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Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: a case study of oil palm (Elaeis guineensis Jacq.)

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Abstract

Genomic selection (GS) is a method of marker-assisted selection revolutionizing crop improvement, but it can still be optimized. For hybrid breeding between heterozygote parents of different populations or species, specific aspects can be considered to increase GS accuracy: (1) training population genotyping, i.e., only genotyping the hybrid parents or also a sample of hybrid individuals, and (2) marker effects modeling, i.e., using population-specific effects of single nucleotide polymorphism alleles model (PSAM) or across-population SNP genotype model (ASGM). Here, this was investigated empirically for the prediction of the performances of oil palm hybrids for yield traits. The GS model was trained on 352 hybrid crosses and validated on 213 independent hybrid crosses. The training and validation hybrid parents and 399 training hybrid individuals were genotyping by sequencing. Despite the small proportion of hybrid individuals genotyped and low parental heterozygosity, GS prediction accuracy increased on average by 5% (range 1.4–31.3%, depending on trait and model) when training was done using genomic data on hybrids and parents compared with only parental genomic data. With ASGM, GS prediction accuracy increased on average by 3% (− 10.2 to 40%, depending on trait and genotyping strategy) compared with PSAM. We conclude that the best GS strategy for oil palm is to aggregate genomic data of parents and hybrid individuals and to ignore the parental origin of marker alleles (ASGM). To gain a better insight into these results, future studies should examine the respective effect of capturing genetic variability within crosses and taking segregation distortion into account when genotyping hybrid individuals, and investigate the factors controlling the relative performances of ASGM and PSAM in hybrid crops.

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Availability of data and material

Data used here are available from the corresponding author with the permission of PALMELIT SAS.

Code availability

Custom code used here is available from the corresponding author on reasonable request.

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Acknowledgements

The authors acknowledge SOCFINDO (Indonesia), CRAPP (Benin) and PalmElit (France) for planning and carrying out the field trials with CIRAD (France) and for authorizing the use of the phenotypic data for this study. We acknowledge the CETIC (African Center of Excellence in Information and Communication Technologies) for support, and thank the UMR AGAP genotyping technology platform (CIRAD, Montpellier), the DArT company (www.diversityarrays.com) and the CIRAD-UMR AGAP HPC data center of the South Green bioinformatics platform (http://www.southgreen.fr/) for their help. This research was partly funded by a grant from PalmElit SAS.

Funding

This work was partly supported by a grant from PALMELIT SAS.

Author information

Authors and Affiliations

  1. Department of Plant Biology, Faculty of Science, University of Yaoundé I, Yaoundé, Cameroon

    Achille Nyouma & Joseph Martin Bell

  2. CETIC (African Center of Excellence in Information and Communication Technologies), University of Yaoundé I, Yaoundé, Cameroon

    Achille Nyouma & David Cros

  3. PalmElit SAS, 34980, Montferrier sur Lez, France

    Florence Jacob, Benoit Cochard & Tristan Durand-Gasselin

  4. CIRAD, UMR AGAP Institut, 34398, Montpellier, France

    Achille Nyouma, Virginie Riou, Aurore Manez, Virginie Pomiès & David Cros

  5. UMR AGAP Institut, University of Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France

    Virginie Riou, Aurore Manez, Virginie Pomiès & David Cros

  6. INRAB, CRA-PP, Pobè, Benin

    Hubert Domonhedo

  7. P.T. SOCFINDO Medan, Medan, Indonesia

    Deni Arifiyanto

Authors
  1. Achille Nyouma
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  2. Joseph Martin Bell
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  3. Florence Jacob
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  4. Virginie Riou
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Contributions

AN performed data analysis, under the supervision of DC and JMB. The paper was written by AN and DC, with the help of FJ. BC, TDG, DA and HD participated in designing field experiments, producing the plant material, managing field trials, and collecting phenotypic data. The molecular data were generated by AM, VR and VP.

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Correspondence to David Cros.

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Communicated by Bing Yang.

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Nyouma, A., Bell, J.M., Jacob, F. et al. Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: a case study of oil palm (Elaeis guineensis Jacq.). Mol Genet Genomics 297, 523–533 (2022). https://doi.org/10.1007/s00438-022-01867-5

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