Speciation of a tropical fungal species pair following transoceanic dispersal

Molecular Phylogenetics and Evolution 51 (2009) 413–426

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Speciation of a tropical fungal species pair following transoceanic dispersal Miao Liu *, Michael G. Milgroom, Priscila Chaverri 1, Kathie T. Hodge Department of Plant Pathology and Plant–Microbe Biology, Cornell University, Ithaca, NY 14853, USA

a r t i c l e

i n f o

Article history: Received 13 January 2007 Revised 1 December 2008 Accepted 12 March 2009 Available online 24 March 2009 Keywords: Moelleriella libera Moelleriella raciborskii Hypocreales Fungi Biogeography Migration Coalescence Phylogenetics Paleotropics Neotropics

a b s t r a c t This study focuses on a pair of fungal species, Moelleriella libera and M. raciborskii (Ascomycota: Clavicipitaceae) from the neotropics and paleotropics, respectively, that are phenotypically nearly indistinguishable. Molecular analyses based on DNA sequences from RNA polymerase II subunit 2 (RPB2), translation elongation factor 1-a (EF1-a) and b-tubulin genes confirm that they are recently derived sister species. Speciation appears to have followed an historical transoceanic dispersal event. Models of population structure and migration from TCS, IM, and coalescent-based analyses suggest there is little gene flow between the two species. The direction of dispersal, investigated using the progression rule and coalescent-based gene genealogies, was likely from the New World to the Old World. Ó 2009 Elsevier Inc. All rights reserved.

1. Introduction Fungal biologists have only recently begun to explore the speciation and historical distribution of fungi. Due to rapid fungal speciation and reduced morphology, many morphological species have been revealed to comprise multiple genetically isolated lineages, which can be considered phylogenetic (Taylor et al., 2000) or cryptic species (Kohn, 2005). Despite their morphological similarities, genetic approaches have often revealed differences among these cryptic species that impact pathogenesis, virulence, and ecological associations (Harrington and Rizzo, 1999; Kohn, 2005; Taylor et al., 2000). Many species pairs exhibit disjunct Old World–New World distributions, but the origins of the disjunction are not understood. The recent literature of the field is marked by a changing emphasis on vicariance versus transoceanic dispersal as a driving force (de Queiroz, 2005). Before the 1960s, oceanic dispersal was a common explanation. Later, and increasingly after the validation of platetectonic theory, many disjunct distributions were explained as vicariance events (e.g., southern beeches, cichlid fishes, pleurodi-

* Corresponding author. Present address: Biodiversity (Mycology and Botany), Eastern Cereal and Oilseed Research Centre, Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, Ont., Canada K1A 0C6. E-mail addresses: [email protected], [email protected] (M. Liu). 1 Present address: Department of Plant Sciences and Landscape Architecture, University of Maryland, College Park, Maryland 20742, USA. 1055-7903/$ - see front matter Ó 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.ympev.2009.03.014

ran turtles, etc. (Knapp et al., 2005; also see Patterson, 1981)). Among fungi, vicariance has been invoked to explain the distribution of phylogenetic species of the Gibberella fujikuroi (O’Donnell et al., 1998) and Hyphoderma setigerum (Nilsson et al., 2003) species complexes, as well as the worldwide distribution of shiitake mushrooms (Lentinula species) (Hibbett, 2001). On the other hand, recent advances in estimating the divergence time of taxa by nucleotide substitutions have suggested that many sister taxa distributed across the ocean diverged far more recently than can be explained by continental fragmentation events. In such cases, oceanic dispersal is a more reasonable explanation for disjunct patterns of distribution. Fungi can be dispersed by a variety of propagules, including spores, sclerotia, long-lived rhizomorphs and mycelia embedded in a host substrate—it would not be surprising to find that oceanic dispersal should have played important role in creating disjunct distributions. Vilgalys and Sun (1994) invoked intercontinental dispersal to explain the distribution pattern of the Pleurotus ostreatus species complex; Hibbett (2001) inferred the long distance dispersal of Lentinula species between Australia and New Zealand. The origin and direction of dispersal are of interest. Phylogenetic analysis and coalescent-based approaches have potential for elucidating such polarities (Carbone and Kohn, 2004; Carbone et al., 2004; Hudson et al., 1992; Humphries and Parenti, 1999; Rosenberg and Nordborg, 2002; Templeton, 1998). Retrospective approaches through phylogeography have also been useful to shed light on mechanisms of fungal speciation (Kohn, 2005). Population genetic models, e.g., isolation and migration,

