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Mito-nuclear discordance with evidence of sharedancestral polymorphism and selection in cactophilicspecies of Drosophila

FERNANDO F. FRANCO1*, TA�IS C. LAVAGNINI2, FABIO M. SENE3,4 andMAURA H. MANFRIN3,4

1Depto. Biologia, Centro de Ciencias Humanas e Biol�ogicas, Universidade Federal de S~ao Carlos,Sorocaba, Brazil2Programa de P�os-graduac�~ao em Biologia Comparada, Faculdade de Filosofia, Ciencias e Letras deRibeir~ao Preto, Universidade de S~ao Paulo, Ribeir~ao Preto, Brazil3Departamento de Biologia – Faculdade de Filosofia, Ciencias e Letras de Ribeir~ao Preto,Universidade de S~ao Paulo, Ribeir~ao Preto, Brazil4P�os-Graduac�~ao, Depto. Gen�etica – Faculdade de Medicina de Ribeir~ao Preto, Universidade de S~aoPaulo, Ribeir~ao Preto, Brazil

Received 27 January 2015; revised 23 March 2015; accepted for publication 23 March 2015

The Drosophila serido haplogroup is a monophyletic group composed of the following four cryptic and cactophilicspecies that are endemic to eastern Brazil: D. borborema, D. gouveai, D. seriema and D. serido. Here, weinvestigate the mito-nuclear discordance in these species found among the cytochrome c oxidase subunit I (COI)mitochondrial gene, the autosomal alpha-Esterase-5 (a-Est5) and the X-linked period gene (per). Our analysisindicates that shared polymorphisms in these three molecular markers may be explained by the maintenance ofancestral polymorphisms rather than introgressive hybridization. The primary structures of COI, per and a-Est5genes evolve primarily under purifying selection, but we detected some sites that evolved under positive selectionin a-Est5. Considering the high variability of cacti species in eastern Brazil and the role attributed to Drosophilaesterases in digestion metabolism and/or the detoxification of several compounds found in cactus tissues, weconjecture about the role of natural selection triggered by host shifts as an important factor in the intraspecificdiversification of the D. serido haplogroup. © 2015 The Linnean Society of London, Biological Journal of theLinnean Society, 2015, 000, 000–000.

ADDITIONAL KEYWORDS: COI – alpha-Esterase-5 – introgression – period – positive selection – sharedpolymorphism.

INTRODUCTION

The study of genealogical relationships of genes inclosely related species addresses the well known‘genes trees vs. species trees’ problem (Maddison,1997). The commonly described causes of such in-congruences include the maintenance of ancestralpolymorphism, interspecific gene flow, and naturalselection (Machado & Hey, 2003). These eventsmay be greatly variable across animal genomes,generating conflicting genealogical patterns such as

the so-called mito-nuclear discordance (Funk &Omland, 2003; Toews & Brelsford, 2012; Teskeet al., 2014).

Theoretical and statistical frameworks have beenused to differentiate the non-mutually exclusive pos-sibilities for explaining a mito-nuclear discordance.However, although the detection of signatures of nat-ural selection at the molecular level may be easilyaccessed through a series of selection tests currentlyavailable (reviewed in Nielsen, 2005), it is particu-larly difficult to distinguish between introgressionand incomplete lineage sorting to explain the sharedpolymorphism in closely related species (Durand*Corresponding author. E-mail: [email protected]

1© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, ��, ��–��

Biological Journal of the Linnean Society, 2015, ��, ��–��. With 2 figures.

et al., 2011; Teske et al., 2014). This difficulty occurssimply because although these species often sharegenetic variation for extensive periods, they fre-quently present an incomplete reproductive isolationallowing introgressive hybridization (Machado &Hey, 2003). Biogeographic information may be usefulto solve this issue because incomplete lineage sortingis not expected to leave any predictable geographicalpattern, whereas one of the signatures of introgres-sive hybridization is the identification of genealogicalincongruence near secondary contact zones (Funk &Omland, 2003; Toews & Brelsford, 2012). However,when there is a broad overlap in the geographicaldistribution of a species, detecting signatures ofintrogression may be challenging, particularly in situ-ations of low genetic divergence.

Genealogical disagreements between nuclear(nuDNA) and mitochondrial (mtDNA) sequenceswere previously observed in the monophyletic SouthAmerican cactophilic species Drosophila seridohaplogroup, which encompass D. borborema Vilela &Sene, D. gouveai Tidon-Sklorz & Sene, D. seridoVilela & Sene and D. seriema Tidon-Sklorz & Sene(D. buzzatii cluster; D. repleta group) (Manfrin &Sene, 2006; Kokudai, Sene & Manfrin, 2011). Theseare closely related cryptic species that can be identi-fied by male external genital morphology (Silva &Sene, 1991; Manfrin & Sene, 2006), which uses cactihost as an obligatory breeding site (Pereira, Vilela &Sene, 1983; Manfrin & Sene, 2006). There are fewecological data available about the specificity of cactiuse for D. serido haplogroup species and most of ourknowledge is based on punctual description of flyemergences from rooted cactus tissues (e.g. Pereiraet al., 1983; Ruiz et al., 2000) or logical conclusionsbased on samples collected in places with only asingle cacti species. This is the case, for example, ofthe D. gouveai populations of Central Brazil thatoccur on rock fields where only Pilosocereus machrisiigrows (Moraes et al. 2009). Nevertheless, the currentdistribution of the D. serido haplogroup includes sev-eral sympatric zones within the semi-arid BrazilianCaatinga biome (Manfrin & Sene, 2006; SupportingInformation, Fig. S1), an open vegetation area with ahigh amount of and rich species diversity of cacti(Taylor & Zappi, 2004), therefore supplying a moreheterogeneous environment for cactophilic flies toexplore.

