Lack of global population genetic differentiation in the arbuscular
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Molecular Ecology (2009) doi: 10.1111/j.1365-294X.2009.04359.x Lack of global population genetic differentiation in the arbuscular mycorrhizal fungus Glomus mosseae suggests a recent range expansion which may have coincided with the spread of agriculture S Ø R E N R O S E N D A H L , * P E T E R M C G E E † and J O S E P H B M O R T O N ‡ *Department of Biology, University of Copenhagen, Oster Farimagsgade 2D, DK-1353 Copenhagen K, Denmark, †School of Biological Sciences, University of Sydney, Sydney, NSW 2006, Australia, ‡Division of Plant and Soil Sciences, West Virginia University, Morgantown, WV, 26506-6108 USA Abstract The arbuscular mycorrhizal fungus Glomus mosseae is commonly found in agricultural fields. The cosmopolitan species is found in Africa, Europe, America, Asia and Australia. Three hypotheses may explain this worldwide distribution: First, speciation occurred before the continents separated 120 Ma; second, the distribution is a result of humanmediated dispersal related to agriculture and finally, the morphologically defined species may encompass several local endemic species. To test these hypotheses, three genes were sequenced from 82 isolates of G. mosseae originating from six continents and the resulting sequences analysed for geographical subdivision and estimation of migration between continents. Coalescent analyses estimated divergence and age of mutations. Bayesian coalescent modelling was used to reveal important past population changes in the global population. The sequence data showed no geographical structure, with identical genotypes found on different continents. Coalescence analyses indicated a recent diversification in the species, and the data could be explained by a recent population expansion in G. mosseae. The results of this study suggest that speciation and the range expansion happened much later than continental spread and that human activity may have had a major impact on the dispersal and the population structure of the fungus. Keywords: agriculture, cosmopolitan, evolution, population structure Received 12 May 2009; revision received 2 August 2009; accepted 9 August 2009 Introduction Arbuscular mycorrhizal fungi (AMF) are among the most common organisms found on this planet, as they form a mutualistic symbiosis with most plants in almost all types of vegetation and habitats (Smith & Read 2008). The benefits of these fungi for plant nutrition have been recognized for more than four decades, and numerous recent studies have demonstrated their crucial role in ecological processes at all scales (Van der Heijden et al. 1998). Correspondence: Søren Rosendahl, Fax: +45 3532 2321; E-mail: soerenr@bio.ku.dk 2009 Blackwell Publishing Ltd Fossil AMF dating back to Ordovician (Redecker et al. 2000) and molecular data (Berbee & Taylor 1993) support the hypothesis first proposed by Pirozynski & Malloch (1975) that fungi, and AMF in particular, evolved with the first terrestrial plants, and it is possible that AMF facilitated the transition from aquatic to terrestrial life forms. Fossilized mycorrhizal structures and resting spores resemble contemporary structures, suggesting that the fungi may have undergone few morphological changes during 400 Myr (Morton 1990; Remy et al. 1994). Sexual reproduction via meiosis or sexual reproductive structures has not been reported. All of this evidence suggests that these fungi may have evolved clonally over several 2 S . R O S E N D A H L , P . M C G E E and J . B . M O R T O N million years (Judson & Normark 1996). Analyses of multilocus genotypes have provided stronger evidence of clonality in AM fungal populations (Rosendahl & Taylor 1997; Stukenbrock & Rosendahl 2005a,b). Genetic constraints imposed by clonal evolution as well as design constraints on breadth of phenotypes might explain the low species number in Glomeromycota, in spite of the broad host range of its members (Cairney 2000). Some AMF species are clearly widely distributed globally, and few species have been proven to be endemic. A hypothesis to explain pandemism among AMF is that speciation occurred when all continents were part of the supercontinent Pangaea. This supercontinent started to break up during the Jurassic period (200–150 Ma) and slow clonal evolution constrained morphological evolution so that further speciation did not occur after the continents drifted apart (Morton 1990). If speciation occurred before the continents drifted apart, then those clonal populations on different continents should have diverged genetically as a result of random genetic drift and natural selection (Linder et al. 2003). The pandemic distribution of some Glomeromycotan fungi has not been studied in detail. In their criticism of the ‘everything-is-everywhere’ hypothesis, Taylor et al. (2006) produced evidence that cosmopolitan species may obscure endemic species. In Glomeromycota, morphological characters resolving species are confined exclusively to subcellular components of spores (Morton et al. 1995); therefore, the number of phenotypes possible within that design space is relatively low. Developmental constraints on morphological variation probably obscure significant genetic differences among