Evidence map›Paper›PMID 15156357›Full record

ReviewFunctional & integrative genomics2004

Activation tagging in plants: a tool for gene discovery.

Helen Tani, Xinwei Chen, Pedro Nurmberg, John J Grant, Marjorie SantaMaria, Andrea Chini, Eleanor Gilroy, Paul R J Birch, Gary J Loake

Abstract readReview
PubMed Publisher
In one paragraph

Review in Functional & integrative genomics, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Review
  2. Article
  3. A partial T-DNA insertion nearmicroPublication biology · 2020
    Article
  4. Article
  5. Article
  6. Article
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  8. Article
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  11. Article
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  14. Article
  15. Article
  16. Article
  17. Review
  18. A barley activation tagging system.Plant molecular biology · 2007
    Article
  19. Article
  20. 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

9 authors.

Helen TaniInstitute of Cell and Molecular Biology, University of Edinburgh, King's Buildings, EH9 3JH, Edinburgh, UK.
Xinwei Chen
Pedro Nurmberg
John J Grant
Marjorie SantaMaria
Andrea Chini
Eleanor Gilroy
Paul R J Birch
Gary J Loake

Funding

Biotechnology and Biological Sciences Research Council 15/P16595Biotechnology and Biological Sciences Research Council 15/P20067
6 · The paper itself

Abstract

A significant limitation of classical loss-of-function screens designed to dissect genetic pathways is that they rarely uncover genes that function redundantly, are compensated by alternative metabolic or regulatory circuits, or which have an additional role in early embryo or gametophyte development. Activation T-DNA tagging is one approach that has emerged in plants to help circumvent these potential problems. This technique utilises a T-DNA sequence that contains four tandem copies of the cauliflower mosaic virus (CaMV) 35S enhancer sequence. This element enhances the expression of neighbouring genes either side of the randomly integrated T-DNA tag, resulting in gain-of-function phenotypes. Activation tagging has identified a number of genes fundamental to plant development, metabolism and disease resistance in Arabidopsis. This review provides selected examples of these discoveries to highlight the utility of this technology. The recent development of activation tagging strategies for other model plant systems and the construction of new more sophisticated vectors for the generation of conditional alleles are also discussed. These recent advances have significantly expanded the horizons for gain-of-function genetics in plants.

Indexed as

Genes, PlantGenetic TechniquesMutagenesisImmunity, InnateModels, BiologicalPlant DevelopmentPlants

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.