successful gene expression studies using validated qpcr ...€¦ · assay design & validation...
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Successful gene expression studies using validated qPCR assays
Jan Hellemans, CEO Biogazelle
webinar
October 28th, 2015
Agenda
• Requirements for high quality qPCR assays
• Approaches for qPCR assay validation
• How good a result can be achieved with highly optimized design tools
• How to easily discover additional genes of interest
• Best practice in qPCR
Online poll
How would you rank your current knowledge about gene expression assay design?
a) basic
b) advanced
c) expert
qPCR is reference technology for nucleic acid quantification
• sensitivity and specificity
• wide dynamic range
• speed
• relatively low cost
• conceptual and practical simplicity
qPCR is easy to perform ≠ easy to do it right
• many steps involved
• all need to be right
Introduction
R
relative quantification
quality control
statistical analysis
C
Prepare – cycle – report
P
experiment design
samples
assays
prepare cycle report
R
relative quantification
quality control
statistical analysis
C
Prepare – cycle – report
P
experiment design
samples
assays
prepare cycle report
Assay design & validation
design
• amplicon length
• primer positions (exonic or intron-spanning)
Considerations & best practices
Assay design & validation
design
• amplicon length
• primer positions (exonic or intron-spanning)
Considerations & best practices
gene
exonic
intron-spanning
Assay design & validation
design
• amplicon length
• primer positions (exonic or intron-spanning)
• transcript coverage
Considerations & best practices
gene
transcript 1
transcript 2
transcript 3
2 3 12 3 2coverage
Assay design & validation
design
• amplicon length
• primer positions (exonic or intron-spanning)
• transcript coverage
in silico verification
• specificity prediction (retropseudogenes and other homologues)
• secondary structure analysis
wet lab validation (experimental)
• specificity assessment (gel, melt, amplicon sequencing)
• Cq of NTC (for SYBR assays)
• amplification efficiency determination (slope, E, SE(E), r2)
Considerations & best practices
Assay design & validation
design
• amplicon length
• primer positions (exonic or intron-spanning)
• transcript coverage
in silico verification
• specificity prediction (retropseudogenes and other homologues)
• secondary structure analysis
wet lab validation (experimental)
• specificity assessment (gel, melt, amplicon sequencing)
• Cq of NTC (for SYBR assays)
• amplification efficiency determination (slope, E, SE(E), r2)
Considerations & best practices
Properties of the perfect assay
• specific for the gene of interest => no off-target amplification
• detection of all transcript variants
• detection not affected by polymorphisms => no allelic bias or drop out
• amplification efficiency ~100%
• no gDNA co-amplification
• no primer dimer formation
The perfect assay
Online poll
How do you currently obtain your ‘perfect’ qPCR assay?
a) using your own home brewed assays
b) buying pre-designed assays (commercial)
c) currently not designing any gene expression assays
The perfect assay
• For some genes, there is no perfect assay
• no unique sequence (homology with other genes –pseudogenes)
... or the best possible
Gene homology in olfactory receptor genes prevents perfect designs
1532 / 2043 (75%) of genes without perfect design have homologous genes that differ less than 12.5% (2 variations per 16 bases)
0%5%
10%15%20%25%30%35%40%45%50%
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distances (clustalW) between all genes without perfect design
The perfect assay
• For some genes, there is no perfect assay
• no unique sequence (homology with other genes –pseudogenes)
• no common sequence among all transcripts
• regions are excluded because of repeats, secondary structures, SNPs, homology, ...
• Make the best possible compromise and report potential issues
• Design in silico quality control wet lab validation
... or the best possible
Assay design using primerXL
• database of genomic information (transcripts, SNPs, ...)
• tools for target region selection (maximize transcript coverage)
• primer3 design engine
• analysis of secondary structures and SNPs in primer & probeannealing regions
• specificity prediction (BiSearch, bowtie)
• relaxation cascade (from perfect to best possible)
Impact of primer mismatches on qPCR assay performance
Lefever, Clin Chem 2013
BiSearch specificity prediction
• BiSearch loose• 1222222222222222
• BiSearch strict• 1233333333333
BiSearch specificity prediction
• BiSearch loose• 1222222222222222
• only the gene of interest (FFAR2)
• BiSearch strict• 1233333333333
reads seq gene_list official_symbol location
