Evidence map›Paper›PMID 29145448›Full record

ArticlePloS one2017

Steps to achieve quantitative measurements of microRNA using two step droplet digital PCR.

Erica V Stein, David L Duewer, Natalia Farkas, Erica L Romsos, Lili Wang, Kenneth D Cole

Abstract readValidation Study
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Droplet Digital CRISPR for Nucleic Acid Detection.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Erica V SteinBiosystems and Biomaterials Division, Materials Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America.ORCID http://orcid.org/0000-0001-8778-8846
David L DuewerChemical Sciences Division, Materials Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America.
Natalia FarkasEngineering Physics Division, Physical Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America.
Erica L RomsosBiomolecular Measurement Division, Materials Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America.
Lili WangBiosystems and Biomaterials Division, Materials Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America.
Kenneth D ColeBiosystems and Biomaterials Division, Materials Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, Maryland, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Droplet digital PCR (ddPCR) is being advocated as a reference method to measure rare genomic targets. It has consistently been proven to be more sensitive and direct at discerning copy numbers of DNA than other quantitative methods. However, one of the largest obstacles to measuring microRNA (miRNA) using ddPCR is that reverse transcription efficiency depends upon the target, meaning small RNA nucleotide composition directly effects primer specificity in a manner that prevents traditional quantitation optimization strategies. Additionally, the use of reagents that are optimized for miRNA measurements using quantitative real-time PCR (qRT-PCR) appear to either cause false positive or false negative detection of certain targets when used with traditional ddPCR quantification methods. False readings are often related to using inadequate enzymes, primers and probes. Given that two-step miRNA quantification using ddPCR relies solely on reverse transcription and uses proprietary reagents previously optimized only for qRT-PCR, these barriers are substantial. Therefore, here we outline essential controls, optimization techniques, and an efficacy model to improve the quality of ddPCR miRNA measurements. We have applied two-step principles used for miRNA qRT-PCR measurements and leveraged the use of synthetic miRNA targets to evaluate ddPCR following cDNA synthesis with four different commercial kits. We have identified inefficiencies and limitations as well as proposed ways to circumvent identified obstacles. Lastly, we show that we can apply these criteria to a model system to confidently quantify miRNA copy number. Our measurement technique is a novel way to quantify specific miRNA copy number in a single sample, without using standard curves for individual experiments. Our methodology can be used for validation and control measurements, as well as a diagnostic technique that allows scientists, technicians, clinicians, and regulators to base miRNA measures on a single unit of measurement rather than a ratio of values.

Indexed as

Cell LineDNA, ComplementaryHumansMicroRNAsReal-Time Polymerase Chain ReactionTemperatureDNA, ComplementaryMicroRNAs

Identifiers

PMID29145448
PMCPMC5690473

What OpenQuestion holds

Textmetadata
LicenceCC0
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.