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Genetics and Molecular Biology

Print version ISSN 1415-4757On-line version ISSN 1678-4685

Genet. Mol. Biol. vol.30 no.1 São Paulo  2007 



Intraspecific differentiation of Chilean isolates of the entomopathogenic fungi Metarhizium anisopliae var. anisopliae as revealed by RAPD, SSR and ITS markers



Viviana Becerra VelásquezI; Mario Paredes CárcamoI; Carmen Rojo MeriñoI; Andrés France IglesiasII; Jorge Franco DuránIII

IGenetic and Plant Breeding Department, Instituto de Investigaciones Agropecuarias, INIA Quilamapu, Chillán, Chile
IIAgronomy Department, Instituto de Investigaciones Agropecuarias, INIA Quilamapu, Chillán, Chile
IIIDepartment of Biometrics, Statistics and Computer Sciences, Facultad de Agronomía, Universidad de la República, Montevideo, Uruguay

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The genus Metarhizium consists of a diverse group of asexual entomopathogenic fungi, which have a wide geographical distribution. The Chilean National Agricultural Research Institute (Instituto de Investigaciones Agropecuarias - INIA, Quilamapu Chile) has collected about 350 isolates of Metarhizium anisopliae var. anisopliae from central and southern Chile. These isolates have been partially characterized using morphological traits such as conidia size and shape, colony color, growth pattern and the efficiency of the isolates in controlling specific pests. However, further characterization with molecular markers could detect differences in DNA which could help to better understand the genetic diversity and structure of Chilean populations of this fungus. We analyzed approximately 10% of the INIA collection (39 isolates selected at random) collected from different geographical origins using the polymerase chain reaction (PCR)-random amplified polymorphic DNA (RAPD) method, simple sequences repeat (SSR or microsatellites) analysis and the PCR-restriction fragment length polymorphism (RFLP) assay of internal transcribed spacer (ITS)-rDNA sequences. The RAPD data revealed high genetic diversity in this fungus and an average of 41% of similarity while SSR analysis detected 45.2% similarity and the ITS markers 70.2% similarity. For the three molecular markers, this diversity was not associated with the geographical origin of these isolates.

Key words: Metarhizium, genetic diversity, RAPD, SSR, ITS markers.




Entomopathogenic fungi are an attractive alternative for the biological control of insect pests, mainly because they are safer for plants, animals and the environment relative to conventional pesticides (Khetan, 2001). Furthermore, such fungi have also been evaluated as biological control agents for more than 200 economically important insects species (Tanada and Kaya, 1993; Maurer et al., 1997; Zurek and Keddie, 2000). Since 1996, the Insect-Pathology Program at the Chilean National Agricultural Research Institute (Instituto de Investigaciones Agropecuarias - INIA, Quilamapu, Chile) has collected over 1000 isolates of entomopathogenic fungi from throughout the Chile, with about 350 isolates having been classified as Metarhizium anisopliae var. anisopliae (Guerrero et al., 1999; France et al., 2000) according the parameters described by Humber (1997) and Alves (1998). This germplasm is important, since Chile's ecological conditions show contrasting climates varying from hot and dry areas in the North to the very wet and cold areas near the Antarctic in the South. Preliminary research has indicated that many of these isolates show promising pathogenicity against important Coleoptera insect pests (France et al., 2000).

Several kinds of molecular techniques have been used to study genetic diversity, for example, labeled probes to detect restriction fragment length polymorphism (RFLP) (Hegedeus and Khachatourians, 1993; Maurer et al., 1997) and methods based on the polymerase chain reaction (PCR) such as the use of random amplified polymorphic DNA (RAPD) (Fegan et al., 1993; Bidochka et al., 1994; Piatti et al., 1998; Freire, 2001; Jensen et al., 2001; Gaitan et al., 2002), simple sequences repeat (SSR or microsatellites) analysis (Kretzner et al., 2000; Enkerli et al., 2001, 2005) and internal transcribed spacer (ITS)-rDNA sequence RFLP analysis (Rakotonirainy et al., 1994; Buscot et al., 1996; Coates et al., 2002a). Even though they have different and complementary discriminatory power RAPD, SSR and RFLP analysis have been very effective in detecting genetic diversity in several species (Couteaudier et al., 1998; Glare and Inwood, 1998; Coates et al., 2002b; Enkerli et al., 2005). In Chile, however, there has been no previous molecular characterization of entomopathogenic fungi populations.

