evolution of manduca sexta hornworms and relatives: biogeographical analysis reveals an ancestral...

Molecular Phylogenetics and Evolution 68 (2013) 381–386

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Molecular Phylogenetics and Evolution

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Short Communication

Evolution of Manduca sexta hornworms and relatives: Biogeographicalanalysis reveals an ancestral diversification in Central America

1055-7903/$ - see front matter � 2013 Elsevier Inc. All rights reserved.http://dx.doi.org/10.1016/j.ympev.2013.04.017

⇑ Corresponding author. Fax: +1 352 392 0479.E-mail address: kawahara@flmnh.ufl.edu (A.Y. Kawahara).

Akito Y. Kawahara a,⇑, Jesse W. Breinholt a, Francesca V. Ponce a, Jean Haxaire b, Lei Xiao a,Greg P.A. Lamarre c,d, Daniel Rubinoff e, Ian J. Kitching f

a Florida Museum of Natural History, University of Florida, Gainesville, FL 32611, USAb Honorary Attaché, Muséum National d’Histoire Naturelle de Paris, Le Roc, F-47310 Laplume, Francec Université Antilles Guyane, UMR Ecologie des Forêts de Guyane, 97310 Kourou, French Guianad INRA, UMR Ecologie des Forêts de Guyane, 97310 Kourou, French Guianae Department of Plant and Environmental Protection Sciences, University of Hawai’i, Manoa, Honolulu, HI 96822, USAf Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD, UK

a r t i c l e i n f o a b s t r a c t

Article history:Received 14 December 2012Revised 21 March 2013Accepted 19 April 2013Available online 3 May 2013

Keywords:HawkmothHornwormManducaquinquemaculatusPhylogenySphingidae

The hawkmoth genus Manduca is a diverse group of very large, conspicuous moths that has served as animportant model across many biological disciplines. Two species in particular, the tobacco hornworm(Manduca sexta) and the tomato hornworm (Manduca quinquemaculatus) have been researched exten-sively. Studies across biological fields have referred to these two species as being closely related or evensister species, but the extent to which these two model organisms are related remains largely unknown.We conducted a comprehensive multi-gene phylogenetic analysis of Manduca, based on both an ML andBayesian framework, which resulted in a monophyletic Manduca but only when two other genera, Dolbaand Euryglottis are included. We tentatively conclude that the sister group to Manduca sexta comprisesthe Caribbean M. afflicta and M. johanni, and the sister lineage to this clade includes M. quinquemaculatusand the Hawaiian M. blackburni. Thus, M. sexta and M. quinquemaculatus are closely related, but are notsister species. Biogeographical analyses reveal an ancestral center of diversification in Central America,and Manduca appears to have subsequently colonized North and South America. Our phylogeny providesan important foundation for comparative studies of two model organisms and their relatives.

� 2013 Elsevier Inc. All rights reserved.

1. Introduction

The hawkmoth genus Manduca is a diverse group of very large,conspicuous moths that has served as a model across many biolog-ical disciplines. Much like the fruit fly genus Drosophila, Manduca isa model for research in biochemistry, developmental biology, ecol-ogy, endocrinology, functional morphology, physiology, neurobiol-ogy and genomics (Roe et al., 2009). Two species in particular, thetobacco hornworm Manduca sexta (Linnaeus, 1763) and the tomatohornworm Manduca quinquemaculatus (Haworth, 1803) are peststhat have been researched extensively. Studies across biologicalfields have referred to these two species as being closely related(e.g. Halitschke et al., 2001; Reisenman et al., 2010; Yoshinagaet al., 2010), or even ‘‘sister species’’ (e.g. Kessler and Baldwin,2002, 2004; Nihout and Suzuki, 2008), but the extent to whichthese two model organisms are related remains largely unknown.Uncovering relationships between the two model species and their

relatives will provide a valuable evolutionary framework withimplications for a broad array of research disciplines.

