The use of wing shape for characterising macroevolution in mosquitoes (Diptera: Culicidae)

Infection, Genetics and Evolution 77 (2020) 104052

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Research paper

The use of wing shape for characterising macroevolution in mosquitoes (Diptera: Culicidae)

T

⁎

Camila Lorenza,b, , Lincoln Suesdekc,d a

Departamento de Epidemiologia, Faculdade de Saúde Pública, Universidade de São Paulo, Av. Dr. Arnaldo, 715, São Paulo CEP 05509-300, Brazil Biologia da Relação Patógeno-Hospedeiro- Instituto de Ciências Biomédicas, Universidade de São Paulo, Av. Prof. Lineu Prestes, 2415, São Paulo CEP 05508-000, Brazil c Instituto Butantan, Av. Vital Brazil 1500, Butantã, São Paulo, SP CEP 05503-900, Brazil d Instituto de Medicina Tropical, Universidade de São Paulo, Av. Dr. Enéas de Carvalho Aguiar 470, Jardim América, São Paulo, SP CEP 05403-000, Brazil b

A R T I C LE I N FO

A B S T R A C T

Keywords: Geometric morphometrics Landmark Subfamily Phylogenetic signal

The wing form of culicid mosquitoes shows considerable variation among groups: this phenomenon has been addressed by several studies through space-time analyses in mosquito populations, species, and genera. The observed variation results from a combination of two distinct factors: heredity and phenotypic plasticity. The first is usually related to wing shape, a complex character that may serve as a taxonomic marker in specific cases. We hypothesized that wing shape might be phylogenetically meaningful in Culicidae. In this study, we applied a geometric morphometrical approach based on 18 landmarks in 81 species of mosquitoes, representing 19 different genera, to investigate whether wing shape can help retrieve macroevolutionary patterns or identify any phylogenetic signals. We observed that wing shape differed considerably among groups, especially between Anophelinae and Culicinae subfamilies; thus, some wing shape elements may be synapomorphic. Comparisons among wing consensus after Procrustes superimposition revealed that landmark #1, located between the veins RS and R1, was the most variable. Sabethini tribe was distinguished from other taxa owing to a strong phylogenetic signal of its wings, whereas other culicids presented weaker signals and were not that distinguishable. Evolutionary forces such as natural selection, evolutionary limitation/constraint, or canalization mechanisms might drive the evolution of wing phenotype. These findings suggest that the wing undergoes evolution over long periods, but is not neutral enough to reconstruct the phylogenetic history of these insects. Gene-based studies should be performed to understand the driving forces in wing evolution.

1. Introduction Body shape and body form (shape and size when analysed together) are important phenotypic characters of species and show morphological adaptations connected to their life-history strategies (Vogel, 1994). Particularly in insects, the wing is a key structure that reveals ancient evolutionary patterns that allowed successful exploitation of scattered resources by enabling dispersal into new different environments (Combes and Daniel, 2003). Wing shape, size, and venation patterns are highly conserved and species-specific (Crozatier et al., 2004; Waddington, 1940). Insect wing veins are the primary supporting structures in wings (Combes and Daniel, 2003), and some change in the wing venation pattern could influence flight. Wing veins are also involved in diverse aspects of insect ecology and can vary widely even among closely related species (True et al., 1999; Wittkopp et al., 2003), but the causes of differences among vein patterns during evolution

remain unclear (de Celis and Diaz-Benjumea, 2003). Morphological characterization of complex structures such as wings is difficult and influenced by subjectivity, and often undermines comparative analyses. In these cases, it is useful to have a method such as morphometrics, which allows perception and quantification of these variations among individuals. Morphometrics is a descriptive mathematical model of the dissimilarities among geometric shapes of objects. Geometric morphometrics (GM) particularly allows multivariate statistical study of biological structures, because it considers several characteristics of a complex body structure simultaneously (Monteiro, 1999). The wings are the main target structure of this analysis because they have a two-dimensional structure and the wing veins intersect forming points (landmarks) that are ideal for morphometric comparisons. Specifically, several studies have been conducted to show the evolutionary processes using GM in the wing shape of mosquitoes

⁎ Corresponding author at: Departamento de Epidemiologia, Faculdade de Saúde Pública, Universidade de São Paulo, Av. Dr. Arnaldo, 715, São Paulo CEP 05509300, Brazil. E-mail address: [email protected] (C. Lorenz).

https://doi.org/10.1016/j.meegid.2019.104052 Received 5 April 2019; Received in revised form 16 September 2019; Accepted 24 September 2019 Available online 25 October 2019 1567-1348/ © 2019 Elsevier B.V. All rights reserved.

