Genomic selection in forest tree breeding

By D. Grattapaglia, M. Resende. Tree Genetics & Genomes, 2011

410 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/bc22b40efc045f4716158de8efdc236b76abf4e9

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In Genetics

Citations in the corpus

Breeding trees resistant to insects and diseases: putting theory into application (2017, background): “This can only be accomplished using sufficiently large training populations that have undergone at least some breeding and have been carefully phenotyped for the desired trait, resources that only the most-advanced and wellfunded forest tree breeding programs can produce (Jannink et al. 2010; Isik 2”
Genomic selection in forest tree breeding: the concept and an outlook to the future (2014, methodology): “The size of the training population had a relatively minor effect on accuracy of GEBV in simulation studies (Grattapaglia and Resende 2011).”
Genomic Relationship Matrix for Correcting Pedigree Errors in Breeding Populations: Impact on Genetic Parameters and Genomic Selection Accuracy (2014, methodology): “The utility of GS in plant and animal breeding depends on the accuracy of the GS models developed to predict BV (Goddard and Hayes, 2009; Habier et al., 2010; Jannink et al., 2010; Grattapaglia and Resende, 2011; Heffner et al., 2010).”
Assessment of the Genetic Diversity in Forest Tree Populations Using Molecular Markers (2014, background): “genome-wide selection approaches have become feasible for accelerating forest tree breeding [7,8].”
Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application (2017, background): “can be greatly reduced and the expected genetic gains per unit of time can be increased (Grattapaglia and Resende 2011; Isik 2014).”
The genomics of local adaptation in trees: are we out of the woods yet? (2017, background): “2009), and particularly under the framework of genomic selection (GS) in trees (Wong and Bernardo 2008; Grattapaglia and Resende 2011; Iwata et al. 2011; defined and reviewed by Grattapaglia 2017).”
Accuracy of Genomewide Selection for Different Traits with Constant Population Size, Heritability, and Number of Markers (2013, background): “, 2011a), forest trees (Grattapaglia and Resende, 2011), and maize (Albrecht et al.”
Whole-Genome Regression and Prediction Methods Applied to Plant and Animal Breeding (2013, methodology): “For applications in plants, it has been shown that GS outperforms conventional marker-assisted selection (Heffner et al. 2010, 2011) and that it has the potential to be substantially more efficient per unit of time than phenotypic selection (Grattapaglia and Resende 2011; Zhao et al. 2012).”
Prospects for genomic selection in conifer breeding: a simulation study of Cryptomeria japonica (2011, background): “(2001)—which is a form of MAS incorporating all marker information from the entire genome in the prediction—has attracted increasing attention in plant breeding (Heffner et al. 2009; Jannink et al. 2010; Grattapaglia and Resende 2010) as well as animal breeding (Hayes et al.”
Forests and global change: what can genetics contribute to the major forest management and policy challenges of the twenty-first century? (2016, background): “, over 15,000–30,000 markers in forest trees), genomic selection approaches are able to predict phenotypes with variable degrees of accuracy, depending on the effective population size of the base population, linkage disequilibrium, heritability and the genetic architecture of the desired trait (Gra”
Non-Destructive Evaluation Techniques and What They Tell Us about Wood Property Variation (2019, background): “The use of DNA markers promises to lower selection age even more, reducing the need for continuous phenotypic assessment, including wood properties [28,29].”
Growing Plantation Forests (2010, background): “Research is continuing on the use of molecular markers to aid in selection in breeding programmes (Falconer and Mackay 1996; Boyle et al. 1997; Walter et al. 1998; Burley 2001; Kumar and Garrick 2001; van Buijtenen 2001; Potts 2004; Tani et al. 2004; Lörz and Wenzel 2005; Srivastava and Narula 2005;”
Potential for evolutionary responses to climate change – evidence from tree populations (2013, methodology): “Alternatively, genomic selection methods could be used to build predictive models that do not need to identify the particular loci underlying adaptive genetic responses (Grattapaglia & Resende, 2011; Iwata et al., 2011; Holliday et al., 2012; Resende et al., 2012).”