Ecological and molecular data indicate that theexploitation of a new cacti host is an important com-ponent in the diversification of the cactophilic speciesof Drosophila, particularly considering the metabolicgenes at both coding sequences and transcriptionalchanges (Matzkin et al., 2006; Piccinali et al., 2007;Bono et al., 2008; Matzkin, 2012, 2014; Soto et al.,2014). The variability of cacti species in terms

of nutritional composition, alcohols, esters, andalkaloids is supposedly the environmental pressuredriving these changes (Piccinali et al., 2007; Matz-kin, 2014; Soto et al., 2014). In fact, studies of molec-ular evolution with the alpha-Esterase-5 (a-Est5)gene suggest that it may be evolving under direc-tional selection in allopatric populations of D. buzz-atii, which exploits different hosts, suggesting thatthis gene may play an important role in the adapta-tion process of the cactophilic species of Drosophilain South America (Piccinali et al., 2007).

Considering this information, we evaluated themolecular variation in the sequence of the a-Est5gene in different populations of the four species ofthe D. serido haplogroup. In addition, we evaluatedthe variation in the CLOCK/CYCLE heterodimerinhibition domain inhibitory domain (CCID) of theperiod gene (per), which is hypothesised to haveevolved under purifying selection (Franco et al.,2010) and thus accumulates synonymous substitu-tion at a rate that is often equated with the rate ofneutral nucleotide substitution (Miyataka, Yasunaga& Nishida, 1980). To investigate the mito-nucleardiscordance, data from nuclear genes were comparedwith previous data provided by the cytochrome c oxi-dase subunit I (COI) mtDNA gene (Manfrin, de Brito& Sene, 2001; de Brito, Manfrin & Sene, 2002;Franco & Manfrin, 2013).

We worked under the following predictions: (1) con-sidering the coalescent theory and the eventual neu-trality of molecular variation of the three markers,we would expect a smaller amount of shared polymor-phisms in mtDNA than nuDNA; and (2) alterna-tively, higher amounts of shared polymorphism inmtDNA than nuDNA could be related to introgres-sion of mtDNA, restricting the acquisition of recipro-cal monophyletic, or maintenance of ancestralpolymorphism in mtDNA coupled with selectiveforces decreasing the shared polymorphism in thenuclear markers. Based on these predictions, we com-pared the topologies and the genetic variation indicesfrom each of the molecular markers. We also ana-lyzed interspecific gene flow using the isolation withmigration model (IM) (Hey & Nielsen, 2004; Hey,2010) and performed tests for selection using the sitemodels approach (Nielsen & Yang, 1998; Yang, 2000)and MK test (McDonald & Kreitman, 1991). Our dataallowed us to conclude that both the maintenance ofancestral polymorphism in mtDNA and natural selec-tion in nuclear sequences are responsible for themito-nuclear discordance found between the threemolecular markers. The selection in the a-Est5 geneis discussed according to the hypothesis that thisgene is associated with the diversification process ofcactophilic species of Drosophila, as previously pro-posed (Piccinali et al., 2007).

© 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, ��, ��–��

2 F. F. FRANCO ET AL.

MATERIAL AND METHODS

SAMPLES

Our sample design included the analysis of 136sequences of X-linked per gene and 113 sequences ofautosomal a-Est5 gene from individual flies of theD. serido haplogroup from 21 locations (Table 1,Fig. 1). To compare the genetic diversity withmtDNA, we used the 165 COI sequences availablefrom the same geographical locations (Table 1).

ISOLATION OF PERIOD AND ALPHA-ESTERASE-5 GENE

FRAGMENTS

The genomic DNA of adult male flies was extractedusing a Wizard Genomic DNA Purification kit

(Promega, Madison, WI, USA). We amplified fragmentsof per using the primers and conditions described byFranco et al. (2010), and for a-Est5, we followed theconditions described by Santos et al. (2009). The ampli-fication products were visualised in 1% agarose gels.For DNA purification, the polymerase chain reaction(PCR) products were treated using an ExoSap-It kit(GE Healthcare, Little Chalfont, Buckinghamshire,UK). A DNA template reaction for sequencing was pre-pared according to the BigDye Terminator CycleSequencing Ready Reaction kit manual (Perkin-Elmer,Foster City, CA, USA) using the same primers andtemperatures for amplification. Automatic DNAsequencing was performed using an ABI Prism 377sequencer (Applied Biosystems, Foster City, CA, USA).

