Two Genetic models (an embryo model and an endosperm model) were proposed for analyzing genetic effects of nuclear genes, cytoplasmic genes, maternal genes, and nuclear–cytoplasmic interaction (NCI) as well as their genotype by environment interaction for quantitative traits of plant seed. In these models, the NCI effects were partitioned into direct additive and dominance NCI components. Mixed linear model approaches were employed for statistical analysis. For both balanced and unbalanced diallel cross designs, Monte Carlo simulations were conducted to evaluate unbiasedness and precision of estimated variance components of these models. The results showed that the proposed methods work well. Random genetic effects were predicted with an adjusted unbiased prediction method. Seed traits (protein content and oil content) of Upland cotton (Gossypium hirsutum L.) were analyzed as worked examples to demonstrate the use of the models.
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This work was supported in part by the 973 project of National Natural Science Foundation of China. We are grateful to Dr. Jannink Jean-Luc and two anonymous reviewers for useful comments and suggestions on the earlier version of the manuscript.
Communicated by J.-L. Jannink.
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Han, L., Xu, H., Zhu, J. et al. Analysis of genetic effects of nuclear–cytoplasmic interaction on quantitative traits: Genetic models for seed traits of plants. Theor Appl Genet 116, 769–776 (2008). https://doi.org/10.1007/s00122-008-0709-3
- Mean Square Error
- Upland Cotton
- Estimate Variance Component
- Seed Trait
- Mixed Linear Model Approach