Infection, Genetics and Evolution 77 (2020) 104052

C. Lorenz and L. Suesdek

(Dujardin, 2008; Lorenz et al., 2017) through space and time. The wing venation pattern is also used to distinguish among closely related species (Calle et al., 2002; Vidal et al., 2011; Lorenz et al., 2012) or even distinct genera (Wilke et al., 2016). Some studies also used GM combined with genetic approaches for species discrimination (Gómez and Correa, 2017; Altamiranda-Saavedra et al., 2017) or even to compare both markers for genetic and phenetic structure of specific populations (Gómez et al., 2014). Furthermore, studies have been conducted using morphometric data to construct phylogenies (Zelditch et al., 1995, 1998; Swiderski et al., 2000; Guerrero et al., 2003). This is only possible if there is a strong phylogenetic signal (Cole and Lele, 2002) in the morphometric data. The strength of this phylogenetic signal is reflected in the degree of congruence between the morphometric phenogram and the known phylogenetic tree of that taxon (MacLeod and Forey, 2002). Klingenberg and Gidaszewski (2010) studied Drosophila melanogaster subgroup and compared wing landmark data with a well-supported molecular phylogeny. They found conflicts between the trees indicating that wing shape provided incorrect estimates of phylogeny in the D. melanogaster subgroup. For Culicidae, as far as we know, there are no similar studies. In this paper, we performed a comprehensive analysis to verify the macroevolutionary patterns within family Culicidae using wing shape data. For this we used 81 species representing 19 different genera. Our main objectives were: (i) to test the efficiency of GM in distinguishing different genera, subgenera, and tribes within the Culicidae family; (ii) to investigate whether there is any evolutionary pattern in the wing veins, and (iii) to identify whether there is any phylogenetic signal in the wing shape data.

Table 1 Description of all species analysed. Eighty-one species representing 19 genera of Culicidae were used, according to classification of Harbach (2007). All individuals are females collected in 2014/2015. Genera

Subgenera

Species

Collection site

N

Anopheles

Kerteszia

Anopheles cruzii Anopheles homunculus Anopheles laneanus

Cananéia/SP

24 24 8

Nyssorhynchus

Anopheles

Chagasia Aedes

Lophopodomyia Stethomyia – Stegomyia

Aedeomyia

Sallumia Aedeomyia

Lutzia Culex

Lutzia Melanoconion

2. Materials and methods 2.1. Mosquito sampling and identification Details about mosquitoes and collection data from individuals employed in this study are described in Table 1. In total, 1429 individuals were analysed, representing 81 species within 19 different genera, according to classification of Harbach (2007). All individuals were females collected in 2014/2015. Adults were collected using Shannon traps, and immature forms were collected in natural and artificial breeding sites with larval dippers or suction tubes. Morphological characteristics were used for species identification using the key proposed by Forattini (2002). Adult females were stored in 1.5 mL microcentrifuge tubes with silica gel at room temperature until the wings were removed.