populations (Morton 1990), so there is a high probability that genetically divergent endemic species will not be identified without additional molecular criteria (Rosendahl 2008). Gene sequences (Msiska & Morton 2009) offer the possibility of additional discrimination, but phylogenetic analyses of these markers still may not reveal local endemism. A global distribution with little geographical differentiation has been reported for some plant pathogens and other fungi related to human activity. The pandemic spread of Phytophthora infestans is well-known (Goodwin et al. 1994), and for the widespread wheat pathogen Phaeosphaeria nodorum, migration has reduced population differentiation significantly (Stukenbrock et al. 2006). In these cases, the migration correlated with human activity over the past few hundred years, and the lack of geographical differentiation is hypothesized to be a result of continuous migration as well as recent divergence. The species Glomus mosseae has been reported from all continents except the Antarctic. It was first described by Mosse & Bowen (1968) as ‘Yellow Vacuolate’ and the description included collections from Australia, New Zealand and the United Kingdom. The authors concluded that this species was associated with arable land rather than with native vegetation. Subsequently, G. mosseae was isolated from a range of environments, cultivated and used in experiments. The International Bank of Glomales database has 49 registered cultures, of which 37 are from agricultural fields, and only four are from natural or semi-natural vegetation. Of the 76 isolates in the International Collection of AMF (INVAM, West Virginia University), 41 are from known agricultural sites. If G. mosseae occurred on the supercontinent Pangaea, the speciation must have occurred more than 200 Ma. The species then would have spread to the present continents concomitant with continental drift. An alternative hypothesis is that the speciation is more recent, and that association with agricultural environments and practices facilitated the global distribution of the species. Such human-mediated spread would have taken place only within the last few hundred years. Markov chain Monte Carlo (MCMC) Bayesian coalescent analyses provide a method to elucidate demographic patterns in relation to geological and climatic changes (Drummond et al. 2005). Bayesian coalescent modelling has been used to reveal important past population changes (Heller et al. 2008). The models not only provide a time estimate of the divergence and the migration pattern of species between continents, but genetic signatures also reveal marked changes in effective population structure. The aim of this study was to test the hypothesis that the isolates of the species G. mosseae from different continents have the same evolutionary history and to reveal the degree of genetic differentiation of populations inhabiting different continents through estimates of migration and divergence times. Genetic differentiation of G. mosseae populations was inferred from phylogeographical analyses; divergence times and migration of populations were estimated by MCMC analysis. The role of agriculture in the expansion of G. mosseae populations was also examined. Materials and methods Isolates A total of 82 isolates of G. mosseae from six continents were obtained from culture collections, from research laboratories and from soil samples (Table 1). Additionally, 10 isolates of Glomus geosporum were included as an outgroup. 2009 Blackwell Publishing Ltd Isolate az225c ca210 ut101 md122 in101c nv106-1 wi101-1 fl156-1 nv106-2 on201c mi210a mn101-1 mn101-2 mn101-3 mt107-1 wv692-1 sc226-1 ne107a or229 mt107-2 fl156-2 wv692-2 wy111 ho102 b2514045, BEG25 b2514046, BEG25 chg831126, BEG fib292138, BEG29 ukb253138, BEG25 dk9135 dk23135 dk33R132 dk22S132 chg1302712, BEG dk17107 dk21107 dk11107 l543 Beg84 l496 Beg 84 l484 Beg 85 ID 1AZ 2CA 3UT 4MD 5IN 6NV 7WI 8FL 9NV 10ON 11MI 12MN 13MN 14MN 15MT 16WV 17SC 18NE 19OR 20MT 21FL 22WV 23WY 24HO 25UK 26UK 27CH 28FI 29UK 30DK 31DK 32DK 33DK 34CH 35DK 36DK 37DK 38DK 39DK 40DK North America North America North America North America North America North America North America North America North America North America North America North America North America North America North America North America North America North America North America North America North America North America North America Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe Continent Arizona California Utah Maryland Indiana Nevada Wisconsin Florida Nevada Ontario Michigan Minnesota Minnesota Minnesota Montana West Virginia South Carolina Nebraska Oregon Montana Florida West Virginia Wyoming Holland UK, West Sussex UK, West Sussex Switzerland Finland UK, West Sussex Denmark, Stevns Denmark, Stevns Denmark, Vinderød Denmark, Arrenakke Switzerland Denmark, Taastrup Denmark, Taastrup Denmark, Taastrup Denmark, Taastrup Denmark, Taastrup Denmark, Taastrup Region Desert shrub Woodland Grape Experimental plots Prairie Desert shrub Oak savanna Soybean field Desert shrub Woodland Kellogg Station Grassland Grassland Grassland Grassland Corn field Soybean field Unknown Unknown Grassland Soybean field Corn field Desert Unknown Winter wheat Winter wheat Grassland Grassland Winter wheat Pea Field Corn field Fallow Barley