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Data · dataset · 2026

Multi-condition transcriptomic dataset of AGL103-regulated osmotic stress response in Arabidopsis thaliana.

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This project integrates five transcriptome sequencing datasets to systematically elucidate the regulatory function of the MADS-box transcription factor AGL103 in osmotic stress response (mannitol-simulated drought) in Arabidopsis thaliana.

Description

The dataset encompasses the following experimental conditions:Transcriptome comparison between wild-type (WT) and AGL103-overexpressing (AGL103-OX) materials under normal conditions;Transcriptome comparison between wild-type and agl103 mutant materials under normal conditions;Transcriptome comparison between wild-type and AGL103-overexpressing materials following mannitol treatment;Transcriptome comparison between wild-type and agl103 mutant materials following mannitol treatment;Expression profiling of key gene families involved in stress response, cell wall modification, aquaporins, seed storage proteins, and growth regulation.By integrating multi-dimensional data from normal versus stress conditions, as well as gain-of-function versus loss-of-function lines, this project aims to uncover the molecular mechanisms by which AGL103 regulates drought stress tolerance, water transport, cell wall remodeling, and growth/development in plants.

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Genetics 73% · RNA sequencing 65% · Sequencing 75%
Provenance · 1 source records, 13 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.4444810 d agoJSON v1
FieldAssertionExtractorEvidence
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