New Results

Genetic structure of the stingless bee Tetragonisca angustula

Flávio O. Francisco, Leandro R. Santiago, Yuri M. Mizusawa, Benjamin P. Oldroyd, Maria C. Arias
doi: https://doi.org/10.1101/026740

Abstract

The stingless bee Tetragonisca angustula Latreille 1811 is distributed from Mexico to Argentina and is one of the most widespread bee species in the Neotropics. However, this wide distribution contrasts with the short distance traveled by females to build new nests. Here we evaluate the genetic structure of several populations of T. angustula using mitochondrial DNA and microsatellites. These markers can help us to detect differences in the migratory behavior of males and females. Our results show that the populations are highly differentiated suggesting that both females and males have low dispersal distance. Therefore, its continental distribution probably consists of several cryptic species.

Introduction

The stingless bee Tetragonisca angustula Latreille 1811 distributed from Mexico to Argentina is one of the most widespread bee species in the Neotropics (Silveira et al., 2002; Camargo & Pedro, 2013). It is a small (4-5 mm in length), generalist and highly eusocial bee (Michener, 2007) and highly adaptable to different nest sites. Colonies comprise up to 5,000 individuals (Lindauer & Kerr, 1960), and are usually built in tree trunks or in wall cavities. It swarms frequently and is extremely successful in urban environments (Batista et al., 2003; Slaa, 2006; Velez-Ruiz et al., 2013). Tetragonisca angustula is one of the most popular stingless bees for meliponiculture in Latin America (Nogueira-Neto, 1997; Cortopassi-Laurino et al., 2006) and nest transportation and trading is very common among beekeepers.

In general, colony reproduction in stingless bees begins by workers searching for a new nest site within their foraging range (van Veen & Sommeijer, 2000a). Daughter nests are established at most a few hundred meters from the “mother” nest (Nogueira-Neto, 1997). After selecting the site, several workers begin to transport cerumen, propolis and honey from the mother nest to the new one (Nogueira-Neto, 1997). This nest site preparation phase can last from a few days (van Veen & Sommeijer, 2000a) to a few months (Nogueira-Neto, 1997). A virgin queen then leaves the mother nest accompanied by hundreds of workers (van Veen & Sommeijer, 2000b). The next day the virgin queen flies out, mates with presumably one male (Peters et al., 1999; Palmer et al., 2002), returns to the nest and about a week later begins oviposition (van Veen & Sommeijer, 2000b).

In contrast, little is known about the reproductive behavior of stingless bee males. After emergence from brood cells, they remain in the nest for two to three weeks (Cortopassi-Laurino, 2007). They then leave the nest and never return. There are no data about the behavior of males during their period outside the nest. In the laboratory, males can live up to six weeks (Velthuis et al., 2005). Therefore, they likely have two to four weeks for dispersal and reproduction. Males often form mating aggregations, and these are comprised of males from hundreds of different, and not necessarily nearby colonies (Paxton, 2000; Cameron et al., 2004; Kraus et al., 2008; Mueller et al., 2012). This suggests high male dispersal.

Studies on the genetic structure of populations can help us better understand dispersal behavior and evolutionary history. There are three existing population genetic studies of T. angustula (Oliveira et al., 2004; Baitala et al., 2006; Stuchi et al., 2008). These studies are of limited scope due to limited sampling or the use of outdated molecular markers such as RAPDs and isozymes. Thus, the conclusions are ambiguous concerning the extent and direction of gene flow, population differentiation, dispersal and evolutionary history.

Here we evaluate the genetic structure of several populations of T. angustula using mitochondrial DNA (mtDNA) and microsatellite markers. Considering the wide distribution of T. angustula and the commonness of nest transportation and trading, we expect low genetic differentiation among populations despite the low dispersal distance of females during swarming.

Materials and methods

Sampling

We collected 1,002 T. angustula from 457 sites distributed on the mainland and islands in south/south-eastern Brazil (Table S1). Eleven islands all with arboreal vegetation and of area greater than 1.0 km2 were selected, 10 being land-bridge islands isolated about 12,000 years ago (Suguio et al., 2005) and one sedimentary island (Ilha Comprida) which arose about 5,000 years ago (Suguio et al., 2003). The islands range in size from 1.1 to 451 km2 and are 0.1 to 38 km from the mainland (Table S2, Fig. 1). Bees were sampled from nests (n = 125, one per nest) and flowers (n = 877) (Table S1). Samples were grouped into 17 populations, 14 from the mainland and three from islands (Fig. 1).