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can be used to test the hypothesis of recent divergence with limited gene flow against ancient divergence with constant gene exchanges. This study focuses on a pair of morphologically similar microfungal species in the order Hypocreales (Ascomycota), family Clavicipitaceae: Moelleriella libera (Syd.) Chaverri et al. (2008, asexual state, Aschersonia aleyrodis Webber) and M. raciborskii (Zimm.) Liu & Chaverri, comb. nov. (basionym, Hypocrella raciborskii Zimm., Zentbl. Bakt. Parasit. Kde, Abt. II 7(2): 876 (1901), asexual state, A. placenta Berk). In nature, M. libera occurs in the New World tropics, where it causes a fatal disease of whiteflies (Evans and Hywel-Jones, 1990; Petch, 1921), and has been used as a promising biological control agent for the control of whitefly pests (family Aleyrodidae). Moelleriella raciborskii occupies a similar niche in the Old World tropics. They have been treated as two distinct species based on a few minute morphological differences (Petch 1921, 1925; Mains, 1959a,b,c), Due to their nearly indistinguishable morphology and ecological niches, Mains (Mains, 1959a,b,c) tentatively synonymized them. Based upon a recent multilocus phylogenetic analysis (Liu et al., 2006), in which a clade of Old World M. raciborskii isolates nested in the New World M. libera clade, we hypothesize that these two species might have diverged recently, following oceanic dispersal. Recent advances in population genetics have developed models, i.e. isolation and migration, which can be used to test the hypothesis of recent divergence with limited gene flow against ancient divergence with constant gene exchanges. To test this hypothesis, and to infer historical events associated with speciation, we sampled more Old World isolates, used phylogenetic, nested clade, and coalescent-based approaches to analyze fast-evolving nuclear genes, and tested sequence data against the isolation and migration models. 2. Materials and methods 2.1. Isolates and DNA extraction A sample of 36 isolates of M. libera and M. raciborskii were obtained through field collections and culture collections (Table 1). Eight isolates of M. ochracea and one isolate of each of 11 other species were included as reference species. The isolates were cultured by the procedure described by Liu and Hodge (2005). DNA was extracted using the miniprep protocol described in Lee et al. (1988), augmented by adding 2.5 M NaCl in TE before ethanol precipitation to remove polysaccharides (Fang et al., 1992). 2.2. PCR and sequencing Portions of three putatively single-copy, unlinked nuclear genes were sequenced to serve as sources of molecular variation. Part of the gene encoding RNA polymerase II subunit 2 (RPB2) was amplified with the primers RPB2-7f and RPB2-11ar (Liu et al., 1999); translation elongation factor 1-a (EF1-a) with the primers Efdf (AAGGAYGGNCARACYCGNGARCAYGC) and EF-2218R (ATGACACC RACRGCRACRGTYTG) (S. Rehner, pers. comm.); and b-tubulin with T1 and T2 primers (O’Donnell and Cigelnik, 1997). PCR conditions for the amplification of RPB2 were described in Liu and Hodge (2005). For EF1-a, PCR conditions were 95 °C denaturing for 1 min, followed by 10 cycles of denaturing at 94 °C for 1 min, annealing at 66 °C (decreasing 1 °C per cycle) for 1 min, extension at 72 °C for 1.5 min; plus 30 cycles of 94 °C for 1 min, 56 °C for 1 min, 72 °C for 1.5 min; final extension at 72 °C for 10 min. For b-tubulin, PCR conditions were 95 °C denaturing for 5 min, followed by 35 cycles of denaturing at 95 °C for 1 min, annealing at 52 °C for 2 min, extension at 72 °C for 2 min, plus a final extension at 72 °C for 10 min. PCR products were purified using the QIAquick gel purification Kit (Qiagen GmbH, Hilden, Germany). Purified PCR

products were sequenced in both directions at the Biotechnology Resource Center at Cornell University using the PCR primers for EF1-a and b-tubulin, while primer RPB2-7 and the internal primer RPB2-11ARL (Liu and Hodge, 2005) were used for RPB2. All sequences were accessioned in GenBank (Table 1). 2.3. TCS analysis Moelleriella libera and M. raciborskii appear to be recently diverged lineages (Liu et al, 2006), therefore we took a TCS approach appropriate for the interface between population and species to look for genetic subdivision between the two putative species. Based on statistical parsimony (Templeton et al., 1987; Templeton, 1998), TCS analysis estimates gene flow by constructing haplotype networks while accounting for population size and allele frequency (Kingman, 1982a). DNA sequences from the RPB2, EF1-a, and btubulin genes of M. libera and M. raciborskii were analyzed using TCS 1.21 (Clement et al., 2000). Sequences were aligned using default parameters in ClustalW (Thompson et al., 1994). Local misalignments were adjusted by eye. Sequences were collapsed to haplotypes (Table 2). In the subsequent analysis, parsimony probability was set at 95% so that steps with a probability of parsimony higher than 95% would be connected, while those lower than 95% would be left unlinked. Templeton’s inference key (Templeton, 2004) was used to infer biological phenomena based on the TCS results. 2.4. IM, MDIV and MIGRATE analyses We estimated migration using population genetic analyses to infer dispersal events. Models distinguishing migration from isolation were based on the assumptions that there is no recombination within and among the loci; and that the genes are selectively neutral. Guided by the procedure of Carbone et al. (2004) we first collapsed sequences of the three genes for all M. libera and M. raciborskii isolates to unique haplotypes using SNAP Map (Aylor and Carbone, 2003). To detect gene segments lacking recombination and gene conversion, we examined the incompatibility among segregating sites of three gene regions by generating incompatibility matrices in SNAP Clade and Matrix (Markwordt et al., 2004). DnaSP version 3.53 (Rozas and Rozas, 1999) was used to test for neutrality. The estimators incorporated in the program include Tajima’s D (Tajima, 1989), Fu’s Fs (Fu, 1997), Fu and Li’s D*, and Fu and Li’s F* (Fu and Li, 1993). Tajima’s D detects the effects of selection by comparing h derived from Watterson’s (Watterson, 1978) and Tajima’s estimates. Significant differences between these two estimates indicate deviations from neutrality (Tajima, 1989). A significant Fu’s Fs suggests population growth and genetic hitchhiking, while Fu and Li’s tests are best for detecting background selection (Fu and Li, 1993). MIGRATE (Beerli and Felsenstein, 1999, 2001) estimates a migration matrix based on coalescent theory through joint estimation of both maximum likelihood and Bayesian inference (Kingman, 1982a,b). The null hypothesis of no equilibrium migration (M = 0) was tested using MDIV (Nielsen and Wakeley, 2001) through a Markov chain Monte Carlo (MCMC) approach. IM, for isolation and migration (Hey and Nielsen, 2004), was used to estimate if a recent isolation with no migration model fits the DNA sequence data. The latter two models are particularly important to test the hypothesis of recent divergence with no gene flow. 2.5. Phylogenetic analyses The geographic center of origin can be investigated through a biogeographic approach by applying the progression rule (Humphries and Parenti, 1999) to rooted phylogenetic trees. Therefore, parsimony analyses were performed in PAUP4.0b10 (Swofford,

