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Simulation-Based Evaluation of Three Methods for Local Ancestry Deconvolution of Non-model Crop Species Genomes
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 mainl...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Genetics Society of America
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003078/ https://www.ncbi.nlm.nih.gov/pubmed/31862786 http://dx.doi.org/10.1534/g3.119.400873 |
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author | Cottin, Aurélien Penaud, Benjamin Glaszmann, Jean-Christophe Yahiaoui, Nabila Gautier, Mathieu |
author_facet | Cottin, Aurélien Penaud, Benjamin Glaszmann, Jean-Christophe Yahiaoui, Nabila Gautier, Mathieu |
author_sort | Cottin, Aurélien |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7003078 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Genetics Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-70030782020-02-14 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 G3 (Bethesda) Investigations 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. Genetics Society of America 2019-12-20 /pmc/articles/PMC7003078/ /pubmed/31862786 http://dx.doi.org/10.1534/g3.119.400873 Text en Copyright © 2020 Cottin et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Investigations Cottin, Aurélien Penaud, Benjamin Glaszmann, Jean-Christophe Yahiaoui, Nabila Gautier, Mathieu Simulation-Based Evaluation of Three Methods for Local Ancestry Deconvolution of Non-model Crop Species Genomes |
title | Simulation-Based Evaluation of Three Methods for Local Ancestry Deconvolution of Non-model Crop Species Genomes |
title_full | Simulation-Based Evaluation of Three Methods for Local Ancestry Deconvolution of Non-model Crop Species Genomes |
title_fullStr | Simulation-Based Evaluation of Three Methods for Local Ancestry Deconvolution of Non-model Crop Species Genomes |
title_full_unstemmed | Simulation-Based Evaluation of Three Methods for Local Ancestry Deconvolution of Non-model Crop Species Genomes |
title_short | Simulation-Based Evaluation of Three Methods for Local Ancestry Deconvolution of Non-model Crop Species Genomes |
title_sort | simulation-based evaluation of three methods for local ancestry deconvolution of non-model crop species genomes |
topic | Investigations |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7003078/ https://www.ncbi.nlm.nih.gov/pubmed/31862786 http://dx.doi.org/10.1534/g3.119.400873 |
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