Fig. 1
Fig. 1

Posterior probability assignment (vertical axis) of individual genotypes (horizontal axis) for K = 10 (Tetragonisca angustula) according to the program BAPS (upper panel). Below, map of the studied area with the approximate location of the sampled populations. Population names are 1: Teresópolis, 2: Resende, 3: Passa Quatro, 4: Angra dos Reis, 5: Ilha Grande, 6: São Sebastião, 7: Ilha de São Sebastião, 8: Iguape, 9: Ilha Comprida, 10: Apiaí, 11: Guaratuba, 12: Blumenau, 13: São José, 14: Prudentópolis, 15: Porto União, 16: Foz do Iguaçu, and 17: Teodoro Sampaio. Detailed location of all islands visited (lower panels). IGRA: Ilha Grande; IANC: Ilha Anchieta; ITMD: Ilha do Tamanduá; IVIT: Ilha da Vitória; IBUZ: Ilha de Búzios; IBEL: Ilha de São Sebastião; IMTG: Ilha Monte de Trigo. ICOM: Ilha Comprida; ICAR: Ilha do Cardoso; IMEL: Ilha do Mel. ISCA: Ilha de Santa Catarina.

We preserved the specimens in 96% ethanol for transport to the laboratory. DNA extraction followed the protocol described in Francisco et al. (2014). We dried the specimens at room temperature for 20 min prior to DNA extraction. 83

Mitochondrial DNA sequencing

Two mitochondrial genes were partially sequenced: cytochrome c oxidase subunit 1 (COI) and cytochrome b (Cytb). Details about amplification and sequencing are given in Francisco et al. (2014).

Microsatellite genotyping

The samples were genotyped for eleven microsatellite loci: Tang03, Tang11, Tang12, Tang17, Tang29, Tang57, Tang60, Tang65, Tang68, Tang70, and Tang77 (Brito et al., 2009). PCR conditions for each locus are given in Francisco et al. (2014). Electrophoresis, visualization and genotyping were performed according to Francisco et al. (2011).

Micro-checker 2.2.3 (van Oosterhout et al., 2004) was used to identify null alleles and scoring errors. Colony 2.0.1.7 (Jones & Wang, 2010) was used to determine whether individuals collected in the same plant or places nearby were related. Samples were excluded from our data set if matched all of the following three criteria: collected at sites distant less than 2 km, indicated as related by colony, and sharing a mtDNA haplotype. Overall, 722 T. angustula bees from 17 populations were deemed suitable for further genetic analyses (Table 1).

View this table:
Table 1

Population characteristics and genetic diversity in Tetragonisca angustula populations. SA: sampled area in square kilometers. ME: median elevation in meters. N: sample size. NH: number of haplotypes. h ± sd: haplotype diversity and standard deviation. π ± sd: nucleotide diversity and standard deviation. Ar ± se: allelic richness after rarefaction for 22 individuals and standard error. HE ± se: expected heterozigosity and standard error. FIS: inbreeding coefficient.

Genepop 4.1.2 (Rousset, 2008) was used to verify Hardy-Weinberg equilibrium (HWE) in populations and loci and to detect linkage disequilibrium (LD). Markov chain was set for 10,000 dememorizations, 1,000 batches and 10,000 iterations per batch. In cases of multiple comparisons, P-values were corrected by applying Sequential Goodness of Fit test by the program Sgof 7.2 (Carvajal-Rodríguez et al., 2009). This method is advantageous over other correction methods because it increases its statistical power with the increasing of the number of tests (Carvajal-Rodríguez et al., 2009).

Genetic diversity

Arlequin 3.5.1.3 (Excoffier & Lischer, 2010) was used to calculate mtDNA haplotype (h) and nucleotide (π) diversity. Genalex 6.5 (Peakall & Smouse, 2006, 2012) was used to calculate microsatellite allelic richness (A) and expected heterozygosity (HE). Since sample sizes were different, allelic richness was standardized by rarefaction (Ar) using the program Hp-rare 1.0 (Kalinowski, 2005). Differences in Ar among populations were estimated by Mann-Whitney two-tailed U Test (Mann & Whitney, 1947). Inbreeding coefficients (FIS) were calculated for each population with 10,000 permutations using Arlequin.

Population differentiation and gene flow

Mega 5.2.1 (Tamura et al., 2011) was used to calculate the number of base substitutions per site from mitochondrial sequences by averaging over all sequence pairs between populations using the Kimura 2-parameter (K2p) model (Kimura, 1980). Population pairwise θ values (an FST analogue, Weir & Cockerham 1984) were calculated with 10,000 permutations by arlequin using microsatellite alleles. When heterozygosity is high, FST and its analogues may not be appropriate measures of genetic differentiation (Hedrick, 2005; Jost, 2008; Heller & Siegismund, 2009). For this reason, Jost’s Dest (Jost, 2008) was calculated. This statistc is not influenced by heterozygosity (Jost, 2008) and is more appropriate for microsatellite data (Heller & Siegismund, 2009). Global Dest was calculated with 9,999 permutations for mtDNA and microsatellite data using Genalex. Pairwise Dest was calculated only for microsatellite data. Mantel tests between genetic and geographical distances among populations were performed with 9999 permutations by Genalex to verify isolation by distance for both molecular markers.

