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Prominent intraspecic genetic divergence within Anopheles gambiae sibling species triggered by habitatdiscontinuities across a riverine landscapeB. CAPUTO,* D. NWAKANMA, F. P. CAPUTO,* M. JAWARA, E . C . ORIERO, M. HAMID-ADIAMOH, I . DIA, L . KONATE, V. PETRARCA, J . PINTO,** D. J . CONWAY and A. DELLATORRE**Dipartimento di Sanita Pubblica e Malattie Infettive, Istituto Pasteur-Fondazione Cenci-Bolognetti, Universita Sapienza,Piazzale Aldo Moro 5, 00185, Rome, Italy, Medical Research Council Unit, Fajara, P.O. Box 273, Banjul, Gambia, InstitutPasteur, Dakar, Senegal, University of Dakar, Dakar, Senegal, Dipartimento di Biologia e Biotecnologie, Istituto Pasteur- Fondazione Cenci-Bolognetti, Universita La Sapienza, Piazzale Aldo Moro 5, 00185, Rome, Italy, **Centro de Mal

aria e outrasDoencas Tropicais, Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Rua da Junqueira, 100, 1349-008Lisbon, Portugal

Abstract

The Anopheles gambiae complex of mosquitoes includes malaria vectors at differentstages of speciation, whose study enables a better understanding of how adaptation todivergent environmental conditions leads to evolution of reproductive isolation. Weinvestigated the population genetic structure of closely related sympatric taxa thathave recently been proposed as separate species ( An. coluzzii and An. gambiae ), sam-pled from diverse habitats along the Gambia river in West Africa. We characterizedputatively neutral microsatellite loci as well as chromosomal inversion polymorphismsknown to be associated with ecological adaptation. The results revealed strong ecolog-ically associated population subdivisions within both species. Microsatellite loci onchromosome-3L revealed clear differentiation between coastal and inland populations,

which in An. coluzzii is reinforced by a unusual inversion polymorphism pattern, sup-porting the hypothesis of genetic divergence driven by adaptation to the coastal habi-tat. A strong reduction of gene ow was observed between An. gambiae populationswest and east of an extensively rice-cultivated region apparently colonized exclusivelyby An. coluzzii . Notably, this intraspecic differentiation is higher than that observedbetween the two species and involves also the centromeric region of chromosome-Xwhich has previously been considered a marker of speciation within this complex,possibly suggesting that the two populations may be at an advanced stage of differen-tiation triggered by human-made habitat fragmentation. These results conrm ongoingecological speciation within these most important Afro-tropical malaria vectors andraise new questions on the possible effect of this process in malaria transmission.

Keywords: genetics, landscape, molecular evolution, mosquitoes, parasitology, population

genetics-empirical, speciationReceived 28 April 2014; revision received 9 July 2014; accepted 16 July 2014

Introduction

Ecological speciation occurs when adaptation to diver-gent environments, such as different resources or habi-tats, leads to the evolution of reproductive isolation.

Correspondence: Beniamino Caputo, Fax: 0039/0649694268;E-mail: [email protected] for Discoveries section of ME

2014 John Wiley & Sons Ltd

Molecular Ecology (2014) 23, 45744589 doi: 10.1111/mec.12866

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Specically, divergent selection between environmentscauses the adaptive divergence of populations, whichleads to the evolution of reproductive barriers thatdecrease, and ultimately cease, gene ow (Rundle &Nosil 2005). Supported by a growing number of specicexamples (Shafer et al. 2013; and references herein), eco-

logical speciation is thought to be a primary drivingforce in evolutionary diversication. Human-mademodications of physical landscape may contribute tothis process by altering patterns of population connec-tivity and affecting levels of gene ow among popula-tions (Crispo et al. 2011). Studying related populationsat different stages along a speciation continuum isexpected to contribute to a better understanding of mechanisms of ecological speciation (Nosil et al. 2009;Nadeau et al. 2012; Weetman et al. 2012).

A speciation continuum is clearly evident within the Anopheles gambiae complex the most extensively studiedinsect group, due to the medical relevance of some of itsmembers as vectors of human malaria in the sub-SaharanAfrica. Species within the complex exhibit varying levelsof progress towards ecological speciation: this rangesfrom clearly dened, although morphologically indistin-guishable, bonae species (showing sterility in hybridmales and different larval ecologies and host-preferences,Davidson & Jackson 1962; Davidson 1964; Coluzzi et al.2002), to recently diverged/incipient species and formswithin An. gambiae sensu stricto (s.s.) Gillies the specieswith the largest range of distribution and the highestmalaria vectorial capacity showing varying levels of reproductive isolation and ecological divergence. The

rst evidence of a remarkable genetic heterogeneitywithin this species in West Africa originally came fromcytogenetic studies which led to the description of veco-occurring chromosomal forms characterized by dif-ferent chromosome-2 arrangements and larval ecologies(i.e. FOREST, SAVANNA, MOPTI, BAMAKO and BIS-SAU) (Coluzzi et al. 1985, 2002). Afterwards, moleculardiscontinuities in the IGS and ITS regions of ribosomalDNA led to the identication of two nonpanmictic unitsprovisionally named with a non-Linnean nomenclatureas M- and S-molecular forms (della Torre et al. 2001). Inforested areas, mosquitoes of the M- and S-forms are ho-mokaryotypic on chromosome-2 (i.e. FOREST chromo-somal form), while in dry savannahs they show highfrequencies of chromosome-2 inversion polymorphisms(della Torre et al. 2005; Wondji et al. 2005; Lee et al. 2009).S-form is mainly characterized by arrangements typicalof SAVANNA and BAMAKO chromosomal forms andM-form by arrangements typical of MOPTI and/orSAVANNA and/or BISSAU, depending on its geograph-ical origin. In most of their range of sympatry in WestAfrica, M- and S-forms are characterized by a highdegree of reproductive isolation (della Torre et al. 2005),

