TY  - JA
AU  - Fradgley,N.S.
AU  - Gardner,K.A.
AU  - Bentley,A.R.
AU  - Howell,P.
AU  - Mackay,I.
AU  - Scott,M.F.
AU  - Mott,R.
AU  - Cockram,J.
TI  - Multi-trait ensemble genomic prediction and simulations of recurrent selection highlight importance of complex trait genetic architecture for long-term genetic gains in wheat 
SN  - 2517-5025
PY  - 2023///
CY  - United Kingdom
PB  - Oxford University Press
KW  - Genomics
KW  - AGROVOC
KW  - Population
KW  - Recurrent selection
KW  - Simulation
KW  - Triticum aestivum
N1  - Peer review; Open Access
N2  - Cereal crop breeders have achieved considerable genetic gain in genetically complex traits, such as grain yield, while maintaining genetic diversity. However, focus on selection for yield has negatively impacted other important traits. To better understand multi-trait selection within a breeding context, and how it might be optimized, we analysed genotypic and phenotypic data from a genetically diverse, 16-founder wheat multi-parent advanced generation inter-cross population. Compared to single-trait models, multi-trait ensemble genomic prediction models increased prediction accuracy for almost 90 % of traits, improving grain yield prediction accuracy by 3–52 %. For complex traits, non-parametric models (Random Forest) also outperformed simplified, additive models (LASSO), increasing grain yield prediction accuracy by 10–36 %. Simulations of recurrent genomic selection then showed that sustained greater forward prediction accuracy optimized long-term genetic gains. Simulations of selection on grain yield found indirect responses in related traits, involving optimized antagonistic trait relationships. We found multi-trait selection indices could effectively optimize undesirable relationships, such as the trade-off between grain yield and protein content, or combine traits of interest, such as yield and weed competitive ability. Simulations of phenotypic selection found that including Random Forest rather than LASSO genetic models, and multi-trait rather than single-trait models as the true genetic model accelerated and extended long-term genetic gain whilst maintaining genetic diversity. These results (i) suggest important roles of pleiotropy and epistasis in the wider context of wheat breeding programmes, and (ii) provide insights into mechanisms for continued genetic gain in a limited genepool and optimization of multiple traits for crop improvement
UR  - https://hdl.handle.net/10883/22730
DO  - https://doi.org/10.1093/insilicoplants/diad002
T2  - in silico Plants
ER  -