Genomic Selection for growth traits in Eucalyptus: accuracy within and across breeding populations

Grattapaglia, Dário; Resende, Marcos Deon Vilela de; Resende, Márcio Ribeiro; Sansaloni, Carolina; Petroli, César; Missiaggia, A. A.; Takahashi, Elisabete Keiko; Zamprogno, Karina Carnielli; Kilian, Andrzej

doi:10.1186/1753-6561-5-s7-o16

Cited by 20 publications

(17 citation statements)

References 4 publications

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“…Ever since the first experimental GS studies in forest trees (Grattapaglia et al, 2011 ; Resende et al, 2012a , b ), it became clear that prediction accuracies are mainly driven by genetic relationship between training and validation sets and are dependent on G * E and age-age correlations. Predictions will be most effective at the same age and in the same environment where the prediction model was trained.…”

Section: Gs: Advances and Challenges In Forest Treesmentioning

confidence: 99%

Quantitative Genetics and Genomics Converge to Accelerate Forest Tree Breeding

et al. 2018

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Forest tree breeding has been successful at delivering genetically improved material for multiple traits based on recurrent cycles of selection, mating, and testing. However, long breeding cycles, late flowering, variable juvenile-mature correlations, emerging pests and diseases, climate, and market changes, all pose formidable challenges. Genetic dissection approaches such as quantitative trait mapping and association genetics have been fruitless to effectively drive operational marker-assisted selection (MAS) in forest trees, largely because of the complex multifactorial inheritance of most, if not all traits of interest. The convergence of high-throughput genomics and quantitative genetics has established two new paradigms that are changing contemporary tree breeding dogmas. Genomic selection (GS) uses large number of genome-wide markers to predict complex phenotypes. It has the potential to accelerate breeding cycles, increase selection intensity and improve the accuracy of breeding values. Realized genomic relationships matrices, on the other hand, provide innovations in genetic parameters' estimation and breeding approaches by tracking the variation arising from random Mendelian segregation in pedigrees. In light of a recent flow of promising experimental results, here we briefly review the main concepts, analytical tools and remaining challenges that currently underlie the application of genomics data to tree breeding. With easy and cost-effective genotyping, we are now at the brink of extensive adoption of GS in tree breeding. Areas for future GS research include optimizing strategies for updating prediction models, adding validated functional genomics data to improve prediction accuracy, and integrating genomic and multi-environment data for forecasting the performance of genetic material in untested sites or under changing climate scenarios. The buildup of phenotypic and genome-wide data across large-scale breeding populations and advances in computational prediction of discrete genomic features should also provide opportunities to enhance the application of genomics to tree breeding.

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Section: Gs: Advances and Challenges In Forest Treesmentioning

confidence: 99%

Quantitative Genetics and Genomics Converge to Accelerate Forest Tree Breeding

et al. 2018

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“…GS of perennial crops is considered to be more effective than annual crops because of their long generation times. GEBV predictions based on empirical data were presented for Loblolly pine and eucalyptus at the IUFRO Tree Biotechnology Conference 2011 (Table 2 ; Grattapaglia et al , 2011 ; Isik et al , 2011 ; Resende et al , 2011 ). All cases used full-sib families as test populations and the number of individuals ranged from 149 to 920.…”

Section: Recent Progress In Gs Studiesmentioning

confidence: 99%

Will genomic selection be a practical method for plant breeding?

2012

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BackgroundGenomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use.ScopeIn this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed.ConclusionsStatistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory.

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“…By using high density markers covering the whole genome, instead of few significant markers, GS selects favourable individuals based on genomic estimate of breeding value (GEBV) and is expected to address small effect genes that cannot be captured by traditional QTL mapping (Meuwissen et al 2001;Hayes et al 2009). Conventional microarray DArT markers have been successfully applied for GS of wheat (Crossa et al 2010;Rutkoski et al 2012), sugarcane (Guoy et al 2013) and forest trees Eucalyptus (Grattapaglia et al 2011;Resende et al 2012).…”

Section: Discussionmentioning

confidence: 99%

High density SNP and DArT-based genetic linkage maps of two closely related oil palm populations

Gan

Wong

et al. 2017

J Appl Genetics

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Oil palm (Elaeis guineensis Jacq.) is an outbreeding perennial tree crop with long breeding cycles, typically 12 years. Molecular marker technologies can greatly improve the breeding efficiency of oil palm. This study reports the first use of the DArTseq platform to genotype two closely related self-pollinated oil palm populations, namely AA0768 and AA0769 with 48 and 58 progeny respectively. Genetic maps were constructed using the DArT and SNP markers generated in combination with anchor SSR markers. Both maps consisted of 16 major independent linkage groups (2n = 2× = 32) with 1399 and 1466 mapped markers for the AA0768 and AA0769 populations, respectively, including the morphological trait "shell-thickness" (Sh). The map lengths were 1873.7 and 1720.6 cM with an average marker density of 1.34 and 1.17 cM, respectively. The integrated map was 1803.1 cM long with 2066 mapped markers and average marker density of 0.87 cM. A total of 82% of the DArTseq marker sequence tags identified a single site in the published genome sequence, suggesting preferential targeting of gene-rich regions by DArTseq markers. Map integration of higher density focused around the Sh region identified closely linked markers to the Sh, with D.15322 marker 0.24 cM away from the morphological trait and 5071 bp from the transcriptional start of the published SHELL gene. Identification of the Sh marker demonstrates the robustness of using the DArTseq platform to generate high density genetic maps of oil palm with good genome coverage. Both genetic maps and integrated maps will be useful for quantitative trait loci analysis of important yield traits as well as potentially assisting the anchoring of genetic maps to genomic sequences.

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Genomic Selection for growth traits in Eucalyptus: accuracy within and across breeding populations

Cited by 20 publications

References 4 publications

Quantitative Genetics and Genomics Converge to Accelerate Forest Tree Breeding

Quantitative Genetics and Genomics Converge to Accelerate Forest Tree Breeding

Will genomic selection be a practical method for plant breeding?

High density SNP and DArT-based genetic linkage maps of two closely related oil palm populations

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