Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance

Genomic selection (GS) is a powerful tool for improving genetic gain in maize breeding. However, its routine application in large-scale breeding pipelines is limited by the high cost of genotyping platforms. Although sequencing-based and array-based genotyping platforms have been used for GS, few st...

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Main Authors: Yu, Guangning, Cui, Yanru, Jiao, Yuxin, Zhou, Kai, Xin Wang, Yang, Wenyan, Xu, Yiyi, Yang, Kun, Zhang, Xuecai, Pengcheng Li, Zefeng Yang, Yang Xu, Chenwu Xu
Format: Journal Article
Language:Inglés
Published: Elsevier 2023
Subjects:
Online Access:https://hdl.handle.net/10568/126559
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author Yu, Guangning
Cui, Yanru
Jiao, Yuxin
Zhou, Kai
Xin Wang
Yang, Wenyan
Xu, Yiyi
Yang, Kun
Zhang, Xuecai
Pengcheng Li
Zefeng Yang
Yang Xu
Chenwu Xu
author_browse Chenwu Xu
Cui, Yanru
Jiao, Yuxin
Pengcheng Li
Xin Wang
Xu, Yiyi
Yang Xu
Yang, Kun
Yang, Wenyan
Yu, Guangning
Zefeng Yang
Zhang, Xuecai
Zhou, Kai
author_facet Yu, Guangning
Cui, Yanru
Jiao, Yuxin
Zhou, Kai
Xin Wang
Yang, Wenyan
Xu, Yiyi
Yang, Kun
Zhang, Xuecai
Pengcheng Li
Zefeng Yang
Yang Xu
Chenwu Xu
author_sort Yu, Guangning
collection Repository of Agricultural Research Outputs (CGSpace)
description Genomic selection (GS) is a powerful tool for improving genetic gain in maize breeding. However, its routine application in large-scale breeding pipelines is limited by the high cost of genotyping platforms. Although sequencing-based and array-based genotyping platforms have been used for GS, few studies have compared prediction performance among platforms. In this study, we evaluated the predictabilities of four agronomic traits in 305 maize hybrids derived from 149 parental lines subjected to genotyping by sequencing (GBS), a 40K SNP array, and target sequence capture (TSC) using eight GS models. The GBS marker dataset yielded the highest predictabilities for all traits, followed by TSC and SNP array datasets. We investigated the effect of marker density and statistical models on predictability among genotyping platforms and found that 1K SNPs were sufficient to achieve comparable predictabilities to 10K and all SNPs, and BayesB, GBLUP, and RKHS performed well, while XGBoost performed poorly in most cases. We also selected significant SNP subsets using genome-wide association study (GWAS) analyses in three panels to predict hybrid performance. GWAS facilitated selecting effective SNP subsets for GS and thus reduced genotyping cost, but depended heavily on the GWAS panel. We conclude that there is still room for optimization of the existing SNP array, and using genotyping by target sequencing (GBTS) techniques to integrate a few functional markers identified by GWAS into the 1K SNP array holds great promise of being an effective strategy for developing desirable GS breeding arrays.
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spelling CGSpace1265592025-11-06T13:05:07Z Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance Yu, Guangning Cui, Yanru Jiao, Yuxin Zhou, Kai Xin Wang Yang, Wenyan Xu, Yiyi Yang, Kun Zhang, Xuecai Pengcheng Li Zefeng Yang Yang Xu Chenwu Xu marker-assisted selection maize single nucleotide polymorphism hybrids Genomic selection (GS) is a powerful tool for improving genetic gain in maize breeding. However, its routine application in large-scale breeding pipelines is limited by the high cost of genotyping platforms. Although sequencing-based and array-based genotyping platforms have been used for GS, few studies have compared prediction performance among platforms. In this study, we evaluated the predictabilities of four agronomic traits in 305 maize hybrids derived from 149 parental lines subjected to genotyping by sequencing (GBS), a 40K SNP array, and target sequence capture (TSC) using eight GS models. The GBS marker dataset yielded the highest predictabilities for all traits, followed by TSC and SNP array datasets. We investigated the effect of marker density and statistical models on predictability among genotyping platforms and found that 1K SNPs were sufficient to achieve comparable predictabilities to 10K and all SNPs, and BayesB, GBLUP, and RKHS performed well, while XGBoost performed poorly in most cases. We also selected significant SNP subsets using genome-wide association study (GWAS) analyses in three panels to predict hybrid performance. GWAS facilitated selecting effective SNP subsets for GS and thus reduced genotyping cost, but depended heavily on the GWAS panel. We conclude that there is still room for optimization of the existing SNP array, and using genotyping by target sequencing (GBTS) techniques to integrate a few functional markers identified by GWAS into the 1K SNP array holds great promise of being an effective strategy for developing desirable GS breeding arrays. 2023-04 2023-01-04T13:06:32Z 2023-01-04T13:06:32Z Journal Article https://hdl.handle.net/10568/126559 en Open Access application/pdf Elsevier Yu, G., Cui, Y., Jiao, Y., Zhou, K., Wang, X., Yang, W., Xu, Y., Yang, K., Zhang, X., Li, P., Yang, Z., Xu, Y., & Xu, C. (2023). Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance. The Crop Journal, 11(2), 490–498. https://doi.org/10.1016/j.cj.2022.09.004
spellingShingle marker-assisted selection
maize
single nucleotide polymorphism
hybrids
Yu, Guangning
Cui, Yanru
Jiao, Yuxin
Zhou, Kai
Xin Wang
Yang, Wenyan
Xu, Yiyi
Yang, Kun
Zhang, Xuecai
Pengcheng Li
Zefeng Yang
Yang Xu
Chenwu Xu
Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance
title Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance
title_full Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance
title_fullStr Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance
title_full_unstemmed Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance
title_short Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance
title_sort comparison of sequencing based and array based genotyping platforms for genomic prediction of maize hybrid performance
topic marker-assisted selection
maize
single nucleotide polymorphism
hybrids
url https://hdl.handle.net/10568/126559
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