The Arabidopsis RNA-Binding Protein FCA Requires a Lysine-Specific Demethylase 1 Homolog to Downregulate FLC
The Arabidopsis RNA-Binding Protein FCA Requires a Lysine-Specific Demethylase 1 Homolog to Downregulate FLC is a research paper published in Molecular Cell (2007). On theSindex it has a DataRank of 0.870. It has been cited 329 times.
Abstract
A repressor of the transition to flowering in Arabidopsis is the MADS box protein FLOWERING LOCUS C (FLC). FCA, an RNA-binding protein, and FY, a homolog of the yeast RNA 3' processing factor Pfs2p, downregulate FLC expression and therefore promote flowering. FCA/FY physically interact and alter polyadenylation/3' processing to negatively autoregulate FCA. Here, we show that FCA requires FLOWERING LOCUS D (FLD), a homolog of the human lysine-specific demethylase 1 (LSD1) for FLC downregulation. FCA also partially depends on DICER-LIKE 3, involved in chromatin silencing. fca mutations increased levels of unspliced sense FLC transcript, altered processing of antisense FLC transcripts, and increased H3K4 dimethylation in the central region of FLC. These data support a close association of FCA and FLD in mediating H3K4 demethylation and thus transcriptional silencing of FLC and reveal roles for antisense RNA processing and DCL3 function in this regulation.
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FAIR Checklist
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DataRank Breakdown
Base Score Contribution
0.870
From this paper's citation signal
Citation Network Contribution
0
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DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 100% comes from its base citations and 0% from the citation network.
- Base score B(p)
- log1p(citation_count) — grows sub-linearly, so a paper with 1,000 citations is not 10× a paper with 100.
- Network N(p)
- Σ over citers of log1p(Cq) ÷ max(outdegreeq, 1). Being cited by a highly-cited paper with few references counts most.
- Damping factor d = 0.85
- DataRank = (1−d)·B(p) + d·N(p) — the two cards above are each already multiplied by their share.
- Self-citations excluded
- Citers sharing any OpenAlex author ID with this paper are filtered out before the network sum.
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.