On the accuracy of genomic prediction models considering multi-trait and allele dosage in Urochloa spp. interspecific tetraploid hybrids

Matias, Filipe Inácio; Alves, Filipe Couto; Meireles, Karem Guimarães Xavier; Barrios, S. C. L.; Valle, Cacilda Borges do; Endelman, Jeffrey B.; Fritsche‐Neto, Roberto

doi:10.1007/s11032-019-1002-7

Cited by 33 publications

(34 citation statements)

References 74 publications

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“…For this species, a greater amount (g/plant) of TDM and LDM in the progenies has been associated with considerable heritability from the most productive parents (Braz et al, 2013;Braz et al, 2017). Matias et al (2019) also verified the same pattern in interspecific hybrids from Urochloa spp., another genus adapted to tropical conditions. The intermediate heritability of RC and the QTLs associated with this trait that were detected in both parents resulted in hybrids with a good capacity for regrowth.…”

Section: Qtls For Agronomic and Nutritional Traitssupporting

confidence: 67%

High-Resolution Linkage Map With Allele Dosage Allows the Identification of Regions Governing Complex Traits and Apospory in Guinea Grass (Megathyrsus maximus)

et al. 2020

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Section: Qtls For Agronomic and Nutritional Traitssupporting

confidence: 67%

High-Resolution Linkage Map With Allele Dosage Allows the Identification of Regions Governing Complex Traits and Apospory in Guinea Grass (Megathyrsus maximus)

et al. 2020

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“…Expected genetic gain (EGG) was estimated in two ways: the classic method used in rubber tree breeding via the breeder’s equation and phenotypic data and with information from the SNPs obtained via GS. The EGG was calculated according to the methods of Matias et al (2019) and Grattapaglia (2017).…”

Section: Methodsmentioning

confidence: 99%

Genomic Selection in Rubber Tree Breeding: A Comparison of Models and Methods for Managing G×E Interactions

et al. 2019

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Several genomic prediction models combining genotype × environment (G×E) interactions have recently been developed and used for genomic selection (GS) in plant breeding programs. G×E interactions reduce selection accuracy and limit genetic gains in plant breeding. Two data sets were used to compare the prediction abilities of multienvironment G×E genomic models and two kernel methods. Specifically, a linear kernel, or GB (genomic best linear unbiased predictor [GBLUP]), and a nonlinear kernel, or Gaussian kernel (GK), were used to compare the prediction accuracies (PAs) of four genomic prediction models: 1) a single-environment, main genotypic effect model (SM); 2) a multienvironment, main genotypic effect model (MM); 3) a multienvironment, single-variance G×E deviation model (MDs); and 4) a multienvironment, environment-specific variance G×E deviation model (MDe). We evaluated the utility of genomic selection (GS) for 435 individual rubber trees at two sites and genotyped the individuals via genotyping-by-sequencing (GBS) of single-nucleotide polymorphisms (SNPs). Prediction models were used to estimate stem circumference (SC) during the first 4 years of tree development in conjunction with a broad-sense heritability (H 2) of 0.60. Applying the model (SM, MM, MDs, and MDe) and kernel method (GB and GK) combinations to the rubber tree data revealed that the multienvironment models were superior to the single-environment genomic models, regardless of the kernel (GB or GK) used, suggesting that introducing interactions between markers and environmental conditions increases the proportion of variance explained by the model and, more importantly, the PA. Compared with the classic breeding method (CBM), methods in which GS is incorporated resulted in a 5-fold increase in response to selection for SC with multienvironment GS (MM, MDe, or MDs). Furthermore, GS resulted in a more balanced selection response for SC and contributed to a reduction in selection time when used in conjunction with traditional genetic breeding programs. Given the rapid advances in genotyping methods and their declining costs and given the overall costs of large-scale progeny testing and shortened breeding cycles, we expect GS to be implemented in rubber tree breeding programs.

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“…Therefore, our results suggest that to consider diploid dosage for autopolyploid analyses results in a lower ρ . This noteworthy impacts downstream application as in genomic selection where autotetraploid studies have shown a higher (or at least similar) predictive accuracy of dosage models when compared with diploidized models ( de Bem Oliveira et al 2019 ; Matias et al 2019 ; de C. Lara et al 2019).…”

Section: Resultsmentioning

confidence: 99%

“…In breeding, crosses are planned to combine parents with distinct genetic backgrounds, enhancing heterosis and accelerating the development of improved cultivars ( Wricke and Weber 1986 ). Despite the usage of r estimates based on molecular data on polyploid crops as blueberry ( Ferrão et al 2018 ; de Bem Oliveira et al 2019 ), potato ( Endelman et al 2018 ; Amadeu et al 2020 ), and different forages (de C. Lara et al 2019; Matias et al 2019 ), there is a lack of studies about the computation of pairwise relatedness in polyploidy species where researchers need to be able to estimate r in the best possible way.…”

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confidence: 99%

Estimation of Molecular Pairwise Relatedness in Autopolyploid Crops

Amadeu

Lara

Muñoz

et al. 2020

G3 Genes|Genomes|Genetics

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A suitable pairwise relatedness estimation is key to genetic studies. Several methods are proposed to compute relatedness in autopolyploids based on molecular data. However, unlike diploids, autopolyploids still need further studies considering scenarios with many linked molecular markers with known dosage. In this study, we provide guidelines for plant geneticists and breeders to access trustworthy pairwise relatedness estimates. To this end, we simulated populations considering different ploidy levels, meiotic pairings patterns, number of loci and alleles, and inbreeding levels. Analysis were performed to access the accuracy of distinct methods and to demonstrate the usefulness of molecular marker in practical situations. Overall, our results suggest that at least 100 effective biallelic molecular markers are required to have good pairwise relatedness estimation if methods based on correlation is used. For this number of loci, current methods based on multiallelic markers show lower performance than biallelic ones. To estimate relatedness in cases of inbreeding or close relationships (as parent-offspring, full-sibs, or half-sibs) is more challenging. Methods to estimate pairwise relatedness based on molecular markers, for different ploidy levels or pedigrees were implemented in the AGHmatrix R package.

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On the accuracy of genomic prediction models considering multi-trait and allele dosage in Urochloa spp. interspecific tetraploid hybrids

Cited by 33 publications

References 74 publications

High-Resolution Linkage Map With Allele Dosage Allows the Identification of Regions Governing Complex Traits and Apospory in Guinea Grass (Megathyrsus maximus)

High-Resolution Linkage Map With Allele Dosage Allows the Identification of Regions Governing Complex Traits and Apospory in Guinea Grass (Megathyrsus maximus)

Genomic Selection in Rubber Tree Breeding: A Comparison of Models and Methods for Managing G×E Interactions

Estimation of Molecular Pairwise Relatedness in Autopolyploid Crops

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