Inviting an author to review:
Find an author and click ‘Invite to review selected article’ near their name.
Search for authorsSearch for similar articles
49
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Droplet Digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data

      research-article
      1 , , 2 , 2
      Scientific Reports
      Nature Publishing Group UK

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Quantitative PCR (qPCR) has become the gold standard technique to measure cDNA and gDNA levels but the resulting data can be highly variable, artifactual and non-reproducible without appropriate verification and validation of both samples and primers. The root cause of poor quality data is typically associated with inadequate dilution of residual protein and chemical contaminants that variably inhibit Taq polymerase and primer annealing. The most susceptible, frustrating and often most interesting samples are those containing low abundant targets with small expression differences of 2-fold or lower. Here, Droplet Digital PCR (ddPCR) and qPCR platforms were directly compared for gene expression analysis using low amounts of purified, synthetic DNA in well characterized samples under identical reaction conditions. We conclude that for sample/target combinations with low levels of nucleic acids (Cq ≥ 29) and/or variable amounts of chemical and protein contaminants, ddPCR technology will produce more precise, reproducible and statistically significant results required for publication quality data. A stepwise methodology is also described to choose between these complimentary technologies to obtain the best results for any experiment.

          Related collections

          Most cited references18

          • Record: found
          • Abstract: found
          • Article: not found

          A practical approach to RT-qPCR-Publishing data that conform to the MIQE guidelines.

          Given the highly dynamic nature of mRNA transcription and the potential variables introduced in sample handling and in the downstream processing steps (Garson et al. (2009)), a standardized approach to each step of the RT-qPCR workflow is critical for reliable and reproducible results. The MIQE provides this approach with a checklist that contains 85 parameters to assure quality results that will meet the acceptance criteria of any journal (Bustin et al. (2009)). In this paper we demonstrate how to apply the MIQE guidelines (www.rdml.org/miqe) to establish a solid experimental approach. Copyright 2010. Published by Elsevier Inc.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Real-time quantitative RT-PCR: design, calculations, and statistics.

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Statistical significance of quantitative PCR

              Background PCR has the potential to detect and precisely quantify specific DNA sequences, but it is not yet often used as a fully quantitative method. A number of data collection and processing strategies have been described for the implementation of quantitative PCR. However, they can be experimentally cumbersome, their relative performances have not been evaluated systematically, and they often remain poorly validated statistically and/or experimentally. In this study, we evaluated the performance of known methods, and compared them with newly developed data processing strategies in terms of resolution, precision and robustness. Results Our results indicate that simple methods that do not rely on the estimation of the efficiency of the PCR amplification may provide reproducible and sensitive data, but that they do not quantify DNA with precision. Other evaluated methods based on sigmoidal or exponential curve fitting were generally of both poor resolution and precision. A statistical analysis of the parameters that influence efficiency indicated that it depends mostly on the selected amplicon and to a lesser extent on the particular biological sample analyzed. Thus, we devised various strategies based on individual or averaged efficiency values, which were used to assess the regulated expression of several genes in response to a growth factor. Conclusion Overall, qPCR data analysis methods differ significantly in their performance, and this analysis identifies methods that provide DNA quantification estimates of high precision, robustness and reliability. These methods allow reliable estimations of relative expression ratio of two-fold or higher, and our analysis provides an estimation of the number of biological samples that have to be analyzed to achieve a given precision.
                Bookmark

                Author and article information

                Contributors
                Sean_Taylor@bio-rad.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                25 May 2017
                25 May 2017
                2017
                : 7
                : 2409
                Affiliations
                [1 ]ISNI 0000 0001 2187 1663, GRID grid.418312.d, , Bio-Rad Laboratories, Inc., ; Hercules, CA 94547 USA
                [2 ]ISNI 0000 0001 2197 8284, GRID grid.265703.5, Department of Chemistry, Biochemistry and Physics, , Université du Québec à Trois-Rivières, ; 3351 boul. des Forges, Trois-Rivières, QC G9A 5H7 Canada
                Author information
                http://orcid.org/0000-0003-3411-0673
                Article
                2217
                10.1038/s41598-017-02217-x
                5445070
                28546538
                058dcabb-6d7d-4a59-acb4-9137bd6440fd
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 February 2017
                : 7 April 2017
                Categories
                Article
                Custom metadata
                © The Author(s) 2017

                Uncategorized
                Uncategorized

                Comments

                Comment on this article

                scite_
                485
                5
                423
                0
                Smart Citations
                485
                5
                423
                0
                Citing PublicationsSupportingMentioningContrasting
                View Citations

                See how this article has been cited at scite.ai

                scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.

                Similar content212

                Cited by220

                Most referenced authors516