Quantitative PCR

1. Quantitative PCR Bioinformatics & Gene Discovery 2007 Wilhelm Johannsen Centre for Functional Genome Research

2. QPCR & Gene discovery in the Post-genomic Era • The human genome is sequenced, then why go gene discovering? • Other genomes to work on ! • Gaps in the human genome remain • Not all human genes have yet been identified • Not all human expressed sequences are mapped to the DNA-genome • Splice-variants or aberrant composite proteins • Novel functions or relations assigned to old proteins • Non-coding RNA Wilhelm Johannsen Centre for Functional Genome Research

3. Overview • What is PCR? • Quantitation of gene expression • Methodology • Experimental design • Problems • Applications at WJC Wilhelm Johannsen Centre for Functional Genome Research

4. What is PCR? Denaturation • A PCR (Polymerase Chain Reaction) is a highly specific, enzymatic process, where a well defined DNA sequence is amplified exponentially • The process use a simple non-isothermal enzymatic reaction using primers nucleotides & a thermostable DNA-polymerase • Ideally, after 40 cycles, one starting copy of a gene would yield 240 copies of that DNA fragment, i.e., ~1.1x1012 copies • Yields μg worth of DNA, plenty to be able to sequence, clone and visualize on an agarose gel Extension Annealing Some graphics modified from Andy Vierstrate, http://users.ugent.be/~avierstr/principles/pcr.html Wilhelm Johannsen Centre for Functional Genome Research

5. Quantitation of gene expression • Quantitation of gene expression can supply important biological information about gene function and relationships • Quantitation of gene expression may discriminate between normal and diseased states • Always remember that high or low gene expression not necessarily indicate high/low protein levels Wilhelm Johannsen Centre for Functional Genome Research

6. Quantitation of gene expresion-- Immobilised Methodology-- • Northern blotting • Gel-based • Relatively inexpensive equipment • Involves hybridisation steps • Time, sample & labor intensive • Few samples, target genes to be handled simultaneously • Simple data calculations • Micro-arrays • Chip-based • Expensive equipment • Involves hybridisation steps • Technology time and labor intensive • Many samples, target genes to be handled simultaneously • Extensive data calculations Tiao, Hobler, et al.: JCI, 99, 163-168, 1999 http://www.well.ox.ac.uk/genomics/facilitites/Microarray/Welcome.shtml Wilhelm Johannsen Centre for Functional Genome Research

7. Quantitation of gene expresion--PCR Methodology-- • Semi-quantitative PCR • Gel-based • Inexpensive equipment • Involves hybridisation steps • Time, sample & labor conservative • Multiple samples but few target genes simultaneously • Simple data calculations • Real-time PCR (QPCR) • Gel-free? • Expensive equipment • Involves hybridisation steps • Time, sample & labor conservative • Multiple samples but few target genes simultaneously • Extensive data calculations Schulze, Hansen et al, Nature Genet. 1996 Wilhelm Johannsen Centre for Functional Genome Research

8. QPCR - why ? • Conservative (10-50 ng template) • Sensitive • Broad dynamic range • Rapid (1-2 hrs) • Relatively inexpensive (DKK 5-15/sample) • Multiple samples can be processed simultaneously (1->96) • Possible multiplexing • Unambiguous results • Gradual expression differences can be detected • Gel-free Wilhelm Johannsen Centre for Functional Genome Research

9. What is QPCR? Denaturation • PCR as usual • Additional quantitation step • Optional Melting curve generation Extension Quantitate Annealing Melting curve Plateau Exponential Signal noise Wilhelm Johannsen Centre for Functional Genome Research

10. Semi-quantitative endpoint PCRvs. QPCR C(t)=18.5 C(t)=11 Wilhelm Johannsen Centre for Functional Genome Research

11. Melting curves – circumvention of ’dirty’ reactions Wilhelm Johannsen Centre for Functional Genome Research

12. Endpoint analysis Simple Inexpensive Gel-based system ’Yes/No’ quantitation Multiplexing possible Broad enzyme range Variable cycle number QPCR Little more complex Slightly More expensive Gel-free system Relative quantitation Absolute quantitation Multiplexing possible Clean PCR ? Limited enzyme range Invariable cycle number Pro’s & con’s Wilhelm Johannsen Centre for Functional Genome Research

13. Overview • What is PCR? • Quantitation of gene expression • Methodology • Experimental design • Problems • Applications at WJC Wilhelm Johannsen Centre for Functional Genome Research

14. Chemistry 1 • SYBR green (quantitation, melting curve) • Taqman Assay (quantitation, genotyping, multiplex) • Hybridization probes (quantitation, genotyping) • Molecular beacons (quantitation, genotyping) • Scorpions (genotyping) • Light-Up probes (quantitation, genotyping) • Ampliflour universal detection system (quantitation, multiplex) • LUX fluorogenic primers (quantitation, multiplex) • Universal Probe Library (quantitation) Wilhelm Johannsen Centre for Functional Genome Research

15. Selected QPCR strategies SYBR Hyb. probes Taqman Lux Wilhelm Johannsen Centre for Functional Genome Research

16. Chemistry 2 • Commercially available kits • Variation in kit quality • Lower batch-to-batch variation • Limited range of thermostable polymerases • For ’difficult’ fragments kits may be a poor choice • Do it yourself (DIY) kit • Select your own polymerase • Relatively simple to set-up • Higher Batch-to-batch variation Wilhelm Johannsen Centre for Functional Genome Research

17. Rapid DIY kit 0.5X SYBR 1X SYBR 2.5X SYBR 5X SYBR Wilhelm Johannsen Centre for Functional Genome Research

18. Overview • What is PCR? • Quantitation of gene expression • Methodology • Experimental design • Problems • Applications at WJC Wilhelm Johannsen Centre for Functional Genome Research

19. Experimental design • Search WWW for good ideas & help • Always design the experiment before actually doing it & equally important, stick to it!! • Decide how you want to calculate your results • Take the time to create spreadsheets that you will use for the calculations!! Wilhelm Johannsen Centre for Functional Genome Research

20. Wilhelm Johannsen Centre for Functional Genome Research

21. QPCR calculation strategies • Serial dilution of ’known’ standards (standard curves) • ∆c(t) • ∆∆c(t) • PCR efficiency Wilhelm Johannsen Centre for Functional Genome Research

22. QPCR-at-a-glance- WJC-NSGene SOP - • RNA extraction/purchase • RNA quantitation • DNAse treatment • Test for DNA contamination • RNA quantitation • Reverse transcription • Prepare primers spanning intron (if possible) • QPCR gene of interest (GOI) • QPCR house keeping gene (HKG) • Calculation, quality control & normalisation Wilhelm Johannsen Centre for Functional Genome Research

23. Software • GeNorm (Freeware/shareware) • REST (Freeware/shareware) • qBase (Freeware/shareware) • Genex • qGene (Freeware/shareware) • SoFAR (Commercial) • Bestkeeper (Freeware/shareware) • LinReg PCR (Freeware/shareware) • Dart PCR • DATAN (Commercial) Wilhelm Johannsen Centre for Functional Genome Research

24. Spreadsheets • Use a standardized spreadsheet for calculations – it pays off in the long run and saves you a lot of aggravation!! • Use somebody else’s spreadsheet • Build your own spreadsheet around somebody else’s basic work – it saves time! • Create your own spreadsheet from scratch Wilhelm Johannsen Centre for Functional Genome Research

25. WJC-NSgene Spreadsheet • Bestkeeper normalisation (Pfaffl, MW. 2004) • Multiple calculation strategies • Selective removal of: • Kinetic outliers (Bar, T. 2003) • Data points with aberrant melting curves • Data points with large sample variation • Data points outside standard curve Wilhelm Johannsen Centre for Functional Genome Research

26. Overview • What is PCR? • Quantitation of gene expression • Methodology • Experimental design • Problems • Applications at WJC Wilhelm Johannsen Centre for Functional Genome Research

27. Selected QPCR problems • RNA quantity/quality • Quantitation of RNA • Reverse transcription • QPCR itself • Standard curves • Normalisation Wilhelm Johannsen Centre for Functional Genome Research

28. Quantitation of RNA • Spectrophotometric determination • Advantages • Cheap • Fast • Disadvantages • Inaccurate • Fluorimetric determination • Advantages • More accurate • More sensitive • Disadvantages • More expensive • Slower Wilhelm Johannsen Centre for Functional Genome Research

29. RNA quality • RNA quality - a key item for successful QPCR • RT or PCR inhibitors may be carried over during extraction of RNA • Always store RNA at -80 C • Wear gloves • Assess RNA quality best as possible • Agarose gels – rule of thumb: 2 bands; upper twice as intensive as lower • Chip (e.g. Agilent Bioanalyzer) Wilhelm Johannsen Centre for Functional Genome Research

