Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding

Montesinos-López, O A and Montesinos-Lopez, A and Acosta, R and Varshney, R K and Bentley, A and Crossa, J (2022) Using an incomplete block design to allocate lines to environments improves sparse genome-based prediction in plant breeding. The Plant Genome (TSI), 15 (1). pp. 1-24. ISSN 1940-3372

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Abstract

Genomic selection (GS) is a predictive methodology that trains statistical machine-learning models with a reference population that is used to perform genome-enabled predictions of new lines. In plant breeding, it has the potential to increase the speed and reduce the cost of selection. However, to optimize resources, sparse testing methods have been proposed. A common approach is to guarantee a proportion of nonoverlapping and overlapping lines allocated randomly in locations, that is, lines appearing in some locations but not in all. In this study we propose using incomplete block designs (IBD), principally, for the allocation of lines to locations in such a way that not all lines are observed in all locations. We compare this allocation with a random allocation of lines to locations guaranteeing that the lines are allocated to the same number of locations as under the IBD design. We implemented this benchmarking on several crop data sets under the Bayesian genomic best linear unbiased predictor (GBLUP) model, finding that allocation under the principle of IBD outperformed random allocation by between 1.4% and 26.5% across locations, traits, and data sets in terms of mean square error. Although a wide range of performance improvements were observed, our results provide evidence that using IBD for the allocation of lines to locations can help improve predictive performance compared with random allocation. This has the potential to be applied to large-scale plant breeding programs.

Item Type:	Article
Divisions:	Center of Excellence in Genomics and Systems Biology
CRP:	UNSPECIFIED
Uncontrolled Keywords:	plant breeding, genome-based prediction, incomplete block designs (IBD)
Subjects:	UNSPECIFIED
Depositing User:	Mr Nagaraju T
Date Deposited:	18 Mar 2024 11:01
Last Modified:	18 Mar 2024 11:01
URI:	http://oar.icrisat.org/id/eprint/12592
Official URL:	https://acsess.onlinelibrary.wiley.com/doi/full/10...
Projects:	UNSPECIFIED
Funders:	UNSPECIFIED
Acknowledgement:	We thank all scientists, field workers, and lab assistants from the National Programs, CIMMYT, and ICRISAT who collected the data used in this study. We are thankful for the financial support provided by the Bill & Melinda Gates Foundation [INV-003439, BMGF/FCDO, Accelerating Genetic Gains in Maize and Wheat for Improved Livelihoods (AG2MW)], the USAID projects [USAID Amend. No. 9 MTO 069033, USAID CIMMYT Wheat/AGGMW, AGG-Maize Supplementary Project, AGG (Stress Tolerant Maize for Africa], and the CIMMYT CRP (maize and wheat). We acknowledge the financial support provided by the Foundation for Research Levy on Agricultural Products (FFL), and the Agricultural Agreement Research Fund (JA) in Norway through NFR grant 267806.
Links:	Google Scholar

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