Dataset Information

Leaf proteome of Glycine max in response to ethylene, ABA and combined ABA+ethylene treatments

ABSTRACT: Phytohormones play a central role in plant physiology. Despite the significant understanding in the hormone signaling, a deep understanding of downstream targets is missing. Therefore, we used a shotgun proteomics approach to investigate the ethylene, ABA and ABA+ethylene signaling in soybean leaves. A protamine sulfate precipitation (PSP) method was used for the enrichment of the low-abundance proteins which were then identified by label-free quantitative proteomics. A total of 5171 unique proteins were identified, of which 1182 were differentially modulated in one or more treatments. Functional annotation of the differentially modulated proteins showed that these were mainly associated with the biosynthesis of secondary metabolites and fatty acid metabolism.

OTHER RELATED OMICS DATASETS IN: MTBLS531

INSTRUMENT(S): Q Exactive

ORGANISM(S): Glycine Max

TISSUE(S): Leaf

SUBMITTER: Katharina Kramer

LAB HEAD: Dr. Sun Tae Kim

PROVIDER: PXD006989 | Pride | 2018-04-05

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	151102_KT_YiWa_STQ_01_sdb1.raw	Raw
	151102_KT_YiWa_STQ_01_sdb2.raw	Raw
	151102_KT_YiWa_STQ_01_sdb3.raw	Raw
	151102_KT_YiWa_STQ_02_sdb1.raw	Raw
	151102_KT_YiWa_STQ_02_sdb2.raw	Raw

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Publications

A Multi-Omics Analysis of Glycine max Leaves Reveals Alteration in Flavonoid and Isoflavonoid Metabolism Upon Ethylene and Abscisic Acid Treatment.

Gupta Ravi R Min Cheol Woo CW Kramer Katharina K Agrawal Ganesh Kumar GK Rakwal Randeep R Park Ki-Hun KH Wang Yiming Y Finkemeier Iris I Kim Sun Tae ST

Proteomics 20180307 7

Phytohormones are central to plant growth and development. Despite the advancement in our knowledge of hormone signaling, downstream targets, and their interactions upon hormones action remain largely fragmented, especially at the protein and metabolite levels. With an aim to get new insight into the effects of two hormones, ethylene (ET) and abscisic acid (ABA), this study utilizes an integrated proteomics and metabolomics approach to investigate their individual and combined (ABA+ET) signaling ...[more]

PMID: 29457974

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