30. Reverse Transcription • Reverse transcription as a major cause for QPCR inconsistency: • RNA extraction • RT time • Choice of Reverse transcriptase • Amount of RNA transcribed • Inhibition by Reverse Transcriptase • Potentially sequence dependent Wilhelm Johannsen Centre for Functional Genome Research

31. Reverse transcription 1- RT time - • Same RNA • 3 RT-reactions • Same RT-mix • 50 min RT, average of 3 genes • 90 min RT, average of 3 genes Wilhelm Johannsen Centre for Functional Genome Research

32. Reverse transcription 2- RT variation - • Same RNA • 3 RT-reactions-3 different days • Different RT-mixes Wilhelm Johannsen Centre for Functional Genome Research

33. Reverse transcription 5- Summary - • Find optimal Time for RT reaction • If possible use same RNA extraction method • Prepare adequate amounts of cDNA to perform all experiments simultaneously • Only compare results from different RT reactions with some scepticism Wilhelm Johannsen Centre for Functional Genome Research

34. cDNA stability • cDNA is remarkable stable when stored at appropriate conditions (-20 C) • No detectable degradation for > 12 months with repeated thawing/freezing cycles • Check cDNA panel occasionally to verify quality Wilhelm Johannsen Centre for Functional Genome Research

35. PCR itself as a problem • The PCR reaction • Template concentration • Inhibitors • Optimization • Plastware • Inadequate thermocycler • The operator • Pipetting errors • Setting up reactions • Wrong PCR programs Wilhelm Johannsen Centre for Functional Genome Research

36. Standard curves • Serial dilutions of known sequences used for ‘metering’ of unknown concentrations • Complexity much different from real life! • Simple to construct • Clones • Purified PCR products • Dynamic range might be compromised Wilhelm Johannsen Centre for Functional Genome Research

37. Dynamic range Wilhelm Johannsen Centre for Functional Genome Research

38. Fuzzing ’bout dynamic range & target genes Wilhelm Johannsen Centre for Functional Genome Research

39. Some ways to circumvent ‘short’ standard curves • Resuspend standard template in a suitable carrier (e.g., tRNA, bacterial DNA, linear acrylamide), to increase complexity • Decrease reaction volume • Increase amount of template in PCR reaction • Change plastware, transparent  white plates increase signal strength • Prepare new primers • Change enzyme/kit • Further optimize PCR reaction (e.g., Magnesium etc.) • Despair…….. Wilhelm Johannsen Centre for Functional Genome Research

40. Standard curve 1- Weirdo - Wilhelm Johannsen Centre for Functional Genome Research

41. Standard curve 2- Weirdo - Wilhelm Johannsen Centre for Functional Genome Research

42. Standard curve 3- Weirdo - Wilhelm Johannsen Centre for Functional Genome Research

43. Standard curve - Summary - • Standard curves can be extended and complexity restored by various additives • Be aware of potential PCR inhibitors! Wilhelm Johannsen Centre for Functional Genome Research

44. Selected QPCR problems • RNA quality • Quantitation of RNA • Reverse transcription • QPCR itself • Standard curves • Normalisation Wilhelm Johannsen Centre for Functional Genome Research

45. Why normalise? • Correct for differences in input template • Initial RNA quantitation • Pipetting errors • Cdna synthesis • ’Housekeeping’ genes used for this purpose should be: • Expressed ubiquitously • Expressed at even levels in all tissues examined • Good ’Housekeeping’ genes – do they exist? Wilhelm Johannsen Centre for Functional Genome Research

46. Normalisation is a relative problem • Single or few related tissues • Many Gene of interest (GOI) • Need few HKGs • Multiple tissues • Many GOI • Need many HKGs Wilhelm Johannsen Centre for Functional Genome Research

47. Adrenal gland Salivary gland Bone marrow Skeletal muscle Cerebellum Spleen Adult brain Testis Heart Thymus Kidney Thyroid Liver Trachea Lung Uterus Placenta Colon Prostate Small intestine Pancreas Fetal brain Spinal cord Fetal liver Corpus callosum Amygdala Caudate nucleus Hippocampus Thalamus Pituitary gland WJC/NsGene cDNA panel Wilhelm Johannsen Centre for Functional Genome Research

48. ‘Semi-related’ tissues Wilhelm Johannsen Centre for Functional Genome Research

49. Genorm’ed HKG factor Wilhelm Johannsen Centre for Functional Genome Research

50. Multi-tissue HKG quagmire! 373 fold difference Wilhelm Johannsen Centre for Functional Genome Research