although assortative mating may periodically or locally break down (Lee et al. 2013a). However, genomic diver-gence is not uniformly distributed throughout the gen-ome, suggesting that many loci may be independentlysubject to divergent selection (Turner et al. 2005; Neafseyet al. 2010; Reidenbach et al. 2012). The phenotypic conse-

quences of this genetic divergence are not yet fully clear,although it is known that the two forms are not homoge-neously distributed in different types of larval sites andshow different seasonality as a consequence of M-formshigher ability to exploit semi-permanent larval habitatsavailable also in the dry seasons (Lehmann & Diabate2008; Gimonneau et al. 2010, 2012). Based on thesegenetic and bionomical differences, M-form was recentlyraised to formal taxonomic species status as An. coluzzii(Coetzee et al. 2013). Therefore, hereafter, An. coluzziiand An. gambiae will be used to refer to M- and S-form,respectively, and An. gambiae s.s. Gillies to refer to thespecies before the splitting. Although the Plasmodiuminfection rate of wild populations of the two species has been poorly investigated so far (Ndiath et al. 2011; Fryxellet al. 2012; Boissiere et al. 2013), the impact of this recentspeciation process in modulating physiological/behavio-ural traits relevant in malaria transmission and controlhas been highlighted with reference to different levels of susceptibility to Plasmodium infections (White et al. 2011)and to insecticides (Santolamazza et al. 2008; Ndjema

et al. 2009). Finally, further genetic subdivisions have been observed in both species at a macro-geographicalscale: within An. coluzzii between forest and savannah bi-omes in West Africa (Slotman et al. 2006; Lee et al. 2009;

Pinto et al. 2013) and within An. gambiae westward andeastward of the Rift Valley (Lehmann et al. 1999, 2003;Wang-Sattler et al. 2007).

Paracentric chromosomal inversions are known toplay a major role in determining local population sub-structuring within both An. coluzzii and An. gambiae(Coluzzi et al. 1979, 2002), by acting as mechanisms of adaptation to marginal ecological conditions and serv-ing as triggers to speciation through the mechanismdescribed as ecotypication (Coluzzi 1982). The bestexample of this mechanism is the case of the An. gam-biae Gillies BAMAKO chromosomal form in Mali(Coluzzi et al. 1985, 2002; Toure et al. 1998), which ischaracterized by locally selected adaptive karyotypesmaking it t to a peculiar larval habitat (i.e. laterite rockpools) and eventually leading to formation of reproduc-tive barriers isolating it from sympatric SAVANNAchromosomal form populations (Manoukis et al. 2008;Neafsey et al. 2010; Lee et al. 2013b).

We analysed An. coluzzii and An. gambiae populationscollected along the Gambia river, with the aim to assessthe patterns of genetic structure and to determine thedegree of genetic isolation among populations of these


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species across different habitats highly affected byhuman activities in a region where high numbers of An. coluzzii/An. gambiae hybrids have been reported(Caputo et al. 2008). In fact, the study area is situated between the hypothesized core of a putative secondarycontact region in Guinea Bissau and the rest of the spe-

cies range, where hybridization is overall very low andinterspecic differentiation is relatively high (Oliveiraet al. 2008; Caputo et al. 2011; Marsden et al. 2011; Weet-man et al. 2012; Nwakanma et al. 2013). Moreover, pre-vious data on inversion polymorphisms in the region(Bryan et al. 1982) highlighted the existence of two (par-tially) reproductively isolated chromosomally differenti-ated populations of An. gambiae s.s. Gillies (i.e. theBISSAU and SAVANNA chromosomal forms, showingopposite frequencies of 2Rb, 2Rd and 2La inversions,Coluzzi et al. 1985), suggesting that inversion polymor-phisms may have played a role in promoting differenti-ation within this species. We compared the spatialpopulation genetic structure inferred from presumablyneutral nuclear microsatellite markers on chromosome-X and chromosome-3 with that inferred from presum-ably adaptive chromosomal paracentric inversions onchromosome-2. The results obtained highlighted strik-ing ecologically based population subdivisions, furthersupporting the existence of a continuous speciation pro-cess, possibly triggered by human-made habitat frag-mentation, within one of the major Afro-tropicalmalaria vector species.

Materials and methods

Samples and study area

Anopheles gambiae s.s. (Gillies) mosquitoes analysed inthis study were selected from 35 local population sam-ples (Table S1, Supporting information) collected duringthe 2006 rainy season in a 400-km-long transect alongthe Gambia river from the western coastal region of TheGambia (16 450W) to south-eastern Senegal (12 070W),along which four main ecological areas were identied(Caputo et al. 2008): (i) Lower River Area (LRA), furthersubdivided into three subareas: Western Lower RiverArea (LRA-W), South Bank Lower River Area (LRA-S)and North Bank Lower River Area (LRA-N); (ii) CentralRiver Area (CRA); (iii) Upper River Area (URA); and(iv) Eastern Area (EA), further subdivided intothree subareas: Tambacounda (EA-TAM), Wassadou(EA-WAS) and Kedougou (EA-KED). Samples have beenidentied as M-form and S-form by Caputo et al. (2008),hereafter referred to as An. coluzzii and An. gambiae(Coetzee et al. 2013), respectively. Anopheles coluzzii/ An. gambiae putative hybrids reported by Caputo et al.(2008) were not included in the analyses.

