Comparison of RAPDs, AFLPs and SSR markers for the genetic ...

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566 crossing-over in meiosis. In our study,the microsatellite analysis yielded nearly twice as much information as the AFLP markers,and three times more information than the RAPDs. This high level of polymorphism provided by the SSR technique is similar to that reported in other comparative studies (in soybean, Powell et al.,1996; in maize, Pejic et al.,1998; inMusa, Crouch et al.,1999; in table grapes, Cenı´ sandSa´ nchez Escribano,1999). The Assay Efficiency Index (Ai),or the ENA identified per assay,is of particular interest,as it combines the ENA identified per locus and the number of polymorphic bands detected per assay. For our study, this index allowed us to compare techniques that detect multiple alleles and one or two bands per assay,such as SSR analysis,with techniques that detect two alleles and multiple bands per assay,such as RAPD and AFLP analysis. The highest value of Ai was obtained by the AFLP method,with 4.0,compared with 3.4 for SSRs ARTICLE IN PRESS F. Javier Gallego et al. / Food Microbiology 22 (2005) 561–568 1a 2a 6a 69 1a 2a 6a 7a 8a 9a 6s 8s 3a 2n 5a 4n 7s 5n 8n 7n 6n 9n 1n 3n 3s 5s 4a 2s 9s 4s 1s 53 61 75 7a 8a 9a 3a 5a 4a 1s 4s 9s 7n 9n 2n 8n 1n 3n 6n 4n 5n 2s 7s 3s 6s 8s 5s 0.988 0.991 0.994 0.997 1.000 0.975 0.981 0.987 0.994 1.000 (a) (b) 1a 6a 7a 50 87 66 90 1a 6a 7a 9a 8a 2a 4a 1s 9s 2s 4s 6s 8s 5a 1n 2n 3n 6n 9n 3a 3s 4n 5n 8n 7s 7n 5s 98 54 88 99 76 8a 9a 2a 5a 3a 4a 4s 9s 2s 1s 6s 8s 1n 3n 6n 9n 2n 4n 5n 8n 7s 7n 5s 3s 0.234 0.425 0.617 0.808 1.000 0.964 0.973 0.982 0.991 1.000 (c) (d) Fig. 4. Dendrograms showing the clustering of the 27 Sacharomyces cerevisiae strains in this study. Dendrograms were created using (a) RAPD analysis (b) AFLP analysis,(c) SSR analysis,and (d) the combination of the three marker types. The numbers at the forks indicate the percentage of a group’s occurrence in a bootstrap resampling of 1000 trees. and 2.1 for RAPDs,in agreement with the results obtained by other authors (in maize, Pejic et al.,1998). This is due to the simultaneous detection of a large number of polymorphic bands per assay unit by AFLP markers. Based on the above results,it appears that microsatellite analysis is capable of revealing the highest level of information per single marker,whereas AFLP markers can detect the highest number of polymorphisms in a single assay. However,the Assay Efficiency Index can be experimentally modified,and will increase in the case of SSR analysis if multiplex PCR is adopted. In this particular study,two types of multiple PCR reactions were used,each permitting the amplification of three loci. As a result,the number of assay units decreased from six to two,in turn causing Ai to increase from 3.4 to 10.2 for microsatellite analysis. Thus,SSR markers obtained the highest value for Ai,making them
the most efficient markers in the study. This value may rise even higher if attempts to optimize this technique into a single multiple reaction involving all six microsatellites prove successful. Another important factor to consider when evaluating marker efficiency is the ability to determine relationships between yeast strains based on an estimation of genetic similarity (Figs. 4a–c). Genetic similarity coefficients were obtained (Table 3) for all three PCR-derived techniques,reflecting the extreme variability and high resolving power of these methods. These same results, including lower similarity estimates for SSR analysis than for both RAPDs and AFLPs,have been reported in equivalent studies performed using other organisms (in soybean, Powell et al.,1996; in maize, Pejic et al., 1998; in Musa, Crouch et al.,1999). These findings suggest that differences exist between a technique that amplifies unique sequences,such as microsatellite analysis,and other methods that amplify multiple sequences,such as RAPD and AFLP techniques. Poor correlation between estimates of genetic similarity based on the three different techniques evaluated in this study indicates that these methods may selectively screen for different regions of the genome. To further explore this issue,as well as the close similarity between the strains assayed,a greater number of loci should be analysed. In an effort to