days. One-step RT-PCR is done using the same RNa samples, and PCr products are analyzed by polyacrylamide gel elec trophoresis (PAGE). For some unknown reason, the second experiment shows different quantitative data. Which data ar correct? Without a sufficient number of samples to calculate stan- dard deviation, one cannot make any quantitative analysis For quantitative PCR, the sample size has to be large enough and the standard curve must show that PCR was linear within the range one is examining. To do this, serial dilution of a positive control must be run simultaneously, and the test samples have to fall within this range of amplification. Minimums of three to four samples are required for reliable statistical analysis of the data. It is also a good idea to generate enough cDNA to run multiple experiments to reduce error due to differences in the cDNA syn hesis step. The positive control must also be properly stored so hat loss or damage of DNa does not generate false negative results High-tech, automated PCR synthesis and detection systems are useless if the sample preparation destroys the mRNA, co-purifies PCR inhibitors, or the PCr primer design amplifies genomic DNA. Your results will only be as good as the weakest parameter in your PCR strategy Manipulate the Reaction to Meet Your Needs Table 11.3 describes positive and negative effectors of the PCr reaction. These data can help you plan your experiment or modify our strategy if your results aren't satisfacto DEVELOPINGA PCR STRATEGY THE EXPERIMENTAL STAGE What Are the Practical Criteria for Evaluating a dNA Polymerase for Use in PCR An appreciation of what your research objective requires from a PCr product should be central to your selection of a ther mostable dNa polymerase. Were you planning to identify a rare mutation in a heterogeneous population as in allelic polymor- phisms(Frohman, Dush, and Martin, 1988)? As the copy number gets smaller (less than 10), the need for high-fidelity enzyme or enzyme mixes increases, as discussed below. In contrast, if you're screening a batch of transgenic mice for the presence or absence of a marker gene via Southern hybridization, enzyme fidelity might not be as crucial. Most applications do not require high 296 Aoyagi296 Aoyagi days. One-step RT-PCR is done using the same RNA samples, and PCR products are analyzed by polyacrylamide gel elec￾trophoresis (PAGE). For some unknown reason, the second experiment shows different quantitative data. Which data are correct? Without a sufficient number of samples to calculate stan￾dard deviation, one cannot make any quantitative analysis. For quantitative PCR, the sample size has to be large enough and the standard curve must show that PCR was linear within the range one is examining. To do this, serial dilution of a positive control must be run simultaneously, and the test samples have to fall within this range of amplification. Minimums of three to four samples are required for reliable statistical analysis of the data. It is also a good idea to generate enough cDNA to run multiple experiments to reduce error due to differences in the cDNA syn￾thesis step. The positive control must also be properly stored so that loss or damage of DNA does not generate false negative results. High-tech, automated PCR synthesis and detection systems are useless if the sample preparation destroys the mRNA, co-purifies PCR inhibitors, or the PCR primer design amplifies genomic DNA. Your results will only be as good as the weakest parameter in your PCR strategy. Manipulate the Reaction to Meet Your Needs Table 11.3 describes positive and negative effectors of the PCR reaction. These data can help you plan your experiment or modify your strategy if your results aren’t satisfactory. DEVELOPING A PCR STRATEGY: THE EXPERIMENTAL STAGE What Are the Practical Criteria for Evaluating a DNA Polymerase for Use in PCR? An appreciation of what your research objective requires from a PCR product should be central to your selection of a ther￾mostable DNA polymerase. Were you planning to identify a rare mutation in a heterogeneous population as in allelic polymor￾phisms (Frohman, Dush, and Martin, 1988)? As the copy number gets smaller (less than 10), the need for high-fidelity enzyme or enzyme mixes increases, as discussed below. In contrast, if you’re screening a batch of transgenic mice for the presence or absence of a marker gene via Southern hybridization, enzyme fidelity might not be as crucial. Most applications do not require high