Molecular characterization and genetic structure of Quercus acutissima germplasm in China using microsatellites
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Quercus acutissima is native to eastern Asia. It has a wide distribution in China and China is an important component in understanding the ecology and genetic structure of this species. Q. acutissima attained high economic value for hardwood product and can be managed as an energy tree species. To investigate the genetic variation of Q. acutissima provenances, 12 microsatellite primer pairs were used to analyze 672 trees sampled from 28 provenances of Q. acutissima in China. All of the tested microsatellite loci proved to be effective for the studied Q. acutissima provenances. The results revealed that allele numbers varied from 5 to 13 per locus, with an average of 8 alleles per locus. The mean observed heterozygosity and expected heterozygosity were 0.4927 and 0.7023, respectively. The relatedness of the provenances was studied using the arithmetic mean algorithm based on Nei’s genetic distance and principal coordinates analysis. Interestingly, both approaches revealed two main groups: one consisted of the eastern Chinese provenances, and the other comprised of the western Chinese provenances. An analysis of molecular variance indicated that most genetic variation was contained within populations (84 %). The two microsatellite markers developed in this study may be employed for genetic characterization of other oak species. Considering the management or breeding programs of Q. acutissima provenances in China, we should treat each main group as a single gene resource.
KeywordsMicrosatellites Quercus acutissima Genetic structure Germplasm Provenance Management
We would like to thank Dr. T. M. Yin for his valuable comments on the manuscript. We owe special thanks to Dr. Z. L. Liu for his previous work on collecting acorns of Q. acutissima. We would also like to acknowledge Y. Xia and Y. X. Chen for their contributions in collecting samples. We gratefully acknowledge the assistance of C. P. Xie in the plotting of the geographic map using ArcGis. This work was supported by the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), the National Key Technology R&D Program (2008BAC39B01, 2008BAC39B06), the Doctorate Fellowship Foundation of Nanjing Forestry University, and the National Public Benefit Research Foundation of China (200704034).
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