Assessment on Evaluating Parameters of Rice Core Collections Constructed by Genotypic Values and Molecular Marker Information

Eleven evaluating parameters for rice core collection were assessed based on genotypic values and molecular marke＇ information. Monte Carlo simulation combined with mixed linear model was used to eliminate the interference from environment in order to draw more reliable results. The coincidence rate of range （CR） was the optimal parameter. Mean Simpson index （MD）, mean Shannon-Weaver index of genetic diversity （M1） and mean polymorphism information content （MPIC） were important evaluating parameters. The variable rate of coefficient of variation （VR） could act as an important reference parameter for evaluating the variation degree of core collection. Percentage of polymorphic loci （p） could be used as a determination parameter for the size of core collection. Mean difference percentage （MD） was a determination parameter for the reliability judgment of core collection. The effective evaluating parameters for core collection selected in the research could be used as criteria for sampling percentage in different plant germplasm populations.

Study on Genetic Diversity of Agronomic Traits and Genetic Relationships among Core Collections of Bitter Gourd

[Objective] This study aimed to investigate the genetic diversity of agronomic traits and genetic relationships among core collections of bitter gourd.[Method] Total 141 germplasms of bitter gourd were selected,and the genetic diversity of 13 agronomic traits was analyzed.In addition,total 46 core collections of bitter gourd were employed,and their genetic relationships were analyzed based on the phenotypic values and genotypic values of 5 agronomic traits,respectively.[Result] The genetic diversity analysis of agronomic traits showed that the genetic diversity indexes of the 4 qualitative traits of bitter gourd germplasms ranged from 0.46 to 1.34;the distribution of the 9 quantitative traits data was more dispersed with average coefficient of variation of 20.02%.The genetic relationship analysis showed that based on the phenotypic values and genotypic values of the 5 quantitative traits,the genetic distances among the 46 core collections of bitter gourd were different.Based on the genotypic values,the genetic distances among the 46 bitter gourd core collections ranged from 0.84 to 10.71.The 46 germplasms were divided into 17 groups with the rescaled distance of 8.5,which further classified the relationships among different germplasms.[Conclusion] This study will lay a solid foundation for the effective utilization of core collections and new variety breeding in bitter gourd.

The Limitations of Polygenic Hypothesis and Theorizing about Dual Multiple Factors and Three Normal Distributions

The original data of Nilsson-Ehle experiment in wheat were analyzed with existent genetic knowledge. It indicated that the core of polygenic hypothesis from this experiment was that a character similarity produced by additive effect of multiple genes was the basis of continuous variation. Its precondition was for effective genes to have equal effect, to show merodominance and binomial distribution and to inherit independently. In fact, quantitative characters were determined by many genes with different property, effect and behavior. So it was difficult to solve all problems of continuous variation by the aid of polygenic hypothesis. The researchers should seek new ways. With Mendelian group as research object and by means of Lyapunov central limit theorem it was proved that both genotypic value G and the environmental effect in a niche E were subordinated to the normal distribution and respectively. According to additivity of the normal distribution the phenotype P = G + E also obeyed the normal distribution P = G + E ~ and quantitative characters showed continuous variation, whether or not the linkage was presented, whether or not every gene effect was equal, whether or not there were dominance and what kind of dominance between alleles. Moreover it was discussed that the quantitative characters in self-fertilized organism and clone were submitted to the normal distribution and presented continuous variation too.

Investigation of Combining Plant Genotypic Values and Molecular Marker Information for Constructing Core Subsets

In the present study, a strategy was proposed for constructing plant core subsets by clusters based on the combination of continuous data for genotypic values and discrete data for molecular marker InformaUon. A mixed linear model approach was used to predict genotyplc values for eliminating the environment effect. The ＂mixed genetic distance＂ was designed to solve the difficult problem of combining continuous and discrete data to construct a core subset by cluster. Four commonly used genetic distances for continuous data （Euclidean distance, standardized Euclidean distance, city block distance, and Mahalanobls distance） were used to assess the validity of the conUnuous data part of the mixed genetic distance; three commonly used genetic distances for discrete data （cosine distance, correlaUon distance, and Jaccard distance） were used to assess the validity of the discrete data part of the mixed genetic distance, A rice germplasm group with eight quantitative traits and information for 60 molecular markers was used to evaluate the validity of the new strategy. The results suggest that the validity of both parts of the mixed geneUc distance are equal to or higher than the common geneUc distance. The core subset constructed on the basis of a combination of data for genotyplc values and molecular marker information was more representative than that constructed on the basis of data from genotypic values or molecular marker informaUon alone. Moreover, the strategy of using combined data was able to treat dominant marker informaUon and could combine any other continuous data and discrete data together to perform cluster to construct a plant core subset.