Evidence map›Paper›PMID 17127211›Full record

ReviewGenomics, proteomics & bioinformatics2006

Functional characterization of gibberellin-regulated genes in rice using microarray system.

Asad Jan, Setsuko Komatsu

Abstract readReview
In one paragraph

Review in Genomics, proteomics & bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. OsWRKY114 Is a Player in Rice Immunity againstInternational journal of molecular sciences · 2023
    Article
  2. Article
  3. Article
  4. GAFunctional & integrative genomics · 2018
    Article
  5. Article
  6. Article
  7. 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

2 authors.

Asad JanNational Institute of Agrobiological Sciences, Tsukuba 305-8602, Japan.
Setsuko Komatsu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gibberellin (GA) is collectively referred to a group of diterpenoid acids, some of which act as plant hormones and are essential for normal plant growth and development. DNA microarray technology has become the standard tool for the parallel quantification of large numbers of messenger RNA transcripts. The power of this approach has been demonstrated in dissecting plant physiology and development, and in unraveling the underlying cellular signaling pathways. To understand the molecular mechanism by which GA regulates the growth and development of plants, with reference to the monocot model plant-rice, it is essential to identify and analyze more genes and their products at the transcription and translation levels that are regulated by GA. With the availability of draft sequences of two major rice types, indica and japonica rice, it has become possible to analyze global expression profiles of genes on a genome scale. In this review, the progress made in finding new genes in rice leaf sheath using microarray system and their characterization is discussed. It is believed that the findings made in this regard have important implications for understanding the mechanism by which GA regulates the growth and development of rice.

Indexed as

Gene Expression Regulation, PlantOligonucleotide Array Sequence AnalysisGenomicsGibberellinsGlycosyltransferasesModels, BiologicalOryzaPlant LeavesPlants, Genetically ModifiedProtein KinasesProtein Serine-Threonine KinasesPyruvate Dehydrogenase Acetyl-Transferring KinaseRNA, MessengerGibberellinsGlycosyltransferasesProtein KinasesProtein Serine-Threonine KinasesPyruvate Dehydrogenase Acetyl-Transferring KinaseRNA, Messengerxyloglucan endotransglycosylase

Identifiers

PMID17127211
PMCPMC5054068

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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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.