Genetic structure of the shea tree (Vitellaria paradoxa C.F. Gaertn.) population and fatty acid-based selection of elite genotypes in Benin 

Bodjrenou GJ, Gbètoho M, Honfo F, et al (2026) Genetic structure of the shea tree (Vitellaria paradoxa C.F. Gaertn.) population and fatty acid-based selection of elite genotypes in Benin. Physiology and Molecular Biology of Plants 1–16. https://doi.org/10.1007/s12298-026-01734-2

The shea tree (Vitellaria paradoxa C.F. Gaertn.) is an important source of oil, primarily used in the chocolate, cosmetics, and food industries. However, the absence of elite domesticated varieties limits breeding and optimal utilization. This study explores the genetic diversity, population structure and biochemical variation to identify genotypes with high oilseed potential in Benin. A total of 167 trees were genotyped using DArTseq technology, generating 3,720 high-quality single nucleotide polymorphism (SNP) markers after strict filtering. Data for two years (2023–2024) were collected, including agromorphological and biochemical data (fat content and fatty acid profile). Genetic diversity analysis revealed a moderate genetic diversity, with expected heterozygosity values of He = 0.21. Analysis of Molecular Variance (AMOVA) revealed significant differentiation (p < 0.01), with 7.9% of variance attributed to differences among populations. Population structure analysis distinguished three genetic groups (Pop1, Pop2, Pop3), with strong differentiation between Pop1 and Pop3 (FST > 0.85). Correlation analysis revealed positive relationships between nut traits and fatty acid composition. Five major fatty acids were found in the shea kernels: stearic (C18:0; 141.5 mg/g ≈ 45.6%), oleic (C18:1n-9, 125.49 mg/g ≈ 43.7%), linoleic (C18:2n-6, 17.43 mg/g ≈ 5.98%), palmitic (C16:0, 9.9 mg/g ≈ 3.6%), and arachidic (C20:0, 4.63 mg/g ≈ 1%). Genotypes BG104, BG109, BG114, BG214 and BG258 were elite candidates for fat and fatty acid content. This study offers an overview of the genetic potential of shea trees in Benin, identifying the best genotypes with high concentrations of fat and fatty acid composition for future breeding programs.

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