The 70 described species of Manduca are distributed in bothNorth and South America, with the highest diversity in the Neo-tropics (Kitching et al., 2011). The group is believed to be mono-phyletic (Kitching and Cadiou, 2000) with a South Americanorigin (Schreiber, 1978). Neither the ancestral distribution ofManduca, nor those of species complexes within the genus hasbeen formally studied. Reconstructing historic patterns of Manducacan help us understand present-day patterns of: (1) taxonomic andbiogeographical diversity; (2) physiology and behavior across thegenus; and (3) genetic variation that can advance control measuresagainst M. sexta and M. quinquemaculatus.

Three studies have proposed relationships among Manduca spe-cies: Rothschild and Jordan (1903), Kawahara et al. (2009) andRubinoff et al. (2012). Rothschild and Jordan proposed a ‘‘tree’’ inwhich they showed relationships based on shared morphologicalfeatures, but their work was not a formal character-based phyloge-netic analysis. Kawahara et al. (2009) utilized molecular data toexamine the evolution of Sphingidae and confidently placed thegenus Dolba within Manduca. They also determined that Manduca

382 A.Y. Kawahara et al. / Molecular Phylogenetics and Evolution 68 (2013) 381–386

florestan and M. muscosa are closely related, separated from a cladeconsisting of Dolba, M. quinquemaculatus and M. sexta. While Kawa-hara et al.’s study revealed novel relationships between Dolba andspecies in Manduca, their phylogeny only included four Manducaspecies. Rubinoff et al.’s (2012) study was aimed at understandingthe placement of Hawaii’s endangered Manduca blackburni and in-cluded only six Manduca species. In the present paper, we in-creased taxon sampling to 51 species, representing 73% of thespecies diversity in the genus and constructed a molecular phylog-eny to test: (1) whether Manduca is monophyletic, (2) the extent towhich M. sexta and M. quinquemaculatus are related, and (3) assessthe probability of the ancestral distribution of the genus, M. sexta,and M. quinquemaculatus.

Fig. 1. Taxon and gene sampling design. Two separate datasets were constructed,differing in the number of taxa and genes. Dataset 1 included only nuclear genes,Dataset 2 included all four genes and a block of missing data. Numbers on the leftrefer to the number of samples.

2. Material and methods

2.1. Sequencing and alignment

We sequenced four genes, three nuclear and one mitochondrial.Our data set included 51 of the 70 described taxa, representing 73%of species in the genus. Genes and their sequence lengths were:CAD (2928 bp), elongation factor-1a (EF-1a, 1228 bp), wingless(402 bp) and the ‘‘barcode’’ region of COI (658 bp), totalling5216 bp. These genes were chosen because they have demon-strated utility in providing phylogenetic signal among hawkmothgenera (e.g. Kawahara et al., 2009; Rubinoff et al., 2012). Themajority of DNA sequence data were generated at the Universityof Florida McGuire Center for Lepidoptera and Biodiversity, FloridaMuseum of Natural History, while others were obtained from priorpublications. Some COI sequences were obtained from the BOLDdatabase (www.boldsystems.org; see Table S1). Primers, protocols,and molecular techniques largely follow recent publications on themolecular systematics of hawkmoths and relatives (e.g. Kawaharaet al., 2009; Rubinoff et al., 2009, 2012; Zwick et al., 2011). We at-tempted to sequence all genes for all samples that we could obtain.However, because some did not amplify well, we subsequentlyused additional internal primer pairs for two genes. These internalprimers were (forward and reverse primers): CADm5F andCADm1mR (CAD), and ef44 and efrcM4 (EF-1a). Wingless andCOI sequences were not amplified with internal primers. Becauseour goal was to construct a comprehensive phylogeny of Manduca,we also incorporated COI sequence data to represent species thatotherwise did not have any molecular data (Table S1).