Table 1. Samples of species used in this study for period (per), alpha-Esterase-5 (a-Est5) and cytochrome c oxidase

subunit I (COI) genes

Species and

locations (LC) GC N per per Accessions

N

a-Est5a-Est5accessions COI COI accessions

D. serido

Morro do Chap�eu,

BA (N39)

11.60°S.41.20°W

1 FJ267340 – – 1 JN124572

Mucuge, MG

(N45)

13.00°S.41.40°W

1 FJ267339 1 KM885078 5 JN124588–JN124592

Milagres, BA

(1431)

11.20°S.39.90°W

3 FJ267328–FJ267332 3 KM885070–KM885072

1 *

Arraial do Cabo,

RJ (N20)

23.00°S.42.00°W

5 FJ267333–FJ267337 4 KM885074–KM885077

8 KM972557–KM972564

Bertioga, SP

(H49)

23.90°S.46.10°W

1 FJ267338 1 KM885073 1 *

S~ao Sebasti~ao, SP

(N17)

23.82°S.45.42°W

– – – – 1 KM972565

D. gouveai

Petrolina, PB

(N36)

09.10°S.40.60°W

5 FJ267356–FJ267360 5 KM885092–KM885095;

KM885100

9 JN124690–JN124698

Juazeiro, BA

(N47)

09.50°S.40.50°W

4 FJ267361–FJ267364 4 KM885079–KM885081;

KM885099

5 JN124699–JN124703

Xique-Xique, BA

(N44)

10.90°S.42.54°W

4 KM888244–KM888247 3 KM885096–KM885098

10 JN124715–JN124724

Ibotirama, BA

(J78)

12.10°S.43.30°W

5 FJ267341–FJ267345 4 KM885088–KM885091

9 JN124676–JN124684

Cristalina, GO

(J75)

16.70°S.47.70°W

5 FJ267346–FJ267350 2 KM885086;

KM885087

5 JN124685–JN124689

Altin�opolis, SP

(H6)

21.10°S.47.60°W

1 FJ267355 – – 9 †

Analandia, SP

(J67)

22.10°S.47.70°W

4 FJ267351–FJ267354 4 KM885082–KM885085

0 –


MITO-NUCLEAR DISCORDANCE IN DROSOPHILA 3

http://www.ncbi.nlm.nih.gov/nuccore/FJ267340

http://www.ncbi.nlm.nih.gov/nuccore/JN124572


http://www.ncbi.nlm.nih.gov/nuccore/KM885078





























Table 1. Continued

Species and

locations (LC) GC N per per Accessions

N

a-Est5a-Est5accessions COI COI accessions

D. seriema

Morro do Chap�eu,

BA (N39)

11.60°S.41.20°W

5 FJ267381–FJ267382;KM888290–KM888292

5 KM885041–KM885043;

KM885052;

KM885053

8 JN124786–JN124792;*

Cach. Ferro

Doido, BA

(N42)

11.63°S.41.00°W

9 KM888300–KM888308 6 KM885064–KM885069

7 JN124793–JN124799

10 km S de

Morro do

Chap�eu, BA

(N40)

11.65°S.41.29°W

2 KM888298–KM888299 2 KM885054;

KM885063

2 JN124820–JN124821

Mucuge, MG

(N45)

13.00°S.41.40°W

10 FJ267383–FJ267387;KM888293–KM888297

8 KM885037;

KM885044–KM885051

9 JN124800–JN124807;*

Gr~ao Mogol, MG

(N48/N49)

16.60°S.42.90°W

6 KM888315–KM888320 3 KM885038–KM885040;

KM885055;

KM885056

6 JN124808–JN124812;*

Serra do Cip�o,

MG (N57)

19.29°S.43.60°W

7 FJ267388; KM888309–KM888314

6 KM885057–KM885062

8 JN124813–JN124819;*

D. borborema

Petrolina, PB

(N36)

09.10°S.40.60°W

1 KM888257 1 KM885107 1 JN124769

Milagres, BA

(J92)

11.20°S.39.90°W

9 FJ267365–FJ267369;KM888248–KM888251

7 KM885108–KM885114

11 JN124725–JN124733;*

Morro da

Barrinha, BA

(N37)

09.90°S.40.30°W

10 FJ267370–FJ267374;KM888252–KM888256

9 KM885115–KM885123

10 JN124734–JN124743

10 km S de

Morro do

Chap�eu, BA

(N40)

11.65°S.41.29°W

1 KM888258 1 KM885124 1 JN124770

Andara�ı, BA

(N46)

12.86°S.41.31°W

4 KM888259–KM888262 4 KM885125–KM885128

5 JN124744–JN124748

Juazeiro, BA

(N47)

09.50°S.40.50°W

10 FJ267375–FJ267376;KM888263–KM888270

7 KM885129–KM885135

10 JN124749–JN124758

Pocinhos, PB

(N68)

07.17°S.36.05°W

4 KM888276–KM888279 3 KM885138;

KM885148;

KM885149

4 JN124771–JN124774

Junco do Serido,

PB (N70)

07.00°S.36.71°W

10 KM888280–KM888289 9 KM885139–KM885147

10 JN124775–JN124784

Gr~ao Mogol, MG

(N48)

16.60°S.42.90°W

9 FJ267377–FJ267380;KM888271–KM888275

8 KM885101–KM885101–6;

KM885136;

KM885137

10 JN124759–JN124768

LC, location code; GC, geographic coordinates; N, number of individuals.

