Use of real-time PCR for determining copy number and zygosity in transgenic plants

This review examines how real-time PCR can be used to determine copy number and zygosity in transgenic plants. Distinguishing between plants that harbor one and two copies of a transgene or are hemizygous and homozygous requires the ability to routinely distinguish twofold differences, a detection difference which approaches the resolution of PCR-based quantification methods. After explaining the basic principles, especially the threshold cycle (Ct value) as the basic measuring unit in real-time PCR, we introduce three quantitation methods currently in use. While the absolute and relative standard curve approaches are qualitative methods that distinguish high-copy from low-copy transformants, the comparative ( ) method with double-dye oligonucleotides (TaqMan probes) is able to detect twofold differences. In order to obtain reliable results, Ct values for an amplicon should be below 25 and the standard deviation below 0.3. Although real-time PCR can deliver exact copy number determinations, the procedure is not fail-safe. Therefore, real-time PCR should to be viewed as complementary to—rather than as a replacement of—other methods such as Southern analysis, but it is particularly useful as a preliminary screening tool for estimating copy numbers of a large number of transformants.     

Statistical analysis of real-time PCR data

Background  

Even though real-time PCR has been broadly applied in biomedical sciences, data processing procedures for the analysis of quantitative real-time PCR are still lacking; specifically in the realm of appropriate statistical treatment. Confidence interval and statistical significance considerations are not explicit in many of the current data analysis approaches. Based on the standard curve method and other useful data analysis methods, we present and compare four statistical approaches and models for the analysis of real-time PCR data.     

Unbiased and Locally Efficient Estimation of Genetic Effect on Quantitative Trait in the Presence of Population Admixture

Summary Population admixture can be a confounding factor in genetic association studies. Family‐based methods ( Rabinowitz and Larid, 2000 , Human Heredity 50, 211–223) have been proposed in both testing and estimation settings to adjust for this confounding, especially in case‐only association studies. The family‐based methods rely on conditioning on the observed parental genotypes or on the minimal sufficient statistic for the genetic model under the null hypothesis. In some cases, these methods do not capture all the available information due to the conditioning strategy being too stringent. General efficient methods to adjust for population admixture that use all the available information have been proposed ( Rabinowitz, 2002 , Journal of the American Statistical Association 92, 742–758). However these approaches may not be easy to implement in some situations. A previously developed easy‐to‐compute approach adjusts for admixture by adding supplemental covariates to linear models ( Yang et al., 2000 , Human Heredity 50, 227–233). Here is shown that this augmenting linear model with appropriate covariates strategy can be combined with the general efficient methods in Rabinowitz (2002) to provide computationally tractable and locally efficient adjustment. After deriving the optimal covariates, the adjusted analysis can be carried out using standard statistical software packages such as SAS or R . The proposed methods enjoy a local efficiency in a neighborhood of the true model. The simulation studies show that nontrivial efficiency gains can be obtained by using information not accessible to the methods that rely on conditioning on the minimal sufficient statistics. The approaches are illustrated through an analysis of the influence of apolipoprotein E (APOE) genotype on plasma low‐density lipoprotein (LDL) concentration in children.     

Analysis of twin data using SAS

Summary .  Twin studies are essential for assessing disease inheritance. Data generated from twin studies are traditionally analyzed using specialized computational programs. For many researchers, especially those who are new to twin studies, understanding and using those specialized computational programs can be a daunting task. Given that SAS (Statistical Analysis Software) is the most popular software for statistical analysis, we suggest that the use of SAS procedures for twin data may be a helpful alternative and demonstrate that we can obtain similar results from SAS to those produced by specialized computational programs. This numerical validation is practically useful, because a natural concern with general statistical software is whether it can deal with data that are generated from special study designs such as twin studies and if it can test a particular hypothesis. We concluded through our extensive simulation that SAS procedures can be used easily as a very convenient alternative to specialized programs for twin data analysis.     

