Kinetics Quality Assessment for real-time PCR

For proper DNA quantification by real-time PCR, compared samples should have similar PCR efficiencies. This assumption might not be always correct, as suggested by hundreds of publications dealing with PCR inhibition. The current methods to ensure proper quantification, normalization with reference genes and Internal Amplification Control (IAC), might not address the problem well. Reference and target genes might be inhibited to different levels with different quantitative effect of the inhibitor. Internal amplification controls are difficult to design and produce, and might severely affect the accuracy and sensitivity of quantification up to 10 folds. Kinetics Quality Assessment (Kinetics QA) is a set of statistical tools to verify the requirement of efficiency similarity. In this work we used Kinetics QA to show that dissimilar efficiencies in compared samples are associated with aberrant quantities. Therefore, we suggest using Kinetics QA to assess real-time PCR quality. Kinetics QA tests do not require additional bench work nor reagents, and they do not affect assay accuracy and sensitivity. However, Kinetics QA tools can be used only at the detectable phase of the reaction and therefore we recommend their use to assign technical reason for aberrant results and not automatically exclude any suspected sample

Kinetics Quality Assessment for real-time PCR

For proper DNA quantification by real-time PCR, compared samples should have similar PCR efficiencies. This assumption might not be always correct, as suggested by hundreds of publications dealing with PCR inhibition. The current methods to ensure proper quantification, normalization with reference genes and Internal Amplification Control (IAC), might not address the problem well. Reference and target genes might be inhibited to different levels with different quantitative effect of the inhibitor. Internal amplification controls are difficult to design and produce, and might severely affect the accuracy and sensitivity of quantification up to 10 folds. Kinetics Quality Assessment (Kinetics QA) is a set of statistical tools to verify the requirement of efficiency similarity. In this work we used Kinetics QA to show that dissimilar efficiencies in compared samples are associated with aberrant quantities. Therefore, we suggest using Kinetics QA to assess real-time PCR quality. Kinetics QA tests do not require additional bench work nor reagents, and they do not affect assay accuracy and sensitivity. However, Kinetics QA tools can be used only at the detectable phase of the reaction and therefore we recommend their use to assign technical reason for aberrant results and not automatically exclude any suspected sample

Kinetics quality assessment for relative quantification by real-time PCR

For proper relative quantification by real-time PCR, compared samples should have similar PCR efficiencies. To test this prerequisite, we developed two quality tests: (i) adjustment of a test for kinetic outlier detection (KOD) to relative quantification; and (ii) comparison of the efficiency variance of test samples with the efficiency variance of samples with highly reproducible quantification. The tests were applied on relative quantification of two genes in 30 sets of 5 replicate samples (same treatment, different animals). Ten low-quality sets and 28 outliers were identified. The low-quality sets showed higher coefficient of variation (cv)% of DNA quantities in replicate experiments than high-quality sets (63% versus 26%; P = 0.001) and contained a higher proportion of outlying quantities (35% versus 5.9%; P = 0.001) when individual samples were detected by adjusted KOD. Outlier detection with adjusted KOD reduced thefalse detection of outliers by 213 compared with the previous, nonadjusted version of KOD (20% versus 5.9%; P = 0.001). We conclude that the presented tests can be used to assign technical reasons to outlying observations

Kinetics quality assessment for relative quantification by real-time PCR

For proper relative quantification by real-time PCR, compared samples should have similar PCR efficiencies. To test this prerequisite, we developed two quality tests: (i) adjustment of a test for kinetic outlier detection (KOD) to relative quantification; and (ii) comparison of the efficiency variance of test samples with the efficiency variance of samples with highly reproducible quantification. The tests were applied on relative quantification of two genes in 30 sets of 5 replicate samples (same treatment, different animals). Ten low-quality sets and 28 outliers were identified. The low-quality sets showed higher coefficient of variation (cv)% of DNA quantities in replicate experiments than high-quality sets (63% versus 26%; P = 0.001) and contained a higher proportion of outlying quantities (35% versus 5.9%; P = 0.001) when individual samples were detected by adjusted KOD. Outlier detection with adjusted KOD reduced thefalse detection of outliers by 213 compared with the previous, nonadjusted version of KOD (20% versus 5.9%; P = 0.001). We conclude that the presented tests can be used to assign technical reasons to outlying observations

Kinetic outlier detection (kod) in real-time PCR

Real-time PCR is becoming the method of choice for precise quanti®cation of minute amounts of nucleic acids. For proper comparison of samples, almost all quanti®cation methods assume similar PCR ef®ciencies in the exponential phase of the reaction. However, inhibition of PCR is common when working with biological samples and may invalidate the assumed similarity of PCR ef®ciencies. Here we present a statistical method, Kinetic Outlier Detection (KOD), to detect samples with dissimilar ef®ciencies. KOD is based on a comparison of PCR ef®ciency, estimated from the ampli®cation curve of a test sample, with the mean PCR ef®ciency of samples in a training set. KOD is demonstrated and validated on samples with the same initial number of template molecules, where PCR is inhibited to various degrees by elevated concentrations of dNTP; and in detection of cDNA samples with an aberrant ratio of two genes. Translating the dissimilarity in ef®ciency to quantity, KOD identi®es outliers that differ by 1.3±1.9-fold in their quantity from normal samples with a P-value of 0.05. This precision is higher than the minimal 2-fold difference in number of DNA molecules that real-time PCR usually aims to detect. Thus, KOD may be a useful tool for outlier detection in real-time PCR

Differential gonadotropin-releasing hormone (GnRH) and GnRH receptor messenger ribonucleic acid expression patterns in different tissues of the female rat across the estrous cycle

GnRH, the main regulator of reproduction, is produced in a variety of tissues outside of the hypothalamus, its main site of synthesis and release. We aimed to determine whether GnRH produced in the female rat pituitary and ovaries is involved in the processes leading to ovulation. We studied the expression patterns of GnRH and GnRH receptor (GnRH-R) in the same animals throughout the estrous cycle using real-time PCR. Hypothalamic levels of GnRH mRNA were highest at 1700 h on proestrus, preceding the preovulatory LH surge. No significant changes in the level of hypothalamic GnRH-R mRNA were detected, although fluctuations during the day of proestrus are evident. High pituitary GnRH mRNA was detected during the day of estrus, in the morning of diestrus 1, and at noon on proestrus. Pituitary GnRH-R displayed a similar pattern of expression, except on estrus, when its mRNA levels declined. Ovarian GnRH mRNA levels increased in the morning of diestrus 1 and early afternoon of proestrus. Here, too, GnRH-R displayed a somewhat similar pattern of expression to that of its ligand. To the best of our knowledge, this is the first demonstration of a GnRH expression pattern in the pituitary and ovary of any species. The different timings of the GnRH peaks in the three tissues imply differential tissue-specific regulation. We believe that the GnRH produced in the anterior pituitary and ovary could play a physiological role in the preparation of these organs for the midcycle gonadotropin surge and ovulation, respectively, possibly via local GnRH-gonadotropin axes