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Combinatorial activities of SHORT VEGETATIVE PHASE and FLOWERING LOCUS C define distinct modes of flowering regulation in Arabidopsis

Overview of attention for article published in Genome Biology, February 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)

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12 X users
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6 Facebook pages

Citations

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145 Dimensions

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186 Mendeley
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3 CiteULike
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Title
Combinatorial activities of SHORT VEGETATIVE PHASE and FLOWERING LOCUS C define distinct modes of flowering regulation in Arabidopsis
Published in
Genome Biology, February 2015
DOI 10.1186/s13059-015-0597-1
Pubmed ID
Authors

Julieta L Mateos, Pedro Madrigal, Kenichi Tsuda, Vimal Rawat, René Richter, Maida Romera-Branchat, Fabio Fornara, Korbinian Schneeberger, Paweł Krajewski, George Coupland

Abstract

The initiation of flowering is an important developmental transition as it marks the beginning of the reproductive phase in plants. The MADS-box transcription factors (TFs) FLOWERING LOCUS C (FLC) and SHORT VEGETATIVE PHASE (SVP) form a complex to repress the expression of genes that initiate flowering in Arabidopsis. Both TFs play a central role in the regulatory network by conferring seasonal patterns of flowering. However, their interdependence and biological relevance when acting as a complex have not been extensively studied. We characterized the effects of both TFs individually and as a complex on flowering initiation using transcriptome profiling and DNA-binding occupancy. We find four major clusters regulating transcriptional responses, and that DNA binding scenarios are highly affected by the presence of the cognate partner. Remarkably, we identify genes whose regulation depends exclusively on simultaneous action of both proteins, thus distinguishing between the specificity of the SVP:FLC complex and that of each TF acting individually. The downstream targets of the SVP:FLC complex include a higher proportion of genes regulating floral induction, whereas those bound by either TF independently are biased towards floral development. Many genes involved in gibberellin-related processes are bound by the SVP:FLC complex, suggesting that direct regulation of gibberellin metabolism by FLC and SVP contributes to their effects on flowering. The regulatory codes controlled by SVP and FLC were deciphered at the genome-wide level revealing substantial flexibility based on dependent and independent DNA binding that may contribute to variation and robustness in the regulation of flowering.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 186 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 <1%
Switzerland 1 <1%
Unknown 184 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 38 20%
Researcher 37 20%
Student > Master 27 15%
Student > Bachelor 16 9%
Student > Doctoral Student 9 5%
Other 22 12%
Unknown 37 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 103 55%
Biochemistry, Genetics and Molecular Biology 40 22%
Engineering 2 1%
Medicine and Dentistry 2 1%
Environmental Science 1 <1%
Other 2 1%
Unknown 36 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 16 December 2015.
All research outputs
#4,572,366
of 25,371,288 outputs
Outputs from Genome Biology
#2,717
of 4,467 outputs
Outputs of similar age
#61,613
of 367,176 outputs
Outputs of similar age from Genome Biology
#53
of 65 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 367,176 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 83% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.