*Data from Manfrin et al. (2001);

†Data from de Brito et al. (2002).












































DATA ANALYSIS

The forward and reverse sequences of each taxonwere compared, corrected and edited using BioEdit(Hall, 1999). The sequences were aligned using theClustalW program v. 1.8 (Thompson, Higgins &Gibson, 1994). Standard indices of nucleotide diver-sity (p), the number of polymorphic sites (S), haplo-typic diversity (Hd), and the number of distincthaplotypes (H) were computed using DNAsp 4.20(Rozas et al., 2003). The jModelTest version 3.7(Darriba et al., 2012) was used to determine the bestamong 88 models of nucleotide evolution using theAkaike information criterion (AIC), Bayesian infor-mation criterion (BIC) and Decision Theory (DT).The AIC, BIC and DT agree in the selection ofTVMef + I + G and HKY + I + G (Hasegawa, Kishino& Yano, 1985) as the best models for a-Est5 and per,respectively. For COI we assumed the GTR + I + Gmodel, as previously estimated to explain nucleotide

evolution of this gene in the D. serido haplogroup(Franco & Manfrin, 2013).

We used statistical parsimony (Templeton, Crandall& Sing, 1992) to generate haplotype networks usingthe program TCS v.1.21 (Clement, Posada & Craldall,2000). The degree of interspecific variation was esti-mated using analyses of molecular variance (AMOVA;Excoffier, Smouse & Quattro, 1992), with each speciesconsidered a reproductive group. AMOVA was alsoused to estimate population structure in each species.AMOVA was performed using Arlequin 3.0 (Excoffier,Laval & Schneider, 2005).

The IM model (Hey & Nielsen, 2004) suitable toanalyze more than two populations (Hey, 2010), wasperformed in IMa2. The three molecular markersused are not linked following the IMa2 assumption.Furthermore, we perform the PHI test (Bruen, Phi-lippe & Bryant, 2006) to detect recombination eventsin our molecular markers using SplitsTree4 v.4.13.1

Figure 1. Topographic map showing the Drosophila serido haplogroup locations sampled for this study. The location

codes are listed in Table 1.



(Huson & Bryant, 2006). For IMa2 analysis each spe-cies was considered a group, and their phylogeneticrelationships were based on the descriptionsby Franco et al. (2010) and Oliveira et al. (2011):D. serido, [(D. gouveai, (D. seriema, D. borborema)].The geometric mean of the population mutation rate(h = 4Nu) of the independent loci was used to esti-mate priors for population size and migration rateparameters, as suggested in the IMa2 manual. Weperformed learning runs with heating schemes forthe Metropolis coupled Markov Chain until parame-ters were convergent. The final analysis was per-formed ten times with different seed numbers toassess repeatability and refute pseudo-convergence.The Markov Chain had 105 steps for the burn-in and106 steps for the data collection, with 10 Metropoliscoupled Markov Chains. In this analysis, we assumeda HKY substitution model (Hasegawa et al., 1985) forall loci. We used the ‘-p7’ flag of IMa2 to estimate theposterior distribution for the number of migrationevents (M = m/l) for each locus. Non-zero estimatesfor migration events were considered to support geneflow.

Because we are using protein coding genes, weperformed selection tests from different approaches.First, we compared the relative number of synony-mous and non-synonymous substitutions within andbetween species for each gene with the MK test.Under neutrality, the ratio of non-synonymous andsynonymous polymorphisms should be similar withinspecies and between species (McDonald & Kreitman,1991). The significance for departures of neutralexpectations was estimated using the G-test.

We also estimated x ratios, which is a measure ofnatural selection acting on the protein to perform asite-specific analysis of selection. Briefly, statisticallysignificant values of x < 1, = 1 and > 1 signify puri-fying selection, neutral evolution and positive selec-tion, respectively. This tests were carried out usingcodeml software in PAML v. 4.7 (Yang, 2007) follow-ing a site models approach, which allows the x ratioto vary among sites (Nielsen & Yang, 1998; Yang,2000). To perform selection analysis, the non-codingregions were excluded from the sequences. A rootedtree for each gene in each species was generatedusing MrBayes software version 3.2.2 (Ronquistet al., 2012). We assumed HKY + I + G andGTR + I + G for per and COI, respectively. Fora-Est5, in the absence of TVMef + I + G in MrBayeswe also assumed the model GTR + I + G, as thismodel was the fourth best model according to jModel-Test analysis to explain a-Est5 molecular evolutionand the first of those available in MrBayes. TheMCMC runs during 107 generations, starting with arandom tree and a burn-in fraction of 25% of eachrun was discarded. After the analysis, trees were

exported to a Newick format using FigTree softwareversion 1.4 (http://tree.bio.ed.ac.uk/software/figtree/).Sequences from D. buzzatii (DQ204660.1, FJ267311.1,KF632603.1) and D. koepferae (DQ204680, FJ267318,KP404433) were used as outgroup.

Six models were tested in the codeml software asfollows: (1) M0 (one ratio) estimates a general x forthe data set; (2) M1a (nearly neutral) allows twocategories of codon sites, x0 < 1 and x1 = 1, withproportions p0 and p1 (1 � p0); (3) M2 (selection)allows a third category compared with the M1amodel and x2 > 1, with a proportion of p2(1 � p0 � p1); (4) M3 (discrete) classifies codon sitesin k discrete classes, x0, x1 and x2, with proportionsp0, p1 and p2 (1 � p0 � p1); (5) M7 (beta) specifies aneutral model in which x follows a beta distributionwith estimated parameters p and q of the beta distri-bution; and (6) M8 (beta, x), which is similar to M7,allows a third category, xS > 1 (Yang, 2007).

