Population Structure of the Melon Fly, Bactrocera Cucurbitae, in Reunion Island

Population structure of the melon fly, Bactrocera cucurbitae, in Reunion Island

C. Jacquard, M. Virgilio, P. David, S. Quilici, M. De Meyer & H. Delatte

Biological Invasions

ISSN 1387-3547 Volume 15 Number 4

Biol Invasions (2013) 15:759-773 DOI 10.1007/s10530-012-0324-8

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1 23 Author's personal copy

Biol Invasions (2013) 15:759–773 DOI 10.1007/s10530-012-0324-8

ORIGINAL PAPER

Population structure of the melon ﬂy, Bactrocera cucurbitae, in Reunion Island

C. Jacquard • M. Virgilio • P. David • S. Quilici • M. De Meyer • H. Delatte

Received: 11 July 2011 / Accepted: 21 August 2012 / Published online: 4 September 2012 Ó Springer Science+Business Media B.V. 2012

Abstract The melon fly, Bactrocera cucurbitae with populations from the African continent and, to a (Coquillett) (Diptera: Tephritidae) is an agricultural lesser extent, from Asia. The B. cucurbitae clusters pest of major significance worldwide that primarily show distinct distributions across eastern and western attacks cucurbit crops. In Reunion Island, it represents locations in Reunion Island (but not at different the main tephritid pest on cucurbits. In this paper, we altitudes or between wild and cultivated host plants or provide a genetic characterization of populations of B. between sampling periods), and their abundance is cucurbitae from Reunion Island and investigate their also correlated with the average amount of rainfall. geographical origin using ten microsatellite loci at two Microsatellite and sequence analyses suggest Africa as mitochondrial gene fragments. Microsatellites reveal the most probable source area for populations the occurrence of three different genetic clusters of of B. cucurbitae in Reunion Island. B. cucurbitae in Reunion Island, all clearly distinguishable from their African and Asian relatives. Keywords Bactrocera cucurbitae Á Microsatellites Á These three clusters are sympatric and show no signs Mitochondrial data Á Population structure Á Migration Á of recent bottlenecks. Levels of gene flow among Tephritidae clusters are relatively high, yet gene flow also occurs

Introduction Electronic supplementary material The online version of this article (doi:10.1007/s10530-012-0324-8) contains supplementary material, which is available to authorized users. The family Tephritidae includes more than 4,000 species worldwide, some of which, known as ‘fruit & C. Jacquard ( ) Á S. Quilici Á H. Delatte flies’, are of major economic importance because of UMR C53 PVBMT CIRAD-Universite´ de La Reúnion, CIRAD Poˆle de Protection des Plantes, 7 Chemin de l’Irat, the damage they cause in vegetable and fruit crops, 97410, Saint-Pierre, Reúnion, France particularly in tropical and subtropical areas (Fletcher e-mail: [email protected] 1987; White and Elson-Harris 1992). Due to increases in movements of people and international trade, cases M. Virgilio Á M. De Meyer Royal Museum for Central Africa, Leuvensesteenweg 13, of invasions by members of this family are increasing, 3080 Tervuren, Belgium despite stringent quarantine measures (White et al. 2000; Duyck et al. 2004). P. David The melon fruit fly, Bactrocera cucurbitae (Co- UMR 5175, CNRS Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), 1919 Route de Mende, quillett), is a pest of major significance on fleshy 34293 Montpellier Cedex, France fruits and vegetables, particularly cucurbits, and may 123 Author's personal copy

760 C. Jacquard et al. cause damage to more than 125 different species of seasonal fluctuations of populations (Vayssie`res plants (White and Elson-Harris 1992; Dhillon et al. 1999). However, in this particular insular context, it 2005). It belongs to the subgenus Zeugodacus is still unknown as to whether there has been a Hendel, a group that has a strong preference for specialization to the different available habitats. Cucurbitaceae (White and Elson-Harris 1992; White In a previous study (Virgilio et al. 2010), we 2006). In many countries, this fly is responsible for provided a large-scale description of the population high infestation rates in cucurbit crops and induces structure of B. cucurbitae and showed the existence of significant losses, depending on the cucurbit species five main population groups worldwide. They corre- and the season (White and Elson-Harris 1992; spond to populations that colonize the African conti- Vayssie`res 1999; Dhillon et al. 2005). With the nent, Reunion Island, Central Asia, East Asia and development of the international fruit trade and the Hawaii, respectively. Indeed, this first study showed correlative extension of the geographical range of that samples from Reunion Island are genetically B. cucurbitae, more attention is currently being paid different from all the other groups and suggested that to this species (Wu et al. 2009). they share a Central Asian origin with African Native to Asia (Bezzi 1913), this fruit fly has a large populations. In this work, we further investigate the geographical distribution area worldwide, but our population structure of B. cucurbitae in Reunion knowledge of its colonization history remains limited Island by implementing a multifactorial experimental (Virgilio et al. 2010). For example, it has been a design based on samples reared from different wild successful invader in Southeast Asia, in Australia and and cultivated hosts and collected at a range of on some islands of Oceania, in Africa and in South altitudes and locations. The objectives of this study America (Dhillon et al. 2005). In the Indian Ocean are: (1) to describe the fine-scale population structure Islands, the melon fly first colonized the Mascarene of B. cucurbitae in Reunion Island; (2) to verify Islands (Reunion, Mauritius, Rodrigues). Its presence possible relationships between genetic patterns and was first recorded in Mauritius in 1942 (Orian and spatial and temporal distribution of B. cucurbitae in Moutia 1960), in Reunion Island in 1972 (Etienne Reunion Island; (3) to investigate the colonization 1972) and, more recently, in 1999 in the Seychelles route(s) of B. cucurbitae in Reunion Island by (White et al. 2000). considering Asia and Africa as possible population Although the host range of the melon fly always sources; and (4) to compare the large-scale genetic includes many cucurbit species as preferred hosts, structuring resulting from different genetic markers some differences in its dietary preferences have been (i.e., microsatellites and DNA sequences of mitochon- described among populations from different geo- drial gene fragments). graphic regions (Vayssie`res et al. 2007; Ryckewaert et al. 2010). This species is typically oligophagous in the Mascarene Islands, with a host range centered on Materials and methods Cucurbitaceae (Orian and Moutia 1960; Vayssie`res 1999), whereas it appears to be more polyphagous in Datasets and sampling design Africa and could infest mango or orange, for example (Vayssie`res et al. 2007). In Reunion Island, cucurbit We considered four different datasets that included: crops are affected by three species of Tephritidae: 2,258 multilocus microsatellite genotypes of B. cucurbitae, Dacus ciliatus (Loew) and Dacus B. cucurbitae from Reunion Island (dataset 1); 2,795 demmerezi (Bezzi) (Vayssie`res 1999). The distribu- microsatellite genotypes of specimens from Reunion tion areas of these species are somewhat overlapping, Island, the African continent, Asia, Hawaii, the Sey- which induces an interspecific competition for a chelles and Mauritius (2,258, 226, 250, 25, 23 and 13 common range of host plants (Vayssie`res 1999; genotypes, respectively) (dataset 2); 1,292 microsat- Vayssie`res et al. 2008). B. cucurbitae currently infests ellite genotypes of B. cucurbitae from Reunion Island, 12 genera of plants on the island that belong to three the African continent, Asia, Hawaii, Seychelles and plant families (Cucurbitaceae, Passifloraceae and Mauritius (755, 226, 250, 25, 23 and 13 genotypes, Solanaceae). Its distribution extends from sea level respectively) (dataset 3) and 100 concatenated mito- to 1100 m during summer throughout the island, with chondrial DNA sequences of specimens from Reunion 123 Author's personal copy