Baps 6 (Corander et al., 2008; Cheng et al., 2013) was used to infer population structure using microsatellites and the geographic coordinates of the sampled individuals to spatially cluster them. Baps 6 provides a Bayesian analysis of genetic population structure that creates K groups of individuals based on the similarity of their genotypes. The program was initially ran 5 times for each of K = 1 to 17 and then 10 times for each of K = 5 to 14. These results were used for admixture analysis with 200 iterations to estimate the admixture coefficients for the individuals, 200 simulated reference individuals per population and 20 iterations to estimate the admixture coefficients of the reference individuals.

Estimates of rates and direction of current and/or recent migration (m) between populations were determined by the program bayesass 3 (Wilson & Rannala, 2003) using microsatellites multilocus genotypes through Markov chain Monte Carlo (MCMC) techniques. We performed five independent runs with 107 MCMC iterations, burn-in of 106 iterations and sampling frequency of 2,000. The delta values used were 0.25 (migration), 0.40 (allele frequencies) and 0.55 (inbreeding).

Assessment of population demography

To detect any recent bottleneck events we used the program bottleneck 1.2.02 (Piry et al., 1999). We used the two-phased model (TPM) of mutation which is suggested as the most appropriate for microsatellites (Di Rienzo et al., 1994). The variance among multiple steps was 12 and the proportion of stepwise mutation model in the TPM was 95% as suggested by Piry et al. (1999). Altogether 10,000 iterations were performed. The significance of any deviation was determined with a Wilcoxon sign-rank test.

Results

Island occurrences

Tetragonisca angustula was found and collected on five of the 11 islands visited (Table 1). However, only the samples from Ilha Grande, Ilha de São Sebastião and Ilha Comprida were included in the analyses. The other collections were not included due to small sample size (Ilha do Cardoso, n = 1), and to individuals being highly related, with anecdotal reports of introduced nests (Ilha de Santa Catarina, see Francisco et al. (2014)).

MtDNA diversity 164

The COI gene sequences were 417 bp long (GenBank accession numbers KF222891-KF223893) and 32 haplotypes were identified. The Cytb sequences were 391 bp long (KF223894-KF224896) and generated 43 haplotypes. Most differences among haplotypes were synonymous substitutions, since the number of distinct amino acid sequences were four for COI and 15 for Cytb. We concatenated the nucleotide sequences (808 bp) for population analyses.

The 722 concatenated sequences defined 73 haplotypes. Since h and π were positively correlated (r = 0.510, P = 0.036, n = 17) we hereafter use π as our measure of mtDNA diversity. Nucleotide diversity ranged from 0.0006 ± 0.0019 (Passa Quatro) to 0.0407 ± 0.0251 (Ilha Comprida) (Table 1).

There was a non-significant positive correlation between the size of the sampled area and mtDNA diversity (r = 0.135, P = 0.606, n = 17). The correlation between median elevation and mtDNA diversity was negative but non-significant (r = −0.428, P = 0.087, n = 17).

MtDNA differentiation

Population structure was high. Of 73 haplotypes 67 were population-specific. We built a haplotype network where the frequency and distribution of haplotypes are shown (Fig. S1). The network shows a ‘star-pattern’ centered on four haplotypes. It illustrates the high number of endemic haplotypes, and the great number of nucleotide substitutions that separate the Porto União/Foz do Iguaçu populations from the others. The populations of Teresópolis, Resende, Prudentópolis, Angra dos Reis, and Ilha Grande all feature unique haplotypes.

Global Dest was 0.772 (P < 0.001) indicating a highly significant population structure. The highest K2p values were found for Porto União/Foz do Iguaçu with respect to all other populations (2.809% to 3.306%) (Table 2).

View this table:
Table 2

Estimates of evolutionary divergence over sequence pairs between populations of Tetragonisca angustula. The number of base substitutions per site from averaging over all sequence pairs between populations are shown. Analyses were conducted using the Kimura 2-parameter model (Kimura, 1980) and involved 722 nucleotide sequences. Population abbreviations as in Table 1.

Microsatellite diversity

After the Sequential Goodness of Fit correction, deviation from HWE was occasional, likely arising from type 1 error, and therefore no locus was removed from the analyses (Table S3). No significant LD was found between any pair of loci (all P > 0.05).

Microsatellite diversity was moderate to high. Ar and HE were positively correlated (r = 0.787, P < 0.001, n = 17). Hereafter we use Ar as our measure of microsatellite diversity. Ar was standardized for 22 individuals and ranged from 5.37 (Porto União) to 9.45 (Resende) (Table 1). Ar was significantly different only between Porto União and Resende (U = 93, P = 0.033) and Porto União and Teresópolis (U = 29, P = 0.039).

There was a negative but non-significant correlation between Ar and size of the sampled area (r = -0.114, P = 0.662, n = 17) and between Ar and median elevation (r = −0.084, P = 0.748, n = 17).