Grassland Barley Barley Barley Wheat Wheat Wheat Habitat J. Stutz A. Murphy T. Wood P. Millner R. Kemery G. Bethlenfalvay F. Landis N. Schenck G. Bethlenfalvay T. McGonigle N. Johnson H. Agwa H. Agwa H. Agwa C. Rosier J. Morton D. Watson D. Watson J. Trappe C. Rosier N. Schenck J. Morton P. Millner S. Sturmer John Dodd John Dodd H.Gamper M.Vestberg John Dodd S.Rosendahl S.Rosendahl S.Rosendahl S.Rosendahl H.Gamper S.Rosendahl S.Rosendahl S.Rosendahl S.Rosendahl S.Rosendahl S.Rosendahl Collector 1 1 1 1 26 10 10 10 10 10 2 2 2 2 2 10 2 18 7 26 18 11 11 26 10 10 18 24 18 18 9 18 18 3 22 19 28 26 26 17 (1) (1) (1) (1) (1) (9) (9) (9) (9) (9) (2) (2) (2) (2) (2) (9) (2) (1) (1) (1) (1) (1) (1) (1) (9) (9) (1) (15) (1) (1) (8) (1) (1) (3) (12) (12) (12) (1) (1) (11) LSU 1 1 1 1 3 11 11 11 11 11 10 10 10 10 11 1 10 2 12 11 11 1 11 3 11 11 11 11 11 11 11 4 11 11 11 11 11 3 3 11 FOX 1 1 1 1 1 7 7 7 7 1 7 7 7 7 1 1 7 1 5 1 1 1 1 1 7 7 9 10 9 1 1 2 8 1 1 1 1 1 1 1 TOR Table 1 List of isolates, their origin, habitat and the collector. The last three columns indicate the haplotypes. For LSU, the numbers in parentheses indicate the haplotype after incompatible sites were removed GLOBAL STRUCTURE OF AMF 3 2009 Blackwell Publishing Ltd Isolate sp9.38 Beg 124 sp13.19 Beg 128 sp18.41 sp27.35 sp28.29 sp29.6 sp29.8 sp43.18 sp63.14 sp81.3 sp81.4 DK-Gm1 DKK04D22 DKB01D4 CL378 cu134a br221 sf117-1 sf1171-2 sy710-1 sy710-2 nb103c phi3138,BEG55 phi4138 BEG55 xj11138 BEG225 xj32138 BEG227 xj33138 BEG227 xz12138 BEG229 ja205c Bur11-9 Bur11-11 Pm1.2-17 NBR41 Narrabii City beach, WUM 16 City beach, WUM 16 AU2 AU8-7 AU8-8 AU33 AU34-29 au34-30 ID 41SP 42SP 43SP 44SP 45SP 46MA 47MA 48SP 49SP 50SP 51SP 52DK 53DK 54DK 55CL 56CU 57BR 58SA 59SA 60SY 61SY 62NB 63PH 64PH 65CI 66CI 67CI 68CI 69JA 70BU 71BU 72PM 73NB 74NA 75CB 76CB 77AU 78AU 79AU 80AU 81AU 82AU Table 1 Continued Europe Europe Europe Europe Europe Africa Africa Europe Europe Europe Europe Europe Europe Europe South America South America South America Africa Africa Asia Asia Africa Asia Asia Asia Asia Asia Asia Asia Australia Australia Australia Australia Australia Australia Australia Australia Australia Australia Australia Australia Australia Continent Spain (Jaén province) Spain (L’Alcudia, Valencia) Spain (Granada) Spain (Alicante province) Spain (Andarax, Almerı́a) Morocco (Oved Bahat, Rabat) Morocco (Oved Bahat, Rabat) Spain (Cartagena, Murcia) Spain (Aznalcóllar, Sevilla) Spain (Sierra de Baza, Granada) Spain (Sierra de Baza, Granada) Denmark, Taastrup Denmark, Taastrup Denmark, Taastrup Colombia Cuba Brazil South Africa South Africa Syria Syria Namibia Philippines Philippines China, Hetian China, Kashi China, Kashi China, Tibet Japan Butrren Junction, NSW Burren Junction, NSW Pittsworth Qld Paddock 4, Auscott, Narrabi, NSW Auscott, Narrabri, NSW Perth, WA Perth, WA Sydney basin Sydney basin Sydney basin Sydney basin Sydney basin Sydney basin Region Pasture Pasture Cotton Cotton Roadside Sand dune Sand dune Restored roadside Restored roadside Restored roadside Restored roadside Restored roadside Restored roadside Rosa canina Rosa canina Pea Barley Fallow M. esculenta Forest Serrata Agricultural (proprietary) Agricultural (proprietary) Barley nursery Barley nursery Desert shrub Cassava Cassava Maize Maize Maize Grassland Olea europaea var. sylvestris Olea europaea Citrus macrophylla Zea mays Stypa tenacissima Habitat 11 13 14 4 30 8 30 15 16 12 1 29 18 5 26 25 18 10 10 25 25 7 24 24 23 23 23 23 1 21 18 18 18 18 13 13 18 27 6 18 18 20 C. Azcón-Aguilar ⁄ C. Cano C. Azcón-Aguilar ⁄ J. Palenzuela J.M. Barea ⁄ M. Vázquez C. Azcón-Aguilar ⁄ J. Palenzuela J.M. Barea ⁄ J. Palenzuela R. Azcón ⁄ J. Palenzuela R. Azcón ⁄ J. Palenzuela J.M. Barea ⁄ J. Palenzuela C. Azcón-Aguilar ⁄ C. Cano J.M. Barea ⁄ J. Palenzuela J.M. Barea ⁄ J. Palenzuela S.Rosendahl S.Rosendahl S.Rosendahl E. Sieverding R. Herrera L. Maia A. Smit A. Smit D. Sands D. Sands C. Klopatek John Dodd John Dodd Gu Feng Gu Feng Gu Feng Gu Feng K. Akashi Richard Heath Richard Heath Peter McGee Peter McGee Peter McGee Tom Nicolson ⁄ Lyn Abbott Tom Nicolson ⁄ Lyn Abbott Peter McGee Peter McGee Peter McGee Peter McGee Peter McGee Peter McGee (1) (1) (1) (4) (10) (7) (10) (8) (10) (1) (1) (1) (1) (1) (1) (16) (1) (9) (9) (16) (16) (1) (15) (15) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (1) (17) (6) (1) (1) (13) LSU Collector 7 9 9 5 6 6 6 11 6 11 11 3 11 11 1 11 11 11 11 11 11 11 11 11 11 11 8 11 1 11 11 11 11 11 11 11 11 11 11 11 11 11 FOX 6 1 1 3 1 1 1 1 1 1 1 1 3 4 1 7 11 7 7 7 7 1 10 10 1 1 1 1 1 3 3 3 3 3 3 3 8 7 7 8 3 3 TOR 4 S . R O S E N D A H L , P . M C G E E and J . B . M O R T O N 2009 Blackwell Publishing Ltd GLOBAL STRUCTURE OF AMF 5 Multilocus haplotyping Nested multiplex PCR was run on single spores (Stukenbrock & Rosendahl 2005b), with DNA amplified from a minimum of four spores per fungal isolate. In cases where sequences were not identical, an additional four spores were sampled and both sequence types were included in the analyses. Three genes were targeted for amplification: 424 bp spanning the variable D2 region of the LSU rRNA gene using primers RK4f and LR4r, a219-bp intron in the FOX2 gene with primers FOX603f and FOX868r and a 302-bp intron in the TOR gene with primers TOR1071f and TOR1444r (Stukenbrock & Rosendahl 2005b). The PCR