论数量性状遗传的双多因素与三正态分布

On Dual Multiple Factors and Three Normal Distributions of the Inheritance of Quantitative Characters

摘要: 本文讨论了以Nilsson-Ehle小麦杂交实验为基础的多基因假说的不足，提出了数量性状遗传的双多因素与三正态分布理论。小麦粒色属果皮遗传。Nilsson-Ehle小麦杂交实验，F1籽粒为老红色，F2籽粒为同一中红色，F3籽粒由白色到最红色，发生分离，呈二项分布，是离散型分布。这是3对基因积加作用的结果。依据该实验建立的多基因假说解决不了数量性状的连续性问题。数量性状不是1-几个单位性状，是许多单位性状的集合，涉及相当多位点性质不同的基因。小生境环境效应是许多因子综合作用的结果。在随机交配的孟德尔群体中，各基因位点贡献相互独立，各环境因子贡献相互独立，而且二者相互独立，按李雅普诺夫中心极限定理，基因型值G、小生境环境效应E和表现型P = G + E呈3正态分布，数量性状表现连续性变异。

Abstract: In this paper, the shortages of polygenic hypothesis based on Nilsson-Ehl’e hybridization experi-ment in wheat were discussed, and the theory of dual multiple factors and three normal distribu-tions of the inheritance of quantitative characters was put forward. The grain colors in wheat be-longed to the pericarp inheritance. In Nilsson-Ehle’s hybridization experiment in wheat, F1 grains were old red, F2 grains were uniformly medium red, and F3 grains were various shades of red and white representing segregation and the binomial distribution. These are the consequence of the inheritance of the additive effect of 3 gene pairs. Mathematically, this distribution is not continuous, but discrete. So the polygenic hypothesis based on this experiment did not solve the continuous variation in the inheritance of quantitative characters. Quantitative trait is often not a single unite character or several unite characters, but is a set of many unite characters. It involves numerous genes at fairly many loci. The environmental effect in a niche is a result of the combined action of many factors. In a Mendelian population for individuals to randomly mate, the contribution of every gene locus is independent, the contribution of every environmental factor in a niche is independent, and the two are independent of each other. According to Lyapunov central limit theorem, genotypic value G is submitted to the normal distribution, the environmental effect E in a niche is submitted to the normal distribution, and phenotype P = G + E is also submitted to the normal distribution. The quantitative characters present continuous variation.