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Table 1 Fungal isolates, geographic origins and GenBank accession numbers. GenBank numbers in bold indicate the sequences generated in this study. Other sequences with GenBank numbers starting with DQ were generated by Liu et al. (2006); those starting with AY were generated by Liu and Hodge (2005) and Liu et al. (2005). Speciesa

Isolate

Voucher

Origin

M. libera (New World)

CR08 CR19 CR20 FL16 FL44 FL45 FL48 FL49 JB133 MCA2465 ML175-1 ML175-2 ML175-3 ML175-4 PC321 PC413-1 PC434 PC439 PC553 PC578 AFR28 AFR114 ARSEF2154 ARSEF4209 BCC1454 BCC 2163 BCC 2175 BCC 2227 BCC 2230 CBS 34984 CBS 91779 CHN1 CHN3 CHN4 PC533 AFR34A AFR68 AFR116 CHN2 CR22 ML201-2G PC451 PC626 CR28 CR02 CR25 CR33 CR34 ARSEF 2396 BCC2339 BCC1487 AFR55 PC613 PC597 AFR33

ARSEFb 7512 CUPc 67341 CUP 67342 ARSEF 7311 ARSEF 7339 ARSEF 7340 ARSEF 7343 ARSEF 7344 ARSEF 7641 ARSEF 7642 CUP-PR-4421-1 ARSEF 7393 ARSEF 7394 CUP-PR-4421-4 ARSEF 7617 CUP 67519 CUP 67525 CUP 67528 PC553 PC578 ARSEF 7637 ARSEF 7616 ARSEF 2154 ARSEF 4209 BCCd 1454 BCC 2163 BCC 2175 BCC 2227 BCC 2230 CBSe 34984 CBS 91779 ARSEF 7607 ARSEF 7686 ARSEF 7609 – CUP 67556 CUP 67560 ARSEF 7639 ARSEF 7608 CUP 67345 ARSEF 7397 CUP 67531 PC626 ARSEF7514 ARSEF 7509 ARSEF 7513 ARSEF 7515 CUP 67369 ARSEF 2396 BCC2339 BCC1487 – – – CUP 67510

Costa Rica Costa Rica Costa Rica USA USA USA USA USA Panama Guyana Puerto Rico Puerto Rico Puerto Rico Puerto Rico Costa Rica Honduras Mexico Mexico Bolivia Bolivia Ghana Cameron Malaysia Indonesia Thailand Thailand Thailand Thailand Thailand Japan China China China China Vietnam Ghana Ghana Cameron China Costa Rica Puerto Rico Mexico Ecuador Costa Rica Costa Rica Costa Rica Costa Rica Costa Rica Philippines Thailand Thailand Ghana Bolivia Bolivia Ghana

M. raciborskii (Old World)

M. ochracea

M. turbinata H. viridans M. zhongdongii M. phyllogena M. rhombispora A. insperata A. sp. A. sp. A. napoleonae A. castanea A. blumenaviensis H. africana

GenBank No. RPB2

EF1-a

b-Tubulin

AY932776 DQ069943 DQ069941 DQ069932 DQ069934 DQ069935 DQ069936 DQ069933 DQ069940 DQ069950 DQ069944 DQ069945 DQ069946 DQ069947 DQ069942 DQ069937 DQ069938 DQ069939 DQ069948 DQ069949 DQ069965 DQ069964 DQ069951 DQ069953 DQ069955 DQ069954 DQ069952 DQ069963 DQ069956 DQ069958 DQ069959 DQ069960 DQ069961 DQ069962 DQ069957 DQ069968 DQ069969 DQ069970 DQ069971 DQ069972 DQ069973 DQ069974 DQ069975 AY932777 AY932767 AY932772 AY932778 DQ069977 DQ069976 – DQ069978 DQ069979 DQ069980 DQ069981 DQ069982

DQ069994 DQ069995 DQ069992 DQ069983 DQ069985 DQ069986 DQ069987 DQ069984 DQ069991 DQ070002 DQ069996 DQ069997 DQ069998 DQ069999 DQ069993 DQ069988 DQ069989 DQ069990 DQ070000 DQ070001 DQ070017 DQ070016 DQ070003 DQ070005 DQ070007 DQ070006 DQ070004 DQ070015 DQ070008 DQ070010 DQ070011 DQ070012 DQ070013 DQ070014 DQ070009 DQ070020 DQ070021 DQ070022 DQ070023 DQ070024 DQ070025 DQ070026 DQ070027 DQ070028 DQ070030 DQ070031 DQ070032 DQ070033 DQ070029 DQ070035 DQ070034 AY986936 AY986944 AY986930 AY986943

DQ070045 DQ070046 DQ070043 – DQ070037 – DQ070038 DQ070036 DQ070042 DQ070053 DQ070047 DQ070048 DQ070049 DQ070050 DQ070044 DQ070039 DQ070040 DQ070041 DQ070051 DQ070052 DQ070067 DQ070066 DQ070054 DQ070056 DQ070058 DQ070057 DQ070055 DQ070065 DQ070059 DQ070060 DQ070061 DQ070062 DQ070063 DQ070064 – – – – – – – – – – – DQ070068 – – – – – – – –

a M. indicates the sexual stage, Moelleriella; A. indicates species known only from their Aschersonia asexual stage (all known Moelleriella spp. have an Aschersonia asexual state). b ARS Collections of Entomopathogenic Fungi, USDA-ARS Plant Protection Research Unit, US Plant, Soil, and Nutrition Laboratory, Tower Road, Ithaca, New York 14853, USA. c Cornell University Plant Pathology Herbarium, Department of Plant Pathology and Plant-Microbe Biology, Cornell University, Ithaca, New York 14853, USA. d BIOTEC Culture Collection, Bangkok, Thailand. e Centraalbureau voor Schimmelcultures, Utrecht, The Netherlands.