Single gene datasets were initially created to test for laboratorycontamination, and subsequently concatenated into a data matrix.The four genes were aligned separately using MAFFT 6.857b(Katoh, 2011) with the G-INS-I algorithm. PartitionFinderV1.0.1(Lanfear et al., 2012) was used to determine the best substitutionmodel implementing the Akaike Information Criterion (AIC;Akaike, 1973) for the optimal partitioning strategy for each geneand codon position.

2.2. Datasets

We constructed two different datasets to estimate the phylog-eny of Manduca, differing in gene and taxon sampling (Fig. 1).We chose to construct two different datasets because sequencedata were not available for all samples in the study, and our goalwas to obtain a robust phylogeny with as many ingroup taxa aspossible. Conducting phylogenetic analyses with a few genes canoften result in trees with weak support or with incorrect relation-ships (e.g. Sanderson and Driskell, 2003) but allows one to includemany taxa, whereas constructing phylogenies with greater genesampling but with fewer taxa can increase branch support, butcan also result in misleading relationships (e.g. Heath et al.,

2008). We first estimated trees based on the dataset that only in-cluded species with nuclear data (49 samples; Dataset 1). We thenestimated phylogenies based on a concatenated dataset of all fourgenes (CAD, EF-1a, WG, COI) including taxa for which we have onlyCOI barcode data (83 samples total; Dataset 2), but which also in-cluded a large amount of missing data. We used trees presented inKawahara et al. (2009) to determine outgroups. Nine outgroups,based on sequence availability and proximity to Manduca, were in-cluded in the analysis (Table S1).

2.3. Phylogeneticanalyses

Phylogenetic analyses were conducted in both a Bayesian andML framework. We ran two independent Bayesian runs in MrBayes3.2 (Ronquist et al., 2012) each with a cold chain and three hotchains. Each run started from a random tree using default flat pri-ors, sampling every 1000th generation for 250 million generationswith unlinked statefreq, revmat, shape, and pinvar parameters. Thenumber of parameters (nst) and rate heterogeneity (G, I or G + I)were assigned to each partition following the PartitionFinder re-sults. Split frequencies below 0.01 and convergence of the negativelog likelihood posterior distribution between runs were used todetermine the burn-in. The number of generations to exclude asburn-in were assessed from the MrBayes output and the programTracer 1.5 (Rambaut and Drummond, 2007). Converged MrBayesruns were combined after the exclusion of burn-in and a majorityrule consensus tree created with nodal confidence assessed by pos-terior probabilities. Maximum likelihood analyses were run inRAxML 7.3.2 (Stamatakis, 2006) implementing the optimal parti-tions estimated in PartitionFinder. For all RAxML analyses, we exe-cuted 200 ML tree searches with a random starting tree as well as200 ML tree searches that start from a bootstrapped tree topology.The tree with the best likelihood score was selected and we as-sessed confidence in nodal support through 1000 bootstrap repli-cations estimated in RAxML.

2.4. Hypothesis testing

The Approximately Unbiased (AU) test of Shimodaira (2002)was conducted to compare confidence between our results and aprior morphology-based hypothesis that Manduca is monophyletic(Kitching and Cadiou, 2000). While sampling only a few Manduca

Table 1The best nucleotide substitution model and the number of parsimony informativecharacters for each partition.

Gene/codonposition

Best substitutionmodel

Parsimony informativecharacters

CAD/1 HKY + I 52CAD/2 HKY + I 21CAD/3 HKY + I + G 432EF-1a/1 HKY + I 2EF-1a/2 F81 + I 10EF-1a/3 GTR + G 114WG/1 SYM + I 7WG/2 JC 1WG/3 GTR + G 57COI/1 GTR + I + G 34COI/2 F81 + I 4COI/3 GTR + G 153

