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Real-time PCR-based method for the estimation of genome sizes.

ABSTRACT: The fast and reliable estimation of the genome sizes of various species would allow for a systematic analysis of many organisms and could reveal insights into evolutionary processes. Many methods for the estimation of genome sizes have already been described. The classical methods are based on the determination of the phosphate content in the DNA backbone of total DNA isolated from a defined number of cells or on reassociation kinetics of high molecular weight genomic DNA (c(0)t assay). More recent techniques employ DNA-specific fluorescent dyes in flow cytometry analysis, image analysis or absorption cytometry after Feulgen staining. The method presented here is based on the absolute quantification of genetic elements in a known amount (mass) of genomic DNA by real-time quantitative PCR. The method was evaluated on three different eukaryotic species, Saccharomyces cerevisiae (12.1 Mb), Xiphophorus maculatus (550 Mb) and Homo sapiens sapiens (2.9 Gb), and found to be fast, highly accurate and reliable.

SUBMITTER: Wilhelm J

PROVIDER: S-EPMC156059 | biostudies-literature | 2003 May

REPOSITORIES: biostudies-literature

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Real-time PCR-based method for the estimation of genome sizes.

Wilhelm Jochen J Pingoud Alfred A Hahn Meinhard M

Nucleic acids research 20030501 10

The fast and reliable estimation of the genome sizes of various species would allow for a systematic analysis of many organisms and could reveal insights into evolutionary processes. Many methods for the estimation of genome sizes have already been described. The classical methods are based on the determination of the phosphate content in the DNA backbone of total DNA isolated from a defined number of cells or on reassociation kinetics of high molecular weight genomic DNA (c(0)t assay). More rec ...[more]

PMID: 12736322

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Project description:BackgroundAs compared with traditional transgene copy number detection technologies such as Southern blot analysis, real-time PCR provides a fast, inexpensive and high-throughput alternative. However, the real-time PCR based transgene copy number estimation tends to be ambiguous and subjective stemming from the lack of proper statistical analysis and data quality control to render a reliable estimation of copy number with a prediction value. Despite the recent progresses in statistical analysis of real-time PCR, few publications have integrated these advancements in real-time PCR based transgene copy number determination.ResultsThree experimental designs and four data quality control integrated statistical models are presented. For the first method, external calibration curves are established for the transgene based on serially-diluted templates. The Ct number from a control transgenic event and putative transgenic event are compared to derive the transgene copy number or zygosity estimation. Simple linear regression and two group T-test procedures were combined to model the data from this design. For the second experimental design, standard curves were generated for both an internal reference gene and the transgene, and the copy number of transgene was compared with that of internal reference gene. Multiple regression models and ANOVA models can be employed to analyze the data and perform quality control for this approach. In the third experimental design, transgene copy number is compared with reference gene without a standard curve, but rather, is based directly on fluorescence data. Two different multiple regression models were proposed to analyze the data based on two different approaches of amplification efficiency integration. Our results highlight the importance of proper statistical treatment and quality control integration in real-time PCR-based transgene copy number determination.ConclusionThese statistical methods allow the real-time PCR-based transgene copy number estimation to be more reliable and precise with a proper statistical estimation. Proper confidence intervals are necessary for unambiguous prediction of trangene copy number. The four different statistical methods are compared for their advantages and disadvantages. Moreover, the statistical methods can also be applied for other real-time PCR-based quantification assays including transfection efficiency analysis and pathogen quantification.

Project description:BackgroundCurrently real time PCR is the most precise method by which to measure gene expression. The method generates a large amount of raw numerical data and processing may notably influence final results. The data processing is based either on standard curves or on PCR efficiency assessment. At the moment, the PCR efficiency approach is preferred in relative PCR whilst the standard curve is often used for absolute PCR. However, there are no barriers to employ standard curves for relative PCR. This article provides an implementation of the standard curve method and discusses its advantages and limitations in relative real time PCR.ResultsWe designed a procedure for data processing in relative real time PCR. The procedure completely avoids PCR efficiency assessment, minimizes operator involvement and provides a statistical assessment of intra-assay variation. The procedure includes the following steps. (I) Noise is filtered from raw fluorescence readings by smoothing, baseline subtraction and amplitude normalization. (II) The optimal threshold is selected automatically from regression parameters of the standard curve. (III) Crossing points (CPs) are derived directly from coordinates of points where the threshold line crosses fluorescence plots obtained after the noise filtering. (IV) The means and their variances are calculated for CPs in PCR replicas. (V) The final results are derived from the CPs' means. The CPs' variances are traced to results by the law of error propagation. A detailed description and analysis of this data processing is provided. The limitations associated with the use of parametric statistical methods and amplitude normalization are specifically analyzed and found fit to the routine laboratory practice. Different options are discussed for aggregation of data obtained from multiple reference genes.ConclusionA standard curve based procedure for PCR data processing has been compiled and validated. It illustrates that standard curve design remains a reliable and simple alternative to the PCR-efficiency based calculations in relative real time PCR.

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Real-time PCR-based method for the estimation of genome sizes.

Publications

Real-time PCR-based method for the estimation of genome sizes.

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