Six populations had inbreeding coefficients (FIS) significantly different from zero (P < 0.05). The highest FIS (0.2177) was found in São José (Table 1).

Microsatellite differentiation

Global Dest was high (0.375, P < 0.001) and indicates population structure. Pairwise comparisons also detected population structure, since most θ values were between 0.05 and 0.15 (Table S4) and most Dest values were higher than 0.25 (Table 3). Pairwise θ and Dest were positively correlated (r = 0.977, P < 0.001, n = 136) and we use Dest as our measure of microsatellite differentiation hereafter. Dest ranged from 0.0204 (Guaratuba × Blumenau) to 0.8464 (Prudentópolis × Foz do Iguaçu). High Dest values were always detected in comparisons between Porto União/Foz do Iguaçu and other populations. Low differentiation was observed in some populations near the coast (Iguape, Apiaí, Guaratuba, Blumenau, and São José) but also inland (Porto União × Foz do Iguaçu and Prudentópolis × Teodoro Sampaio).

View this table:
Table 3

Pairwise index of differentiation (Dest) from microsatellite data of Tetragonisca angustula. Population abbreviations as in Table 1.

Population structure was also suggested by the spatial cluster approach used by BAPS, which determined K = 10 as the most likely optimal number of clusters (probability of 98.99%). The clusters were [Foz do Iguaçu/Porto União], [Iguape/Apiaí/Guaratuba/ Blumenau/SãoJosé], [Ilha Comprida], [São Sebastião], [Ilhabela], [Ilha Grande], [Passa Quatro], [Teodoro Sampaio/Prudentópolis], [Teresópolis], [Resende/Angra dos Reis] (Fig. 1). Dest results are in good agreement with these clusters.

The results of the migration rates estimated in bayesass suggested a low level of gene flow throughout the studied area (Table S5). Only 15 out of 272 comparisons showed m > 0 between two populations. Most of the populations that showed evidence of gene flow are near the coast (Fig. 1), but inland populations such as Porto União × Foz do Iguaçu also showed evidence of gene flow. Migration is directional. For instance, the non-differentiation detected between Prudentópolis × Teodoro Sampaio is apparently due to a high migration rate (0.2486 migrants per generation) from Prudentópolis to Teodoro Sampaio, whereas migration in the opposite direction was not detected (Table S5). The results obtained by bayesass are in good agreement with the population structure indicated by θ, Dest and baps.

Isolation by distance

There was a positive and significant correlation between geographic and genetic distance for both mitochondrial (r = 0.415, P = 0.004, n = 136) and microsatellite markers (r = 0.464, P < 0.001, n = 136).

Population demography

We did not detect recent bottlenecks in any of the 17 populations (all P > 0.1392, Table S6).

Discussion

Our results show that T. angustula populations are highly differentiated as demonstrated by mtDNA and microsatellite markers. This suggests that both females and males have low dispersal distance.

Per population mtDNA nucleotide diversity (π) ranged from low to high. High π suggests that a population had a long evolutionary history and a large effective population size. Low π may be explained by lineage sorting or suggest that a population bottleneck has occurred in the past (Avise, 2000). The characteristic star shape of the T. angustula haplotype network provides evidence of relatively recent local extinction, re-colonization, and population expansion. Several phylogeographic studies of vertebrate and invertebrate populations, conducted in some of the areas that we studied, also found low mtDNA nucleotide diversity (Cabanne et al., 2007; Carnaval et al., 2009; Batalha-Filho et al., 2010; Brito & Arias, 2010; Francisco & Arias, 2010; D’Horta et al., 2011; Bell et al., 2012). As argued in these papers, changes in sea level during the Pleistocene generated population bottlenecks followed by species expansion, and this is reflected in localized low nucleotide diversity to this day. Therefore, it is likely that populations that have high mtDNA diversity (e.g. Angra dos Reis) did not experience recent bottlenecks, while populations with low mtDNA diversity (e.g. Passa Quatro) are in regions that likely arose by a recent population expansion.

Overall, we found high mitochondrial genetic differentiation between populations. Similar population structuring has been observed for other stingless bee species (Brito & Arias, 2010; Francisco & Arias, 2010; Quezada-Euán et al., 2012; Brito et al., 2013; Francisco et al., 2013). The mtDNA population structure of stingless bees probably arises from their reproductive behavior. Nonetheless, some populations are not well differentiated from others. This is likely due to gene natural flow, although human transportation also likely plays a role. For instance, haplotypes 34, 35, and 36 all found in Ilha Comprida, were similar to those found in Passa Quatro/Teodoro Sampaio (34 and 36) and Teresópolis (35) (Fig. S1). Due to the high frequency of endemic haplotypes, and the physical distance between these populations, we suggest that nests have been transported to Ilha Comprida causing an artificial increase in this population’s mtDNA diversity.