2843 CATGGCAGTCACCATCTTCTGCTACTGGCGTTTTGTGTGGATCATGCTCTCCCAGCCCCTTGTGGGGGCCCAGAGGCGGCGCCGAGCCGTGGGGCTGGCTGTGGTGACGCTGCTCAATTTCCTGGTGTGCTTCGGACCTTACAGATCGGAA
ENSG00000126262 FFAR2 19:35940617-35942667
1897 GTAAGGTCCGAAGCACACCAGGAAATTGAGCAGCGTCACCACAGCCAGCCCCACGGCTCGGCGCCGCCTCTGGGCCCCCACAAGGGGCTGGGAGAGCATGATCCACACAAAACGCCAGTAGCAGAAGATGGTGACTGCCATGAGATCGGAA
ENSG00000126262 FFAR2 19:35940617-35942667
1535 GTAAGGTCCGAAGCACACCGAGAGCTGGGAGCAGGAGCTACACAGTCTGCTGGCCTCACTGCACACCCTGCTGGGGGCCCTGTACGAGGGAGCAGAGACTGCTCCTGTGCAGAATGAAGGCCCTGGGGTGGAGATGCTGCTGTCCTCAGAA
ENSG00000141456 AC091153.1 17:4574680-4607632
1097 CATGGCAGTCACCATCTTCTGAGGACAGCAGCATCTCCACCCCAGGGCCTTCATTCTGCACAGGAGCAGTCTCTGCTCCCTCGTACAGGGCCCCCAGCAGGGTGTGCAGTGAGGCCAGCAGACTGTGTAGCTCCTGCTCCCAGCTCTCGG
ENSG00000141456 AC091153.1 17:4574680-4607632
1091 CATGGCAGTCACCATCTTCTGAGGACAGCAGCATCTCCACCCCAGGGCCTTCATTCTGCACAGGAGCAGTCTCTGCTCCCTCGTACAGGGCCCCCAGCAGGGTGTGCAGTGAGGCCAGCAGACTGTGTAGCTCCTGCTCCCAGCTCTCGGT
ENSG00000141456 AC091153.1 17:4574680-4607632
Wet lab validation
PCR composition• total volume: 5 μl
• instrument: Bio-Rad CFX384 (with CFX Automation System)
• mastermix: Bio-Rad SsoAdvanced SYBR
• primer conc: 250 nM each
PCR program• default cycling protocol for SsoAdvanced SYBR (Ta=60°C)
Samples• cDNA: 25 ng (total RNA equivalents – Agilent Universal human reference
RNA = MAQC A)
• gDNA: 2.5 ng (Roche)
• NTC: water + carrier (5 ng/μl yeast transfer RNA)
• synthetic template (pooled 60-mers in concentration range: 20 M – 20 copies)
setup
Wet lab validation
• lab validation of 103 053 assays (human, mouse and rat coding genes)
• 1 456 142 reactions
• 3 822 PCR plates (384-well)
• equivalent to 15 288 PCR plates (96-well)
some numbers
305 m
Amplification efficiency
• initial publication: Vermeulen et al., Nucleic Acids Research, 2009
• Biogazelle approach (easy & cost effective)
• 60-mer
• no modifications, standard desalted
• 7 points dilution series: 20 000 000 > 20 molecules
• equivalent to full length double stranded template
• limitation: behavior of first cycles amplifying from cDNA are not evaluated
synthetic templates
30 nt 3’30 nt 5’
ds template ss oligor2<0.99 1 1median E 2.00 2.01average E 2.00 2.01count E <> [1.90-2.10] 1 3paired t-test p-value 0.14
Amplification efficiencydistribution (n = 50 133)
89%
Amplification efficiencydistribution (n = 50 133)
89%
redesign
redesign
Specificity
amplicon sizing ( + melt analysis for SYBR assays)
• limited sensitivity for detecting low level non-specific coamplification
• failure to observe non-specific amplification of sequences with similar size and/or Tme.g. expressed pseudogenes or homologous genes
next level of specificity assessment
• in silico specificity predictions by BiSearch
• massively parallel sequencing of pooled PCR products
• average coverage > 1000-fold lab specificity > 99.9%
• 50 – 200 times more sensitive than size analysis and Sanger sequencing
NGS for increased sensitivity
Specificitymost assays are 100% on-target
Specificity
0%
25%
50%
75%
100%
% o
n-ta
rge
t
2/3 of non-specific assays may go unnoticed without NGS
0% 20% 40% 60%
0 < x < 0.10.1 < x < 0.20.2 < x < 0.30.3 < x < 0.40.4 < x < 0.50.5 < x < 0.60.6 < x < 0.70.7 < x < 0.80.8 < x < 0.9
0.9 < x < 1
Specificity
perfect 60 293 86%
acceptable(<10% non-specific) 5 866 8%
predicted non-specificity(no specific design found) 1 204 2%
failing specificity QC criteria 2 467 4%
the power of in silico verification
Online poll
How do you validate your assay’s specificity?
a) Melt curves
b) Size analysis (gel or capillary)
c) Restriction digestion with gel analysis
d) Sequencing of PCR products
Online poll
Do you know the MIQE initiative?
a) Yes
b) No
MIQE compliant PrimePCR assayvalidation data sheet for human, mouse & rat
• building on the confidence validated on > 100,000 assays
• skip wet lab validation
• 9 organisms
• assays for SYBR or with probe
27,155 19,762 19,310 25,006 15,307
20,184 19,049 6,572 21,360
PrimePCR assay for 9 extra organisms
Screening vs targeted
Transcriptome• microarray or RNA-seq• hypothesis generating• few samples (high cost per sample)
Gene panels• qPCR (high sensitivity, low cost)• selection of genes based on pathway, cell type or disease• convenient balance between blind screening and targeted
analysis
Individual gene(s)• qPCR• high flexibility, customization• low cost per sample
0%
10%
20%
30%
40%
50%
60%
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90%
100%
ribo-depletion RNAseq -detection
poly-A RNAseq - detection
qPCR - detection
ribo-depletion RNAseq -quantification
poly-A RNAseq - quantification
qPCR - quantification
Saturation analysisMAQC A - % of PrimePCR
Questions?
Thank you for your attention!
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