1998). In order to efficiently find the optimal tree, we used parsimony ratchet searching strategy through PAUPRat (Sikes and Lewis, 2001). Fifteen independent runs each with 200 iterations were conducted. Gaps were treated as missing data. Bootstrapping analysis was based on 1000 replicates of a full heuristic search with TBR branch-swapping, each with 10 replicates of a random addition sequence for the combined dataset, or 10,000 ‘‘Fast” stepwise-addition sequences for individual gene analyses. Gene se-

quences were analyzed separately and using a combined, total evidence approach. Partitioned Bremer support was calculated by TreeRot V3 (Sorenson and Franzosa, 2007) to re-evaluate the congruence of the gene partitions. Bayesian analyses were performed using MrBayes 3.0B5 (Huelsenbeck and Ronquist, 2001) to estimate the phylogeny with combined datasets of RPB2 and EF1-a for 56 operational taxonomic units (OTUs); RPB2, EF1-a and b-tubulin for 34 OTUs (the intron

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Table 2 Haplotypes of M. libera and M. raciborskii for different genes. Gene

Haplotype a

10 11 12 13 14 15 16 17 18 19 20 21

FL16, FL49, FL44, FL45, FL48 PC413_1 PC434 PC439 JB133 CR20, PC321 CR08 CR19 ML175_1, ML175_2, ML175_3, ML175_4, PC553 PC578 MCA2465 ARSEF 2154 ARSEF 4209 BCC1454 BCC2163 BCC2175 BCC2230 PC533 CBS34984, CBS91779 CHN1, CHN3, CHN4, BCC2227 AFR114, AFR28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

FL16 FL49, CR08 CR19 FL44, FL45, FL48, PC413_1 PC434, PC439 JB133 CR20 PC321 ML175_1, ML175_4 ML175_2 ML175_3 PC553 PC578 MCA2465 ARSEF 2154 ARSEF 4209 BCC1454 BCC2163 BCC2175 BCC2230 PC533 CBS43984 CBS91779 CHN1, CHN3 CHN4 BCC2227 AFR114, AFR28

b-Tubulin

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Fl49, FL44, FL48, PC413_1 PC434, PC439 JB133 CR20, PC321 CR08 CR19 PC553 PC578 ML175_1, ML175_2, ML175_3 ML1275_4 MCA2465 ARSEF 2154 ARSEF 4209 BCC1454 BCC2163 BCC2175 BCC2230 BCC2227 CBS34984 CBS91779, CHN3, CHN4 CHN1 AFR114 AFR28

Non-recombining region of b-tubulin + EF1-ab

A

ARSEF 2154

B C

AFR114, AFR28 CR20 (continued on next page)

RPB2

EF1-a

1 2 3 4 5 6 7 8 9

Isolate

Table 2 (continued) Gene

Haplotype

Isolate

D E F G H I J K L M N O P Q R S T U

PC321 ML175_1, ML175_2, ML175_3, ML175_4 PC578 BC2227 ARSEF 4209 BCC2175 BCC2230 JB133 FL49, CR08, CR19 PC434, PC439 FL44, FL48, PC413_1 PC553 MCA2465 BCC2163 BCC1454 CHN1, CHN3 CHN4 CBS34984

a Haplotypes of RPB2, EF1-a and b-tubulin were summarized by TCS (Clement et al., 2000) and used for estimating haplotype networks through statistical parsimony. When multiple isolates have the same haplotype, the first isolate number was used to represent the haplotype in haplotype networks (Fig. 3). b Haplotypes of non-recombining b-tubulin and EF1-a (excluding 7 incompatible sites) were derived by SNAP Map (Aylor and Carbone, 2003) and SITE version 1.1 (Hey and Wakeley, 1997) and used for coalescent analysis (Fig 5).

in b-tubulin could not be unambiguously aligned in our broader sample of fourteen species because of its fast-evolving nature). Modeltest 3.8 (Posada and Crandall, 1998) was used to choose appropriate models for each data partitions. In MrBayes, the prior distributions for datasets and partitions were set as follow: for RPB2 partition in the two gene dataset (RPB2 and EF1-a), stationary state frequencies (Statefreqpr): fixed (0.2314, 0.2934, 0.2538, 0.2214), substitution rates (Revmatpr): fixed (1.0000, 4.9215, 1.0000, 1.0000, 8.2926, 1.0000), proportion of invariable sites (Pinvarpr): fixed (0. 5501), shape parameter for gamma distribution of rate variation (Shapepr): exponential (1.3488); for EF1-a in the two gene dataset, Statefreqpr: fixed (0.2031, 0.3384, 0.2443, 0.2142), Revmatpr: fixed (0.5115, 1.4891, 0.9036, 0.3825, 5.2466, 1.0000), Pinvarpr: fixed (0.4133), Shapepr: exponential (0.6890). In the analyses of combined dataset of three genes, RPB2 partition: Statefreqpr: fixed (0.2555, 0.2842, 0.2531, 0.2072), Revmatpr: fixed (0.6478, 7.8575, 0.9601, 3.0507, 19.6960, 1.0000), Pinvarpr: fixed (0.5669), Shapepr: exponential (0.7830); EF1-a partition: Statefreqpr: fixed (0.2202, 0.3085, 0.2495, 0.2218), Revmatpr: fixed (0.4236, 0.9618, 1.4357, 0.2631, 7.6132, 1.0000), Pinvarpr: fixed (0), Shapepr: exponential (0.2767); b-tubulin partition: Statefreqpr: fixed (0.2025, 0.2903, 0.2525, 0.2548), Revmatpr: fixed (1.0000, 3.5558, 1.0000, 1.0000, 6.3317, 1.0000), Pinvarpr: fixed (0), Shapepr: exponential (0.5710) Four incrementally heated Markov chains were run, and samples were taken every 100 generations for 5000,000 generations. Average standard deviations of split frequencies were checked before terminating the program. Likelihood values were examined and samples before the likelihood value reached the stationary phase were discarded (burn-in = 25%); the remaining samples were used to estimate the posterior probabilities. Maximum likelihood analyses were performed using GARLI v0.96 (Zwickl, 2006). Model specific settings: for combined dataset of RPB2 and EF1-a: relative rate matrix parameter (r) 0.5644 2.3783 0.8922 0.5046 6.0175; equilibrium state frequency (e) 0.2218 0.3128 0.2516 0.2138; shape parameter (a) 0.8158; proportion of invariable sites (p) 0.4824. For combined dataset of RPB2, EF1-a and b-tubulin: r 0.3619 2.0208 0.8009 0.6134 5.3201 e 0.2269 0.2942 0.2488 0.2301 a 0.6378 p 0.5080.

