Empirical Selection of Informative Microsatellite Markers within Co-ancestry Pig Populations Is Required for Improving the Individual Assignment Efficiency

  • Lia, Y.H. (Department of Animal Science and Technology, National Taiwan University) ;
  • Chu, H.P. (Taitung Animal Propagation Station, Livestock Research Institute) ;
  • Jiang, Y.N. (Department of Animal Science and Technology, National Taiwan University) ;
  • Lin, C.Y. (Taitung Animal Propagation Station, Livestock Research Institute) ;
  • Li, S.H. (Department of Life Science, National Taiwan Normal University) ;
  • Li, K.T. (Institute of History and Philology, Academia Sinica) ;
  • Weng, G.J. (Institute of Wildlife Conservation, National Pingtung University of Science and Technology) ;
  • Cheng, C.C. (Graduate Institute of Hakka Cultural Industry, National Pingtung University of Science and Technology) ;
  • Lu, D.J. (School of Forestry and Resource Conservation, National Taiwan University) ;
  • Ju, Y.T. (Department of Animal Science and Technology, National Taiwan University)
  • Received : 2013.06.26
  • Accepted : 2013.12.12
  • Published : 2014.05.01


The Lanyu is a miniature pig breed indigenous to Lanyu Island, Taiwan. It is distantly related to Asian and European pig breeds. It has been inbred to generate two breeds and crossed with Landrace and Duroc to produce two hybrids for laboratory use. Selecting sets of informative genetic markers to track the genetic qualities of laboratory animals and stud stock is an important function of genetic databases. For more than two decades, Lanyu derived breeds of common ancestry and crossbreeds have been used to examine the effectiveness of genetic marker selection and optimal approaches for individual assignment. In this paper, these pigs and the following breeds: Berkshire, Duroc, Landrace and Yorkshire, Meishan and Taoyuan, TLRI Black Pig No. 1, and Kaohsiung Animal Propagation Station Black pig are studied to build a genetic reference database. Nineteen microsatellite markers (loci) provide information on genetic variation and differentiation among studied breeds. High differentiation index ($F_{ST}$) and Cavalli-Sforza chord distances give genetic differentiation among breeds, including Lanyu's inbred populations. Inbreeding values ($F_{IS}$) show that Lanyu and its derived inbred breeds have significant loss of heterozygosity. Individual assignment testing of 352 animals was done with different numbers of microsatellite markers in this study. The testing assigned 99% of the animals successfully into their correct reference populations based on 9 to 14 markers ranking D-scores, allelic number, expected heterozygosity ($H_E$) or $F_{ST}$, respectively. All miss-assigned individuals came from close lineage Lanyu breeds. To improve individual assignment among close lineage breeds, microsatellite markers selected from Lanyu populations with high polymorphic, heterozygosity, $F_{ST}$ and D-scores were used. Only 6 to 8 markers ranking $H_E$, $F_{ST}$ or allelic number were required to obtain 99% assignment accuracy. This result suggests empirical examination of assignment-error rates is required if discernible levels of co-ancestry exist. In the reference group, optimum assignment accuracy was achievable achieved through a combination of different markers by ranking the heterozygosity, $F_{ST}$ and allelic number of close lineage populations.


  1. Anderson, J. A., G. A. Churchill, J. E. Autrique, S. D. Tanksley, and M. E. Sorrells. 1993. Optimizing parental selection for genetic linkage maps. Genome 36:181-186.
  2. Banks, M. A. and W. Eichert. 2000. WHICHRUN (version 3.2), a computer program for population assignment of individuals based on multilocus genotype data. J. Hered. 91:87-89.
  3. Banks, M. A., W. Eichert, and J. B. Olsen. 2003. Which genetic loci have greater population assignment power? Bioinformatics 19:1436-1438.
  4. Bjornstad, G. and K. H. Roed. 2002. Evaluation of factors affecting individual assignment precision using microsatellite data from horse breeds and simulated breed crosses. Anim. Genet. 33:264-270.
  5. Boitard, S., C. Chevalet, M. J. Mercat, J. C. Meriaux, A. Sanchez, J. Tibau, and M. Sancristobal. 2010. Genetic variability, structure and assignment of Spanish and French pig populations based on a large sampling. Anim. Genet. 41:608-618.
  6. Bond, J. M., E. M. Veenendaal, D. D. Hornby, and A. J. Gray. 2002. Looking for progenitors, a molecular approach to finding the origins of an invasive weed. Biol. Invasions 4:349-357.
  7. Botstein, D., R. L. White, H. Skolmick, and R. W. Davis. 1980. Construction of a genetic linkage map in man using restriction fragment length polymorphism. Am. J. Hum. Genet. 32:314-331.
