Dataset Information

Resource allocation optimization with multi-trait genomic prediction for bread wheat (Triticum aestivum L.) baking quality.

ABSTRACT: KEY MESSAGE:Multi-trait genomic prediction models are useful to allocate available resources in breeding programs by targeted phenotyping of correlated traits when predicting expensive and labor-intensive quality parameters. Multi-trait genomic prediction models can be used to predict labor-intensive or expensive correlated traits where phenotyping depth of correlated traits could be larger than phenotyping depth of targeted traits, reducing resources and improving prediction accuracy. This is particularly important in the context of allocating phenotyping resource in plant breeding programs. The objective of this work was to evaluate multi-trait models predictive ability with different depth of phenotypic information from correlated traits. We evaluated 495 wheat advanced breeding lines for eight baking quality traits which were genotyped with genotyping-by-sequencing. Through different approaches for cross-validation, we evaluated the predictive ability of a single-trait model and a multi-trait model. Moreover, we evaluated different sizes of the training population (from 50 to 396 individuals) for the trait of interest, different depth of phenotypic information for correlated traits (50 and 100%) and the number of correlated traits to be used (one to three). There was no loss in the predictive ability by reducing the training population up to a 30% (149 individuals) when using correlated traits. A multi-trait model with one highly correlated trait phenotyped for both the training and testing sets was the best model considering phenotyping resources and the gain in predictive ability. The inclusion of correlated traits in the training and testing lines is a strategic approach to replace phenotyping of labor-intensive and high cost traits in a breeding program.

SUBMITTER: Lado B

PROVIDER: S-EPMC6244535 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Resource allocation optimization with multi-trait genomic prediction for bread wheat (Triticum aestivum L.) baking quality.

Lado Bettina B Vázquez Daniel D Quincke Martin M Silva Paula P Aguilar Ignacio I Gutiérrez Lucia L

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik 20180919 12

<h4>Key message</h4>Multi-trait genomic prediction models are useful to allocate available resources in breeding programs by targeted phenotyping of correlated traits when predicting expensive and labor-intensive quality parameters. Multi-trait genomic prediction models can be used to predict labor-intensive or expensive correlated traits where phenotyping depth of correlated traits could be larger than phenotyping depth of targeted traits, reducing resources and improving prediction accuracy. T ...[more]

PMID: 30232499

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Project description:Background and aimsGluten proteins are the major storage protein fraction in the mature wheat grain. They are restricted to the starchy endosperm, which forms white flour on milling, and interact during grain development to form large polymers which form a continuous proteinaceous network when flour is mixed with water to give dough. This network confers viscosity and elasticity to the dough, enabling the production of leavened products. The starchy endosperm is not a homogeneous tissue and quantitative and qualitative gradients exist for the major components: protein, starch and cell wall polysaccharides. Gradients in protein content and composition are the most evident and are of particular interest because of the major role played by the gluten proteins in determining grain processing quality.MethodsProtein gradients in the starchy endosperm were investigated using antibodies for specific gluten protein types for immunolocalization in developing grains and for western blot analysis of protein extracts from flour fractions obtained by sequential abrasion (pearling) to prepare tissue layers.Key resultsDifferential patterns of distribution were found for the high-molecular-weight subunits of glutenin (HMW-GS) and γ-gliadins when compared with the low-molecular-weight subunits of glutenin (LMW-GS), ω- and α-gliadins. The first two types of gluten protein are more abundant in the inner endosperm layers and the latter more abundant in the subaleurone. Immunolocalization also showed that segregation of gluten proteins occurs both between and within protein bodies during protein deposition and may still be retained in the mature grain.ConclusionsQuantitative and qualitative gradients in gluten protein composition are established during grain development. These gradients may be due to the origin of subaleurone cells, which unlike other starchy endosperm cells derive from the re-differentiation of aleurone cells, but could also result from the action of specific regulatory signals produced by the maternal tissue on specific domains of the gluten protein gene promoters.

Project description:BackgroundThe analyses of protein synthesis, accumulation and regulation during grain development in wheat are more complex because of its larger genome size compared to model plants such as Arabidopsis and rice. In this study, grains from two wheat cultivars Jimai 20 and Zhoumai 16 with different gluten quality properties were harvested at five development stages, and were used to displayed variable expression patterns of grain proteins.ResultsProteome characterization during grain development in Chinese bread wheat cultivars Jimai 20 and Zhoumai 16 with different quality properties was investigated by 2-DE and tandem MALDI-TOF/TOF-MS. Identification of 117 differentially accumulated protein spots representing 82 unique proteins and five main expression patterns enabled a chronological description of wheat grain formation. Significant proteome expression differences between the two cultivars were found; these included 14 protein spots that accumulated in both cultivars but with different patterns and 27 cultivar-different spots. Among the cultivar-different protein spots, 14 accumulated in higher abundance in Jimai 20 than in Zhoumai 16, and included NAD-dependent isocitrate dehydrogenase, triticin precursor, LMW-s glutenin subunit and replication factor C-like protein. These proteins are likely to be associated with superior gluten quality. In addition, some proteins such as class II chitinase and peroxidase 1 with isoforms in developing grains were shown to be phosphorylated by Pro-Q Diamond staining and phosphorprotein site prediction. Phosphorylation could have important roles in wheat grain development. qRT-PCR analysis demonstrated that transcriptional and translational expression patterns of many genes were significantly different.ConclusionsWheat grain proteins displayed variable expression patterns at different developmental stages and a considerable number of protein spots showed differential accumulation between two cultivars. Differences in seed storage proteins were considered to be related to different quality performance of the flour from these wheat cultivars. Some proteins with isoforms were phosphorylated, and this may reflect their importance in grain development. Our results provide new insights into proteome characterization during grain development in different wheat genotypes.

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Dataset Information

Resource allocation optimization with multi-trait genomic prediction for bread wheat (Triticum aestivum L.) baking quality.

Publications

Resource allocation optimization with multi-trait genomic prediction for bread wheat (Triticum aestivum L.) baking quality.

Similar Datasets

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