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Mitigation of the effect of variability in digital PCR assays through use of duplexed reference assays for normalization.

ABSTRACT: Digital PCR has been promoted as a technique for obtaining absolute measures of the amount of nucleic acid target sequence in a sample, but still lacks standardization in data reporting. The initial method of representing data as copies per microliter produced inconsistent results and made inter-assay comparisons difficult. Normalizing copies to amount of nucleic acid gives more uniform results, but factors influencing the effective concentration of nucleic acid in the final digital PCR assay must be considered. Using droplet digital PCR and previously validated reference genes duplexed with target genes, a method of normalization was developed to estimate the amount of input nucleic acid in individual assays, subsequently reporting the number of copies of target gene relative to this amount. Correcting for the actual amount of amplifiable nucleic acid present demonstrated a higher correlation between various dilutions of sample mRNA and allowed more accurate comparisons of digital PCR results.

SUBMITTER: Coulter SJ

PROVIDER: S-EPMC6424105 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Mitigation of the effect of variability in digital PCR assays through use of duplexed reference assays for normalization.

Coulter Sherry J SJ

BioTechniques 20180801 2

Digital PCR has been promoted as a technique for obtaining absolute measures of the amount of nucleic acid target sequence in a sample, but still lacks standardization in data reporting. The initial method of representing data as copies per microliter produced inconsistent results and made inter-assay comparisons difficult. Normalizing copies to amount of nucleic acid gives more uniform results, but factors influencing the effective concentration of nucleic acid in the final digital PCR assay mu ...[more]

PMID: 30091389

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Project description:BackgroundNormalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introduce additional variability into normalized expression levels due to innate variation (between tissues, individuals, etc). To minimize this innate variability, multiple reference genes are used. Current methods of selecting reference genes make an assumption of independence in their innate variation. This assumption is not always justified, which may lead to selecting a suboptimal set of reference genes.ResultsWe propose a robust approach for selecting optimal subset(s) of reference genes with the smallest variance of the corresponding normalizing factors. The normalizing factor variance estimates are based on the estimated unstructured covariance matrix of all available candidate reference genes, adjusting for all possible correlations. Robustness is achieved through bootstrapping all candidate reference gene data and obtaining the bootstrap upper confidence limits for the variances of the log-transformed normalizing factors. The selection of the reference gene subset is optimized with respect to one of the following criteria: (A) to minimize the variability of the normalizing factor; (B) to minimize the number of reference genes with acceptable upper limit on variability of the normalizing factor, (C) to minimize the average rank of the variance of the normalizing factor. The proposed approach evaluates all gene subsets of various sizes rather than ranking individual reference genes by their stability, as in the previous work. In two publicly available data sets and one new data set, our approach identified subset(s) of reference genes with smaller empirical variance of the normalizing factor than in subsets identified using previously published methods. A small simulation study indicated an advantage of the proposed approach in terms of sensitivity to identify the true optimal reference subset in the presence of even modest, especially negative correlation among the candidate reference genes.ConclusionsThe proposed approach performs comprehensive and robust evaluation of the variability of normalizing factors based on all possible subsets of candidate reference genes. The results of this evaluation provide flexibility to choose from important criteria for selecting the optimal subset(s) of reference genes, unless one subset meets all the criteria. This approach identifies gene subset(s) with smaller variability of normalizing factors than current standard approaches, particularly if there is some nontrivial innate correlation among the candidate genes.

Project description:BACKGROUND: Usually the reference genes used in gene expression analysis have been chosen for their known or suspected housekeeping roles, however the variation observed in most of them hinders their effective use. The assessed lack of validated reference genes emphasizes the importance of a systematic study for their identification. For selecting candidate reference genes we have developed a simple in silico method based on the data publicly available in the wheat databases Unigene and TIGR. RESULTS: The expression stability of 32 genes was assessed by qRT-PCR using a set of cDNAs from 24 different plant samples, which included different tissues, developmental stages and temperature stresses. The selected sequences included 12 well-known HKGs representing different functional classes and 20 genes novel with reference to the normalization issue. The expression stability of the 32 candidate genes was tested by the computer programs geNorm and NormFinder using five different data-sets. Some discrepancies were detected in the ranking of the candidate reference genes, but there was substantial agreement between the groups of genes with the most and least stable expression. Three new identified reference genes appear more effective than the well-known and frequently used HKGs to normalize gene expression in wheat. Finally, the expression study of a gene encoding a PDI-like protein showed that its correct evaluation relies on the adoption of suitable normalization genes and can be negatively affected by the use of traditional HKGs with unstable expression, such as actin and alpha-tubulin. CONCLUSION: The present research represents the first wide screening aimed to the identification of reference genes and of the corresponding primer pairs specifically designed for gene expression studies in wheat, in particular for qRT-PCR analyses. Several of the new identified reference genes outperformed the traditional HKGs in terms of expression stability under all the tested conditions. The new reference genes will enable more accurate normalization and quantification of gene expression in wheat and will be helpful for designing primer pairs targeting orthologous genes in other plant species.

Project description:The human rhinovirus (RV) is a positive-stranded RNA virus that causes respiratory tract diseases affecting both the upper and lower halves of the respiratory system. RV enhances its replication by concentrating RNA synthesis within a modified host membrane in an intracellular compartment. RV infections often occur alongside infections caused by other respiratory viruses, and the RV virus may remain asymptomatic for extended periods. Alongside qualitative detection, it is essential to accurately quantify RV RNA from clinical samples to explore the relationships between RV viral load, infections caused by the virus, and the resulting symptoms observed in patients. A reference material (RM) is required for quality evaluation, the performance evaluation of molecular diagnostic products, and evaluation of antiviral agents in the laboratory. The preparation process for the RM involves creating an RV RNA mixture by combining RV viral RNA with RNA storage solution and matrix. The resulting RV RNA mixture is scaled up to a volume of 25 mL, then dispensed at 100 µL per vial and stored at -80 °C. The process of measuring the stability and homogeneity of RV RMs was conducted by employing reverse transcription droplet digital polymerase chain reaction (RT-ddPCR). Digital PCR is useful for the analysis of standards and can help to improve measurement compatibility: it represents the equivalence of a series of outcomes for reference materials and samples being analyzed when a few measurement procedures are employed, enabling objective comparisons between quantitative findings obtained through various experiments. The number of copies value represents a measured result of approximately 1.6 × 105 copies/μL. The RM has about an 11% bottle-to-bottle homogeneity and shows stable results for 1 week at temperatures of 4 °C and -20 °C and for 12 months at a temperature of -80 °C. The developed RM can enhance the dependability of RV molecular tests by providing a precise reference value for the absolute copy number of a viral target gene. Additionally, it can serve as a reference for diverse studies.

Dataset Information

Mitigation of the effect of variability in digital PCR assays through use of duplexed reference assays for normalization.

Publications

Mitigation of the effect of variability in digital PCR assays through use of duplexed reference assays for normalization.

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