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玉米种质改良项目的基因组预测

Genomic prediction for the Germplasm Enhancement of Maize project.

作者信息

Rogers Anna R, Bian Yang, Krakowsky Matthew, Peters David, Turnbull Clint, Nelson Paul, Holland James B

机构信息

Program in Genetics, North Carolina State Univ., Raleigh, NC, 27695, USA.

Bayer Crop Science, 700 Chesterfield Pkwy W, Chesterfield, MO, 63017, USA.

出版信息

Plant Genome. 2022 Dec;15(4):e20267. doi: 10.1002/tpg2.20267. Epub 2022 Oct 24.

Abstract

The Germplasm Enhancement of Maize (GEM) project was initiated in 1993 as a cooperative effort of public- and private-sector maize (Zea mays L.) breeders to enhance the genetic diversity of the U.S. maize crop. The GEM project selects progeny lines with high topcross yield potential from crosses between elite temperate lines and exotic parents. The GEM project has released hundreds of useful breeding lines based on phenotypic selection within selfing generations and multienvironment yield evaluations of GEM line topcrosses to elite adapted testers. Developing genomic selection (GS) models for the GEM project may contribute to increases in the rate of genetic gain. Here we evaluated the prediction ability of GS models trained on 6 yr of topcross evaluations from the two GEM programs in Raleigh, NC, and Ames, IA, documenting prediction abilities ranging from 0.36 to 0.75 for grain yield and from 0.78 to 0.96 for grain moisture when models were cross-validated within program and heterotic group. Predicted genetic gain from GS ranged from 0.95 to 2.58 times the gain from phenotypic selection. Prediction ability across program and heterotic group was generally poorer than within groups. Based on observed genomic relationships between GEM breeding lines and their tropical ancestors, GS for either yield or moisture would reduce recovery of exotic germplasm only slightly. Using GS models trained within program, the GEM programs should be able to more effectively deliver on its mission to broaden the genetic base of U.S. germplasm.

摘要

玉米种质资源改良(GEM)项目始于1993年,是公共部门和私营部门玉米(Zea mays L.)育种者的一项合作努力,旨在提高美国玉米作物的遗传多样性。GEM项目从优良温带系与外来亲本的杂交后代中选择具有高顶交产量潜力的后代系。GEM项目基于自交世代内的表型选择以及GEM系顶交与优良适应性测试系的多环境产量评估,已发布了数百个有用的育种系。为GEM项目开发基因组选择(GS)模型可能有助于提高遗传增益率。在此,我们评估了基于北卡罗来纳州罗利市和爱荷华州艾姆斯市两个GEM项目6年顶交评估数据训练的GS模型的预测能力,结果表明,当模型在项目和杂种优势群内进行交叉验证时,籽粒产量的预测能力范围为0.36至0.75,籽粒含水量的预测能力范围为0.78至0.96。GS预测的遗传增益是表型选择增益的0.95至2.58倍。跨项目和杂种优势群的预测能力通常比群内的要差。基于观察到的GEM育种系与其热带祖先之间的基因组关系,无论是产量还是含水量的GS只会略微降低外来种质的恢复率。使用在项目内训练的GS模型,GEM项目应该能够更有效地实现其拓宽美国种质遗传基础的使命。

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