The PCR technique combined with RAPD analysis (Welsh and McClelland, 1990; Williams et al., 1990) has been extensively used to determine the genetic diversity of various entomopathogenic fungi (Cobb and Clarkson, 1993; Bidochka et al., 1994; Neuvéglise et al., 1994; Neuvéglise and Brygoo, 1994; Bidochka et al., 1995; Hodge et al., 1995; Fungaro et al., 1996; Maurer et al., 1997) including Metarhizium (Fegan et al., 1993; Leal et al., 1994) and to relate genetic diversity to pathogenicity index (Bridge et al., 1997) and to identify strains (Milner et al., 2002).

More recently, SSR markers have been used as powerful molecular markers for the study of the population genetics of fungi (Coates et al., 2002a; Enkerli et al., 2001; 2005), SSR markers being particularly useful because they are highly polymorphic (multi-allelic) between strains due to the variation of the number of repeats, co-dominant and highly reproducible compared with other markers. The main disadvantage of SSR markers is that the development of primers is time-consuming and expensive, but this can be offset by the fact that transferability of primer sequences within genera is high and allows primers to be shared between laboratories.

Nuclear ribosomal RNA sequences, especially the two internal transcribed spacers (ITS1 and ITS2), have demonstrated differential rates of nucleotide changes that allow intra-specific comparison of fungi (Neuveglise et al., 1994; Buscot et al., 1996). The treatment of PCR-amplified DNA fragments with restriction endonucleases forms the basis of the RFLP technique which has been used to investigate the inter and intraspecific diversity of the ITS sequences of entomopathogenic fungi (Coates et al., 2002 b). Shih et al. (1995) reported a moderate level of mutation in the ITS1 region of Beauveria bassiana, although ITS2 was invariant for in this specie. However, Beauveria brongniartii isolated from a single host showed higher ITS2 sequence variation (Neuveglise and Brygoo, 1994) and at least 5 RFLPs have been detected among Beauveria species (Neuveglise et al., 1994; Glare and Inwood, 1998) for the ITS regions, considered to be a well-conserved sequence.

The objectives of this study were to determine the level of genetic diversity in a core sample of Chilean isolates of Metarhizium anisopliae var anisopliae using several molecular markers and to evaluate different molecular markers which are suitable for the genetic fingerprinting of this enthomopathogen.


Material and Methods

Fungal strains and DNA extraction.

We investigated 39 of the approximately 350 Metarhizium anisopliae var. anisopliae (France et al., 2000) isolates collected from different geographic hosts and regions of Chile and maintained in the Chilean National Agricultural Research Institute (Instituto de Investigaciones Agropecuarias - INIA, Quilamapu, Chile) collection, details of the strains investigated being shown in Table 1.

Monosporic cultures of the fungi were obtained by plating multisporic isolates onto Petri plates containing potato dextrose agar (PDA: containing (gL-1) Dextrose, 20; Potato extract, 20; agar, 20) and incubating the plates at 27 °C for 3 days and then cultivating single spore colonies in Sabouraud media: containing (gL-1) Peptone, 10; Dextrose, 40; agar, 20; supplemented with 1% (w/v) of yeast extract (Difco, France) to produce mycelium for DNA extraction.

For each fungal isolate, about 50 mg of mycelium was homogenized in DNA extraction buffer (100 mM Trizma; 1.4 M NaCl; 20 mM EDTA; 1% polyvinylpyrrolidone; 2% cetyltrimethylammonium bromide (CTAB); 1% mercaptoethanol; 10 mg/mL proteinase K; pH 8.0) and incubated for 45 min at 65 °C. After incubation the mixture was extracted twice with 24:1 chloroform:isoamyl alcohol, centrifuged at 3500 revs min-1 for 15 min and the DNA precipitated with isopropanol and stored at -20 °C overnight, after which the DNA was washed with 70% and 95% alcohol, dried at room temperature and re-suspended in 150 µL of TE buffer pH 8.0. The DNA concentration was measured with a fluorometer and the DNA stock solutions kept at -80 °C until needed. All percentages w/v.

