Successful gene expression studies using validated qPCR assays Jan - PowerPoint PPT Presentation

Successful gene expression studies using validated qPCR assays Jan Hellemans, CEO Biogazelle webinar October 28 th , 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

Introduction 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

Prepare – cycle – report relative experiment design quantification C P R quality control samples prepare cycle report statistical analysis assays

Prepare – cycle – report relative experiment design quantification C P R quality control samples prepare cycle report statistical analysis assays

Assay design & validation Considerations & best practices design • amplicon length • primer positions (exonic or intron-spanning)

Assay design & validation Considerations & best practices design • amplicon length • primer positions (exonic or intron-spanning) gene exonic intron-spanning

Assay design & validation Considerations & best practices design • amplicon length • primer positions (exonic or intron-spanning) • transcript coverage gene transcript 1 transcript 2 transcript 3 coverage 2 3 2 3 2 1

Assay design & validation Considerations & best practices 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)

Assay design & validation Considerations & best practices 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)

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 ... or the best possible • For some genes, there is no perfect assay • no unique sequence (homology with other genes – pseudogenes)

Gene homology in olfactory receptor genes prevents perfect designs distances (clustalW) between all genes without perfect design 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 1 101 201 301 401 501 601 701 801 901 1001 1101 1201 1301 1401 1501 1601 1701 1801 1901 2001 1532 / 2043 (75%) of genes without perfect design have homologous genes that differ less than 12.5% (2 variations per 16 bases)

The perfect assay ... or the best possible • 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

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 & probe annealing 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 BiSearch strict • • 1222222222222222 1233333333333

BiSearch specificity prediction • • BiSearch loose BiSearch strict • • 1222222222222222 1233333333333 • only the gene of interest (FFAR2) reads seq gene_list official_symbol location 2843 CATGGCAGTCACCATCTTCTGCTACTGGCGTTTTGTGTGGATCATGCTCTCCCAGCCC ENSG00000126262 FFAR2 19:35940617- CTTGTGGGGGCCCAGAGGCGGCGCCGAGCCGTGGGGCTGGCTGTGGTGACGC 35942667 TGCTCAATTTCCTGGTGTGCTTCGGACCTTACAGATCGGAA 1897 GTAAGGTCCGAAGCACACCAGGAAATTGAGCAGCGTCACCACAGCCAGCCCC ENSG00000126262 FFAR2 19:35940617- ACGGCTCGGCGCCGCCTCTGGGCCCCCACAAGGGGCTGGGAGAGCATGATCC 35942667 ACACAAAACGCCAGTAGCAGAAGATGGTGACTGCCATGAGATCGGAA 1535 GTAAGGTCCGAAGCACACCGAGAGCTGGGAGCAGGAGCTACACAGTCTGCTGG ENSG00000141456 AC091153.1 17:4574680- CCTCACTGCACACCCTGCTGGGGGCCCTGTACGAGGGAGCAGAGACTGCTCCT 4607632 GTGCAGAATGAAGGCCCTGGGGTGGAGATGCTGCTGTCCTCAGAA 1097 CATGGCAGTCACCATCTTCTGAGGACAGCAGCATCTCCACCCCAGGGCCTTCATT ENSG00000141456 AC091153.1 17:4574680- CTGCACAGGAGCAGTCTCTGCTCCCTCGTACAGGGCCCCCAGCAGGGTGTGCA 4607632 GTGAGGCCAGCAGACTGTGTAGCTCCTGCTCCCAGCTCTCGG 1091 CATGGCAGTCACCATCTTCTGAGGACAGCAGCATCTCCACCCCAGGGCCTTCATT ENSG00000141456 AC091153.1 17:4574680- CTGCACAGGAGCAGTCTCTGCTCCCTCGTACAGGGCCCCCAGCAGGGTGTGCA 4607632 GTGAGGCCAGCAGACTGTGTAGCTCCTGCTCCCAGCTCTCGGT

Wet lab validation setup 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)

Wet lab validation some numbers 305 m • 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)

Amplification efficiency synthetic templates • initial publication: Vermeulen et al., Nucleic Acids Research, 2009 • Biogazelle approach (easy & cost effective) • 60-mer 30 nt 5’ 30 nt 3’ • no modifications, standard desalted • 7 points dilution series: 20 000 000 > 20 molecules • equivalent to full length double stranded template ds template ss oligo r2<0.99 1 1 median E 2.00 2.01 average E 2.00 2.01 count E <> [1.90-2.10] 1 3 paired t-test p-value 0.14 • limitation: behavior of first cycles amplifying from cDNA are not evaluated

Amplification efficiency distribution (n = 50 133) 89%

Amplification efficiency distribution (n = 50 133) redesign 89% redesign

Specificity NGS for increased sensitivity 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 Tm e.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

Specificity most assays are 100% on-target

Specificity 2/3 of non-specific assays may go unnoticed without NGS 100% 0.9 < x < 1 0.8 < x < 0.9 0.7 < x < 0.8 75% 0.6 < x < 0.7 % on-target 0.5 < x < 0.6 50% 0.4 < x < 0.5 0.3 < x < 0.4 0.2 < x < 0.3 25% 0.1 < x < 0.2 0 < x < 0.1 0% 0% 20% 40% 60%

Specificity the power of in silico verification perfect 60 293 86% acceptable 5 866 8% (<10% non-specific) predicted non-specificity 1 204 2% (no specific design found) failing specificity QC criteria 2 467 4%

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 assay validation data sheet for human, mouse & rat

PrimePCR assay for 9 extra organisms • building on the confidence validated on > 100,000 assays • skip wet lab validation • 9 organisms 27,155 19,762 19,310 25,006 15,307 20,184 19,049 6,572 21,360 • assays for SYBR or with probe