Genome Core Fall Users Group MeetingOct. 15, 2008

• Requesting services, forms, pricing, and sample submission.Kathryn Thompson and Sonia Mirza

• Ambion TaqMan Gene Expression Cells-to-CT Kit: Evaluation ofgene expression data obtained from cell lysates.Langdon Smythe

• SABiosciences RT2 qPCR Arrays: Evaluation of a plate-basedhigh throughput qPCR product. Jennifer Dang

• Sequenom MassArray System: Current successes andchallenges. Kirsten Copren

The Sequenom MassArray System:Current Successes and Challenges

Kirsten A. Copren, Ph.D.Genome Analysis Core

Oct. 15, 2008

Sequenom MassArray System

NIH SIG Grant April 2007

1st Project Feb. 2008

Regular operation July 2008

MassArray Science, the CliffsNotes

1. Single Base PrimerExtension (iPlex-SNPs)

2. Base Specific Cleavage(MassCleave-Methylation)

http://sequenom.com

http://mysequenom.com

SNP Workflow

• Assay Design - 1 day• Order Oligos - 1 week• Mix/Adjust Oligos (1-2 days)• Sample preparation (size dependent)• Validation - 3 days• Run: PCR,SAP,iPlex,MS- (4-5 chips/week)• Analysis, Clustering - Quick• Analysis, Verification by Eye - 1 day

Example Turnaround Times

1. One week (Design, Order, Run):17 SNPs, 1-Plex, 164 samples, 1 Chip

2. Three weeks (Run & Analysis Only):43 SNPs, 2-Plex, 1248 samples, 7 Chips

Date Species # SNPs Plex # Samples Call Rate StatusFeb-08 Human 25 2 192 99% CompletedMar-08 Mouse 11 1 192 98% CompletedAug-08 Mouse 17 1 164 97% CompletedAug-08 Canine 101 3 102 97% CompletedSep-08 Human 43 2 1248 95-97% CompletedSep-08 Mouse 44 2 ~300 In ProgressOct-08 Human 122 4 ~800 In QueueNov-08 Human 150 4/5 ~1000 DesigningNov-08 Mouse 22 2 80 Designing

SNP Projects

DNA 260/280 > 1.7 recommended

Project Design Considerations

• Think 384!

• Choose lowest plex level and maximize SNPs perplex.

• Start with more SNPs than desired (~15%)

• 97% Call Rates for successful assays to date

• Validation not necessary. Saves Time.

Challenges

• System complicated, extensive training andeducation required

• No Pre-PCR liquid handling capacity

• No high throughput DNA quantificationmethod at Cancer Ctr

• Standardize project/sample parameters

Currently….

• 3/5 of Core Staff trained for independentusage

• Evaluation of Pre-PCR liquid handlerunderway

• Grant submitted for 8-Channel Nanodrop,Pico Green DNA quantification protocol underinvestigation

• Sample/Project submission standardizationunderway

Methylation Workflow

• Design primers• Optimize PCR (1-4 weeks)• Bisulfite Treat DNA (1 day)• PCR, Run Gel (1/2 day)• Run: SAP,MassCleave, MS (4-5 chips/week)• Data Analysis (Quick)

Date Species # Amplicons # Samples Total Rxns StatusAug-12 Human 4 96 384 CompletedAug-12 Human 4 45 384 CompletedOct-12 Human 2 20-40 384 Re-Design

Methylation Projects

Considerations

• PCR primer design and optimization crucial.

• Reaction unit is per amplicon. Range 100-600 bp,300-400 optimal. One gene may require multipleamplicons.

• Bisulfite treatment largest source of unavoidablevariation. Requires 500 ng DNA/sample

• Some success with FFPE with small amplicons (100-150bp)

• Requires analysis of PCR bands on gel to ensuresuccess of run.

Current Application Development

• Detecting HPV-16 and HPV-18 in samples atattomolar level (<10 copies)

• Fine mapping of chromosomal deletions fromarray CGH data (CNVs)

Successes

• Excellent SNP call rates

• Methylation analysissuccessful with carefulconsideration to PCR

• “Flexible” system, butoptimal designs most cost-effective

• Quantification applicationsavailable more sensitive thanQPCR method

• Increasing throughputdemands

• Training, education, anddocumentation to increaseunderstanding of workflowand design considerations

• Time required to developand optimize applications

Challenges

Next Seminar Hosted by Genome Core

Friday, Nov. 7, 2008Sponsored by Sigma Aldrich12:00 – 1:00 p.m., Lurie Conference Room

qPCR Principles and Applications: Assay optimizationtechniques to improve target quantification

Tania Nolan, Ph.D., Global Manager, Sigma-Genosys

Topics:• Improving assay design• Potential issues with template variability• Improving data normalization• Consistency in data analysis

“The patience to wait until the mud settles and the water runsclear” (Lao Tzu)

USERS

• Elliot Sherr• Nathan Osbun• Rosemary Akhurst• Michael Benizou• Minh Thu Luu• Steve Hamilton• Jennifer Yokoyama• Joe Costello• Chibo Hong• Katie Ridd• Maria DaCosta• Joel Palefsky

SUPPORT & ASSISTANCE

• NIH• Cancer Center• Allan Balmain, Director• Genome Core Staff (Langdon,

Jenny, Kate, Sonia)• Randy Davis• Greg Hamilton• Sequenom: esp. Jodee Steinberg,

Charles Tetzlaff, Pam Shaw