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Genetic analysis of Cheirostylis species based on microsatellite markers

Published online by Cambridge University Press:  02 October 2014

Supajit Sraphet*
Affiliation:
Institute of Molecular Biosciences, Mahidol University, Salaya, Nakhon Pathom 73170, Thailand
Anuwat Saengsri
Affiliation:
Institute of Molecular Biosciences, Mahidol University, Salaya, Nakhon Pathom 73170, Thailand
Duncan R. Smith
Affiliation:
Institute of Molecular Biosciences, Mahidol University, Salaya, Nakhon Pathom 73170, Thailand
Kanokporn Triwitayakorn*
Affiliation:
Institute of Molecular Biosciences, Mahidol University, Salaya, Nakhon Pathom 73170, Thailand
*
* Corresponding authors: E-mail: [email protected]; [email protected]
* Corresponding authors: E-mail: [email protected]; [email protected]

Abstract

Microsatellite markers specific to Cheirostylis yunnanensis Rolfe were developed using an enriched genomic DNA library technique. The library was constructed using (AG)20 and (CAG)20 oligonucleotide repeats. A total of 48 primer pairs were designed and tested with 48 C. yunnanensis Rolfe samples, resulting in 11 polymorphic loci. The number of alleles per locus ranged from 2 to 12, with an average of six alleles. The observed and expected heterozygosity ranged from 0.0426 to 0.8085 and 0.0421 to 0.9078, respectively. Of the 11 polymorphic loci, three showed a significant deviation from Hardy–Weinberg equilibrium and one exhibited linkage disequilibrium. Cross-species amplification was tested with five samples of Cheirostylis of unknown species resulting in eight loci that could be amplified, with the number of alleles ranging from one to two. The microsatellite markers developed in this study will be useful for the genetic analysis of C. yunnanensis in order to differentiate species as well as to establish a conservation plan for this species.

Type
Short Communication
Copyright
Copyright © NIAB 2014 

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References

Benbouza, H, Jacquemin, JM, Baudoin, JP and Mergeai, G (2006) Optimization of a reliable, fast, cheap and sensitive silver staining method to detect SSR markers in polyacrylamide gels. Biotechnology, Agronomy, Society and Environment 10: 7781.Google Scholar
Butcher, PA, Decroocq, S, Gray, Y and Moran, GF (2000) Development, inheritance and cross-species amplification of microsatellite markers from Acacia mangium . Theoretical and Applied Genetics 101: 12821290.Google Scholar
Doyle, JJ and Doyle, JL (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochemical Bulletin 19: 1115.Google Scholar
Kunkeaw, S, Tangphatsornruang, S, Smith, DR and Triwitayakorn, K (2010) Genetic linkage map of cassava (Manihot esculenta Crantz) based on AFLP and SSR markers. Plant Breeding 129: 112115.CrossRefGoogle Scholar
Martins, WS, Lucas, DC, Neves, KF and Bertioli, DJ (2009) WebSat – a web software for microsatellite marker development. Bioinformation 3: 282283.Google Scholar
Miller, M (1997) Tools for population genetic analysis (TFPGA) 1.3. A windows program for the analysis of allozyme and molecular population genetic data Computer software distributed by author (http://www.marksgeneticsoftware.net/tfpga.htm).Google Scholar
Rao, AN (2011) A review of the subfamily Spiranthoideae Dressler (Orchidaceae) in Arunachal Pradesh. Bulletin of Arunachal Forest Research 27: 133.Google Scholar
Raymond, M and Rousset, F (1995) GENEPOP (version 1.2): population genetics software for exact tests and ecumenicism. Journal of Heredity 86: 248249.CrossRefGoogle Scholar
Rousset, F (2008) GENEPOP'007: a complete re-implementation of the Genepop software for Windows and Linux. Molecular Ecology Resources 8: 103106.CrossRefGoogle ScholarPubMed
Roy, M, Watthana, S, Stier, A, Richard, F, Vessabutr, S and Selosse, M (2009) Two mycoheterotrophic orchids from Thailand tropical dipterocarpacean forests associate with a broad diversity of ectomycorrhizal fungi. BMC Biology 7: 51.CrossRefGoogle ScholarPubMed
Salin, S (2006) Wild Orchid of Thailand. Bangkok, Thailand: Baan Lae Suan Press. 496 pp. (In Thai).Google Scholar
Santisuk, T, Chayamarit, K, Pooma, R and Suddee, S (2006) Thailand Red Data: Plants. Bangkok, Thailand: Office of Natural Resources and Environmental Policy and Planning. 256 pp.Google Scholar
Seidenfaden, G (1978) Orchid genera in Thailand VI. Neottioideae Lindl. Dansk Botanisk Arkiv Udgivet af Dansk Botanisk Forening 32: 6175.Google Scholar
Sraphet, S, Boonchanawiwat, A, Thanyasiriwat, T, Boonseng, O, Tabata, S, Sasamoto, S, Shirasawa, K, Isobe, S, Lightfoot, DA, Tangphatsornruang, S and Triwitayakorn, K (2011) SSR and EST-SSR-based genetic linkage map of cassava (Manihot esculenta Crantz). Theoretical and Applied Genetics 122: 11611170.Google Scholar
Thaithong, O (1999) Orchids of Thailand. In OEPP Biodiversity Series, vol. 8. Bangkok, Thailand: Office of Environmental Policy and Planning. 239 pp.Google Scholar
Wang, C, Liu, X, Peng, S, Xu, Q, Yuan, X, Feng, Y, Yu, H, Wang, Y and Wei, X (2014) Development of novel microsatellite markers for the BBCC Oryza genome (Poaceae) using high-throughput sequencing technology. PLoS ONE 9: e91826. Doi:10.1371/journal.pone.0091826.CrossRefGoogle ScholarPubMed