Heterosis prediction system based on non-additive genomic prediction models in cucumber (Cucumis sativus L.)

Liu, Ce; Liu, Huan; Xiao, Wang; Han, Yike; Meng, Huanwen; Cheng, Zhihui

doi:10.1016/j.scienta.2021.110677

Cited by 7 publications

(4 citation statements)

References 48 publications

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“…In addition, genetic distance has also been used to evaluate parental genetic differences and, as a result, to predict heterosis and select parents for a cross. However, the relationship between heterosis and genetic distance remains unclear due to inconsistent findings from various studies (Cheres et al, 2000;Yingbin et al, 2019;Liu et al, 2022). However, clonally propagated crops, including sugarcane, are highly heterozygous polyploids, where virtually all gametes produced by any parental genotype are distinct, and all F 1 descendants are unique (Wei et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

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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Section: Discussionmentioning

confidence: 99%

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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“…In addition, genetic distance has also been used to evaluate parental genetic differences and, as a result, to predict heterosis and select parents for a cross. However, the relationship between heterosis and genetic distance remains unclear due to inconsistent findings from various studies (Cheres et al 2000; Liu et al 2022; Yingbin et al 2019). However, most clonally propagated crops are polyploid and highly heterozygous, particularly sugarcane.…”

Section: Discussionmentioning

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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“…In model maize, the existence of strong correlation between vigour depression and, on the one hand, heterosis and, on the other hand, the genetic distance of the parents, calculated using both morpho-physiological traits (Moll et al, 1965) and molecular marker data (Reif et al, 2003), has been proven. In horticultural crops, the relationship between heterosis and the genetic distance between parents is in some cases controversial: yield traits have been examined in fruit vegetables such as tomato (Fortuny et al, 2021), eggplant (Rodrıǵuez-Burruezo et al, 2008;Kaushik et al, 2018), cucumber (Liu et al, 2022), pepper (Geleta et al, 2004) and melon (Luan et al, 2010;Dafna et al, 2021), where a negative or no correlation between them was observed, suggesting that the genetic distance between parents is not a strong predictor in these fruit vegetables. In contrast, heterosis in root biomass in carrot and radish was observed, and moderate positive relationships between yield, heterosis and the genetic distance of parental lines were observed.…”

Section: Heterosis and The Starting Point Of Knowledgementioning

confidence: 99%

“…Thanks to the rapid advancement of genome sequencing technologies, genome-wide association studies (GWASs) have allowed the identification of gene loci connected to heterosis and associated phenotypes (Huang and Han, 2014). Despite lots of progress has been made in understanding the phenomenon of heterosis at the genetic and genomics levels, the new molecular omics techniques are still developed and set on major model species (i.e., cereals) and Arabidopsis (Liu et al, 2022). However a recent growing number of horticultural crops have been examined using integrated omics (transcriptome, metabolome, proteome, and epigenome) approaches that are becoming more widely available (Li et al, 2017;Natalini et al, 2021;Pott et al, 2021;Yu et al, 2021).…”

Section: Study Of Heterosis With a Molecular Viewmentioning

confidence: 99%

Heterosis in horticultural crop breeding: combining old theoretical bases with modern genomic views

Farinati,

Scariolo,

Palumbo

et al. 2023

Front. Hortic.

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Heterosis in plants has been among the challenging topics for plant scientists worldwide. The production of F1 hybrid varieties of seed-propagated horticultural species is one of the most successful applications of plant breeding techniques. The exploitation of the heterosis phenomenon promotes homogeneity and maximizes crop yields and is a way for breeders to legally control and protect their commercial products. In the past heterosis has been largely studied and explored in cereal crop systems, considering maize as a model for understanding the genetic bases of this phenomenon. To date, crossbreeding in horticultural vegetables has also rapidly progressed. F1 hybrid varieties are available for many horticultural crops, including both allogamous and autogamous species. Several genetic and nongenetic mechanisms have been applied to facilitate the large-scale production of F1 hybrid seeds in vegetable crops to prevent undesirable selfing. Although the development and commercialization of F1 hybrids is currently common in agriculture, this phenomenon is still being investigated at different levels. With the rapid accumulation of knowledge on plant genome structures and gene activities and the advancement of new genomics platforms and methodologies, significant progress has been achieved in recent years in the study of the genetic and molecular bases of heterosis. This paper provides a brief overview of current theoretical advances and practical predictions of the molecular mechanisms underlying heterosis in plants. The aim is to carefully summarize the fundamental mechanisms of heterosis in plants, focusing on horticultural plant breeding, to improve the existing knowledge in this research area. We describe the quantitative genetic model of phenotypic variation and combine evolutionary, phenotypic and molecular genetic views to explain the origin and manifestation of heterosis and its significance for breeding F1 hybrid varieties in horticultural crops. The principles of genomic prediction and its applications in genomic selection are then covered.

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Heterosis prediction system based on non-additive genomic prediction models in cucumber (Cucumis sativus L.)

Cited by 7 publications

References 48 publications

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

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

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

Heterosis in horticultural crop breeding: combining old theoretical bases with modern genomic views

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