Tree Genetics & Genomes

, 14:71 | Cite as

Performance of multi-trait genomic selection for Eucalyptus robusta breeding program

  • Tahina Rambolarimanana
  • Lolona Ramamonjisoa
  • Daniel Verhaegen
  • Jean-Michel Leong Pock Tsy
  • Laval Jacquin
  • Tuong-Vi Cao-Hamadou
  • Garel Makouanzi
  • Jean-Marc Bouvet
Original Article
Part of the following topical collections:
  1. Breeding


In forest tree genetic improvement, multi-trait genomic selection (GS) may have advantages in improving the accuracy of the genotype estimation and shortening selection cycles. For the breeding of Eucalyptus robusta, one of the most exotic planted species in Madagascar, volume at 49 months (V49), total lignin (TL), and holo-cellulose (Holo) were considered. For GS, 2919 single nucleotide polymorphisms (SNP) were used with the genomic best linear unbiased predictor (GBLUP) method, which was as efficient as the reproducing kernel Hilbert space (RKHS) and elastic net methods (EN), but more adapted to multi-trait modeling. The efficiency of individual I model, including the genomic data, was much higher than the provenance effect P model. For example, with V49, mean goodness-of-fit was: rI_Full = 0.79, rP_Full = 0.37 for I and P, respectively. The prediction accuracies using the cross-validation procedure were lower for V49: rI = 0.29 rP = 0.28. The genetic gains resulting from the indexes associating (V49, TL) and (V49, Holo) were higher using I than for the P model; for V49, the relative genetic gain was 37 and 20%, respectively, with 5% of selection intensity. The single-trait approach was as efficient as the multi-trait approach given the weak correlations between V49 and TL or Holo. The I model also brings greater diversity: for V49 the number of provenances represented in a selected population was two and three with the P model, and 6 and 16 with the I model.


GBLUP Selection index Lignin Cellulose Genetic diversity Madagascar 



This study was conducted within the framework of the PhD fellowship funded by CIRAD for the research platform in the “Forest and Biodiversity in Madagascar” partnership. Field experiments were conducted at FOFIFA, the forest experimental station of Mahela in Madagascar in the framework of the E. robusta breeding program. Near infrared spectroscopy analyses were performed under the technical supervision of Gilles Chaix in the CIRAD laboratories in Montpellier, France. We thank our colleagues in Madagascar for their valuable help in sampling. We also thank the two reviewers for their valuable comments and suggestions to improve the first version of the manuscript.

Data archiving statement

Data will be available from the Dryad Digital Repository if the manuscript is accepted. The data will consist in two files: a file with the phenotype of the 415 trees and a file with the 2919 SNP for each of the tree.

Author contributions

Implementation and sampling: TR, JML, DV, and JMB; study and analysis design: TR, TC, JL, and JMB. TR and JMB supervised the writing and LR, TV, GM, and JML contributed ideas, comments, analyses, and revised manuscript versions.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Supplementary material

11295_2018_1286_MOESM1_ESM.docx (61 kb)
ESM 1 (DOCX 60 kb)


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Tahina Rambolarimanana
    • 1
    • 2
  • Lolona Ramamonjisoa
    • 1
  • Daniel Verhaegen
    • 2
    • 3
  • Jean-Michel Leong Pock Tsy
    • 2
    • 4
  • Laval Jacquin
    • 3
  • Tuong-Vi Cao-Hamadou
    • 3
  • Garel Makouanzi
    • 5
  • Jean-Marc Bouvet
    • 2
    • 3
  1. 1.ESSA, Ecole Supérieure des Sciences AgronomiquesUniversité d’AntananarivoAntananarivoMadagascar
  2. 2.Dispositif de recherche et d’enseignement en partenariat “Forêts et Biodiversité à Madagascar”Cirad-FOFIFA-Université d’AntananarivoAntananarivoMadagascar
  3. 3.UMR AGAP, Amélioration Génétique et Adaptation des Plantes Tropicales et MéditerranéennesUniv Montpellier, CIRAD, INRA, Montpellier SupAgroMontpellierFrance
  4. 4.DRFGRN, Département des Recherches Forestières et de Gestion des Ressources NaturellesFOFIFAAntananarivoMadagascar
  5. 5.ENSAF, Ecole Supérieure des Sciences Agronomiques et ForestièresUniversité Marien NGOUABIBrazzavilleRépublique du Congo

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