Traceability through physical labels is well established, but it is not highly reliable as physical labels can be easily changed or lost. Application of DNA markers to the traceability of food plays an increasingly important role for consumer protection and confidence building. In this study, we tested the efficiency of 16 polymorphic microsatellites and their combinations for tracing 368 fish to four populations where they originated. Using the maximum likelihood and Bayesian methods, three most efficient microsatellites were required to assign over 95% of fish to the correct populations. Selection of markers based on the assignment score estimated with the software WHICHLOCI was most effective in choosing markers for individual assignment, followed by the selection based on the allele number of individual markers. By combining rapid DNA extraction, and high-throughput genotyping of selected microsatellites, it is possible to conduct routine genetic traceability with high accuracy in Asian seabass.
References
[1]
Hastein T, Hill B, Berthe F, Lightner D (2001) Traceability of aquatic animals. Rev Sci Tech Oie 20: 564–583.
[2]
Dalvit C, De Marchi M, Cassandro M (2007) Genetic traceability of livestock products: A review. Meat Sci 77: 437–449.
[3]
Guerard F, Sellos D, Le Ga Y (2005) Fish and shellfish upgrading, traceability. In: Gal YL, Ulber R, editors. Marine Biotechnology I. NY: Springer. pp. 127–163.
[4]
Opara LU (2003) Traceability in agriculture and food supply chain: a review of basic concepts, technological implications, and future prospects. J Food Agri Envir 1: 101–106.
[5]
Rodríguez-Ramírez R, González-Córdova AF, Vallejo-Cordoba B (2011) Review: Authentication and traceability of foods from animal origin by polymerase chain reaction-based capillary electrophoresis. Ana Chim Acta 685: 120–126.
[6]
Loftus R (2005) Traceability of biotech-derived animals: application of DNA technology. Rev Sci Tech Oie 24: 231–242.
[7]
Ogden R (2008) Fisheries forensics: the use of DNA tools for improving compliance, traceability and enforcement in the fishing industry. Fish Fish 9: 462–472.
[8]
Cirillo A, Del Gaudio S, Di Bernardo G, Galderisi U, Cascino A, et al. (2009) Molecular characterization of Italian rice cultivars. Eur J Food Res Tech 228: 875–881.
[9]
Maldini M, Marzano FN, Fortes GG, Papa R, Gandolfi G (2006) Fish and seafood traceability based on AFLP markers: Elaboration of a species database. Aquaculture 261: 487–494.
[10]
Liu ZJ, Cordes JF (2004) DNA marker technologies and their applications in aquaculture genetics. Aquaculture 238: 1–37.
[11]
Weber JL, May PE (1989) Abundant class of human DNA polymorphisms which can be typed using the polymerase chain-reaction. Am J Hum Genet 44: 388–396.
[12]
Yue GH, Beeckmann P, Bartenschlager H, Moser G, Geldermann H (1999) Rapid and precise genotyping of porcine microsatellites. Electrophoresis 20: 3358–3363.
[13]
Glover KA, Hansen MM, Lien S, Als TD, H？yheim B, et al. (2010) A comparison of SNP and STR loci for delineating population structure and performing individual genetic assignment. BMC Genet 11: 2.
[14]
Liu Z (2011) Next generation sequencing and whole genome selection in aquaculture. New York: Wiley.
[15]
FAO (2010) The State of World Fisheries and Aquaculture – 2010 (SOFIA). Roma: FAO.
[16]
Glover KA, Skilbrei OT, Skaala ？ (2008) Genetic assignment identifies farm of origin for Atlantic salmon Salmo salar escapees in a Norwegian fjord. ICES J Mar Sci 65: 912–920.
[17]
Glover KA, Hansen MM, Skaala ？ (2009) Identifying the source of farmed escaped Atlantic salmon (Salmo salar): Bayesian clustering analysis increases accuracy of assignment. Aquaculture 290: 37–46.
[18]
Glover KA (2010) Forensic identification of fish farm escapees: the Norwegian experience. Aquaculture Environment Interactions 1: 1–10.
[19]
Glover KA (2008) Genetic characterisation of farmed rainbow trout in Norway: intra-and inter-strain variation reveals potential for identification of escapees. BMC Genet 9: 87.
[20]
Hayes B, Sonesson AK, Gjerde B (2005) Evaluation of three strategies using DNA markers for traceability in aquaculture species. Aquaculture 250: 70–81.
[21]
Hansen MM, Kenchington E, Nielsen EE (2001) Assigning individual fish to populations using microsatellite DNA markers. Fish Fish 2: 93–112.