RAPD analysis

For each isolate, PCR-RAPD of the extracted DNA was performed in a PTC-220 thermocycler (Dyad MJ Research) for 40 cycles of 35 s at 94 °C, 35 s at 40 °C and 1 min at 72 °C, and a final additional 10 min cycle at 72 °C. Reactions were carried out in a total volume of 25 µL containing 0.2 µM of dNTPs, 0.2 µM of the primer, 1x PCR amplification buffer, 0.3 mM of MgCl2, 1 U Taq DNA Polymerase (Invitrogen) and 25 hg of DNA template and ultrapure water. Reactions were done twice to evaluate the consistency of the banding patterns for all isolates studied.

Products were separated on a 1.5% (w/v) agarose gel in 1x TAE buffer (40 mM Tris acetate, 1 mM EDTA, pH 8.0) at 100 V for 3.5 h. The gels were stained with ethidium bromide and visualized with UV light using a Cole Palmer FLUO-LINK FLX apparatus and photographed for later evaluation.

A pre-screening of eight M. anisopliae isolates with 64 primers from the OPA-A, OPA-B, OPA-M, OPA-C, OPA-AD and OPA-AB series (Operon Technologies, California, USA) was performed to select the most informative primers. For the final evaluation of the 39 isolates we selected 20 primers (OPA-03, 04, 08, 09, 10, 11, 12, to 13; OPC-01; OPD-02, 03, 07, 08, 13, 17 and18; and OPAB-03, 04, 09 and 11).

SSR analysis

The same 39 isolates were analyzed with 12 SSR primers (Ma097, 099, 142, 145, 164, 165, 195, 210, 307, 325, 327 and 375) (Enkerli et al., 2005). The PCR reactions were performed in a PTC-220 thermocycler using 10 hg of genomic DNA from each isolate, 1x PCR buffer, 0.2 µM of dNTPs, 2.5 mM MgCl2, 200 µM of forward and reverse primers, and 0.5 U Taq DNA polymerase (Invitrogen). Amplification started with an initial step of 4 min at 95 °C, followed by 38 cycles of 1 min at 95 °C, 1 min at 50 °C (44 ° or 56 °C depending on the primer set) and 1 min at 72 °C, with a final 4 min extension at 72 °C. Products were separated on 6% denaturing polyacrylamide gel in 1 x TBE buffer at 1800 V for about 2 h. The DNA fragments were stained with silver nitrate and the fragment sizes determined based on internal and external size standards. The Ma307 and Ma325 primers did not amplify.

ITS analysis

Oligonucleotide primers ITS1, ITS2, ITS3, ITS4 and ITS5 were used for ITS PCR-amplification (White et al., 1990). The PCR reactions were carried out in a PTC-220 thermocycler using a total volume of 25 µL containing 0.2 µM of dNTPs, 0.2 µM of the ITS forward and reverse primers, 1xPCR amplification buffer, 0.25 mM of MgCl2, 1 U Taq DNA Polymerase (Invitrogen) and 25 hg of DNA template and an initial amplification step of 3 min at 94 °C, followed by 35 cycles of 30 s at 94 °C, 40 s at 57 °C, and 20 min at 72 °C. Restriction of the PCR products was carried out according to the manufacturer's instructions using the following endonucleases: Acc I, Alu I, Dde I, Eco RI, Eco RV, Hae III, Hha I, Hinf III, Hpa II, Mbo I, MseI, Msp I, Nde II, Rsa I, Sin I, Tru 9I and Xho I. Restriction fragments were separated on 6% polyacrylamide gel (20x20) in 1x TBE buffer at 100 V for 2 h. Ethidium bromide gel staining was performed and the DNA fragments visualized under UV light, the molecular weights of the fragments being determined by comparison with a 100 bp DNA ladder using the 1D Image Analysis program (Kodak digital system).

Data analysis

For each marker, polymorphic bands were considered as binary characters and scored as present (1) or absent (0). Genetic similarity between pairs was estimated using Jaccard's coefficient with the SIMQUAL option. The similarity matrix was run on sequential, agglomerative, hierarchical and nested clustering (SAHN) (Sneath and Sokal, 1973) using the unweighted pair-group method with arithmetic average (UPGMA) clustering algorithm to generate a dendrogram. The COPH option was used to generate a matrix of cophenetic values which was used in the MXCMOP option to calculate the correlation between the cophenetic matrix and the original SIMQUAL matrix. This analysis measured goodness-of-fit under 1000 permutations and provided a cophenetic correlation value (r). A cophenetic correlation value of r 0.9 is considered a very good fit according to Mantel (1967). All computations were undertaken using the NTSYSpc 2.1 program (Rohlf, 2000).