A likelihood ratio test (LRT) was performed usingthe formula 2Dl = l1 � l0 (where l1 is the likelihood ofmodel 1, l0 is the likelihood of model 0 (null hypothe-sis) and 2Dl is the difference between the model likeli-hoods being compared), among the neutral (M0, M1aand M7) and selection (M3, M2a and M8) models, andthe results were compared using a chi-squared distri-bution in which the degrees of freedom (d.f.) were thedifferences among the estimated parameters betweenthe models being compared. Significant LRT for M0vs. M3 tests variability in selective pressure amongsites, but should not be considered as a reliable testfor positive selection (Yang, 2006), for this it is neces-sary to obtain a significant LRT between M1a vs.M2a and M7 vs. M8 models. As we detected siteslikely under positive selection, the Na€ıve EmpiricalBayes (NEB) test (Nielsen & Yang, 1998; Yang, 2000)was performed assuming the M3 model to indicatewhich codons present significant statistical signal ofpositive selection. When such codons were detected, agraphical representation was generated from the rstfile (M3 model) to visualise the posterior probabilitiesin each site class.

We estimated the effective number of codons (Nc)for characterizing codon usage bias, following themethodology (new Nc) of Sun et al. (2012). The Nc

ranges from 20 (extreme bias) to 61 (no bias). Tocalculate Nc we use the software DAMBE 5.5.9 (Xia,2013), assuming standard genetic code for the nuclearloci and invertebrate mtDNA genetic code for COI.

RESULTS

In total, 363 bp of exon 5 of period from 136 individu-als were analysed for the D. serido haplogroupspecies, including 11 Drosophila serido, 24 D. gouveai,



http://tree.bio.ed.ac.uk/software/figtree/

http://www.ncbi.nlm.nih.gov/nuccore/DQ204660.1

http://www.ncbi.nlm.nih.gov/nuccore/FJ267311.1

http://www.ncbi.nlm.nih.gov/nuccore/KF632603.1

http://www.ncbi.nlm.nih.gov/nuccore/DQ204680


http://www.ncbi.nlm.nih.gov/nuccore/KP404433

39 D. seriema and 62 D. borborema (Table 1). Thesequences contain the conserved period regions C4and C5 interspaced by non-conserved regions N3 andN4 within the CCID domain (Franco et al., 2010). Intotal, 55 per haplotypes were obtained with 10, 10, 13and 19 haplotypes exclusively from D. serido, D. gou-veai, D. seriema and D. borborema, respectively. OnlyD. seriema and D. borborema shared haplotypes

(Fig. 2A). For the esterase gene, 745 bp of exon 4,exon 5 and an intron between them were sequencedfrom 113 individuals of the D. serido haplogroupspecies, including nine Drosophila serido, 22D. gouveai, 33 D. seriema and 49 D. borborema(Table 1). In total, 35 haplotypes were obtainedwith 4, 6, 14 and 10 haplotypes exclusively fromD. serido, D. gouveai, D. seriema and D. borborema,

A

C

B

Figure 2. Statistical parsimony network showing genealogical relationships among haplotypes of the species from the

Drosophila serido haplogroup based on the period gene (A), alpha-Esterase-5 gene (B) and cytochrome c oxidase subunit

I (C). The exclusive haplotypes are represented by colours according to the legend, and the shared haplotypes are repre-

sented in white, with small colour circles inside to identify the species that share the haplotype. The size of both the

numbers and the circles is proportional to the haplotype frequency. Each line corresponds to one mutational step, and

the small circles represent missing haplotypes. Table S1 shows the distribution of haplotypes among the populations

sampled.



respectively. Only D. seriema and D. gouveai sharedhaplotypes (Fig. 2B). We used the COI subset pub-lished previously (Manfrin et al., 2001; de Britoet al., 2002; Franco & Manfrin, 2013; Table 1), gen-erating 42 haplotypes with 4, 7, 15 and 10 haplo-types exclusively from D. serido, D. gouveai,D. seriema and D. borborema, respectively as wellas six shared haplotypes (Fig. 2C). The geographicaldistribution of the haplotypes is detailed in Sup-porting Information Table S1. The standard diver-sity indices calculated for the sequences of thegenes for each species as well as the recombinationtests results are shown in Table 2.

In agreement with the genealogy of per (Fig. 2A)and a-Est5 (Fig. 2B), the variation found among spe-cies was always higher than within species indicatingsignificant genetic differentiation of these loci in thespecies of flies studied here (Table 2). For a-Est5, fourdistinctive networks were obtained, indicating anextrapolation of the connection limit that excludeshomoplastic changes set at 95% (Templeton et al.,1992). The AMOVA indicated that for COI, variationis higher within species than among species (Table 2),in concordance with COI genealogy (Fig. 2C).

We performed an IM analysis to investigatewhether the shared polymorphism in mtDNA datacan be explained by interspecific gene flow due to theobservation of almost entirely fixed differences in thenuclear loci. For all runs, the values for the highest

probability density (HPD) include zero (Table 3),indicating that shared haplotypes in mtDNA andnuDNA markers should be a consequence of themaintenance of ancestral polymorphisms.