conditions were the same as that used by Stukenbrock & Rosendahl (2005b). Sequencing was performed by Macrogen Inc, Seoul Korea. Sequences are deposited in GenBank under the following accession nos: FOX2: GQ330656–GQ330737, LSU: GQ330738–GQ330819 and TOR: GQ330820–GQ330901. The LSUrDNA data were supplemented with GenBank sequences from Glomus geosporum, Glomus caledonium, Glomus coronatum and Glomus constrictum, and analysed using NeighborNet in the Splits Tree 4 application (version 4.10) (Huson 1998; Huson & Bryant 2006). Distances were calculated using the UncorrectedP method, which computes the proportion of nucleotide positions at which two sequences differ. Ambiguous states were treated as missing data. Compatibility Sequences of all three genes were aligned manually and the alignments were entered into SNAP workbench (Aylor et al. 2006). The alignments were combined using the Combine and Map modules in the SNAP workbench and were collapsed into haplotypes excluding indels and infinite site violations. The haplotypes were imported into pars (Phylip) for a phylogenetic analysis with unweighted parsimony. An inferred strict consensus tree was entered into SNAP Clade (Bowden et al. 2008) to analyse compatibility among variable nucleotide sites in the sequences (Jakobsen et al. 1997). The LSU showed several incompatibilities and as coalescent models assume no recombination, incompatible sites were removed using CladeEx (Aylor et al. 2006). Population differentiation The hypothesis of no genetic differentiation within G. mosseae was tested among the North American, European and Australian population. A combined file of haplotypes and geographical locations (continents) was generated using SNAP Map. The file was converted into a distance matrix using Seqmatrix, and genetic 2009 Blackwell Publishing Ltd subdivision between the three continents was tested with Permtest and the Nearest Neighbor statistics, Snn (Hudson et al. 1992). Snn is a measure of how often the nearest neighbours of sequences are found in the same locality. Populations are considered undifferentiated when Snn values are near 0.5, whereas values approaching 1.0 indicate significant differentiation (Malvárez et al. 2007). Significance was calculated by comparing observed statistics with a distribution produced by 100 000 random permutations. Migration and time of divergence between North American, European and Australian populations were studied by coalescent analysis performed with Migration and Divergence (MDIV) (Nielsen & Wakeley 2001). MDIV implements likelihood and Bayesian methods using MCMC coalescent simulations that estimate population mean mutation rate h, divergence time ⁄ rate of migration and the time span because two populations diverged from their most recent common ancestor (TMRCA). An infinite site model was used in sampling 2 · 106 trees with a burn-in of 5 · 105. Max T (time of divergence) was set to 3 and Max M (migration) to 10. The analysis was repeated three times with similar results. Gene tree The ancestral history of G. mosseae isolates was reconstructed by coalescent analyses performed in Genetree (Griffiths & Tavaré 1994). Genetree estimates the joint likelihood surfaces with respect to h (Theta) for each possible rooted gene genealogy. Genetree also computes time span to TMRCA and mutation age. A minimum of 10 simulations of 1 million runs each with different random seeds was used to ensure convergence of the results between runs. For the genealogy with the highest likelihood, age of mutations was estimated. Treepic (Griffiths & Tavaré 1994) was used to generate a genealogy depicting coalescent time units. As a result of the conflicting sites in the LSU data set, the Genetree analyses were performed separately on the LSU alignment and on a combined FOX2–TOR alignment. The Genetree analysis of both G. mosseae data sets revealed a lack of ancestral mutations, and data from all three loci were combined with a data set obtained from the closely related species, G. geosporum. Coalescent time (T) was converted to real time (t) using t = NeTg, where Ne is the effective population size and g is the generation time in years. Ne was calculated from the estimated h values as: Ne = h ⁄ 2l, where l is the mutation rate per site. The mutation rate was not known, and so mutations were assumed to be neutral and increased at a rate of 1 · 109 substitutions per site per year (Kasuga et al. 2002). 6 S . R O S E N D A H L , P . M C G E E and J . B . M O R T O N Demographic models For each of the three genes, nucleotide diversity (pi) (Nei 1987) and haplotype diversity were estimated and the data were tested for deviation from neutral evolution by Tajima’s D test (Tajima 1989) and Fu and Li’s F* and D* tests (Fu and Li 1993) using the program DnaSP ver. 5.00 (Rozas et al. 2003). These tests not only test for departures from neutrality caused by selection, but should also detect the impact of population expansion or decline (Rogers & Harpending 1992). The hypothesis of a recent population expansion of G. mosseae was evaluated by calculating mismatch distributions as the pairwise differences between haplotypes. Mismatch distribution is usually unimodal in populations that have passed thorough expansion, whereas it is multimodal in population at demographic equilibrium (Rogers & Harpending 1992). Mismatch distribution was calculated based on haplotypes obtained by concatenating the LSU, FOX2 and TOR loci into a single 925-bp sequence after gaps were excluded, using DnaSP 5.00 (Rozas et al. 2003). The observed distribution was compared with an expected frequency distribution based on a population growth-decline model with an initial h = 0 and a final h = 1000. The program BEAST version 1.4.7 (Drummond & Rambaut 2007) provided a hypothesis of the demographic history of G. mosseae populations based on sequence genealogies obtained from combining FOX2 and TOR sequences. BEAST uses a Bayesian coalescent-based procedure with MCMC to sample the posterior distribution of genealogical trees, coalescence events and demographic parameters through time, given observed DNA sequence data and a substitution model. An expansion growth model was used as the primary demographic model in this analysis. The nucleotide substitution models that best fit observed data were estimated with the program jModelTest version 0.1.1 (Posada 2008). A normal distributed substitution rate and a mean of 1 · 109 substitutions per site based on the values by Kasuga et al. (2002) was applied to a strict molecular clock model. The substitution model HKY (Hasegawa et al. 1985) was chosen based on Akaike information criterion (Akaike 1973) in jModelTest MCMC chains were run with 107 iterations, with trees sampled at every 1000 iterations and a burn-in of 1000. Such an extensive run was possible through the use of the Computational Biology Service Unit at Cornell University, which is partially funded by Microsoft Corporation. Log files were analysed using tracer version 1.4 (Rambaut & Drummond 2007), and effective sample size values were used to evaluate whether sufficient MCMC chains were utilized. To assess the robustness of parameter estimates, three independent chains were run with identical settings using data from the focal populations. The three runs yielded very similar parameter inferences. The program log combiner version 1.4.7 (Drummond & Rambaut 2007) combined the chains into a composite chain. The expansion model was compared with a model of constant population size representing the simplest possible demographic history and an exponential growth model, to determine its utility compared with that of other demographic models. Bayes factor tests in tracer evaluated the models by importance of sampling of the marginal likelihoods of each of the three demographic models. Results The number of haplotypes identified from LSU, FOX2 and TOR markers of 82 isolates of G. mosseae differed between continents and varied with the gene markers (Table 2). Of the three gene markers, the LSU region yielded the most haplotype variation. Sequences differed between individual spores from the same cultures, but in most the differences were minor and involved either gaps or single nucleotide substitutions. For a few spores, sequences differed by up to 6 bp. When haplotypes differed in the same culture, variants were included in the analyses. Table 2 Number of samples and haplotypes from the six continents. Haplotype (gene) diversity and its sampling variance, Nucleotide diversity, pi (p) estimated according to Nei (1987) Continent Isolates (n) No. haplotypes (h) Haplotype diversity Hd (variance) Nucleotide diversity pi North America Europe South America Africa Asia Australia Total 23 29 3 7 7 13 82 13 25 3 5 4 8 32 0.945 0.988 NA 0.905 0.810 0.936 0.978 0.00742 0.00733 NA 0.00819 0.00540 0.00601 0.00730 (0.0009) (0.00018) (0.0106) (0.0169) (0.00257) (0.00004) 2009 Blackwell Publishing Ltd GLOBAL STRUCTURE OF AMF 7 analysis showed a reticulate structure in most species, but only among the interior branches, indicating homoplasy rather than recombination. Compatibility Fig. 1 NeighborNet parsimonious tree based on LSUrDNA. The circles indicate morphological species. The Glomus mosseae sequences are from this study and other sequences are from GenBank. When the three genes were combined, the haplotype map showed 37 variable sites, excluding indels and infinite site variations. A total of 32 haplotypes were identified. The compatibility matrix for the combined data set revealed no incompatible sites among and within the FOX and TOR genes, whereas the LSUrRNA gene showed several incompatibilities (Fig. 2). No recombination blocks were detected within the LSU alignment. The LSU data set was reduced from 30 to 17 haplotypes when incompatible sites were excluded. This reduction was mainly the result of collapsing 10 haplotypes into one haplotype (H1). The combined FOX2 TOR alignment revealed 19 haplotypes with 26 variable sites. NeighborNet NeighborNet analysis of the LSUrRNA gene that all of the globally distributed G. mosseae tions formed a cluster distinguishable from the of other closely related Glomus species (Fig. LSU 2009 Blackwell Publishing Ltd showed populaclusters 1). The FOX2 Migration and diversification As the samples obtained from Africa, South America and Asia were low, populations from these continents were not included in this analysis. Focusing on Europe, TOR Fig. 2 Site compatibility matrix for the LSU, FOX2 and TOR locus, generated in SNAP Clade. The diagonal line highlights the symmetry in the matrix and the horizontal line the borders between the three genes. Numbers designate variable sites in the sequences and incompatible sites are indicated by dark fields, and compatible sites are left white. 