Evidence map›Paper›PMID 25888347›Full record

ArticleBMC molecular biology2015

Pre-amplification in the context of high-throughput qPCR gene expression experiment.

Vlasta Korenková, Justin Scott, Vendula Novosadová, Marie Jindřichová, Lucie Langerová, David Švec, Monika Šídová, Robert Sjöback

Open access · hybridAbstract read
In one paragraph

Article in BMC molecular biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
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

24 citing papers in PubMed, 48 citations in OpenAlex.

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  14. Development of a high-throughput real-time PCR system for detection of enzootic pathogens in pigs.Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc · 2020
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  19. Subtyping of Swine Influenza Viruses Using a High-Throughput Real-Time PCR Platform.Frontiers in cellular and infection microbiology · 2018
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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

8 authors at 4 institutions in 4 countries.

Vlasta KorenkováLaboratory of Gene Expression, Institute of Biotechnology, Academy of Sciences of the Czech Republic, Prague, Czech Republic. vlasta.korenkova@ibt.cas.cz.
Justin ScottQFAB Bioinformatics, University of Queensland - St Lucia QLD, Brisbane, Australia. j.scott@qfab.org.
Vendula NovosadováLaboratory of Gene Expression, Institute of Biotechnology, Academy of Sciences of the Czech Republic, Prague, Czech Republic. vendula.novosadova@ibt.cas.cz.
Marie JindřichováLaboratory of Gene Expression, Institute of Biotechnology, Academy of Sciences of the Czech Republic, Prague, Czech Republic. M.Jindrichova@seznam.cz.
Lucie LangerováLaboratory of Gene Expression, Institute of Biotechnology, Academy of Sciences of the Czech Republic, Prague, Czech Republic. lucie.langerova@ibt.cas.cz.
David ŠvecLaboratory of Gene Expression, Institute of Biotechnology, Academy of Sciences of the Czech Republic, Prague, Czech Republic. david.svec@ibt.cas.cz.
Monika ŠídováLaboratory of Gene Expression, Institute of Biotechnology, Academy of Sciences of the Czech Republic, Prague, Czech Republic. monika.sidova@ibt.cas.cz.
Robert SjöbackTATAA Biocenter, Göthenburg, Sweden. robert.sjoback@tataa.com.
Czech Academy of Sciences · CZInstitute of Microbiology · BYTataa Biocenter (Sweden) · SEThe University of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the introduction of the first high-throughput qPCR instrument on the market it became possible to perform thousands of reactions in a single run compared to the previous hundreds. In the high-throughput reaction, only limited volumes of highly concentrated cDNA or DNA samples can be added. This necessity can be solved by pre-amplification, which became a part of the high-throughput experimental workflow. Here, we focused our attention on the limits of the specific target pre-amplification reaction and propose the optimal, general setup for gene expression experiment using BioMark instrument (Fluidigm).

resultsFor evaluating different pre-amplification factors following conditions were combined: four human blood samples from healthy donors and five transcripts having high to low expression levels; each cDNA sample was pre-amplified at four cycles (15, 18, 21, and 24) and five concentrations (equivalent to 0.078 ng, 0.32 ng, 1.25 ng, 5 ng, and 20 ng of total RNA). Factors identified as critical for a success of cDNA pre-amplification were cycle of pre-amplification, total RNA concentration, and type of gene. The selected pre-amplification reactions were further tested for optimal Cq distribution in a BioMark Array. The following concentrations combined with pre-amplification cycles were optimal for good quality samples: 20 ng of total RNA with 15 cycles of pre-amplification, 20x and 40x diluted; and 5 ng and 20 ng of total RNA with 18 cycles of pre-amplification, both 20x and 40x diluted.

conclusionsWe set up upper limits for the bulk gene expression experiment using gene expression Dynamic Array and provided an easy-to-obtain tool for measuring of pre-amplification success. We also showed that variability of the pre-amplification, introduced into the experimental workflow of reverse transcription-qPCR, is lower than variability caused by the reverse transcription step.

Indexed as

Gene Expression ProfilingHealthy VolunteersHumansReverse Transcriptase Polymerase Chain ReactionRNA, MessengerSensitivity and SpecificityRNA, Messenger

Identifiers

PMID25888347
PMCPMC4365555
OpenAlexW2006369674

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.