Evidence map›Paper›PMID 19336411›Full record

ArticleNucleic acids research2009

Real-time monitoring of aRNA production during T7 amplification to prevent the loss of sample representation during microarray hybridization sample preparation.

Isabelle Gilbert, Sara Scantland, Isabelle Dufort, Olga Gordynska, Aurélie Labbe, Marc-André Sirard, Claude Robert

Abstract readValidation Study
In one paragraph

Article in Nucleic acids research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

7 authors.

Isabelle GilbertCentre de Recherche en Biologie de la Reproduction, Département des sciences animales, Université Laval, Québec, Canada.
Sara Scantland
Isabelle Dufort
Olga Gordynska
Aurélie Labbe
Marc-André Sirard
Claude Robert

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene expression analysis performed through comparative abundance of transcripts is facing a new challenge with the increasing need to compare samples of known cell number, such as early embryos or laser microbiopsies, where the RNA contents of identical cellular inputs can by nature be variable. When working with scarce tissues, the success of microarray profiling largely depends on the efficiency of the amplification step as determined by its ability to preserve the relative abundance of transcripts in the resulting amplified sample. Maintaining this initial relative abundance across samples is paramount to the generation of physiologically relevant data when comparing samples of different RNA content. The T7 RNA polymerase (T7-IVT) amplification is widely used for microarray sample preparation. Characterization of the reaction's kinetics has clearly indicated that its true linear phase is of short duration and is followed by a nonlinear phase. This second phase leads to modifications in transcript abundance that biases comparison between samples of different types. The impact assessment performed in this study has shown that the standard amplification protocol significantly lowers the quality of microarray data, rendering more than half of differentially expressed candidates undetected and distorting the true proportional differences of all candidates analyzed.

Indexed as

Nucleic Acid Amplification TechniquesAnimalsCattleDNA-Directed RNA PolymerasesEmbryo, MammalianFemaleGene Expression ProfilingKineticsOligonucleotide Array Sequence AnalysisOligonucleotide ProbesOocytesReverse Transcriptase Polymerase Chain ReactionRNA, AntisenseViral Proteinsbacteriophage T7 RNA polymeraseDNA-Directed RNA PolymerasesOligonucleotide ProbesRNA, AntisenseViral Proteins

Identifiers

PMID19336411
PMCPMC2677895

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Registered trials

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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.