| Northeast Asia is one of the major regions where grow rice (Oryza sativa L.), and sums up7%of the global rice yields. The popularization of new improved varieties has significantly increased the yields in this region. However, the genetic base of these varieties is becoming narrow in recent years, which will threaten the safety and sustainable development of rice production. It is necessary to explore new alien germplasm in order to expand gene pool in the breeding program. Eventually the integrated gene pool will benefit to the improvement of current varieties with wide environmental adaptation and high yield and quality. In this project,278japonica rice accessions(Oryza sativa L. subsp. japonic a)(78landraces and200improved varieties) from nine rice ecotypes were selected from seven regions for study. The seven regions are Heilongjiang, Jilin and Liaoning provinces of China, Japan, Korea, Democratic People’s Republic of Korean, and the Russian Far East District of Russian Federation. We investigated31plant type traits in years of2010and2011and genotyped them with154pairs of polymorphic SSR markers respectively. This study systematically investigated the genetic diversity and differentiation of all varieties and the association mapping between SSR markers and plant type traits. Major findings in this project showed as below:①Analyses of genetic diversity of plant type traits indicated that:genetic diversity index (He) and polymorphism information content (PIC) were0.8289and0.8087in2010,0.8287and0.8094in2011; with an average of0.8288and0.8091in two years, respectively. Of the31plant type traits, spike length, the first internode length from the top, plant height, the width, length, and bowstring length of flag leaf, spike bowstring length, the length and bowstring length of the second top leaf showed smaller variation, whereas difference between the length and bowstring length of the third top leaf, the fifth internode length from the top, difference between the length and bowstring length of the second top leaf, basal angle of the second top leaf, basal angle of spike, the fourth internode length from the top, open angle of the second top leaf, basal angle of flag leaf, difference between the length and bowstring length of flag leaf, and spike heading length showed larger variation. Open angle of flag leaf, the third internode length from the top, open angle of the third top leaf and spike length had a higher level of genetic diversity, whereasc the fifth internode length from the top, difference between the length and bowstring length of the second top leaf, difference between the length and bowstring length of flag leaf, basal angle of spike, flag leaf width and open angle of the second top leaf had a relatively lower level of genetic diversity.Comparisons of different traits among9rice ecotypes showed that spike heading length, open angle of the third top leaf, basal angle of flag leaf, and open angle of flag leaf had significant genotypic differences. The improved varieties from Liaoning had significant larger width of flag leaf and widths of the second and third top leaf but significant smaller open angle of spike than those in other regions. The landraces in Heilongjiang and improved varieties in Russian Far East District of Russian Federation had significantly larger basal of the second top leaf than that of other rice ecotypes. Japanese improved varieties had the highest diversity of plant type traits, and Russian Far East District of Russian Federation improved varieties had the lowest. Considering the similarity on the degree of consistency in plant type traits among different rice ecotypes, Heilongjiang landraces and Russian Far East District of Russian Federation improved varieties were high; Heilongjiang improved varieties, Jinlin improved varieties, Japanese improved varieties, and Korean improved varieties were high; and Liaoning improved varietis and Democratic People’s Republic of Korean improved varieties were high.①Genetic diversity analyses based on SSR markers revealed that a total of823alleles were detected by154polymorphic SSR markers, with each a range of2to9allelic variations. The average of observed allele numbers (Na), Nei’s gene diversity (He), polymorphism information content (PIC) and Shannon index (Ⅰ) were5.344,0.624,0.586and1.144, respectively. Heilongjiang landraces had the highest He and PIC, followed by Jilin landraces, Japanese improved varieties, Heilongjiang improved varieties, Russian Far East district of Russian Federation improved varieties, Liaoning improved varieties, Jilin improved varieties, Korean improved varieties, and Democratic People’s Republic of Korean improved varieties. According to the genetic identify, the nine rice ecotypes were divided into3subgroups:Heilongjiang landraces and Jilin landraces; Russian Far East district of Russian Federation improved varieties, and the rest of other rice ecotypes.②Association analyses indicated that a total of89loci were significantly associated with different traits in2010and2011, with a range of2.22～18.09%phenotypic variation. Of the89loci,23showed significant association in both years and66showed significant association in a single year. Of which42were significantly associated with one trait,47were significantly associated with two or more traits. The positive ratio of associated markers ranged0～116.20%, and the negative ratio ranged-76.28%～0.RM536was associated with eleven traits, the most when compared to other markers.The impact of one locus on multiple traits was gained by different allelic variations. A total of68allelic variations with the largest positive (negative) effects were detected in both years. The positive ratio of the largest allelic variations ranged9.08～460.19%, and the negative ratio ranged-166.87～-1.39%. Of the68allelic variations,43affected only one trait and25affected two or more traits. Seven allelic variations had the largest positive (negative) allele effect in both years.④The analyses on genetic relationships between plant height and its components showed that there was positive correlation between plant height and its components. The variation of the third internode length from the top had the most contribution to plant height. Many associated markers indirectly affected plant height through influencing its different components. By using conditional association mapping,27markers were significantly associated with plant height and explained2.76～11.89%phenotypic variation. Of the27associated markers,5were detected in both years,22were detected in a single year. |
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