Population structure of Bactrocera cucurbitae in Reunion Island 761

Island, the African continent, Asia and Hawaii (7, 44, genetic structuring worldwide. Specimens of dataset 2 45 and 4 DNA sequences, respectively) (dataset 4). included individuals of Reunion Island from dataset 1 Dataset 1 was used for the ﬁne-scale analysis of the and those from populations considered in Virgilio et al. genetic diversity, genetic structuring and bottlenecks in (2010). Dataset 3 was used for the analysis of gene ﬂow Reunion Island. Specimens of dataset 1 were collected among Reunion Island, Asia and Africa. This dataset at 11 locations in Reunion Island, each including three was obtained by randomly reducing numbers of indi- randomly chosen sites located at altitudinal ranges of viduals from Reunion Island in dataset 2 to have a more 0–400 m, 400–600 m and 600–1200 m. At each site, 15 well-balanced model. A large-scale phylogeographic infested sample fruits were collected from cultivated analysis was implemented using dataset 4. It included hosts and 15 from wild cucurbit hosts (Fig. 1,Table1). specimens from Reunion Island as well as from possible Sampling was repeated twice, from January to April and source areas sampled across the worldwide distribution from June to September 2009. Infested cucurbits were of B. cucurbitae and including: Benin (n = 3), Burkina reared following the procedure of Ekesi et al. (2007)and Faso (n = 2), Congo (n = 6), Guinea (n = 5), Ivory emerged B. cucurbitae adults were counted, sex-sorted Coast (n = 3), Kenya (n = 7), Senegal (n = 1), Sudan and individually stored at -20 °C in 96 % ethanol. (n = 9), Tanzania (n = 4), Bangladesh (n = 8), India Dataset 2 was used for analysis of genetic diversity and (n = 5), Pakistan (n = 5), Cambodia (n = 7), China

Fig. 1 Map of sampling location of Bactrocera cucurbitae (a); Sampling sites (N = 11) of Bactrocera cucurbitae numbered according to Table 1 (b). Brown, yellow and red lines designate the three altitudinal classes (altitudinal class 1 (0–400 m), altitudinal class 2 (400–600 m) and altitudinal class 3 (600–1,200 m), respectively). Black dots indicate sampling done in the 11 locations on Reunion Island. Pie charts show the frequency of individuals that belong to clusters R1, R2 and R3, for each sampling site. (Color ﬁgure online)

