Specific and sensitive detection of the conifer pathogen Gremmeniella abietina by nested PCR
© Zeng et al; licensee BioMed Central Ltd. 2005
Received: 28 June 2005
Accepted: 09 November 2005
Published: 09 November 2005
Gremmeniella abietina (Lagerb.) Morelet is an ascomycete fungus that causes stem canker and shoot dieback in many conifer species. The fungus is widespread and causes severe damage to forest plantations in Europe, North America and Asia. To facilitate early diagnosis and improve measures to control the spread of the disease, rapid, specific and sensitive detection methods for G. abietina in conifer hosts are needed.
We designed two pairs of specific primers for G. abietina based on the 18S rDNA sequence variation pattern. These primers were validated against a wide range of fungi and 14 potential conifer hosts. Based on these specific primers, two nested PCR systems were developed. The first system employed universal fungal primers to enrich the fungal DNA targets in the first round, followed by a second round selective amplification of the pathogen. The other system employed G. abietina-specific primers in both PCR steps. Both approaches can detect the presence of G. abietina in composite samples with high sensitivity, as little as 7.5 fg G. abietina DNA in the host genomic background.
The methods described here are rapid and can be applied directly to a wide range of conifer species, without the need for fungal isolation and cultivation. Therefore, it represents a promising alternative to disease inspection in forest nurseries, plantations and quarantine control facilities.
Gremmeniella abietina (Lagerb.) Morelet is among the most destructive conifer forest pathogens in the northern hemisphere. This ascomycete fungus has a broad host range and causes stem canker and shoot dieback in many conifer species of the genera Pinus, Abies, Picea, Larix, Tsuga and Pseudotsuga [1–3]. In Sweden, G. abietina is found on the two native conifers Picea abies and Pinus sylvestris, as well as the introduced species, Pinus contorta [4–6].
Under favorable conditions, the life cycle of G. abietina takes two years to complete . The fungus may grow in the host as an endophyte for more than one year [7, 8], and infected trees can remain undetected for several years before manifesting visible symptoms. This poses difficulties for diagnosing disease at an early stage, using asymptomatic materials. Nursery seedling inspection and quarantine control require sensitive detection methods to limit the spread of the pathogen. Various morphological, physiological, pathogenic and biochemical characters and molecular markers have been employed to distinguish and characterize different races and types of the fungus, such as the North American race (NA), European (EU) race, and large tree type (LTT) and small tree type (STT) [9–15]. Most of these methods require isolation of the fungus in culture. This process is time consuming and is not appropriate for the detection of the fungus directly in infected but asymptomatic tissues.
Specific polymerase chain reaction (PCR) based detection methods are sensitive and robust techniques when used in plant disease diagnostic research. By employing specific PCR primers it is possible to selectively amplify the pathogen from infected tissues without the need for isolation. Among the different PCR techniques, nested PCR (a two-step PCR system in which the first round PCR products are subjected to a second round PCR amplification with more specific primers) is extremely sensitive and allows the detection of a fungal pathogen in minute amounts of infected material [16–18]. Recently, a nested PCR procedure was developed for the detection of G. abietina . This method is based on the polymorphic sites in the ribosomal DNA (rDNA) internal transcribed spacer (ITS). The ITS evolves rapidly and significant variations within a species or even within a genome have been reported for fungi and plants [20–23]. The specific markers from the ITS region are, therefore, potentially unstable because of the high mutation rate, and would need to be validated by extensive sample testing. The 18S rRNA gene is much more conservative compared to the ITS. Specific markers developed from this DNA region are less likely to be invalid due to intraspecific variations producing false negative detections.
