Many Camellia oleifera germplasm resources were collected from Guizhou Province, but the fruit morphological variation and genetic diversity of C. oleifera germplasm resources remain unclear. The genetic diversity of C. oleifera germplasms resources in Guizhou was studied based on fruit traits and simple sequence repeat (SSR) molecular markers to build a core collection. This paper aims to provide a scientific basis for the collection, management, development, and utilization of C. oleifera resources in Guizhou province. The variation coefficients among and within varieties of seven fruit phenotypic traits of C. oleifera ranged from 11.79% to 61.76% and from 8.15% to 42.31%, respectively, showing rich phenotypic variation. Furthermore, 12 SSR markers were used to analyze the genetic diversity. These primers generated 214 polymorphic bands, and the average number was 17.833. The average number of effective alleles (Ne), Shannon's information index (I), observed heterozygosity (Ho), expected heterozygosity (He), polymorphic information content (PIC), and major allele frequency (MAF) were 8.999, 2.301, 0.965, 0.50, 0.836, and 0.238, respectively. The results showed that 12 SSR markers had high polymorphism, and the genetic diversity of 167 C. oleifera germplasm resources was high. Based on SSR molecular marker information and fruit traits clustering, 167 C. oleifera germplasm resources were divided into three groups. When constructing core collections based on fruit traits and molecular marker information, the PowerCore-25 of core collections greatly preserves fruit traits and improves genetic diversity. This paper can provide a reference for the genetic diversity and fruit traits variation of C. camellia germplasm resources in Guizhou Province. It is significant for establishing a core collection, thus promoting germplasm innovation and the development of the oil tea industry in Guizhou.
Genetic Diversity Analysis and Core Germplasm Collection Construction of Camellia oleifera Based on Fruit Phenotype and SSR Data.
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作者:Zhu Yunzheng, Liang Deyang, Song Zejun, Tan Yi, Guo Xiaolan, Wang Delu
| 期刊: | Genes | 影响因子: | 2.800 |
| 时间: | 2022 | 起止号: | 2022 Dec 13; 13(12):2351 |
| doi: | 10.3390/genes13122351 | ||
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