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Table 1 Host plants (wild: W, cultivated: C) and number of Table 1 continued specimens of B. cucurbitae sampled in La Reunion at 11 locations (numbers according to Fig. 1b.) and two sampling Location Hosts Summer Winter periods (summer 2009, winter 2009) 2009 2009 Location Hosts Summer Winter Cyclanthera pedata (W) – 40 2009 2009 Momordica charantia (W) 30 57 Sechium edule (W) – 2 1 Coccinia grandis (W) 54 – 10 Coccinia grandis (W) – 20 Cucumis sativus (C) 54 – Lagenaria sphaerica (W) – 2 Cucurbita maxima (C) 84 21 Momordica charantia (W) – 25 Cyclanthera pedata (W) – 22 11 Coccinia grandis (W) 26 – Luffa acutangula (C) 26 – Cucurbita maxima (C) 56 – Lycopersicum escultentum (C) – 1 Momordica charantia (W) 43 47 Momordica charantia (W) 48 39 Sechium edule (W) 3 5 Coccinia grandis 2 (W) – 7 (n = 6), Indonesia (n = 6), Malaysia (n = 5), the Cucumis sativus (C) 28 – Philippines (n = 3) and Hawaii (n = 4). Cucurbita maxima (C) 10 38 Momordica charantia (W) 30 49 Microsatellite genetic structuring 3 Coccinia grandis (W) 20 – Cucumis sativus (C) 41 – Individual flies of datasets 1, 2 and 3 were genotyped at Cucurbita maxima (C) – 26 ten microsatellite loci (Table 2) (BcCIRC3, BcCIRD3, Cucurbita pepo (C) 24 – BcCIRD11, BcCIRE8, BcCIRF3, BcCIRF4, BcCIRG1, Momordica charantia (W) 38 – BcCIRH7, BcCIRH9 and BcCIRH10) (Delatte et al. 4 Cucurbita maxima (C) 62 34 2010). DNA was extracted from adult specimens by Cucumis sativus (C) 8 25 slightly modifying the extraction protocols described in Momordica charantia (W) 50 84 Baruffi et al. (1995) and Delatte et al. (2010). PCR were Sechium edule (W) 1 1 performed in a total volume of 15 ll, containing Solanum mauritianum (W) – 6 115–130 ng DNA, 0.3 lM of each primer and 7.5 ll 5 Coccinia grandis (W) – 19 master mix of QiagenÓ multiplex PCR kit. Amplifica- Cucumis sativus (C) 33 9 tions were performed with an initial denaturation step Cucurbita maxima (C) 116 61 (5 min at 94 °C),followedby35cyclesof30sat Cyclanthera pedata (W) – 2 94 °C, 30 s at 54 °C and 30 s at 72 °C, with a final Lagenaria leucaritha (C) – 21 elongation step of 5 min at 72°. Primer sequences and Momordica charantia (W) 23 54 methods for DNA amplification, electrophoresis and 6 Cucurbita maxima (C) 46 38 allele scoring were performed using the methods Momordica charantia (W) 66 67 described in Anderson et al. (2010). Microsatellite 7 Cucurbita maxima (C) 59 9 alleles were separated on an automated ABI Prism 3,100 Cucurbita pepo (C) 28 – Genetic Analyzer (Applied Biosystem) and scored with Momordica charantia (W) 53 – Genemapper v4 (Applied Biosystem). Individuals that 8 Citrillus lanatus (C) 19 – showed two amplification failures for a locus were Coccinia grandis (W) 17 21 considered to be non-amplifiable for that locus. Cucumis sativus (C) 30 – The genetic diversity of populations from Reunion Momordica charantia (W) 12 26 Island was quantified by calculating the mean number 9 Coccinia grandis (W) 24 – of alleles per locus (Na), observed heterozygosity Cucumis sativus (C) – 19 (Hobs) and Nei and Chesser (1983) unbiased expected Cucurbita maxima (C) 50 28 heterozygosity (Hnb), using GENETIX 4.05 (Belkhir Cucurbita pepo (C) 21 – et al. 1996). Deviations from the Hardy–Weinberg equilibrium were tested with a two-tailed Fisher’s

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Table 2 Microsatellite loci used in this study. Tm: locus-speciﬁc annealing temperature Mix Locus- Repeat motif Primer sequences Fluorescent Size of Allele Tm A accession label cloned range size number fragment (pb)

1 BcCIRD3- (CA)7 FCTGATGAGTCCAATAAAATGC VIC 161 150–170 55 °C6 GQ863216 RCTGCCATCATATCCTTTGTT

BcCIRF3- (AC)9 FCCGGATAGACGTAAGCACT NED 177 161–194 55 °C7 GQ863218 RAACCGTAGGTGACGTGTG

BcCIRG12- (AC)8 (TG)6 FCCATAGCAACGAATGCTG NED 280 252–284 55 °C6 GQ863219 (AGC)4 RTGCGTACAAAGGACCAAC

BcCIRH10- (CA)9 FTCAGCTCTGCACCTACTCA PET 241 214–256 55 °C9 GQ863220 RTGCTGTAATGCACGATTG

BcCIRH9- (AC)9 FCAACAACCTAACTTCAATCACA FAM 272 251–281 55 °C8 GQ863222 RACCTTCTCTTAAACCGTTAGAC

2 BcCIRH2- (CAA)5 FGACTTTCGGCAGCAAATA VIC 215 205–214 54 °C4 GQ863221 RCTGACAAAATGCAGCGTA

BcCIRE7- (TTG)5 FCTGCCACTATCCCTCTTG NED 193 179–200 54 °C7 GQ863224 RCCAACGAGAAAAGCAATAA

BcCIRE8- (CA)7 FCGACTTTGGAGTGCTTTG PET 200 179–200 56 °C7 GQ863225 RACACGAGCGCATAACAAC

BcCIRH7- (TG)8 FGTGCAGCTAGGCAGGTAG FAM 148 140–164 54 °C5 GQ863226 RGATTCGTTGCGAAGGTAG

BcCIRC3- (TG)7 FAAGCGTCAATGAGACAGC FAM 215 201–217 55 °C6 GQ863223 RCTGCTTGAGGGCAAGTAA A number of alleles (Delatte et al. 2010)

exact test in GENEPOP 4.0 (Raymond and Rousset number of population clusters was inferred separately