For SSR analysis, based on the allelic profile, the PowerMarker program (Liu and Muse, 2005) was used to calculate the number of alleles per locus, gene diversity (He) and the polymorphic information content (PIC). For ITS analysis, genotypes were determined by using gel fragment patterns of different primer-restriction enzyme combinations. Finally, the specific genotypes for strain identification were analyzed.

Analysis of molecular variance (AMOVA) and fixation index(Fst, q)(Weir and Cockerham 1984; Weir 1996; Excoffier et al., 2005) was calculated to clarify molecular patterns of within-population variation for the 39 isolates, collected in two main geographical areas (central and southern Chile, Table 1). All calculations were performed using Arlequin 3.01 software (Excoffier et al., 2005). The total variance was partitioned into genetic variance between/among geographical areas and among isolates within geographical areas.


Results and Discussion

RAPD analysis

The 20 RAPD primers used to analyzed the 39 isolates of M. anisopliae generated a total of 189 bands ranging from 200 bp to 1500bp, but only bands that amplified consistently over two DNA extractions and PCR experiments were used for the analysis. We found that 96.8% of the bands were polymorphic and 5 to 13 bands were obtained for each RAPD marker depending on the primer used, with an average of 9.5 bands per primer. These results agree with other RAPD studies on M. anisopliae (Leal-Bertioli et al., 2000). In our study seven primers (OPA-04, 03, 09 and 13; OPAB-09; OPC-01; and OPD-02) were the most informative, since they detected the greatest number of polymorphic bands and produced a high number of banding patterns. These primers detected 43.4% of the total polymorphic bands. The OPA-03 primer was important because it was able to discriminate the commercially available Qu-M633 isolate from the other isolates (Figure 1).



The similarity data dendrogram clustered the 39 isolates into three main clades with a general average similarity coefficient of 41.3%. Clades I and III clustered the isolates mostly collected in the southern X region, while clade II clustered isolates collected in a wider area. The dendrogram was statistically supported by a high cophenetic correlation value (r = 0.96).

Our results showed that the PCR-RAPD analysis was useful in detecting genetic variability within and between groups of isolates collected from different geographical areas. No identical genotypes were detected by these analysis (Figure 1).

The AMOVA results (Table 2) indicated that the within population variance accounted for 89.8% of the total genetic variation while the between population variance accounted for the remaining 10.2% of the variation. However, RAPD analysis did not detect any association between the genetic diversity of the isolates and the location from which the isolates were collected. The fixation index of 0.1025 suggested that little genetic differentiation had occurred between central and southern populations based on geographical distribution (Table 1 and 2).



SSR analysis

Analysis of the same 39 Chilean M. anisopliae isolates using microsatellites markers also indicated a high level of diversity in this entomopathogenic fungi. Only a couple of primers amplified the QuM-180 isolate so this isolate was not included in the analysis of the SSR data, which means that the number of isolated analyzed was 38. Of the 12 SSR primers used only ten amplified with our isolates and since 52 alleles were detected the mean number of alleles per locus was 5.2, with a range of from 2 to 9 (Table 3). These values are higher than those obtained by Enkerli et al. (2005) in populations of M. anisopliae collected in Switzerland. In our study, the Ma375 locus was the most frequent allele found in every isolate (Table 3).



The gene diversity (He) value estimates the probability that two alleles at any randomly chosen locus are different from each other, in our case the 39 isolates showed a mean He value of 0.27. The polymorphic information content (PIC) is a measure of the probability that two randomly sampled genotypes have different allelic profiles, the mean PIC value for our isolates being 0.52 (Table 3). This information indicates that our Chilean M. anisopliae isolates had a high degree of biodiversity. We detected 10 distinct M. anisopliae genotypes in populations from the Chilean central zone, of which only isolates Qu-M501, QuM-481 and QuM-436 were identical (Table 1). In populations from the Chilean southern zone we detected 16 distinct genotypes, six of which we detected in several isolates. However, in both geographical areas the number of identical genotypes were low but more diversity might have been detected if more isolates had been investigated, remembering that 38 isolates represented only about 10% of the M. anisopliae isolates in the INIA collection.

Jacard's genetic similarity coefficient gave an average similarity value of 45.2%, and separated the Chilean isolates into three major clades (Figure 2). Clades I and III clustered the isolates mostly collected in region X of the southern zone, while Clade II included isolates collected from different regions. It is important to note that both the RAPD and SSR data generated dendrograms with three well-defined clades that clustered almost the same isolates in each clade, although they had different pair-wise similarity coefficients. The dendrogram generated with the SSR data was supported statistically by a high cophenetic correlation value (r = 0.97).



