Genomic selection for morphological and yield-related traits using genome-wide SNPs in oil palm

Gina A Garzón-Martínez; Jaime A Osorio-Guarín; Leidy P Moreno; Silvio Bastidas; Luz Stella Barrero; Marco Lopez-Cruz; Felix E Enciso-Rodríguez

doi:10.1007/s11032-022-01341-5

Genomic selection for morphological and yield-related traits using genome-wide SNPs in oil palm

Mol Breed. 2022 Nov 18;42(12):71. doi: 10.1007/s11032-022-01341-5. eCollection 2022 Dec.

Authors

Gina A Garzón-Martínez¹, Jaime A Osorio-Guarín¹, Leidy P Moreno², Silvio Bastidas², Luz Stella Barrero¹, Marco Lopez-Cruz^{3

4}, Felix E Enciso-Rodríguez^{1

5}

Affiliations

¹ Centro de Investigación Tibaitatá, Corporación Colombiana de Investigación Agropecuaria (Agrosavia), Mosquera, Cundinamarca Colombia.
² Centro de Investigación Palmira, Corporación Colombiana de Investigación Agropecuaria (Agrosavia), Palmira, Valle del Cauca Colombia.
³ Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI USA.
⁴ Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI USA.
⁵ Blueberry Breeding Program, Department of Horticulture Sciences, University of Florida, 2211 Fifield Hall, 2550 Hull Rd, Gainesville, FL 32611 USA.

Abstract

Oil palm is the most important oil crop worldwide. Colombia is the fourth largest producer, primarily relying on production from interspecific hybrids, derived from crosses between Elaeis oleifera and Elaeis guineensis (OxG). However, conventional breeding can take up to 20 years to generate a new variety. Therefore, reducing the breeding cycle while improving the genetic gain for complex traits is desirable. Genomic selection (GS) is an approach with the potential to achieve this goal. In this study, we evaluated 431 F₁ interspecific hybrids (OxG) and 444 backcrosses (BC₁) for morphological and yield-related traits. Genomic predictions were performed with the G-BLUP model using three different population datasets for training the model: the same population (TRN₁), the other population (TRN₂), and both populations (TRN₁₊₂). Higher multi-family prediction accuracies were obtained for foliar area (0.3 in OxG) and trunk height (0.47 in BC₁) when the model was trained with TRN₁. Single-family prediction accuracies were lower in the OxG compared to BC₁ families for traits such as trunk diameter, trunk height, bunch number, and yield using TRN₁. Conversely, lower prediction accuracies were obtained for most traits when the model was trained using TRN₂ (< 0.1). Multi-trait models showed a substantial increase of the predictions for traits such as yield (0.22 for OxG and 0.44 for BC₁), because of the genetic correlations between traits. The results herein highlighted the potential of GS for parental selection in OxG and BC₁ populations, but further studies are required to improve the models to select individuals by their genetic value.

Supplementary information: The online version contains supplementary material available at 10.1007/s11032-022-01341-5.

Keywords: Genomic selection; Hybrid; Oil palm; SNP.

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