1995). Single and multilocus inbreeding indices (Fis) for the two datasets using the procedure of Evanno et al. were calculated according to the fixation index of Weir (2005) and calculating the ad hoc statistic DK (with K and Cockerham (1984). Null allele frequencies were ranging from 1 to 10 and ten replicate runs for each estimated with FreeNa (Chapuis and Estoup 2007) for value of K). STRUCTURE analyses were run under the each locus in each population. admixture model, location information (see Table 1) Interpopulational genetic differentiation was esti- (Hubisz et al. 2009) and an initial burn-in period of 105 mated through pairwise Fst values (Weir and Cockerham iterations followed by a run of 106 Markov chain 1984) as implemented in ARLEQUIN 3.5 (Excoffier Monte Carlo (MCMC) repetitions. Admixture propor- et al. 2005). Genetic discontinuities among groups of tions of samples and individuals were visualized using populations in Reunion Island (dataset 1) were tested DISTRUCT 1.1 (Rosenberg 2004). through hierarchical analysis of molecular variance The amount and direction of gene flow among (AMOVA) according to nine different grouping schemes populations from Asia, Africa and the three population (see results). F statistics and variance components were groups from Reunion Island (dataset 3) were estimated tested through 1,000 iterations in ARLEQUIN. using the Maximum Likelihood approach of The population structuring and coancestry of MIGRATE-N 3.1.6 (Beerli and Felsenstein 2001). B. cucurbitae was investigated through the Bayesian The scaled migration rate (M = m/l, i.e., the migra- clustering algorithm of STRUCTURE 2.3.3 (Pritchard tion rate per generation divided by the mutation rate et al. 2000). Analyses were repeated using both per generation) was used as an estimator of gene flow. datasets 1 and 2 and dataset 3 (data not shown). The We avoided estimating the number of migrants (Nm)

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764 C. Jacquard et al. since this parameter strictly depends on estimates of function. GLMMs were simplified by removing non- population sizes, which can be biased when some of significant terms hierarchically starting with high-order the assumptions of MIGRATE are violated (see terms. Model simplification was continued until the discussion). The MIGRATE analysis was performed current and previous models significantly deviated from using ten short chains with 1,000 sampled genealogies each other. The significance test was based on differ- and three long chains with 2,000 sampled genealogies. ences in deviance. We used F-tests (ratio of the change Heating was active with four chains of different in deviance to the residual deviance, each divided by the temperatures (1,000,000.00, 3.00, 1.50, and 1.00). appropriate degrees of freedom) instead of Chi-squares Preliminary runs were used to choose adequate priors to account for overdispersion. The final models con- for theta and migration values, after which three tained only explanatory variables with P values smaller independent runs were performed (1,000 burn-in than 0.05. We constructed graphs based on model pre- steps, static heating scheme with four concurrent dictions to predict the abundance of individuals of each chains). Independent runs were checked for conver- cluster according to the different factors. All models and gence by comparing the resulting posterior distribu- tests were performed using the package ‘‘lme4’’ (Bates tions and estimated values of parameters. et al. 2011) of R 2.14.0 (R Development Core Team The BOTTLENECK program, version 1.2.02 2011). (Cornuet and Luikart 1996), was used to test recent demographic reduction or expansion on the three Phylogeographic analysis of mitochondrial groups of B. cucurbitae from Reunion Island (see sequences results). Two mutation models were considered: the stepwise mutation model (SMM) that assumed that Specimens of dataset 4 were sequenced at two mutations are the result of one-step changes, and the mitochondrial DNA gene fragments (COI, ND6) two-phased model of mutation (TPM) that allows a according to the methods described in Virgilio et al. small proportion (5 %) of multi-step changes (Piry (2009). A minimum spanning network built in TCS et al. 1999; Luikart and Cornuet 1998). Deviations 1.13 (Clement et al. 2000) with the most parsimonious from expected heterozygosity were tested with the branch connections between the concatenated COI- nonparametric Wilcoxon test of BOTTLENECK ND6 haplotypes (1297 bp) was used to visualize the using 1,000 permutations. large-scale phylogeographic patterns of B. cucurbitae.

Spatial distribution of microsatellite genotypes in Reunion Island Results

Differences in the relative abundances of clusters of Population structure in Reunion Island and gene B. cucurbitae in Reunion Island (as identified by flow STRUCTURE on dataset 1) were investigated through Analysis of Deviance (McCullagh and Nelder 1989). The analysis of samples from Reunion Island showed Specimens were assigned to one of the three clusters, a mean number of alleles (Na) of 3.1 per locus, a R1, R2, R3 (see results), based on their highest significant departure from the Hardy–Weinberg equi- coancestry coefficient (Q). Differences in the spatial librium and an estimated frequency of null alleles of and temporal distribution of relative frequencies of each 0.045 (Table 3). Similar levels of genetic diversity cluster were tested by evaluating the effects of (1) were observed in Reunion Island and Africa and Asia altitude (0–400 m, 400–600 m and 600–1200 m), (2) (ranging from 3.1 to 3.6), except for the Central Asian longitude (eastern vs. western locations), sampling population that had a high mean number of alleles per period (summer 2009 vs. winter 2009), as well as the locus of 4.7. correlation with the average amount of rainfall (across The STRUCTURE analysis of dataset 1 showed a the 3 months of each sampling period; http://www. main break in the slope of likelihood distribution at K = 3 margouilla.net/). The relative frequency of each cluster (DK = 76.44; Figs. 2, 3a). The spatial distribution of was fitted as a generalized linear mixed model (GLMM) individuals with a coancestry coefficient Q [ 0.8 is fitted with a Poisson distribution of error and a log link showninFig.1. Individuals and average Q values at the 123 Author's personal copy

Population structure of Bactrocera cucurbitae in Reunion Island 765

Table 3 Summary of genetic variability at 10 microsatellite loci in populations of B. cucurbitae sampled in La Re´union (details of the three clusters R1, R2, R3 are shown), Africa and Asia Sites n Hobs Hnb Fis An Allelic richness