Nuclear genetic diversity was moderate to high in all populations. Microsatellite diversity was not significantly different between populations except for Porto União. This result shows that the ecological features of each sampling site are not influencing the molecular diversity. Indeed, variables such as size of the sampled area and median elevation were not significantly correlated with genetic diversity for both mtDNA and microsatellites. Moreover, our results did not detect recent bottleneck (e.g. due to habitat fragmentation) in any of the studied populations. However, it is worth emphasizing that theoretical and practical studies have shown that habitat fragmentation affects immediately the genetic structure by increasing it, while the reduction of genetic diversity may take longer (Varvio et al., 1986; Keyghobadi et al., 2005). According to this statement, it will be necessary to monitor the genetic diversity of T. angustula populations studied over years, since currently high structure was detected.

Evidence of inbreeding was found in six populations (Angra dos Reis, Blumenau, São José, Porto União, Foz do Iguaçu and Teodoro Sampaio). This might be an artifact caused by Wahlund effect (Hartl & Clark, 2007) and/or a consequence of the low dispersal of T. angustula. If the latter is true, the persistence of these populations is at risk (Keller & Waller, 2002).

Microsatellite data also indicated high genetic structuring and low gene flow among populations. This suggests that like females, the dispersal distance of males is also quite limited even between populations separated by 34 km of continuous forest. It is interesting here to note that all island populations were differentiated from their mainland counterparts, indicating that males do not cross water for distances as short as 300 m. The program BAYESASS suggested that the highest migration rate is from Prudentópolis to Teodoro Sampaio, populations separated by more than 300 km. These two populations do not share any mtDNA haplotypes suggesting that this gene flow is mediated only by males following the stepping stone model (Kimura & Weiss, 1964).

For both markers population clusters appear to be unrelated to physical barriers (such as rivers or mountain ranges) or forest presence, indicating that genetic connectivity demands more than just habitat connectivity (Marsden et al., 2012). Populations may diverge even when there are no apparent obstacles to gene flow due to low dispersal, geographic distance and genetic drift (isolation by distance). Overall, the population structure of T. angustula is shaped by isolation by distance.

The highest genetic divergence observed was between Porto União/Foz do Iguaçu and the remaining populations. At least 15 mtDNA mutation steps separate these two populations from the others. This represents about 2.8 to 3.3% divergence, which is as high as the divergence between lineages A and Y of Apis mellifera (Franck et al., 2001), which are thought to have diverged over one million years ago (Whitfield et al., 2006). Francisco et al. (2014) suggested that bees from Porto União and Foz do Iguaçu might belong to the subspecies T. angustula fiebrigi while the others to T. angustula angustula.

Among the islands we visited only Ilha do Mel (Zanella, 2005), Ilha de Santa Catarina (Steiner et al., 2006) and Ilha Grande (Lorenzon et al., 2006) had been previously surveyed for bees and T. angustula was reported on all of them. We did not locate T. angustula on six of the 11 islands we visited. Our failure to verify T. angustula on most islands may be due its ancestral absence on the islands when they became isolated or to its extinction after isolation. The constraint on queen dispersal prevents (re)colonization of islands whose distance from the mainland is greater than a few hundred of meters. Even if (re)colonization has occurred, its establishment may not have been successful. With low dispersal, T. angustula has low effective population size and high extinction rate. Island size may be critical to the survival of viable T. angustula populations – we were unable to locate them on any island less than 28 km2. Competition among colonies doubtless limits the number of colonies an island can support so that small islands may not be able to maintain viable populations of T. angustula. The rarity of stingless bee species on islands has been noted elsewhere (Schwartz-Filho & Laroca, 1999; Zanella, 2005).

Our results indicate that T. angustula is not genetically homogeneous across the studied area. Considering that this species has a continental distribution, we speculate this species is ancient and includes wide range of genetically different taxa with the same (or similar) morphology. Sampling across its entire distribution range is needed to elucidate its taxonomic status as well as its evolutionary history.

Disclosure

The authors have no conflict of interest.

Acknowledgments

We are grateful to Paulo Henrique P. Gonçalves for his help with the sampling and to Susy Coelho and Julie Lim for technical assistance. We thank Adílson de Godoy, Carlos Chociai, Flávio Haupenthal, Geraldo Moretto, Marcos Wasilewski, Marcos Antonio, Renato Marques, José Moisés, André Trindade, Teófilo, Eduardo da Silva, Guaraci Cordeiro, Marcos Fujimoto, PC Fernandes, Samuel Boff, Thaiomara Alves, the managers and the staff of the Parks, the residents of Ilha da Vitória, Ilha de Búzios and Ilha Monte de Trigo, and countless people who assisted us in the fieldwork. We thank Dr. Jeffrey Lozier for comments on an early version of this manuscript. For permits, we thank Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis (IBAMA) and Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio) (18457-1), Instituto Florestal do estado de São Paulo (260108 - 000.000.002.517/0 2008), Instituto Ambiental do estado do Paraná (128/09) and Instituto Estadual do Ambiente do Rio de Janeiro (E-07/300.011/0). This work was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (04/15801-0; 08/07417-6; 08/08546-4; 10/18716-4; 10/50597-5) and Australian Research Council. This work was developed in the Research Center on Biodiversity and Computing (BioComp) of the Universidade de São Paulo (USP), supported by the USP Provost’s Office for Research.