SELECTION TESTS

Most results of the MK test were not significant,indicating that there are no significant differencesbetween fixed and polymorphic substitutions(Table 4), therefore we cannot reject the null hypoth-esis that mutations have been neutral based on thisstatistics. We detect an excess of fixed replacementdifferences only for D. gouveai, suggesting positiveselection at a-Est5 (Table 4). Conversely, in thecodon-based tests with robust statistical framework,we detected slight distinctive results. First, thesetests for per and COI sequences suggested that bothare under purifying selection for all analysed species(Supporting Information, Tables S2 and S3). Con-versely, for the a-Est5 sequences the LRT showedsignificant results for positive selection in differentsites in each species (Supporting Information, TableS4, Figs S2–S5).

For D. serido, two codons, 126 and 196, showed evi-dence of positive selection (Supporting Information,Fig. S4), however only the former were statisticallysignificant. Codon 196 showed evidence of positiveselection in D. borborema (Supporting Information,

Table 2. Summary statistics, recombination test (PHI) and AMOVA for period (per) (363 bp), alpha-Esterase-5 (a-Est5)(745 bp) and cytochrome c oxidase subunit I (COI) (557 bp). SDO, D. serido, GOU, D. gouveai, SMA, D. seriema, BOR,

D. borborema

Loci/species

Summary statisticsPHI test

Effective number

of codonsAMOVA

N H Hd S p P value

New Nc (SD:

standard

deviation) ФST

Variation

among

species, %

Variation

within

species, %

(A) period 136 55 0.951 41 0.0172 < 0.05 0.69* 69.16 30.84

SDO 11 10 0.909 11 0.0097 0.37 50.44 (0.67)

GOU 28 10 0.357 9 0.0076 0.14 51.49 (0.27)

SMA 39 17 0.436 9 0.0057 0.05 51.83 (0.47)

BOR 58 23 0.396 17 0.0055 0.33 51.62 (0.35)

(B) Esterase 113 35 0.984 109 0.0204 0.16 0.87* 86.77 13.23

SDO 9 4 0.667 19 0.1381 1.00 48.91 (1.27)

GOU 22 8 0.569 05 0.0014 0.19 49.20 (0.27)

SMA 30 13 0.811 10 0.0019 0.50 47.99 (0.38)

BOR 49 10 0.915 35 0.0656 0.06 47.97 (0.31)

(C) COI 165 42 0.868 35 0.0095 0.87 0.35* 34.82 65.17

SDO 16 5 0.775 10 0.0082 1.00 41.44 (0.30)

GOU 47 11 0.835 20 0.0107 0.58 41.09 (0.74)

SMA 40 21 0.935 23 0.0108 0.68 41.27 (0.62)

BOR 62 14 0.670 10 0.0024 0.58 40.78 (0.46)

*P < 0.05.



Fig. S2), but, in this case, it showed statistical signifi-cance. D. gouveai and D. seriema were the speciesthat had the greater number of codons under positiveselection. In D. gouveai, five codons (62, 126, 140, 170and 216) were observed (Supporting Information, Fig.S3), and all of them were statistically significant. ForD. seriema, six codons (73, 126, 140, 166, 208 and216) were found under positive selection (SupportingInformation, Fig. S5), but only the first four showedstatistical significance.

An interesting fact is that some shared codonsamong species were statistically significant in onespecies but not in the other, as shown by codons196 and 216 in D. serido and D. borborema, andD. gouveai and D. seriema, respectively. Conversely,codons 126 and 140 shared between D. serido,D. seriema and D. gouveai and between D. gouveaiand D. seriema, respectively, were statistically signif-icant in both cases.

Our analysis indicates a modest codon bias in thethree segments and similar among the species(Table 2). In this sense, codon usage bias is notexpected to affect our interpretation of selection testsresults.

DISCUSSION

By analysing the haplotypic variation from threemolecular markers, we found mito-nuclear discor-dance in cactophilic species of the Drosophila seridohaplogroup (D. buzzatii cluster). The three molecularmarkers analysed have distinctive effective popula-tion sizes: per is X-linked, a-Est5 is autosomal andCOI is mitochondrial; therefore, only by demographyshould we expect more shared polymorphisms innuDNA than in mtDNA because the sorting is inver-sely proportional to the effective size (Funk &Omland, 2003). However, these expectations werenot observed in our sample, as a-Est5 demonstratedless shared polymorphism, followed by per and COIgenes (Fig. 2). The failure to observe the aboveexpected pattern, as occurred in the present work, ismost easily explained to be due to the introgressionof mtDNA or some selective force in nuDNA (Petit &Excoffier, 2009; Debiasse, Nelson & Hellberg, 2014).

Previous studies have explained mito-nucleardiscordance in the D. buzzati cluster due to unidirec-tional introgression between populations of the fol-lowing species: D. gouveai and D. antonietae at thelimits of their distribution (Manfrin et al., 2001),D. buzzatii and D. koepferae in sympatric areas(Piccinali, Aguad�e & Hasson, 2004; Franco et al.,2010) and D. serido and D. antonietae in a secondarycontact zone (Kokudai et al., 2011). Furthermore,experimental data indicate that there are differentT

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degrees of reproductive isolation among these specieswith no evidence of complete reproductive isolation(Madi-Ravazzi, Bicudo & Manzato, 1997; Machado,Madi-Ravazzi & Tadei, 2006; Oliveira et al., 2011).In this sense, the occurrence of introgressive mtDNAhybridization is a reliable hypothesis to explain theshared haplotypes from this molecule among speciesin the D. serido haplogroup. Nevertheless, we didnot find significant evidence of mtDNA gene flow(Table 3), and the most conservative conclusion isthat the shared polymorphism is a consequence ofthe maintenance of ancestral polymorphism. To sup-port this, the shared haplotypes of mtDNA are allo-cated in the interior of the genealogy, whichcharacterises them as more ancient haplotypes(Funk & Omland, 2003). They are among those withhigher output weight values in statistical parsimonyanalysis, with haplotype 13 predicted as likely to bethe most ancient (weight = 0.15). Moreover, there isno geographical distribution pattern of the haplo-types shared between species indicating that theyare restricted to sympatric populations, with the sin-gle exception of haplotype 18 (Supporting Informa-tion, Fig. S6). This result is not surprising if weconsider that, in recently divergent species, themaintenance of ancestral polymorphism is anexpected event, as the complete lineage sortingrequires time.

