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A plant-based chemical genomics screen for the identification of flowering inducers

Overview of attention for article published in Plant Methods, October 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

blogs
1 blog
twitter
7 tweeters

Citations

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5 Dimensions

Readers on

mendeley
45 Mendeley
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Title
A plant-based chemical genomics screen for the identification of flowering inducers
Published in
Plant Methods, October 2017
DOI 10.1186/s13007-017-0230-2
Pubmed ID
Authors

Martijn Fiers, Jorin Hoogenboom, Alice Brunazzi, Tom Wennekes, Gerco C. Angenent, Richard G. H. Immink

Abstract

Floral timing is a carefully regulated process, in which the plant determines the optimal moment to switch from the vegetative to reproductive phase. While there are numerous genes known that control flowering time, little information is available on chemical compounds that are able to influence this process. We aimed to discover novel compounds that are able to induce flowering in the model plant Arabidopsis. For this purpose we developed a plant-based screening platform that can be used in a chemical genomics study. Here we describe the set-up of the screening platform and various issues and pitfalls that need to be addressed in order to perform a chemical genomics screening on Arabidopsis plantlets. We describe the choice for a molecular marker, in combination with a sensitive reporter that's active in plants and is sufficiently sensitive for detection. In this particular screen, the firefly Luciferase marker was used, fused to the regulatory sequences of the floral meristem identity gene APETALA1 (AP1), which is an early marker for flowering. Using this screening platform almost 9000 compounds were screened, in triplicate, in 96-well plates at a concentration of 25 µM. One of the identified potential flowering inducing compounds was studied in more detail and named Flowering1 (F1). F1 turned out to be an analogue of the plant hormone Salicylic acid (SA) and appeared to be more potent than SA in the induction of flowering. The effect could be confirmed by watering Arabidopsis plants with SA or F1, in which F1 gave a significant reduction in time to flowering in comparison to SA treatment or the control. In this study a chemical genomics screening platform was developed to discover compounds that can induce flowering in Arabidopsis. This platform was used successfully, to identify a compound that can speed-up flowering in Arabidopsis.

Twitter Demographics

The data shown below were collected from the profiles of 7 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 18%
Student > Master 5 11%
Researcher 5 11%
Student > Bachelor 4 9%
Professor > Associate Professor 4 9%
Other 6 13%
Unknown 13 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 40%
Biochemistry, Genetics and Molecular Biology 8 18%
Engineering 2 4%
Chemistry 2 4%
Computer Science 1 2%
Other 0 0%
Unknown 14 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 September 2019.
All research outputs
#2,532,125
of 20,304,732 outputs
Outputs from Plant Methods
#128
of 952 outputs
Outputs of similar age
#51,328
of 295,198 outputs
Outputs of similar age from Plant Methods
#4
of 13 outputs
Altmetric has tracked 20,304,732 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 952 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 295,198 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.