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Genomic selection to improve husk tightness based on genomic molecular markers in maize

INTRODUCTION: The husk tightness (HTI) in maize plays a crucial role in regulating the water content of ears during the maturity stage, thereby influencing the quality of mechanical grain harvesting in China. Genomic selection (GS), which employs molecular markers, offers a promising approach for id...

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Autores principales: Liu, Yuncan, Ao, Man, Lu, Ming, Zheng, Shubo, Zhu, Fangbo, Ruan, Yanye, Guan, Yixin, Zhang, Ao, Cui, Zhenhai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10566295/
https://www.ncbi.nlm.nih.gov/pubmed/37828926
http://dx.doi.org/10.3389/fpls.2023.1252298
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author Liu, Yuncan
Ao, Man
Lu, Ming
Zheng, Shubo
Zhu, Fangbo
Ruan, Yanye
Guan, Yixin
Zhang, Ao
Cui, Zhenhai
author_facet Liu, Yuncan
Ao, Man
Lu, Ming
Zheng, Shubo
Zhu, Fangbo
Ruan, Yanye
Guan, Yixin
Zhang, Ao
Cui, Zhenhai
author_sort Liu, Yuncan
collection PubMed
description INTRODUCTION: The husk tightness (HTI) in maize plays a crucial role in regulating the water content of ears during the maturity stage, thereby influencing the quality of mechanical grain harvesting in China. Genomic selection (GS), which employs molecular markers, offers a promising approach for identifying and selecting inbred lines with the desired HTI trait in maize breeding. However, the effectiveness of GS is contingent upon various factors, including the genetic architecture of breeding populations, sequencing platforms, and statistical models. METHODS: An association panel of maize inbred lines was grown across three sites over two years, divided into four subgroups. GS analysis for HTI prediction was performed using marker data from three sequencing platforms and six marker densities with six statistical methods. RESULTS: The findings indicate that a loosely attached husk can aid in the dissipation of water from kernels in temperate maize germplasms across most environments but not nessarily for tropical-origin maize. Considering the balance between GS prediction accuracy and breeding cost, the optimal prediction strategy is the rrBLUP model, the 50K sequencing platform, a 30% proportion of the test population, and a marker density of r2=0.1. Additionally, selecting a specific SS subgroup for sampling the testing set significantly enhances the predictive capacity for husk tightness. DISCUSSION: The determination of the optimal GS prediction strategy for HTI provides an economically feasible reference for the practice of molecular breeding. It also serves as a reference method for GS breeding of other agronomic traits.
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spelling pubmed-105662952023-10-12 Genomic selection to improve husk tightness based on genomic molecular markers in maize Liu, Yuncan Ao, Man Lu, Ming Zheng, Shubo Zhu, Fangbo Ruan, Yanye Guan, Yixin Zhang, Ao Cui, Zhenhai Front Plant Sci Plant Science INTRODUCTION: The husk tightness (HTI) in maize plays a crucial role in regulating the water content of ears during the maturity stage, thereby influencing the quality of mechanical grain harvesting in China. Genomic selection (GS), which employs molecular markers, offers a promising approach for identifying and selecting inbred lines with the desired HTI trait in maize breeding. However, the effectiveness of GS is contingent upon various factors, including the genetic architecture of breeding populations, sequencing platforms, and statistical models. METHODS: An association panel of maize inbred lines was grown across three sites over two years, divided into four subgroups. GS analysis for HTI prediction was performed using marker data from three sequencing platforms and six marker densities with six statistical methods. RESULTS: The findings indicate that a loosely attached husk can aid in the dissipation of water from kernels in temperate maize germplasms across most environments but not nessarily for tropical-origin maize. Considering the balance between GS prediction accuracy and breeding cost, the optimal prediction strategy is the rrBLUP model, the 50K sequencing platform, a 30% proportion of the test population, and a marker density of r2=0.1. Additionally, selecting a specific SS subgroup for sampling the testing set significantly enhances the predictive capacity for husk tightness. DISCUSSION: The determination of the optimal GS prediction strategy for HTI provides an economically feasible reference for the practice of molecular breeding. It also serves as a reference method for GS breeding of other agronomic traits. Frontiers Media S.A. 2023-09-26 /pmc/articles/PMC10566295/ /pubmed/37828926 http://dx.doi.org/10.3389/fpls.2023.1252298 Text en Copyright © 2023 Liu, Ao, Lu, Zheng, Zhu, Ruan, Guan, Zhang and Cui https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Liu, Yuncan
Ao, Man
Lu, Ming
Zheng, Shubo
Zhu, Fangbo
Ruan, Yanye
Guan, Yixin
Zhang, Ao
Cui, Zhenhai
Genomic selection to improve husk tightness based on genomic molecular markers in maize
title Genomic selection to improve husk tightness based on genomic molecular markers in maize
title_full Genomic selection to improve husk tightness based on genomic molecular markers in maize
title_fullStr Genomic selection to improve husk tightness based on genomic molecular markers in maize
title_full_unstemmed Genomic selection to improve husk tightness based on genomic molecular markers in maize
title_short Genomic selection to improve husk tightness based on genomic molecular markers in maize
title_sort genomic selection to improve husk tightness based on genomic molecular markers in maize
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10566295/
https://www.ncbi.nlm.nih.gov/pubmed/37828926
http://dx.doi.org/10.3389/fpls.2023.1252298
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