Karyotyping

Polytene chromosome preparations were obtained fromall half-gravid females of the Caputo et al. (2008) sam-ple following della Torre (1997) (Table S1, Supportinginformation). Mosquitoes were collected with paper-cupmouth aspirators (Coluzzi & Petrarca 1973), droppedalive into Carnoy xative (three parts pure ethanol:onepart glacial acetic acid) and stored at 20 C. Chromo-some scoring was carried out under a phase-contrastoptical microscope. Paracentric inversion karyotypeswere scored according to the nomenclature and conven-tions of Coluzzi et al. (1979) and Tour e et al. (1998), thatis, standard (uninverted) and inverted arrangementswere considered as alternative alleles of a biallelic locus(where locus = chromosomal region containing aninversion polymorphism, and allele = inversion orienta-tion arrangement), as in the cases of 2Rj and 2La. How-ever, when dealing with overlapping inversions

(standing on the same chromosomal region see Col-uzzi et al. 1979; page 490, for details), we treated themas alternative alleles belonging to the same multi-alleliclocus (named inversion system), whose wild typewas the standard arrangement (indicated by the symbol+, usually followed by the letter referring to the inver-sion system). Moreover, 2Rbc and 2Rcu tandem inver-sions (Coluzzi et al. 1977; Ashburner et al. 1986) wereconsidered as alternative alleles to the inversion sys-tems 2Rb and 2Rd, respectively, as 2Rc inversion(which represents a common arrangement) is contigu-ous and in complete linkage disequilibrium with 2Rband 2Rd inversions. As a consequence, the multi-allelicinversion system 2Rb (locus) included 2R + b , b, bc, bk,arrangements (alleles) and system 2Rd included 2R +d ,d, cu, bk. However, to simplify the Hardy Weinberg(HW) calculations when the inversion system had morethan two alternative inverted arrangements and particu-larly when the frequencies of some of them were low,2R-karyotypes were reorganized into three categories(as in a biallelic system), as in the following examplerelative to inversion system 2Rb in An. coluzzii: (i) stan-dard homokaryotype: 2R + b / + b ; (ii) heterokaryotype:pooling of the karyotypes formed by the standardarrangement and one of the alternative inverted

arrangements (2R + b

/b, + b

/bc); (iii) alternative homo-karyotype: pooling of all the other karyotypes carryingarrangements alternative to the standard (2Rb/b, b/bc, bc/bc).

Microsatellite genotyping

Specimens for microsatellite analysis were selected from14 sampling sites (Fig. 1a, Table S1, Supporting infor-mation), chosen to have a highly representative sample


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for each species from each ecological area across thetransect.

Twenty microsatellite loci (Zheng et al. 1996; Wanget al. 1999; Table S5, Supporting information), 10 on chro-mosome-X and 10 on chromosome-3, were genotyped toavoid potential bias resulting from reduced recombina-

tion or selective pressures acting on chromosome-2 inver-sions. Each locus was amplied using the protocolsdescribed by Donnelly et al. (1999). Fragment analysiswas performed by capillary electrophoresis on an auto-mated sequencer (ABI 3730, Applied Biosystems) atMRC, Banjul, The Gambia. Three to four amplied prod-ucts, with different uorescent labels, were analysed permicroplate well, according to the following groups:Group 1: H242, H128, H249 and H119; Group 2: H55,H577 and H59; Group 3: H758, H93 and 45C; Group 4:H145, H25, ND5B1 and ND6U2; Group 5: H77, ND5C1and H678; Group 6: H7, ND5D1 and ND6U4.

To control for possible variation in allele size scoring between capillary electrophoresis runs, the same posi-tive controls consisting of PCR products of one An. co-luzzi and one An. gambiae specimens from a laboratorycolony were included in all runs. One additional posi-tive control (DNA template from a colony mosquito)and one negative control (no template) were alsoincluded to assess PCR quality. Allele sizes were scoredfrom electropherograms using the software GENEMARKER(SoftGenetics, USA).

Statistical analyses

Microsatellite diversity per locus and per populationwas estimated by computing allele richness (Rs, Mousa-dik & Petit 1996), expected heterozygosity (He, Nei1987) and inbreeding coefcient (F IS , Weir & Cocker-ham 1984) using FSTAT 2.9.3.2 (Goudet 2001). Signi-cance of F IS values was assessed by randomization testsin FSTAT Departure from HW equilibrium for each locusin each population, and linkage disequilibrium (LD) between each pair of loci in each population wasassessed using Fishers exact tests in GENEPOP ON THE WEB(Rousset 2008).

Estimates of FST (Weir & Cockerham 1984) were cal-culated using ARLEQUIN 3.5 (Excofer & Lischer 2010)among samples of each species from different ecologicalareas/subareas. Signicance of the estimates wasassessed using 2000 permutations. Pairwise FST dis-tances were used to build a neighbour-joining dendro-gram using T REE F IT (Kalinowski 2008). We ran 1000 bootstrap pseudo-replicates over loci to test the reliabil-ity of the neighbour-joining dendrogram. Whenevermultiple tests were performed, the nominal signicancelevel (a = 0.05) was adjusted by the sequential Bonfer-roni procedure (Holm 1979).

The Bayesian spatially explicit analysis implementedin TESS 2.3.1 (Francois et al. 2006 and Chen et al. 2007)was applied to identify subgroups within each specieswith a priori knowledge of the geographical origin of each specimen based on the overall set of 20 microsatel-lite loci or chromosomal inversion system. This process

takes into account the spatial dependency of the geneticstructure (i.e. individuals from neighbouring sites aremore likely to be similar than those from more distantones), thus allowing control for the inuence of isola-tion by distance on the clustering patterns. The twoadmixed models available in T ESS, CAR and BYM(Durand et al. 2009) were used in the analysis. The TESSanalysis considered increasing values of Kmax (themaximum number of populations in the data set) from2 to 9, with 10 runs at each Kmax. Each run included100 000 sweeps with a burn-in of 50 000 sweeps; consis-tency of results across runs was visually checked. Themost likely value of K was determined based on thevalue at which the decreasing deviance information cri-terion (DIC) values reached a point of inection and thenumber of distinct clusters stabilized (Chen et al. 2007;Durand et al. 2009). The estimated individual member-ship probabilities of the ten runs of the optimal Kmaxwere averaged using the greedy algorithm in C LUMPP(Jakobsson & Rosenberg 2007) to correct for discrepan-cies between runs. The results of the spatially explicitanalysis conducted in TESS were very similar for the twoadmixture models used. So, we reported results of theBYM model. We considered individuals as reliablyassigned to a cluster when their assignment probability

exceeded 0.8, and when necessary, we considered sam-pled populations as assigned to a cluster when theirmean individual assignment probability exceeded 0.5(Latch et al. 2006).

