Impact of Genetic Divergence on the Ratio of Variance Due to Specific vs. General Combining Ability in Winter Triticale

Fischer, Sandra E.; Möhring, Jens; Maurer, Hans Peter; Piepho, Hans‐Peter; Thiemt, E. M.; Schön, C. C.; Melchinger, Albrecht E.; Reif, Jochen C.

doi:10.2135/cropsci2008.12.0689

Cited by 13 publications

(13 citation statements)

References 19 publications

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“…Based on quantitative genetic theory, it has been shown that genetically distinct heterotic groups decrease the 2 2 SCA GCA / s s ratio, supporting GCA-based hybrid prediction (Reif et al, 2007). These findings were confirmed in experimental studies by, for instance, Fischer et al (2009) using 210 single-cross triticale hybrids. The two-way hybrids in our study are based on genetically distinct male and female pools (Fig.…”

Section: High Prediction Ability Of Hybrid Performance Based On Gca Ementioning

confidence: 67%

Genomic Prediction of Barley Hybrid Performance

Liu

Zhao

et al. 2016

The Plant Genome

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Hybrid breeding in barley (Hordeum vulgare L.) offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP) array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA) effects was moderate, amounting to 0.56 and 0.48 for two-and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two-and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

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Section: High Prediction Ability Of Hybrid Performance Based On Gca Ementioning

confidence: 67%

Genomic Prediction of Barley Hybrid Performance

Liu

Zhao

et al. 2016

The Plant Genome

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“…This can be interpreted as an indicator that σ 2 GCA is of low importance and consequently, this suggests that prediction accuracy can only be enhanced slightly by considering GCA eff ects. Increasing genetic divergence of the two parental populations tends to lead to a high ratio of σ 2 GCA vs. σ 2 SCA (Fischer et al, 2009). This is supported by a significant association between mid-parent and hybrid performance and therefore, relevance of additive gene actions.…”

Section: Prediction Of Hybrid Performancementioning

confidence: 82%

“…The σ 2 GCA /σ 2 SCA ratio in hybrids varies depending on the allele frequencies between parents (Reif et al, 2007). Increasing genetic divergence of the two parental populations tends to lead to a high ratio of σ 2 GCA vs. σ 2 SCA (Fischer et al, 2009). Therefore, development of genetically divergent heterotic groups is pivotal for establishing a hybrid breeding program in durum wheat.…”

Section: Prediction Of Hybrid Performancementioning

confidence: 99%

Hybrid Breeding in Durum Wheat: Heterosis and Combining Ability

et al. 2010

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Hybrid breeding facilitates a maximum exploitation of heterosis. The objectives of our research were to (i) examine the magnitude of heterosis over the mid‐ and better parent for yield, yield components, and quality traits in Central European spring durum wheat and (ii) investigate the efficiency of parental selection based on mid‐parent value or general combining ability effects. Sixteen inbred lines and 40 incomplete factorial crosses were field‐evaluated for eight agronomic traits at 10 environments in Germany. For grain yield, the hybrids yielded on average 10% higher than the mid‐parent performance, and the maximum superiority was 22%. The significantly positive contrast between inbreeding depression and mid‐parent heterosis for grain yield indicated the presence of positive additive x additive epistatic interactions. Furthermore, the best hybrid outperformed the best line variety by 1.01 Mg ha−1 We conclude that there is a potential for hybrid breeding in durum wheat.

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“…The last example is a dataset of triticale (×Triticosecale Wittm.) (Fischer et al, 2009). The experiment was replicated twice in each of fi ve locations and included 280 entries in an α-design with 28 blocks and 10 entries per block.…”

Section: Datasetsmentioning

confidence: 99%

“…Given this approach, fitting of a mixed model to complex block structures, spatial error structures and heterogeneous variances within the mixed‐model approach is straightforward. Later in this paper, we will demonstrate the implementation with three datasets described in the literature (Hayman, 1954; Lonnquist and Gardner, 1961; Fischer et al, 2009).…”

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confidence: 99%

REML‐Based Diallel Analysis

2011

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Diallel analyses can give different results depending on the model and the experimental design. A unified framework to fit and compare different models by mixed‐model packages is lacking. We, therefore, present a general diallel model and the required additional restrictions for the genetic variance–covariance structure to become equivalent to other commonly used diallel models. We discuss the definitions and requirements of the commonly used models compared with the general model and provide an analysis for three real datasets. If the assumptions regarding the genetic variance–covariance structure are not fulfilled, biased variance‐component estimates for general and specific combining ability effects are obtained when using random genetic effects. We implemented a general diallel model in the statistical software packages SAS and ASReml and give detailed program codes. If no a priori information about the genetic model for genotypes is available, the general model can be used to analyze all diallel designs easily with standard statistical software.

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Impact of Genetic Divergence on the Ratio of Variance Due to Specific vs. General Combining Ability in Winter Triticale

Cited by 13 publications

References 19 publications

Genomic Prediction of Barley Hybrid Performance

Genomic Prediction of Barley Hybrid Performance

Hybrid Breeding in Durum Wheat: Heterosis and Combining Ability

REML‐Based Diallel Analysis

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