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Mining the Wheat Grain Proteome

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posted on 2022-09-09, 07:08 authored by D Vincent, A Bui, D Ram, V Ezernieks, Frank Bedon, J Panozzo, P Maharjan, Simone RochfortSimone Rochfort, Hans DaetwylerHans Daetwyler, Matthew HaydenMatthew Hayden
Bread wheat is the most widely cultivated crop worldwide, used in the production of food products and a feed source for animals. Selection tools that can be applied early in the breeding cycle are needed to accelerate genetic gain for increased wheat production while maintaining or improving grain quality if demand from human population growth is to be fulfilled. Proteomics screening assays of wheat flour can assist breeders to select the best performing breeding lines and discard the worst lines. In this study, we optimised a robust LC–MS shotgun quantitative proteomics method to screen thousands of wheat genotypes. Using 6 cultivars and 4 replicates, we tested 3 resuspension ratios (50, 25, and 17 µL/mg), 2 extraction buffers (with urea or guanidine-hydrochloride), 3 sets of proteases (chymotrypsin, Glu-C, and trypsin/Lys-C), and multiple LC settings. Protein identifications by LC–MS/MS were used to select the best parameters. A total 8738 wheat proteins were identified. The best method was validated on an independent set of 96 cultivars and peptides quantities were normalised using sample weights, an internal standard, and quality controls. Data mining tools found particularly useful to explore the flour proteome are presented (UniProt Retrieve/ID mapping tool, KEGG, AgriGO, REVIGO, and Pathway Tools).

Funding

This research was funded by the Grains Research and Development Corporation (GRDC), Project DJP2001-008RTX.

History

Publication Date

2022-01-10

Journal

International Journal of Molecular Sciences

Volume

23

Issue

2

Article Number

713

Pagination

24p.

Publisher

MDPI

ISSN

1661-6596

Rights Statement

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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