PostgenomicsFUNCTIONAL GENOMICS

DNA Chips and Microarrays

CSUS, Nov 15, 2001

Zeljka Smit-McBride

zsmcbride@ucdavis.edu

University of California, Davis

Central Dogma of Molecular Biology

DNA makes RNA makes PROTEIN

LEVEL OF SINGLE GENE ANALYSIS

DNA

RNA

PROTEIN

RNA PROTEIN

TRANSCRIPTION TRANSLATION

LEVEL OF THE WHOLE GENOME ANALYSIS

GENOME

RNA

PROTEIN

TRANSCRIPTOME

PROTEOMETRANSCRIPTION

TRANSLATION

EFFECT OF mRNA OVEREXPRESSION

NORMAL OVEREXPRESSED

THE -OME AND -OMICS

GENOMICS: study of GENOME; how many GENES, physical map,

sequence of their DNA, structure…

FUNCTIONAL GENOMICS: study of TRANSCRIPTOME; which, when, where and how

much mRNA expressed…

PROTEOMICS: study of PROTEOME; which PROTEINS, when, where and

how much…

What is functional genomics ?

• To understand the relationship between genotype (a particular set of genes) and phenotype (a set of features of the whole organism), we need to look at the function of the entire genome. This is reflected in the cellular expression pattern of mRNA. This is the area of study of functional genomics.

New technology - Microarrays

• robotic engineering • pin technology • molecular biology • DNA sequencing

• computers• optical technology• laser technology • informatics

•Able to look at gene expression programs on a very large scale

•Advancements in several technologies:

• Orderly grid or matrix of genes

• we know exactly which gene is at each spot

What is microarray?

Custom microarray

Hexokinase Phospho Glucoisom.

Phospho fructokinase

Aldolase Isomerase

Triose phosphate d.

Phospho glycerokinase

Phospho Glyceromut.

Enolase Pyruvate kinase

Pyruvate Dehydro.

Citrate synthase

Aconitase Isocitrate Dehydrogen.

alpha-Keto glutarate d.

Succinyl-CoA synthetase

Succinate dehydrog.

Malate dehydrog.

Glucose-6 P dehydrog.

6-Phospho glucolacto.

6-Phospho gluconate d.

Ribulose- P 3-epimer

Ribosephos. isomerase

Trans ketolase

Ribose P Pyrophospho

Trans aldolase

ATP synthase

Rubisco

Hexokinase Phospho Glucoisom.

Phospho fructokinase

Aldolase Isomerase

Triose phosphate d.

Phospho glycerokinase

Phospho Glyceromut.

Enolase Pyruvate kinase

Pyruvate Dehydro.

Citrate synthase

Aconitase Isocitrate Dehydrogen.

alpha-Keto glutarate d.

Succinyl-CoA synthetase

Succinate dehydrog.

Malate dehydrog.

Glucose-6 P dehydrog.

6-Phospho glucolacto.

6-Phospho gluconate d.

Ribulose- P 3-epimer

Ribosephos. isomerase

Trans ketolase

Ribose P Pyrophospho

Trans aldolase

ATP synthase

Rubisco

DNA microarrays

• DNA microarrays are microscopic groups of thousands of DNA molecules of known sequence attached to a solid surface.

• Traditional Spoted arrays - cDNA

• DNA chip – oligonucleotides synthesized in situ

What is cDNA ?

Genomic DNA

hnRNA

mRNA

cDNA

protein

Exon 1 Exon 2 Exon 3

splicing

Reverse transcription

transcription

DNA on the slide after hybridization

Duggan, et al, Nature Genetics Supplement, Vol21, Jan 1999

Components of the of functional genomics analysis

• RNA sample preparation

• Array generation and sample analysis

• Data handling and analysis - bioinformatics

The front end - from sample to RNA

Bowtell, DDL, Nature Genetics Supplement, Vol 21, Jan 1999, pp 25-32

Middleware: making and using microarrays

Bowtell, DDL, Nature Genetics Supplement, Vol 21, Jan 1999, pp 25-32

Back end: moving and handling data

Bowtell, DDL, Nature Genetics Supplement, Vol 21, Jan 1999, pp 25-32

Important principles from molecular biology

• DNA makes RNA makes PROTEIN

• Genetic Code

• A=T and G=C

• Complementary strands hybridize

• Genomic DNA vs mRNA vs cDNA

Gene expression analysis using DNA microarrays

DNA microarray

TEP 1

cDNA

mRNA

P.O.Brown & D.Botstein, Nature Genetics Supplement, Vol 21, Jan 1999, pp 33-37

• we know exactly which gene is at each spot

• based on color of each spot after the experiment we can tell which gene expressions have changed

After hybridization...

