Evidence map›Paper›PMID 16158238›Full record

ArticlePlant molecular biology2005

Comparison of transcript profiling on Arabidopsis microarray platform technologies.

Jeffrey D Pylatuik, Pierre R Fobert

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Plant molecular biology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

2 authors.

Jeffrey D PylatuikPlant Biotechnology Institute, National Research Council Canada, 110 Gymnasium Place, S7N 0W9, Saskatoon, Saskatchewan, Canada.
Pierre R Fobert

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To date there have been few systematic studies comparing the results of transcript profiling from different microarray platform technologies. We evaluated in detail two different Arabidopsis thaliana microarray platforms: our own Genomic Amplicon arrays and the Qiagen long oligonucleotide arrays designed by Operon; furthermore, we cross-validated these arrays against the Affymetrix AG and ATH1 GeneChips. Data were obtained from all three platforms in each of two separate experiments; (1) at 2 h and (2) 8 h following a salicylic acid treatment applied to both wild-type and npr1-3 mutant plants. A total of 20 hybridizations were performed, analyzing the expression of 26,814 unique locus IDs. We demonstrate that intensity rank is a key variable that affects both inter-platform and cross-platform reproducibility. Although general agreement between platform technologies is low, data derived from high signal intensities (90th percentile) can correlate as well between differing platforms as replicates within the same platform (r=0.4-0.7). We also show that the identification of differentially expressed genes by significance analysis of microarrays is influenced by signal intensity and that overlap between significant gene lists from different platform technologies was as high as 67% when low intensity values were removed. Validation of 41 genes by Northern blot hybridization showed that all platform technologies performed well, qualitatively confirming 83-100% of differential gene expression. Our results suggest that the potential for the broad integration of microarray data from different platforms and laboratories is promising.

Indexed as

Gene Expression ProfilingArabidopsisBlotting, NorthernGene Expression Regulation, PlantGenotypeMutationOligonucleotide Array Sequence AnalysisReproducibility of Results

Identifiers

What OpenQuestion holds

Textmetadata
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.