standardized next generation sequencing abundance … dpcr qpcr talk... · 2016-08-01 · cv ngs...

Standardized Next

Generation

Sequencing

Abundance

Measurements

(StarSeq) using

Competitive

Template Mixtures

AccuGenomics Inc.

dPCR & qPCR 2016

* Nature Biotechnology November 2012

Need for NGS Standardization

dPCR & qPCR 2016

• More Accurate – Controls for library bias

• Improve Throughput – Amplicon convergence

• QA – every target in every sample

Targeted RNA

Sequencing

• QA metrics – sensitivity and precision for every mutation

Targeted DNA

Sequencing

dPCR & qPCR 2016

NORMAL NGS PROCEEDURE

StarSeq Workflow

MULTIPLEX COMPETATIVE

PCR

BARCODE &

ADAPTERS

SEQUENCE

COUNT CT & NT

• Multiplex PCR to saturation converges high &

low abundance targets

• NT:CT ratio maintained throughout library

construction

• Calculate sample abundance from NGS CT

and NT counts

dPCR & qPCR 2016

StarSeq ERCC Reference Standards

• Very good correlation between StarSeq vs. real-time qPCR.

• ROC curves indicate 95% confidence at detecting two-fold or

greater changes.

PLoS ONE (2013) 8(11)

dPCR & qPCR 2016

Multiplex Competitive PCR Converges High

& Low Templates

• PCR conditions converge amplicons toward equimolar concentrations.

• IS:NT ratio maintained while low and high abundance counts

converge.

Abundance

Convergence

PCR

dPCR & qPCR 2016

StarSeq Increases Sample Throughput

TRANSCRIPT ABUNDANCE

REA

DS P

ER

TA

RG

ET

• StarSeq ratio measurements eliminate the existing requirement for abundance

based on total count.

• Convergence allows measurement of targets separated over 8 log concentration

with <1000 counts

PLoS ONE (2013) 8(11)

dPCR & qPCR 2016

Additional Enrichment for Targeted RNAseq

y = 0.9785x - 0.0355

R² = 0.95

0

1

2

3

4

5

6

7

0 1 2 3 4 5 6Flu

idig

m M

ole

cu

le L

OG

ab

un

da

nc

e

Traditional LOG abundance

Transcript Abundance

0

1

2

3

4

5

0 1 2 3 4 5 6

Flu

idig

m S

eq

ue

nc

e L

OG

Co

un

ts/S

am

ple

Sequence LOG Counts/Sample

Sequence Counts Measured

• Addition of Fluidigm Access Array™

• Reduces complications of incompatible primer pairs

• Improves convergence

dPCR & qPCR 2016

FFPE SamplesRNA from FFPE samples – 1 cm2 area x 10 µm (depth) =

1 ug RNA into a 60 uL Reverse Transcription

1 uL of RT into Pre-amp below

(~17 ng of FFPE RNA derived cDNA)

Multiplex Pre-amplification with Target Specific Primers that have Universal Adapter Tails

in the Presence of Competitive Internal Standards

Sta

rSe

q

qPCR

dPCR & qPCR 2016

• More Accurate – Controls for library bias.

• Improve Throughput – Amplicon convergence

• QA – every target in every sample

Targeted RNA

Sequencing

RNAseq Summary

dPCR & qPCR 2016

DNAseq

dPCR & qPCR 2016

Allelic Frequency Testing Effected by

Sampling Issues

Addition of competitive templates ensures accurate target detection

Biomolecular Detection and Quantification (2015) 5:30–37

dPCR & qPCR 2016

Stochastic Error Estimate

EXPECTED

CV

EXPECTED CV

MEA

SU

RED

CV

(n

=4)

Biomolecular Detection and Quantification (2015) 5:30–37

H520 x H23 cell lines mixed at

different ratios and dilutions for 4

SNP measurements (n=4)

dPCR & qPCR 2016

Background Mutations

Introduced by NGS Method

Biomolecular Detection and Quantification (2015) 5:30–37

Sensitive detection of low frequency mutation is confounded by a

variable NGS introduced mutation rate

dPCR & qPCR 2016

NGS INDUCED FREQ DIFFERENCE OF NT - IS

LOG(NT-IS)

Fre

qu

en

cy

-1.0 -0.5 0.0 0.5 1.0

01

00

20

03

00

40

0

Competitive Templates

Competitive template mutation rate estimates NGS background

mutation rate.

Biomolecular Detection and Quantification (2015) 5:30–37

dPCR & qPCR 2016

Targeted DNAseq QA

EXPECTED

CV

NGS

MUTATION

RATE

ALLELIC

FREQUENCY

CONFIDENCE

INTERVAL

ESTIMATE

ALLELIC

LOD

Quality score for every mutation in every sample.

dPCR & qPCR 2016

• More Accurate – Controls for library bias.

• Improve Throughput – Amplicon convergence

• QA – every target in every sample

Targeted RNA

Sequencing

• QA metrics – sensitivity and precision for every mutation

Targeted DNA

Sequencing

StarSeq Benefits

dPCR & qPCR 2016

Acknowledgements

Thomas Blomquist,

M.D./Ph.D.

Erin Crawford, M.S.

Jeff Hammersley, M.D.

Dan Olson, M.D., Ph.D.

Ragheb Assaly, M.D.

Younsook Yoon, M.D.

DA Hernandez

Lauren Stanoszek, B.A.

University of Toledo AccuGenomics, Inc.

Tom Morrison, Ph.D.

Brad Austermiller, B.S.

Nick Lazaridis, Ph.D.

Fluidigm

Luke Stewart