Phenacomyia Culex

Microculex

2.2. Geometric morphometrics analysis We used the methods described by Lorenz et al. (2012); Lorenz and Suesdek (2013) for the geometric morphometrics analyses of the wing. The wings of the species Anopheles and Aedeomyia were stained with acid fuchsin because they had many spots and their veins were very transparent, making it difficult to mark the landmarks. For the other species collected, only an alcohol brush was used to aid the removal of wing scales. Only the right wings of female individuals were used. The wings were then mounted on a microscope slide with a cover slip and photographed under 40× magnification with a Leica DFC320 digital camera coupled to a Leica S6 microscope. On each wing image, 18 landmarks were digitized (Fig. 1) using TpsDig V1.40 software (Rohlf, 2005). All specimens were scored by a single experimenter (C.L.). The coordinates were analysed using TpsRelw 1.36 (Rohlf, 2003a) and relative warps analyses (Principal Components) were conducted. These data were used to calculate the canonical variables and the Mahalanobis distance using TpsUtil 1.26 (Rohlf, 2004), TpsRelw 1.36 (Rohlf, 2003a), TpsRegr 1.28 (Rohlf, 2003b), Statistica 7.0 (StatSoft, Inc, 2004), and MorphoJ 1.02 (Klingenberg, 2011) software programs. The allometric effect was not removed from the analysis because we consider allometric size variation as part of the species identification

Trichoprosopon

– –

Johnbelkinia Toxorhynchites

– Lynchiella

Uranotaenia

Uranotaenia

Anopheles Anopheles Anopheles Anopheles Anopheles Anopheles Anopheles

bellator albitarsis deaneorum strodei triannulatus darlingi aquasalis

Anopheles oswaldoi Anopheles evansae Anopheles galvaoi Anopheles intermedius Anopheles fluminensis Anopheles gilesi Anopheles nimbus Chagasia fajardi Aedes aegypti Aedes albopictus Aedes hortator Aedeomyia squamipennis Lutzia bigoti Culex sacchettae Culex corentynensis Culex spissipes Culex zeteki Culex vaxus Culex rabelloi Culex ribeirensis Culex atratus Culex palaciosi Culex oedipus Culex pilosus Culex bastagarius Culex ensiformis Culex corniger Culex quinquefasciatus Culex nigripalpus Culex coronator Culex usquatus Culex declarator Culex mollis Culex aphylactus Culex pleuristriatus Culex carioca Culex imitator Culex ocellatus Trichoprosopon pallidoventer Johnbelkinia longipes Toxorhynchites portoricensis Uranotaenia pulcherrima Uranotaenia geometrica

Campos do Jordão/SP Cananéia/SP Frutal/MG

Manaus/AM Rio de Janeiro/ RJ Cananéia/SP

Manaus/AM Rio Branco/AC São Paulo/SP Cananéia/SP Frutal/MG Rio Branco/AC Cananéia/SP Manaus/AM Frutal/MG

Cananéia/SP

São Paulo/SP Manaus/AM Cananéia/SP

Rio de Janeiro/ RJ Cananéia/SP Manaus/AM

Rio de Janeiro/ RJ Frutal/MG Monte Negro/RO

36 18 11 14 23 28 36 8 1 2 1 2 1 6 1 35 35 6 13 17 9 5 2 2 12 2 15 10 22 2 2 2 7 27 16 19 16 17 16 10 3 3 6 6 2 2 10 3 1 2

(continued on next page)

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explicitly map shape data onto a phylogenetic tree (imported from a nexus file). The function “Map onto Phylogeny” does such a mapping, which can be used to visualize reconstructed ancestral shapes or to superimpose the phylogeny onto ordination plots. Moreover, MorphoJ produces new datasets with reconstructed changes along the branches of the phylogeny and independent contrasts. The genetic phylogeny was obtained in Reidenbach et al. (2009), and was based on a tree from six nuclear protein-coding genes (arginine kinase, CAD, catalase, enolase, hunchback, and white). We excluded the genera Johnbelkinia, Lutzia and Runchomyia from this analysis due to the lack of genetic data in the literature for comparisons. In this manner it is possible to evaluate whether the branches of the genetic tree topology are positioned in the same space in which the wing shape is more similar between genera.

