Dataset Information

Simultaneous selection for grain yield and protein content in genomics-assisted wheat breeding.

ABSTRACT:

Key message

Large genetic improvement can be achieved by simultaneous genomic selection for grain yield and protein content when combining different breeding strategies in the form of selection indices. Genomic selection has been implemented in many national and international breeding programmes in recent years. Numerous studies have shown the potential of this new breeding tool; few have, however, taken the simultaneous selection for multiple traits into account that is though common practice in breeding programmes. The simultaneous improvement in grain yield and protein content is thereby a major challenge in wheat breeding due to a severe negative trade-off. Accordingly, the potential and limits of multi-trait selection for this particular trait complex utilizing the vast phenotypic and genomic data collected in an applied wheat breeding programme were investigated in this study. Two breeding strategies based on various genomic-selection indices were compared, which (1) aimed to select high-protein genotypes with acceptable yield potential and (2) develop high-yielding varieties, while maintaining protein content. The prediction accuracy of preliminary yield trials could be strongly improved when combining phenotypic and genomic information in a genomics-assisted selection approach, which surpassed both genomics-based and classical phenotypic selection methods both for single trait predictions and in genomic index selection across years. The employed genomic selection indices mitigated furthermore the negative trade-off between grain yield and protein content leading to a substantial selection response for protein yield, i.e. total seed nitrogen content, which suggested that it is feasible to develop varieties that combine a superior yield potential with comparably high protein content, thus utilizing available nitrogen resources more efficiently.

SUBMITTER: Michel S

PROVIDER: S-EPMC6531418 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Simultaneous selection for grain yield and protein content in genomics-assisted wheat breeding.

Michel Sebastian S Löschenberger Franziska F Ametz Christian C Pachler Bernadette B Sparry Ellen E Bürstmayr Hermann H

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik 20190227 6

<h4>Key message</h4>Large genetic improvement can be achieved by simultaneous genomic selection for grain yield and protein content when combining different breeding strategies in the form of selection indices. Genomic selection has been implemented in many national and international breeding programmes in recent years. Numerous studies have shown the potential of this new breeding tool; few have, however, taken the simultaneous selection for multiple traits into account that is though common pr ...[more]

PMID: 30810763

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Project description:KEY MESSAGE:Simultaneous genomic selection for grain yield, protein content and dough rheological traits enables the development of resource-use efficient varieties that combine superior yield potential with comparably high end-use quality. Selecting simultaneously for grain yield and baking quality is a major challenge in wheat breeding, and several concepts like grain protein deviations have been developed for shifting the undesirable negative correlation between both traits. The protein quality is, however, not considered in these concepts, although it is an important aspect and might facilitate the selection of genotypes that use available resources more efficiently with respect to the quantity and quality of the final end products. A population of 480 lines from an applied wheat breeding programme that was phenotyped for grain yield, protein content, protein yield and dough rheological traits was thus used to assess the potential of using integrated genomic selection indices to ease selection decisions with regard to the plethora of quality traits. Additionally, the feasibility of achieving a simultaneous genetic improvement in grain yield, protein content and protein quality was investigated to develop more resource-use efficient varieties. Dough rheological traits related to either gluten strength or viscosity were combined in two separate indices, both of which showed a substantially smaller negative trade-off with grain yield than the protein content. Genomic selection indices based on regression deviations for the two latter traits were subsequently extended by the gluten strength or viscosity indices. They revealed a large merit for identifying resource-use efficient genotypes that combine both superior yield potential with comparably high end-use quality. Hence, genomic selection opens up the opportunity for multi-trait selection in early generations, which will most likely increase the efficiency when developing new and improved varieties.

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Project description:Wider pea (Pisum sativum L.) cultivation has great interest for European agriculture, owing to its favorable environmental impact and provision of high-protein feedstuff. This work aimed to investigate the extent of genotype × environment interaction (GEI), genetically based trade-offs and polygenic control for crude protein content and grain yield of pea targeted to Italian environments, and to assess the efficiency of genomic selection (GS) as an alternative to phenotypic selection (PS) to increase protein yield per unit area. Some 306 genotypes belonging to three connected recombinant inbred line (RIL) populations derived from paired crosses between elite cultivars were genotyped through genotyping-by-sequencing and phenotyped for grain yield and protein content on a dry matter basis in three autumn-sown environments of northern or central Italy. Line variation for mean protein content ranged from 21.7 to 26.6%. Purely genetic effects, compared with GEI effects, were over two-fold larger for protein content, and over 2-fold smaller for grain and protein yield per unit area. Grain yield and protein content exhibited no inverse genetic correlation. A genome-wide association study revealed a definite polygenic control not only for grain yield but also for protein content, with small amounts of trait variation accounted for by individual loci. On average, the GS predictive ability for individual RIL populations based on the rrBLUP model (which was selected out of four tested models) using by turns two environments for selection and one for validation was moderately high for protein content (0.53) and moderate for grain yield (0.40) and protein yield (0.41). These values were about halved for inter-environment, inter-population predictions using one RIL population for model construction to predict data of the other populations. The comparison between GS and PS for protein yield based on predicted gains per unit time and similar evaluation costs indicated an advantage of GS for model construction including the target RIL population and, in case of multi-year PS, even for model training based on data of a non-target population. In conclusion, protein content is less challenging than grain yield for phenotypic or genome-enabled improvement, and GS is promising for the simultaneous improvement of both traits.

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Dataset Information

Simultaneous selection for grain yield and protein content in genomics-assisted wheat breeding.

Key message

Publications

Simultaneous selection for grain yield and protein content in genomics-assisted wheat breeding.

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