北方统一大豆试验的基因组分析和预测模型

IF 1.9 3区 农林科学 Q2 AGRONOMY
Crop Science Pub Date : 2025-08-29 DOI:10.1002/csc2.70138
Cleiton A. Wartha, Benjamin W. Campbell, Vishnu Ramasubramanian, Liana Nice, Adam Brock, Guohong Cai, M. Milad Eskandari, George Graef, Mathew E. Hudson, David Hyten, Adam L. Mahan, Nicolas F. Martin, Leah McHale, Carrie Miranda, Eliana Monteverde Dominguez, Rex Nelson, Katy Rainey, Istvan Rajcan, Andrew Scaboo, William Schapaugh, Asheesh K. Singh, João Paolo Gomes, Dechun Wang, Aaron J. Lorenz
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引用次数: 0

摘要

北方统一大豆试验(NUST)是由美国农业部协调的一个区域田间试验网络,用于评估公共机构开发的试验大豆(甘氨酸max L.)菌株。NUST编辑、整理和报告的历史数据包括一个有价值的多环境试验数据集,包括28年来在199个地点,总计1652个环境中评估的从成熟组00到成熟组IV的相关优质大豆种质。我们的目的是表征NUST实验菌株的遗传结构,使用历史表型数据进行全基因组关联研究,并评估这些历史数据对基因组预测模型训练的有用性。采用BARCSoySNP6K法收集了2544株NUST实验菌株的分子标记信息。在10号染色体上靠近已知大豆成熟基因E2的区域,早熟组和晚熟组之间的固定指数值较高。我们没有发现来自不同育种计划的菌株之间存在很强的遗传差异,这反映了公共项目之间的种质共享。对重要农艺性状的全基因组关联分析发现了标记-性状关联,其中许多与文献中报道的数量性状位点重叠。使用NUST历史数据训练的基因组预测模型在大多数情况下产生了中等到高的预测能力,这表明这些数据可以对训练集做出有用的贡献。我们已经公开了这些数据,作为其他人研究优质公共大豆种质中基因型-表型关系的数据资源,并为基因组学辅助育种的推进和实施开发预测模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Genomic analysis and predictive modeling in the Northern Uniform Soybean Tests

Genomic analysis and predictive modeling in the Northern Uniform Soybean Tests

Genomic analysis and predictive modeling in the Northern Uniform Soybean Tests

Genomic analysis and predictive modeling in the Northern Uniform Soybean Tests

Genomic analysis and predictive modeling in the Northern Uniform Soybean Tests

The Northern Uniform Soybean Tests (NUST) are a regional field trial network coordinated by the United States Department of Agriculture to evaluate experimental soybean (Glycine max L.) strains developed by public institutions. Historical data from the NUST compiled, curated, and reported herein comprise a valuable multi-environment trial dataset including relevant elite soybean germplasm from maturity groups 00 to IV evaluated over 28 years in 199 locations, totaling 1652 environments. Our aim was to characterize the genetic structure of the NUST experimental strains, perform genome-wide association studies using historical phenotypic data, and assess the usefulness of these historical data for genomic prediction model training. Molecular marker information was collected on 2544 unique NUST experimental strains using the BARCSoySNP6K assay. High fixation index values between early and later maturity groups were observed in a region on chromosome 10 near the known soybean maturity gene E2. We failed to find strong genetic divergence between strains from different breeding programs, reflecting the germplasm sharing common among public programs. Genome-wide association analyses on important agronomic traits identified marker-trait associations, many of which overlap with quantitative trait loci previously reported in the literature. Genomic prediction models trained using the historical NUST data produced moderate to high predictive abilities in most cases, suggesting these data could make useful contributions to training sets. We have made these data publicly available as a data resource for others to study genotype–phenotype relationships within elite public soybean germplasm and develop predictive models for advancement and implementation of genomics-assisted breeding.

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来源期刊
Crop Science
Crop Science 农林科学-农艺学
CiteScore
4.50
自引率
8.70%
发文量
197
审稿时长
3 months
期刊介绍: Articles in Crop Science are of interest to researchers, policy makers, educators, and practitioners. The scope of articles in Crop Science includes crop breeding and genetics; crop physiology and metabolism; crop ecology, production, and management; seed physiology, production, and technology; turfgrass science; forage and grazing land ecology and management; genomics, molecular genetics, and biotechnology; germplasm collections and their use; and biomedical, health beneficial, and nutritionally enhanced plants. Crop Science publishes thematic collections of articles across its scope and includes topical Review and Interpretation, and Perspectives articles.
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