Effect of clonal testing on the efficiency of genomic evaluation in forest tree breeding
Jazyk angličtina Země Velká Británie, Anglie Médium electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
35194102
PubMed Central
PMC8864020
DOI
10.1038/s41598-022-06952-8
PII: 10.1038/s41598-022-06952-8
Knihovny.cz E-zdroje
- MeSH
- genom rostlinný genetika MeSH
- genomika metody MeSH
- lesy * MeSH
- rodokmen MeSH
- selekce (genetika) genetika MeSH
- šlechtění rostlin metody MeSH
- stromy genetika MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Through stochastic simulations, accuracies of breeding values and response to selection were assessed under traditional pedigree-(BLUP) and genomic-based evaluation methods (GBLUP) in forest tree breeding. The latter provides a methodological foundation for genomic selection. We evaluated the impact of clonal replication in progeny testing on the response to selection realized in seed orchards under variable marker density and target effective population sizes. We found that clonal replication in progeny trials boosted selection accuracy, thus providing additional genetic gains under BLUP. While a similar trend was observed for GBLUP, however, the added gains did not surpass those under BLUP. Therefore, breeding programs deploying extensive progeny testing with clonal propagation might not benefit from the deployment of genomic information. These findings could be helpful in the context of operational breeding programs.
Zobrazit více v PubMed
Grattapaglia D, Resende MDV. Genomic selection in forest tree breeding. Tree Genet. Genomes. 2010;7:241–255. doi: 10.1007/s11295-010-0328-4. DOI
Iwata H, Hayashi T, Tsumura Y. Prospects for genomic selection in conifer breeding: A simulation study of Cryptomeria japonica. Tree Genet. Genomes. 2011;7:747–758. doi: 10.1007/s11295-011-0371-9. DOI
Denis M, Bouvet JM. Efficiency of genomic selection with models including dominance effect in the context of Eucalyptus breeding. Tree Genet. Genomes. 2013;9:37–51. doi: 10.1007/s11295-012-0528-1. DOI
Id, Y. L. & Dungey, H. S. Expected benefit of genomic selection over forward selection in conifer breeding and deployment. PubMed PMC
Stejskal, J., Lstibůrek, M., Klápště, J., Čepl, J. & El-Kassaby, Y. A. Effect of genomic prediction on response to selection in forest tree breeding.
Neale DB, Savolainen O. Association genetics of complex traits in conifers. Trends Plant Sci. 2004;9:325–330. doi: 10.1016/j.tplants.2004.05.006. PubMed DOI
White, T. L., Adams, W. T. & Neale, D. B.
Russell JH, Libby WJ. Clonal testing efficiency: The trade-offs between clones tested and ramets per clone. Can. J. For. Res. 1986;16:925–930. doi: 10.1139/x86-164. DOI
Rosvall O, Lindgren D, Mullin TJ. Sustainability robustness and efficiency of a multi-generation breeding strategy based on within-family clonal selection. Silvae Genet. 1998;47:307–321.
Lindgren D, Danusevicius D, Rosvall O. Unequal deployment of clones to seed orchards by considering genetic gain, relatedness and gene diversity. Forestry. 2009;82:17–28. doi: 10.1093/forestry/cpn033. DOI
Russell JH, Loo-Dinkins JA. Distribution of testing effort in cloned genetic tests. Silvae Genet. 1993;42:98.
R Core Team, Rf. R: A language and environment for statistical computing. (2013).
Jombart, T. & Ahmed, I. adegenet 1.3–1: New tools for the analysis of genome-wide SNP data. PubMed PMC
Morrissey MB, Wilson AJ. Pedantics: An r package for pedigree-based genetic simulation and pedigree manipulation, characterization and viewing. Mol. Ecol. Resour. 2010;10:711–719. doi: 10.1111/j.1755-0998.2009.02817.x. PubMed DOI
Gilmour, A. R., Gogel, B. J., Cullis, B. R., Welham, S. J. & Thompson, R. ASReml user guide release 4.1 functional specification.
Mrode, R. A.
VanRaden PM. Efficient methods to compute genomic predictions. J. Dairy Sci. 2008;91:4414–4423. doi: 10.3168/jds.2007-0980. PubMed DOI
Gurobi Optimization, I. Gurobi optimizer reference manual, version 6.0. http//www.gurobi.com. Retrieved (2014).
Lstibůrek M, Hodge GR, Lachout P. Uncovering genetic information from commercial forest plantations: Making up for lost time using “Breeding without Breeding”. Tree Genet. Genomes. 2015;11:55. doi: 10.1007/s11295-015-0881-y. DOI
Henryon M, et al. Pedigree relationships to control inbreeding in optimum-contribution selection realise more genetic gain than genomic relationships. Genet. Sel. Evol. 2019;51:1–12. doi: 10.1186/s12711-019-0475-5. PubMed DOI PMC
Jighly A, et al. Boosting genetic gain in allogamous crops via speed breeding and genomic selection. Front. Plant Sci. 2019;10:1364. doi: 10.3389/fpls.2019.01364. PubMed DOI PMC
Habier D, Fernando RL, Dekkers JCM. The impact of genetic relationship information on genome-assisted breeding values. Genetics. 2007;177:2389–2397. doi: 10.1534/genetics.107.081190. PubMed DOI PMC
Habier D, Fernando RL, Garrick DJ. Genomic BLUP decoded: A look into the black box of genomic prediction. Genetics. 2013;194:597–607. doi: 10.1534/genetics.113.152207. PubMed DOI PMC