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Genomewide Prediction Accuracy within 969 Maize Biparental Populations
Author(s) -
Lian Lian,
Jacobson Amy,
Zhong Shengqiang,
Bernardo Rex
Publication year - 2014
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci2013.12.0856
Subject(s) - biology , quantitative trait locus , heritability , linkage disequilibrium , population , zoology , locus (genetics) , test weight , poaceae , zea mays , grain yield , genotype , genetics , agronomy , single nucleotide polymorphism , demography , gene , sociology
In genomewide selection, the expected correlation between predicted and true genotypic values ( r MG ) has been previously derived as a function of the training population size ( N ), heritability ( h 2 ), and effective number of chromosome segments ( M e ) affecting the trait. Our objectives were to determine: (i) the mean and variability of r MG in 969 biparental maize ( Zea mays L.) breeding populations for seven traits, (ii) if r MG can be predicted in advance, and (iii) how N , h 2 , and number of markers ( N M ) affect r MG . We modified a previous equation for expected r MG to account for linkage disequilibrium ( r 2 ) between a marker and a quantitative trait locus (QTL). Across the 969 populations, the mean and range (in parentheses) of observed r MG was 0.45 (−0.59, 1.03) for grain yield, 0.59 (−0.34, 0.96) for moisture, 0.55 (−0.24, 1.10) for test weight, 0.49 (−0.22, 1.04) for stalk lodging, 0.41 (−0.30, 0.93) for root lodging, 0.47 (−0.45, 0.97) for plant height, and 0.42 (−0.43, 0.94) for ear height. The observed r MG values were centered around the expected r MG when r 2 was accounted for, but the observed r MG had a large spread around the expected r MG . The r 2 ( Nh 2 ) 1/2 had the strongest association with observed r MG . When r 2 ( Nh 2 ) 1/2 exceeded 8, the proportion of r MG equal to or larger than 0.50 reached 90% among all the population–trait combinations. We conclude it is difficult to predict r MG in advance, but that rules of thumb based on r 2 ( Nh 2 ) 1/2 can help achieve a high r MG .