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For all analyses, trees including 14 Moelleriella species (56 OTUs) were outgroup-rooted with Epichloë elymi Schardl & Leuchtman (RPB2, GenBank No. DQ069966; EF1-a, DQ070018), and Cordyceps militaris Link (RPB2, DQ069967; EF1-a, DQ070019). Analyses that included only M. libera and M. raciborskii (34 OTUs) were outgroup-rooted with a closely related species, M. zhongdongii Liu and Hodge. (Sequence data were obtained for this study; see Section 3.) 2.6. Coalescent analysis We also used a coalescent-based approach to infer migration events from gene genealogies (Carbone et al., 2004; Griffiths and Tavare, 1995; Hudson et al., 1992; Nielsen and Wakeley, 2001; Rosenberg and Nordborg, 2002; Templeton, 1998). The coalescent-based program GENETREE 9.0 (Griffiths; http:// www.maths. monash.edu.au/~mbahlo/mpg/gtree.html) recon-

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structs the ancestral history of haplotypes by assuming an infinitely-many-sites model in the absence of recombination and selection. The migration matrix from MIGRATE was used as starting backward migration matrix for coalescent analysis using GENETREE version 9.0 (Griffiths and Tavare, 1994; Bahlo and Griffiths, 2000) as implemented in SNAP Workbench (Carbone et al., 2004; Price and Carbone, 2005) to reconstruct the ancestral history of haplotypes. Historical inferences were made based on the coalescentbased genealogies with highest root probability. 3. Results 3.1. Amplification and alignment Fragments of 950, 850 and 740 bp were amplified from RPB2, EF1-a and b-tubulin, respectively. RPB2 and EF1-a were aligned

Fig. 1. Haplotype networks produced by TCS (Clement et al., 2000) based on (A) RPB2, (B) EF1-a, (C) b-tubulin. Parsimony probability was set at 95%. Haplotypes with dark background are from the Old World; those with light backgrounds are from the New World. When multiple isolates have the same haplotype, the first isolate number was used to represent the haplotype (see Table 2).

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Fig. 1 (continued)

for 14 species (56 isolates) resulting in 1598 characters (752 for RPB2, 846 for EF1-a). Because of the fast-evolving nature of the b-tubulin intron, the nucleotide sequences of the b-tubulin gene could only be aligned without ambiguity for M. libera and M. raciborskii and their close relative M. zhongdongii (36 isolates). Therefore phylogenetic analyses with this gene include only the latter three species. The alignment of b-tubulin sequences resulted in 732 characters. 3.2. Network estimation by TCS TCS analysis collapsed sequence data from 35 isolates to 21 haplotypes for RPB2, 26 for EF1-a, and 23 for b-tubulin (Table 2). For RPB2, the analyses resulted in two large networks corresponding to the Old World and the New World, one small network comprising two New World haplotypes and a single unconnected New World haplotype (Fig. 1A). EF1-a analysis yielded one large network, in which Old World haplotypes grouped together and were distinctly separated from New World haplotypes, and two unconnected haplotypes, one each from the Old and New World; this network also shows a lineage with two distinct New World haplotypes (CR20 and PC321), each as distinct from the rest of the New World haplotypes as the Old World haplotypes (Fig. 1B). The analysis of b-tubulin reveals two large networks corresponding to the Old World and the New World, and three unconnected haplotypes, two of them from the New World, one from the Old World (Fig. 1C). New World and Old World haplotypes always formed distinct lineages. According to Templeton’s (2004) inference key, the lack of intermediate haplotypes existing between these two geographic regions is consistent with allopatric fragmentation.