We also employed the model-based Bayesian methodimplemented in STRUCTURE 2.3.3 (Pritchard et al. 2000) based on overall microsatellite data to identify sub-groups without prior information on An. coluzzii/ An. gambiae distinction or on the geographical locationof sampled individuals. Scenarios with K = 1 7 popula-tions were explored using 100 000 iterations as burn-infollowed by 500 000 iterations for parameter estimation, based on the admixture model and assuming correlatedallele frequencies. Each run was performed 15 times,and results were processed with STRUCTURE HARVESTERversion 0.56.4 (Earl & vonHoldt 2012); the optimal valueof K was selected by comparing the estimated log-prob-ability of the data under each K [l(k)] (Pritchard et al.2000) and by the rate of change in the log-probability of data between successive K -values ( M K -values, Evannoet al. 2005). Admixture between the inferred clusterswas computed as the average ancestry proportion (Q)of each sampled population in each cluster ( K ).



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(a)

(b)

(c)

(d)



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The possible occurrence of a signicant relationship between genetic differentiation (pairwise FST ) and geo-graphical distances separating populations was assessed by Mantel tests. Pairwise overland distances betweensites were estimated using the distance tool available inQUANTUM GIS 2.0.0 (Quantum GIS 2011) and were log-

transformed. As the existence of a signicant pattern of isolation by distance may affect the outcome of clusteranalyses, we attempted to tease apart the effects of geo-graphical distance and population clustering on geneticdiversity by carrying out partial Mantel tests (Legendre& Legendre 1983). To this aim, binary matrices weregenerated by assigning values of 1 to comparisons between samples from the same cluster (as dened bythe clustering analyses above) and of 0 from distinctclusters. Both simple and partial Mantel tests were car-ried out with the program IBDWS 3.23 (Jensen et al. 2005)with 10 000 randomizations. The signicance of the cor-relations was tested by permutation as described inLegendre & Legendre (1983). Inter- and intraclusterpairwise FST values were plotted against geographicdistances (Kms).

Pairwise FST values (Weir & Cockerham 1984) per mi-crosatellite locus were computed using MICROSATELLITEANALYZER (MSA) version 4.05 between species and between different TESS clusters in the intraspecic analy-sis; signicance of the estimates was assessed using1000 permutations.

To compare chromosomal and microsatellite diver-sity, we used a procedure proposed by Hedrick (2005)and implemented in the RECODEDATA program (Meir-

mans 2006; Meirmans & Hedrick 2011) to standardizelevels of differentiation according to heterozygosity forthe two sets of markers (i.e. chromosomal inversionsand microsatellite loci), which show different levels of heterozygosity and evolve following distinct muta-tional models. This software recodes genetic data bymaximizing heterozygosity in the total population,given the observed heterozygosity within subpopu-lations, and derives standardized FST estimates,therefore allowing for direct comparisons between esti-mates obtained from markers with different mutationrates.

Conformity to expectation under neutral evolutionwas tested individually for each of the 20 microsatelliteloci through a model-based test directed towards thedetection of outlier loci. We used the software L OSITAN(Antao et al. 2008) to identify loci showing unusuallyhigh FST values, taking into account their heterozygosity

(Beaumont & Nichols 1996). We ran L OSITAN rst todetermine a candidate subset of selected loci to removethem from the nal computation of neutral FST . Next,we used the stepwise-mutation model and the optionForce mean FST which approximate a desired FST byrunning a bisection algorithm over repeated simula-tions. Condence interval was set to 99.5%.

For chromosomal inversions, following Ayala et al.(2011), we repeated this analysis approximating theexpected distribution of FST conditional upon heterozy-gosity given the reference level of differentiation pro-vided by the microsatellite loci that showed neutralevolution. To that end, we ran L OSITAN to characterizethe joint distribution of FST and He with an average dif-ferentiation equal to that observed across neutral micro-satellite loci ( An. gambiae FST = 0.051; An. coluzzii FST = 0.017). We used the above-described algorithms tocharacterize the joint distribution of FST and He and tocalculate the empirical P-values associated with eachstudied polymorphism.

Results

Chromosomal inversions

Overall, 1306 specimens (937 An. coluzzii and 369 An. gambiae) from 25 sampling sites across the east westtransect along the Gambia river were karyotyped(Tables S1 S3, Supporting information). Fig. 1a showsthe geographical distribution and frequencies of themost common inversion polymorphisms (2Rj, 2Rb,2Rbc, 2Rbk, 2Rd, 2Rcu and 2La; Fig. 1b) found in thetwo species in the eight ecological areas/subareas alongthe transect.

Figure 1c shows the neighbour-joining FST dendro-gram obtained from inversion polymorphism data; twohighly differentiated groups are observed: a group

Fig. 1 Inversion polymorphisms in Anopheles coluzzii and An. gambiae along the Gambia river. (a) Histograms represent frequenciesof alternative chromosome-2 inversion arrangements in 25 sampling sites (dots) grouped in eight ecological areas/subareas (purplecircles): LRA-W = Western Lower River Area; LRA-S = South Bank Lower River Area, LRA-N = North Bank Lower River Area,CRA = Central River Area; URA = Upper River Area, EA-TAM = Tambacounda Eastern Area, EA-WAS = Wassadou Eastern Area,EA-KED = Kedougou Eastern Area. Numbers refer to the 14 samples genotyped by microsatellites (Fig. 2; Table S1, Supporting infor-mation). n = sample sizes. (b) Diagrammatic representation of inversion polymorphisms on right (2R) and left (2L) arms of standard(i.e. uninverted) chromosome-2. Colour codes as in legend. (c) Neighbourjoining dendrogram from a matrix of FST values amongsamples of each species assembled in ecological areas/subareas. (d) Proportion of assignment of each specimen to clusters as inferred by TESS analysis based on chromosomal inversions.