8 S . R O S E N D A H L , P . M C G E E and J . B . M O R T O N Fig. 3 Migration and time of divergence. The curves show the posterior probability distributions between samples generated in MDIV. The X-axes represent time measured in 2Ne generations and the Y-axes are the likelihood functions for migration and time of divergence. Top: Europe vs. North America; middle: Europe vs. Australia; and bottom: North America vs. Australia. North America and Australia, the Nearest Neighbor statistics for the pairwise comparisons gave values between 0.50 and 0.57, and revealed no significant subdivisions. This was also shown by MDIV, where estimates of migration M and time of divergence T were obtained from likelihood estimates (Fig. 3). TMRCA, when converted to real time assuming a neutral mutation rate of 10)9 per site and a generation time of one year, was estimated to be between 5 and 6.6 Myr. As no significant subdivision was detected, time of divergence was not converted to real time. Genetree The coalescent analysis in Genetree (Fig. 4A, B) showed for both data sets that all mutations were recent, with a notable absence of ancient mutations. Internal structure and geographical subdivisions were not observed, suggesting that they were absent. The LSU tree with the highest likelihood (3.96 · 10)25) was selected giving a h value of 4.47 ± 1.50 and a TMRCA of 0.9 coalescent units. The combined FOX–TOR tree with the highest likelihood was 1.83 · 10)25 and a h estimate of 5.22 ± 1.63 and a TMRCA of 0.95 ± 0.25. Coalescent times were converted to real time using a generation time of 1 year and a mutation rate of 1 · 10)9 neutral substitutions per site. The effective population size Ne was estimated from the h values, giving a real-time estimate from 2.0 · 106 to 7.1 · 106 years. Another data set including combined sequences of the three genes from G. mosseae with isolates of Glomus geosporum was also analysed. In this analysis, a 216-bp region of the LSU spanning the D2 region was used. The analysis discriminated 20 haplotypes based on 54 variable sites after removing conflicting sites. The gene tree analysis showed a different topology of the gene tree from the two species (Fig. 5). The tree with the highest likelihood had a likelihood of 1.6 · 10)36 and a h of 9.8 and a TMRCA of 2.9 in coalescent units. Conversion to real-time estimates of 2009 Blackwell Publishing Ltd GLOBAL STRUCTURE OF AMF 9 A B Fig. 4 Coalescent-based gene genealogy inferred using Genetree for (A) LSU and (B) the combined sequence data from FOX2 and TOR. The timescale is in coalescent units of effective population size. Solid circles indicate the distribution of mutations in the genealogy. The mutations are numbered according to their positions (Fig. 2). The number of isolates representing the different haplotypes from the different continents is indicated below the gene genealogy. age suggested that G. mosseae and G. geosporum began to diverge 2.03 · 107 years ago, with G. mosseae evolving 5 · 106 years ago. Population size changes Tajima’s D and Fu & Li’s F* and D* statistics were not significant and the hypothesis of neutrality could not be rejected (Table 3). The distribution of the observed pairwise nucleotide site differences (mismatch distribution) was similar to the expected distribution in an expanding population (Fig. 6). The final theta was set to 1000 (infinite) and the initial theta was estimated to be 1.23. This gave an estimated date of the growth s = 5.52 measured in units of mutational time. In spite of the insignificant Tajima’s D and Fu & Li’s F* and D*, the star-like pattern of the network of G. mosseae (Fig. 1) and the result of the mismatch distribution (Fig. 6) indicated that a population expansion may have occurred. The reconstruction of the demographic changes in BEAST also supported a high likelihood for a population expansion (Table 4). The model suggested that the expansion was recent (Fig. 7). Assuming a mutation rate of 10)9, the expansion must have occurred within 500 000 years BP. 2009 Blackwell Publishing Ltd Discussion No significant genetic differentiation among the populations of G. mosseae from different continents was detected. G. mosseae originating from sites around the globe had similar population structure and thus may be considered a cosmopolitan species. The lack of differentiation is unexpected as glomeromycotan fungi are an ancient clonally reproducing monophyletic group and G. mosseae is considered to be as ancient as its relatives. Judson & Normark (1996) hypothesize that speciation of glomeromycotan fungi took place before the continents drifted apart, with subsequent conservation of traits resulting from the absence of recombination. If true, speciation would have occurred more than 200 Ma during the Permian and Triassic periods. However, geographical separation and genetic isolation should have resulted in genetic differentiation of populations on different continents. The coalescent analysis in both Genetree and the MDIV suggested that speciation occurred more recently after continents separated. A more plausible explanation for the pandemic distribution coupled with lack of