The aim of the present study was to develop a stable, specific and sensitive method for detecting G. abietina infection in a broad range of hosts. There was no intention to differentiate between the races/types of the fungus, which would be difficult using this conserved DNA segment. The 18S rRNA gene was sequenced from G. abietina isolated from four host species. Highly specific primers were designed for G. abietina, based on extensive sequence homology analysis. Two nested PCR systems were developed for sensitive detection of the pathogen in host tissues. The first system employed fungal universal primers in the first round PCR, to enrich the fungal rDNA in the plant genomic background, followed by the specific amplification of G. abietina rDNA in the second round PCR. The second system employed G. abietina specific primers in both PCR rounds. Both approaches can detect the presence of G. abietina in composite samples with high sensitivity. This procedure is rapid and can be used directly on plant materials without the need for fungal isolation and subsequent cultivation. The methods described here represent a promising alternative to disease inspection in forest nurseries, plantations and quarantine control facilities.
Specific amplification of G. abietina
Evaluation of detection sensitivity
If the method is to be used for the early detection of infection in bulked samples in forest practice, a high level of sensitivity is required. Three different tests using a dilution series of G. abietina genomic DNA, with and without other background DNA, were conducted to compare the detection limits of the different PCR setups. The lowest DNA dilution that could provide a reproducible, unambiguous visible signal (in 3 μl PCR product) on ethidium bromide stained gels after electrophoresis was defined as the PCR detection limit.
Other fungal strains and conifer species included in this study.
Aspergillus niger UPSC 1769
Aspergillus ochraceus UPSC 1983
Aspergillus flavus UPSC 1768
Aspergillus penicilloides ALI 231
Aspergillus versicolor UPSC 2027
Aspergillus silvaticus ALI 234
Cladosporium cladosporioides ALI 50
Chrysonilia sitophila ALI 346
Eurotium herbariorum ALI 216
Fusarium culmorum UPSC 1981
Microdochium nivale UPSC 3273
Mucor plumbeus UPSC 1492
Paecilomyces variotii UPSC 1651
Penicillium commune CBS 343.51
Penicillium italicum UPSC 1577
Penicillium chrysogenum UPSC 2020
Penicillium brevicompactum ALI 319
Penicillium frequentans ALI 218
Rhizopus microsporus UPSC 1758
Stachybotrys bisbyi CBS 317.72
Stachybotrys chartarum CBS 330.37
Stachybotrys dichroa CBS 182.80
Stachybotrys oenanthes CBS 252.76
Stachybotrys kampalensis CBS 388.73
Stachybotrys microspora CBS 186.79
Trichoderma reesei QM 9414
Trichoderma viride ALI 210
Ulocladium botrytis CBS 173.82
Wallemia sebi UPSC 2502
Phacidium infestans A387
Phacidium infestans A391
To simulate the detection of G. abietina in a composite fungal background, the dilution series of G. abietina DNA was mixed with equal volumes of DNA from seven other fungi (Test 3, Table 2). In contrast to the previous two tests, this composite fungal DNA produced a visible amplification product (ca. 1.7 Kb in size) in all seven DNA dilution mixtures after the first round PCR with universal fungal primers (data not shown). This was due to the presence of background fungal DNA (ca. 9 ng) in all PCR mixes, no matter how little G. abietina DNA was present: the NS1/8 primers were compatible with all of the fungi in the mixture. Following the nested PCR, the detection limit was 0.075 ng G. abietina DNA in the background of 9 ng of other fungal DNA (i.e. about a hundredth of the fungal background DNA, Fig. 4a, b Test 3). This is a pronounced decrease in detection sensitivity compared to Tests 1 and 2. In contrast, the detection sensitivity of the nested PCR using the specific primers in both PCR steps was not affected by the presence of other fungal DNA, and gave the same detection sensitivity as in Test 1 and 2 (Fig. 4c Test 3).