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characterized by high chromosomal complexity includingall eastern An. gambiae samples (URA +EA) and a groupincluding all An. coluzzii and remaining An. gambiaesamples characterized by much lower chromosomalcomplexity (mean FST for An. gambiae eastern samples,URA+EA, vs. others = 0.22 95% CI 0.036). The latter

group is further subdivided into a group including An. gambiae LRA-W+LRA-N samples and An. coluzziiLRA-N ones, and a second group including all remain-ing An. coluzzii samples.

The results of the Bayesian spatially explicit analysisimplemented in TESS conrm the presence of two clus-ters within An. gambiae. The Deviance Information Cri-terion (DIC) decreases gradually from K max = 2, withno clear point of inection. Individual q-matrices stabi-lize at K max = 2, and no clearly dened new clustersappear at higher values of K max. The two An. gambiaeclusters, spatially segregated westward and eastward of CRA, correspond to the following: (i) a western group(LRA; n = 176, green in Fig. 1d) characterized by karyo-types based on inversion systems on chromosomal arm2R, that is 2Rb and 2Rd (1 8 in Table S2, Supportinginformation) and (ii) an eastern group (URA +EA;n = 193; yellow) characterized by the eight karyotypesshared with the previous group and additional 36 kary-otypes based on inversion systems 2Rj, 2Rb, 2Rd (9 44in Table S2, Supporting information) and few otherrarer inversions, showing high frequencies in somesites. Polymorphisms 2Rb and 2Rd are observedthroughout the range of distribution of An. gambiae,although inverted arrangements are signicantly more

frequent in the eastern (2Rb = 0.68; 2Rd = 0.68) thanin the western group (2Rb = 0.34; 2Rd = 0.39) (2Rb:Chi-square test = 82.17, d.f. = 1, P 0.001; 2Rd: Chi-square test = 62.21, d.f. = 1, P 0.001). Moreover, theeastern group is also characterized by the exclusivepresence of: (i) inversion 2Rj (0.32); (ii) 2Rj-associated2Rbk arrangement (0.04), (iii) 2Rcu (0.07), (iv) 2Rbc(0.01) and (v) four new chromosome-2 paracentricinversions, one of which forms a stable polymorphism(namely, 2R63, Pombi et al. 2008). Frequencies of 2Lainversion do not signicantly differ between the east-ern (0.78) and the western (0.72) groups. Inversionsystems 2Rj, 2Rb, 2Rd and 2La are mostly in agreementwith HW equilibrium in every ecological area, and sig-nicant linkage disequilibrium (LD) (Table S4, Support-ing information) is detected only in EA sample, whereall possible associations between arrangements withinthe 2R-arm are found.

On the other hand, An. coluzzii is characterized byfew chromosome-2 karyotypes, based on inversions2Rb, 2Rd and 2La (1 15 in Table S3, Supporting infor-mation). TESS analysis does not highlight a strong spatialpartitioning as observed in An. gambiae, although

populations from LRA-W (red in Fig. 1e) and CRA(blue) show some degree of differentiation from theothers. In fact, when compared with frequenciesobserved in the rest of the study area (Fig. 1a): (i) LRA-W samples show the lowest frequency of 2Rb (0.45;Chi-square test = 6.6, d.f. = 1, P 0.001) and the high-

est of 2Rd (0.43; Chi-square test = 1.5, d.f. = 1,P 0.001), while (ii) CRA samples show the highestfrequency of 2Rb (0.70; Chi-square test = 26.6, d.f. = 1,P 0.001) and lowest of 2Rd (0.13; Chi-squaretest = 1.27, d.f. = 1, P 0.001). Inversion 2Ru is occa-sionally observed and 2Rbc is only found at frequencies

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Microsatellites

Overall 472 specimens (272 An. coluzzii and 200 An. gambiae) from 14 populations along the Gambiariver were genotyped (Table S1, Supporting informa-tion): polymorphism at the 20 microsatellite loci is mod-

erate to high, with mean allele richness ( Rs) varyingfrom 4.12 (AGXND5DI) to 11.73 (AGXND6U4) andexpected heterozygosity ( He) between 0.64 (AG-XND5DI) and 0.94 (AGXND6U4). After Bonferroni cor-rection, 21 signicant departures from HW proportionsare observed out of 280 tests performed, all due to het-erozygote decits. Locus AG3H758 comprises 30% of the signicant tests. Two populations from LRA-Wcomprise 52% of the signicant tests. Five signicantLD tests are observed out of 2660 performed. Subse-quent analyses did not provide different results whenlocus AG3H758 was excluded and therefore the results below are given for the entire set of microsatellite.

When a nonspatial model ( STRUCTURE) is applied tothe overall data without a priori identication of thetwo species, results show the existence of four clusters,largely corresponding to two An. gambiae and two An. coluzzii groups ( K = 4; Fig. 2a): Cluster 1 (green)includes most An. gambiae western specimens (LRA-W+LRA-N; Q = 0.81); Cluster 2 (yellow) includes all An. gambiae (URA+EA; Q = 0.84) and some An. coluzzii(EA; Q = 0.52) specimens from eastward sites; Cluster 3(red) includes most An. coluzzii specimens from coastalarea (LRA-W; Q = 0.76); Cluster 4 (blue) includes most An. coluzzii specimens from inner areas (LRA-

N+CRA+URA; Q = 0.78). The neighbour-joining den-drogram built based on FST values between pairs of populations conrms results of STRUCTURE analysis(Fig. 2b).

Results of spatially explicit Bayesian analysis con-ducted by TESS at the intraspecic level shown in Fig. 2c(i) conrm the strong reduction of gene ow between An. gambiae western and eastern groups alreadyshown based on inversion polymorphisms, (ii) reveal afurther subdivision within the western group (meanDIC values reached a point of inection at K max = 3,i.e. LRA-W, LRA-N and URA +EA) and (iii) highlight adifferentiation between An. coluzzii coastal andinland populations ( K max = 2, LRA-W vs. LRA-N+CRA+URA+EA; higher values of Kmax providealmost identical results).