References

  1. ↵
    Avise, J. C. (2000) Phylogeography: The History and Formation of Species. Harvard University Press, Cambridge, MA.
  2. ↵
    Baitala, T. V., Mangolin, C. A., Toledo, V. A. A. and Ruvolo-Takasusuki, M. C. C. (2006) RAPD polymorphism in Tetragonisca angustula (Hymenoptera; Meliponinae, Trigonini) populations. Sociobiology, 48, 1–13.
    OpenUrl
  3. ↵
    Batalha-Filho, H., Waldschmidt, A. M., Campos, L. A. O., Tavares, M. G. and Fernandes-Salomão, T. M. (2010) Phylogeography and historical demography of the neotropical stingless bee Melipona quadrifasciata (Hymenoptera, Apidae): incongruence between morphology and mitochondrial DNA. Apidologie, 41, 534–547.
    OpenUrlCrossRef
  4. ↵
    Batista, M. A., Ramalho, M. and Soares, A. E. E. (2003) Nesting sites and abundance of Meliponini (Hymenoptera: Apidae) in heterogeneous habitats of the Atlantic Rain Forest. Lundiana, 4, 19–23.
    OpenUrl
  5. ↵
    Bell, R. C., Brasileiro, C. A., Haddad, C. F. B. and Zamudio, K. R. (2012) Evolutionary history of Scinax treefrogs on land-bridge islands in south-eastern Brazil. Journal of Biogeography, 39, 1733–1742.
    OpenUrl
  6. ↵
    Brito, R. M. and Arias, M. C. (2010) Genetic structure of Partamona helleri (Apidae, Meliponini) from Neotropical Atlantic rainforest. Insectes Sociaux, 57, 413–419.
    OpenUrl
  7. ↵
    Brito, R. M., Francisco, F. O., Domingues-Yamada, A. M. T., Gonçalves, P. H. P., Pioker, F. C., Soares, A. E. E. and Arias, M. C. (2009) Characterization of microsatellite loci of Tetragonisca angustula (Hymenoptera, Apidae, Meliponini). Conservation Genetics Resources, 1, 183–187.
    OpenUrl
  8. ↵
    Brito, R. M., Francisco, F. O., Françoso, E., Santiago, L. R. and Arias, M. C. (2013) Very low mitochondrial variability in a stingless bee endemic to cerrado. Genetics and Molecular Biology, 36, 124–128.
    OpenUrl
  9. ↵
    Cabanne, G. S., Santos, F. R. and Miyaki, C. Y. (2007) Phylogeography of Xiphorhynchus fuscus (Passeriformes, Dendrocolaptidae): vicariance and recent demographic expansion in southern Atlantic forest. Biological Journal of the Linnean Society, 91, 73–84.
    OpenUrlCrossRefWeb of Science
  10. ↵
    1. J.S. Moure,
    2. D. Urban &
    3. G.A.R. Melo
    Camargo, J. M. F. and Pedro, S. M. (2013) Meliponini Lepeletier, 1836. Catalogue of Bees (Hymenoptera, Apoidea) in the Neotropical Region - online version (eds J.S. Moure, D. Urban & G.A.R. Melo), available at http://www.moure.cria.org.br/catalogue. Accessed Apr/02/2015.
  11. ↵
    Cameron, E. C., Franck, P. and Oldroyd, B. P. (2004) Genetic structure of nest aggregations and drone congregations of the southeast Asian stingless bee Trigona collina. Molecular Ecology, 13, 2357–2364.
    OpenUrlCrossRefPubMed
  12. ↵
    Carnaval, A. C., Hickerson, M. J., Haddad, C. F. B., Rodrigues, M. T. and Moritz, C. (2009) Stability predicts genetic diversity in the Brazilian Atlantic Forest hotspot. Science, 323, 785–789.
    OpenUrlAbstract/FREE Full Text
  13. ↵
    Carvajal-Rodríguez, A., Uña-Alvarez, J. and Rolán-Alvarez, E. (2009) A new multitest correction (SGoF) that increases its statistical power when increasing the number of tests. BMC Bioinformatics, 10, 209.
    OpenUrlCrossRefPubMed
  14. ↵
    Cheng, L., Connor, T. R., Sirén, J., Aanensen, D. M. and Corander, J. (2013) Hierarchical and spatially explicit clustering of DNA sequences with BAPS software. Molecular Biology and Evolution, 30, 1224–1228.
    OpenUrlCrossRefPubMedWeb of Science
  15. ↵
    Corander, J., Sirén, J. and Arjas, E. (2008) Bayesian spatial modeling of genetic population structure. Computational Statistics, 23, 111–129.
    OpenUrl
  16. ↵
    Cortopassi-Laurino, M. (2007) Drone congregations in Meliponini: what do they tell us? Bioscience Journal, 23, 153–160.
    OpenUrl
  17. ↵
    Cortopassi-Laurino, M., Imperatriz-Fonseca, V. L., Roubik, D. W., Dollin, A., Heard, T., Aguilar, I. B., et al. (2006) Global Meliponiculture: challenges and opportunities. Apidologie, 37, 1–18.
