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Exon Array Analysis Changing the Landscape of Gene Expresson Profiling Tzu L. Phang Ph. D. Department of Medicine Division of Pulmonary Sciences and Critical Care Medicine

Exon Array Analysis Changing the Landscape of Gene Expresson Profiling Tzu L. Phang Ph. D. Department of Medicine Division of Pulmonary Sciences and Critical

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Page 1: Exon Array Analysis Changing the Landscape of Gene Expresson Profiling Tzu L. Phang Ph. D. Department of Medicine Division of Pulmonary Sciences and Critical

Exon Array AnalysisChanging the Landscape of

Gene Expresson Profiling

Tzu L. Phang Ph. D.Department of Medicine

Division of Pulmonary Sciences and Critical Care Medicine

Page 2: Exon Array Analysis Changing the Landscape of Gene Expresson Profiling Tzu L. Phang Ph. D. Department of Medicine Division of Pulmonary Sciences and Critical

Alternative Splicing (AS) important regulatory mechanism in gene expression Estimated 70% of all genes undergo AS About 15% of AS known to cause some form of genetic

disease.

AAAA(n) AAAA(n)

Different Types of Alternative Splicing Events

Cassettealternative exon

Alternative 5’splice sites

Alternative 3’splice site

Intronretention

Mutually exclusivealternative exons

Alternative promoterand first exon

Alternative poly Aand terminal exon

Constitutive exon

Alternative exon

Page 3: Exon Array Analysis Changing the Landscape of Gene Expresson Profiling Tzu L. Phang Ph. D. Department of Medicine Division of Pulmonary Sciences and Critical

Exon 1.0 ST 5.4 millions, 5 m

features 1.4 millions probesets

(exon) 3 gene level annotations:

Core: 17 K genes• RefSeq and full length

mRNA Extended: 129 K genes

• Core + cDNA-based annotation

Full: 262 K genes• Extended + ab-initio

gene predictions

HG_U133plus2 1.3 millions, 11 m features 54,000 probeset (gene)

AAGCTCCTGGTCTGATCTGGGATA25-mer DNA (minimum)

Exon

Gene

Probeset

Page 4: Exon Array Analysis Changing the Landscape of Gene Expresson Profiling Tzu L. Phang Ph. D. Department of Medicine Division of Pulmonary Sciences and Critical

Exon Array Analysis Work Flow

Background bins % GC content

0

500

1000

1500

2000

A positive SI unit indicate higher inclusion rate for the exon in sample 1, or low-expression for the exon in sample 2

Page 5: Exon Array Analysis Changing the Landscape of Gene Expresson Profiling Tzu L. Phang Ph. D. Department of Medicine Division of Pulmonary Sciences and Critical

Start 100%

20.2%

8.34%

6.53%

4.95%

4.61%

1,411,399

284,258

117,816

92,256

69,830

64,996

“core” genes only

DABG filtered

Cross-hybr filtered

1927

58

46

2927

67

63

Exonic Regions

Intronic Regions

Intergenic Regions

< 10 x median

< 10 x fold change

Platelet

HealthyHeart

MyocardialInfarction

3100 exons2066 exonsSplicing Index threshold = abs(3.0)

Splicing Index + -

Results

SplicingIndexIntervals

Frequen

cy

http://xmap.picr.man.ac.uk/

SYNPO

Page 6: Exon Array Analysis Changing the Landscape of Gene Expresson Profiling Tzu L. Phang Ph. D. Department of Medicine Division of Pulmonary Sciences and Critical

Wide opened areas:

Compare different detection methods ANOSVA, ASAP, GenASAP, SPLICE, etc

Develop algorithm to mine the noisy data Cluster genes into similar alternative splice

forms Splicing graphs, modeling approaches, etc

Functional impact analysis of alternative splicing Discovery of miRNA (intergenic regions) Impact of SNiP on alternative splicing detection