As in the case of chromosomal inversions, a signi-cant effect of geographical distance in shaping the pat-terns of genetic variation among populations is evidentin both species (Mantel tests: P < 0.01; r = 0.548 and0.482 in An. gambiae and An. coluzzii, respectively).However, when controlling for the effect of populationclustering within An. gambiae, the variation explained

by the regression is not signicant (PMT: r = 0.139),while the effect of the population clustering in shapingthe pattern of genetic variation remains signicant evenwhen controlling for the geographical distances (PMT:r = 0.564; P < 0.01). Both r values of PMT remain signif-icant in the case of An. coluzzii (r = 0.370 when control-

ling for population clustering; r = 0.575 whencontrolling for geographical distances; P < 0.01). In fact, FST values between pairs of An. gambiae populationsfrom the three clusters revealed by TESS are higher thanthose between pairs of populations from the same clus-ter with analogous geographic distances (Fig. S1c, Sup-porting information), suggesting that barriers to geneow may play a role in determining genetic differentia-tion within this species. The same pattern is not soclearly observed in An. coluzzii (Fig. S1d, Supportinginformation) .

FST estimates of microsatellite loci plotted againsttheir respective He values show four loci not mappingwithin the 99.5% condence envelope of FST estimatesexpected under neutrality (Fig. 3a,b): (i) two loci map-ping in the centromeric region of chromosome-X (i.e.AGXND6U2, P < 0.005 and AGXND5D1, P = 0.021)among the three An. gambiae TESS clusters; and (ii) twoloci on chromosomal arm-3L (i.e. AG3H242 andAG3H577) among the three An. gambiae clusters (bothP < 0.005) and between the two An. coluzzii ones (bothP < 0.005). The two X-linked loci show highest FST val-ues when comparing each of the An. gambiae TESS clus-ters west of the CRA (red and green in Fig. 2d) withthe eastern cluster (yellow) (Fig. 3c). The two 3L-linked

loci show highest FST values between An. gambiaecoastal cluster (red) and cospecic populations from therest of the transect (green and yellow) (Fig. 3c), as wellas between the two An. coluzzii TESS clusters (Fig. 3d).Generally, lower FST values are observed between An. gambiae and An. coluzzii than within each species(Fig. 3e), with the exception of AGX678 locus, which isknown to be highly divergent in the two species (Stumpet al. 2005; Wang-Sattler et al. 2007; Oliveira et al. 2008).

Comparison between chromosomal and microsatellitedata

Additional analyses were performed to compare esti-mates of population differentiation obtained by the twodifferent sets of markers (i.e. microsatellite loci andchromosomal inversions). We took into considerationthe two major intraspecic clusters resulting from boththe above-reported chromosomal and microsatelliteanalyses, that is the An. gambiae western and easterngroups and the An. coluzzii coastal and inlandgroups. Values of standardized estimates of populationdifferentiation (Hedrick 2005; Meirmans 2006; Meirmans



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URA EA

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Fig. 2 Microsatellite polymorphisms in Anopheles coluzzii and An. gambiae along the Gambia river. (a) Distribution of clusters inferred by STRUCTURE analysis based on 20 microsatellite loci. Pies represent the average ancestry proportions of each cluster in the 14 num- bered sampling sites: smallest pies = 5 n 10; intermediate pies = 10 < n < 25; largest pies = n 25. (b) Neighbour-joining dendro-gram from a matrix of FST values among samples of each species assembled in ecological areas/subareas. (c) Proportion of assignment of each specimen to clusters as inferred by TESS analysis based on 20 microsatellite loci. Numbers refer to sampling siteswithin each ecological areas/subareas: LRA-W = Western Lower River Area; LRA-N = North Bank Lower River Area; CRA = Cen-tral River Area; URA = Upper River Area; EA-TAM- = Tambacounda Eastern Area; EA-KED = Kedougou Eastern Area.



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C C

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0.35Cluster red vs greenCluster red vs yellowCluster yellow vs green

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0.00 0.20 0.40 0.60 0.80He

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F s t

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3H577

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(a) (b)

Fig. 3 Neutrality tests and pairwise estimates of genetic differentiation based on microsatellite loci. a & b: Single-locus FST estimatesamong TESS clusters (Fig. 2) plotted against expected heterozygosity (Nei 1987) within Anopheles gambiae (a) and An. coluzzii (b). Outlierloci are referred to by their acronyms. Lines represent the 99.5% condence limits under the neutrality hypothesis. c, d & e: FST values of individual microsatellites on chromosome-X (left) and chromosome-3 (right) among: (c) TESS clusters within An. gambiae; (d) TESS clusterswithin An. coluzzii; (e) An. gambiae and An. coluzzii. TESS clusters are dened based on Fig. 2. * signicant tests.



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& Hedrick 2011) for microsatellite and chromosomalinversions, respectively, are as follows: 0.29 and 0.23 between the western and eastern An. gambiae groups,0.19 and 0.16 between the coastal and inland An. co-luzzii ones, and 0.13 and 0.09 between An. coluzzii and An. gambiae along their entire range.

Discussion

The results of our microsatellite genotyping show that An. coluzzii and An. gambiae maintain strong genetic dif-ferentiation at the chromosome-X centromeric regionalong the Gambia river, although this region is situated between the core of the two species putative secondarycontact region in Guinea Bissau and the rest of the spe-cies range, where hybridization is overall very low andinterspecic differentiation is relatively high (Oliveiraet al. 2008; Caputo et al. 2011; Weetman et al. 2012). Thisis fully consistent with previous results from The Gam- bia, as well as from neighbouring far-west populations(Marsden et al. 2011; Nwakanma et al. 2013). A detailedanalysis of interspecies introgression and gene ow is being carried out separately.

