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New insights into trait introgression with the look-ahead intercrossing strategy
Trait introgression (TI) can be a time-consuming and costly task that typically requires multiple generations of backcrossing (BC). Usually, the aim is to introduce one or more alleles (e.g. QTLs) from a single donor into an elite recipient, both of which are fully inbred. This article studies the p...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10085795/ https://www.ncbi.nlm.nih.gov/pubmed/36821776 http://dx.doi.org/10.1093/g3journal/jkad042 |
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author | Ni, Zheng Moeinizade, Saba Kusmec, Aaron Hu, Guiping Wang, Lizhi Schnable, Patrick S |
author_facet | Ni, Zheng Moeinizade, Saba Kusmec, Aaron Hu, Guiping Wang, Lizhi Schnable, Patrick S |
author_sort | Ni, Zheng |
collection | PubMed |
description | Trait introgression (TI) can be a time-consuming and costly task that typically requires multiple generations of backcrossing (BC). Usually, the aim is to introduce one or more alleles (e.g. QTLs) from a single donor into an elite recipient, both of which are fully inbred. This article studies the potential advantages of incorporating intercrossing (IC) into TI programs when compared with relying solely on the traditional BC framework. We simulate a TI breeding pipeline using 3 previously proposed selection strategies for the traditional BC scheme and 3 modified strategies that allow IC. Our proposed look-ahead intercrossing method (LAS-IC) combines look-ahead Monte Carlo simulations, intercrossing, and additional selection criteria to improve computational efficiency. We compared the efficiency of the 6 strategies across 5 levels of resource availability considering the generation when the major QTLs have been successfully introduced into the recipient and a desired background recovery rate reached. Simulations demonstrate that the inclusion of intercrossing in a TI program can substantially increase efficiency and the probability of success. The proposed LAS-IC provides the highest probability of success across the different scenarios using fewer resources compared with BC-only strategies. |
format | Online Article Text |
id | pubmed-10085795 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-100857952023-04-12 New insights into trait introgression with the look-ahead intercrossing strategy Ni, Zheng Moeinizade, Saba Kusmec, Aaron Hu, Guiping Wang, Lizhi Schnable, Patrick S G3 (Bethesda) Investigation Trait introgression (TI) can be a time-consuming and costly task that typically requires multiple generations of backcrossing (BC). Usually, the aim is to introduce one or more alleles (e.g. QTLs) from a single donor into an elite recipient, both of which are fully inbred. This article studies the potential advantages of incorporating intercrossing (IC) into TI programs when compared with relying solely on the traditional BC framework. We simulate a TI breeding pipeline using 3 previously proposed selection strategies for the traditional BC scheme and 3 modified strategies that allow IC. Our proposed look-ahead intercrossing method (LAS-IC) combines look-ahead Monte Carlo simulations, intercrossing, and additional selection criteria to improve computational efficiency. We compared the efficiency of the 6 strategies across 5 levels of resource availability considering the generation when the major QTLs have been successfully introduced into the recipient and a desired background recovery rate reached. Simulations demonstrate that the inclusion of intercrossing in a TI program can substantially increase efficiency and the probability of success. The proposed LAS-IC provides the highest probability of success across the different scenarios using fewer resources compared with BC-only strategies. Oxford University Press 2023-02-23 /pmc/articles/PMC10085795/ /pubmed/36821776 http://dx.doi.org/10.1093/g3journal/jkad042 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of the Genetics Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Investigation Ni, Zheng Moeinizade, Saba Kusmec, Aaron Hu, Guiping Wang, Lizhi Schnable, Patrick S New insights into trait introgression with the look-ahead intercrossing strategy |
title | New insights into trait introgression with the look-ahead intercrossing strategy |
title_full | New insights into trait introgression with the look-ahead intercrossing strategy |
title_fullStr | New insights into trait introgression with the look-ahead intercrossing strategy |
title_full_unstemmed | New insights into trait introgression with the look-ahead intercrossing strategy |
title_short | New insights into trait introgression with the look-ahead intercrossing strategy |
title_sort | new insights into trait introgression with the look-ahead intercrossing strategy |
topic | Investigation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10085795/ https://www.ncbi.nlm.nih.gov/pubmed/36821776 http://dx.doi.org/10.1093/g3journal/jkad042 |
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