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Genomic selection can accelerate the biofortification of spring wheat

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Genomic selection enabled accurate prediction for the concentration of 13 nutritional element traits in wheat.

Abstract

Wheat biofortification is one of the most sustainable strategies to alleviate mineral deficiency in human diets. Here, we investigated the potential of genomic selection using BayesR and Bayesian ridge regression (BRR) models to predict grain yield (YLD) and the concentration of 13 nutritional elements in grains (B, Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Na, Ni, P and Zn) using a population of 1470 spring wheat lines. The lines were grown in replicated field trials with two times of sowing (TOS) at 3 locations (Narrabri-NSW, all lines; Merredin-WA and Horsham-VIC, 200 core lines). Narrow-sense heritability across environments (locations/TOS) ranged from 0.09 to 0.45. Co, K, Na and Ca showed low to negative genetic correlations with other traits including YLD, while the remaining traits were negatively correlated with YLD. When all environments were included in the reference population, medium to high prediction accuracy was observed for the different traits across environments. BayesR had higher average prediction accuracy for mineral concentrations (r = 0.55) compared to BRR (r = 0.48) across all traits and environments but both methods had comparable accuracies for YLD. We also investigated the utility of one or two locations (reference locations) to predict the remaining location(s), as well as the ability of one TOS to predict the other. Under these scenarios, BayesR and BRR showed comparable performance but with lower prediction accuracy compared to the scenario of predicting reference environments for new lines. Our study demonstrates the potential of genomic selection for enriching wheat grain with nutritional elements in biofortification breeding.

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Acknowledgements

The authors acknowledge the financial support of the Grains Research and Development Corporation, University of Sydney, and Agriculture Victoria under the project US00081, which made this research possible.

Funding

Grain Research and Development Corporation, University of Sydney, and Agriculture Victoria under the project US00081.

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Authors and Affiliations

  1. Agriculture Victoria, Centre for AgriBioscience, AgriBio, Bundoora, VIC, Australia

    Reem Joukhadar, Matthew J. Hayden & Hans D. Daetwyler

  2. School of Life and Environmental Sciences, Plant Breeding Institute, Sydney Institute of Agriculture, The University of Sydney, Narrabri, NSW, Australia

    Rebecca Thistlethwaite & Richard M. Trethowan

  3. School of Life and Environmental Sciences, Plant Breeding Institute, Sydney Institute of Agriculture, The University of Sydney, Cobbitty, NSW, Australia

    Richard M. Trethowan

  4. School of Applied Systems Biology, La Trobe University, Bundoora, VIC, Australia

    Matthew J. Hayden & Hans D. Daetwyler

  5. College of Science and Engineering, Flinders University, Sturt Road, Bedford Park, South Australia, 5042, Australia

    James Stangoulis & Suong Cu

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  1. Reem Joukhadar
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  2. Rebecca Thistlethwaite
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  7. Hans D. Daetwyler
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Contributions

HD,RiT, RJ: planned the study; RJ: analysed the data and drafted the manuscript; ReT,RiT,JS,SC phenotyped the population; MH: provided the genotype data; HD: supervised the study; all authors read, edited and approved the final copy of the manuscript.

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Correspondence to Reem Joukhadar.

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Communicated by Jessica Rutkoski.

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Joukhadar, R., Thistlethwaite, R., Trethowan, R.M. et al. Genomic selection can accelerate the biofortification of spring wheat. Theor Appl Genet 134, 3339–3350 (2021). https://doi.org/10.1007/s00122-021-03900-4

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