Here we focus on the strong population structuringconsistently revealed within both An. coluzzii and An. gambiae by the two sets of markers used, that isputatively neutral, rapidly evolving microsatellite lociand chromosomal inversion polymorphisms, whichinclude relatively large areas of the genome often asso-ciated with ecological adaptation . Strong populationsubstructuring was not an unexpected result for para-

centric chromosomal inversions, which have beenrepeatedly involved in ecological structuring of popula-tions both among species of the An. gambiae complex(Coluzzi et al. 1979, 2002; Ayala & Coluzzi 2005), andwithin An. gambiae s.s. Gillies (Tour e et al. 1998). In par-ticular, one of the best examples of intraspecic struc-turing based on inversion polymorphisms wasdocumented precisely in the Senegambia region, wherethe BISSAU and SAVANNA chromosomal forms wereshown to intergrade from coastal areas inland (Bryanet al. 1982; Petrarca et al. 1983; Coluzzi et al. 1985). Onthe contrary, the pattern of population structuring dis-closed by the microsatellite data presented here wasunexpected. In fact, previous microsatellite studies gen-erally revealed a low population structuring of Afro-tropical malaria vectors, probably due to retention of ancestral polymorphisms, homoplasy and/or molecularsignatures of recent population expansion and geneow (Donnelly et al. 2001; Krzywinski & Besansky 2003;Michel et al. 2005; Ayala et al. 2011). In particular,observations by Ayala et al. (2011) on An. funestus inCameroon showed strong population structuring amonggeographical/ecological zones based on chromosomal

inversions, but weak signals based on microsatellites,suggesting that the population structure depicted bychromosomal arrangements is likely the result of localadaptation, which could lead to propitious conditionsfor incipient speciation, increasing genetic drift betweengeographically isolated populations. Our results sug-

gest that Gambian groups within An. coluzzii and An. gambiae have reached a more advanced stage of genetic divergence, even though the geographical scaleis smaller than that between An. funestus populations inCameroon. Moreover, contrary to Ayala et al. (2011),some of the microsatellites (and not all chromosomalinversions) seem to mark loci under selection in Gam- bian populations.

A clear differentiation mostly based on some 3L-mi-crosatellite loci is observed between coastal (i.e. fromLRA-W) and inland An. coluzzii and An. gambiae popu-lations. Signals of strong genetic discontinuities betweenmangrove strand zone and deciduous forest-savannapopulations were already observed in a microsatelliteanalysis of Ghanaian samples (Yawson et al. 2007). Atodds with the presumably expected neutrality of themicrosatellite markers, signs of selective pressuresexerted by the coastal/inland ecosystems and relatedecotone on the genetic pools of both species areobserved in two microsatellite loci on chromosome-3L.Within An. coluzzii, this discontinuity is reinforced bythe inversion polymorphism pattern of coastal popula-tions (i.e. highest frequencies of 2Rd and lowest of 2Rband 2La inversions) as opposed to the inland ones, rem-iniscent of the BISSAU and SAVANNA chromosomal

forms partitioning (Bryan et al. 1982; Coluzzi et al.1985). This supports the hypothesis of an ecologicallydriven genetic divergence due to adaptation to thepeculiar characteristic of the coastal habitat (e.g. salt/ brackish water habitat and/or competition with theeuryhaline sympatric Anopheles melas sibling species).Noteworthy, this is also in agreement with the moregeneral hypothesis of an ongoing ecological speciationprocess involving niche expansion of salinity-tolerantcoastal populations of An. coluzzii into larval habitats of marginal quality (Cassone et al. 2014).

In addition to the above-mentioned peculiarities of the coastal populations, data reveal an even strongerlevel of genetic discontinuity within An. gambiae. In fact,striking genetic differences, compatible with a strongreduction of gene ow, are observed between westernand eastern An. gambiae populations, that is popula-tions west and east of the central part of the transect(i.e. CRA), apparently exclusively colonized by An. co-luzzii (Caputo et al. 2008). First, An. gambiae westernpopulations are characterized by low chromosomalinversion diversity, while eastern populations displaya very high degree of chromosomal complexity. This is



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based on a higher number of inversion polymorphisms,typical of contiguous populations from areas surround-ing the Fouta-Djalon massif, which incompletely inter-grade with neighbouring SAVANNA populations(Petrarca et al. 1983; Toure et al. 1998; Coluzzi et al.2002; della Torre et al. 2005). Second, a very high

genetic differentiation at the microsatellite level evenhigher than that observed between An. gambiae and An. coluzzii is observed between western and east-ern populations. The role played by loci on centromericregion of chromosome-X in this differentiation possiblysuggests that the two An. gambiae populations are at anadvanced stage of differentiation. Notably, evidencefrom other insect groups (e.g. Garrigan et al. 2012; Mar-tin et al. 2013) shows that during speciation, sex chro-mosomes display a more advanced stage of xationthan autosomes. Moreover, the hypothesis of somecommon X-linked genes modulating reproductive isola-tion being widely shared among An. gambiae subtaxawas also proposed for An. gambiae BAMAKO andSAVANNA chromosomal forms in Mali (Lee et al.2013b).

The observed lack of gene ow between the westernand eastern An. gambiae groups could be ascribed tothe existence of a vast ecotone, represented by theextensive rice-cultivated area at the centre of the tran-sect, where only An. coluzzii has been reported so far,probably due to its more effective exploitation of rice-associated breeding sites (Caputo et al. 2008; Diabateet al. 2008; Gimonneau et al. 2012). Interestingly, theinversion polymorphisms characterizing An. coluzzii

populations in rice-cultivated areas (i.e. high frequen-cies of 2Rb inversion) are different from those of An. coluzzii found in ecologically similar areas in theinner delta of the upper Niger river (Tour e et al. 1994,1998) or in other inundated areas of neighbouring WestAfrican regions (e.g. Vall ee du Kou, Burkina Faso;Robert et al. 1991). The latter populations are character-ized by high frequencies of 2Rbc an alternativearrangement of 2Rb inversion system, typical of MOPTIchromosomal form which has been hypothesized as amajor genetic factor allowing the adaptation of MOPTIto rice-cultivated habitats (Coluzzi et al. 1985; Toureet al. 1998). Results from the Gambia river suggest thatthe adaptation to this habitat is instead an An. coluzziifeature independent from its inversion pattern, with2Rbc representing a local adaptation of populationsfrom the basins of Niger and Volta rivers. This isstrengthened by the observation that An. gambiae popu-lations from areas contiguous to rice elds along theGambia river show an inversion pattern similar to thatof rice-associated An. coluzzii populations, although An. gambiae is not apparently able to colonize the rice-eld habitat. Reidenbach et al. (2012) proposed that An.

coluzzii may have originated in association with domes-tication of rice ( Oryza glaberrima) in Africa. The presentresults are in agreement with this hypothesis and sug-gest that the observed different chromosomal patternsof An. coluzzii populations from the Gambia river vs.the Niger river may reect the two-stage rice domesti-

cation of African rice ( Oryza glaberrima) in west Africa,that is rst in the inland delta oodplains of the upperNiger River in Mali about 20003000 years ago, andlater in the far-west region (Li et al. 2011).