RED - OVEREXPRESSED

GREEN - UNDEREXPRESSED

YELLOW - NO CHANGE

Applied Genomics Exploiting the human genome

• Molecular diagnostics of cancer

• SNPs and Personal pills

• Pharmacogenomics and new drugs

• Structural genomics and new targets

• and many more

Gene expression in Molecular Diagnostics

Molecular Classification of Malignant Melanoma

A chip of a different flavor

GeneChip

GeneChip Expression Analysis Process

GeneChip expressionanalysis probe array

Each probe cell containsmillions of copies of a specificoligonucleotide probe

Biotinylated RNAtarget from experi-mental sample

Streptavidin-phycoerythrinconjugate

Image of hybridized probe array

Oligonucleotide Arrays

Southern et al, Nature Genetics Suppl., Vol 21, Jan 1999

Light directed oligonucleotide synthesis

Lipshutz, R.J., Fodor, S.P.A., Gingeras, T.R. & D. LockhartNature Genetics Supl., Vol 21, Jan 1999, pp. 20-24

GeneChip Expression Array Design

Perfect match probe cells

Mismatch probe cells

mRNA

DNA probe pairsReference Sequence

Lipshutz, RJ, Fodor, SPA, Gingeras, TR & DJ Lockhart, Nature Genetics Supplement, Vol 21, Jan 1999, pp 20-24

Fluorescence Intensity Image

Perfect Match OligoMismatch Oligo

Gene expression oligonucleotide array performance characteristics

Routine use Current Limit

Starting material 5 ug total RNA 0.5 ug total RNA

Detection specificity 1:100,000 1:2x106

Difference detection Twofold changes 10% changes

Dynamic range (linear detection)

~500-fold 104 -fold

Number of probe pairs per gene or EST

20 4

Number of genes or ESTs per array

12,000 40,000

SNP - single nucleotide polymorphism

• Variations in the gene sequence, resulting in the amino acid change in the protein, which results in the altered function

• Genotyping of oncogenes - cancer causing or permitting genes

• Identifying and genotyping drug response gene variants

Genotyping Arrays

120,000 probes for3,000 biallelic loci

Allele AAllele B

MismatchPerfect MatchPerfect MatchMismatch

GenotypeA/A B/B A/B

High throughput VistaArray microarrays platform for SNPs

genotyping

Array(256 elements)

Array platform(96 arrays/plate)

Evans, WE & Relling, MV, Science, Vol 286, Oct 15, 1999

Pharmacogenomics

Translating functional genomics into rational therapeutics

Structural Genomics- High Throughput Protein Structure Determination

The Exponential Growth of Biological Information

NCBI, Aug 2001

The Gene Machine grows

16 96-deep well plates

The Q-bot picks 3,000 colonies/hour

The Eppendorf manifold does 384 minipreps at a time

PCR reactions set up with a Beckman biomek 2000

Tetrads run 384 PCR reactions at a time

ABI 3700 runs 8 96-well plates/day

Birth of a new scientific discipline:

Bioinformatics

Bioinformatics is:Trying to Swim in a Sea of Data

A

A A

G

T

G

C T

G A T

C

T

T

TC

T

CG

A

T

C T A

T

A G

C

“Now we’ve done it! Now, we’ll really need big computers to help us make sense out of this!”

BIOINFORMATICS

BIOLOGY

COMPUTERSCIENCE

INFORMATIONTECHNOLOGY

TRANSLATION INITIATION FACTORS eIFs-

NOVEL MECHANISM OF ONCOGENESIS

OVEREXPRESSION OF TRANSLATION INITIATION FACTORS IN CANCER

BREAST, BLADDER,PROSTATE, LYMPHOMASHEAD&NECK, COLON

BREAST, LUNGSOESOPHAGUS

PROSTATET-CELL LEUKEMIA

MELANOMA

eIF2

LYMPHOMAS

TRANSLATION INITIATION FACTORS - NOVEL MECHANISM OF

ONCOGENESIS

• FUTURE DIRECTIONS• PROSTATE CANCER

– DETECTION • MARKERS FOR EARLIEST CANCER STAGES

• MARKERS FOR THE RISK OF METASTASIS

• TUMOR PROGRESSION MARKERS

– TREATMENT• NOVEL THERAPEUTIC TARGETS

– MECHANISM• HYPOTHESIS - ROLE IN INCURABLE ANDROGEN

INDEPENDENT PROSTATE CANCER STAGE

Where to from here?

Sci.Am., Aug 2001

E-cell The Self-surviving Cell Model

TRENDs in Biotechnology,Vol 19, No 6, June 2001

Conclusions

• There is life after genomics revolution ! Genome information exploitation !

• Pharmaceutical industry can move faster -design better drugs, utilize more targets

• Massive move toward automation and high-throughput sample analysis

• Expression profiling is painting the functional picture of the physiology of the cell and eventually tissue, organism...

On-line Resources

• NCBI-http://www.ncbi.nlm.nih.gov/• Stanford- http://genome-www.stanford.edu/• Affymetrix- http://www.affymetrix.com• Silicon Genetics-

http:www.signetics.com/GeneSpring/• Brown Lab, Stanford University-

http://cmgm.stanford.edu/pbrown/explore• MicroArray Project, NIH-

http://www.nhgri.nih.gov/• E-cell- http://www.e-cell.org/

THE END