Applications of AFLP and ISSR techniques in detecting genetic diversity in the soybean brown stem rot pathogen Phialophora gregata

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Mycol. Res. 105 (8) : 936–940 (August 2001). Printed in the United Kingdom.

Applications of AFLP and ISSR techniques in detecting genetic diversity in the soybean brown stem rot pathogen Phialophora gregata

Xiangqi MENG* and Weidong CHEN* Department of Crop Sciences, University of Illinois at Urbana-Champaign, and Illinois Natural History Survey, 607 East Peabody Drive, Champaign, IL 61820, USA. E-mail : w-chen7!uiuc.edu. Received 6 December 1999 ; accepted 8 February 2000.

AFLP (amplified fragments length polymorphism) and ISSR (inter simple sequence repeat) analyses were used to detect genetic diversity among 46 Phialophora gregata isolates including 41 from soybean, four from mung bean, and one from adzuki bean. Five AFLP primers amplified 55 fragments, of which 20 bands were polymorphic. Thirteen ISSR primers amplified 66 fragments, of which 45 bands were polymorphic. The ISSR technique detected more polymorphism than the AFLP technique did. A UPGMA (unweighted pair-group arithmetic mean) dendrogram was constructed based on the 121 amplified fragments with AFLP and ISSR primers to depict genetic diversity and relationships among the 46 isolates. Various levels of DNA polymorphism were detected among P. gregata isolates from soybean and mung bean. The estimated average genetic diversity is 0.079 for the population of 45 isolates from soybean and mung bean. The ISSR technique was shown to be more effective and economic than the AFLP technique in detecting genetic variation in P. gregata.

INTRODUCTION Brown stem rot (BSR) of soybean (Glycine max), caused by the soilborne hyphomycete Phialophora gregata, was first found in 1944 in Illinois, USA (Allington & Chamberlain 1948). BSR has been reported in Canada (Hidebrand 1948), Egypt (Gray 1989), Japan (Yamamoto et al. 1990), and Mexico (Morgan & Dunleavy 1966). The pathogen can cause interveinal chlorosis and necrosis on leaves or brown discoloration of the vascular and pith tissues of the stem, and blighting can be seen in the later season. The disease development was influenced by temperature (Allington & Chamberlain 1948, Gray 1973), plant age and stage of development (Gray 1973, Phillips 1972), and inoculum density (Adee et al. 1995). Two special forms of P. gregata were reported (Kobayashi et al. 1991), P. gregata f. sp. sojae infecting soybean and P. gregata f. sp. adzukicola infecting adzuki bean (Vigna angularis). BSR is an economically important soybean disease in the midwestern United States. The yield loss due to BSR can be up to 44 % under favourable conditions for the disease development (Dunleavy & Weber 1967, Mengistu & Grau 1987, Sills et al. 1991). Use of disease-resistant cultivars and crop rotation are the most practical means for BSR control.

* Corresponding author. † Present address : Department of Plant Pathology, University of California, Davis, CA 95616, USA.

Phenotypical variation among soybean isolates of P. gregata has been reported. Gray (1973) proposed type I and type II isolates based on their ability to cause BSR symptoms. Mengistu & Grau (1986) demonstrated that various levels of pathogenicity existed among 25 P. gregata isolates. Variation in sporulation, culture type, virulence and growth rate was also reported (Hamilton & Boosalis 1955, Phillips 1973). However, no information is available on genetic variation among soybean isolates of P. gregata. Knowledge of genetic variation among P. gregata isolates is useful for effective management of the BSR disease. Many molecular techniques have been used to study genetic variation in P. gregata. Genetic differences between soybean and adzuki bean isolates were detected in isozyme banding patterns (Yamamoto et al. 1990), total nuclear DNA contents, the number of repetitive DNA and AT-rich regions (Yamamoto et al. 1995), the ITS sequences (Chen et al. 1996), presence of an group I intron in the nuclear rDNA (Chen et al. 1998). However, no variation among soybean and mung bean (Vigna radiata) isolates was detected in isozyme banding patterns (Mengistu & Grau 1986, Yamamoto et al. 1990), mitochondrial DNA restriction fragment patterns (Gray & Hepburn 1992), or rDNA-ITS region sequences (Chen et al. 1996). Consequently no specific markers are available for individual strains. Ecological studies of BSR could not track individual introduced strains (Chen et al. 1999). Recently AFLP (amplified fragment length polymorphism) and ISSR (inter simple sequence repeat) markers have been

