An Introduction to qRT-PCR Assays Using Sybr Green (Using SDS ...
An Introduction to qRT-PCR Assays Using Sybr Green (Using SDS ... An Introduction to qRT-PCR Assays Using Sybr Green (Using SDS ...
can one be certain that an internal control is not also affected by theexperimental treatment?The most reliable approach to this issue is the use of multiple internalcontrols, which allows comparisons between controls as described byVandesompele (2002). This approach requires the use of several internalcontrols, and provides a method of calculating how stable any internal controlis based upon comparison with other internal controls. By then using thegeometric mean, outlier effects are reduced. The primary advantage of thisapproach is the confidence that this provides in the whole normalisationprocess. A secondary advantage is that accurate normalisation helps reduceassay variance (ie: makes it easier to see real differences).A frequently overlooked aspect of gene expression analysis is thewidespread assumption that internal controls will be expressed at the samelevel in different cell types. This is dependent upon the internal control geneexpression accurately reflecting the RNA content of the sample. However, ifdifferent samples contain different cell densities, different cell sizes, ordifferent cell subpopulations (heterogeneity), this may affect the accuracy ofthe comparisons.For example, when comparing the expression of a target gene in thesame volume of RNA extracted from liver and heart, normalisation assumesthat the internal control is expressed similarly in liver and heart. This may notbe the case, and if the gene chosen as an internal control is actually morehighly expressed in the liver, then the normalised expression will as such belower in the liver when compared with the heart.As such, it is recommended that a similar amount of RNA is used foreach reverse transcription reaction (we typically aim for 1 ug RNA), as theinternal control data should therefore be comparable. If this is not the case, itsuggests either differences in RNA quality or RT efficiency, or alternatively, ifdifferent tissues are being analysed, differences in internal control expressionmay occur. Also, it is worth recording the mass of tissue used, the RNA yieldsand the proportion of this that is subsequently used – quantify as much aspossible!c) Quality controlsIf your experimental sample group will all fit on a single plate, then interassaydifferences will not present any problem.However, ongoing assays present a different situation, and necessitatethe use of a quality control – a control sample that is run on every plate,which provides a reference point by which samples from different assays canbe compared. Quality controls may take the form of a standard curve orcDNA samples that are included on every plate, and ideally should bealiquotted prior to use and not freeze-thawed.
One approach is to include the untreated control group on everyexperimental treatment plate, to allow the analysis of experimental effects tobe made with confidence.2) Primer DesignPrimers should be around 20-30 nucleotides long, and have an annealingtemperature of 58-60°C. Product size is not such an issue with Sybr as withTaqMan, and slightly larger products may be advantageous. Products largerthan 100 bp possess a higher melting temperature, and are thus easier toseparate from any primer-dimer artefacts. Secondly, as Sybr green is a DNAbindingdye, larger products will bind more dye and fluoresce more,improving the assay sensitivity. We have found 100-300 bp products workwell, and have used products up to 500 bp with no reduction in amplificationrate.Where possible, primers should be designed to span one or moreintrons, to prevent amplification of genomic DNA (or at least allowdiscrimination between cDNA and gDNA products). Runs of three or more Gand Cs at the 3’ end should be avoided where possible to prevent extension ofmisprimes, and checking primers for complementarity or formation ofprimer-dimers is recommended.Primer TestingPrimers should be tested using Sybr green MM, rather than using normal Taq.As the Sybr MM uses a modified Taq enzyme and contains all the reactioncomponents premixed, little optimisation is possible. As such, primers thatwork well with other kits may not work necessarily work with the Sybr MMand vice versa. As such, time is best spent checking primers with the reactionmix which is going to be used for the assay, and the volumes that are usedcompared to a whole 96-well plate is minimal.Primers can be tested on any representative cDNA, and you do notneed to waste valuable experimental samples testing primers.The following reaction should enable analysis of primers:ulSybr Green MM 25 x 1Primers (25uM stock): F 1 0.5 uMR 1 0.5 uMH20 22cDNA 1FINAL 50 ul
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can one be certain that an internal control is not also affected by theexperimental treatment?The most reliable approach <strong>to</strong> this issue is the use of multiple internalcontrols, which allows comparisons between controls as described byVandesompele (2002). This approach requires the use of several internalcontrols, and provides a method of calculating how stable any internal controlis based upon comparison with other internal controls. By then using thegeometric mean, outlier effects are reduced. The primary advantage of thisapproach is the confidence that this provides in the whole normalisationprocess. A secondary advantage is that accurate normalisation helps reduceassay variance (ie: makes it easier <strong>to</strong> see real differences).A frequently overlooked aspect of gene expression analysis is thewidespread assumption that internal controls will be expressed at the samelevel in different cell types. This is dependent upon the internal control geneexpression accurately reflecting the RNA content of the sample. However, ifdifferent samples contain different cell densities, different cell sizes, ordifferent cell subpopulations (heterogeneity), this may affect the accuracy ofthe comparisons.For example, when comparing the expression of a target gene in thesame volume of RNA extracted from liver and heart, normalisation assumesthat the internal control is expressed similarly in liver and heart. This may notbe the case, and if the gene chosen as an internal control is actually morehighly expressed in the liver, then the normalised expression will as such belower in the liver when compared with the heart.As such, it is recommended that a similar amount of RNA is used foreach reverse transcription reaction (we typically aim for 1 ug RNA), as theinternal control data should therefore be comparable. If this is not the case, itsuggests either differences in RNA quality or RT efficiency, or alternatively, ifdifferent tissues are being analysed, differences in internal control expressionmay occur. Also, it is worth recording the mass of tissue used, the RNA yieldsand the proportion of this that is subsequently used – quantify as much aspossible!c) Quality controlsIf your experimental sample group will all fit on a single plate, then interassaydifferences will not present any problem.However, ongoing assays present a different situation, and necessitatethe use of a quality control – a control sample that is run on every plate,which provides a reference point by which samples from different assays canbe compared. Quality controls may take the form of a standard curve orcDNA samples that are included on every plate, and ideally should bealiquotted prior <strong>to</strong> use and not freeze-thawed.
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