Detection of G. abietina infection in Pinus contorta by nested PCR
Gremmeniella abietina is widespread and causes severe damage to several conifer species. Large-scale forest epidemics have been reported from several continents [1, 6, 24–26]. The disease can spread through infected seedling nurseries. Intercontinental migration of the pathogen has also been reported as a result of international transportation of infected forest materials [27, 28]. Rapid detection methods that can be applied directly to asymptomatic tissues would be valuable for forest disease management. Previously reported methods for the morphological, biochemical, pathogenic or genetic characterization of this fungus require its isolation in culture [14, 28–31]. Such characterization allows the species to be subdivided into different races and types. However, host differentiation of the fungus is very limited and different races/types can coexist in the same geographic region and infect the same host species [27, 29, 30, 32, 33]. Therefore, for forest management, a general detection method for G. abietina, regardless of race/type, would be highly desirable. The identical 18S rDNA sequences from G. abietina of NA, EU, LTT and STT race/type isolated from different hosts indicate that, in this fungus, the sequence is conservative. Therefore, markers based on it exhibit general intraspecific applicability. A high specificity of the detection system is a prerequisite for its application in pathogen diagnosis. The specific primers developed in this study successfully detected G. abietina at species level and, thus, can function as rapid molecular markers for its identification and detection in composite fungal or plant samples without the need for isolation and cultivation. By verifying these DNA markers in a wide range of conifer species, the present study indicates that this detection system can be applied to all potential hosts, so it should be a valuable forest management tool across broad geographic regions.
Apart from the specificity, the sensitivity of a detection system is also important for early infection diagnosis, particularly in bulk samples. The sensitivity of a PCR assay depends on several factors, most importantly on the primer composition, structure and homology to the target molecule. In this study, when the three pairs of primers, NS1/8, NS.Grem3/4 and NS.Grem5/6, were tested on G. abietina DNA in single-step PCR with the same number of cycles, NS.Grem3/4 was found to be ca. 10 times more efficient than the other two pairs. The higher amplification efficiency of NS.Grem3/4 was consistent across all PCR assays (Fig. 4). Thus, careful design and selection of the primers can significantly improve the sensitivity of a PCR assay.
Nested PCR was employed in this study to improve the detection sensitivity of the pathogen in the hosts. The use of universal fungal primers in the first round PCR enriches the fungal rDNA in the plant genomic background, then, in the second round, there is selective amplification of the target pathogen. This approach is particularly attractive when screening for multiple fungal pathogens in minor amount of plant tissue. The nested PCR developed in this study can detect as little as a single fungal genome even in high background levels of pine DNA. The template DNA concentration and composition can influence the efficiency of nested PCR. In the presence of a high proportion of other fungal DNA the detection limit of nested PCR with outer primers being the fungal universal primers NS1/8 was significantly decreased, mainly due to primer competition in the first round PCR. Since the universal primers are compatible with all the fungi in the mixture, the very small proportion of G. abietina present (<0.1%) would have little chance to compete for the primers. The target template was, therefore, not enriched in the first round PCR, which in turn affected the nested PCR sensitivity. This problem can be avoided by employing G. abietina-specific primers in both PCR rounds. The nested PCR based on this approach showed high detection sensitivity for G. abietina even in a high background of other fungal DNA. In real situations, the detection systems would usually be used on either suspected G. abietina infections or asymptomatic tissues. DNA isolated from these materials would mostly comprise the host DNA and DNA from endophytic fungi. G. abietina may or may not be the major component among the endophytic fungi. Thus, the nested PCR system using specific primers in both PCR steps would satisfy both the specificity and sensitivity requirements for diagnostic applications.
In the analysis of plant samples, extraction of sufficient fungal genomic DNA is also important since the fungal tissue is usually present at low levels relative to the amount of host tissue. If this is not achieved, the detection sensitivity may be inadequate and could result in a false negative. For large conifer trees, the stage and degree of the disease development as well as tissue sampling position would also affect the pathogen's detection. In the early stage of infection the amount and the spread of fungal mycelia is limited. Tissues from parts of the tree other than the close vicinity of the infection site may give negative detection. Thus, for large conifers multiple samples should be collected from the suspected tree for examination.
This study developed rapid, specific and sensitive detection systems for the conifer pathogen G. abietina. The specific markers were validated for a broad range of conifer hosts and fungi. Thus, the detection methods described here could have broad applications in forest protection and disease management programs. It should be also recognized that different race/types of G. abietina have distinct epidemiological and aetiological attributes and the ideal molecular assay should allow the user to identify not only the species but also the races and biotypes. The assay reported here could be used in combination with other race or biotype-specific assays [12, 19], either in a multiplex or in a sequential fashion, to better understand the distribution and disease development of different G. abietina infections.
