Simulation-based evaluation of three methods for local ancestry deconvolution of non-model crop species genomes

Cottin Aurélien, Penaud Benjamin, Glaszmann Jean-Christophe, Yahiaoui Nabila, Gautier Mathieu. 2020. Simulation-based evaluation of three methods for local ancestry deconvolution of non-model crop species genomes. G3 - Genes Genomes Genetics, 10 (2) : pp. 569-579.

Journal article ; Article de recherche ; Article de revue à facteur d'impact Revue en libre accès total
Published version - Anglais
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Abstract : Hybridizations between species and subspecies represented major steps in the history of many crop species. Such events generally lead to genomes with mosaic patterns of chromosomal segments of various origins that may be assessed by local ancestry inference methods. However, these methods have mainly been developed in the context of human population genetics with implicit assumptions that may not always fit plant models. The purpose of this study was to evaluate the suitability of three state-of-the-art inference methods (SABER, ELAI and WINPOP) for local ancestry inference under scenarios that can be encountered in plant species. For this, we developed an R package to simulate genotyping data under such scenarios. The tested inference methods performed similarly well as far as representatives of source populations were available. As expected, the higher the level of differentiation between ancestral source populations and the lower the number of generations since admixture, the more accurate were the results. Interestingly, the accuracy of the methods was only marginally affected by i) the number of ancestries (up to six tested); ii) the sample design (i.e., unbalanced representation of source populations); and iii) the reproduction mode (e.g., selfing, vegetative propagation). If a source population was not represented in the data set, no bias was observed in inference accuracy for regions originating from represented sources and regions from the missing source were assigned differently depending on the methods. Overall, the selected ancestry inference methods may be used for crop plant analysis if all ancestral sources are known.

Mots-clés libres : Local ancestry inference, Crops, Admixture, Simulation analysis

Classification Agris : F30 - Plant genetics and breeding

Champ stratégique Cirad : CTS 1 (2019-) - Biodiversité

Auteurs et affiliations

  • Cottin Aurélien, CIRAD-BIOS-UMR AGAP (FRA) - auteur correspondant
  • Penaud Benjamin, Université de Montpellier (FRA)
  • Glaszmann Jean-Christophe, CIRAD-BIOS-UMR AGAP (FRA) ORCID: 0000-0001-9918-875X
  • Yahiaoui Nabila, CIRAD-BIOS-UMR AGAP (FRA)
  • Gautier Mathieu, INRAE (FRA) - auteur correspondant

Source : Cirad-Agritrop (

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