  8. Caratti, S., L. Rossi, B. Sona, S. Origlia, S. Viara, G. Martano, C. Torre, and C. Robino. 2010. Analysis of 11 tetrameric STRs in wild boars for forensic purposes. Forensic Sci. Int. Genet. 4: 339-342.
  9. Carr, M. R. 1996. PRIMER user manual. Ver 4.0. Plymouth routines in multivariate ecological research. Plymouth Marine Laboratory, Plymouth, UK.
  10. Cavalli-Sforza, L. L. and A. W. F. Edwards. 1967. Phylogenetic analysis, models and estimation procedures. Am. J. Med. Genet. 19:233-257.
  11. Chang, W. H., H. P. Chu, Y. N. Jiang, S. H. Li, Y. Wang, C. H. Chen, K. J. Chen, C. Y. Lin, and Y. T. Ju. 2009. Genetic variation and phylogenetics of Lanyu and exotic pig breeds in Taiwan analyzed by nineteen microsatellite markers. J. Anim. Sci. 87:1-8.
  12. Cornuet, J. M., S. Piry, G. Luikart, A. Estoup, and M. Solignac. 1999. New methods employing multilocus genotypes to select or exclude populations as origins of individuals. Genetics 153: 1989-2000.
  13. Coutellec, M. A. and T. Caquet. 2011. Heterosis and inbreeding depression in bottlenecked populations, a test in the hermaphroditic freshwater snail Lymnaea stagnalis. J. Evol. Biol. 24:2248- 2257.
  14. Efron, B. 1983. Estimating the error rate of a prediction rule, Improvement on cross-validation. J. Am. Stat. Assoc. 78:316-331.
  15. Goudet, J. 2001. FSTAT, a program to estimate and test gene diversities and fixation indices (version 2.9.3) [Internet]. [cited 2014 Jan 22] Available from:
  16. Gray, R. D., A. J. Drummond, and S. J. Greenhill. 2009. Language phylogenies reveal expansion pulses and pauses in Pacific settlement. Science 323:479-483.
  17. Guinand, B., K. T. Scribner, K. S. Page, K. Filcek, and L. Main. 2006. Effects of coancestry on accuracy of individual assignments to population of origin: examples using great lakes lake trout (Salvelinus namaycush). Genetica 127:329-340.
  18. Guinand, B., K. T. Scribner, A. Topchy, K. S. Page, W. Punch, and M. K. Burnham-Curtis. 2004. Sampling issues affecting accuracy of likelihood-based classification using genetical data. Environ. Biol. Fish. 69:245-259.
  19. Hale, M. L., T. M. Burg, and T. E. Steeves. 2012. Sampling for microsatellite-based population genetic studies: 25 to 30 individuals per population is enough to accurately estimate allele frequencies. PLoS ONE 7(9):e45170.
  20. ISAG-FAO. 2004. Secondary Guidelines: Measurement of Domestic Animal Diversity (MoDAD): Recommended Microsatellite Markers.
  21. Jiang, Y. N., C. Y. Wu, C. Y. Huang, H. P. Chu, M. W. Ke, M. S. Kung, K. Y. Li, S. H. Li, C. H. Wang, Y. Wang, and Y. T. Ju. 2008. Inter-population and intra-population maternal lineage genetics of Lanyu pig (Sus scrofa) by analysis of mitochondrial cytochrome b and control region sequences. J. Anim. Sci. 86:2461-2470.
  22. Kalinowski, S. T. 2005. Do polymorphic loci require large sample sizes to estimate genetic distances? Heredity 94:33-36.
  23. Kalinowski, S. T., M. L. Taper, and T. C. Marshall. 2007. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol. Ecol. 16:1099-1106.
  24. Kim, T. H., K. S. Kim, B. H. Choi, D. H. Yoon, G. W. Jang, K. T. Lee, H. Y. Chung, H. Y. Lee, H. S. Park, and J. W. Lee. 2005. Genetic structure of pig breeds from Korea and China using microsatellite loci analysis. J. Anim. Sci. 83:2255-2263.
  25. Kimura, M. and J. F. Crow. 1964. The number of alleles that can be maintained in a finite population. Genetics 49:725-738.
  26. Koskinen, M. T. 2003. Individual assignment using microsatellite DNA reveals unambiguous breed identification in the domestic dog. Anim. Genet. 34:297-301.
