QRT-PCR

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{{main|Choosing reference genes for qPCR normalisation}}
{{main|Choosing reference genes for qPCR normalisation}}
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Picking reference genes will make or break your quantification via qPCR (real time PCR). If you pick only one reference gene and your pick is not constant across different conditions or samples, your results will be skewed. Choose several reference genes and check whether they satisfy the criteria for a good reference gene.
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Picking reference genes will make or break your quantification via qPCR (real time PCR). If you pick only one reference gene and your pick is not constant across different conditions or samples, your results will be skewed. Choose several reference genes and check whether they satisfy the criteria for a good reference gene. Some commonly used reference genes, like 18S and GAPDH, are known to be problematic but continue to be used.
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Some commonly used reference genes are known to be problematic but continue to be used. 18S is a bad choice because it is typically much more abundant than the mRNA you are probing for (copy numbers should be in the same ballpark) and 18S is degraded differently than the average mRNA. Another common but bad choice is GAPDH. It's not just a metabolic enzyme but has many other functions [http://en.wikipedia.org/wiki/Glyceraldehyde_3-phosphate_dehydrogenase#Additional_functions] and is therefore regulated in many ways. Its levels are not constant [Zhu 2001 PMID 11237753] and problems using GAPDH as a qPCR reference gene have been published [Ke 2000 PMID 10799275, Suzuki 2000 PMID 10948434].
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*'''[[User:Ajeffs|Ajeffs]]''' 06:55, 21 April 2007 (EDT): Screen a handful of ref genes, select the most stable using genorm, bestkeeper etc, use at least 2 reference genes for subsequent reactions and normalisation. Inlcude your genorm M values when publishing qPCR data.
== Primer selection ==
== Primer selection ==

Revision as of 06:29, 8 February 2008

Quantitative reverse transcriptase PCR (QRT-PCR) is a PCR technique used to determine the amount of cDNA in a sample. It is the most commonly used form of quantitative PCR (qPCR). This technique is also called real-time reverse transcriptase PCR.

Contents

Comparison of normalisation methods

There is an ongoing debate what is the best way to normalise qPCR data. Reference genes are the most common method, although single unverified reference genes invalidate the qPCR data generated. Total RNA, ribosomal RNA, and genomic DNA have been suggested as alternative methods.

Reference genes

Most common method. Best practise is a panel, e.g. [1] not just a single reference gene and including data on suitability as reference genes. Often housekeeping gene  is used here instead of reference gene but the term is poorly defined and can be misleading.

RNA

Total rRNA [2] [3], or total RNA. Drawback: rapidly dividing cells will have more rRNA and different rRNA/mRNA ratio which will complicate comparison; difference in cDNA synthesis not taken into account.

Genomic DNA

Genomic DNA or cell number. Drawbacks: RNA degrades faster than RNA which can distort the data; sample cannot be DNase treated; efficiency of cDNA synthesis not taken into account.

Reference mRNAs

Main article: Choosing reference genes for qPCR normalisation

Picking reference genes will make or break your quantification via qPCR (real time PCR). If you pick only one reference gene and your pick is not constant across different conditions or samples, your results will be skewed. Choose several reference genes and check whether they satisfy the criteria for a good reference gene. Some commonly used reference genes, like 18S and GAPDH, are known to be problematic but continue to be used.

  • Ajeffs 06:55, 21 April 2007 (EDT): Screen a handful of ref genes, select the most stable using genorm, bestkeeper etc, use at least 2 reference genes for subsequent reactions and normalisation. Inlcude your genorm M values when publishing qPCR data.