increase the integrity of our analysis,a single dendrogram was constructed that combines the information obtained from all three marker types (Fig. 4d). This genetic tree revealed that only the topology of some groupings is conserved,with non-significant groups appearing random regardless of the number of markers studied. Further physiological experimentation is needed in order to determine if the conserved groups are correlated with traits of interest. Based on the results of this study,RAPD markers were the least polymorphic markers of those evaluated, and consequently had the least resolving power. Although the amount of variability detected with RAPD analysis is dependent upon the selection of appropriate primers,this method has the advantage of being inexpensive and simple to perform,and does not require a previous knowledge of the genome. Problems with reproducibility have plagued the use of this technique in the past,due to the low temperature of the hybridization of the primers. However,we were able to limit these problems in this study,as evidenced by the results of our duplicate analysis,by careful DNA preparation,strict adherence to amplification protocols and a rigorous interpretation of the results. The AFLP technique resulted in high resolution and good reproducibility in this study,a finding substantiated by the recent use of AFLP markers in the identification and intraspecific differentiation of S. cerevisiae strains (deBarros Lopes et al.,1999). This technique,however,is much more technically complex ARTICLE IN PRESS F. Javier Gallego et al. / Food Microbiology 22 (2005) 561–568 567 than the use of SSR markers,requiring numerous experimental steps at a higher cost per informative marker. Despite these limitations,the AFLP technique has great value as a tool for use in genetic mapping and evolutionary studies,as it can test a large number of loci distributed randomly throughout a genome. Unlike microsatellites,AFLP markers are not highly variable, providing a less biased estimate of population variability. SSR analysis revealed the highest genetic variability in the microbial population studied,also achieving the greatest discriminatory power. It also proved to be the most efficient method,with the highest number of effective alleles per assay. We also found the results of SSR to be faster and easier to interpret than the other techniques studied,making it an ideal technique for use in the characterization and identification of S. cerevisiae strains. Successful SSR analysis,however,depends on the proper design and synthesis of primers,requiring a considerable amount of effort in the selection of polymorphic microsatellites that afford specific amplifications. Our study benefited from an available panel of six microsatellite loci and the appropriate primers needed for its specific amplification (Pe´ rez et al.,2001). In summary,SSR amplifications is a simple and effective method,with a high degree of discrimination and reproducibility,that can be used in the identification and intraspecific differentiation of S. cerevisiae strains,a species of great importance in industrial fermentations. Acknowledgments This research was supported by grants SC94-126 from the Programa Sectorial I+D Agrario y Alimentario and RM00-001 from the Accio´ n Estratégica ‘‘Conservacio´ n de los recursos gene´ ticos de interés agroalimentario’’ del Plan Nacional de Investigacio´ n Cientı´ fica,Desarrollo e Innovacio´ n Tecnolo´ gica (I+D+I) from the Instituto Nacional de Investigacio´ n y Tecnologı´ a Agraria y Alimentaria (INIA) (Spain). References Cenı´ s,J.L.,Sánchez Escribano,E.M.,1999. Evaluación de cuatro te´ cnicas genéticas de identificación (isoenzimas,RAPDs,microsate´ lites y AFLPs) en variedades de uva de mesa. In: Identificación molecular de germoplasma de vid. Jornadas de Agronomía. IMIA, Comunidad de Madrid,pp. 129–144. Crouch,J.H.,Crouch,H.K.,Constandi,H.,Van Gysel,A.,Breyne,P., Van Montagu,M.,Jarret,R.L.,Ortiz,R.,1999. Comparison of PCR-based molecular marker analyses of Musa breeding populations. Mol. Breed. 5,233–244. deBarros Lopes,M.,Soden,A.,Henschke,P.A.,Langridge,P.,1996. PCR differentiation of commercial yeast strains using intro splice site primers. Appl. Environ. Microbiol. 62,4514–4520.
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