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Zhang K.,Southwest University | Zhang K.,Sweet Potato Engineering and Technology Research Center | Wu Z.-D.,Southwest University | Li Y.-H.,Southwest University | And 13 more authors.
Journal of Integrative Agriculture | Year: 2014

To determine the genetic diversity and population structure of sweet potato accessions cultivated in China, and to establish the genetic relationships among their germplasm types, a representative collection of 240 accessions was analyzed using inter-simple sequence repeat (ISSR) markers. The mean genetic similarity coefficient, Nei's gene diversity, and shared allele distance of tested sweet potato accessions were 0.7302, 0.3167 and 0.2698, respectively. The 240 accessions could be divided into six subgroups and five subpopulations based on neighbor-joining (NJ) clustering and STRUCTURE results, and obvious genetic relationships among the tested sweet potato accessions were identified. The marker-based NJ clustering and population structure showed no distinct assignment pattern corresponding to flesh color or geographical ecotype of the tested sweet potato germplasm. Analysis of molecular variance (AMOVA) revealed small but significant difference between white and orange-fleshed sweet potato accessions. Small but significant difference were also observed among sweet potato accessions from the Southern summer-autumn sweet potato region, the Yellow River Basin spring and summer sweet potato region and the Yangtze River Basin summer sweet potato region. This study demonstrates that genetic diversity in the tested sweet potato germplasm collection in China is lower than that in some reported sweet potato germplasm collections from other regions. Pedigree investigations suggest that more diverse Chinese sweet potato varieties should be formed by broadening the selection scope of breeding parents and incorporating the introduced varieties into future breeding programs. © 2014 Chinese Academy of Agricultural Sciences.

Zhang K.,Southwest University | Zhang K.,Sweet Potato Engineering and Technology Research Center | Wu Z.,Southwest University | Wu Z.,Sweet Potato Engineering and Technology Research Center | And 14 more authors.
Frontiers in Plant Science | Year: 2016

Sweet potato (Ipomoea batatas L.) is a nutritious food crop and, based on the high starch content of its storage root, a potential bioethanol feedstock. Enhancing the nutritional value and starch quantity of storage roots are important goals of sweet potato breeding programs aimed at developing improved varieties for direct consumption, processing, and industrial uses. However, developing improved lines of sweet potato is challenging due to the genetic complexity of this plant and the lack of genome information. Short sequence repeat (SSR) markers are powerful molecular tools for tracking important loci in crops and for molecular-based breeding strategies; however, few SSR markers and marker-trait associations have hitherto been identified in sweet potato. In this study, we identified 1824 SSRs by using a de novo assembly of publicly available ESTs and mRNAs in sweet potato, and designed 1476 primer pairs based on SSR-containing sequences. We mapped 214 pairs of primers in a natural population comprised of 239 germplasms, and identified 1278 alleles with an average of 5.972 alleles per locus and a major allele frequency of 0.7702. Population structure analysis revealed two subpopulations in this panel of germplasms, and phenotypic characterization demonstrated that this panel is suitable for association mapping of starch-related traits. We identified 32, 16, and 17 SSR markers associated with starch content, β-carotene content, and starch composition in the storage root, respectively, using association analysis and further evaluation of a subset of sweet potato genotypes with various characteristics. The SSR markers identified here can be used to select varieties with desired traits and to investigate the genetic mechanism underlying starch and carotenoid formation in the starchy roots of sweet potato. © 2016 Zhang, Wu, Tang, Lv, Luo, Zhao, Liu, Huang and Wang.

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