Table 1 (continued) Genera

Subgenera

Species

Collection site

N

Coquillettidia

Rhynchotaenia

Coquillettidia chrysonotum Coquillettidia venezuelensis Coquillettidia albicosta Coquillettidia albifera Coquillettidia hermanoi Coquillettidia juxtamansonia Ochlerotatus serratus Ochlerotatus scapularis Ochlerotatus fulvus Ochlerotatus argyrothorax Psorophora cingulata Psorophora lutzii Psorophora ferox Psorophora albipes Psorophora saeva Psorophora albigenu Haemagogus capricornii Haemagogus leucocelaenus Limatus durhamii Limatus flavisetosus Mansonia wilsoni Mansonia amazonensis Mansonia titillans Sabethes undosus Runchomyia reversa Wyeomyia confusa Wyeomyia aporonoma Wyomyia pilicauda

Cananéia/SP

30

Ochlerotatus

Ochlerotatus Chrysoconops Protomacleaya

Psorophora

Haemagogus

Limatus Mansonia

Sabethes Runchomyia Wyeomyia

Grabhamia Janthinosoma Psorophora

Janthinosoma Haemagogus Conopostegus – – Mansonia – Peytonulus Runchomyia Prosopolepis Triamyia Phoniomyia

17 11 23 6 18

Monte Negro/RO Cananéia/SP

19 25 2 3

Manaus/AM Cananéia/SP

16 23 18 20 4 2 1 2

3. Results

Rio de Janeiro/ RJ

Principal Component analyses grouped individuals according to their affinities of the wing shape (Fig. 2). Samples were separated by genera, and the first two Principal Components accounted for 45.32% of the total variation. A clear grouping was observed of Anopheles detached from the other genera. Johnbelkinia, Toxorhynchites, and Uranotaenia genera appear isolated in the morphospace. Each group presented considerable variation with respect to its dispersion in the morphospace and consequently presented differences in morphological diversity. According to Suesdek (in Lorenz et al., 2017), the morphological diversity of each group can be measured using the “amount of dispersion” of individuals in the principal component morphospace. Using this metric, it is possible to note that the Coquillettidia and Culex genera showed great intraspecific variation in wing shape and appeared more dispersed in the morphospace (Fig. 3). To avoid biases due to the different sample size of each group, we standardised samples to nearly 25 haphazardly taken individuals for each group; when fewer samples were available, we used all of them. Canonical Variate analyses (CVA) were also performed to better visualize the pattern of grouping among genera (Fig. 4). We found three main clusters in the data: (1) species of the genus Anopheles, (2) representatives of the Sabethini tribe (Limatus, Johnbelkinia, Sabethes, Runchomyia, Trichoprosopon and Wyeomyia), and (3) all other tribes: Culicini (Culex and Lutzia), Aedini (Aedes, Haemagogus, Ochlerotatus and Psorophora), Mansoninii (Coquillettidia and Mansonia) and Aedeomyinii (Aedeomyia). The genera Toxorhynchites and Uranotaenia appear separated from the others as the wing shape of these species is not similar to any of the other genera analysed. In order to verify whether wing shape variation is also evident within each genus or tribe, CVA was performed separately for each group (Fig. 5). In all analyses, the genera or subgenera were correctly segregated into different clusters representing different taxa in the morphospace of canonical variables. The subgenera within Anopheles and the genera within the Sabethini tribe were segregated perfectly on the canonical variate 1 and 2 axis. After Procrustes superimposition, an alignment between the extremes of differentiation in the wing shape among all genera was performed (Fig. 6). Landmark #1, located on the wing edge between veins RS and R1, was the most variable among all the 81 species analysed and was important mainly for differentiation between the subfamilies Anophelinae and Culicinae. To assess the similarity between all groups, a phenogram based on Procrustes distances was also constructed, which considers intra and interspecific variations (Fig. 7). The neighbour joining tree shows the segregation of all the mosquito genera, and the Sabethini tribe appears as a monophyletic group. The genetic tree topology was plotted on the morphospace of the Principal Components of wing shape to relate the two analyses (Fig. 8). Reconstruction of evolutionary changes revealed a divergent pattern, where the genetic tree topology was deformed in the morphospace, that is, the branches of the genetic tree became distorted to fit shape

12 11 2 1 7 9 16 17 5 7

Fig. 1. A wing of Culicidae with the 18 landmarks used in this study.