    OpenUrlCrossRef
  18. ↵
    D’Horta, F. M., Cabanne, G. S., Meyer, D. and Miyaki, C. Y. (2011) The genetic effects of Late Quaternary climatic changes over a tropical latitudinal gradient: diversification of an Atlantic Forest passerine. Molecular Ecology, 20, 1923–1935.
    OpenUrlCrossRefPubMedWeb of Science
  19. ↵
    Excoffier, L. and Lischer, H. E. (2010) Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Molecular Ecology Resources, 10, 564–567.
    OpenUrl
  20. ↵
    Francisco, F. O. and Arias, M. C. (2010) Inferences of evolutionary and ecological events that influenced the population structure of Plebeia remota, a stingless bee from Brazil. Apidologie, 41, 216–224.
    OpenUrl
  21. ↵
    Francisco, F. O., Brito, R. M., Santiago, L. R., Gonçalves, P. H. P., Pioker, F. C., Domingues-Yamada, A. M. T. and Arias, M. C. (2011) Isolation and characterization of 15 microsatellite loci in the stingless bee Plebeia remota (Apidae: Meliponini). Conservation Genetics Resources, 3, 417–419.
    OpenUrl
  22. ↵
    Francisco, F. O., Santiago, L. R. and Arias, M. C. (2013) Molecular genetic diversity in populations of the stingless bee Plebeia remota: A case study. Genetics and Molecular Biology, 36, 118–123.
    OpenUrl
  23. ↵
    Francisco, F. O., Santiago, L. R., Brito, R. M., Oldroyd, B. P. and Arias, M. C. (2014) Hybridization and asymmetric introgression between Tetragonisca angustula and Tetragonisca fiebrigi. Apidologie, 45, 1–9.
    OpenUrlCrossRef
  24. ↵
    Franck, P., Garnery, L., Loiseau, A., Oldroyd, B. P., Hepburn, H. R., Solignac, M. and Cornuet, J.-M. (2001) Genetic diversity of the honeybee in Africa: microsatellite and mitochondrial data. Heredity, 86, 420–430.
    OpenUrlCrossRefPubMedWeb of Science
  25. ↵
    Hartl, D. L. and Clark, A. G. (2007) Principles of Population Genetics, 4th edn. Sinauer Associates, Inc., Sunderland, MA.
  26. ↵
    Hedrick, P. W. (2005) A standardized genetic differentiation measure. Evolution, 59, 1633–1638.
    OpenUrlCrossRefPubMedWeb of Science
  27. ↵
    Heller, R. and Siegismund, H. R. (2009) Relationship between three measures of genetic differentiation GST, DEST and G’ST: how wrong have we been? Molecular Ecology, 18, 2080–2083.
    OpenUrlCrossRefPubMedWeb of Science
  28. ↵
    Jones, O. R. and Wang, J. (2010) colony: a program for parentage and sibship inference from multilocus genotype data. Molecular Ecology Resources, 10, 551–555.
    OpenUrl
  29. ↵
    Jost, L. (2008) GST and its relatives do not measure differentiation. Molecular Ecology, 17, 4015–4026.
    OpenUrlCrossRefPubMedWeb of Science
  30. ↵
    Kalinowski, S. T. (2005) hp-rare 1.0: a computer program for performing rarefaction on measures of allelic richness. Molecular Ecology Notes, 5, 187–189.
    OpenUrlCrossRefWeb of Science
  31. ↵
    Keller, L. F. and Waller, D. M. (2002) Inbreeding effects in wild populations. Trends in Ecology and Evolution, 17, 230–241.
    OpenUrlCrossRefWeb of Science
  32. ↵
    Keyghobadi, N., Roland, J., Matter, S. F. and Strobeck, C. (2005) Among- and within-patch components of genetic diversity respond at different rates to habitat fragmentation: an empirical demonstration. Proceedings of the Royal Society B, 272, 553–560.
    OpenUrlCrossRefPubMed
  33. ↵
    Kimura, M. (1980) A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences. Journal of Molecular Evolution, 16, 111–120.
    OpenUrlCrossRefPubMedWeb of Science
  34. ↵
    Kimura, M. and Weiss, G. H. (1964) The stepping stone model of population structure and the decrease of genetic correlation with distance. Genetics, 49, 561–576.
    OpenUrlFREE Full Text
  35. ↵
    Kraus, F. B., Weinhold, S. and Moritz, R. F. A. (2008) Genetic structure of drone congregations of the stingless bee Scaptotrigona mexicana. Insectes Sociaux, 55, 22–27.
    OpenUrlCrossRefWeb of Science
  36. ↵
