Abstract
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).
Highlights
Contributing about 20% of the total calories consumed by humans, wheat (Triticum aestivum L.) is the most cultivated crop worldwide
We developed a label-free, gel-free quantitation method to analyse the proteome of wheat grain using LC–Mass spectrometry (MS) and LC–MS/MS
This high throughput method is suitable for processing thousands of samples and does not compromise LC–MS peak resolution
Summary
Contributing about 20% of the total calories consumed by humans, wheat (Triticum aestivum L.) is the most cultivated crop worldwide. Wheat offers a wide adaptability and high yield potentials, and contains gluten proteins whose viscoelastic properties allow dough to be turned into bread and other food products such as pasta and noodles [1]. Sustaining wheat production and quality with reduced agrochemical inputs and developing new varieties with enhanced quality for specific end-uses are the main objectives addressed by breeding programs [1]. There is an ongoing requirement for wheat research and breeding to accelerate genetic gain to increase wheat yield while maintaining or improving grain quality traits if the demands of human population growth are to be met [2]. Owing to the large size of wheat polyploid genome, containing more than 85% of repetitive Efficient breeding and germplasm section strategies must be underpinned by functional annotations of the whole genome.
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