Predicting Genetic Variance from Genomewide Marker Effects Estimated from a Diverse Panel of Maize Inbreds

Abstract

Predicting the genetic variance (VG) in a biparental population has been difficult. Our objective was to determine whether the population mean, VG, and mean of the top 10% of progeny in a cross can be predicted effectively from genomewide marker effects estimated from a diverse panel of inbreds. Eight maize (Zea mays L.) crosses that differed in their predicted mean and VG were evaluated for plant and ear height and growing degree days to silking. Each cross was represented by 120 to 144 random F3 lines that were evaluated in balanced experiments at three locations in Minnesota in 2017. Correlations between the observed and predicted means of each breeding population were significant (r ≥ 0.80, P = 0.05) for all three traits. However, correlations between the observed and predicted VG were nonsignificant (−0.24 to 0.14) for the three traits. Correlations between the observed and predicted mean of the top 10% of progeny in each cross were significant (P = 0.05) for plant height (0.72), but not for ear height and silking date. These results for predicting the mean of the top 10% of progeny reflected the ability to predict the mean but not VG. We concluded that the mean, but not the VG, of biparental crosses can be effectively predicted from genomewide marker effects estimated from a diverse panel of inbreds.