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used successfully to detect genetic variation in fungi and plants (Kantety et al. 1995, Mueller et al. 1996, Godwin et al. 1997, O’Neill et al. 1997). Both AFLP and ISSR techniques have been demonstrated to be reproducible and effective molecular markers. In this study, we analysed a collection of 46 P. gregata isolates using the AFLP and ISSR techniques. The objective of this study was to determine the effectiveness of AFLP and ISSR techniques in detecting genetic variation among P. gregata isolates from soybean.

cultures were grown on green bean broth (25 grams of frozen green bean blended in 500 ml distilled water, and filtered through four layers of cheesecloth, with a final volume of 1000 ml) for 14 d at 18 to 20 mC. Mycelia were harvested by vacuum filtration through Whatman No. 1 filter paper. The harvested mycelia were either used immediately for DNA extraction or stored at k70 m until use. DNA was isolated as described previously (Chen et al. 1992). Representative isolates have been deposited at the American Type Culture Collection (ATCC) under nos ATCC 96387, 204450, and 204451.

MATERIALS AND METHODS AFLP and ISSR

Fungal isolates, culture conditions, and DNA isolation The 46 Phialophora gregata isolates used in this research were predominantly isolated from soybean from midwestern United States (Table 1). The single isolate A8 from adzuki bean from Japan belongs to P. gregata f. sp. adzukicola and was used as an outgroup. The remaining 45 isolates from mung bean and soybean belong to P. gregata f. sp. sojae. For DNA isolation,

Table 1. Grouping of the 46 isolates of Phialophora gregata by host and geographic location. Host

Geographic location

Number of isolates*

Adzuki bean Mung bean Soybean

Japan Illinois, USA Illinois, USA Indiana, USA Iowa, USA Ohio, USA Wisconsin, USA

1 4 7 2 1 1 30 46

Total * Isolate codes are presented in Fig. 3.

The PCR conditions were optimized for both AFLP and ISSR analyses. The different concentrations of DNA and MgCl # and different batches of fungal genomic DNA had no differences in AFLP and ISSR banding patterns for the same isolate and primer combination. Fungal genomic DNA of each isolate was PCR-amplified at least twice and upto ten times. Only major reproducible amplicons were used for data analysis. The procedure for AFLP was modified from that of Mueller et al. (1996). Fungal genomic DNA digestion and ligation to adapters were conducted simultaneously at 37 m for 4 h in a volume of 20 µl containing 2 µg fungal DNA, 20 units Pst1 (GIBCO–BRL) 0.2 µg adapters, 1 unit T4 DNA ligase, 0.5 m ATP, 10 m Tris-HAc (pH 7.5), 10 m MgAc, 50 m potassium acetate, and 2 m dithiotreitol using the following Pst1 adapter : 5h ctcgtagactgcgtacatgca 3h 3h gagcatctgacgcatgt 5h After DNA digestion and ligation, 10 µl ammonium acetate (7.5 ) and 60 µl pre-cold ethanol (70 %) were added and centrifuged at 14 000 rpm for 10 min and the supernatant was

Table 2. The DNA fragments of Phialophora gregata isolates amplified with AFLP and ISSR primers.