process (Dujardin, 2008). Discriminant analysis and reclassification tests were performed using the Mahalanobis distances as estimators of the metric distance. Thin-plate splines were obtained by regression of the canonical scores versus the shape components using TpsRegr 1.28 (Rohlf, 2003b). In order to calculate the most influential landmarks between species, we used the TET and COV programs (XYOM-CLIC, 2019). A Neighbour Joining tree was constructed based on the Mahalanobis distance to illustrate species segregation patterns using PHILIP software (Felsenstein, 1995). 2.3. Wing shape x genetics In order to compare the genetic and morphological approaches, the wing shape coordinates data from the 18 landmarks were extracted into Principal Components; a plot of the first 2 principal components is an optimal representation in 2 dimensions because it is the plot that shows the maximal amount of variation among species means (Klingenberg and Gidaszewski, 2010). Subsequently, the mean of the wing variation found for each sampled genus was plotted into morphospace; the phylogeny constructed with genetic data was then combined with this information using MorphoJ 1.02 (Klingenberg, 2011) software. MorphoJ implements several approaches to tackle this type of study that 3

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Fig. 2. Principal Component analysis of the 19 Culicidae genera sampled, using 18 wing landmarks. The numbers in parentheses represent the percentage of variation of each component. The ellipses evidences each group with probability of 90%.

4. Discussion

characteristics of each genus. If both trees (GM and genetics) were congruent, it would be expected to observe perfect collinearity between them in the morphospace, with no distortion or overlap among branches. This visual inspection therefore suggested that there is no clear phylogenetic signal for these genera. Nevertheless, it is possible to note an evolutionary pattern among the genera, where Aedes and Culex have landmark #1 more displaced to the left. The first 2 principal components accounted for 42.5% and 29.1%, respectively, of the variation among the means for the genera.

Our results demonstrate that Culicidae taxa show considerable differences in their wing shape, based on their clear separation into distinct groups in the morphospace of canonical variables. Principal component analyses, which usually identify only very evident patterns, detected a segregation of subfamilies Anophelinae and Culicinae. They diverged about 200 million years ago (Reidenbach et al., 2009), and it seems that their wing shape has accompanied such differentiation. This

Fig. 3. Morphological diversity estimated from the morphospace of PCs for each genus. The values in the vertical axis are logarithmic scales. The genus Chagasia was not considered because a single individual was sampled, so there was no morphological diversity. 4

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Fig. 4. Canonical Variate analysis of the 19 Culicidae genera evidencing three major groups: subfamily Anophelinae, tribe Sabethini and other mosquitoes. Toxorhynchites and Uranotaenia genera appear isolate. The ellipses evidences each group with probability of 90%.

constraints and patterns (Gilchrist et al., 2000). Insect wing veins are the primary supporting structures in wings (Combes and Daniel, 2003); thus, some drastic change in the wing venation pattern could influence flight. However, based on the findings of our study, even if there is some functional canalization or constraint, these variations can at least be used to identify the groups and subgroups within Culicidae. Regarding morphological diversity, all the analysed genera presented different levels of intraspecific diversity, ranging from very low (Uranotaenia) to very high (Culex and Coquillettidia). It is known that the greater the intraspecific diversity, the harder it is to distinguish groups with accuracy. Some landmarks were more variable than others and were consequently more useful in identifying species or genera. Comparison of the wing consensus after Procrustes superimposition revealed that the most variable landmark was #1, located on the edge of the wing between the veins RS and R1. This anatomical landmark is important mainly for differentiating between the subfamilies Anophelinae and Culicinae. Future studies should be conducted to understand why this landmark is so diagnostic. It is possible that its anatomical morphology is a unitary phylogenetic character for subfamilies, such as a synapomorphy. According to Dujardin (2008), the wing landmarks of mosquitoes are differently affected by the same stimulus, and the posterior border may undergo morphological changes depending on the influence of external factors. Other landmarks also showed great variation among groups, especially #14, #15 and #16, located in the centre of the wing. Wootton (1992) and Wootton (1998) studied dragonflies (Odonata) and identified several wing features that drastically improve the aerodynamic properties of the wing through increased structural support; they referred to these as “smart mechanisms”. These include the nodus, which serves as a major structural support along the leading edge of the wing and the pterostigma, which reduces vibration at the wing tip during flight (Bybee et al., 2008). For some species of Culicidae, such as the genus Aedes sp. for example, the wing is an important structure to flight as well as sexual signalling (Cator et al., 2010). It is still unknown if these variations in landmarks and patterns of wing veins within each species have some ecological or