Overall, our results show a remarkable populationstructuring at a mesogeographic scale in each of thespecies, although at different levels. A rst level islikely to be associated to ecological adaptation of bothspecies to different kinds of larval habitat along theGambia river, whose basin widens westwards. In fact,the larval habitat changes from water-retaining alluvialdeposits characterized by marshy vegetation and man-grove woods in the coast, to inundated rice cultivationsand rain-dependent freshwater pools in free-drainingsoil inland (Bgh et al. 2003; Caputo et al. 2008). A sec-ond level of structuring could be related to habitat seg-regation triggered by relatively recent human-madeenvironmental changes (e.g. the introduction of exten-sive rice cultivations) which are possibly leading to fur-ther subdivision within An. gambiae. This may representan example of how human alterations of the physicallandscape can affect gene ow by inuencing thedegree of contact between populations, eventually lead-ing to new species formation in a short evolutionarytime frame (Crispo et al. 2011). It would be interesting

to further investigate whether An. gambiae was initiallycontinuously distributed along the Gambia river andlater diverged due to the introduction of rice cultiva-tions, or whether it only recently colonized the wes-tern/coastal area, previously exclusively occupied by An. coluzzii, as suggested by Caputo et al. (2011) andWeetman et al. (2012).

Although the results here presented refer to popula-tions along an ecological transect strongly affected bythe presence of the Gambia river and related intensehuman activities (Wood 2013), the observed substruc-turing of An. gambiae in two units seems to extendsouthwards. In fact, preliminary results from a similartransect conducted in Guinea Bissau suggest an analo-gous west east genetic partitioning within An. gambiae(Pinto et al., unpublished results). It is relevant toremind here that the far-west region is proposed to bea secondary contact zone between An. gambiae and An. coluzzii (Caputo et al. 2011; Weetman et al. 2012). Itmay be hypothesized that the greater interspecichybridization observed in the study area compared tothe rest of the species sympatric range may play a rolein promoting the subdivisions highlighted within



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An. gambiae. This hypothesis seems to be reinforced byevidence showing that gene ow in the far-west mayoccur asymmetrically from An. coluzzii to An. gambiae(Marsden et al. 2011; Nwakanma et al. 2013). Thus,introgression of An. coluzzii genetic material into thegenome of westerly An. gambiae populations may have

contributed to increase divergence from the easterlyones allowing a better adaptation to the ecology of thewesternmost/coastal habitat.

Finally, our data open a new area of investigation toevaluate the following: (i) the geographical extension of substructuring within An. gambiae, studying the puta-tive ecotone represented by rice cultivation in The Gam- bia, to conrm the hypothesis of a role of human-driven environmental changes in promoting geneticdivergence; (ii) the role of ecological adaptation in shap-ing the divergence of the two An. gambiae units, withparticular reference to the role of paracentric inversions(e.g. exclusive presence of 2Rj in the eastern unit) andthe genes they contain; (iii) the existence and signi-cance of islands of divergence on chromosome-X cen-tromeric region between the two An. gambiae units;(iv) the role of interspecic hybridization and asymmet-ric introgression occurring in the far-west region aspossible triggers of intraspecic divergence and possibly speciation. Last but not least, from the malariologi-cal perspective, further studies are needed to assess thepossible relevance of the substructuring observedwithin An. gambiae in malaria epidemiology (e.g. differ-ential susceptibility of the two units to Plasmodiuminfections and/or different host-preferences), as well as

for vector control activities (e.g. differential resistance toinsecticides).

Acknowledgements

This piece of work originates from the seeds of inspiration thatMario Coluzzi planted in each of us. We are grateful to Emi-liano Mancini, David Weetman and the two anonymousreviewers for comments and suggestions to improve the manu-script. This work was supported by UK Medical ResearchCouncil (MRC) funding for the Malaria Research Programmeof the MRC Gambia Unit, MIUR-FIRB Futuro in Ricerca 2010Grant to BC (Grant No RBFR106NTE), and by Ricerca Scienti-ca 2012 Grant by Universit a di Roma SAPIENZA to AdT.

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B.C., D.C., J.P. and A.d.T. designed the study; D.N.,M.J., E.C.O., M.H.A., I.D. and L.K. contributed to eldwork and molecular genotyping; B.C. and V.P. per-formed cytogenetic analysis; B.C. and F.P.C. analyseddata; B.C., F.P.C. and A.d.T. wrote the rst draft of themanuscript; all authors contributed to the nal versionof the manuscript.

Data accessibility

Sampling locations, inversion polymorphism data andmicrosatellite genotypes: Dryad doi: 10.5061/dryad.601fk.

Supporting information

Additional supporting information may be found in the online ver-sion of this article.

Fig. S1 Intra-specic pairwise F ST values plotted against geo-graphic distances.

Fig. S2 Neutrality tests based on inversion polymorphisms.

Table S1 Anopheles coluzzii and An. gambiae samples along theGambia river.

Table S2 Anopheles coluzzii 2R-karyotypes.

Table S3 Anopheles gambiae 2R-karyotypes.

Table S4 Fishers exact tests of Linkage Disequilibrium.

Table S5 Microsatellite loci genotyped.



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