Genetic control of seed proteins in wheat

Maternal effects influencing DNA endoreduplication in developing endosperm of Zea mays

A large proportion of the nuclei in developing endosperm of Zea mays L. undergoes endoreduplication. Nuclear preparations of the entire endosperm from maize kernels of inbred lines, their reciprocal hybrids, and in some cases, F2 and F3 endosperm tissue were evaluated using flow cytometry. Data relative to DNA endoreduplication patterns, percentage of nuclei undergoing endoreduplication, and mean DNA content per nucleus were obtained. The patterns of endoreduplication and extent of DNA amplification differ among some inbreds. In all experiments, the endoreduplication patterns show that the F1 endosperm is more similar to the maternal parent than to the paternal parent. F2 endosperms reveal little difference in endoreduplication patterns among individuals within an F2 family and no more variation than the F1 endosperms. In contrast, F3 endosperms showed greater variation among their endoreduplication patterns. These results indicate a maternal effect on endoreduplication; that is, the genotype of the maternal parent's nuclear genome exerts control over the endoreduplication activities of endosperm tissue.Key words: endosperm, endoreduplication, maternal effect, flow cytometry, Zea mays L.

Analysis of cytoplasmic and maternal effects. II. Genetic models for triploid endosperms

Genetic models for quantitative traits of triploid endosperms are proposed for the analysis of direct gene effects, cytoplasmic effects, and maternal gene effects. The maternal effect is partitioned into maternal additive and dominance components. In the full genetic model, the direct effect is partitioned into direct additive and dominance components and high-order dominance component, which are the cumulative effects of three-allele interactions. If the high-order dominance effects are of no importance, a reduced genetic model can be used. Monte Carlo simulations were conducted in this study for demonstrating unbiasedness of estimated variance and covariance components from the MINQUE (0/1) procedure, which is a minimum norm quadratic unbiased estimation (MINQUE) method setting 0 for all the prior covariances and 1 for all the prior variances. Robustness of estimating variance and covariance components for the genetic models was tested by simulations. Both full and reduced genetic models are shown to be robust for estimating variance and covariance components under several situations of no specific effects. Efficiency of predicting random genetic effects for the genetic models by the MINQUE (0/1) procedure was compared with the best linear unbiased prediction (BLUP). A worked example is given to illustrate the use of the reduced genetic model for kernel growth characteristics in corn (Zea mays L.).