金黄色葡萄球菌基因表达的DNA扣除法

[目的]金黄色葡萄球菌作为一种分布广泛的致病微生物和研究革兰氏阳性菌遗传背景的模式菌株,利用real-time RT PCR对相关毒素及调控基因进行表达定量分析,在生物、医学、食品检测等领域具有较大研究价值.[方法]对制备好的反转录(RT,含有cDNA和DNA)和非反转录(RTˉ,仅含DNA)样品进行Real-time PCR检测,根据经典(1 E)ˉ△△Ct相对定量算法并结合PCR效率公式建立一种基因表达相对定量分析的DNA扣除法,将得到的Ct值转换为各样品含量,从RT样品中扣除RTˉ样品的量,无需DNaseⅠ酶解处理就可以去除DNA的影响,RTˉ样品的检测结果还可同时作为稳定的DNA内参.[结果]采用以上方法分析金黄色葡萄球菌肠毒素A基因(sea)、16S rRNA和RNA Ⅲ的表达情况,在含有葡萄糖的NB培养基中sea的相对转录水平随着葡萄糖浓度的增大而升高,RNAⅢ的相对转录水平随葡萄糖浓度的变化而产生小幅度的波动,16S rRNA在菌体生长初期时的表达量较为稳定;与绝对定量法比较,结果差异较小(均小于15%),且差异不显著(p＞0.05).[结论]这种基于DNA扣除法的Real-time RT PCR相对定量方法可以有效的对金黄色葡萄球菌的基因表达进行分析.     

大鼠血管组织血管紧张素原基因表达的实时PCR定量分析

目的:探讨大鼠血管组织血管紧张素原(angiotensinogen,AGT)低丰度mRNA表达的实时PCR定量分析方法,并将其用于检测模拟失重大鼠基底和股动脉血管组织AGT mRNA的表达.方法:提取8周模拟失重(SUS)与对照组(CON)大鼠血管组织的总RNA,进行反转录后,对目的基因AGT与内参照基因GAPDH的mRNA进行实时PCR分析.应用TaqMan-MGB探针,测出上述mRNA实时PCR反应的放大效率(E)及阈循环数Ct,再依据一定数学模型由E与Ct得出经GAPDH归一化的AGT mRNA表达变化.结果:与CON相比,SUS大鼠基底动脉组织AGT mRNA表达增加240%,而股动脉组织则降低66%.结论:本工作为定量检测大鼠血管组织低丰度mRNA表达提示了一种特异、灵敏、精确、重复性好的简便方法.     

Optimization of 6-carboxy-X-rhodamine concentration for real-time polymerase chain reaction using molecular beacon chemistry

The optimal 6-carboxy-X-rhodamine (ROX) concentration, which is used as a passive reference dye for real-time quantitative polymerase chain reaction (PCR) with molecular beacon chemistry, was determined with the Mx4000 Multiplex Quantitative PCR System. Additionally, the effects of changing ROX concentrations on PCR reproducibility, Ct values, and efficiency were investigated with this system by using the PCR data obtained from amplification of the Escherichia coli shiga toxin 2 (stx2) gene and the Campylobacter jejuni luxS gene. This study indicated that different ROX concentrations influence many aspects of the real-time PCR reaction. ROX concentration variation could have consequences in the analysis of quantitative data and may lead to erroneous results. This study further indicated that the optimal ROX concentration is 60 nmol/L for real-time PCR, using molecular beacon chemistry for PCR assay of luxS and stx2 genes.     

Processing of gene expression data generated by quantitative real-time RT-PCR

Quantitative real-time PCR represents a highly sensitive and powerful technique for the quantitation of nucleic acids. It has a tremendous potential for the high-throughput analysis of gene expression in research and routine diagnostics. However, the major hurdle is not the practical performance of the experiments themselves but rather the efficient evaluation and the mathematical and statistical analysis of the enormous amount of data gained by this technology, as these functions are not included in the software provided by the manufacturers of the detection systems. In this work, we focus on the mathematical evaluation and analysis of the data generated by quantitative real-time PCR, the calculation of the final results, the propagation of experimental variation of the measured values to the final results, and the statistical analysis. We developed a Microsoft Excel-based software application coded in Visual Basic for Applications, called Q-Gene, which addresses these points. Q-Gene manages and expedites the planning, performance, and evaluation of quantitative real-time PCR experiments, as well as the mathematical and statistical analysis, storage, and graphical presentation of the data. The Q-Gene software application is a tool to cope with complex quantitative real-time PCR experiments at a high-throughput scale and considerably expedites and rationalizes the experimental setup, data analysis, and data management while ensuring highest reproducibility.     

