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Development of a Highly Informative Microsatellite (SSR) Marker Framework for Rice (Oryza sativa L.) Genotyping

机译:水稻(Oryza sativa L.)基因分型的高信息微卫星(SSR)标记框架的开发

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摘要

To select highly informative microsatellite markers (SSRs) and establish a useful genetic SSR framework for rice genotyping, 15 rice (Oryza sativa L.) cultivars including six indica varieties and nine japonica varieties were used to analyze the polymorphism information content (PIC) value of 489 SSR markers. A total of 1 296 alleles were detected by 405 polymorphic markers with an average of 3.2 per locus. The PIC value of each chromosome was ranged from 0.4039 (chromosome 2) to 0.5840 (chromosome 11). Among the two rice subspecies, indica (0.3685-0.4952) gave a higher PIC value than japonica (0.1326-0.3164) and displayed a higher genetic diversity. Genetic diversity of indica was high on chromosome 12 (0.4952) and low on chromosome 8 (0.3685), while that for japonica was high on chromosome 11 (0.3164) and low on chromosome 2 (0.1326). A SSR framework including 141 highly informative markers for genotyping was selected from 199 SSR markers (PIC > 0.50). Ninety-three SSR markers distributed on 12 chromosomes were found to be related to indica-japonica differentiation. Of these 93 pairs of SSR primers, 17 pairs were considered as core primers (all the japonica varieties have the same specific alleles, while the indica varieties have another specific alleles), 48 pairs as the second classic primers (all the japonica or indica varieties have the same specific alleles, while the indica or japanica varieties have two or more other specific alleles ) and 28 pairs as the third classic primers (all the japonica and indica varieties have two or more alleles, but the specific alleles are different between japonica and indica). Thirty-two SSR markers were selected to be highly informative and useful for genetic diversity analysis of japonica varieties. This work provides a lot of useful information of SSR markers for rice breeding programs, especially for genotyping, diversity analysis and genetic mapping.

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