Tree Genetics & Genomes

, Volume 7, Issue 2, pp 241–255 | Cite as

Genomic selection in forest tree breeding

Original Paper

Abstract

Genomic selection (GS) involves selection decisions based on genomic breeding values estimated as the sum of the effects of genome-wide markers capturing most quantitative trait loci (QTL) for the target trait(s). GS is revolutionizing breeding practice in domestic animals. The same approach and concepts can be readily applied to forest tree breeding where long generation times and late expressing complex traits are also a challenge. GS in forest trees would have additional advantages: large training populations can be easily assembled and accurately phenotyped for several traits, and the extent of linkage disequilibrium (LD) can be high in elite populations with small effective population size (N e) frequently used in advanced forest tree breeding programs. Deterministic equations were used to assess the impact of LD (modeled by N e and intermarker distance), the size of the training set, trait heritability, and the number of QTL on the predicted accuracy of GS. Results indicate that GS has the potential to radically improve the efficiency of tree breeding. The benchmark accuracy of conventional BLUP selection is reached by GS even at a marker density ~2 markers/cM when N e ≤ 30, while up to 20 markers/cM are necessary for larger N e. Shortening the breeding cycle by 50% with GS provides an increase ≥100% in selection efficiency. With the rapid technological advances and declining costs of genotyping, our cautiously optimistic outlook is that GS has great potential to accelerate tree breeding. However, further simulation studies and proof-of-concept experiments of GS are needed before recommending it for operational implementation.

Keywords

Genome-wide selection Effective population size Linkage disequilibrium Marker-assisted selection MAS 

Notes

Acknowledgments

This work was supported by the Brazilian Ministry of Science and Technology through FINEP grant 1755-01 (Genolyptus project), EMBRAPA Macroprogram grant 03.08.01.010, CNPq grant 577047/2008-6, and CNPq research productivity fellowships awarded to DG and MDVR. We thank the anonymous reviewers for their comments and suggestions on the manuscript.

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Plant Genetics LaboratoryEMBRAPA-Genetic Resources and BiotechnologyBrasíliaBrazil
  2. 2.Graduate Program in Genomic Sciences and BiotechnologyUniversidade Catolica de BrasíliaBrasíliaBrazil
  3. 3.EMBRAPA Forestry, Estrada da RibeiraColomboBrazil
  4. 4.Department of Forest EngineeringUniversidade Federal de Viçosa-UFVViçosaBrazil

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