首页|Genomic selection methods for crop improvement:Current status and prospects

Genomic selection methods for crop improvement:Current status and prospects

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With marker and phenotype information from observed populations, genomic selection (GS) can be used to establish associations between markers and phenotypes. It aims to use genome-wide markers to estimate the effects of all loci and thereby predict the genetic values of untested populations, so as to achieve more comprehensive and reliable selection and to accelerate genetic progress in crop breeding. GS models usually face the problem that the number of markers is much higher than the number of phenotypic observations. To overcome this issue and improve prediction accuracy, many models and algorithms, including GBLUP, Bayes, and machine learning have been employed for GS. As hot issues in GS research, the estimation of non-additive genetic effects and the combined analysis of multiple traits or multiple environments are also important for improving the accuracy of prediction. In recent years, crop breeding has taken advantage of the development of GS. The principles and characteristics of current popular GS methods and research progress in these methods for crop improvement are reviewed in this paper.

Genomic selectionPredictionAccuracyCrop

Xin Wang、Yang Xu、Zhongli Hu、Chenwu Xu

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Jiangsu Provincial Key Laboratory of Crop Genetics and Physiology/Co-Innovation Center for Modern Production Technology of Grain Crops/Key Laboratory of Plant Functional Genomics of Ministry of Education, Yangzhou University, Yangzhou 225009, Jiangsu, China

College of Information Engineering, Yangzhou University, Yangzhou 225009, Jiangsu, China

State Key Laboratory of Hybrid Rice, College of Life Sciences, Wuhan University, Wuhan 430072, Hubei, China

National High Technology Research and Development Program of ChinaNational Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaNatural Science Foundations of Jiangsu ProvinceNatural Science Foundation of the Jiangsu Higher Education InstitutionsOpen Research Fund of State Key Laboratory of Hybrid Rice (Wuhan University)Science and Technology Innovation Fund Project in Yangzhou UniversityPriority Academic Program Development of Jiangsu Higher Education Institutions and the Innovative Research Team of Universit

2014AA10A601-52016YFD010030391535103BK2015001014KJA210005KF2017012016CXJ021

2018

作物学报(英文版)

作物学报(英文版)

CSCD
ISSN：
年,卷(期)：2018.6(4)
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