TY - JOUR
T1 - Prediction of genetic variance in biparental maize populations
T2 - Genomewide marker effects versus mean genetic variance in prior populations
AU - Lian, Lian
AU - Jacobson, Amy
AU - Zhong, Shengqiang
AU - Bernardo, Rex N
N1 - Publisher Copyright:
© Crop Science Society of America.
PY - 2015
Y1 - 2015
N2 - Good methods are lacking for predicting the genetic variance (VG) in biparental populations. Our objective was to determine whether genomewide marker effects and related populations could be used to predict the VG when two parents (A and B) are crossed to form a segregating population. For each of 85 A/B populations, 2 to 23 maize (Zea mays L.) populations with A and B as one of the parents were used as the training population. In the genomewide selection model, the testcross VG in A/B was predicted as the variance among the predicted genotypic values of progeny from a simulated A/B population. In the mean variance model, VG in A/B was predicted as the mean of VG in a series of A/* populations and */B populations, where * denotes a random parent. The correlations between observed and predicted VG were significant (P = 0.05) for both the genomewide selection model (0.18 for yield, 0.49 for moisture, and 0.52 for test weight) and the mean variance model (0.26 for yield, 0.46 for moisture, and 0.50 for test weight). The percentages of bias in estimates of VG were −28 to −60% for the genomewide selection model, but were only −1 to 5% for the mean variance model. Our results indicated that the VG in an A/B population could be predicted as the mean variance among populations with A and B as one of the parents. The mean variance model should be practical in breeding programs because it simply uses phenotypic data from prior, related populations.
AB - Good methods are lacking for predicting the genetic variance (VG) in biparental populations. Our objective was to determine whether genomewide marker effects and related populations could be used to predict the VG when two parents (A and B) are crossed to form a segregating population. For each of 85 A/B populations, 2 to 23 maize (Zea mays L.) populations with A and B as one of the parents were used as the training population. In the genomewide selection model, the testcross VG in A/B was predicted as the variance among the predicted genotypic values of progeny from a simulated A/B population. In the mean variance model, VG in A/B was predicted as the mean of VG in a series of A/* populations and */B populations, where * denotes a random parent. The correlations between observed and predicted VG were significant (P = 0.05) for both the genomewide selection model (0.18 for yield, 0.49 for moisture, and 0.52 for test weight) and the mean variance model (0.26 for yield, 0.46 for moisture, and 0.50 for test weight). The percentages of bias in estimates of VG were −28 to −60% for the genomewide selection model, but were only −1 to 5% for the mean variance model. Our results indicated that the VG in an A/B population could be predicted as the mean variance among populations with A and B as one of the parents. The mean variance model should be practical in breeding programs because it simply uses phenotypic data from prior, related populations.
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U2 - 10.2135/cropsci2014.10.0729
DO - 10.2135/cropsci2014.10.0729
M3 - Article
AN - SCOPUS:84928681071
SN - 0011-183X
VL - 55
SP - 1181
EP - 1188
JO - Crop Science
JF - Crop Science
IS - 3
ER -