difference between the subfamilies can be attributed to the evolutionary age of each group or some evolutionary pressure. Several studies have reported the high heritability of wing shape in Diptera, sometimes over 60% (Mousseau and Roff, 1987; Bitner-Mathé and Klaczko, 1999; Gilchrist and Partridge, 2001; Hoffmann and Shirriffs, 2002; Jirakanjanakit et al., 2007). Also, some recent quantitative genetic studies have provided evidence of strong genetic determinism for this trait in Drosophila (Iriarte et al., 2003; Breuker et al., 2006; Patterson and Klingenberg, 2007). In our study, geometric morphometrics proved to be a useful tool for detecting interspecific variations, and the wing shape also proved to be a good marker to reveal ancient evolutionary patterns such as subfamilies, subgenera, and tribes. Other studies have used this technique and have been able to separate similar species that are often phylogenetically close (Calle et al., 2002; Henry et al., 2010; Lorenz et al., 2012, 2015). The CVA revealed three main groupings: (1) Anophelinae subfamily, (2) Sabethini tribe, and (3) all the other remaining genera, what means that clear wing shape patterns are recognisable for taxa 1 and 2. Wing shape is generally used as a taxonomic marker and indicator of microevolutionary processes (Dujardin, 2008; Vidal et al., 2011; Gómez et al., 2014; Lorenz et al., 2014). Additionally, as noted here, it also appears to be a good indicator of macroevolution in different major subgroups, such as genera, subfamilies or tribes. We also observed overlapping among several Culicinae genera, what shows that wing shape evolutionary patterns are heterogeneous across taxa. There are some possible explanations for this phenomenon, including (i) conservation of the wing phenotype among the subgenera due to natural selection, evolutionary limitation and/or correlated evolution among them (Smith et al., 2011), or (ii) canalization mechanisms that preserve the phenotype of important anatomical structures such as wing veins (Gibson and Wagner, 2000; Debat and David, 2001). Developmental mechanisms impose patterns and constraints, during growth, on the shape of resulting structures and organs. In contrast, natural selection acts on phenotypes to produce adaptive variation, but only within the bounds imposed by developmental 5

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Fig. 5. Canonical Variate analysis within separate groups: Aedini and Sabethini tribes, showing each genus, and Anopheles and Culex genera, showing each subgenus. The numbers in parentheses represent the percentage of variation of each canonical variate.

monophyly of Sabethini, and are in accordance with recent synapomorphic gene inversions in this tribe (Lorenz et al., 2019). The genera Chagasia and Anopheles remained together in the topology, indicating that their wings are somehow similar, as also observed in Psorophora and Ochlerotatus, representing the tribe Aedini. The rarely studied genus Lutzia, presented a wing shape more similar to that of Culex species; this is related to its phylogenetic position, since it is a genus belonging to the Culicini tribe (Harbach, 2007). However, most of the clusters formed had no correlation with their current known phylogeny (Reidenbach et al., 2009). Testing the correlation between morphometric traits and phylogeny has long been a goal for studies on the evolution of shape (Klingenberg and Gidaszewski, 2010). However, our results showed that wing shape of most Culicidae taxa did not present a strong phylogenetic signal. The morphometric data provided an incongruous estimate for the general reconstruction of the family Culicidae. The wing shape similarity within Sabethini and among various genera of Culicidae were unexpected, given that the family Culicidae is about 200 million years old (Reidenbach et al., 2009) and was prone to accumulate profound wing shape variability. Paradoxically, from the microevolutionary perspective, wing shape of culicids is fast-evolving (Motoki et al., 2012; Lorenz et al., 2017; Suesdek, 2019), and it also responds to artificial selection (Jirakanjanakit et al., 2007). The herein reported cases of homogeneity among some taxa may be an expression of evolutionary canalisation