La Reúnion 2258 0.467 0.485 0.036* 0.045 (0.044) 3.1 R1 788 0.434 0.457 0.050* 0.045 (0.046) 5.4 R2 ?877 0.528 0.466 0.134ns 0.014 (0.030) 4.9 R3 ?593 0.424 0.430 0.016* 0.038 (0.037) 5.1 African continent 214 0.373 0.462 0193* 0.050 (0.103) 4.9 East Africa 134 0.378 0.443 0.146* 0.097 (0.097) 3.3 West Africa 80 0.363 0.457 0.208* 0.048 (0.094) 3.4 Asia 250 0.373 0.462 0.330* 0.115 (0.091) 8.2 Central Asia 103 0.389 0.541 0.282* 0.078 (0.091) 4.7 South East Asia 80 0.300 0.433 0.310* 0.103 (0.123) 3.3 Cambodia/China 67 0.367 0.468 0.218* 0.105 (0.085) 3.6 n Number of individuals, Hobs observed heterozygosity, Hnb expected unbiased heterozygosity (Nei and Chesser 1983), Fis: Weir and Cockerham’s (1984) estimate of Wright (1951) fixation index (* significant deviations from HWE after false discovery rate correction), An average frequency of null alleles (standard deviations in parentheses), Allelic richness mean number of alleles

both cultivated and wild hosts (Table 1). The STRUC- TURE analysis of dataset 2 showed a main break in the slope of likelihood distribution at K = 2(DK = 15.44), as well as a second break for K = 5(DK = 5.19). At K = 2, samples from Reunion Island, while being clearly differentiated from the Asian specimens, could not be distinguished from samples from Africa. The three clusters from Reunion Island could only be distinguished at K = 5 and were genetically differentiated from both the African cluster (included individuals from the Seychelles and Mauritius) and the Asian cluster (com- prising individuals from Hawaii) (Fig. 3b, c). Migration rates among the three clusters from Reunion Island (R1, R2 and R3) were comparable and ranged from 12.96 to 15.29 (Table 5). Lower values were observed from the African continent to Reunion Island (range: 9.50–10.25) and from Reunion Island to Africa (range: 9.05–9.95), as well as from Asia to Reunion Island (range: 6.76–7.87) and from Reunion Island to Asia (range: 4.25–4.98). There was no evidence of recent bottlenecks in Fig. 2 DK obtained in STRUCTURE with K max ranging from 2 to 10 (according to Evanno et al. 2005) for the analysis run for Reunion Island under either mutation model, and a samples of Reunion Island (dataset 1) and for the analysis of this significant deficiency in expected heterozygosity (He) samples plus those of Africa and Asia (dataset 2). Each value was detected under the SMM, suggesting a recent was obtained by averaging the posterior probabilities of ten population expansion. independent runs AMOVA quantified the partition of genetic variation among and within five different sample groups different locations are shown in Fig. 1 and Table 4, (Table 6). Groups were defined on the basis of either respectively. The three clusters from Reunion Island Bayesian analysis (STRUCTURE clusters), geo- included individuals from different locations and from graphical criteria (sampling location) or the nature 123 Author's personal copy

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Fig. 3 Structure bar plots representing assignements of geno- individuals from dataset 2: each individual is represented by a types of Bactrocera cucurbitae to each cluster. Structure vertical line that is partitioned into K = 2(b) and K = 5 analysis of individuals from Reunion Island from dataset 1: (c) colored components. Clusters are separated by vertical black each individual is represented by a vertical line that is bars partitioned into K = 3 colored components (a); analysis of

Table 4 Average coancestry coefficients (Q) obtained for STRUCTURE (note that this is expected because B. cucurbitae at 11 localities in La Reúnion these groups have been defined a posteriori to Cluster maximize genetic differences among clusters and the internal homogeneity of each cluster). In contrast, R1 R2 R3 all fixation indices calculated using sample locations 1 0.30 0.65 0.05 or host plants as grouping variables were low, 2 0.28 0.69 0.03 ranging from 0 to 0.04. There was no significant 3 0.25 0.08 0.68 genetic differentiation among host plants. However, 4 0.36 0.05 0.59 genetic differentiation among localities, although 5 0.63 0.11 0.26 low (Fct = 0.01), was significant. 6 0.27 0.72 0.01 7 0.46 0.28 0.26 Distribution of the genetic clusters in Reunion 8 0.14 0.66 0.20 Island 9 0.32 0.16 0.52 10 0.35 0.56 0.10 Only longitude and average rainfall significantly 11 0.23 0.73 0.03 affected the relative frequency of individuals of the three clusters (Table 7), whereas altitude and sampling Location numbers according to Fig. 1b period did not. This shows heterogeneous distributions of host plants (cultivated or wild). The highest of the three clusters on the east coast (average daily difference among groups (Fct = 0.12) is observed rainfall for 6 months = 11.045 ± 4.546 mm) and on when groups correspond to the three clusters found in the west coast (average daily rainfall for 6 months = 123 Author's personal copy

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Table 5 MIGRATE maximum likelihood estimates (confi- five groups of B. cucurbitae from La Reúnion (R1, R2 R3), dence intervals in parentheses) of migration rates (M), number Africa (AF) and Asia (AS) as resulting from the STRUCTURE of migrants per generation (Nm) and population sizes (H) for analysis shown in Fig. 2c MNm