Primers

Sequence*

Polymorphic fragments

Total number of fragments

Size range (bps)

AFLP2 AFLP3 AFLP4 AFLP6 AFLP7

gactacgtacatgcagca gactacgtacatgcagga gactacgtacatgcaggg gactacgtacatgcaggt gactacgtacatgcagct AFLP Subtotal caccaccaccaccac gtggtggtggtggtg ggatggatggatggat ggatggatggatggat cacacacacacacacaa cacacacacacacacag gtgtgtgtgtgtgtgta gtgtgtgtgtgtgtgtc tctctctctctctctcc tctctctctctctctcg ctctctctctctctctRc ctctctctctctctctRg acacacacacacacacYg ISSR Subtotal Total

3 5 5 3 4 20 4 4 4 1 1 2 2 1 3 5 4 10 4 45 65

10 9 12 10 14 55 5 6 6 3 6 3 5 2 3 5 5 12 5 66 121

537–2036 510–2036 506–1836 450–1636 600–1536

ISSR003 ISSR004 ISSR007 ISSR815 ISSR817 ISSR818 ISSR819 ISSR820 ISSR823 ISSR824 ISSR844 ISSR845 ISSR857

* R l purines, ‘ g ’ or ‘ a ’ ; Y l pyrimidines, ‘ c ’ or ‘ t ’.

396–1836 340–1218 334–1018 767–1018 490–818 298–918 406–1018 506–1018 406–1736 767–2636 368–1636 500–1436 190–817

DNA polymorphism in Phialophora gregata

Data analysis The first approach was based on discrete characters. Each amplicon was considered as a character and each character had two possible states of presence (coded as 1) and absence (coded as 0). Only major amplicons were counted. A binary data matrix (121 DNA ampliconsi46 isolates) was formed. Dice similarity (Sd) was calculated for each pair of isolates as Sd l 2Nxy\(NxjNy), where Nx and Ny are the number of amplicons in isolates X and Y, respectively, and Nxy is the number of positive amplicons shared by the two isolates (0–0 matches excluded) (Rohlf 1990). This is mathematically the same as the formula for the fraction of DNA bands shared by two individuals (Hartl & Clark 1989). Cluster analysis with the unweighted pair group method with an arithmetic average (UPGMA) algorithm was performed using NTSYS-PC (Rohlf 1990) to produce a dendrogram. The second approach was based on allelic frequencies. Each amplicon produced by both AFLP and ISSR techniques was considered as a putative locus containing two possible alleles (positive and null). Nei’s measure of gene diversity of each locus was calculated for the population. Genetic diversity is defined as the probability that two randomly chosen alleles from a population will be different and is given by the formula H l 1kPi#, where Pi is the frequency of the i-th allele. RESULTS AND DISCUSSION Genetic variation was detected among 46 P. gregata isolates using both AFLP and ISSR techniques. Of eight designed AFLP primers screened, three primers (AFLP 1, 5, and 8) did not amplify any polymorphic fragments, but the other five primers (AFLP 2, 3, 4, 6, and 7) amplified 55 fragments

AS1–2

A8

IN6

IN5

ABS2–4

HS3–4

AS4–4

PG8

OH2

1KB 2036 bp 1636 bp 1018 bp

517 bp 506 bp

IN6

AS4–4

HS4–3

ABS3–4

HS3–4

AA3–1

G3

A8

OH2

Fig. 1. AFLP banding patterns on 10 % polyacrylamide gel of nine Phialophora gregata isolates amplified with primer AFLP7, after staining with ethidium bromide. Isolate designations are indicated on top of the gel. 1 KB l GIBCO–BRL 1 Kb DNA ladder with fragment sizes indicated on the left. The four polymorphic amplicons are indicated with arrows.

