RGA

Information RGA

Description

Member of the VHIID/DELLA regulatory family. Contains homopolymeric serine and threonine residues, a putative nuclear localization signal, leucine heptad repeats, and an LXXLL motif. Putative transcriptional regulator repressing the gibberellin response and integration of phytohormone signalling. DELLAs repress cell proliferation and expansion that drives plant growth. The protein undergoes degradation in response to GA via the 26S proteasome. RGA1 binds to PIF3 and inhibits its DNA binding activity and thus affects the expression of PIF3 regulated genes. RGA may be involved in reducing ROS accumulation in response to stress by up-regulating the transcription of superoxide dismutases. Represses GA-induced vegetative growth and floral initiation. Rapidly degraded in response to GA. Involved in fruit and flower development.

Full Name

GRAS family transcription factor family protein

Source NCBI

ReMap Statistics

Datasets
2
Biotypes
2
Peaks
14,863
Non-redundant peaks
13,019

TF Classification

Familly
REM
Sub Familly
NA

Source AtTFDB

External IDs

JASPAR
Ensembl
AT2G01570
UniProt
Q9SLH3
Genevisible
Q9SLH3
RefSeq
NM_126218.3
Aliases
All peaks RGA
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Non redundant peaks RGA
Download BED file
SEQUENCES RGA
Download FASTA file
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Datasets Table for RGA

Target name Target modification Ecotype/Strain Biotype Biotype modification Source Species Experiment Peaks
RGA Ler Ler_seedling 11d GEO Arabidopsis thaliana GSE59187 4,366
RGA Ler Ler_inflorescence-apices GEO Arabidopsis thaliana GSE94926 10,497
Target name Target modification Ecotype/Strain Biotype Biotype modification Source Species Experiment Peaks

ReMap is a database of transcriptional regulators peaks derived from curated ChIP-seq, ChIP-exo, DAP-seq experiments in Human and Thaliana.

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The ReMap catalogues (2020, 2018, 2015) are under CC BY-NC 4.0 international license, while ReMapEnrich, remap-pipeline under GNU GPLv3 licence.

Inserm TAGC
AMU AMU-MESO

This work was granted access to the HPC resources of Aix-Marseille Université financed by the project Equip@Meso (ANR-10-EQPX-29-01) of the program "Investissements d’Avenir" supervised by the Agence Nationale de la Recherche.