The segments of COI and per gene used here areprimarily under purifying selection (SupportingInformation, Table S3), in concordance with previousstudies in the D. buzzatii cluster (de Brito et al.,2002; Franco et al., 2010). The low levels of non-synonymous substitutions in COI and per are most

likely connected to functional constraints, consideringthe important role of COI in the respiratory chain(Garesse, 1988) and per in the circadian clock regula-tion (Chang & Reppert, 2003; Tauber & Kyriacou,2008). Curiously, even under similar selective regimesin their coding region, the per gene presents low lev-els of shared polymorphism and higher interspecificvariation when compared with COI (Fig. 2, Table 2).These results suggest that other selective events couldcontribute to the accelerated loss of shared polymor-phism in the per sequences, such as a hitchhikingeffect. The Fu0s Fs test applied to per sequencesshowed negative and significant results for D. serido(�6.54; P < 0.02), D. seriema (�11.26; P < 0.02) andD. borborema (�19.07, P < 0.02), suggesting an excessof alleles that is congruent with genetic hitchhiking(Fu, 1997). Indeed, the CCID domain region of per, asanalysed here, is closed to the C2 (conserved region 2)and N2 (non-conserved 2) regions of the per gene. Theformer includes the structurally conserved PASdomain, which is involved in the regulation of clockgenes (Tauber & Kyriacou, 2008), whereas the latterpresents the tandemly arranged Thr–Gly region,which is hypothesised to be related to temperaturecompensation mechanisms, at least in populations ofD. melanogaster (Costa et al., 1992; Kyriacou, Peixoto& Costa, 2007). However, the hypothesis of genetichitchhiking for the per gene, despite being plausible,needs to be considered with caution, at least if weconsider that both esterase (data not showed) andCOI data (Franco & Manfrin, 2013) also present nega-tive and significant values for Fu’s Fs for these spe-cies, a result that could be interpreted as populationgrowth. In fact, the patterns of sequence variation at

Table 4. Fixed and polymorphic variation at COI, per and a-Est5 and tests for departure from neutrality

Species Substitution

COI per a-Est5

Fixed Polymorphic Test Fixed Polymorphic Test Fixed Polymorphic Test

D. serido Syn 32 7 G-test

NS

11 11 G-test

NS

5 38 G-test

NS

Nsyn 2 3 3 2 0 23

D. gouveai Syn 27 14 G-test

NS

14 8 G-test

NS

8 33 G-test*

Nsyn 1 4 5 3 1 28

D. borborema Syn 30 10 G-test

NS

13 15 G-test

NS

6 55 G-test

NS

Nsyn 1 1 4 4 0 30

D. seriema Syn 27 19 G-test

NS

14 9 G-test

NS

8 40 G-test

NS

Nsyn 2 4 4 1 1 28

NS, non-significant (P > 0.05).

*P < 0.05.



a neutral locus undergoing genetic hitchhiking aresimilar to those in an expanding population (Fay &Wu, 2000).

Although most sites of a-Est5 are under purifyingselection, in all species there are some sites thatevolve under positive selection (Supporting Informa-tion, Table S4), suggesting intragenic heterogeneousselective constraints. Considering the cactophilicflies, evidence of positive selection in a-Est5 has beenreported in Argentinean and Australian populationsof D. buzzatii. Due to its role in digestion and/ordetoxification metabolism attributed to Drosophilaesterases, these results were considered to be relatedto the ecological association of this species with itsprickly pear cacti host from the Opuntia genus (Picc-inali et al., 2007).

The influence of host shift in morphology, life char-acteristics and gene expression have been intenselystudied and seems to be an important component indiversification of cactophilic Drosophila (Matzkin,2014; Soto et al., 2014), and is congruent with thehypothesis that host shifts are frequently correlatedwith reproductive isolation and could eventually leadto ecological speciation (Nosil, Crespi & Sandoval,2002; Funk, Nosil & Etges, 2006). Drosophila mojav-ensis Patterson & Crow, for example, inhabits thedeserts of western North America and presents fourallopatric populations groups that are each associ-ated with chemically distinct cacti hosts (Matzkin,2014). Previous studies have indicated differentialexpression of detoxification genes in stocks of thisspecies reared in different host cacti (Matzkin et al.,2006; Matzkin, 2012). Furthermore, populationgenetic data with some of these genes suggest posi-tive selection associated with the host races ofD. mojavensis (Matzkin, 2008). Similarly, the posi-tive selection in a-Est5 detected here could be associ-ated with the diversification of D. serido haplogroupspecies triggered by the exploration and associationof new cacti host.