1KB

discarded. The DNA was dried and resuspended in 100 µl 1iTE buffer before use for PCR. PCR amplification was conducted using 10–20 ng ligated DNA, 2 µl 10iPCR buffer, 1.5 m MgCl , 0.25 unit Taq # DNA polymerase (GIBCO–BRL, USA), 0.05 m dATP, dGTP, dCTP, and dTTP, 0.25 m primer in a volume of 20 µl. Each of eight AFLP primers was designed based on the Pst1 adapter sequence with two base extensions, cc, ca, ga, gg, gc, gt, ct, and cg, and was named as AFLP1, 2, 3, 4, 5, 6, 7, and 8, respectively (Table 2). The thermal cycling parameters for PCR amplification were one cycle of 3 min at 94 m, 1 min at 55 m, and 2 min at 72 m followed by 40 cycles of 45 s at 94 m, 45 s at 55 m, and 1 min at 72 m. ISSR primers used in this research were the Microsatellite set F9 from the Biotechnology Laboratory, University of British Columbia, Canada. The PCR amplification volume, reagents, and profile were the same as those used for AFLP, except that total genomic DNA was used for PCR. All the amplicons produced by AFLP and ISSR were separated by electrophoreses on 1.5 % agarose (Midwest Scientific, St Louis, MO) and 10 % polyacrylamide gels (FMC BioProducts, Rockland, ME). The gels were either stained with ethidium bromide, visualized over  light, and photographed or stained with AgNO using Silver Sequence DNA Staining $ Reagents (Promega Corporation, WI).

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3054 bp 2036 bp 1636 bp 1018 bp

Fig. 2. ISSR banding patterns on 10 % polyacrylamide gel of nine Phialophora gregata isolates amplified with primer ISSR824, after staining with AgNO . Isolate designations are indicated on top of $ the gel. 1 KB l GIBCO–BRL 1 Kb DNA ladder with fragment sizes indicated on the left.

ranging in size from about 450–2036 bps, of which 20 fragments were polymorphic (Fig. 1, Table 2). Of 90 ISSR primers screened, thirteen primers amplified 66 fragments ranging in size from about 190–2636 bps, of which 45 fragments were polymorphic (Fig. 2, Table 2). The frequency of polymorphic fragments of ISSR (68.2 %) was larger than that of AFLP (36.4 %). The amplicons generated by the primers that did not show polymorphisms were excluded from the analyses. Although variation in P. gregata has been previously reported among soybean isolates in morphology, cultural characters, and pathogenicity (Gray 1973, Hamilton & Boosalis 1955, Mengistu & Grau 1986, Phillips 1973), several molecular techniques including isozyme analysis (Mengistu & Grau 1986, Yamamoto et al. 1990), RFLP of mtDNA (Gray & Hepburn 1992), nuclear rDNA (Chen et al. 1996, 1998, Harrington et al. 2000) did not detect any polymorphism within soybean isolates of P. gregata. In this study, we showed that the AFLP and ISSR techniques are more sensitive in detecting genetic variation than the previously used techniques and can be used to effectively detect genetic variation among

X. Meng and W. Chen

939 OH2 BSR101 H96–1 H96–2 H96–3 H96–4 H96–5 H96–6 H96–7 H96–8 C101–5 PG6–3 HB3–5 PG7 PG18 I16 K3 LM4 AR1 C101–2 H101–5 H101–4 PG8 PG20 PG16 MBU3 IN6 G3 IN5 MBU2 A101–1 H101–3 AA4–3 HS2–2 MBU11 AA3–1 HB1–2 AB3–4 ABS2–4 PG21 AS1–2 HS4–3 HS3–4 AS4–4 AS2–4 A8

0.70

0.75

0.80

0.85 0.90 Dice similarity

0.95

1.00

Fig. 3. Dendrogram depicting the genetic variation and relationships among the 46 Phialophora gregata isolates, based on Dice (Sd) similarity coefficeints using unweighted pair-group arithmetic average method (UPGMA).