3.3. Migration estimates 3.3.1. Incompatibility of segregating sites Among M. libera and M. raciborskii isolates (Table 1) there are 60 segregating sites in RPB2, 63 in EF1-a, and 99 in b-tubulin. Using SNAP Clade and Matrix (Markwordt et al., 2004), we examined the segregating sites in order to select a region lacking incompatibility for coalescent analysis. We found many incompatible sites scattered through the whole RPB2 region, which violates the assumption of non-recombining sequences for coalescent-based analysis (Carbone et al., 2004), therefore we did not use this gene in coalescent-based analyses. In b-tubulin, the region from nucleotide (nt) 27 to nt 204 lacked incompatibility (Fig. 2A) and was considered a non-recombining block. In EF1-a, although most segregating sites were compatible, several sites (i.e. 19, 28, 50 and 57) were strongly incompatible with other sites (Fig. 2B). Exclusion of seven incompatible sites resulted in a compatible matrix. The partial b-tubulin region (28–204 nt) and EF1-a, excluding seven incompatible segregating sites, were subjected to coalescent analysis. 3.3.2. Tests for neutrality For b-tubulin in the New World population, Fu and Li’s D* and F* deviate significantly from 0 at the 5% significance level (Table 3), indicating that background selection might be operating. In contrast, we could not reject a hypothesis of neutrality for b-tubulin in the Old World population and for EF1-a in both populations. 3.3.3. Migration estimates by IM, MDIV and MIGRATE The non-recombining segment of b-tubulin included only a limited amount of variation (176 nt in length; 32 segregating sites), so its power to reconstruct ancestral history is low. We

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therefore combined the b-tubulin and EF1-a gene regions (resulting in 82 segregating sites). The two genes are generally compatible except for four segregating sites, hence we excluded the four sites in the analysis as we did for EF1-a. The migration matrix estimated by MIGRATE (Beerli and Felsenstein, 1999,

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2001) suggested that there are low levels of migration from the New World to the Old World (M = 0.436, Table 4), and no migration in the opposite direction. In contrast, the MDIV analysis found no evidence for migration; the shape of the distribution of posterior probabilities from MDIV suggests the null

Fig. 2. Compatibility of segregating sites of b-tubulin (A) and EF1-a (B). When two segregating sites infer congruent relationships among OTUs, they are compatible and marked as ‘‘
”. When two segregating sites infer incongruent relationships among OTUs, they are incompatible and marked as ‘‘x”. (A) b-Tubulin: the block shows a nonrecombining region. (B) EF1-a: arrows in the left column show four segregating sites severely incongruent with other sites. Exclusion of these four segregating sites increased the overall compatibility among segregating sites (in the right column).

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Fig. 2 (continued)

hypothesis M = 0 cannot be rejected (Fig. 3). The shapes of the estimated densities of marginal log likelihoods from IM analyses fit the model of low gene flow and short divergence time (Fig. 4). The result is consistent with a hypothesis of recent divergence with little or no migration (Nielsen and Wakeley, 2001). 3.4. Inference of direction of dispersal 3.4.1. Parsimony analyses Separate parsimony analyses of RPB2, EF1-a and a b-tubulin intron result in generally congruent tree topologies, i.e. there are no conflicts among the tree topologies in terms of the nodes with strong support (bootstrap >70%) (Mason-Gamer and Kellogg, 1996). A combined analysis of RPB2 and EF1-a with 56 isolates results in a monophyletic clade of Old World isolates (100%) and a paraphyletic group of New World isolates (Fig. 5A). However, combining all three genes results in two monophyletic clades, in which the Old World clade has high bootstrap support (98%), while the New World clade has low support (68%) (Fig. 5B). Partitioned Bremer supports suggest

that support for a monophyletic New World clade comes only from the b-tubulin dataset, not the other two genes. 3.4.2. Bayesian and maximum likelihood analyses In Bayesian analyses with separate model setting for each partition, both two-gene analysis (RPB2 and EF1-a) and three-gene analysis (RPB2, EF1-a, and b-tubulin intron) resulted in a monophyletic group of the Old World isolates with high posterior probability (100% and 98%, respectively), and a paraphyletic group of the New World isolates. Maximum likelihood analyses by GARLI recovered the patterns from parsimony analysis, i.e. a strong supported Old World monophyly (100%) and a New World paraphyly from the two-gene analyses; two monophylies from the three-gene analyses (94% support for the Old World clade, <50% for the New World clade). In summary, in all analyses, the Old World isolates always form a strong supported monophyletic clade; while the New World isolates sometime form a monophyly sometime a paraphyly depending the analyzing algorithm and gene regions used.

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M. Liu et al. / Molecular Phylogenetics and Evolution 51 (2009) 413–426 Table 3 Tests of neutrality on selected gene regions. Gene region

Population

Neutrality test Tajima’s D

a

Fu’s Fs

Fu and Li’s D*

Fu and Li’s F*

b-Tubulin nt 4–204

Old New

0.582 ( 1.46) 1.520* ( 1.41)

0.246 ( 3.96) 1.504 ( 3.86)

1.324 ( 1.76) 1.956* ( 1.82)

1.173 ( 1.75) 1.940* ( 1.78)

EF1-ab

Old New

1.011 ( 1.41) 1.289 ( 1.42)

3.480 ( 4.18) 2.363 ( 5.17)

1.337 ( 1.71) 1.593 ( 1.88)

1.301 ( 1.69) 1.605 ( 1.85)

a

‘‘Old” indicates the Old World populations; ‘‘New” the New World population. Seven segregating sites were deleted to avoid incompatibility; the deletion had no effect on the result of neutrality test. Indicates the null hypothesis of neutrality is rejected at the 5% level of significance; numbers in parentheses are critical values for each test.

b *

Table 4 Migration estimates based on combined gene regions. Gene region

b-Tubulin nt 4-204 and EF1-

a a

Population

1: Old 2: New

Ln(L)

0.017 0.017

h [4Ne l]

M (4 Nm)

0.017 0.011

_ 2.45e

1, X

a

2, X 11

0.4367 _

X = receiving population.

Fig. 4. The posterior distribution of M1 (from the Old World to the New World) and M2 (from the New World to the Old World) based non-recombining block of EF1-a and b-tubulin by using IM. HKY model was selected by the program, m1 and m2 (maximum scalar of migration) were set as 1 based on the results from preanalyses. Markov chain was set as 10,000,000, and burn-in 100,000. Five independent runs were performed and resulted in almost identical distributions.