Fungal strains, plant species and genomic DNA extraction
Gremmeniella abietina isolates examined in this study.
G. abietina ALI 531
G. abietina ALI 532
G. abietina ALI 533
G. abietina ALI 534
G. abietina ALI 569
Arctic circle, Finland
G. abietina ALI 570
G. abietina ALI 571
G. abietina ALI 572
G. abietina ALI 573
G. abietina ALI 574
G. abietina US 810105
G. abietina US 790048
G. abietina CF 910032
G. abietina ALI G90
G. abietina ALI G148
G. abietina ALI G139
G. abietina ALI G3
G. abietina ALI G4
G. abietina ALI G6
G. abietina ALI G15
G. abietina ALI G16
G. abietina ALI G17
G. abietina ALI F113
G. abietina ALI F114
G. abietina ALI F116
G. abietina ALI F129
G. abietina ALI F174
Fourteen conifer species from three families (Pinaceae, Cupressaceae and Taxodiaceae) were selected to represent the potential range of hosts (Table 2). Since pines are most susceptible to this pathogen, eight pine species native to Asia, Europe and North America were selected, representing the two Pinus subgenera: Pinus and Strobus. Three other reported hosts of G. abietina were also included: Picea, Abies and Larix. Seeds of each species were germinated on sterilized Petri dish for 2 – 3 weeks and used for DNA isolation. Twigs from six infected trees of P. contorta were collected in the forest of northern Sweden. From these, both brown and green needles were collected for DNA isolation.
The fungal genomic DNAs were isolated from a pure culture of each strain following the procedure described by Wu et al . The genomic DNAs of the conifer species were isolated using a DNeasy® Plant Mini Kit (Qiagen, Germany). The pine needles were thoroughly homogenized, as follows. Two ceramic beads, 4 mm in diameter (Iuchi, Japan) and 350 mg of 0.5 mm zirconia-silica beads (Biospec Products, Inc., Bartlesville, OK, USA), were placed in a 2-ml microtube containing 100 mg pine needles. The tubes were placed in a Mini-Bead Beater (Biospec Products, Inc.) and homogenized for 2 min at the maximum speed. The rest of the isolation procedure followed that suggested by the manufacturer of the DNeasy Plant Mini Kit (Qiagen, Germany).
To increase the detection sensitivity, two nested PCR systems were developed. One approach used the 18S rDNA-based universal fungal primers NS1 and NS8  as outer primers in the first round PCR. Amplification was performed in a volume of 25 μl containing 1 – 5 ng of template DNA, 10 pmol of each primer, 0.75 U of Taq DNA polymerase (Invitrogen Life Technologies, USA), 200 μM of each dNTP (Amersham Pharmacia Biotech, USA), and 1.5 mM MgCl2. PCR conditions were optimized to comprise an initial denaturation of 3 min at 95°C, followed by 36 cycles of 94°C for 30 s, 45°C for 45 s and 72°C for 90 s, followed by a final extension of 10 min at 72°C. A 1 μl aliquot of the first round PCR product was used as the template in the second round, using the G. abietina-specific primers NS.Grem3/4 or NS.Grem5/6. The PCR conditions for these two specific primer pairs were similar to the NS1/8 amplification, except that the PCR cycles were decreased to 25 in the second round PCR and the annealing temperatures were 60°C and 56°C for NS.Grem3/4 and NS.Grem5/6, respectively. In another approach, G. abietina-specific primer pair NS.Grem3/4 was used in the first round PCR and NS.Grem5/6 in the second round. The PCR procedure is the same as that described above. A negative control was included in all PCR runs. PCR products (3 μl) were analyzed by electrophoresis on 1.4% agarose gels in 1× TAE buffer. The gels were stained with ethidium bromide and visualized under UV light using a Gel Doc 2000 fluorescent gel documentation system (Bio-Rad, USA).