P. gregata isolates from soybean. Sixty five of the 121 amplicons (54 %) were polymorphic among the 46 isolates. Excluding the adzuki bean isolate, 30 % of the amplicons were polymorphic among the soybean isolates. In comparing the AFLP and the ISSR techniques, the ISSR technique was more effective in detecting genetic variation than the AFLP technique used in this research. The ISSR technique generated more polymorphic amplicons than the AFLP technique did. Furthermore, the ISSR technique requires a smaller amount of genomic DNA than the AFLP technique does, and does not require the process of enzymatic digestion and ligation. Also the procedure of the ISSR technique has a number of advantages over other molecular techniques such as RAPD (randomly amplified polymorphic DNA) and SSRs (simple sequence repeats). The ISSR technique is more specific than RAPD technique due to the use of longer primer sequences allowing more stringent annealing conditions in PCR amplification. The primer of simple sequence repeats will amplify the region between two properly oriented SSRs. It was reported that ISSR is more reproducible than RAPD (Godwin et al. 1997) and has higher levels of polymorphism than RFLP (Kantety et al. 1995). SSRs, also known as microsatellites, are ubiquitous in higher organisms and have been utilized as successful genetic markers for the study of genetic diversity and mapping (Cregan et al. 1994, Ro$ der et al. 1995, Wu & Tanksley 1993). However, utilization of SSR

requires the knowledge of the flanking sequences of SSRs in order to design specific primers for PCR amplification. In ISSR, knowledge of DNA sequence is not required for designing primers. Thus the portability of the ISSR technique allows it to be applied to organisms about which little genetic information is available, such as P. gregata. A UPGMA dendrogram depicting the genetic diversity among 46 P. gregata isolates was constructed based on the 121 DNA bands amplified with AFLP and ISSR primers (Fig. 3). The outgroup isolate (A8) from adzuki bean was approximately 72.7 % similar to and can be clearly distinguished from all the soybean and mung bean isolates. This result is consistent with previous reports on genetic differences between the two formae speciales in pathogenicity (Kobayashi et al. 1983, 1991), isozyme patterns (Mengistu & Grau 1986, Yamamoto et al. 1990), repetitive sequences and nuclear DNA content (Yamamoto et al. 1995), and nuclear rDNA (Chen et al. 1996, 1998). However, the isolates obtained from mung bean could not be differentiated from those from soybean (Fig. 3). A previous report showed that isolates of P. gregata isolated from mung bean and soybean cross infect both hosts (Gray & Pataky 1994). One isolate from Ohio (OH2) showed the same banding patterns with those of ten isolates from Wisconsin. The similarities among 45 soybean and mung bean isolates ranged from about 90 % to 100 % based on the 121 amplicons. The average genetic diversity (H) of the 121 loci was very low (H l 0.079) in the population of 45 P. gregata isolates from soybean and mung bean. Most of the isolates were collected from areas within about 300 km radius from Illinois, Indiana, and Wisconsin. No significant difference in genetic diversity was detected among isolates from the three states. Our data suggest that the level of genetic variation among soybean isolates of P. gregata is very low. The genetic diversity of the 45 isolates from soybean and mung bean was only about 0.079. The average genetic diversity would be even lower than the estimated value if all the amplicons produced by the other primers that did not generate polymorphisms were included in the analyses. It is significant to be able to detect genetic variation among soybean isolates of P. gregata. It will enable us to study correlations between genetic variation and other phenotypic traits, such as sporulation and pathogenicity. It will also allow us to develop molecular markers for tracking specific isolates in ecological studies such as interactions of introduced strains of P. gregata with other fungi inhabiting soybean stems, which was previously not possible (Chen et al. 1999). REFERENCES Adee, E. A., Grau, C. R. & Oplinger, E. S. (1995) Inoculum density of Phialophora gregata related to severity of brown stem rot and yield of soybean in microplot studies. Plant Disease 79 : 68–73. Allington, W. B. & Chamberlain, D. W. (1948) Brown stem rot of soybean. Phytopathology 56 : 1065–1077. Chen, W. (1992) Restriction fragment length polymorphisms in enzymatically amplified ribosomal DNAs of three heterothallic Pythium species. Phytopathology 82 : 1467–1472. Chen, W, Gray, L. E. & Grau, C. R. (1996) Molecular differentiation of fungi associated with brown stem rot and detection of Phialophora gregata in resistant and susceptible soybean cultivars. Phytopathology 86 : 1140–1148.

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