Dataset Information

Microarray analysis of gene expression under different light conditions

ABSTRACT: The size of tomato fruits are largely dependent on growth conditions. To obtain insights on how light intensity contributes to translocation from a leaf and a fruit, we developed a plant irradiation system based on light-emitting diodes (LEDs) to a leaf. By using this system, we investigated the changes of transcript profiles of tomato leaves and fruits grown under different light conditions.

ORGANISM(S): Solanum lycopersicum

PROVIDER: GSE35020 | GEO | 2012/05/02

SECONDARY ACCESSION(S): PRJNA151157

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Tomato (Solanum lycopersicum) is a model crop for studying development regulation and ripening in flesh fruits and vegetables. Supplementary light to maintain the optimal light environment can lead to the stable growth of tomatoes in greenhouses and areas without sufficient daily light integral. Technological advances in genome-wide molecular phenotyping have dramatically enhanced our understanding of metabolic shifts in the plant metabolism across tomato fruit development. However, comprehensive metabolic and transcriptional behaviors along the developmental process under supplementary light provided by light-emitting diodes (LED) remain to be fully elucidated. We present integrative omic approaches to identify the impact on the metabolism of a single tomato plant leaf exposed to red LEDs of different intensities during the fruit development stage. Our special light delivery system, the “simplified source-sink model”, involves the exposure of a single leaf below the second truss to red LED light of different intensities. We evaluated fruit-size- and fruit-shape variations elicited by different light intensities. Our findings suggest that more than high-light treatment (500 mmol/m^2/s) with the red LED light is required to accelerate fruit growth for 2 weeks after anthesis. To investigate transcriptomic and metabolomic changes in leaf- and fruit samples we used microarray-, RNA sequencing-, and gas chromatography-mass spectrometry techniques. We found that metabolic shifts in the carbohydrate metabolism and in several key pathways contributed to fruit development, including ripening and cell-wall modification. Our findings suggest that the proposed workflow aids in the identification of key metabolites in the central metabolism that respond to monochromatic red-LED treatment and contribute to increase the fruit size of tomato plants. This study expands our understanding of systems-level responses mediated by low-, appropriate-, and high levels of red light irradiation in the fruit growth of tomato plants.

Dataset Information

Microarray analysis of gene expression under different light conditions

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets