Insect Science (2014) 00, 1–13, DOI 10.1111/1744-7917.12134

ORIGINAL ARTICLE

Species and endosymbiont diversity of Bemisia tabaci (Homoptera: Aleyrodidae) on vegetable crops in Senegal Delatte Hel ´ ene ` 1 , Baudin Remy ´ 1 , Becker Nathalie2 , Girard Anne-Laure3 , Ramatoulaye Sidebe Traore´ 3 , Lett Jean-Michel1 and Reynaud Bernard1 1 CIRAD,

UMR PVBMT, F-97410 Saint-Pierre, La Reunion, France, 2 Museum National d’Histoire Naturelle, Institut de Systematique, ´ ´

Evolution, Biodiversite, ´ ISYEB, UMR 7205 CNRS, UPMC, EPHE, 75005 Paris, France, and 3 TECHNISEM, Zone d’activite´ Anjou Actiparc de Jumelles, 49160 Longue-Jumelles, France ´

Abstract Bemisia tabaci-transmitted geminiviruses are one of the major threats on cassava and vegetable crops in Africa. However, to date, few studies are available on the diversity of B. tabaci and their associated endosymbionts in Africa. More than 28 species have been described in the complex of B. tabaci cryptic species; among them, 2 are invasive pests worldwide: MED and MEAM1. In order to assess the species diversity of B. tabaci in vegetable crops in Senegal, several samplings in different localities, hosts and seasons were collected and analyzed with nuclear (microsatellite) and mitochondrial (COI) markers. The bacterial endosymbiont community was also studied for each sample. Two species were detected: MED Q1 and MEAM1 B. Patterns of MED Q1 (dominance on most of the samples and sites, highest nuclear and mitochondrial diversity and broader secondary endosymbiont community: Hamiltonella, Cardinium, Wolbachia and Rickettsia), point toward a predominant resident begomovirus vector group for MED Q1 on market gardening crops. Furthermore, the lower prevalence of the second species MEAM1 B, its lower nuclear and mitochondrial diversity and a narrower secondary endosymbiont community (Hamiltonella/Rickettsia), indicate that this genetic group is exotic and results from a recent invasion in this area. Key words begomovirus vectors; endosymbionts diversity; MED and MEAM1 species; microsatellites; mtCOI phylogeny; whitefly

Introduction Whitefly-transmitted geminiviruses are one of the major threats to staple food and vegetable crop production in Africa. For example, cassava production has been affected recently by pandemics of 2 virus diseases: cassava mosaic disease (CMD) and cassava brown streak disease, inducing severe yield losses and food scarcity (Legg et al., 2011). Despite the fact that CMDs are well trans-

Correspondence: Delatte H´el`ene, CIRAD-UMR PVBMT, 3P, 7, ch de l’IRAT, 97410 Saint Pierre, La R´eunion, France. Tel: 0262-262-49-9235; fax: 0262-262-49-9293; email: [email protected]

mitted by infected cuttings, whiteflies (Bemisia tabaci) were also recognized to play a crucial role in the spread of this disease (Legg, 2010). Indeed, being polyphagous and more prolific on infected plants, whiteflies enhanced the rate of dissemination of the virus (Legg & Thresh, 2000). As a result B. tabaci are a serious problem in many African countries not only due to their capacity to transmit CMD, but also to transmit other begomoviruses on vegetable crops, such as tomato (Czosnek & Laterrot, 1997; Fauquet et al., 2003). To date, there have been no practical solutions to combat this emerging problem, due to the inability of the subsistence farmers that grow staple food like cassava to afford expensive inputs, such as insecticides (Omongo et al., 2012). CMD incidence and severity across Africa is well documented. Fewer studies are 1

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Fig. 1 Map of the 5 sites sampled (Africa with Senegal in Zoom) and prevalence’s of each of the Bemisia tabaci species, in gray MED Q1 and in black MEAM1 B.

available on incidence of other begomoviruses on vegetable crops and cotton in Africa, whose only way of transmission on annual plants, such as market gardening crops, relies on B. tabaci. The whitefly B. tabaci is a complex of cryptic species containing over 28 morphologically indistinguishable putative species (Dinsdale et al., 2010; De Barro et al., 2011; Liu et al., 2012). Most of those species are area specific (Boykin et al., 2007), except two of them: one originating from the Mediterranean area and named “MED” as such (formally referred to as the “Q biotype”), and the other from Middle East-Asia Minor named “MEAM1” (formally referred to as the “B biotype”). Both species have recently spread to most of the countries of the world, and are found in a broad host range of vegetable crops, from cotton to ornamental plants (De Barro et al., 2011). The MED Q group was described as composed of 3 cytochrome oxydase I (COI)-differentiated groups: MED Q1, MED Q2 and MED Q3 (Gueguen et al., 2010). Among those polyphagous species, particular whitefly species of the B. tabaci complex are specialized on cassava (Legg et al., 2002; Abdullahi et al., 2003; Delatte et al., 2011; Khan et al., 2011; Mugerwa et al., 2012; Rey et al., 2012). Indeed, the knowledge of these vector species is extremely important for their management, especially in mixt cropping system with cassava. The different genetic species of B. tabaci were reported to harbor a specific secondary bacterial endosymbiont community (up to 7 secondary endosymbionts are known (Zchori-Fein & Brown, 2002; Bing et al., 2013), correlated to the genetic species observed (Chiel et al., 2007; Gueguen et al., 2010; Thierry et al., 2011; Gnankine et al., 2013a). These facultative endosymbionts are mainly vertically transmitted, but horizontal transfer may occur within and between species at different evolutionary time scales (Moran et al., 2008; Mouton et al., 2012).

In the western African country Senegal, occurrence of several begomoviruses associated with cassava (OkaoOkuja et al., 2004) or tomato (D’Hondt & Russo, 1985) have been reported and incriminated whiteflies, however, without species distinction. As seen above, B. tabaci is a complex of several species with different biological traits; knowing their specific species distribution, as well as their associated endosymbiotic fauna, is of first interest for pest management. The objective of this study was to study the diversity of whitefly species, evaluate their genetic diversity and their endosymbiont communities, associated to a large panel of vegetable crops in different locations in Senegal.

Materials and methods Study area Our study was conducted in Senegal, located on the west of the African continent, bounded by the Atlantic Ocean to the west, as well as by following countries: Mauritania, Mali, Guinea, Guinea-Bissau and Gambia. The climate is tropical with 2 main seasons: the dry season and the rainy season. Whitefly sampling B. tabaci adults were collected during the 2 main seasons of 2009, within the dry season (January–May) and the rainy season (June–August). Samplings were carried out in 5 locations over Senegal on 7 different host plants (Fig. 1, Table 1). After collections, adults were stored in 95% ethanol at –20 °C. Adults were morphologically sexed under a binocular (40×) stereomicroscope, as in Calvert et al. (2001), before DNA extraction. Host plants included only cultivated plants: tomato (Lycopersicon esculentum), African eggplant  C

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Station Baobab 1

Station Baobab 1

Station Baobab 1

Station Baobab 1 Station Baobab 1 Station Baobab 2

Station Baobab 2

Station Cordia

Station Cordia

1

1

1

1

2

3

3

2

1

Station Baobab 1

Locality

1

Sites

Institute of Zoology, Chinese Academy of Sciences, 00, 1–13 Pi3

Ae3

Gi2

To2

Go1

Ee1

Pe1

Ae1

Pi1

To1

Acronym

Chili pepper

African eggplant

Pumpkin

Tomato

European eggplant Okra

Pepper

African eggplant

Chili pepper

Tomato

Capsicum fructescens

Solanum ethiopicum

Cucurbita maxima

Solanum melongena Abelmoschus esculentus Lycopersicon esculentum

Capsicum annuum

Solanum ethiopicum

Capsicum fructescens

Lycopersicon esculentum

Host plant

30% B & 70% Q1

10% B & 90% Q1

80% B & 20% Q1

85% B & 15% Q1

50% B & 50% Q1

44% B & 56% Q1

80% B & 20% Q1

10% B & 90% Q1

10% B & 90% Q1

100% Q1

Genetic group/species

20

10

15

20

4

9

10

10

10

10

N

Rainy

Rainy

Dry

Dry

Dry

Dry

Dry

Dry

Dry

Dry

Season

Table 1 Sampling information of the different genetic groups of whiteflies according to locality, host plant and season.

JN119575;JN119592;JN119594;JN119599; JN119616;JN119618;JN119639;JN119641; JN119662;JN119664;JN119679;JN119681; JN119699;JN119702;JN119721;JN119723; JN119726;JN119744;JN119745 JN119577;JN119579;JN119601;JN119623; JN119625;JN119646;JN119648;JN119667; JN119668;JN119685;JN119687;JN119706; JN119708;JN119731;JN119733 JN119572;JN119596;JN119602;JN119620; JN119626;JN119649;JN119669;JN119688; JN119709;JN119734 JN119580;JN119583;JN119604;JN119607; JN119629;JN119631;JN119643;JN119652; JN119654;JN119665;JN119672;JN119682; JN119691;JN119692;JN119703;JN119712; JN119714;JN119728;JN119736 (to be continued)

JN119573;JN119581;JN119597;JN119605; JN119621;JN119644;JN119666;JN119683; JN119704;JN119729 JN119674;JN119582;JN119606;JN119628; JN119630;JN119651;JN119653;JN119671; JN119690;JN119711;JN119735 JN119584;JN119608;JN119632;JN119655; JN119673;JN119675;JN119693;JN119713; JN119737 JN119587;JN119611;JN119635;JN119658; JN119677;JN119695;JN119716;JN119718; JN119727;JN119741 JN119588;JN119590;JN119612;JN119636; JN119659;JN119696;JN119719;JN119742 JN119614;JN119661;JN119678;JN119698

Accession number

Whitefly and associated endosymbionts in Senegal 3

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Camberene

Camberene

5

Khombole

Locality

5

4

Sites

Table 1 Continue.

Ee5

To5

Pi4

Acronym

African eggplant

Tomato

Chili pepper

Solanum ethiopicum

Lycopersicon esculentum

Capsicum fructescens

Host plant

4% B & 96% Q1

33% B & 67% Q1

100% Q1

Genetic group/species

27

15

30

N

Rainy

Rainy

Dry

Season

JN119585;JN119586;JN119589;JN119591; JN119609;JN119610;JN119613;JN119615; JN119633;JN119634;JN119637;JN119638; JN119656;JN119657;JN119660;JN119676; JN119694;JN119697;JN119715;JN119717; JN119720;JN119738;JN119739;JN119740; JN119743 JN119593;JN119595;JN119617;JN119619; JN119640;JN119642;JN119663;JN119700; JN119722;JN119724;JN119746 JN119574;JN119576;JN119598;JN119600; JN119622;JN119624;JN119645;JN119680; JN119684;JN119701;JN119705;JN119725; JN119730;JN119747;JN119578;JN119603; JN119627;JN119647;JN119650;JN119670; JN119686;JN119689;JN119707;JN119710; JN119732

Accession number

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Whitefly and associated endosymbionts in Senegal

(Solanum ethiopicum), European eggplant (Solanum melongena), Chilli pepper (Capsicum frutescens), pepper (Capsicum annuum), okra (Abelmoschus esculentus) and pumpkin (Cucurbita maxima). DNA extraction Due to their haplo-diploid status, only females were used in this study. A modified version of the protocol described in Delatte et al. (2005) was applied. Each field-captured whitefly was incubated in 50 μL extraction buffer [50 mmol/L KCl, 10 mmol/L Tris-base (pH 8), 0.45% IGEPALCA-630, 0.45% Tween 20 and 500 mg/mL proteinase K (Sigma)] at 65 °C for 20 h, then a last step of incubation was performed at 95 °C for 10 min. Extracts were finally stored at –20 °C until use. Nuclear and mitochondrial diversity Microsatellite amplification and genotyping A total of 342 adults were genotyped using 10 microsatellite loci: P7, P62, P53, P41, P32, P5, P11, P59 (Delatte et al., 2006), Bem25 (De Barro et al., 2003) and Ms145 (Dalmon et al., 2008). The equivalent of 10 ng genomic DNA was used for amplification with the QIAGEN multiplex PCR Master Mix kit according to the manufacturer’s instructions in a final volume of 15 μL. One of each pair of primers was end-labeled with the fluorochromes NED, VIC, PET or FAM (Applied Biosystems). Two primer mixes were used: (i) P7, P62, P53, P41, P32, Bem25 and (ii) P5, P11, P59, Ms145 at 400 nmol/L each. A first step of denaturation at 94 °C for 5 min was followed by 40 cycles at 94 °C for 30 sec, 50 °C for 30 sec, 72 °C for 1 min, with a final elongation step for 10 min at 72 °C. Note that 2 μL of 1/60th diluted polymerase chain reaction (PCR) products were mixed with 10.7 μL of ultra-pure Hi-Di-formamide TM (Applied Biosystems) and 0.3 μL of size marker (GeneScan 500Liz), and loaded onto an ABI Prism 3100 Genetic Analyser (Applied Biosystems) automated sequencer. Allele sizes were determined using GeneMapper v4.0. Microsatellite and genetic diversity analyses To analyze our data, we used the Bayesian clustering program STRUCTURE version 2.3.3 (Pritchard et al., 2000). This software differentiates mixed populations on the basis of allele frequency at each locus. The number of individuals and allele frequencies in each cluster, as well as individual assignments, are outputs of the analysis. In order to determine the optimal number of populations (K) of our sample, STRUCTURE was  C 2014

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run for K ranging from 1 to 20 (each K was run 10 times). The method of Evanno et al. (2005) was used to find the uppermost level of structure in the data set (statistics were calculated using structure Harvester online: http://taylor0.biology.ucla.edu/structureHarvester/). The optimal K turned out to be K = 2. The software was then run twice, with and without the admixture option, which allows for some mixed ancestry within individuals. To use STRUCTURE, Hardy–Weinberg equilibrium (HWE) and linkage equilibrium are assumed within each group. Both hypotheses were tested a posteriori on each cluster using exact tests implemented in Genepop 4.0 (Rousset, 2008). Some assumptions of STRUCTURE, such as HWE and linkage equilibrium, are potentially violated by the haplo-diploid status and reproduction of this species. We also conducted another clustering method that does not make these assumptions: a principal components analysis (PCA) of allele frequencies using R 2.15 (R Development Core Team, 2004). We visualized the position of the groups and individuals defined by the STRUCTURE software along the axes of genetic variation. Significant deviations from HWE for individuals of the 2 genetic groups were evaluated using an exact probability test in Genepop 4.0. Allele frequencies, observed and expected heterozygosities, as well as excess of heterozygotes (FIS ) were analyzed using Genepop 4.0. Mitochondrial amplification and analysis Mitochondrial COI (mtCOI) sequences (Table 1) were obtained by PCR amplification with the primer set COIF-C1 and COI-R-C1. The PCR was conducted in a final volume of 25 μL with 10× PCR Optibuffer (Eurogentec), 0.2 mmol/L dNTPs (New England Biolabs), 1.5 mmol/L MgCl2 , 400 nmol/L of each primer, 1 unit of DAp GoldStar (Eurogentec) and 10 ng of insect DNA extract. A first step of denaturation at 94 °C for 5 min followed by 35 cycles at 94 °C for 1 min, 57 °C for 1 min, 72 °C for 1 min, with a final elongation step for 7 min at 72 °C. Each PCR product was sequenced (Macrogen Inc., Sequencing Service, Korea). Sequences produced in this study were identified using the algorithm BLAST into GenBank (http://www.ncbi.nlm.nih.gov) and submitted to GenBank (Table 1). Ten other mtCOI sequences were obtained from public sequence databases using Tax browser (http:// www.ncbi.nlm.nih.gov/Taxonomy/taxonomyhome.html). Multiple sequence alignments were constructed using the CLUSTALW-based subalignment tool available in MEGA version 4 (Tamura et al., 2007) and by manual editing. The optimal model of sequence evolution defined by JModelTest (Posada, 2008) was the HKY

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D. H´el`ene et al. Table 2 Genetic diversity according to Bemisia tabaci genetic groups and per sites, comprising allelic richness (a), observed and expected heterozygosity (He and Ho) and FIS .

used for phylogenetic reconstruction. MrBayes 3.1 was used for Bayesian phylogenetic inference (Ronquist & Huelsenbeck, 2003). In all analyses, 4 Markov chains were allowed to sample parameters and tree topologies every 100 generations for 3 000 000 generations. At the end of each run the average standard deviation of split frequencies was below 0.01. Inspecting sampled parameter values by eye with Tracer (Tracer 2003–2006, MCMC Trace File Analyser, A. Rambaut and A. Drummond, University of Oxford) showed stabilized values after 1000 generations; the first 10 000 generations were discarded as a conservative burn-in. For each Bayesian analysis, Tracer was also used to check that autocorrelation between samples was limited enough to produce effective sample sizes greater than 200 for each parameter. Runs of each analysis performed with MrBayes converged with Potential Scale Reduction Factor (PSRF) values at 1. Trees were visualized with Figtree (FigTree, 2006–2009, A. Rambaut).

MEAM1

MED

Sites

a

Ho

He

Site 1 Site 2 Site 3 Site 4 Site 1 Site 2 Site 3 Site 4 Site 5

2.72 2.73 2.79 2.96 3.47 3.13 3.37 3.49 3.42

0.425 0.507 0.471 0.418 0.500 0.483 0.492 0.532 0.513

0.460 0.464 0.503 0.426 0.602 0.592 0.604 0.619 0.604

FIS (W&C) 0.123 −0.101 0.045 0.112 0.170 0.185 0.178 0.150 0.154

Note: None of the FIS were significant.

ond, genetic variation was partitioned into 3 different levels: among endosymbiont combinations (Fct ), within endosymbiont combinations among host plants (Fsc ) and within host plants (Fst ). Third, genetic variation was partitioned into 3 different levels: among endosymbiont combinations (Fct ), within endosymbiont combinations among season (Fsc ) and within seasons (Fst ). All other combinations of clustering levels were analyzed as well. Significance was tested by 1023 permutations as described by Excoffier et al. (2005).

Secondary endosymbiont community detection First, we checked the quality of the bacterial DNA extraction, using primers PortF/PortR for PCR detection of the primary endosymbiont Portiera aleyrodidarum, and then used a PCR multiplex to detect the secondary symbiotic community as described in Thierry et al. (2011). The presence of 5 secondary endosymbionts was tested: Cardinium, Hamiltonella, Rickettsia, Wolbachia and Arsenophonus. For multiplex analysis, 10 ng of the total insect DNA extract was used for amplification with the QIAGEN multiplex PCR Master Mix kit. About 2 μL of the 1/20th diluted PCR product was mixed with 10.7 μL of ultrapure formamide and 0.3 μL of size marker (GeneScan 1200 Liz, Foster City, CA, USA), and loaded onto an ABI Prism 3100 Genetic Analyser (Applied Biosystems) automated sequencer. Detection of secondary endosymbionts was performed using GeneMapper v4.0.

Results B. tabaci species prevalence’s In 3 localities out of 5, MED Q1 was predominant and always found in sympatry with MEAM1 B. In 1 locality MED Q1 was less abundant; albeit in sympatry with MEAM1 B (Baobab2), in another it was the only species found (Khombole, Fig. 1, Table 1). To be noted, no locality harbored MEAM1 B only. Both species were found during the different seasons prospected and on the different host plant species sampled, in most sites in sympatry. No other B. tabaci species was found.

Genetic structure versus symbiotic diversity To assess whether endosymbiotic combinations among a B. tabaci genetic group structured the nuclear genetic diversity, we tested season, sites or host plant by a hierarchical analysis of molecular variance (AMOVA) using ARLEQUIN version 3.11 (Excoffier et al., 2005). We performed 3 analyses for each of the 2 genetic groups. First, genetic variation was partitioned into the 3 following levels: among endosymbiont combinations (Fct ), within endosymbiont combinations among sites (Fsc ) and within sites (Fst ) (Supplementary data, Table S1). Sec-

Genetic diversity and structuring A total of 190 individuals successfully amplified for more than 8 microsatellite loci out of 10, as well as for the primary endosymbiont P. aleyrodidarum, and provided successful sequencing of the mtCOI gene. The 10 microsatellite loci had 4–22 alleles each, with allelic richness ranging from 2.72 to 3.49 (according to site and species; Table 2).  C

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Phylogenetic analysis mtCOI sequencing of each sample confirmed the clustering and allowed us to assign to STRUCTURE cluster 1 the B. tabaci genetic group named MED Q1 and to cluster 2 the group MEAM1 B (Fig. 3). Three and 8 mt haplotypes were respectively retrieved from the 58 individuals of the MEAM1 B genetic group, and the 132 individuals of the MED Q1 genetic group (Fig. 3).

Secondary endosymbiont community analyses

Fig. 2 Multivariate analysis of Bemisia tabaci populations of Senegal: 1st and 2nd components of a principal component analysis (PCA) of 10-loci microsatellites from MEAM1 and MED species defined by STRUCTURE software. The relative contributions of the 2 first axes explained 98% of the total genetic variation, with 81% and 17% for the 1st and the 2nd axis, respectively.

Population structure among samples was investigated using assignation probabilities given by STRUCTURE software. We found, according to STRUCTURE, a high structuring of K = 2 populations (DK = 16 000; Evanno’s graphs are available upon request), with 132 and 58 individuals assigned to cluster 1 and 2, respectively. It was considered that an individual assignation probability in the [0.10; 0.90] interval belonged to a hybrid genotype, the others from pure populations; no hybrids were detected in the data set. Another run was launched with STRUCTURE among each of the clusters in order to test for substructure. The same parameters were used, and no substructure was detected among each cluster. The PCA was performed to visualize the major axes of genetic variation within the sample, and the position of the groups defined by the STRUCTURE software along these axes (Fig. 2). The PCA confirmed the Bayesian clustering method implemented in STRUCTURE. The two axes explained 99% of the total genetic variation, with 82% and 17% for the 1st and the 2nd axis, respectively. The PCA clearly separated 2 groups of genotypes on the 1st axis. The genetic differentiation between both group was also very strong and significant with Fst = 0.26 (GENEPOP). No significant deviation from HWE was detected among all sites among each genetic group (Table 2), so that population assignations obtained by STRUCTURE were considered as reliable.

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Low secondary endosymbiont diversity was observed within the MEAM1 B genetic group, with only Hamiltonella and Rickettsia endosymbionts (Fig. 4). Most of the individuals within this genetic group were bi-infected (81%) and the remaining ones were monoinfected by Hamiltonella. Neither Rickettsia monoinfection nor noninfected individuals were detected within this B cluster. On the contrary, high diversity of secondary endosymbionts was detected among MED Q1 genetic group, comprising Wolbachia, Cardinium, Hamiltonella and Rickettsia. Most of the individuals within this genetic group were monoinfected by Hamiltonella (49%), and bi-infected by Cardinium–Hamiltonella (27%) or Hamiltonella–Wolbachia (17%). Only 2 individuals were found noninfected. Two rare infections were found with only 1 individual per symbiotype: Cardinium– Hamiltonella–Wolbachia and Cardinium–Rickettsia. In order to test the influence of the secondary endosymbiont community on the different ecological factors taken into account the sampling (season, host plant, sites), we used a AMOVA. Three different AMOVA were run for each genetic group, according to secondary endosymbiont communities and season, or host plant or sites. None of the AMOVA gave significant structuring according to the ecological factors tested for both genetic groups (data not shown). Most of the variation was distributed within individuals. In parallel pairwise Fst matrices per genetic group were built according to the secondary endosymbiont community, and no significant differences were found between populations bearing different secondary endosymbiont communities on the nuclear data (Table 3). Despite the lack of nuclear data substructuring within the MED Q1 genetic group, a group could be observed with mt data, comprising almost all (but one) individuals bearing the secondary endosymbiont Wolbachia (the aforementioned exception bearing 3 endosymbionts: Wolbachia, Cardinium and Hamiltonella) (data not shown; Figs. 2 and 3).

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Fig. 3 Phylogenetic tree indicating the relationships between the DNA sequences of the mitochondrial COI of Bemisia tabaci for all samples used in this study (see Table 1) and those of a representative sampling of publicly available close sequences. The tree was constructed using MrBayes. Numbers associated with nodes indicate the posterior probability for those nodes.

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Fig. 4 Individual infection status observed in Bemisia tabaci populations. Each column of color corresponds to a specific endosymbiont, red for Hamiltonella, pink for Cardinium, yellow for Wolbachia and blue for Rickettsia. In mixed populations, proportion of MED Q1 individuals is indicated in gray and MEAM1 B in white. Species, sites, host plants, number of individuals tested (defined using COI marker) are indicated at the top of the graphs. Table 3 Pairwise matrices of Fst among Bemisia tabaci species (MED and MEAM1) and partitioned according to secondary endosymbiont communities (Genepop). Genetic group MEAM1 B H Genetic group MED Q1 H HR CH

HR −0.00065 WH

H

HR

0.00183 0.00944 −0.00047

0.00435 0.00173

−0.00997

Note: None of the pairwise Fst were significantly different from each other.

Discussion Evidence of two genetic groups of B. tabaci on crops was detected on the west coast of Senegal: the Mediter C 2014

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ranean Q1 and the Middle East-Asia Minor 1 B. Both genetic groups were well separated on nuclear (Bayesian and PCA analyses on microsatellite data) as well as on mitochondrial data, showing no panmixy between populations, despite sympatry of both groups observed in the field. In Africa, a wide range of subgroups are known within the Africa MEAM1 group, such as the African Silverleaf, Sub-Saharan, J, L or within the Sub-Saharan Africa silverleafing S genetic group (Sseruwagi et al., 2005; Boykin et al., 2007; Mugerwa et al., 2012), whereas in this study all whiteflies tested, successfully amplified but were only part of the MEAM1 B or MED Q1 genetic groups. These two genetic groups are known as invasive worldwide, good competitors and more resistant to insecticides than resident genetic groups or subgroups (Horowitz et al., 2005; Delatte et al., 2009; Crowder et al., 2010; Yuan et al., 2012; Gnankine et al., 2013b). Samplings for this study