Africa to La Reúnion AF to R1 9.5 (8.70–10.02) 2.92 (2.68–3.08) AF to R2 9.54 (8.43–10.07) 2.93 (2.59–3.10) AF to R3 10.25 (9.72–11.29) 3.15 (2.99–3.47) La Reúnion to Africa R1 to AF 9.95 (8.96–10.48) 2.81 (2.53–2.96) R2 to AF 9.05 (8.10–9.55) 2.53 (2.27–2.67) R3 to AF 9.25 (8.77–10.15) 2.64 (2.50–2.89) Asia to La Reúnion AS to R1 7.18 (6.39–7.64) 2.85 (2.54–3.04) AS to R2 6.76 (6.00–7.20) 2.69 (2.39–2.86) AS to R3 7.87 (7.41–8.76) 3.13 (2.95–3.48) La Reúnion to Asia R1 to AS 4.72 (4.16–5.02) 1.33 (1.18–1.42) R2 to AS 4.25 (3.72–4.54) 1.19 (1.04–1.27) R3 to AS 4.98 (4.47–5.28) 1.42 (1.27–1.50) Within La Reúnion R1 to R2 12.96 (11.91–13.56) 3.66 (3.36–3.83) R1 to R3 15.29 (14.65–16.61) 4.32 (4.14–4.69) R2 to R1 14.94 (13.65–15.59) 4.18 (3.82–4.37) R2 to R3 14.93 (14.27–16.63) 4.18 (4.00–4.66) R3 to R1 15.06 (14.01–15.71) 4.29 (3.99–4.48) R3 to R2 13.44 (12.36–14.05) 3.83 (3.52–4.00) Africa to Asia 8.13 (7.76–8.82) 2.50 (2.39–2.71) Asia to Africa 13.16 (12.03–13.76) 5.23 (4.78–5.47) H

R1 1.13 (1.08–1.16) R2 1.12 (1.09–1.17) R3 1.14 (1.12–1.20) AF 1.23 (1.20–1.30) AS 1.59 (1.55–1.67)

2.355 ± 2.185 mm) of Reunion Island. Indeed, as et al. (2010) was measured by the fixation index, Fst shown in Fig. 1, individuals belonging to cluster 1 were (Table 8 in supplementary material). Pairwise Fst present everywhere on the island but were more values between clusters of Reunion Island and the abundant in the western part, whereas cluster 2 was other countries tested were significant. The Hawaiian found mostly along the east and south coast of the population seems to be well separated from that of island, and individuals of cluster 3 were predominant in Reunion Island with pairwise Fst ranging from 0.314 the western part. The results of our predictions confirm to 0.387. Furthermore, pairwise Fst values between the these trends, regardless of the season (Fig. 4). three clusters and the African and Asian populations are on the same order. Within Reunion Island, individuals of clusters 2 and 3 were much closer, Population differentiation whereas cluster 1 was the most genetically divergent of the other two. In addition, populations of Mauritius Genetic divergence between clusters of Reunion and the Seychelles were closer to clusters 2 and 3 from Island and those from data published in Virgilio Reunion Island than to cluster 1.

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Table 6 Analysis of molecular variance (AMOVA) testing the partitioning of genetic variation among and within groups corresponding to: (C) clusters (Cluster1, Cluster2, Cluster3), (L): sampling locations, (H) nature of hosts-plants Group Among groups Among samples within groups Within samples Fct % Va Fsc % Vb Fst % Vc

C 0.12*** 12.13 0.23 0.02*** 0.04 1.87 0.14*** 1.65 85.99 _L 0.01* 1.16 0.02 0.02*** 2.28 0.04 0.03*** 96.55 1.61 _H 0.00ns -0.25 -0.01 0.03*** 3.14 0.08 0.03*** 97.11 2.35 Cluster1_L 0.01*** 1.28 0.03 0.02*** 2.20 0.05 0.03*** 96.52 2.17 Cluster1_H 0.00ns 0.00 0.00 0.03*** 3.39 0.08 0.03*** 96.61 2.17 Cluster2_L 0.01* 0.64 0.01 0.01*** 1.12 0.03 0.02*** 98.24 2.29 Cluster2_H 0.00ns -0.32 -0.01 0.02*** 1.99 0.04 0.02*** 98.33 1.86 Cluster3_L 0.01* 0.66 0.01 0.03*** 2.92 0.06 0.04*** 96.41 1.92 Cluster3_H 0.00ns -0.02 0.00 0.04*** 3.68 0.08 0.04*** 96.34 2.06 AMOVA testing the effects of (L) and (H) was repeated separately for Cluster1, Cluster2, and Cluster3. Individuals were assigned to cluster 1, 2 or 3 according to the STRUCTURE analysis (n.s.: not signiﬁcant a P \ 0.05; *** P \ 0.001, ** P \ 0.01, * P \ 0.05)

Table 7 Analysis of deviance on abundance of the three clusters found on La Reúnion Effect Ddev Dd.f. Residual dev Residual d.f. F P l 511.51 2 822.89 82 65.71 1.3121E - 17*** rr 32.58 2 343.96 82 4.19 0.02* All the effects tested in the model are given and their significance is indicated. Ddev corresponds to the changes in deviance due to the suppression of the ‘‘effect’’ term from the referenced model. The residual deviance and d.f. relate to the reference model. F-tests and corresponding P-values test the significance of the effect. Code for effects: l = longitude (East or West), rr = daily rainfall average for 3 months (n.s.: not significant a P \ 0.05; *** P \ 0.001, **P \ 0.01, * P \ 0.05)

