RNA

Array ofgene-specificprobes

ZIP-Code Array vs. Gene-Specific Array

Array ofcomplementary

ZIP-code probes

Array ofgene-specificprobes

gene-specificprimer

template specificprimer extension and labelling

template DNA or RNA

ZIP-code

5’

Transcript Profiling on ZIP-Code Array

ZIP-code

5’

primer extension and labelling

AAAAAA-3’

gene-specificprimer

ZIP-code

5’

primer extension and labelling

AAAAAA-3’

sample 1

sample 2

gene-specificprimer

hybridisation toZIP-code array

Transcript Profiling on ZIP-Code Array100000

10000

1000

100

10

34.7

7.0 6.2

-25.9

sign

al in

tens

ity

30

20

10

0

-10

-20

n-fo

ld c

hang

e

standardhybridisation

ZIP-codeanalysis

6.36.4

24.3

-35.7

3.4

20

10

0

-10

-20

-30

n-fo

ld c

hang

e

10000

1000

100

10

sign

al in

tens

ity

yeasthyphe

n-foldchange

Drosophila Exon-Specific PCR-ProductsDrosophila Microarray

Hild et al. (2003)Genome Biol. 5, R3.Boutros et al. (2004)Science 303, 382-385.Hollich et al. (2004)Biotechniques 37, 282-284.

23k Trypanosoma bruceiGenomic Fragment Microarray

T. brucei Microarray

Diehl et al. (2002)Mol. Biochem. Parasit. 123, 115-123.Brems et al. (2005)Mol. Biochem. Parasit. 139, 163-172.

Drosophila Genomic ArrayDrosophila Microarray

X

2L

2R

3R

4

(3L)

Minimal tiling path of 25,000 shotgun clonesmade from 320,000 clones used in sequencing

Hollich et al. (2004) Biotechniques 37, 282-284.

Variation by Preparation

Tumour sample 1vs.

Control

Tumour sample 2vs.

Control

C

2

C

1

Kinetic Parameters

spot size and format stirring vs. non-stirring incubation

In Situ Signal Amplificationsupported by

EU

self-assembly

targethybridisation

seco

ndar

yhy

brid

isat

ion

1600

1200

800

400

010 100 1 10 100 1 10

zmol amol fmol

Fluo

resc

. int

ensi

ty R2 = 0.9857


EU

NH

ODMTO

NH

ODMTO

O

P N(Pr)2O

CNEt

Symmetric doubler phosphoramidite

25 nt 25 nt

26 nt

2000 nt

50 nt

20 40 60 80 100

Temperature / C

Rel

ativ

e ab

sorp

tion

550

259

Rel

ativ

e ab

sorp

tion Absorption

Self-assembly76 nt

Meltingbehaviour

200 400 600 800

Wavelength / nm


EU Transcriptional profiling on Drosophila microarray

Ambion ArrayControl PCR spots

branchedoligomers control

Concordance Analysis

frequ

ency

[%

]

0.1 1 10

20

15

10

5

0

frequ

ency

[%

]

20

15

10

5

00.1 1 10

One samplelabelled with

Cy3 and Cy5

Two sampleslabelled withCy3 and Cy5

M-CHiPSData Processing Software



Cy3 and Cy5


frequ

ency

[%

]

frequ

ency

[%

]

20

15

10

5

00.1 1 100.1 1 10

20

15

10

5

0M-CHiPS

Data Processing Software



Cy3 and Cy5


frequ

ency

[%

]

0.1 1 10

20

15

10

5

0

frequ

ency

[%

]

20

15

10

5

00.1 1 10

±σM-CHiPSData Processing Software

Multi-Conditional HybridisationIntensity Processing SoftwareM-CHiPS

Database currently holds data of more than 5,900 experiments.

Database Browser

PostgreSQLDatabase

Selection of arbitrary subset

Matlab-based microarray data mining tools including- Normalisation - Quality filtering- Clustering, Correspondence analysis - Automated analysis of annotations

www.dkfz.de/funct_genome www.mchips.org

Normalisation Based onthe Majority of All Signal Intensities

log regressionlinear regression

logarithmic scalelinear scaleM-CHiPS



log regressionlinear regression




linear regression log regression



Normalisation

Each data set is correlated with the median of all controlsand fitted by linear or logarithmic regression.