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species, the molecular study of Kawahara et al. (2009) confidentlyplaced Dolba within Manduca, and Euryglottis as sister toDolba + Manduca. We conducted ML analyses with greater taxonsampling, that: (1) constrained the monophyly of Manduca withoutDolba and Euryglottis; (2) constrained the monophyly of Manducaplus Euryglottis, but excluded Dolba; and (3) constrained the mono-phyly of Manduca plus Dolba but excluded Euryglottis. AU statisticaltests were conducted in CONSEL 0.20 (Shimodaira and Hasegawa,2001) to determine the difference in fit to data of the constrainedand unconstrained trees, using scripts that were developed for pre-vious studies (e.g. Cho et al., 2011; Kawahara et al., 2011; Regieret al., 2009, 2013). We also conducted a Bayesian topological test(Huelsenbeck et al., 2002) on the 10,000 trees from the posteriordistribution of the MCMC chains and searched for the number oftrees that had a topology that fit that constraint.

2.5. Ancestral area reconstruction

We used the program RASP 2.1a (Yu et al., 2011) for ancestralbiogeographic reconstruction. RASP is based on a Bayesian ances-tral state reconstruction method that determines the probabilityof each ancestral area averaged over all sampled trees in the pos-terior distribution. We re-rooted trees in PAUP� 4.0b (Swofford,2002) and coded each taxon according to biogeographical regions,as defined by Morrone (2006). The regions were: Nearctic (A);Mexican Transition Zone (B); Caribbean, including parts of CentralAmerica (C); Amazonian (D); Chacoan (E); Parana (F); South Amer-ican Transition Zone (G); and Andean (H). Because our outgroupsampling was limited, we did not want to bias the ancestral areaprobabilities based on the presence or absence of outgroups. Weapproached this issue in two ways: (1) we coded the distributionof each outgroup to reflect its known distribution, and (2) we ran-domly selected a single outgroup and treated it as a ‘‘dummy’’ out-group. This dummy outgroup was coded as being present in allareas with equal probability to cover the wide range of geographicareas. We ran 10 chains for 5 million generations in RASP, samplingevery 1000th generation with a burnin of 2 million generationswith the outgroup option set to wide.

3. Results

3.1. Sequencing and partitioning

The level of sequence completeness of Dataset 1 was consider-ably higher than Dataset 2. The percentage of missing data for bothdatasets, by gene, were (Dataset 1/Dataset 2): CAD (41.5%/65.0%),EF-1a (16.7%/50.9%), wingless (0.02%/42.3%), COI (0.05%/0.04%).Partitioning by gene and codon position (12 partitions) resultedin the highest AIC score in PartitionFinder. The best substitutionmodel for each partition (Table 1) was incorporated in all MrBayesanalyses and the partitioning scheme was implemented in RAxML.

3.2. Phylogenetic analyses

Phylogenetic analyses based on both ML and Bayesian optimal-ity criteria resulted in a monophyletic Manduca but only when Dol-ba and Euryglottis were included; otherwise the genus waspolyphyletic. Three well-supported groups (>0.97 PP) were identi-fied within Manduca: (1) the florestan complex (node E; 1.0 PP); (2)the sexta complex (node G; >0.97 PP); and (3) the occulta complex(node I; >0.99 PP; Fig. 2). Bayesian analyses of Dataset 1 and Data-set 2 resulted in non-conflicting topologies, and a few nodes re-ceived poor support (<0.60 PP). ML and Bayesian results differedby the relationships among clades from the unsupported lefeburiicomplex being monophyletic in the Bayesian analysis and falling

out independently yet still basal in the ML analyses (Figs. S1 andS2). Phylogenetic analyses of the nuclear gene dataset alone (Data-set 1) generally provided stronger branch support than the datasetthat included COI with more missing data (Dataset 2). In somecases, node support dropped >35% in ML bootstrap between Data-set 1 and 2 (Figs. S1 and S2).

