Successful gene expression studies using validated qpcr assays. Jan Hellemans, CEO Biogazelle webinar October 28 th, 2015

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1 Successful gene expression studies using validated qpcr assays Jan Hellemans, CEO Biogazelle webinar October 28 th, 2015

2 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

3 Online poll How would you rank your current knowledge about gene expression assay design? a) basic b) advanced c) expert

4 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

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

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

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

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

9 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

10 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)

11 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)

12 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

13 The perfect assay

14 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

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

16 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% / 2043 (75%) of genes without perfect design have homologous genes that differ less than 12.5% (2 variations per 16 bases)

17 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

18 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)

19 Impact of primer mismatches on qpcr assay performance Lefever, Clin Chem 2013

20 BiSearch specificity prediction BiSearch loose BiSearch strict

21 BiSearch specificity prediction BiSearch loose BiSearch strict only the gene of interest (FFAR2) reads seq gene_list official_symbol location 2843 CATGGCAGTCACCATCTTCTGCTACTGGCGTTTTGTGTGGATCATGCTCTCCCAGCCC CTTGTGGGGGCCCAGAGGCGGCGCCGAGCCGTGGGGCTGGCTGTGGTGACGC TGCTCAATTTCCTGGTGTGCTTCGGACCTTACAGATCGGAA 1897 GTAAGGTCCGAAGCACACCAGGAAATTGAGCAGCGTCACCACAGCCAGCCCC ACGGCTCGGCGCCGCCTCTGGGCCCCCACAAGGGGCTGGGAGAGCATGATCC ACACAAAACGCCAGTAGCAGAAGATGGTGACTGCCATGAGATCGGAA 1535 GTAAGGTCCGAAGCACACCGAGAGCTGGGAGCAGGAGCTACACAGTCTGCTGG CCTCACTGCACACCCTGCTGGGGGCCCTGTACGAGGGAGCAGAGACTGCTCCT GTGCAGAATGAAGGCCCTGGGGTGGAGATGCTGCTGTCCTCAGAA 1097 CATGGCAGTCACCATCTTCTGAGGACAGCAGCATCTCCACCCCAGGGCCTTCATT CTGCACAGGAGCAGTCTCTGCTCCCTCGTACAGGGCCCCCAGCAGGGTGTGCA GTGAGGCCAGCAGACTGTGTAGCTCCTGCTCCCAGCTCTCGG 1091 CATGGCAGTCACCATCTTCTGAGGACAGCAGCATCTCCACCCCAGGGCCTTCATT CTGCACAGGAGCAGTCTCTGCTCCCTCGTACAGGGCCCCCAGCAGGGTGTGCA GTGAGGCCAGCAGACTGTGTAGCTCCTGCTCCCAGCTCTCGGT ENSG FFAR2 19: ENSG FFAR2 19: ENSG AC : ENSG AC : ENSG AC :

22 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)

23 Wet lab validation some numbers 305 m lab validation of assays (human, mouse and rat coding genes) reactions PCR plates (384-well) equivalent to PCR plates (96-well)

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

25 Amplification efficiency distribution (n = ) 89%

26 Amplification efficiency distribution (n = ) redesign 89% redesign

27 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% times more sensitive than size analysis and Sanger sequencing

28 Specificity most assays are 100% on-target

29 Specificity 2/3 of non-specific assays may go unnoticed without NGS % on-target 100% 75% 50% 25% 0% 0.9 < x < < x < < x < < x < < x < < x < < x < < x < < x < < x < 0.1 0% 20% 40% 60%

30 Specificity the power of in silico verification perfect % acceptable (<10% non-specific) % predicted non-specificity (no specific design found) % failing specificity QC criteria %

31 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

32 Online poll Do you know the MIQE initiative? a) Yes b) No

33 MIQE compliant PrimePCR assay validation data sheet for human, mouse & rat

34 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

35 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

36 Saturation analysis MAQC A - % of PrimePCR 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% ribo-depletion RNAseq - detection poly-a RNAseq - detection qpcr - detection ribo-depletion RNAseq - quantification poly-a RNAseq - quantification qpcr - quantification 0%

37 Questions?

38 Thank you for your attention!

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