Zhang Li, Yang Mark C K, Wang Xuelu, Larkins Brian A, Gallo-Meagher Maria, Wu Rongling
Department of Statistics, University of Florida, Gainesville, Florida 32611, USA.
Physiol Genomics. 2004 Nov 17;19(3):262-9. doi: 10.1152/physiolgenomics.00052.2004.
We present a statistical model for testing and estimating the effects of maternal-offspring genome interaction on the embryo and endosperm traits during seed development in autogamous plants. Our model is constructed within the context of maximum likelihood implemented with the EM algorithm. Extensive simulations were performed to investigate the statistical properties of our approach. We have successfully identified a quantitative trait locus that exerts a significant maternal-offspring interaction effect on amino acid contents of the endosperm in maize, demonstrating the power of our approach. This approach will be broadly useful in mapping endosperm traits for many agriculturally important crop plants and also make it possible to study the genetic significance of double fertilization in the evolution of higher plants.
我们提出了一个统计模型，用于测试和估计自花授粉植物种子发育过程中母体-子代基因组相互作用对胚和胚乳性状的影响。我们的模型是在通过期望最大化（EM）算法实现的最大似然框架内构建的。我们进行了大量模拟以研究我们方法的统计特性。我们成功鉴定出一个数量性状基因座，它对玉米胚乳的氨基酸含量具有显著的母体-子代相互作用效应，证明了我们方法的有效性。这种方法在绘制许多农业重要作物的胚乳性状图谱方面将具有广泛的用途，并且还使得研究双受精在高等植物进化中的遗传意义成为可能。
