Dataset Information

Deconvolution of the confounding variations for reverse transcription quantitative real-time polymerase chain reaction by separate analysis of biological replicate data.

ABSTRACT: Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) uses threshold cycles (Ct values) for measuring relative gene expression. Ct values are signal-to-noise data composed of target gene expression and multiple sources of confounding variations. Data analysis is to minimize technical noises, evaluate biological variances, and estimate treatment-attributable expression changes of particular genes. However, this function is not sufficiently fulfilled in current analytic methods. An important but unrecognizable problem is that Ct values from all biological replicates and technical repeats are pooled across genes and treatment types. This violates the sample-specific association between target and reference genes, leading to inefficient removal of technical noises. To resolve this problem, here we propose to separate Ct values into replicate-specific data subsets and iteratively analyze expression ratios for individual data subsets. The individual expression ratios, rather than the raw Ct values, are pooled to determine the final expression change. The variances of all biological replicates and technical repeats across all target and reference genes are summed up. Our results from example data demonstrate that this separated method can substantially minimize RT-qPCR variance compared with the traditional methods using pooled Ct profiles. This analytic strategy is more effective in control of technical noises and improves the fidelity of RT-qPCR quantification.

SUBMITTER: Ling D

PROVIDER: S-EPMC3427637 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Deconvolution of the confounding variations for reverse transcription quantitative real-time polymerase chain reaction by separate analysis of biological replicate data.

Ling Daijun D Pike Christian J CJ Salvaterra Paul M PM

Analytical biochemistry 20120502 1

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) uses threshold cycles (Ct values) for measuring relative gene expression. Ct values are signal-to-noise data composed of target gene expression and multiple sources of confounding variations. Data analysis is to minimize technical noises, evaluate biological variances, and estimate treatment-attributable expression changes of particular genes. However, this function is not sufficiently fulfilled in current analytic ...[more]

PMID: 22561916

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Project description:The definitive diagnosis of lyssavirus infection (including rabies) in animals and humans is based on laboratory confirmation. The reference techniques for post-mortem rabies diagnosis are still based on direct immunofluorescence and virus isolation, but molecular techniques, such as polymerase chain reaction (PCR) based methods, are increasingly being used and now constitute the principal tools for diagnosing rabies in humans and for epidemiological analyses. However, it remains a key challenge to obtain relevant specificity and sensitivity with these techniques while ensuring that the genetic diversity of lyssaviruses does not compromise detection. We developed a dual combined real-time reverse transcription polymerase chain reaction (combo RT-qPCR) method for pan-lyssavirus detection. This method is based on two complementary technologies: a probe-based (TaqMan) RT-qPCR for detecting the RABV species (pan-RABV RT-qPCR) and a second reaction using an intercalating dye (SYBR Green) to detect other lyssavirus species (pan-lyssa RT-qPCR). The performance parameters of this combined assay were evaluated with a large panel of primary animal samples covering almost all the genetic variability encountered at the viral species level, and they extended to almost all lyssavirus species characterized to date. This method was also evaluated for the diagnosis of human rabies on 211 biological samples (positive n = 76 and negative n = 135) including saliva, skin and brain biopsies. It detected all 41 human cases of rabies tested and confirmed the sensitivity and the interest of skin biopsy (91.5%) and saliva (54%) samples for intra-vitam diagnosis of human rabies. Finally, this method was successfully implemented in two rabies reference laboratories in enzootic countries (Cambodia and Morocco). This combined RT-qPCR method constitutes a relevant, useful, validated tool for the diagnosis of rabies in both humans and animals, and represents a promising tool for lyssavirus surveillance.

Project description:Background and aimDifferent polymerase chain reaction (PCR) techniques have and are still being used for the direct detection of Brucella DNA in serum samples of different animal species and humans without being validated or properly validated, resulting in discrepancies. Thus, this study aimed to evaluate the diagnostic performance of the TaqMan Real-Time-PCR (RT-PCR) targeting the bcsp31 gene versus conventional PCR for the accurate diagnosis of brucellosis at the genus level in cattle sera.Materials and methodsOne hundred and eighty-four serum samples were collected from bacteriologically positive and negative cows with ages ranging from 1 to 5 years old at some infected private farms in the Nile Delta under quarantine measures as well as brucellosis free farms. These samples were classified into four groups after serological diagnosis and investigated by TaqMan RT-PCR and conventional PCR targeting the IS711 gene for Brucella DNA detection. The diagnostic performance characteristics of both PCR techniques were estimated considering the bacteriological results as a gold standard.ResultsTaqMan RT-PCR revealed superiority over conventional PCR; it was able to detect Brucella DNA in 95% (67/70) and 89% (25/28) of the cattle sera samples belonging to Group 1 (serologically and bacteriologically positive) and Group 2 (serologically negative but bacteriologically positive), respectively. On evaluating the diagnostic performance, TaqMan RT-PCR showed superior diagnostic sensitivity (93.9%), diagnostic specificity (88.4%), performance index (182.3), almost perfect kappa agreement (0.825±0.042), strong positive correlation (r=0.826), high accuracy based on the receiver operating characteristic (ROC) curve, and area under the ROC curve (0.911) at p<0.05 and CI of 95%.ConclusionA cattle serum sample is not the metric of choice for targeting Brucella genomic DNA by conventional PCR. The time-saving and rapid TaqMan RT-PCR method revealed a better diagnostic performance in the detection of Brucella DNA in cattle sera. Such performance offered by TaqMan RT-PCR may be considered a step toward the possibility of using such technology in the direct differentiation between Brucella-infected and -vaccinated cattle immunized by smooth vaccines from cattle sera using primers specific for such vaccines.

Dataset Information

Deconvolution of the confounding variations for reverse transcription quantitative real-time polymerase chain reaction by separate analysis of biological replicate data.

Publications

Deconvolution of the confounding variations for reverse transcription quantitative real-time polymerase chain reaction by separate analysis of biological replicate data.

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