Fig. 3. The migration and divergence time posterior probability distributions between the Old World and the New World populations based on non-recombining block of EF1-a and b-tubulin by MDIV. The simulations were carried out by assuming a finite sites model. Length of the Markov chain was set 20,000,000 steps, burn-in 2000,000. Five independent runs with same parameters were performed and resulted in similar distributions. The graphs were plotted in Excel.

3.4.3. Coalescent analysis Coalescent-based genealogies based on the combined b-tubulin and EF1-a data revealed that lineages of the Old World population coalesce more recently than those of the New World population (Fig. 6). This result is consistent with the evolutionary pattern inferred from some of the gene trees based on phylogenetic analyses (Fig. 5A), in which Old World haplotypes form a strongly supported clade nested in the New World haplotypes. Thus the direction of the migration was more likely from the New World to the Old.

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Fig. 5. Phylogenetic relationships between the Old World isolates and the New World isolates by parsimony analysis. (A) One of 206 most parsimonious trees (MPTs) based on combined RPB2 and EF1-a dataset, L = 2363, CI = 0.400, RI = 0.697, 473 parsimony-informative characters. Numbers on the branches are bootstrapping supports from MP and ML analyses and posterior probabilities from Bayesian analysis, respectively. (B) One of 208 MPTs based on combined RPB2, EF1-a and b-tubulin for subset of OTUs, L = 868, CI = 0.818, RI = 0.871, 256 parsimony-informative characters. The branches in thicker lines show the origin and the divergence of the two species; numbers in bold are the partitioned Bremer supports for each gene RPB2/EF1-a/b-tubulin. Un-bold numbers are the bootstrapping supports from MP and ML analyses and posterior probabilities from Bayesian analysis, respectively.

4. Discussion Our data are consistent with the hypothesis that the Old World species, Moelleriella raciborskii, arose following a dispersal event from an older, New World population of M. libera. Since that time, there appears to have been little migration between the two populations. However, our results leave many questions unanswered. 4.1. Criteria for species recognition As opposed to topology-based species recognition, in which species are diagnosed as monophyletic or reciprocally monophyletic groups with strong support (Dettman et al., 2003), non-topology-based species recognition delimits species based on fixed character differences (Davis and Nixon, 1992; Doyle, 1995), allele frequency differences, genetic distances (de Queiroz and Good, 1997; Highton, 1989, 1998) or lack of evidence of gene flow (Porter, 1990). Incomplete lineage sorting or incomplete phylogenetic reconstruction can sometimes suggest species-level paraphyly and polyphyly (Funk and Omland, 2003; Harrison, 1998; Wiens, 1999). In the present study, population genetic analyses suggest

limited or no recent gene flow between genetically differentiated New World and the Old World populations. Gene genealogies derived from parsimony, Bayesian and maximum likelihood analyses (Fig. 5), and the network from TCS (Fig. 1) analyses show that M. raciborskii (Old World) and M. libera (New World) isolates have not intermingled since their divergence, presenting as either monophyletic or paraphyletic groups. Based on this evidence, the minute morphological differences confirmed by Liu et al. (2006) as well as non-topology-based species concepts, we consider the New and Old World isolates should be viewed as two separate species: Moelleriella libera (asexual state, Aschersonia aleyrodis) in the New World and M. raciborskii (asexual state, Aschersonia placenta) in the Old World. 4.2. Historical biogeography Two major events have been widely considered relevant to observed disjunct distributions across the Pacific Ocean. One is the last relevant Gondwanan fragmentation, which took place about 100 mya (Rosen, 1978; Taylor, 1990). Another is the boreotropical hypothesis, dated to about 50 mya, when warm

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Fig. 5 (continued)

global temperatures facilitated the spread of some tropical species across northern landmasses (Lavin and Luckow, 1993; Tiffney, 1985; Wolfe, 1975). The relevance of these events to speciation in Moelleriella might be predicted based on the time since divergence of M. libera and M. raciborskii. However, the paucity of fossils and our ignorance of phylogenetic relationships in many lineages have hindered calibration of fungal molecular clocks, especially in ascomycetes. Using the molecular clock of the nuclear large subunit ribosomal RNA (LSU) calibrated by Berbee and Taylor (1993), Hibbett (2001) estimated the divergence time of shiitake mushrooms (Basidiomycetes) from New Zealand and Australia (node D) as 8 ± 6 mya. We compared the relevant sequences from his study and observed 10 nucleotide substitutions between the isolates having diverged 8 ± 6 mya supposedly. However, only one substitution in the same fragments of LSU was observed between two Moelleriella species and there is no variation in DNA sequences for the mitochondrial gene encoding ribosomal small subunit RNA (mtSSU) (Liu and Hodge, unpublished). On the other hand, our population genetic tests indicate that the two species diverged recently. The tree topology (Old world clade nesting within the New World clade) implies that the Old World species may be a recently diverged daughter species, or at least that it is in the process of speciation (Harrison, 1998). Given the smaller number of substitutions observed between the two species of Moelleriella, along with the evidence of recent divergence from population genetic analyses and tree

topologies, speciation seems more likely linked to transoceanic dispersal than vicariance. The topology of the rooted tree, with M. raciborskii (Old World) clades being more derived, while the New World clades (Fig. 5A) are more basal, suggests, following the progression rule (Humphries and Parenti, 1999), that the direction of dispersal was likely from the New World to the Old World. It should be noted that fast-evolving b-tubulin intron sequences weakly supported the monophyly of the New World isolates (Fig. 5B), while two more slowly-evolving genes did not. Two isolates from the New World (CR20, PC321) formed a small clade of uncertain relationship. Morphologically these isolates are not distinguishable from other isolates. They may represent a distinct, under-sampled clade and merit more study. Overall the New World clades are basal to those from the Old World. The New World population also exhibits greater genetic variation, a characteristic common to taxa in their center of origin. This hypothesis is also supported by coalescent-based genealogy (Fig. 6), in which Old World haplotypes coalesced more recently than New World haplotypes (i.e. the most recent common ancestor in the Old World is younger than that in the New World). 4.3. Dispersal mechanisms Moelleriella libera and M. raciborskii produce largely rain-dispersed asexual spores, and only occasionally produce ephemeral,