DNA dilutions and mixtures used in the sensitivity test. The relative abundance of G. abietina DNA to the other genomic background DNA is indicated in parentheses.
Test 1G. abietina
Test 2 G. abietina + P. contorta
Test 3 G. abietina + 7 fungi mix
5 × 10-1 ng/μl
5 × 10-1 ng/μl + 4 ng/μl (1:8)
5 × 10-1 ng/μl + 6 ng/μl (1:12)
5 × 10-2 ng/μl
5 × 10-2 ng/μl + 4 ng/μl (1:80)
5 × 10-2 ng/μl + 6 ng/μl (1:120)
5 × 10-3 ng/μl
5 × 10-3 ng/μl + 4 ng/μl (1:800)
5 × 10-3 ng/μl + 6 ng/μl (1:1200)
5 × 10-4 ng/μl
5 × 10-4 ng/μl + 4 ng/μl (1:8000)
5 × 10-4 ng/μl + 6 ng/μl (1:12000)
5 × 10-5 ng/μl
5 × 10-5 ng/μl + 4 ng/μl (1:80000)
5 × 10-5 ng/μl + 6 ng/μl (1:120000)
5 × 10-6 ng/μl
5 × 10-6 ng/μl + 4 ng/μl (1:800000)
5 × 10-6 ng/μl + 6 ng/μl (1:1200000)
5 × 10-7 ng/μl
5 × 10-7 ng/μl + 4 ng/μl (1:8000000)
5 × 10-7 ng/μl + 6 ng/μl (1:12000000)
3 μl in PCR
1:1 vol. mix, 3 μl in PCR
1:1 vol. mix, 3 μl in PCR
We thank Prof Antti Uotila, Helsinki University, Finland, and Dr Gaston Laflamme, Laurentian Forestry Centre, Canadian Forest Service, for providing the Gremmeniella isolates from Finland and US and Canada. We also thank Prof Margareta Karlman, Dr Jesper Witzell and Andreas Bernhold, the Swedish University of Agricultural Sciences, for collecting field samples of Gremmeniella in the northernmost of Sweden. This study was supported by grants from the Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (Formas 24.0372/99), the Swedish Council for Working Life and Social Research (FAS) and the Swedish University of Agricultural Sciences.
- Donaubauer E: Distribution and hosts of Scleroderris lagerbergii in Europe and North America. Eur J For Pathol. 1972, 2: 6-11.View ArticleGoogle Scholar
- Hellgren M: Gremmeniella abietina - disease biology and genetic variation within Fennoscandia. Department of Forest Mycology and Pathology. 1995, Uppsala, Swedish University of Agricultural SciencesGoogle Scholar
- Skilling DD, Riemenschneider DE: Screening conifers for resistance to Gremmeniella abietina. Proc Int Symposium Scleroderris Canker of Conifers. Edited by: Manion PD. 1983, Syracuse, USA, The Hague, Martinus Nijhoff - Dr. W. Junk Publisher, 189-196.Google Scholar
- Barklund P, Rowe J: Gremmeniella abietina (Scleroderris lagerbergii), a primary parasite in a Norway spruce dieback. Eur J For Path. 1981, 11: 97-108.View ArticleGoogle Scholar
- Hellgren M, Barklund P: Studies of the life-cycle of Gremmeniella abietina on scots pine in southern Sweden. Eur J For Path. 1992, 22: 300-311.View ArticleGoogle Scholar
- Karlman M, Hansson P, Witzell J: Scleroderris canker on lodgepole pine introduced in northern Sweden. Can J For Res. 1994, 24: 1948-1959.View ArticleGoogle Scholar
- Lang KJ, Schütt P: Anatomische untersuchungen zur infektionsbiologie von Scleroderris lagerbergii Gr (Brunchorstia pinea (Karst.) von Höhn.). Eur J For Pathol. 1974, 4: 166-174.View ArticleGoogle Scholar
- Marosy M, Patton RF, Upper CD: A Conducive Day Concept to Explain the Effect of Low-Temperature on the Development of Scleroderris Shoot Blight. Phytopathology. 1989, 79: 1293-1301.View ArticleGoogle Scholar
- Dorworth CE, Krywienczyk J: Comparisons among isolates of Gremmeniella abietina by means of growth rate, conidia measurement, and immunogenic reaction. Can J Bot. 1975, 53: 2506-2525.View ArticleGoogle Scholar