The AMOVA results for the SSR data (Table 2) indicated that the within population variance accounted for 81.5% of the total genetic variation while the between population variance accounted for the remaining 18.5% of the variation. This was also reflected by the wide distribution of the isolates in the dendrogram. This low differentiation could be due to the presence of a large number of common alleles, either because the alleles co-evolved independently by mutation or they were identical by descent and distributed through gene flow as has been reported for B. brogniartti (Enkerli et al., 2001). However, this mechanism is still unclear in M. anisopliae (Enkerli et al. , 2005).

The RAPD and SSR analysis indicated that isolates Qu-M173a and Qu-M203 (both collected in the region X of the southern zone) were almost identical genetically. However, compared to RAPD analysis, SSR analysis showed a higher number of isolates to be genetically identical, probably due to the low average number of different alleles in the population studied. The SSR analysis did not detect any association between the genetic diversity of the isolates and the location from which the isolates were collected. The fixation index (Fst = 0.1847) showed that little genetic differentiation had occurred between the Central and Southern populations (Table 2).

Approximately 80% of the isolates were collected from soil samples and about 20% from larval and adult insects. Clade I contained isolate Qu-M490 collected from an adult Forticola auricularia (L.) and isolate Qu-M271 from a curculionid larva. Clade II clustered three insect-derived isolates, Qu-M982 from an adult Dichroplus maculipennis (Bl.), Qu-M253 from a Phytoloema hermanni (Herm) larva and Qu-M489a from a Otiorhynchus sulcatus (Boh.) larva. Clade III contained three insect-derived isolates, Qu-M270 from a Hylamorpha elegans (Burm.) larva, Qu-M363 from an adult Sericoides viridis and Qu-M549 from a Sericoides sp. This agrees with a previous PCR-RFLP study of B. bassiana that concluded that there is a weak association between isolate genotype and insect preference (Coates et al., 2002a), while studies on Metarhizum have shown a weak associationbetween insect host range and isolate genotype (Cobb and Clarkson, 1993; Bidochka et al., 1994).

ITS analysis

Both ITS regions resulted in a single PCR-amplification product for all isolates, while digestion of the ITS1 and ITS2 PCR-amplification products with several restriction enzymes detected several molecular differences between our M. anisopliae isolates (Figure 3). The restriction enzymes Acc I, Dde I, Eco RI, Eco RV, Nde II, Sin I, and Xho I used in this study were not able to detect restriction sites.



Digestion of ITS1 yielded the following fragments (in bp): Hha I, 170 to 90; Hinf III, 260 to 50; Msp I, 180 to 100; Alu I, 300 to 230; Hae III, 300 to 180; Rsa I, 290 to 220; and Tru 9I = 220 to 30 (Figure 3a). Digestion of ITS2 yielded the following fragments (in bp): Hinf III, 270 to 40; Msp I, 290 to 100; Tru 9I, 390 to 150; Alu I, 410 to 400; Hae III, 230 to 150; and Hha I, 180 to 70 (Figure 3b).

A total of 12 genotypes were identified by digesting the ITS1 PCR products with Hha I, Hinf III, Msp I, Tru 9I, Alu I, Hae III and Rsa I while nine genotypes were identified by digesting the ITS2 PCR products with Hha I, Hinf III, Msp I, Tru 9I, Alu I and Hae III. The higher number of restriction sites within ITS1 has been reported in other species (Kuninaga et al., 1997; Zare et al., 1999). Considering both regions together a total of 15 genotypes were identified in the 39 isolates, which were thus reduced to 15 different groups (Figure 4, Table 1). This indicates that genetic discrimination between isolates using ITS was more difficult than with RAPD or SSR. This is corroborated by a lower pair-wise similarity coefficient, which averaged 70.9% compared to those obtained by RAPD and SSR, but even so the dendrogram in Figure 4 shows four clades, with a high percentage of identical isolates within clades I, II and IV. For example, clade I contained ten isolates (25% of the total isolates) with the same genotype, mostly collected from region X of the southern zone, while clade II contained 12 isolates with identical genotypes (Figure 4). For the ITS data, the cophenetic correlation coefficient between the cophenetic matrix and the ITS1-ITS2 data matrix was 0.98, higher than for the RAPD and SSR data.



