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Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies

Mate-allocation strategies in breeding programs can improve progeny performance by harnessing non-additive genetic effects. These approaches prioritise predicted progeny merit over parental breeding value, making them particularly appealing for clonally propagated crops such as sugarcane. We conduct...

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Autores principales: Yadav, Seema, Ross, Elizabeth M., Wei, Xianming, Powell, Owen, Hivert, Valentin, Hickey, Lee T., Atkin, Felicity, Deomano, Emily, Aitken, Karen S., Voss-Fels, Kai P., Hayes, Ben J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10667552/
https://www.ncbi.nlm.nih.gov/pubmed/38023905
http://dx.doi.org/10.3389/fpls.2023.1260517
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author Yadav, Seema
Ross, Elizabeth M.
Wei, Xianming
Powell, Owen
Hivert, Valentin
Hickey, Lee T.
Atkin, Felicity
Deomano, Emily
Aitken, Karen S.
Voss-Fels, Kai P.
Hayes, Ben J.
author_facet Yadav, Seema
Ross, Elizabeth M.
Wei, Xianming
Powell, Owen
Hivert, Valentin
Hickey, Lee T.
Atkin, Felicity
Deomano, Emily
Aitken, Karen S.
Voss-Fels, Kai P.
Hayes, Ben J.
author_sort Yadav, Seema
collection PubMed
description Mate-allocation strategies in breeding programs can improve progeny performance by harnessing non-additive genetic effects. These approaches prioritise predicted progeny merit over parental breeding value, making them particularly appealing for clonally propagated crops such as sugarcane. We conducted a comparative analysis of mate-allocation strategies, exploring utilising non-additive and heterozygosity effects to maximise clonal performance with schemes that solely consider additive effects to optimise breeding value. Using phenotypic and genotypic data from a population of 2,909 clones evaluated in final assessment trials of Australian sugarcane breeding programs, we focused on three important traits: tonnes of cane per hectare (TCH), commercial cane sugar (CCS), and Fibre. By simulating families from all possible crosses (1,225) with 50 progenies each, we predicted the breeding and clonal values of progeny using two models: GBLUP (considering additive effects only) and extended-GBLUP (incorporating additive, non-additive, and heterozygosity effects). Integer linear programming was used to identify the optimal mate-allocation among selected parents. Compared to breeding value-based approaches, mate-allocation strategies based on clonal performance yielded substantial improvements, with predicted progeny values increasing by 57% for TCH, 12% for CCS, and 16% for fibre. Our simulation study highlights the effectiveness of mate-allocation approaches that exploit non-additive and heterozygosity effects, resulting in superior clonal performance. However, there was a notable decline in additive gain, particularly for TCH, likely due to significant epistatic effects. When selecting crosses based on clonal performance for TCH, the inbreeding coefficient of progeny was significantly lower compared to random mating, underscoring the advantages of leveraging non-additive and heterozygosity effects in mitigating inbreeding depression. Thus, mate-allocation strategies are recommended in clonally propagated crops to enhance clonal performance and reduce the negative impacts of inbreeding.
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spelling pubmed-106675522023-01-01 Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies Yadav, Seema Ross, Elizabeth M. Wei, Xianming Powell, Owen Hivert, Valentin Hickey, Lee T. Atkin, Felicity Deomano, Emily Aitken, Karen S. Voss-Fels, Kai P. Hayes, Ben J. Front Plant Sci Plant Science Mate-allocation strategies in breeding programs can improve progeny performance by harnessing non-additive genetic effects. These approaches prioritise predicted progeny merit over parental breeding value, making them particularly appealing for clonally propagated crops such as sugarcane. We conducted a comparative analysis of mate-allocation strategies, exploring utilising non-additive and heterozygosity effects to maximise clonal performance with schemes that solely consider additive effects to optimise breeding value. Using phenotypic and genotypic data from a population of 2,909 clones evaluated in final assessment trials of Australian sugarcane breeding programs, we focused on three important traits: tonnes of cane per hectare (TCH), commercial cane sugar (CCS), and Fibre. By simulating families from all possible crosses (1,225) with 50 progenies each, we predicted the breeding and clonal values of progeny using two models: GBLUP (considering additive effects only) and extended-GBLUP (incorporating additive, non-additive, and heterozygosity effects). Integer linear programming was used to identify the optimal mate-allocation among selected parents. Compared to breeding value-based approaches, mate-allocation strategies based on clonal performance yielded substantial improvements, with predicted progeny values increasing by 57% for TCH, 12% for CCS, and 16% for fibre. Our simulation study highlights the effectiveness of mate-allocation approaches that exploit non-additive and heterozygosity effects, resulting in superior clonal performance. However, there was a notable decline in additive gain, particularly for TCH, likely due to significant epistatic effects. When selecting crosses based on clonal performance for TCH, the inbreeding coefficient of progeny was significantly lower compared to random mating, underscoring the advantages of leveraging non-additive and heterozygosity effects in mitigating inbreeding depression. Thus, mate-allocation strategies are recommended in clonally propagated crops to enhance clonal performance and reduce the negative impacts of inbreeding. Frontiers Media S.A. 2023-11-10 /pmc/articles/PMC10667552/ /pubmed/38023905 http://dx.doi.org/10.3389/fpls.2023.1260517 Text en Copyright © 2023 Yadav, Ross, Wei, Powell, Hivert, Hickey, Atkin, Deomano, Aitken, Voss-Fels and Hayes https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Yadav, Seema
Ross, Elizabeth M.
Wei, Xianming
Powell, Owen
Hivert, Valentin
Hickey, Lee T.
Atkin, Felicity
Deomano, Emily
Aitken, Karen S.
Voss-Fels, Kai P.
Hayes, Ben J.
Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies
title Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies
title_full Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies
title_fullStr Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies
title_full_unstemmed Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies
title_short Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies
title_sort optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10667552/
https://www.ncbi.nlm.nih.gov/pubmed/38023905
http://dx.doi.org/10.3389/fpls.2023.1260517
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