- Uotila A: Physiological and morphological variation among Finnish Gremmeniella abietina isolates. Commun Inst For Fenn. 1983, 119: 1-12.Google Scholar
- Petrini O, Toti L, Petrini LE, Heiniger U: Gremmeniella abietina and G. laricina in Europe: characterization and identification of isolates and laboratory strains by soluble protein electrophoresis. Can J Bot. 1990, 68: 2629-2635.View ArticleGoogle Scholar
- Hamelin RC, Ouellette GB, Bernier L: Identification of Gremmeniella abietina races with random amplified polymorphic DNA markers. Appl Environ Microbiol. 1993, 59: 1752-1755.PubMed CentralPubMedGoogle Scholar
- Lecours N, Toti L, Sieber TN, Petrini O: Pectic Enzyme Patterns as a Taxonomic Tool for the Characterization of Gremmeniella Spp Isolates. Can J Bot. 1994, 72: 891-896.View ArticleGoogle Scholar
- Müller MM, Uotila A: The diversity of Gremmeniella abietina var. abietina FAST-profiles. Mycol Res. 1997, 101: 557-564. 10.1017/S0953756296002894.View ArticleGoogle Scholar
- Dusabenyagasani M, Lecours N, Hamelin RC: Sequence-tagged sites (STS) for studies of molecular epidemiology of scleroderris canker of conifers. Theor Appl Genet. 1998, 97: 789-796. 10.1007/s001220050957.View ArticleGoogle Scholar
- McCartney HA, Foster SJ, Fraaije BA, Ward E: Molecular diagnostics for fungal plant pathogens. Pest Manag Sci. 2003, 59: 129-142. 10.1002/ps.575.View ArticlePubMedGoogle Scholar
- Grote D, Olmos A, Kofoet A, Tuset JJ, Bertolini E, Cambra M: Specific and sensitive detection of Phytophthora nicotianae by simple and nested-PCR. Eur J Plant Path. 2002, 108: 197-207. 10.1023/A:1015139410793.View ArticleGoogle Scholar
- Renker C, Heinrichs J, Kaldorf M, Buscot F: Combining nested PCR and restriction digest of the internal transcribed spacer region to characterize arbuscular mycorrhizal fungi on roots from the field. Mycorrhiza. 2003, 13: 191-198. 10.1007/s00572-002-0214-5.View ArticlePubMedGoogle Scholar
- Hamelin RC, Bourassa M, Rail J, Dusabenyagasani M, Jacobi V, Laflamme G: PCR detection of Gremmeniella abietina, the causal agent of Scleroderris canker of pine. Mycol Res. 2000, 104: 527-532. 10.1017/S0953756299002026.View ArticleGoogle Scholar
- O'Donnell K: Ribosomal DNA internal transcribed spacers are highly divergent in the phytopathogenic ascomycete Fusarium sambucinum (Gibberella pulicaris). Curr Genet. 1992, 22: 213-220. 10.1007/BF00351728.View ArticlePubMedGoogle Scholar
- Gernandt DS, Liston A, Pinero D: Variation in the nrDNA ITS of Pinus Subsection Cembroides: Implications for Molecular Systematic Studies of Pine Species Complexes. Mol Phylogenet Evol. 2001, 21: 449-467. 10.1006/mpev.2001.1026.View ArticlePubMedGoogle Scholar
- James TY, Moncalvo JM, Li S, Vilgalys R: Polymorphism at the ribosomal DNA spacers and its relation to breeding structure of the widespread mushroom Schizophyllum commune. Genetics. 2001, 157: 149-161.PubMed CentralPubMedGoogle Scholar
- Ko KS, Jung HS: Three nonorthologous ITS1 types are present in a polypore fungus Trichaptum abietinum. Mol Phylogenet Evol. 2002, 23: 112-122. 10.1016/S1055-7903(02)00009-X.View ArticlePubMedGoogle Scholar