When the data was analyzed by geographical origin the central zone isolates showed six distinct genotypes while the southern zone isolates contained 13 distinct genotypes, only three of which represented multiple isolates (Table 1).With the ITS markers, as with the RAPD and SSR markers, we were, in general, unable to find any association between isolate diversity and collected location, the exceptions being the ITS Clade I isolates QU-M202 and QU-M203 collected in the X region of the southern zone (Table 1). The differences in the ITS regions detected by PCR-RFLP resulted in a fixation index (Fst = 0.1038) which indicated a low level of genetic differentiation in our M. anisopliae sample. Moreover, AMOVA showed that 89.6% of the within isolate molecular variance was and 10.4% of the total variation occurred between central and southern populations, suggesting a weak geographic origin influence on the genotype of the isolates studied.

The dendrogram generated with the combined RAPD, SSR and ITS similarity data clustered the 39 isolates into three main clades with a general average similarity coefficient of 25.1% (Figure 5). Clades I, II and III clustered the isolates from all regions. The dendrogram was supported statistically by a high cophenetic correlation value (r = 0.91). Results from AMOVA (Table 2) indicated that the within population variation accounted for the 88.2% of the total genetic variation and between population accounted for the remaining 11.8%. As was the case when the RAPD, SSR and ITS data was analyzed separately, the fixation index (Fst = 0.1176) suggested that there was little genetic differentiation between geographic areas (Table 2).



Genotype identification

When implementing biological control using entomopathogenic fungi it is very important to have an efficient system of identifying the fungal isolates used (Coates et al., 2002b) in order to measure their efficiency and detect multiple-isolate infections in the host.

In this study we found that PCR-RAPD detected a higher level of genetic diversity and was able to distinguish different entomopathogenic fungi isolates using at least four primers, but in some cases it was possible to fingerprint an isolate with only one primer. For instance, OPA-03 discriminated QU-M633 from other isolates very clearly. These results agree with previously published work in which PCR-RAPD markers were able to find a large amount of genetic variability between isolates of Entomophaga grylli pathotypes (Bidochka et al., 1995).

Allelic profiling with ten SSR markers detected 22 genotypes among the 38 isolates, isolate QuM-180 was not included in the analysis because only a few primers amplified with this isolate. The following isolates showed identical genotypes as regards the ten SSRs analyzed: Qu-M142, Qu-M271 and Qu-M283; Qu-M202 and Qu-M221b; Qu-M490 and Qu-M558; Qu-M145, Qu-M151a, Qu-M151b, Qu-M173a and Qu-M203; Qu-M159, Qu-M247, Qu-M253 and Qu-M608; Qu-M326 and Qu-M489a; and Qu-M430, Qu-M501, Qu-M553, Qu-M481 and Qu-M436. Since these loci displayed less polymorphism more SSR primers may be required to discriminate between all the genotypes. One of the reasons for this could be that the number of alleles per locus detected in the Chilean M. anisopliae isolates were not enough to have a good discrimination among isolates. In this case, a good PCR-RAPD protocol could allow us to discriminate among individuals.

The conservative nature of our ITS fingerprinting analysis meant that it was very difficult to discriminate between isolates because many of the isolates analyzed shared the same genotype. However, it is interesting to note that isolate QU-M633 was discriminated with RAPD, SSR and ITS markers.

Our results indicate that RAPD, SSR and ITS markers could be used in a complementary manner to identify specific isolates, although SSR markers have the advantage of being more reliable and easier to score than RAPD markers and therefore easier to use. However, because the cross-species transferability of SSR markers is limited (Enkerli et al., 2001) methods such as RAPD, PCR-RFLP or group I intron analysis of 28S rDNA may be advantageous over SSR markers for studies of distantly related isolates at the genus level.



The authors thank the Chilean Science and Technology Fund (FONDECYT) for supporting this research (project N° 1030037) and Macarena Gerding and Cecilia Santelices for their assistance with the entomopathogenic fungi cultures.



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Send correspondence to:
Viviana Becerra Velásquez
Genetic and Plant Breeding Department
Instituto de Investigaciones Agropecuarias
NIA Quilamapu, Casilla 426, Chillán, Chile

Received: January 19, 2006; Accepted: June 27, 2006.



Associate Editor: Márcio de Castro Silva Filho

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