3.3. Hypothesis testing

A prior morphology-based study predicted that Manduca ismonophyletic (Kitching and Cadiou, 2000). In our study, the MLanalysis that constrained the monophyly of Manduca but excludedboth Dolba and Euryglottis had a likelihood score that was signifi-cantly worse than the unconstrained tree (AU test, P < 0.0001).ML constrained trees that excluded one of the two genera (Dolba,Euryglottis) were also statistically worse than the unconstrainedtree (AU test, P < 0.0001). The Bayesian topological test resultedin no trees with a topology that matched the constraint topologies,strengthening the argument that these two genera belong withinManduca.

3.4. Ancestral area reconstruction

RASP analyses provided strong evidence that the ancestral areafor Manduca sensu lato (node A) was Caribbean/Central Americanwith 71% probability (Table 2). There was �54% probability thatthe ancestral distribution for nodes C–K was also Caribbean/Cen-tral American (Table 2). Nodes B and L appear to have a greaterprobability of being Amazonian in origin. The sexta complex hasa relatively high probability of a Caribbean/Central American origin(69%, node G) and the group appears to have subsequently shiftedto North America inthe quinquemaculatus group (76%, node N). Incontrast, the lefeburii complex, while not having strong supportfor its monophyly, likely transitioned from Central America tothe Amazonian region (75%, node B). The florestan complex also ap-pears to have originated in the Caribbean/Central America andthen moved into the Nearctic region, though the probability isnot very high (39%, node M). No significant differences in ancestralstate estimation were observed when outgroup ancestral distribu-tions were coded as uncertain (dummy) or when they followedtheir known distribution.

4. Discussion

4.1. General trends in Manduca evolution

Our multi-gene phylogeny of Manduca provides an importantframework for the evolution of M. sexta and relatives, reveals

Fig. 2. Bayesian consensus of Manduca and relatives, showing ancestral area probabilities as pie charts at key nodes. Red branches lead to taxa that were sampled for nucleargenes (taxa in both Datasets 1 and 2); black branches lead to taxa that were only part of Dataset 2. Hyphens indicate branches that were recovered but had a posteriorprobability of <0.5. Numbers above or below branches indicate branch support. Posterior probabilities from Dataset 1 are in red and posterior probabilities from Dataset 2 arein black. Boxes after species names indicate present-day distributions in the defined bioregions. Scale bar = substitutions/site. (For interpretation of the references to colour inthis figure legend, the reader is referred to the web version of this article.)

384 A.Y. Kawahara et al. / Molecular Phylogenetics and Evolution 68 (2013) 381–386

new insights into the biogeography of the genus, and serves as thefoundation for a revised classification of this model group. Consis-tent with the results of Kawahara et al. (2009), we find strong sup-port for a close relationship between M. florestan and M. muscosa,

and also M. quinquemaculatus and M. sexta. We also confirm statis-tically, with greater taxon sampling, that both Dolba and Euryglottisshould be included within Manduca to retain that genus as mono-phyletic. The taxonomic changes to formally synonymize these

Table 2The posterior probability for each ancestral geographic area estimated in BMC ancestral state reconstruction analysis in the program RASP for each labelled node in Fig. 2.Biogeographical regions refer to zones as defined by Morrone (2006). A hyphen indicates a probability <0.01.

Nodes Nearctic Mexican Transition Caribbean/C. American Amazonian Chacoan Parana SA Transition Andean

A 0.04 0.04 0.71 0.11 0.03 0.02 0.04 0.01B 0.01 0.01 0.18 0.75 0.03 0.01 0.02 –C – 0.01 0.67 0.24 0.02 0.02 0.05 –D 0.18 0.10 0.68 0.02 0.01 0.01 0.02 –E 0.15 0.29 0.54 0.01 0.01 – – –F 0.24 0.05 0.67 0.02 0.01 – 0.01 –G 0.22 0.09 0.69 – – – – –H 0.09 0.04 0.87 – – – – –I 0.20 0.19 0.60 – – – – –J 0.15 0.16 0.69 – – – – –K 0.06 0.07 0.87 – – – – –L – 0.01 0.28 0.34 0.10 0.06 0.20 –M 0.39 0.23 0.30 0.04 0.03 0.01 0.01 –N 0.76 0.09 0.15 – – – – –

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two genera will be published separately and will include morpho-logical data. We also suggest that future studies include Apocalypsisvelox, an Old World species that superficially resembles Euryglottis.