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Fig. 6. Coalescent-based gene genealogy of b-tubulin and EF1-a generated by GENETREE 9.0 (Griffiths and Tavare, 1994). The genealogy shown has the highest root probability (likelihood = 1.0631e 40, SD = 6.3809e 38). The time scales on the right are in coalescent units of effective population size, T = 4N/i(i 1), where, N = effective population size; i = generation. The black dots represent mutations inferred in the lineages; mutation ages were estimated through maximum likelihood. N and P indicate mutations likely to have risen in the New World population and the Old World population, respectively. Three independent runs used different starting random seeds resulted in similar estimates; 1000,000 simulations for each runs, a Watterson’s estimation of h = 11.45. Coalescence is from the bottom (present) to the top (past).

unpigmented, airborne ascospores that seem ill-suited to survive long atmospheric exposure. One possible dispersal vehicle is the whitefly host. Mainly larval pathogens, Moelleriella sometimes infect the adults of whiteflies (Meekes et al., 2002). However in nearly all the cases, infected insects are typically almost totally di-

gested and overgrown by the time the fungal fruiting bodies are mature. For this reason, the host range of Moelleriella species has not been determined. Among multiple possible whitefly host species is Dialeurodes citri, an important aleyrodid pest of Citrus. Dialeurodes citri is known from Asia, Europe, the Americas,

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Mediterranean and Ethiopian regions (Argov et al., 1999; Byrne and Bellows, 1991). Whiteflies were once considered poor fliers, and most attributed their global distribution to human movements. A more recent study observed that whitefly species displays a high migratory and dispersal potential (Byrne, 1999) and can disperse widely by a combination of active flight and passive movement in wind currents or other vehicles, such as infested plant material. Following dispersal to the Old World by their whitefly host, other mechanisms might have contributed to speciation. Host switches and niche specialization have been considered important mechanisms for speciation in fungal pathogens and symbionts; they appear correlated with speciation in the close Moelleriella relative, Cordyceps (Nikoh and Fukatsu, 2000), among ectomycorrhizal fungi in the genus Leccinum (den Bakker et al., 2004) and among plant pathogens including Ceratocystis spp. (Harrington and Wingfield, 1998) and Magnaporthe oryzae (Couch et al., 2005). Studies of the whitefly Bemisia tabaci populations have revealed high genetic variability (de Barro et al., 2000, Rua et al., 2006), subdivided among at least four phylogenetic lineages at the continental scale, and therefore B. tabaci has been considered as a complex of sibling species (reviewed by Perring 2001). We speculate that D. citri might also possess high genetic variability and multiple sibling species among the populations in different continents since D. citri has similar biology to B. tabaci (Byrne, 1999). There is a possibility that adaptation to the insect host has played an important role in the speciation of these fungi. To test this hypothesis, much more information is needed about genetic variation and population subdivision in D. citri. Acknowledgments We thank BCC, CBS and ARSEF for providing fungal isolates, the US Forest Service for permission to collect fungi in the Caribbean National Forest (El Yunqué), and the National Biodiversity Institute (InBio) for facilitating collecting by M.L. in Costa Rica. Our thanks go to all of the people who have provided their specimens and cultures: J.F. Bischoff, G.J. Samuels, H.C. Evans, M.C. Aime, and C.L. Schardl; and also to those who have facilitated our collecting: Jean Lodge, Sharon Cantrell, Sandra Maldonado, Miriam Salgado, and Andrián Muñiz in Puerto Rico; Juventino García Alvarado in Mexico; Phil Arneson in Honduras; Emilia García Diego and De la Quintana in Bolivia; Luis Gomez in Costa Rica; Clayton McCoy, Philip Stansly, Lee Mitchell, Stephan Brown, Ronald Cave, Pete Timmer, and James Kimbrough in Florida; Zengzhi Li and Bo Huang in PR China. Stephen A. Rehner (USDA-ARS, Beltsville) made helpful suggestions on primers. Ignazio Carbone (North Carolina State University) provided help in using SNAP Workbench. We are indebted to Jeff J. Doyle (Cornell University) for providing suggestions and criticisms. This project was supported by the National Science Foundation (0212719), and by the National Research Initiative of the USDA Cooperative State Research, Education and Extension Service (2002-35316-12263). References Argov, Y., Rassler, Y., Voet, H., Rosen, D., 1999. The biology and phenology of the citrus whitefly, Dialeurodes citri, on citrus in the Coastal Plain of Israel. Entomol. Exp. Appl. 93, 21–27. Aylor, D., Carbone, I., 2003. SNAP Combine and Map. Department of Plant Pathology, North Carolina State University, Raleigh, NC. Bahlo, M., Griffiths, R.C., 2000. Inference from gene trees in a subdivided population. Theor. Popul. Biol. 57, 79–95. Beerli, P., Felsenstein, J., 1999. Maximum-likelihood estimation of migration rates and effective population numbers in two populations using a coalescent approach. Genetics 152, 763–773. Beerli, P., Felsenstein, J., 2001. Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach. Proc. Natl. Acad. Sci. USA 98, 4563–4568.

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