Fig. 6. Aligned wing consensus after Procrustes superimposition showing the extremes of differentiation among the 19 genera sampled. The arrow indicates landmark # 1, point with greater variation.

behavioural role that directly influences the flight or copulation of individuals. In order to verify the similarity among all genera, a phenogram was constructed based on the Procrustes distances; using all the 1429 specimens in the analyses, only the Sabethini tribe appeared as a defined group. This cluster corroborates the existing genetic and morphological data in literature (Reidenbach et al., 2009). The wing shapes are closely related among species of Sabethini and, in this case, the wing venation pattern presents a phylogenetic signal (as defined by Cole and Lele, 2002) in the context of family Culicidae. Our findings corroborate the 6

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Fig. 7. Neighbour-Joining tree based on Procrustes distance among 19 Culicidae genera. The monophyletic group (red box) represents the Sabethini tribe. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Munstermann, 1992; Brust et al., 1998). Gene-based studies should investigate the mechanisms of driving forces in wing evolution that are involved in determining hereditary characters; studies on the functionality of internal wing veins may elucidate their possible adaptive value and are also welcome.

(Flatt, 2005) or some kind of evolutionary constraint. In those cases of morphological homogeneity, one cannot discard the possibility of stabilizing natural selection be driving wing shape evolution, as pointed out by Klingenberg and Gidaszewski (2010). However, it is difficult to hypothesize an adaptive value for wing patterns comprising internal veins (not those placed in the border). The responsible genes for wing shape in Culicidae have not been fully known, but polygenic inheritance appear to be involved (Dujardin, 2008). If pleiotropy occurs in those genes, natural selection on pleiotropic traits may indirectly act on wing shape, and this account for the phylogenetic discrepancy between genes and wings. Several other studies have also revealed partial or complete incongruities between phylogenetic trees obtained with genetic and morphometric data (Courant et al., 1997; Marcus et al., 2000; Pretorius and Scholtz, 2001; Cole et al., 2002; Milne and O'Higgins, 2002; Cardini and Elton, 2008). Therefore, the morphometric data may not be reliable indicators of the phylogeny of groups; specifically, in Culicidae, the wings appear to have their own evolution which follows paths distinct from other markers. Even when combination of genetic and morphometric data in Culicidae successfully recovered phylogenetic relationships, genotype-phenotype incongruences occurred (Brust and

5. Conclusions Our analyses increased the available shape information for many taxonomic groups at the Culicidae family and genus level and provided a template for studies on shape in other groups. Our landmark arrangement revealed key morphological characteristics and enabled us to identify combinations of features that are indicative of macroevolution among groups, especially between the Culicinae and Anophelinae subfamilies. We showed that the most variable landmark was #1, located between the veins RS and R1, and that its anatomical morphology could be assigned a synapomorphy in these subfamilies. The diversity of wing vein patterns illustrates how they can dramatically evolve, or inversely be static, within the same range of evolutionary times. Multivariate analyses, such as the geometric morphometrics used here, usually reveal patterns and tendencies that are not Fig. 8. Reconstruction of evolutionary changes in wing shape. The genetic phylogeny was obtained in Reidenbach et al. (2009), and was based on a tree from six nuclear protein-coding genes (arginine kinase, CAD, catalase, enolase, hunchback, and white). This phylogenetic tree topology has been superimposed onto a plot of the first 2 principal components of the covariance matrix among genera means. This is the projection of the multivariate shape space onto a plane that best represents the variation among means (71.6% of the total variance among genera means). The contours of the wing in red represent the ancestor (Anopheles) and the blue represents each compared genus. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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perceivable in other types of analyses. The phylogenetic signal of the wings was not generally confirmed for all groups, but there was a phylogenetic signal observed for some taxonomic groups such as the subfamily Anophelinae and Sabethini tribe. In general, the wing should have a particular evolutionary history that diverges somewhat from the phylogeny of mosquitoes. There could be some evolutionary force acting on wing phenotype, such as natural selection, evolutionary limitation/constraint, or canalization mechanisms that preserves the phenotype of important anatomical structures. We suggest that other morphological characters could be studied in similar analyses to improve the accuracy in discriminating related species of mosquitoes.