Method Output

• Hierarchical Clustering treeEisen et al. (1998) PNAS 95, 14836

• K-Means Clustering set of clustersTavazole et al. (1999) Nat. Genet. 22, 281

• Learning Networks- Neural Networks, e.g. Kohonen Maps set of clusters

Tamayo et al. (1999) PNAS 96, 2907

- Baysian Networks directed graphFriedman et al. (2000) Proc. RECOMB 2000, 127

• Planar Embedding biplot- Multidimensional Scaling

Khan et al. (1998) Cancer Res. 58, 5009

- Principle Components AnalysisHilsenbeck et al. (1999) J. Natl. Cancer Inst. 91, 453

- Correspondence AnalysisFellenberg et al. (2001) PNAS 98, 10781

• Other MethodsBen-Dor et al. (1999) J. Comp. Biol. 6, 281 set of clusters

(incomplete list)

Method Output

• Hierarchical Clustering treeEisen et al. (1998) PNAS 95, 14836

• K-Means Clustering set of clustersTavazole et al. (1999) Nat. Genet. 22, 281

• Learning Networks- Neural Networks, e.g. Kohonen Maps set of clusters

Tamayo et al. (1999) PNAS 96, 2907

- Baysian Networks directed graphFriedman et al. (2000) Proc. RECOMB 2000, 127

• Planar Embedding biplot- Multidimensional Scaling

Khan et al. (1998) Cancer Res. 58, 5009

- Principle Components AnalysisHilsenbeck et al. (1999) J. Natl. Cancer Inst. 91, 453

- Correspondence AnalysisFellenberg et al. (2001) PNAS 98, 10781

• Other MethodsBen-Dor et al. (1999) J. Comp. Biol. 6, 281 set of clusters

(incomplete list)

DataClustering


Marker Identification

Hybridisation data from Affymetrix chips

Correspondence Analysis; Fellenberg et al., PNAS 98, 2001

patients

individual genes


Drosophila Developmental Transcript ProfileDrosophila Microarray

adult

pupal 3

pupal 2

pupal 1embryonic 12-16 h

larval

embryonic 8-12 h

embryonic 4-8 h


embryonic 0-4 h

Pancreatic Cancer vs. Chronic Pancreatitis

carcinomenormal

inflammation


patient

differentiallytranscribed gene


Target Selection

carcinomenormal

inflammation



Target Selection

carcinomenormal

inflammation



Analysis of Gene Ontology (GO) Terms

gene

0% glucose0.01% glucose0.1% glucose1% glucose

GO terms

Effect of glucose on yeast

M-CHiPSData Processing Software Yin et al. (2003) Mol. Microbiol. 48, 713-724.

Analysis of Gene Ontology (GO) Terms

Glu

cone

ogen

esi

Glykolysis

Identification ofaffected pathways

Effect of glucose on yeast

gene

0% glucose0.01% glucose0.1% glucose1% glucose

GO terms


Combination of Information Sources

7089

629845005

Mismatch repair(genes MSH2, MSH3, MLH1)

Traversing start control of mitotic cell cycle

(genes CDK10, CDC2, CDC25C)

normal tissue

new tumour entity

cystictumours

GO annotations

ductaladenocarcinoma


Busold et al. (2005), Bioinformatics, in press.

Complex Antigen-Antibody InteractionsAntibody Microarrays

illustration

EU

Kusnezow & Hoheisel (2002) BioTechniques 33 (suppl.), 14-23.Kusnezow et al. (2003) Proteomics 3, 254-264.Kusnezow & Hoheisel (2003) J. Mol. Recognit. 16, 165-176.Kusnezow et al. (2004) Protein Microarrays (Schena, M., ed.),

247-284.Kusnezow et al. (2005) Handbook of Immunohistochemistry

(Hayat, M.A., ed.), 23-37.

real experiment

Acknowledgements

• Frank LykoEpigenetics Group, DKFZ

• Helmut FriessChirugie Heidelberg

• Thomas GressMedizinische Klinik Abt. I

• Andres MetspaluInstitute of Molecular and Cell Biology

• Heinrich ArlinghausPhysikalisches Institut, Münster

• Nicole HauserInstitut für Grenzflächen und Bioverfahrenstechnik, Stuttgart

UniversitätHeidelberg

UniversitätUlm

TartuUniversity

Universität.Münster.

Functional Genome Analysis, DKFZ, Heidelberg, Nov. 2002

www.dkfz.de/funct_genome

Joint IGB-DKFZ-MolToolsPractical Course:

Analysis and Interpretation of Complex Transcript Data

27 June 2005 - 30 June 2005DKFZ, Heidelberg

There are no costs involved but for accommodation and travel expenses, which will be the responsibility of the participants.

Emphasis of the course will be hands-on data analysis. The participants are encouraged to bring along their own data for analysis.

For more details see: www. dkfz.de/funct_genome

Documents

normal carcinome inflammation