Phylogeographical data suggest that the D. seridohaplogroup began its diversification in the Caatingabiome (de Brito et al., 2002; Franco & Manfrin,2013), a very heterogeneous cacti environment (Tay-lor & Zappi, 2004). Later, events of population rangeexpansions during the Pleistocene as Caatinga toadjacent xeric vegetation areas within the Cerradoand Brazilian Atlantic forest biomes explains thecurrent geographical distribution (Supporting Infor-mation, Fig. S1). These events should supply ecologi-cal opportunities for the diversification of thesespecies through host shifts. The possible distinctivechemical composition of cacti could impose environ-mental pressure for Drosophila metabolic gene diver-sification and could explain, at least partially, thepositive selection in a-Est5 detected here.

The lack of much ecological data, such as the specificbreeding sites of the cactophilic D. serido haplogroup,prevents some correlations of genetic variation withecological factors driving this variation. There aresome reports of the emergence of D. serido haplogroupspecies from different genera of cacti (Pereira et al.,1983; Ruiz et al., 2000; Tidon-Sklorz & Sene, 1995;Kokudai et al., 2011), but this is a very incompleteand simplified picture to associate genetic variationwith host shift. Therefore, further ecological studiesare needed to improve our knowledge of the degree ofspecialisation of each D. serido haplogroup species totheir cacti hosts.

In addition to interspecific divergence, we found apronounced intraspecific a-Est5 differentiation inD. serido species, with one haplogroup (H3 and H4,Fig. 2B) characteristic of Caatinga biome popula-tions and another in xeric areas of Atlantic coastpopulations (H1 and H2, Fig. 2B) in the southern-most geographical distribution of the species (Sup-porting Information, Fig. S1). This intraspecificvariation was also found based on cuticular hydro-carbon information (Oliveira et al., 2011), chromo-some inversion (Ruiz et al., 2000) and aedeagusmorphology (Franco et al., 2008). It is still unclearwhich historical events were important for the evo-lution of these two evolutionary lineages withinD. serido, but we can discuss the ecological aspectsof this differentiation. The Caatinga and Atlanticcoast regions harbour different assemblages of cacti.In the former, they are a high columnar cacti diver-sity, whereas in most of its distribution in the south-east Brazilian Atlantic coast, only the host Cereusfernambucensis is available, an endemic componentof the scrub and dunes vegetation of BrazilianAtlantic forest (Taylor & Zappi, 2004). Therefore,based on our results, we can conclude that naturalselection promoted by host shifts could be importantin early stages of intraspecific diversification ofD. serido.

Our data are congruent with selective forcesreducing the coalescent times in nuDNA rather thanintrogression of mtDNA as the explanation of mito-nuclear discordance that involves COI, per, andaEst5. The suggestion that positive selection ina-Est5 is associated with the cactus host shift is evi-dently the ‘tip of the iceberg’, considering all of themetabolic challenges to explore new resources, and itis likely that several genes are involved in this pro-cess (Matzkin, 2014). The D. serido haplogroupencloses species of recent divergence overlappingtheir distribution in an environment with high cactidiversity but also with species partially occurring inregions with poor cacti diversity. These geographicand ecological situations qualify this group as apotential model to contribute to the understanding of



the genetic basis of host adaptation and its relation-ship with reproductive isolation.

ACKNOWLEDGEMENTS

We are particularly grateful to PR Epifanio for theirtechnical assistance and to five anonymous reviewersfor their helpful comments. This work was supportedby several grants from CAPES, CNPq, FINEP, USPand FAPESP (03/05031-0; 11/51652-2) to MHM; grantsfrom FAPESP to FFF (05/51780-0; 10/19557-7); and toTCL (11/10499-7).

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Figure S1. Geographical distribution of the species of Drosophila buzzatii cluster in South America. The mainriver basin as well as the approximate range of the seasonally dry vegetation in the South America is shownon the map. SDTF: Seasonally Dry Tropical Forest. Adapted from Franco & Manfrin (2013).Figure S2. Amino acids sites and x classes in the nuclear gene alpha-Esterase-5 for Drosophila borborema.Figure S3. Amino acids sites and x classes in the nuclear gene alpha-Esterase-5 for Drosophila gouveai.Figure S4. Amino acids sites and x classes in the nuclear gene alpha-Esterase-5 for Drosophila serido.Figure S5. Amino acids sites and x classes in the nuclear gene alpha-Esterase-5 for Drosophila seriema.Figure S6. Geographical distribution of COI haplotypes shared among the species from D. serido haplogroup.The location codes are the same as those shown in Table S1.Table S1. Distribution among the haplotype populations obtained with period (per), alpha-Esterase-5 (a-Est5)and cytochrome oxidase subunit I (COI) genes. The nomenclature of haplotypes is the same as in Fig. 2. Thelocations codes are the same as in Fig. 1.Table S2. Model parameter estimates, x ratios, log likelihood values (lnL) and test statistics for PAML sitemodels, using the mitochondrial COI gene sequences for the D. serido haplogroup species.Table S3. Model parameter estimates, x ratios, log likelihood values (lnL) and test statistics for PAML sitemodels, using sequences of the nuclear gene period for the D. serido haplogroup species.Table S4. Model parameter estimates, x ratios, log likelihood values (lnL) and test statistics for PAML sitemodels, using the sequences of nuclear gene alpha-Esterase-5 for the D. serido haplogroup species.

