quantitative RT-PCR

Todd Miller - Pharmacology tmiller at newssun.med.miami.edu
Wed Aug 30 07:53:10 EST 1995

In article <41vv5a$hnt at news.acns.nwu.edu>,
Isaac Kim <ikekim at merle.acns.nwu.edu> wrote:
>To make RT-PCR quantitative, you must use primer sequences that are 
>identical to your target because different primers have different 
>efficiencies of amplification. To do this, you can clone the RT-PCR 
>product and either delete or insert a fragment into the PCR product. Now 
>this 'new' product has same sequence for the primers as the target but 
>can be distinguished by size on an agarose gel electorphoresis. PCR using 
>this 'new' product is truly competitive in that the amplification 
>efficiency is equal to the target.

This critical assumption, that the amplification efficiencies of the
target and the competitor are equal, is actually validated (or in most
cases, *not* validated) by an appropriate plot of the data.  If one
plots log (Tn/Cn) vs log Co, where Tn is the amount of target after n
cycles, Cn is the amount of competitor after n cycles and Co is the
amount of competitor at the beginning of the PCR, one should get a 
straight line with slope equal to |1| (the sign depends on the choice
of axes).  Deviations from a slope of |1| show *how* equal the efficiencies
of amplification of the 2 species were.  If this slope is not |1|,
quantification is not justified because a fundamental assumption of
the technique was not substantiated.  Yet if you look in the literature,
there are lots of plots of this with slopes ranging from 0.6 to well
over |1|.  I suspect this technique is too new to have been fully
examined by the scientific community.  The mathematics and more details
of these considerations can be found in an article by Luc Raeymaekers
in _Analytical Biochemistry_ 214: 582-585, 1993.  Since the plot is
made on log-log scales, and the answer is actually the intercept of
this plot, deviations from the predicted slope = |1| can have huge
affects on the estimate of To, the amount of target present initially.

Todd Miller

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