geographical differentiation is that the fungus has been spread much more recently. The absence of geographical differentiation could be the outcome of unobstructed gene flow between 10 S . R O S E N D A H L , P . M C G E E and J . B . M O R T O N 1.0 42 43 Table 3 Tajima’s D, Fu & Li’s D* and F* tests for neutrality of the three alleles. None of the estimates were significant and the null hypothesis of neutrality could not be rejected 40 Tajima’s D Fu & Li’s D* Fu & Li’s F* )1.36276 )1.43958 )1.18532 )1.83429 )1.71679 )1.17227 )1.97806 )1.92401 )1.39928 37 33 0.8 31 45 30 46 28 0.6 22 53 17 15 54 13 0.4 2 8 10 6 19 9 34 5 36 14 38 52 21 1 0.2 1 26 35 51 48 49 50 5 3 G. geosporum 1 18 20 11 12 4 29 3 16 3 LSU FOX2 TOR 7 8 4 1 1 5 2 2 21 32 23 27 24 1 1 41 44 47 25 39 0.0 1 30 3 2 G. mosseae Fig. 5 Coalescent-based gene genealogy inferred using Genetree for the combined sequence data from G. mosseae and G. geosporum. The timescale is in coalescent units of effective population size. Solid circles indicate the distribution of mutations in the genealogy. continents and recent divergence time. As glomeromycotan fungi reside in soil, any spread across oceans presumably involves an effective vector such as humans. Plant pathogens, which also may lack genetic differentiation, are spread around the globe from infected seeds or tubers (Stukenbrock et al. 2006). However, some genetic structuring is apparent among populations of some pathogens, which may arise because of different selection pressures in different environments (Fisher et al. 2005), Differential selection pressures also apply to AMF. The lack of global genetic structure in G. mosseae contrasts with the evidence of genetic structure at the local scale (Stukenbrock & Rosendahl 2005a; Rosendahl & Matzen 2008). Currently, there is no explanation for structure at the local scale; isolation by distance has been ruled out (Rosendahl & Matzen 2008). However, competition between individual mycelia could be an important factor (Rosendahl 2008), because this process would generate a patchy distribution of individuals only at a local scale. The lack of isolation by distance indicates that the fungi have efficient dispersal. However, information is pertinent only at a local scale, and we know little about dispersal at the regional and continental scale. The Genetree analysis of the sequence data showed no ancient mutations in G. mosseae. This evidence supports the hypothesis that the species has evolved clonally, and the complete linkage of genes because of clonality could have contributed to selective sweeps. The lack of ancient mutations makes the estimations of divergence time difficult. However, the topology of the genetree with several recent mutations (Fig. 4A, B) is also consistent with a model where the population has undergone a significant population increase. The genetree thus will not provide conclusive evidence for the hypothesis of ancient clonal evolution of glomeromycotan fungi. Sequence polymorphism within spores has been observed for G. mosseae by Sanders et al. (1995) who found two closely related but different ITS sequences within a single spore. Such polymorphism was not observed with the FOX2 and TOR sequences (Stukenbrock & Rosendahl 2005b), but some intra-spore polymorphism in LSU may have been present. In some cases, one or two positions in the LSU sequences had uncertain reads on the chromatograms, which could be explained by sequence polymorphism. However, as the LSU and the FOX2–TOR genetrees were analysed separately with similar results, intra-spore polymorphism did not seem to influence the result of this study. Recent expansion of G. mosseae is supported by the mismatch distribution and the BEAST analyses, but the time of the expansion is difficult to determine as the generation time and the mutation rate of the 2009 Blackwell Publishing Ltd GLOBAL STRUCTURE OF AMF 11 0.18 Observed 0.16 Constant 0.14 Expanding Frequency 0.12 0.1 0.08 0.06 0.04 0.02 0 0 5 10 15 20 25 30 Pairwise differences Fig. 6 Mismatch distribution for G. mosseae haplotypes. Observed data (filled circles) compared with data expected under demographic expansion in an unsubdivided population model (triangles) and expected under a constant population size model (diamonds). Fig. 7 Model comparison plot showing inferred historical effective population size (Ne) for the global G. mosseae population under a constant size model (dashed line) and an expansion population model (solid line). The 95% highest probability density is indicated using the grey lines. The timescale on the X-axis is in years before present (years BP). disturbances associated with human activity expanded dramatically on all continents. Although we cannot conclude that the range expansion of G. mosseae coincides with increased cropping activities, our data suggest that the expansion could be recent. Agriculture involving annual mycorrhizal hosts over large land masses may have created an ideal habitat for this species. Explosive expansion in disturbed soils is typical of a ruderal life strategy, but this phenomenon does not explain the mechanism enabling the current widespread distribution. Glomus mosseae is wellknown to survive in dried root fragments and as spores in dry soil (McGee et al. 1997). As a consequence of this tolerance of drying, the