Massive parallel sequencing applications in the

pharma environment

Peter Verhasselt

Translational Genomics & Genetics,

Johnson & Johnson Pharmaceutical Research & Development, Belgium

June 16th 2010

Illumina user meeting, Brussels

1

Global R&D Pharma structure @ Johnson & Johnson

2

NeuroscienceCardiovascular

& Metabolism

Infectious

DiseasesImmunology Oncology

Research Capabilities Organisation (RCO)

Biotechnology Center of Excellence

External Innovation

Global Development Organisation

Global Medical Organisation

Cross-Pharma Blobal Regulatory Affairs

Virco-Tibotec @ MechelenJanssen Pharmaceutica @ Beerse

3

• First commercial customer

(October 2003)

• Identification of mechanism of

resistance against antimicrobial

compound

• Identification of novel drug

target

• 454 Life Sciences

Andries K. et al., Science 307, 223-227Published online 9 December 2004

History of Next-Generation sequencing at J&J (1)

History of Next-Generation sequencing at J&J (2)

• March 2008

– Installation of Roche GS-FLX in Virco-Tibotec (Mechelen)

– Study minority variants in viral populations in patient plasma

– Throughout 2009: 25 runs for 24 projects / 416 samples

• Summer 2008

– Installation of SOLiD in Pharmacogenomics group (US)

• December 2009

– Installation of Illumina Genome Analyzer IIx in Beerse

– 3 Runs executed so far

4

Presentation overview

• Who we are and where we fit in the organisation

• History of next-gen sequencing in Johnson & Johnson

• Experiences with the Illumina platform

– miRNA sequencing vs. µ-array analysis

– shRNA library sequencing

– Whole Exome enrichment on SureSelect platform

– Targeted resequencing of subset of oncogenes after enrichement

by hybridization

5

Run 1 : Whole Exome Sure Select enrichment

• Paired-end sequencing sample preparation kit

• Paired-end cluster generation on cBot

• 2* 76 bases paired-end read

6

Lane Sample Yield (Gb) % PF clusters

1 2 pM PhiX 1.3 89

2 2 pM NCI-H522 1.1 91

3 2 pM A549 0.9 91

4 8 pM PhiX 1.8 80

5 4 pM NCI-H522 1.6 84

6 4 pM A549 1.5 88

7 8 pM NCI-H522 1.7 70

8 8 pM A549 1.7 73

11.6

Coverage plots

NCI-H522

A549

100x coverage

Gene density across chromosomes

1 2 3 4 5 6 7 X 8 9 10 11 12 13 14 15 16 17 18 19 20 Y 22 21

Coverage plots versus gene density

NCI-H522

A549

1 2 3 4 5 6 7 X 8 9 10 11 12 13 14 15 16 17 18 19 20 Y 22 21

Coverage across genesB

RC

A1

BR

CA

2

Run 2 : miRNA + sh-library PCR pool

• Small RNA sequencing sample preparation

• Single-end cluster generation on cBot

• 1* 36 bases single-end read

– Tubestrip hybridization protocol

11

Lane Sample (6pM) Primer Yield (Gb) % PF clusters

1 miRNA 1 smRNA/GEX-DpnII 0.8 76

2 miRNA 2 smRNA/GEX-DpnII 0.7 80

3 miRNA 3 smRNA/GEX-DpnII 0.8 77

4 PhiX genomic 0.7 79

5 miRNA 4 smRNA/GEX-DpnII 0.8 80

6 miRNA 5 smRNA/GEX-DpnII 0.7 82

7 miRNA 6 smRNA/GEX-DpnII 0.9 77

8 Sh-library PCR custom 0.2 37

5.6

Short-hairpin RNA library PCR pool sequencing

• shRNA as a tool for RNA interference

• Library pool of 250 shRNA containing plasmids

• Equimolar mixing of plasmid DNA

• Propagation in Bacteria

• Transfection into virusses

• Infection of tumor cell-lines

• Injection in mice to generate xenografts

• Impact of drugs on cell-lines or xenografts

• Barcoding

12

shRNA

P7bc

3 ntP5custom sequencing primer

Barcodes :AGG (WT)

AAG

CCG

GGG

TTG

ACG

CGG

GTG

TAG

13

Short hairpin representation across barcodes

Effect of barcode on amplification/sequencing efficiency ?

Equimolar mixing of PCR pools ?

Short hairpin representation within sample

14

Representation is independent of barcode

miRNA sequencing on Illumina platform

• Small RNA’s (22 – 30 nt)

• Each miRNA can regulate multiple genes

• miRNAs identified as biomarkers

• miR-base 14 contains 721 human entries

• µArray based analysis platforms

– Exicon, Illumina, Affymetrix, Assuragen, Illumina bead array

15

Comparison overview

16

Technologies across cell-lines

17

Run 3 : Custom + whole exome SureSelect

• (Multiplexed) paired-end sequencing sample preparation

• Paired-end cluster generation on cBot

• 2* 76 bases paired-end read + 7 bases index read

– Read 2 primer from multiplexed paired-end kit added to read 2 primer from standard

paired-end sequencing kit

18

Lane Sample (6pM) Yield (Gb) % PF clusters

1 Pool 1 0.04 16

2 Pool 2 0.04 20

3 Pool 3 1.7 85

4 Multiplex PhiX 1.0 54

5 Sample 3 1.7 87

6 Sample 3 1.7 87

7 Sample 4 2.3 82

8 Sample 4 1.3 76

9.8

POP study : Targeted re-sequencing of human genes

19

• Goal :

Simultaneously analyse a subset of the human genome for the

presence of oncology-related mutations in cell-lines or tumour

biopsies

• Technology requirements :

– Specificity

– Uniformity

– Flexibility

– Fit with downstream sequencing technology

– Cost

• Feasibility study to select best combination

20

Target enrichment : Hybridization in solution

47 genes

558 targets

89.698 bp

5118034 1390

Performance of SureSelect + Illumina

69.7 99.9 49.8 99.5 99.3 99.0 55.5

8 samples on 1 GAIIx lane

21

PCR versus hybridization based enrichment

22

PCR + 454 (24) Hyb + Illumina (8)

# reads per sample 92.868 5.118.034

Length 300 b 76 b

Coverage 92.5 x 1390 x

Completeness 98.7 % 99.9 %

Specificity 91.5 % - 73.3 % 69.7 % - 49.8 %

Acknowledgements

• Translational Genomics &

Genetics

– Jeroen Aerssens

– Ina Vandenbroucke

– Carl Van Hove

– Amy Axel

• Bioinformatics

– Herwig Van Marck

• Informatics

– Steven Osselaer

• Functional Genomics

– Kurt Van Baelen

23

• Illumina

– John Baeten

– Herman Blok

• Agilent

– Winfried Van Eyndhoven

– Emily Le Proust