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Declaration of Competing Interests The authors declare that they have no competing interests. Funding LS has been recipient of CNPq fellowships 311805/2014–0 and 311984/2018–5, grants CAPES 23038.005274/2011–24 and 1275/ 2011. CL was recipient of FAPESP 2013/05521–9 and 2017/10297–1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Acknowledgements We are grateful to Fernanda Almeida Lopes for technical and laboratory support. We appreciate the support of the local communities and health workers of Pariquera-Açu: Luiz Carlos de Oliveira, Décio Wach, Jair Donizete da Silva, Francisco Alves dos Santos, and Rui de Lima. We are especially grateful to Aristides Fernandes for mosquito identification. We thank the anonymous reviewers who provided comments that helped us to improve the manuscript. References StatSoft, Inc; Available from: http://www.statsoft.com. 2004. [2016 ago 13]. XYOM-CLIC. 2019 [website] Available on: http://xyom-clic.eu/ Access Jan-2019. Altamiranda-Saavedra, M., Conn, J.E., Correa, M.M., 2017. Genetic structure and phenotypic variation of Anopheles darlingi in Northwest Colombia. Infect. Genet. Evol. 56, 143–151. Bitner-Mathé, B.C., Klaczko, L.B., 1999. Heritability, phenotypic and genetic correlations of size and shape of Drosophila mediopunctata wings. Heredity 83 (6), 688–696. Breuker, C.J., Debat, V., Klingenberg, C.P., 2006. Functional evo-devo. Trends Ecol. Evol. 21 (9), 488–492. Brust, R.A., Munstermann, L.E., 1992. Morphological and genetic characterization of the Aedes (Ochlerotatus) communis complex (Diptera: Culicidae) in North America. Ann. Entomol. Soc. Am. 85 (1), 1–10. Brust, R.A., Ballard, J.W.O., Driver, F., Hartley, D.M., Galway, N.J., Curran, J., 1998. Molecular systematics, morphological analysis, and hybrid crossing identify a third taxon, Aedes (Halaedes) wardangensis sp. nov., of the Aedes (Halaedes) australis species-group (Diptera: Culicidae). Can. J. Zool. 76 (7), 1236–1246. Bybee, S.M., Ogden, T.H., Branham, M.A., Whiting, M.F., 2008. Molecules, morphology and fossils: a comprehensive approach to odonate phylogeny and the evolution of the odonate wing. Cladistics. 24 (4), 477–514. Calle, L., David, A., Quiñones, M.L., Erazo, H.F., Jaramillo, O., 2002. Morphometric discrimination of females of five species of Anopheles of the subgenus Nyssorhynchus from southern and Northwest Colombia. Mem. Inst. Oswaldo Cruz 97 (8), 1191–1195. Cardini, A., Elton, S., 2008. Does the skull carry a phylogenetic signal? Evolution and modularity in the guenons. Biol. J. Linn. Soc. 93 (4), 813–834. Cator, L.J., Ng’Habi, K.R., Hoy, R.R., Harrington, L.C., 2010. Sizing up a mate: variation in production and response to acoustic signals in Anopheles gambiae. Behav. Ecol. (5), 7–13. Cole, T.M., Lele, S., 2002. Richtsmeier. A parametric bootstrap approach to the detection of phylogenetic signals in landmarks data. capítulo 6. School of Medicine, University of Missouri-Kansas City, Kansas City. Combes, S.A., Daniel, T.L., 2003. Flexural stiffness in insect wings I. scaling and the influence of wing venation. J. Exp. Biol. 206 (17), 2979–2987. Courant, F., David, B., Laurin, B., Chaline, J., 1997. Quantification of cranial convergences in arvicolids (Rodentia). Biol. J. Linn. Soc. 62 (4), 505–517. Crozatier, M., Glise, B., Vincent, A., 2004. Patterns in evolution: veins of the Drosophila wing. Trends Genet. 20 (10), 498–505. De Celis, J.F., Diaz-Benjumea, F.J., 2003. Developmental basis for vein pattern variations in insect wings. Int. J. Dev. Biol. 47 (7–8), 653–663.

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