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were only done on vegetable crops, and no cotton, cassava nor free insecticides crops or weeds were sampled. The repartition of the genetic groups of B. tabaci might have been triggered by this selective sampling. The dominance of MED Q1 on most of the samples and sites, the highest nuclear and mitochondrial diversity observed, but also its broader secondary endosymbiont community (Hamiltonella, Cardinium, Wolbachia and Rickettsia, Fig. 4), leads to the conclusion that this genetic group might be the predominant resident begomovirus vector group on market gardening crops. Indeed, other studies also showed a large genetic [on mitochondrial (COI) and nuclear sequences (ITS)] and endosymbiotic diversity among MED Q and dominance of the Q1 populations on vegetable crops in several African countries with similar climatic conditions, such as Burkina Faso (Gnankine et al., 2013a), Cameroon or Sudan (Gueguen et al., 2010). On the contrary, the lower preponderance of MEAM1 B and its lower level of diversity on nuclear or mitochondrial DNA or secondary endosymbiont community (bearing only Hamiltonella/Rickettsia) reveal that the genetic group is exotic and obviously a result of a recent invasion in this area. Indeed, worldwide invasive populations of MEAM1 B were most often found bearing only Hamiltonella/Rickettsia as endosymbiont community (Gueguen et al., 2010; Thierry et al., 2011). Up to now, the subgroup Q1, mostly found in Europe and Africa, was shown to harbor 3 bacteria, with a dominance of Hamiltonella and in low frequencies Wolbachia and/or Cardinium (Gnankin´e et al., 2013a). Rickettsia is thus a newly described endosymbiont for this subgroup, albeit at very low frequencies. It may have been acquired horizontally, such as described by Caspi-Fluger and colleagues (Caspi-Fluger et al., 2011; Caspi-Fluger et al., 2012). Concerning possible fitness advantages provided by secondary endosymbionts, frequency of Hamiltonella was very high (close to 100%) in MEAM1 B and MED Q1 groups within all our samples, and similar results were shown in several studies (Gueguen et al., 2010; Chu et al., 2011; Thierry et al., 2011). Up to now no benefits directly linked to this specific bacterium on the biology of B. tabaci were demonstrated. Rickettsia was predominant in MEAM1 B, and at very low frequencies in MED Q1. Interestingly, an increased sensibility to insecticides has been demonstrated for the presence of this bacterium (Kontsedalov et al., 2008; Ghanim & Kontsedalov, 2009). Our study, focused on cultivated plants, is possibly highlighting the advantage of MED Q1, which does not harbor Rickettsia. Benefits linked to Rickettsia, such as conferring fitness advantages (Himler et al., 2011) or thermotolerance (Brumin et al., 2011), were demonstrated, albeit

in the absence of insecticides. On other models, this bacterium had been proven to induce parasitoid resistance and reaches a prevalence of 70% in some populations of the aphid Acyrtosiphon pisum (Oliver et al., 2003), but nothing similar had been observed in any B. tabaci species. In the case of Wolbachia, no dominance of individuals infected by Wolbachia were observed in populations sampled, whereas this bacteria had been shown to give some protection against parasitism and increased fitness on an invasive B. tabaci MED Q population in China (Xue et al., 2012). Despite different secondary endosymbiont communities within MED Q1 populations, no barrier to gene flow is observed on nuclear data between the different individual bearing different endosymbiont associations. On mitochondrial data, at least 2 different groups are matching with different secondary endosymbiont communities (one comprising nearly all the individuals harboring Wolbachia). This matching suggests different maternal origins for those populations, which might be of 2 geographic origins, where the different symbionts could have been acquired independently and recently. As no substructure between those groups on nuclear data can be observed we can hypothesis that neither Cardinium nor Wolbachia act as a gene flow barrier in those populations. As for hybridization, no such signal has been detected between both MED and MEAM1 species found in sympatry (Fst = 0.26* between both species; structuring analysis Supplementary data; Fig. 1 and PCA in Fig. 2). However, putative hybridization between MEAM1 and MED species were detected in North American and Moroccan natural populations, although at very low frequency (McKenzie et al., 2012; Tahiri et al., 2013). Nevertheless, the low frequency of hybrids observed in both studies are confirming their species “nonhybridizing” status (De Barro et al., 2011). A possible involvement of secondary endosymbionts, albeit not demonstrated so far between both groups, could be hypothetized. For instance, Cardinium and/or Arsenophonus were suggested to interact with the nuclear background of their host and possibly manipulate the reproduction between 2 very close B. tabaci species, the indigenous Indian Ocean and invasive MEAM1 B in La R´eunion (Thierry et al., 2011). However, none of those phenotypes was observed in our sampled populations.

Acknowledgment This study was funded by the CIRAD and the “Conseil R´egional de La R´eunion.”  C

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Supporting Information Additional Supporting Information may be found in the online version of this article at the publisher’s web-site: Table S1 AMOVA hierarchical analysis performed with Arlequin on MED Q and MEAM1 B samples. Data sets were partitioned according to secondary endosymbiont communities and sites. Significance tests (1023 permutations) are indicated with an *.