Application of Microsatellite to Population Genetic Study of the Crocodile Lizard (Shinisaurus crocodilurus Ahl, 1930) in Vietnam
Main Article Content
Abstract
Abstract: Population genetic studies play an important role in designing appropriate conservation plans, especially with regard to morphological distinct or geographically isolated populations. Among available molecular markers, microsatellite is a marker of choice in many population genetic studies because it has a high mutation rate, and as a result, can provide valuable insights into genetic history of a population. Specifically, analyses based on microsatellite can help determine genetic diversity, genetic structure, the number of genetically distinct populations, genetic history, and inbreeding coefficient. In this study, we present methods for generating microsatellite data for the population genetic study of an endangered species, the Crocodile Lizard (Shinisaurus crocodilurus vietnamensis), in Vietnam. Our bottle neck analyses using microsatellite data show that the population of this species in Vietnam already experiences a severe reduction of effective population size. The results of the study have critical implications for conservation of this endangered species in the near future.
Keywords:
Crocodile lizard, Shinisaurus crocodilurus, Microsatellite, Population genetics, Bottlenecks.
References
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[3] Zhu Y, Queller D. C., Strassmann J. E. (2000), A phylogenetic perspective on sequence evolution in microsatellite loci, J Mol Evol, 50(4): 324–338.
[4] Mburu D. Hanotte O. (2005), A practical approach to microsatellite genotyping with special reference to livestock population genetics, ILRI: Nairobi.
[5] Gupta P. K., Varshney R. K. (2000), The development and use of microsatellite markers for genetic analysis and plant breeding with emphasis on bread wheat, Euphytica, 113: 163–185.
[6] Jarl A. A., Oddmund K., Lutz B., Jan T. L. (2008), Microsatellite evolution: Mutations, sequence variation, and homoplasy in the hypervariable avian microsatellite locus HrU10, Bio Med Central, 8(138).
[7] Jingou T., Dan W., Lei C. (2009), Development of Microsatellite Markers by Data Mining from DNA Sequences Data Mining and Knowledge Discovery in Real Life Applications, ed. Julio P. & Adem K., InTech.
[8] Kashi Y, King D., Soller S. (1997), Simple sequence repeats as a source of quantitative genetic variation, Trends Genet, 13(2): 74-78.
[9] Swati P. J., Prabhakar K. R., Vidya S. G. (1999), Molecular markers in plant genome analysis, Curr Sci, 77: 230–240, National chemical laboratory.
[10] A. Bonin, D. Ehrich, S. Manel. (2007), Statistical analysis of amplified fragment length polymorphism data: a toolbox for molecular ecologists and evolutionists, Molecular Ecology, 16: 3737–3758.
[11] Neeraja CN, Maghirang R. R., Pamplona A., Heuer S., Collard B. C., Septiningsih E. M., Vergara G., Sanchez D., Xu K., Ismail A. M., Mackill D. J. (2007_, A marker-assisted backcross approach for developing submergence-tolerant rice cultivars, Theor Appl Genet, 115: 767–776.
[12] Humberto M. R. V. (2013), Informativeness of Microsatellite Markers Microsatellites: Methods and Protocols, ed. Stella K. Kantartzi. Vol. 1006. Springer.
[13] Nguyen T. Q., Hamilton P., Ziegler T. (2014), Shinisaurus crocodilurus. The IUCN Red List of Threatened Species, The IUCN Red List of ThreatenedSpecies. Version 2014.2.. Available from. www.iucnredlist.org. Assessed October 2014.
[14] Huang H., Wang H., Li L., Wu Z., Chen J. (2014), Genetic diversity and population demography of Chinese crocodile lizard (Shinisaurus crocodilurus) in China, Plos One, 9(3): e91570. doi: 10.1371/journal.pone.0091570.
[15] van Schingen M. V., U. Schepp, C. T. Pham, T. Q. Nguyen, Ziegler T. (2015), Last chance to see? A review of the threats to and use of the crocodile lizard, Traffic bulletin, 27(1): 19-26.
[16] van Schingen M., Le D. M., Ngo T. H., Pham T. C., Ha Q. Q., Nguyen Q. T., Ziegler T. (2016), Is there more than one Crocodile Lizard? An Integrative Taxonomic Approach Reveals Vietnamese and Chinese Shinisaurus crocodilurus Represent Separate Conservation and Taxonomic Units, Der Zoologische Garten, 85(2): 240-260.
[17] Pritchard J.K, M. Stephens, Donnelly P. (2000), Inference of population structure using multilocus genotype data, Genetics, 155: 945–959.
[18] Kyung S. K. Thomas W. S. (2013), Microsatellite Data Analysis for Population Genetics. Microsatellites: Methods and Protocols, ed. Stella K. K. Vol. 1006. Springer.
[19] Weir B. S Cockerham C. C. (1984), Estimating F-statistics for the analysis of population structure, Evolution: 1358–1370.
[20] Dent A. E. Bridgett M. H. (2011), STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method, Springer, 4: 359-361.
[21] Evanno G., Regnaut S., Goudet J. (2005), Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study, Molecular Ecology, 14: 2611–2620.
[22] Excoffier L. Lischer H. (2015), Arlequin (version 3.5): An integrated software package for population genetics data analysis.
[23] Bohonak A. J. (2002), IBD (Isolation By Distance): A program for analyses of isolation by distance, Journal of Heredity, 93: 153–154.
[24] Goudet J. (1995), FSTAT (version 1.2): a computer program to calculate F- Statistics, Journal of heredity, 86: 485–486.