A statistical method for the analysis of nonlinear temperature time series from compost

Temperature is widely accepted as a critical indicator of aerobic microbial activity during composting but, to date, little effort has been made to devise an appropriate statistical approach for the analysis of temperature time series. Nonlinear, time-correlated effects have not previously been considered in the statistical analysis of temperature data from composting, despite their importance and the ubiquity of such features. A novel mathematical model is proposed here, based on a modified Gompertz function, which includes nonlinear, time-correlated effects. Methods are shown to estimate initial values for the model parameter. Algorithms in SAS are used to fit the model to different sets of temperature data from passively aerated compost. Methods are then shown for testing the goodness-of-fit of the model to data. Next, a method is described to determine, in a statistically rigorous manner, the significance of differences among the time-correlated characteristics of the datasets as described using the proposed model. An extra-sum-of-squares method was selected for this purpose. Finally, the model and methods are used to analyze a sample dataset and are shown to be useful tools for the statistical comparison of temperature data in composting.     

Validation testing to determine the sensitivity of lateral flow testing for asymptomatic SARS-CoV-2 detection in low prevalence settings: Testing frequency and public health messaging is key

Lateral flow devices (LFDs) are quickly being implemented for use in large-scale population surveillance programs for SARS-CoV-2 infection in the United Kingdom. These programs have been piloted in city-wide screening in the city of Liverpool and are now being rolled out to support care home visits and the return home of University students for the Christmas break. Here, we present data on the performance of LFDs to test almost 8,000 students at the University of Birmingham between December 2 and December 9, 2020. The performance is validated against almost 800 samples using PCR performed in the University Pillar 2 testing lab and theoretically validated on thousands of Pillar 2 PCR testing results performed on low-prevalence care home testing samples. Our data show that LFDs do not detect infections presenting with PCR Ct values over 29 to 30 as determined using the Thermo Fisher TaqPath asssay. This may be of particular importance in detecting individuals that are either at the early, or late stages of infection, and reinforces the need for frequent, recurrent testing.

Antigen-detecting lateral flow tests are faster than PCR tests in detecting SARS-CoV-2 infection and are being implemented for use in large-scale population surveillance in the UK. An evaluation of the performance of the lateral flow devices, validated using PCR, concludes that lateral flow devices do not detect infections presenting with higher PCR Ct values, reinforcing the need for frequent, recurrent testing.     

Accurate Determination of Zygosity in Transgenic Rice by Real-time PCR Does Not Require Standard Curves or Efficiency Correction

A number of quantitative, real-time PCR methods have been developed for determining transgene copy numbers in plants. Here, we demonstrate that the Roche LightCycler^TM system can be used to determine the zygosity of transgenic lines without the use of standard curves or efficiency correction calculations. We have developed a duplex PCR assay which permits the determination of zygosity, relative to a calibrator sample, in transgenic rice lines containing the gene for a viral glycoprotein. Our data demonstrate that unambiguous 2-fold discrimination of copy number can be attained by calculating relative copy number using the threshold crossing point (Ct) calculated by the LightCycler^TM software combined with delta delta Ct calculations, provided that the appropriate calibrator sample is included in each run. The method presented here is rapid, sensitive, robust and easy to optimise.     

qpcR: an R package for sigmoidal model selection in quantitative real-time polymerase chain reaction analysis

The qpcR library is an add-on to the free R statistical environment performing sigmoidal model selection in real-time quantitative polymerase chain reaction (PCR) data analysis. Additionally, the package implements the most commonly used algorithms for real-time PCR data analysis and is capable of extensive statistical comparison for the selection and evaluation of the different models based on several measures of goodness of fit. AVAILABILITY: www.dr-spiess.de/qpcR.html. SUPPLEMENTARY INFORMATION: Statistical evaluations of the implemented methods can be found at www.dr-spiess.de under 'Supplemental Data'.     