Phylogeographic analysis These two groups are separated by a maximum number of 21 mutational steps. Specimens from the A total of 100 specimens of B. cucurbitae were three clusters of Reunion Island (as identified by sequenced at the COI and ND6 gene fragments. The microsatellite analyses) could not be distinguished COI gene fragment (660 bp) produced 13 haplotypes either within Reunion Island or between Reunion with 11 polymorphic sites (eight of which were Island and the African continent. parsimony informative) and an average p-distance between the two main regions (Africa/Reunion Island, Asia/Hawaii) of 0.001 % (S.E. = 0.001 %). The ND6 Discussion gene fragment (638 bp) produced ten unique haplotypes with ten polymorphic sites (four of which were Structure and genetic diversity parsimony informative) and an average p-distance among regions of 0.007 % (S.E. = 0.005 %). The Our results show that there was a significant heterozy- concatenated dataset COI ? ND6 (1298 bp) yielded gote deficiency in Reunion Island (under the Hardy– 22 haplotypes with 21 polymorphic sites (seven of Weinberg model), which is partly due to a Wahlund which were parsimony informative) and an aver- effect. Consequently, there was an allelic divergence age p-distance among regions of 0.003 % (S.E. = inside populations of B. cucurbitae from this tropical 0.002 %). The Minimum Spanning Network revealed island, and the population could be subdivided into the occurrence of two main haplotype groups corre- admixed sub-populations. Moreover, comparison sponding to specimens from (a) Asia and Hawaii, and between Fis values and the allelic richness of Reunion (b) the African continent and Reunion Island (Fig. 5). Island and the other countries tested revealed that there

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Population structure of Bactrocera cucurbitae in Reunion Island 769

Fig. 4 Predicted values of relative abundance of Bactrocera cucurbitae adults on the east and west coasts of Reunion Island according to the daily rainfall average (rr) for 6 months (austral summer and winter 2009) for cluster 1(black), cluster 2 (light gray) and cluster 3 (medium gray)

Fig. 5 Minimum Spanning Network illustrating the phylogeographic relationships of 22 concatenated COI ? ND6 haplotypes observed in 100 specimens of B. cucurbitae from East and West Africa, Congo, Sudan, East and Central Asia, Hawaii and Reunion Island. Circle areas are proportional to haplotype frequencies; small black dots represent missing haplotypes. Each line represents one base pair substitution along the 1,298 bp fragment

was no decrease in genetic diversity (i.e., founder Existence of three clusters in Reunion Island effect). Rather than a significant detectable bottleneck, our data suggest that Reunion Island populations The Bayesian cluster analysis and the analysis of underwent a recent population expansion. This implies molecular variance (Fst = 0.14; Table 6) showed that either multiple introductions or a single introduction of on Reunion Island, samples of B. cucurbitae could be a large number of individuals (Franks et al. 2011). In subdivided into three clusters of comparable size addition, the study of the genetic variation within the (n1 = 789, n2 = 886 and n3 = 616, respectively; B. cucurbitae population from Reunion Island provided Fig. 3a.), and each group contained flies from different no genetic evidence for a host race formation (Fct = 0, locations and host plants. Nevertheless, on the whole, Fst = 0.03; Table 6). There is a weak spatial genetic a distribution pattern of these sympatric clusters could structure, independent of the host plants, within be observed: individuals of cluster 2 were significantly Reunion Island. Considering a rapid pattern of coloni- more distributed in the eastern part of the island, zation, this spatial heterogeneity within this invasive individuals of cluster 3 on the west coast, and the population was probably due to the existence of high majority of individuals of cluster 1 in the northwest of gene flow among sites and hosts, linked to the dispersal the island (Fig. 1b.). These initial observations indi- ability of the pest, B. cucurbitae. cate that individuals of these three clusters differ in

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770 C. Jacquard et al. their geographical distribution and therefore reflect the single inoculum but that during the early stages of the existence of a spatial heterogeneity in the early stages colonization process, three differentiated populations of colonization, which decreased over time. Thus, we emerged from local drift or founder effects. In these predict that the relationships between the relative two cases, the current distribution of the clusters abundance of clusters and the different environmental would primarily reflect the position of their ancestral factors such as climate (rainfall) and topology (zone) populations during the early stages of colonization that will clarify the distribution that we observed (Fig. 4). have progressively spread and admixed during their Actually, individuals that belong to cluster 1 were subsequent spread and population expansion, in which broadly tolerant of both humid and dry conditions, so case genetic differentiation will progressively vanish they were better adapted at the local level to different because of admixture and recombination. In a third niches to maintain large populations under different case, we could hypothesize that the three clusters conditions. Next, clusters 2 and 3 show contrasting represent early stages of a population differentiation patterns: individuals of cluster 2 prefer climates with process (i.e., partially reproductively isolated gene high rainfalls (east coast), whereas the individuals of pools), which may (or may not) have existed prior to cluster 3 prefer the drier west coast. Furthermore, the introduction. Therefore, the current distribution pairwise Fst values (Table 8 in supplementary mate- would be partly driven by local adaptation (if the three rial) revealed that individuals of clusters 2 and 3 are gene pools have different ecological preferences, e.g., very close, whereas individuals of cluster 1 are less with respect to rainfall), and the persistence of genetic similar than the other two. This type of population differentiation in time will therefore depend on their subdivision within a species is usually more frequent degree of reproductive isolation. in an insular environment where the presence of multiple microclimates provides various micro-habi- Origin of clusters from Reunion Island tats that might play a role as an important natural refuge for invaders and thus lead to subdivided The main assumptions of MIGRATE concern constant populations or create more genetic diversity (Subra- population sizes and migration rates, as well as the manian and Mohankumar 2006). Furthermore, with lack of unsampled populations that exchange genes the topology that exists in Reunion Island, rainfall with sampled populations. With recent divergence, differs distinctly between protected mountainsides like after the introduction of B. cucurbitae in Reunion (east coast) and those that are exposed to dominant Island, estimates of migration rates might have been winds (west coast) that allow the existence of upwardly biased. Yet, even under this scenario, gene geographical and ecological niche segregation flow directions and relative proportions can be con- between the three clusters found, even if they overlap. sistently evaluated. Moreover, while population sizes These migration patterns also highlight the existence and numbers of migrants tend to be overestimated with of a high gene flow (Table 5) between these three unsampled populations, estimates of migration rates clusters throughout the island. are not, even when this assumption is violated (Beerli To test the robustness of the substructure found on 2004). Reunion Island under STRUCTURE, we compared Migration rates among the sympatric clusters of our data with the dataset already published by Virgilio Reunion Island were always higher than migration et al. (2010) and found a subdivision in five main rates between Reunion Island and the possible source geographic groups. These groups correspond to the populations from Africa and Asia. This indicates that three clusters of Reunion Island, one from Africa and the three clusters in Reunion Island, even though they another one from Asia (Fig. 3c). Thus, our results are genetically distinguishable, exchange gene flows clearly indicate that samples of B. cucurbitae from and are not genetically isolated among them. Esti- Reunion Island constitute a well-differentiated sub- mates of gene flow from Africa to Reunion Island and group compared to other populations found around the from Reunion Island to Africa are comparable and are world. consistently higher than estimated gene flows between In our case, we could first hypothesize that three Asia and Reunion Island. These data are congruent introductions of distinct populations of B. cucurbitae with two different scenarios: the first involves an occurred and admixed on the island, or that there was a Asian origin of B. cucurbitae in Reunion Island and a 123 Author's personal copy

