Evolva Biotech Evolva Biotech SASA

Microarray and Macro opportunitiesMicroarray and Macro opportunitiesforfor

Discovery informaticsDiscovery informatics

www.evolvabio.comwww.evolvabio.com

S.ShriramS.Shriram

Head of InformaticsHead of Informatics

shriramr@evolvabio.comshriramr@evolvabio.com

Mobile +91 9346738534Mobile +91 9346738534

LocationsLocations

Basel (HQ)Evolution, ScreeningPre-Clinical, Commercial

CopenhagenGenetic Analoging,Productionisation

Hyderabad Libraries, Bioinformatics, Synthetic Chemistry

AgendaAgenda

Introduction to DNA microarraysAlso please refer http://203.193.135.94/seminar05.htm

Types of Microarray

Steps in data analysis

Opportunities

• DNA Microarrays are simply small glass or silicon slides upon the surface of which are arrayed thousands of genes (usually between 100-40,000)

• Expression level measurement of genes is done by a conventional DNA hybridization process

• Data are read using laser-activated fluorescence readers

• The process is automated with robots and software and hence “ultra-high throughput”

What are DNA Microarrays?What are DNA Microarrays?

Need for MicroarraysNeed for Microarrays

What genes are Present/Absent in a cell?

What genes are Present/Absent in the experiment vs. control?

Which genes have increased/decreased expression in experiment vs. control?

Which genes have biological significance?

ApplicationsApplications

Discovery

Leads

PreClinical

Clinical

Target Discovery

Target Validation

Screening

Validation

Optimization

Toxicology

Optimization

Genotyping

ADME Screens

Types of Microarray “chips”Types of Microarray “chips”

Two major types:

a. “Gene chips” from Affymetrixa. Test and control on different chips

b. “Single channel” color

c. A probe set, each of 25 oligos in length

for a given gene

a. Costs $500 or more per chip

b. “Spotted, glass chips” originally from stanforda. Test and control on different chips

b. “Dual channel” colors

c. Probes are single stranded cDNAs of 20 to 100 bases or even longer

d. Costs $10 per slide

Types ….Types ….S

po

tted

cD

NA

ch

ip

Aff

y G

ene

chip

The 6 steps of a DNA microarray experiment (1-3)The 6 steps of a DNA microarray experiment (1-3)

1. Manufacturing of the microarray

2. Experimental design and choice of reference: what to compare to what?

3. Target preparation (labeling) and hybridization

The 6 steps of a microarray experiment (4-6)The 6 steps of a microarray experiment (4-6)

4. Image acquisition (scanning) and quantification (signal intensity to numbers)

5. Database building, filtering and normalization

6. Statistical analysis and data mining

Frabrication….Frabrication….

cDNA / spotted chips

Affymetrix gene chips

Gene chip…..Gene chip…..

GeneChipGeneChip®® Expression Analysis - Hybridization and Staining Expression Analysis - Hybridization and Staining

Array

cRNA Target

Hybridized Array

Streptravidin-phycoerythrinconjugate

Steps in pics… - Quantification of RNASteps in pics… - Quantification of RNA

Steps in pics… - RNA quality checkSteps in pics… - RNA quality check

Steps in pics… - HybridizationSteps in pics… - Hybridization

Rotation: 60 rpm

Temp: 45 C

Time: 16hrs

Steps in pics… - FluidicsSteps in pics… - Fluidics

Steps in pics… - ScanningSteps in pics… - Scanning

Steps in pics… - Scanning resultsSteps in pics… - Scanning results

Steps in pics… - Data generationSteps in pics… - Data generation

Affymetrix Movie

cDNA or spotted chipscDNA or spotted chips

Spotted chips Movie

Spotted chip…Spotted chip…

Spotted chip…Scanning resultsSpotted chip…Scanning results

Overall view of both types together…Overall view of both types together…

Steps in microarray data analysis – Bioinformatics Steps in microarray data analysis – Bioinformatics opportunitiesopportunities

IMAGE ANALYSIS – assign the degree of expression of genes based on intensity

STATISTICAL ANALYSIS – identify the differentially expressed genes (through statistical methods and through other bioinformatics methods)

PATHWAY ANALYSIS – correlate the differentially regulated genes to biological context based pathways

SYSTEMS BIOLOGY - explain the observed phenotypic (or macro-level) changes/effects at the organism level based on overall changes in “affected” pathways of various cells/tissues

From probe level signals to gene abundance estimatesFrom probe level signals to gene abundance estimates

The job of the expression summary algorithm is to take a set of Perfect Match (PM) and Mis-Match (MM) probes, and use these to generate a single value representing the estimated amount of transcript in solution, as measured by that probeset.

