Evidence map›Paper›PMID 28510204›Full record

ArticleBotanical studies2017

Microarray meta-analysis to explore abiotic stress-specific gene expression patterns in Arabidopsis.

Po-Chih Shen, Ai-Ling Hour, Li-Yu Daisy Liu

Abstract read
In one paragraph

Article in Botanical studies, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Novel candidate genes for environmental stresses response in Synechocystis sp. PCC 6803 revealed by machine learning algorithms.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2024
    Article
  4. Article
  5. TheNAR genomics and bioinformatics · 2020
    Article
  6. Molecular Analysis of UV-C Induced Resveratrol Accumulation inInternational journal of molecular sciences · 2019
    Article
  7. Article
  8. Article
  9. Review
  10. 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

3 authors.

Po-Chih ShenBiometrics Division, Department of Agronomy, National Taiwan University, Taipei, Taiwan.
Ai-Ling HourDepartment of Life Science, Fu-Jen Catholic University, Xinbei, Taiwan.
Li-Yu Daisy LiuBiometrics Division, Department of Agronomy, National Taiwan University, Taipei, Taiwan. lyliu@ntu.edu.tw.ORCID http://orcid.org/0000-0001-6997-8101

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAbiotic stresses are the major limiting factors that affect plant growth, development, yield and final quality. Deciphering the underlying mechanisms of plants' adaptations to stresses using few datasets might overlook the different aspects of stress tolerance in plants, which might be simultaneously and consequently operated in the system. Fortunately, the accumulated microarray expression data offer an opportunity to infer abiotic stress-specific gene expression patterns through meta-analysis. In this study, we propose to combine microarray gene expression data under control, cold, drought, heat, and salt conditions and determined modules (gene sets) of genes highly associated with each other according to the observed expression data.

resultsBy analyzing the expression variations of the Eigen genes from different conditions, we had identified two, three, and five gene modules as cold-, heat-, and salt-specific modules, respectively. Most of the cold- or heat-specific modules were differentially expressed to a particular degree in shoot samples, while most of the salt-specific modules were differentially expressed to a particular degree in root samples. A gene ontology (GO) analysis on the stress-specific modules suggested that the gene modules exclusively enriched stress-related GO terms and that different genes under the same GO terms may be alternatively disturbed in different conditions. The gene regulatory events for two genes, DREB1A and DEAR1, in the cold-specific gene module had also been validated, as evidenced through the literature search.

conclusionsOur protocols study the specificity of the gene modules that were specifically activated under a particular type of abiotic stress. The biplot can also assist to visualize the stress-specific gene modules. In conclusion, our approach has the potential to further elucidate mechanisms in plants and beneficial for future experiments design under different abiotic stresses.

Indexed as

Abiotic stressAnalysis of varianceBiplotGene moduleSingular value decompositionThe coefficient of intrinsic dependenceThe weighted gene co-expression network analysis

Identifiers

PMID28510204
PMCPMC5432924

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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.