Population structure of Bactrocera cucurbitae in Reunion Island 771 secondary contact with populations from the African Moreover, knowledge about the geographic origin continent; the second suggests an African origin of could provide specific monitoring and quarantine B. cucurbitae in Reunion Island. measures that target the source area and the means of Using mitochondrial DNA on our data and those of dispersal of invasive species (Estoup and Guillemaud Virgilio et al. (2010), individuals from the three 2010). clusters of Reunion Island (identified by microsatellite analyses) could not be distinguished either within Reunion Island or between Reunion Island and the Conclusion African continent. Although mitochondrial DNA markers are not the best tool to trace back intra- In conclusion, B. cucurbitae on Reunion Island can be population differentiation in a recent past due to a subdivided into three sympatric populations that lower evolution rate and to selection constraints exchange gene flows and that are characterized by (Avise 1994; Moritz et al. 1987; Lunt et al. 1996; heterogeneous spatial distribution on the east/west Grapputo et al. 2005), their use in the present study axis of the island. The phylogeographic structure that allowed us to highlight the fact that there is no emerges from the analysis of mitochondrial evidence of three different haplotypes on Reunion sequences, as well as the Bayesian assignments of Island and that there has not been enough evolutionary STRUCTURE (dataset 2, K = 2), show very minor time for mitochondrial sequences to diverge since the differences between individuals from Reunion Island species was introduced. In addition, this was con- and from the African continent, whereas there is a firmed by our pairwise Fst values (Table 8 in supple- clear distinction between specimens from Reunion mentary material) and our estimated patterns of Island and from Asia. These data are not compatible migration: the emigration rates between populations with the first scenario resulting from the analysis of of Reunion Island and Africa (2.64–2.81, Table 5) are gene flow (Asian origin of B. cucurbitae in Reunion higher than those with Asia (1.19–1.42, Table 5). Island and secondary contact with African popula- Consequently, all our data implies a close relation- tions), but are instead consistent with the African ship with the African continent where the presence of origin of B. cucurbitae in Reunion Island. B. cucurbitae was first recorded in 1936 in Tanzania (http://data.gbif.org/occurences/). We can therefore Acknowledgments We thank Christophe Simiand, Jim Payet, hypothesize that the recent introductions of melon fly Serge Gleńac, Marie-Ludders Moutoussamy, Ce´dric Ajaguin- Soleyen and Antoine Franck for their assistance with field in Reunion Island came from Africa. Indeed, accord- collections and laboratory work. Special thanks to Delphine ing to historical observations, the presence of the Ramalingom for guiding us in using the TITAN calculation melon fly was first recorded in Mauritius in 1942 platform of the University of Reunion Island. This work was (Orian and Moutia 1960), in Reunion Island in 1972 supported by grants from the Regional Council of Reunion Island, the European Union and the Centre de Cooperation International (Etienne 1972) and, more recently, in 1999 in the en Recherche Agronomique pour le De´veloppement (CIRAD). Seychelles (White et al. 2000). Nevertheless, the question remains open as to whether (1) Reunion Island was colonized by a common source that origi- nated on the African continent, which also invaded References Mauritius and the Seychelles; (2) or that Reunion Island was colonized from three sets of introductions Avise JC (1994) Molecular markers, natural history and evo- from Mauritius, with different ecological preferences lution. Chapman & Hall, New York (Vayssie`res 1999). Identifying the precise geographic Baruffi L, Damiani G, Guglielmino CR, Bandi C, Malacrida AR, Gasperi G (1995) Polymorphism within and between pop- source of colonists is essential to assaying the level of ulations of Ceratitis Capitata—comparison between Rapd genetic variation to find the source populations for and Multilocus enzyme electrophoresis data. Heredity introductions of B. cucurbitae, so the native ranges 74:425–437 have to be carefully sampled. Effectively, elucidation Bates D, Maechler M, Bolker B (2011) lme4: linear mixed- effects models using S4 classes. R package version of the history of this alien invasive species on 0.999375-42. http://CRAN.R-project.org/package=lme4 this island may help to determine its potential for Beerli P (2004) Effect of unsampled populations on the esti- future secondary invasions of Indian Ocean islands. mation of population sizes and migration rates between 123 Author's personal copy

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