fungus can be readily transported from place to place in soil (Tommerup & Kidby 1979). Thus, the intervention of humans is unnecessary for the dispersal of the fungus, but critical for creating conditions where G. mosseae can initiate colonization and then flourish. The massive areas sown to annual mycorrhizal hosts may therefore have contributed to the population expansion and increase of G. mosseae. Our data indicate that G. mosseae may have existed before humans dramatically increased land use, perhaps restricted to disturbed sites. Other studies have genes are unknown. Generation time for a clonal fungus with indeterminate hyphal growth is difficult to define. Generation time can be defined as the time from spore germination to spore formation, in which case, there will be several generation times per year. However, as the spores are multinucleate and sporulation does not involve meiosis, occurrence of the latter cannot distinguish generations. For purposes of this analysis, then, a generation time was estimated conservatively to be one year based on the annual growth cycle of many agricultural crops used in this study. The mutation rate from Kasuga et al. (2002) was based on ribosomal genes, and the intron regions used in this analysis may mutate faster. If the time of expansion was initiated 5000 years BP, the mutation rate would be 10)7 or 100 times faster than that determined by Kasuga et al. (2002), which is within the limits of mutation rates in other fungal genes (Stukenbrock et al. 2007; Lang & Murray 2008). Indeed, this mutation rate produces BEAST estimates of the population expansion within the last few hundred years, a period when agriculture and other Table 4 Results from BEAST. Bayes factor (BF) tests comparing three demographic models for the global G. mosseae population. The BF values correspond to rows compared with columns. Marginal tree likelihood of the model: ln P; standard error of the estimate: SE Model ln P(model) SE Exponential growth Constant size Expansion growth Exponential growth Constant size Expansion growth )2254.412 )2252.668 )2251.597 1.15 1.03 1.74 — 5.72 16.70 0.175 — 2.92 0.06 0.343 — 2009 Blackwell Publishing Ltd 12 S . R O S E N D A H L , P . M C G E E and J . B . M O R T O N suggested that G. mosseae represents a ruderal strategist adapted to disturbed systems (Sýkorová et al. 2007) and the fungus appears to colonize plant roots readily, without differential host compatibility. Sporulation often occurs shortly after colonization, and the fungus can produce numerous spores in pot cultures. The species is also present in more permanent vegetation, but with less frequent occurrence (Mosse & Bowen 1968; Helgason et al. 1998; Stutz et al. 2000; Jansa et al. 2002; Rosendahl & Stukenbrock 2004). An opportunistic ecology still may apply in more permanent vegetation systems because of disturbance associated with tracks, tree fall, erosion, fire and floods. If our hypothesis is correct, then human activity has had a potentially huge impact on the population genetics of G. mosseae. The increased disturbance of land, especially from agricultural activity, has created environments where this opportunistic fungus might expand its habitat. Continuing disturbance will ensure the continuation of the species and possibly other Glomalean fungi. Migration between continents has diminished genetic divergence and migration is likely to continue. The origin of G. mosseae is unknown. Too few populations were sampled from Africa, Asia and South America to resolve estimates of genetic diversity. We found the highest population diversity in Europe, which may be a result of greater sampling intensity. More extensive sampling from other continents is needed to identify a possible epicentre for this species. This study provides important clues regarding the possible impact of human activity on population genetics of fungal symbionts. In the case of G. mosseae, the rapid and widespread change in land use for agricultural purposes has opened up possibilities for this opportunistic fungus to dominate communities and migrate rapidly between continents, which in turn have diminished genetic divergence amongst these widely distributed populations. We hypothesize that the evolution and population genetic structure of G. mosseae is strongly influenced by human activity. Several fungi are known to be influenced by human activity, including plant pathogens (Couch et al. 2005; Kohn 2005) and fungi that are found on substrates used by humans including Aspergillus oryza, and Serpula lacrymans (Kauserud et al. 2007). The role of humans is an important consideration in understanding the rate and degree of diversification in G. mosseae and other glomeromycotan species. Other AMF may represent opportunistic fungi, and their biology will be predicated in part by their response to human activities. Consequently, even basic concepts in this universal symbiosis may not be understood solely from studying such ruderal species. Acknowledgements We are grateful to Conchi Azcon, John C Dodd, Lyn Abbott, Hannes Gamper, Gu Feng, Mauritz Westberg and Richard Heath for allowing us to use their cultures and to the many collectors who have contributed to the INVAM collection. We also wish to thank Hans R. 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