- Dorworth CE: Epidemiology of Scleroderris lagerbergii in central Ontario. Can J Bot. 1972, 50: 751-765.View ArticleGoogle Scholar
- Skilling DD, Schneider B, Dasking D: Biology and control of scleroderris canker in North America. 1986, , USDA Forest Service, North Central Experimental StationGoogle Scholar
- Nevalainen S: Gremmeniella abietina in Finnish Pinus sylvestris stands in 1986-1992: a study based on the National Forest Inventory. Scand J Forest Res. 1999, 14: 111-120. 10.1080/02827589950152836.View ArticleGoogle Scholar
- Dorworth CE, Krywienczyk J, Skilling DD: New York isolates of Gremmeniella abietina (Scleroderris lagerbergii) identical in immunogenic reaction to European isolates. Plant Dis Rep. 1977, 61: 887-890.Google Scholar
- Hamelin RC, Lecours N, Laflamme G: Molecular evidence of distinct introductions of the European race of Gremmeniella abietina into North America. Phytopathology. 1998, 88: 582-588.View ArticlePubMedGoogle Scholar
- Hansson P, Wang XR, Szmidt AE, Karlman M: RAPD variation in Gremmeniella abietina attacking Pinus sylvestris and Pinus contorta in northern Sweden. Eur J For Path. 1996, 26: 45-55.View ArticleGoogle Scholar
- Hantula J, Muller MM: Variation within Gremmeniella abietina in Finland and other countries as determined by Random Amplified Microsatellites (RAMS). Mycol Res. 1997, 101: 169-175. 10.1017/S0953756296002225.View ArticleGoogle Scholar
- Wang XR: Genetic variability in the canker pathogen fungus, Gremmeniella abietina. contribution of sexual compared with asexual reproduction. Mycol Res. 1997, 101: 1195-1201. 10.1017/S0953756297003791.View ArticleGoogle Scholar
- Hansson P: Susceptibility of different provenances of Pinus sylvestris, Pinus contorta and Picea abies to Gremmeniella abietina. Eur J For Path. 1998, 28: 21-32.View ArticleGoogle Scholar
- Kaitera J, Seitamaki L, Jalkanen R: Morphological and ecological variation of Gremmeniella abietina var. abietina in Pinus sylvestris, Pinus contorta and Picea abies sapling stands in northern Finland and the Kola Peninsula. Scand J Forest Res. 2000, 15: 13-19. 10.1080/02827580050160420.View ArticleGoogle Scholar
- Wu Z, Tsumura Y, Blomquist G, Wang XR: 18S rRNA Gene Variation among Common Airborne Fungi, and Development of Specific Oligonucleotide Probes for the Detection of Fungal Isolates. Appl Environ Microbiol. 2003, 69: 5389-5397. 10.1128/AEM.69.9.5389-5397.2003.PubMed CentralView ArticlePubMedGoogle Scholar
- Gernandt DS, Platt JL, Stone JK, Spatafora JW, Holst-Jensen A, Hamelin RC, Kohn LM: Phylogenetics of Helotiales and Rhytismatales based on partial small subunit nuclear ribosomal DNA sequences. Mycologia. 2001, 93: 915-933.View ArticleGoogle Scholar
- Wu Z, Wang XR, Blomquist G: Evaluation of PCR primers and PCR conditions for specific detection of common airborne fungi. J Environ Monit. 2002, 4: 377-382. 10.1039/b200490a.View ArticlePubMedGoogle Scholar
- White TJ, Bruns T, Lee S, Taylor J: Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. PCR protocols: A guide to methods and applications. Edited by: Innis MA, Gelfand DH, Sninsky JJ and White TJ. 1990, San Diego, Academic Press, 315-322.Google Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.