  27. Krzanowski, W. 1987. Principles of multivariate analysis, a user's perspective. Clarendon Press, Oxford.
  28. Langella, O. 2002. POPULATIONS 1.2.28, Population genetic software, individuals or populations distances based on allelic frequencies, phylogenetic trees, file conversions [Internet]. [cited 2011 Feb 15] Available from:
  29. Larson, G., T. Cucchi, M. Fujita, E. Matisoo-Smith, J. Robins, A. Anderson, B. Rolett, M. Spriggs, G. Dolman, T. H. Kim, N. T. D. Thuy, E. Randi, M. Doherty, R. A. Due, R. Bollt, T. Djubiantono, B. Griffin, M. Intoh, E. Keane, P. Kirch, K. T. Li, M. Morwood, L. M. Pedrina, P. J. Piper, R. J. Rabett, P. Shooter, G. V. den Bergh, E. West, S. Wickler, J. Yuan, A. Cooper, and K. Dobneybc. 2007. Phylogeny and ancient DNA of Sus provides insights into neolithic expansion in Island Southeast Asia and Oceania. Proc. Natl. Acad. Sci. USA 104: 4834-4839.
  30. Larson, G., R. Liu, X. Zhao, J. Yuan, D. Fuller, L. Barton, K. Dobney, Q. Fan, Z. Gu, X. H. Liu, Y. Luo, P. Lv, L. Andersson, and N. Li. 2010. Patterns of East Asian pig domestication, migration, and turnover revealed by modern and ancient DNA. Proc. Natl. Acad. Sci. USA 107:7686-7691.
  31. Lowenstein, J. H., J. Burger, C. W. Jeitner, G. Amato, S. O. Kolokotronis, and M. Gochfeld. 2010. DNA barcodes reveal species-specific mercury levels in tuna sushi that pose a health risk to consumers. Biol. Lett. 6:692-695.
  32. Marshall, T. C., J. Slate, L. E. B. Kruuk, and J. M. Pemberton. 1998. Statistical confidence for likelihood-based paternity inference in natural populations. Mol. Ecol. 7:639-655.
  33. Nei, M. 1973. Analysis of gene diversity in subdivided populations. Proc. Natl. Acad. Sci. USA 70:3321-3323.
  34. Nei, M. 1978. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89:583-590.
  35. Piry, S., A. Alapetite, J. M. Cornuet, D. Paetkau, L. Baudouin, and A. Estoup. 2004. GeneClass2, A Software for genetic assignment and first-generation migrant detection. J. Hered. 95: 536-539.
  36. Primmer, C. R., T. T. K. Mikko, and J. Piironen. 2000. The one that did not get away: individual assignment using microsatellite data detects a case of fishing competition fraud. Proc. R. Soc. Lond. 267:1699-1704.
  37. Rannala, B. and J. L. Mountain. 1997. Detecting immigration by using multilocus genotypes. Proc. Natl. Acad. Sci. USA. 94: 9197-9201.
  38. Reed, T. E. 1973. Number of gene loci required for accurate estima tion of ancestral population proportions in individual human hybrids. Nature 244:575-576.
  39. Rosenberg, N. A., E. Woolf, J. K. Pritchard, T. Schaap, D. Gefel, I. Shpirer, U. Lavi, B. Bonne-Tamir, J. Hillel, and M. W. Feldman. 2001. Distinctive genetic signatures in the Libyan Jews. Proc. Natl. Acad. Sci. USA 98:858-863.
  40. Rousset, F. 2008. Genepop, a complete reimplementation of the Genepop software for Windows and Linux. Mol. Ecol. Resour. 8:103-106.
  41. Tadano, R., M. Nishibori, and M. Tsudzuki. 2008. High accuracy of genetic discrimination among chicken lines obtained through an individual assignment test. Anim. Genet. 39:567-571.
  42. Wu, C. Y., Y. N. Jiang, H. P. Chu, S. H. Li, Y. Wang, Y. H. Li, Y. Chang, and Y. T. Ju. 2007. The type I Lanyu pig has a maternal genetic lineage distinct from Asian and European pigs. Anim. Genet. 38:499-505.
  43. Wu, M. C., H. P. Chu, and K. J. Chen. 2009. Lanyu pig transforming from the conserved animal to new breeds for medical biology industry. Sci-Tech Policy Rev. 5:88-93.
  44. Yang, S. L., Z. G. Wang, B. Liu, G. X. Zhang, S. H. Zhao, M. Yu, B. Fan, M. H. Li, T. A. Xiong, and K. Li. 2003. Genetic variation and relationships of eighteen Chinese indigenous pig breeds. Genet. Sel. Evol. 35:657-671.
  45. Yeh, F. C., R. C. Yang, and T. Boyle. 1999. POPGENE (Version 1.31), Microsoft Window-bases freeware for population genetic analysis, University of Alberta and the Centre for International Forestry Research.

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