**7. Discussion and prospect**

Rice feeds more than 50% of the world's population and is one of the most important crops in the world. Rice germplasm resource is the primary material for rice breeding and makes a concrete contribution to global wealth creation and food security. Therefore, understanding its valuable genetic diversity and using it in rice genetic improvement is of importance for raising rice yield and the resistance to biotic and abiotic stress as well as improving rice quality to secure global food supplies.

To mine the wide genetic diversity in plant germplasm populations, identification of phenotypic traits might the first and an important step. Besides the agronomic traits, physiological traits, stress-related traits, quality traits, resistant to virus and pets traits, etc. should be furthered studied in details. Based on the full evaluation of phenotypes, a dynamic core collection could be constructed either on a specific target trait or on all the traits so that the core collection could retain as much as genetic diversity with the minimum accessions. The core collection could be furthered studied with high density markers as well as exact measurement of its phenotype.

Association mapping has become a promising approach to mine the elite genes within germplasm population compared to traditional linkage mapping. Association mapping based on a core collection would help to catch as more phenotypic variation as possible. Compared to a natural population or a breeding population with narrow genetic basis, the LD level in a core collection might be low due to its diverse origin. Therefore, more markers might be needed for genome-wide association mapping. However, due to the quick LD decay, fine mapping might be possible with a core collection. To perform a precisely association mapping, multiple replications either locations or years for the phenotypic identification, exact measurement of the population structure and the kinship should be considered. Furthermore, though a rapid progress has been made in genotyping, a quick, automated, economic genotyping technology (such as SNP array) for a large number of germplasm resources are desirable for association mapping with germplasm resources population. How to effectively combine the linkage and association mapping in plants (such as the nested association mapping in maize, NAM) might be another question which should be concerned. Due to such associations could be further applied in rice breeding with molecular assisted selection, it provide a bright future to make use of the elite genes in the diverse germplasm resources.

A strategy is proposed for exploring and utilization of the wide genetic diversity in plant germplasm populations, i.e. firstly, evaluation of the genetic diversity for germplasm populations at phenotypic and genotypic level; secondly, constructing core collection to achieve the maximum diversity with minimum accessions; thirdly, combining linkage mapping and association mapping to map desire QTL in a large scale and with high resolution; fourthly, developing near isogenic lines to verify and fine map QTLs; finally, cloning desirable genes and make use of them in cultivated plant breeding.

## **8. Acknowledgment**

100 Genetic Diversity in Plants

No. Markers Chromosome Map distance (cM) P value R2 (%)

§The Bonferroni threshold (< 0.0036); ¥supported by previous researches; R2 represents the genetic

Table 9. Association mapping results for yield per panicle in 2009 using MLM models.

Rice feeds more than 50% of the world's population and is one of the most important crops in the world. Rice germplasm resource is the primary material for rice breeding and makes a concrete contribution to global wealth creation and food security. Therefore, understanding its valuable genetic diversity and using it in rice genetic improvement is of importance for raising rice yield and the resistance to biotic and abiotic stress as well as improving rice

To mine the wide genetic diversity in plant germplasm populations, identification of phenotypic traits might the first and an important step. Besides the agronomic traits, physiological traits, stress-related traits, quality traits, resistant to virus and pets traits, etc. should be furthered studied in details. Based on the full evaluation of phenotypes, a dynamic core collection could be constructed either on a specific target trait or on all the traits so that the core collection could retain as much as genetic diversity with the minimum accessions. The core collection could be furthered studied with high density markers as well

Association mapping has become a promising approach to mine the elite genes within germplasm population compared to traditional linkage mapping. Association mapping based on a core collection would help to catch as more phenotypic variation as possible. Compared to a natural population or a breeding population with narrow genetic basis, the LD level in a core collection might be low due to its diverse origin. Therefore, more markers might be needed for genome-wide association mapping. However, due to the quick LD decay, fine mapping might be possible with a core collection. To perform a precisely association mapping, multiple replications either locations or years for the phenotypic

28.4 170.4 150.8 67.8 3 141.8 133.5 61 63.5 66.1 73.3 73 96.3 74.5 91.3

0.0392¥ 0.0130¥ 0.0270¥ 0.0491 0.0341 0.0188 0.0152 0.0155¥ 0.0358¥ 0.0049 0.0360 0.0126 0.0282 0.0299¥ 0.0442¥

3.02 4.41 5.17 5.62 4.83 8.74 13.87 5.99 3.14 5.71 3.13 4.45 3.43 3.36 13.00

RM220 PSM369 RM450 RM218 RM153 RM334 RM340 RM182 RM10 RM257 RM242 RM304 RM228 RM309 RM235

variants explained by the marker.

**7. Discussion and prospect** 

quality to secure global food supplies.

as exact measurement of its phenotype.

The authors thank very much to Academician of Chinese academy of science, professor Lu, Yong Gen for his supervision and support for the research. Many thanks are given to Dr. Li, Xiao Ling, Dr. Feng, Jiu Huan, Ms. Zhao, Xing Juan, Mr. Zeng Kai Long, Mr. Deng, Yong Hong, Dr. Xu, Hai Ming for their helps in the experiment and data analysis. The research was supported by Fund of the National Natural Science Foundation of China grant (30700494).

#### **9. References**