The general biogeographical trend in Manduca appears to be anancestral distribution that was Caribbean/Central American, andthat M. sexta, M. quinquemaculatus, and other derived lineages sec-ondarily radiated in North and South America. There were at leasttwo major, deep inter-species ancestral shifts in distribution, onein tand other derived lineageshe lefeburii group and one in thequinquemaculatus group. These shifts, including subsequent intra-specific range changes, might have been facilitated by the well-developed flight muscles of Manduca (Eaton, 1971) that allowedthem to disperse over large distances (Janzen, 1986). These traitsare especially pronounced in hawkmoths with long tongues andhigh visual acuity, such as Manduca. Some hawkmoths have evenevolved ears (Roeder et al., 1968) and sound producing organs(Rothschild and Jordan, 1903) that are thought to improve the in-sects’ ability to avoid predatory bats (Barber et al., 2013; Barberand Kawahara, 2013). While Manduca do not appear to have earsor sound producing organs, they have long spurs on their legs,which may function as a physical defense against attacking bats(Young, 1982), allowing them to survive under greater predatorypressure and expand their ranges.

4.2. Phylogenetic position of M. sexta and M. quinquemaculatus

While numerous studies have referred to M. sexta and M. quin-quemaculatus as sister species (e.g. Kessler and Baldwin, 2002,2004; Nihout and Suzuki, 2008), we have demonstrated that theyare not, despite morphological and ecological similarities (seeRothschild and Jordan (1903) and Kitching et al. (2011) for a listof traits). Instead, M. sexta is more closely related to the clade con-taining the Caribbean M. afflicta + M. johanni. The sister species ofM. quinquemaculatus is the Hawaiian M. blackburni, and this resultis congruent with the preliminary study of Rubinoff et al. (2012),which was based on sparser taxon sampling. It appears that withinthe sexta group, one lineage colonized the Caribbean (ancestor ofM. afflicta + M. johanni), while the other lineage colonized NorthAmerica (M. quinquemaculatus group).

While our study focused on interspecific biogeographical pat-terns, there are also some interesting intra-specific patterns. For in-stance, our sampling shows that within M. sexta, there are twodistinct groups, a South American lineage, and a separate, well-supported North American one (Fig. 2). These results are consistentwith the initial results of Rubinoff et al. (2012), and imply thatthere might be population-level genetic patterns within this spe-cies. Expansion of taxon sampling for broadly distributed species

is ongoing, and we plan a more definitive comparative study fo-cused on the population genetics of M. sexta.

Acknowledgments

We thank Charlie and Kim Mitter (University of Maryland) andFrédéric Bénéluz (Société Entomologique Antilles Guyane) for pro-viding many valuable specimens that were included in this study.Rodolphe Rougerie (INRA) helped obtain some of the COI barcodesequences from BOLD. Jerome Regier (University of Maryland) pro-vided the laboratory space, equipment, and supplies that helpedgenerate sequences early in the development of this project. DavysLopez (University of Florida) helped generate CAD, EF-1a and COIsequence data at the FLMNH. Susan Sorrell, Jillian Sullivan, YuxinZhang and Minjia Zhong (University of Florida) helped preparewing vouchers for identification. We thank Thomas Emmel forhis continuous support. Grant funding came from The National Sci-ence Foundation, Award Numbers DEB-0212910, DEB-0604329,DEB-0918341, IOS-1121739, IOS-1211538, and the National Geo-graphic Society Grant No. 9107-12.

Appendix A. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.ympev.2013.04.017.

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