[22]
Sargent JR, Bell JG, McGhee F, McEvoy J, Webster JL (2001) The nutritional value of fish. In: Kestin SC, Warriss PD, editors. Farmed Fish Quality. Oxford, United Kingdom: Fishing News Books, Blackwll Science Ltd. pp. 3–12.
[23]
Shearer KD (2001) The effect of diet composition and feeding regime on the proximate composition of farmed fishes. In: Kestin SC, Warriss PD, editors. Farmed Fish Quality. Oxford, United Kingdom: Fishing News Books, Blackwll Science Ltd. pp. 31–41.
Yue G, Li Y, Orban L (2001) Characterization of microsatellites in the IGF-2 and GH genes of Asian seabass (Lates calcarifer). Mar Biotechnol 3: 1–3.
[26]
Yue GH, Li Y, Chao TM, Chou R, Orban L (2002) Novel microsatellites from Asian sea bass (Lates calcarifer) and their application to broodstock analysis. Mar Biotechnol 4: 503–511.
[27]
Zhu ZY, Wang CM, Lo LC, Feng F, Lin G, et al. (2006) Isolation, characterization, and linkage analyses of 74 novel microsatellites in Barramundi (Lates calcarifer). Genome 49: 969–976.
[28]
Wang CM, Lo LC, Zhu ZY, Pang HY, Liu HM, et al. (2011) Mapping QTL for an adaptive trait: the length of caudal fin in Lates calcarifer. Mar Biotechnol 13: 74–82.
[29]
Wang CM, Zhu ZY, Lo LC, Feng F, Lin G, et al. (2007) A microsatellite linkage map of barramundi, Lates calcarifer. Genetics 175: 907–915.
[30]
Yue GH, Zhu ZY, Lo LC, Wang CM, Lin G, et al. (2009) Genetic variation and population structure of Asian seabass (Lates calcarifer) in the Asia-Pacific region. Aquaculture 293: 22–28.
[31]
Zhu ZY, Lin G, Lo LC, Xu YX, Feng F, et al. (2006) Genetic analyses of Asian seabass stocks using novel polymorphic microsatellites. Aquaculture 256: 167–173.
[32]
Wang CM, Lo LC, Zhu ZY, Yue GH (2006) A genome scan for quantitative trait loci affecting growth-related traits in an F1 family of Asian seabass (Lates calcarifer). BMC Genomics 7: 274.
[33]
Wang CM, Lo LC, Zhu ZY, Lin G, Feng F, et al. (2008) Estimating reproductive success of brooders and heritability of growth traits in Asian seabass using microsatellites. Aqua Res 39: 1612–1619.
[34]
Yue GH, Orban L (2005) A simple and affordable method for high-throughput DNA extraction from animal tissues for polymerase chain reaction. Electrophoresis 26: 3081–3083.
[35]
Zhu ZY, Wang CM, Lo LC, Lin G, Feng F, et al. (2010) A standard panel of microsatellites for Asian seabass (Lates calcarifer). Anim Genet 41: 208–212.
[36]
Lewis PO, Zaykin D (2000) Genetic Data Analysis: Available: http://hydrodictyon.eeb.uconn.edu/people？/plewis/software.php.Accessed on 2012 Jun 28.
[37]
Goudet J (1995) FSATA (vers.1.2): a computer program to calculate F-statistics. J Herd 85: 485–486.
[38]
Kalinowski ST, Taper ML, Marshall TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol Ecol 16: 1099–1106.
[39]
Excoffier L, Laval G, Schneider S (2005) Arlequin ver. 3.0: An integrated software package for population genetics data analysis. Evolut Bioinfo 1: 47–50.
[40]
Banks M, Eichert W (2000) Computer note. whichrun (version 3.2): a computer program for population assignment of individuals based on multilocus genotype data. J Herd 91: 87–89.
[41]
Piry S, Alapetite A, Cornuet JM, Paetkau D, Baudouin L, et al. (2004) GENECLASS2: a software for genetic assignment and first-generation migrant detection. J Herd 95: 536–539.
[42]
Banks MA, Eichert W, Olsen JB (2003) Which genetic loci have greater population assignment power? Bioinformatics 19: 1436–1438.
[43]
Fan B, Chen Y, Moran C, Zhao S, Liu B, et al. (2005) Individual-breed assignment analysis in swine populations by using microsatellite markers. Asian Austral J Anim Sci 18: 1529.