To do this, .DAT files containing array images are first processed to produce a .CEL file, which contains measured intensities for each probe on the array.

It is the .CEL files that are analysed by the expression calling algorithm.

Gene A Over-expressed in normal tissue

Gene B Over-expressed in tumour

200 10000 50.00 5.644800 4800 1.00 0.009000 300 0.03 -4.91

Cy3 Cy5Cy5Cy3

Cy5Cy3log2

Gen

es

Experiments842

fold248

Underexpressed

Overexpressed

Image Analysis & Data VisualizationImage Analysis & Data Visualization

Two dimensional hierarchical (“Eisen”) ClusteringTwo dimensional hierarchical (“Eisen”) Clustering

1. Experimental Design

2. Image Analysis – raw data

3. Normalization – “clean” data

4. Data Filtering – informative data

5. Model building

6. Data Mining (clustering, pattern recognition, et al)

7. Validation

Microarray Data Process

Statistical Data Pre-processingStatistical Data Pre-processing

Filtering Background subtraction Low intensity spotsSaturated spots Low quality spots (ghost spots, dust spots etc)

NormalizationHousekeeping genes/ control genes

Data to information…..Data to information…..

Molecular Function = elemental activity/task

the tasks performed by individual gene products; examples are carbohydrate binding and ATPase activity

Biological Process = biological goal or objective

broad biological goals, such as mitosis or purine metabolism, that are accomplished by ordered assemblies of molecular functions

Cellular Component = location or complex

subcellular structures, locations, and macromolecular complexes; examples include nucleus, telomere, and RNA polymerase II holoenzyme

The 3 The 3 GGene ene OOntologiesntologies

Pathway KnowledgebasePathway Knowledgebase

Tagging of gene expression data (from Microarray, SAGE, etc) onto the simple clickable pathway maps.

In-silico manipulation of pathways – ie predict the alterations in expression levels in any given tissue or disease conditions

Ease target prioritization

Systems Biology…..the holy grail..Systems Biology…..the holy grail..

AllenAllen

resident cell resident cell activationactivation

inflammatory inflammatory cell influxcell influx

BillBill

resident cell resident cell activationactivation

inflammatory inflammatory cell influxcell influx

8% improvement in FEV1 21% improvement in FEV1

Job OpportunitiesJob Opportunities

Skills in - Image analysis, Statistics, IT, Instrumentation,

Knowledge in - NETWORK AND SYSTEMS BIOLOGY

Companies in India (South):

Software & data analysisStrand Genomics (http://www.strandgenomics.com/datamining.html )

Siri Technologies (http://www.silicocyte.com/dis/index.htm )

Ocimum Biosolutions (http://www.ocimumbio.com/web/arrays/array_design.asp )

Avesthagen (http://www.avesthagen.com/trans.html)

Job OpportunitiesJob Opportunities

Network Biology

Jubilant Biosys (http://jubilantbiosys.com/pd.htm )

Genotypic tech. (http://www.genotypictech.com/home.htm)

Connexious ((http://www.connexios.com/)

Kshema Tech. (http://www.kshema.com/In_BIO-Home.htm)

TATA infotech (http://www.tatainfotech.com/industry/lifescience/index.htm)

Molecular connections (https://www.molecularconnections.com/tools.html)

Others servicesAgilent (http://www.agilent.com/about/newsroom/presrel/2005/20apr-

ca05035.html)

DS Image - microarray instrumentation

(http://www.dssimage.com/genomic_product.htm#micro_arraying)

The Future of DNA chips….The Future of DNA chips….

Protein chips……..Protein chips……..

Thank you….