Identification of the carbonic anhydrase II binding site in the Cl(-)/HCO(3)(-) anion exchanger AE1

The human Cl(-)/HCO(3)(-) anion exchanger (AE1) possesses a binding site within its 33 residue carboxyl-terminal region (Ct) for carbonic anhydrase II (CAII). The amino acid sequence comprising this CAII binding site was determined by peptide competition and by testing the ability of truncation and point mutants of the Ct sequence to bind CAII with a sensitive microtiter plate binding assay. A synthetic peptide consisting of the entire 33 residues of the Ct (residues 879-911) could compete with a GST fusion protein of the Ct (GST-Ct) for binding to immobilized CAII, while a peptide consisting of the last 16 residues (896-911) could not. A series of truncation mutants of the GST-Ct showed that the terminal 21 residues of AE1 were not required for binding CAII. Removal of four additional residues (887-890) from the Ct resulted in loss of CAII binding. Acidic residues in this region (D887ADD) were critical for binding since mutating this sequence in the GST-Ct to DAAA, AAAA, or NANN caused loss of CAII binding. A GST-Ct construct mutated to D887ANE, the homologous sequence in AE2, could bind CAII. AE2 is a widely expressed anion exchanger and has a homologous Ct region with 60% sequence identity to AE1. A GST fusion protein of the 33 residue Ct of AE2 could bind to CAII similarly to the Ct of AE1. Tethering of CAII to an acidic motif within the Ct of anion exchangers may be a general mechanism for promoting bicarbonate transport across cell membranes.     

Mathematical model of real-time PCR kinetics

Several real-time PCR (rtPCR) quantification techniques are currently used to determine the expression levels of individual genes from rtPCR data in the form of fluorescence intensities. In most of these quantification techniques, it is assumed that the efficiency of rtPCR is constant. Our analysis of rtPCR data shows, however, that even during the exponential phase of rtPCR, the efficiency of the reaction is not constant, but is instead a function of cycle number. In order to understand better the mechanisms belying this behavior, we have developed a mathematical model of the annealing and extension phases of the PCR process. Using the model, we can simulate the PCR process over a series of reaction cycles. The model thus allows us to predict the efficiency of rtPCR at any cycle number, given a set of initial conditions and parameter values, which can mostly be estimated from biophysical data. The model predicts a precipitous decrease in cycle efficiency when the product concentration reaches a sufficient level for template-template re-annealing to compete with primer-template annealing; this behavior is consistent with available experimental data. The quantitative understanding of rtPCR provided by this model can allow us to develop more accurate methods to quantify gene expression levels from rtPCR data.     

Statistics of interlaboratory in vitro toxicological studies

Interlaboratory studies are common in toxicology, particularly for the introduction of alternative assays. Numerous papers are available on the statistical analysis of interlaboratory studies, but these deal primarily with the case of a replicated single sample studied in several laboratories. This approach can be used for some assays, but for the majority, the results will be unsatisfactory, i.e. involving great variability between both the dose groups and the laboratories. However, the primary objective of toxicological assays is to achieve similarity between the sizes of effects, rather than to determine absolute values. In the parametric model, the sizes of effects are the studentised differences from the negative control or, for the commonly used dose-response designs, the similarity of the slopes of the dose-response curves. Standard approaches for the estimation of intralaboratory and interlaboratory variability, including Mandel plots, are introduced, and new approaches are presented for demonstrating similarity of effect sizes, with or without assuming a dose-response model. One approach is based on a modification of the parallel-line assay, the other is based on a modification of the interaction contrasts of the analysis of variance. SAS programs are given for all approaches, and real data from an interlaboratory immunotoxicological study are analysed as a demonstration.     

Standardisation of data from real-time quantitative PCR methods – evaluation of outliers and comparison of calibration curves

Background  

As real-time quantitative PCR (RT-QPCR) is increasingly being relied upon for the enforcement of legislation and regulations dependent upon the trace detection of DNA, focus has increased on the quality issues related to the technique. Recent work has focused on the identification of factors that contribute towards significant measurement uncertainty in the real-time quantitative PCR technique, through investigation of the experimental design and operating procedure. However, measurement uncertainty contributions made during the data analysis procedure have not been studied in detail. This paper presents two additional approaches for standardising data analysis through the novel application of statistical methods to RT-QPCR, in order to minimise potential uncertainty in results.