Primer selection

Primer repositories and collections

  • RTPrimerDB is an excellent database storing known primer and probe sequences for popular techniques (SYBR Green I, Taqman, Hybridisation Probes, Molecular Beacon). This can help you save the time of designing and testing your own primers. It is also intended to facilitate standardisation among different laboratories. The database is hosted by the Center for Medical Genetics, Gent, Belgium. Please submit you tested primer pairs.
  • PrimerBank. From the website "PrimerBank is a public resource for PCR primers. These primers are designed for gene expression detection or quantification (real-time PCR). PrimerBank contains over 306,800 primers covering most known human and mouse genes. ...The primer design algorithm has been extensively tested by real-time PCR experiments for PCR specificity and efficiency. We have tested 26,855 primer pairs that correspond to 27,681 mouse genes by Real Time PCR followed by agarose gel electrophoresis and sequencing of the PCR products. The design success rate is 82.6% (22,187 successful primer pairs) based on agarose gel electrophoresis". Don't neglect to check the efficiency and specificity of the oligos yourself though. Link to paper.
  • qPrimerDepot. From the website "This database provides qRT PCR primers for 99.96% human RefSeq sequences. For 99% of intron-bearing genes, the PCR product will cross an exon-exon border which overlaps one of the largest introns. All primers have annealing temperatures approximately 60C". Link to paper.

Primer design

An excellent and fast way to select primers is with the free online-tool Primer3, currently in v0.3. Primer3Plus, a variation of Primer3 has qPCR settings. Or just apply the following or similar settings to Primer3:

  • pair towards 3' end (often more specific, some cDNAs don't contain)
  • pair separated by an exon-exon boundary (reduces genomic background) e.g. last exon & penultimate
  • amplified region must be no biger than 200 bp; usally 60-150 bp
  • GC content: 50-60%
  • min length: 18, max length 24 (best: 20 nt)
  • melting temperature: min 60, max 63, best 60
  • max Tm difference: 10 (shouldn't be more than 1 in final pair)
  • max 3' self complementary: 1
  • max poly-x: 3

Verify by blasting the primers sequences. Target gene should come out with the lowest E value. No other gene should be close. Also check whether possible isoforms will be detected by the candidate primer pair. See also: Designing primers

Sources of variability

Operator

Due to the small amount of liquid handled and the sensitivity of the technique, operator variability is high. Bustin reports that the same qPCR experiment repeated by 3 people using the same reagents lead to very different copy number estimations [Bustin 2002 PMID 12200227, figure 3]:

  • person A: 8·7 × 105
  • person B: 2·8 × 105 different by a factor of 3!
  • person C: 2·7 × 103 different by a factor of 300!!

Reagent lots/age

Different lots of reagents can lead to different results. Experiment repeated by same operator 5 times, same RNA sample, different kits; values are copies/μg total RNA:

  • kit 1: 13±32 × 107
  • kit 2: 5.4±1.6 × 107 - different by a factor of 2.4

Similar experiment with old (9 months 4°C) and new probe (3 months 4°C), values are copies/μg total RNA:

  • old: (5.6 ± 1.3) x 103
  • new: (3.8 ± 0.6) x 108 - different by a factor of 100'000!!

both experiments above from [Bustin 2002 PMID 12200227, figure 4]

Notes

  • The most commonly used specialist reverse transcriptase enzyme for cDNA production is AMV reverse transcriptase. It has RNase H activity (so that RNA molecules are only transcribed once) and has a high temperature stability (to reduce RNA secondary structure and nonspecific primer annealing) [1].
  • Since RNA can degrade with repeated freeze-thaw steps, experimental variability is often seen during successive reverse transcription reactions of the same RNA sample [1].
  • Reverse transcriptase enzymes are notorious for their thermal instability. Repeated removals from the freezer can degrade the efficiency of the enzyme [1].
  • Producing total cDNA from total RNA can be advantageous because
    1. cDNA is more stable than RNA so making total cDNA allows you to make multiple sequence-specific RNA measurements [1].
    2. This approach could reduce experimental variability stemming from RNA degradation [1].
  • To make total cDNA
    1. Use a polyT primer (most but not all eukaryotic mRNA) or random decamers (prokaryotic mRNA) [1].
    2. Random decamers give longer cDNAs on average than random hexamer primers [1].
    3. Use longer reverse transcription reaction times [1].
    4. Ensure that the concentration of deoxynucleotides doesn't run out [1].

Appendix

Specific protocols

See also

External links

  • An excellent, detailed Q-PCR tutorial by Margaret and Richard Hunt, University of South Carolina
  • The venerable qpcrlistserv. Anyone doing qPCR should be subscribed to this list.

References

  1. Matthew B. Avison. Measuring gene expression. New York, NY: Taylor & Francis Group, 2007. isbn:0415374723. [MeasuringGeneExpression]
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