Selection in sugarcane based on inbreeding depression

Azeredo, Amaro Afonso Campos de; Bhering, Leonardo Lopes; Brasileiro, Bruno Portela; Cruz, Cosme Damião; Barbosa, Márcio Henrique Pereira

doi:10.4238/gmr.15027965

Cited by 3 publications

(1 citation statement)

References 12 publications

(18 reference statements)

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“…Furthermore, the presence of these non-additive effects implies a possible gain in overall genetic merit if matings are allocated to exploit dominance (including heterosis) and epistatic effects. In addition, modelling non-additive effects and heterozygosity as effective control of inbreeding would reduce the risk of inbreeding depression in the commercial population, which is substantial for (TCH) in sugarcane (de Azeredo et al 2016; Silva and Gonçalves 2011). Werner et al (2020) also advocated that in clonal breeding programs utilising GS, parents should be chosen based on the genomic prediction of cross-performance while considering dominance effects.…”

Section: Introductionmentioning

confidence: 99%

Genomic mate-allocation strategies exploiting additive and non-additive genetic effects to maximise total clonal performance in sugarcane

Yadav¹,

Ross

Wei

et al. 2022

Preprint

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Mate-allocation in breeding programs can improve progeny performance by exploiting non-additive effects. Breeding decisions in the mate-allocation approach are based on predicted progeny merit rather than parental breeding value. This is particularly attractive when non-additive effects are significant, and the best-predicted progeny can be clonally propagated, for example sugarcane. We compared mate-allocation strategies that leverage non-additive and heterozygosity effects to maximise sugarcane clonal performance to schemes that use only additive effects to maximise breeding value. We used phenotypes and genotypes from a population of 2,909 clones phenotyped in Australian sugarcane breeding final assessment trials for three traits: tonnes of cane per hectare (TCH), commercial cane sugar (CCS), and fibre. The clones from the last generation of this data set were used as parents to simulate families from all possible crosses (1,225), each with 50 progenies. The breeding and clonal values of progeny were predicted using GBLUP (considering only additive effects) and the e-GBLUP model (incorporating additive, non-additive and heterozygosity effects). Integer linear programming was used to identify the optimal mate-allocation among the selected parents. Compared to the breeding value, the predicted progeny value of allocated crossing pairs based on clonal performance (e-GBLUP) increased by 57%, 12%, and 16% for TCH, CCS, and fibre, respectively. In our study, the mate-allocation strategy exploiting non-additive and heterozygosity effects resulted in better clonal performance. However, there was a noticeable decline in additive gain, particularly for TCH, which might have been caused by the presence of large epistatic effects. When crosses were chosen based on clonal performance for TCH, the inbreeding coefficient of progeny was significantly lower than for random mating, indicating that utilising non-additive and heterozygosity effects has advantages for controlling inbreeding depression. Therefore, mate-allocation is recommended in clonal crops to improve clonal performance and reduce inbreeding.

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Section: Introductionmentioning

confidence: 99%

Genomic mate-allocation strategies exploiting additive and non-additive genetic effects to maximise total clonal performance in sugarcane

Yadav¹,

Ross

Wei

et al. 2022

Preprint

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show abstract

Fuzzy controller in the selection of sugarcane and energy cane ideotypes

et al. 2020

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

Yadav,

Ross,

Wei

et al. 2023

Front. Plant Sci.

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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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Selection in sugarcane based on inbreeding depression

Cited by 3 publications

References 12 publications

Genomic mate-allocation strategies exploiting additive and non-additive genetic effects to maximise total clonal performance in sugarcane

Genomic mate-allocation strategies exploiting additive and non-additive genetic effects to maximise total clonal performance in sugarcane

Fuzzy controller in the selection of sugarcane and energy cane ideotypes

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

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