Ridge Regression and Extensions for Genomewide Selection in Maize

被引:208
作者
Piepho, H. P. [1 ]
机构
[1] Univ Hohenheim, Inst Crop Prod & Grassland Sci, D-70599 Stuttgart, Germany
关键词
LINEAR UNBIASED PREDICTION; QUANTITATIVE TRAITS; BREEDING VALUES; GENETIC VALUE; MIXED MODELS; PERFORMANCE; INFORMATION; ACCURACY; MARKERS; BLUP;
D O I
10.2135/cropsci2008.10.0595
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
This paper reviews properties of ridge regression for genomewide (genomic) selection and establishes close relationships with other methods to model genetic correlation among relatives, including use of a kinship matrix and the simple matching coefficient as computed from marker data. A number of alternative models are then proposed exploiting ties between genetic correlation based on marker data and geostatistical concepts. A simple method for automatic marker selection is proposed. The methods are exemplified using a series of experiments with test-cross hybrids of maize (Zea mays L.) conducted in five environments. Results underline the need to appropriately model genotype-environment interaction and to employ an independent estimate of error. It is also shown that accounting for genetic effects not captured by markers may be important.
引用
收藏
页码:1165 / 1176
页数:12
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