A look-ahead Monte Carlo simulation method for improving parental selection in trait introgression

Abstract Multiple trait introgression is the process by which multiple desirable traits are converted from a donor to a recipient cultivar through backcrossing and selfing. The goal of this procedure is to recover all the attributes of the recipient cultivar, with the addition of the specified desir...

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Autores principales:	Saba Moeinizade, Ye Han, Hieu Pham, Guiping Hu, Lizhi Wang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a5ab6b13dbad4ad99f6fa2295050143e
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id	oai:doaj.org-article:a5ab6b13dbad4ad99f6fa2295050143e
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spelling	oai:doaj.org-article:a5ab6b13dbad4ad99f6fa2295050143e2021-12-02T14:21:53ZA look-ahead Monte Carlo simulation method for improving parental selection in trait introgression10.1038/s41598-021-83634-x2045-2322https://doaj.org/article/a5ab6b13dbad4ad99f6fa2295050143e2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83634-xhttps://doaj.org/toc/2045-2322Abstract Multiple trait introgression is the process by which multiple desirable traits are converted from a donor to a recipient cultivar through backcrossing and selfing. The goal of this procedure is to recover all the attributes of the recipient cultivar, with the addition of the specified desirable traits. A crucial step in this process is the selection of parents to form new crosses. In this study, we propose a new selection approach that estimates the genetic distribution of the progeny of backcrosses after multiple generations using information of recombination events. Our objective is to select the most promising individuals for further backcrossing or selfing. To demonstrate the effectiveness of the proposed method, a case study has been conducted using maize data where our method is compared with state-of-the-art approaches. Simulation results suggest that the proposed method, look-ahead Monte Carlo, achieves higher probability of success than existing approaches. Our proposed selection method can assist breeders to efficiently design trait introgression projects.Saba MoeinizadeYe HanHieu PhamGuiping HuLizhi WangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Saba Moeinizade Ye Han Hieu Pham Guiping Hu Lizhi Wang A look-ahead Monte Carlo simulation method for improving parental selection in trait introgression
description	Abstract Multiple trait introgression is the process by which multiple desirable traits are converted from a donor to a recipient cultivar through backcrossing and selfing. The goal of this procedure is to recover all the attributes of the recipient cultivar, with the addition of the specified desirable traits. A crucial step in this process is the selection of parents to form new crosses. In this study, we propose a new selection approach that estimates the genetic distribution of the progeny of backcrosses after multiple generations using information of recombination events. Our objective is to select the most promising individuals for further backcrossing or selfing. To demonstrate the effectiveness of the proposed method, a case study has been conducted using maize data where our method is compared with state-of-the-art approaches. Simulation results suggest that the proposed method, look-ahead Monte Carlo, achieves higher probability of success than existing approaches. Our proposed selection method can assist breeders to efficiently design trait introgression projects.
format	article
author	Saba Moeinizade Ye Han Hieu Pham Guiping Hu Lizhi Wang
author_facet	Saba Moeinizade Ye Han Hieu Pham Guiping Hu Lizhi Wang
author_sort	Saba Moeinizade
title	A look-ahead Monte Carlo simulation method for improving parental selection in trait introgression
title_short	A look-ahead Monte Carlo simulation method for improving parental selection in trait introgression
title_full	A look-ahead Monte Carlo simulation method for improving parental selection in trait introgression
title_fullStr	A look-ahead Monte Carlo simulation method for improving parental selection in trait introgression
title_full_unstemmed	A look-ahead Monte Carlo simulation method for improving parental selection in trait introgression
title_sort	look-ahead monte carlo simulation method for improving parental selection in trait introgression
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/a5ab6b13dbad4ad99f6fa2295050143e
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A look-ahead Monte Carlo simulation method for improving parental selection in trait introgression

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