    Lindauer, M. and Kerr, W. E. (1960) Communication between the workers of stingless bees. Bee World, 41, 29–41, 65–71.
    OpenUrl
  37. ↵
    Lorenzon, M. C. A., Conde, M. M. S. and Barbosa, C. G. (2006) Eusocial Apidae in tropical insular region. Brazilian Archives of Biology and Technology, 49, 733–738.
    OpenUrl
  38. ↵
    Mann, H. B. and Whitney, D. R. (1947) On a test of whether one of two random variables is stochastically larger than the other. The Annals of Mathematical Statistics, 18, 50–60.
    OpenUrlCrossRef
  39. ↵
    Marsden, C. D., Woodroffe, R., Mills, M. G. L., McNutt, J. W., Creel, S., Groom, R., et al. (2012) Spatial and temporal patterns of neutral and adaptive genetic variation in the endangered African wild dog (Lycaon pictus). Molecular Ecology, 21, 1379–1393.
    OpenUrlCrossRefPubMed
  40. ↵
    Michener, C. D. (2007) The Bees of the World, 2nd edn. Johns Hopkins University Press, Baltimore, MD.
  41. ↵
    Mueller, M. Y., Moritz, R. F. A. and Kraus, F. B. (2012) Outbreeding and lack of temporal genetic structure in a drone congregation of the neotropical stingless bee Scaptotrigona mexicana. Ecology and Evolution, 2, 1304–1311.
    OpenUrl
  42. ↵
    Nogueira-Neto, P. (1997) Vida e Criação de Abelhas Indígenas Sem Ferrão. Nogueirapis, São Paulo, SP.
  43. ↵
    Oliveira, R. C., Nunes, F. M. F., Campos, A. P. S., Vasconcelos, S. M., Roubik, D., Goulart, L. R. and Kerr, W. E. (2004) Genetic divergence in Tetragonisca angustula Latreille, 1811 (Hymenoptera, Meliponinae, Trigonini) based on RAPD markers. Genetics and Molecular Biology, 27, 181–186.
    OpenUrl
  44. ↵
    van Oosterhout, C., Hutchinson, W. F., Wills, D. P. M. and Shipley, P. (2004) micro-checker: software for identifying and correcting genotyping errors in microsatellite data. Molecular Ecology Notes, 4, 535–538.
    OpenUrlCrossRefWeb of Science
  45. ↵
    Palmer, K. A., Oldroyd, B. P., Quezada-Euán, J. J. G., Paxton, R. J. and May-Itzá, W.J. (2002) Paternity frequency and maternity of males in some stingless bee species. Molecular Ecology, 11, 2107–2113.
    OpenUrlPubMed
  46. ↵
    Paxton, R. J. (2000) Genetic structure of colonies and a male aggregation in the stingless bee Scaptotrigona postica, as revealed by microsatellite analysis. Insectes Sociaux, 47, 63–69.
    OpenUrl
  47. ↵
    Peakall, R. and Smouse, P. E. (2006) genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes, 6, 288–295.
    OpenUrlCrossRefWeb of Science
  48. ↵
    Peakall, R. and Smouse, P. E. (2012) GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research – an update. Bioinformatics, 28, 2537–2539.
    OpenUrlCrossRefPubMedWeb of Science
  49. ↵
    Peters, J. M., Queller, D. C., Imperatriz-Fonseca, V. L., Roubik, D. W. and Strassmann, J. E. (1999) Mate number, kin selection and social conflicts in stingless bees and honeybees. Proceedings of the Royal Society B, 266, 379–384.
    OpenUrlCrossRefWeb of Science
  50. ↵
    Piry, S., Luikart, G. and Cornuet, J.-M. (1999) BOTTLENECK: a computer program for detecting recent reductions in the effective size using allele frequency data. Journal of Heredity, 90, 502–503.
    OpenUrlCrossRefWeb of Science
  51. ↵
    Quezada-Euán, J. J. G., May-Itzá, W.J., Rincón, M., De la Rúa, P. and Paxton, R. J. (2012) Genetic and phenotypic differentiation in endemic Scaptotrigona hellwegeri (Apidae: Meliponini): implications for the conservation of stingless bee populations in contrasting environments. Insect Conservation and Diversity, 5, 433–443.
    OpenUrl
  52. ↵
    Di Rienzo, A., Peterson, A. C., Garza, J. C., Valdes, A. M., Slatkin, M. and Freimer, N. B. (1994) Mutational processes of simple-sequence repeat loci in human populations. Proceedings of the National Academy of Sciences of the United States of America, 91, 3166–3170.
    OpenUrlAbstract/FREE Full Text
  53. ↵
    Rousset, F. (2008) Genepop’007: a complete re-implementation of the genepop software for Windows and Linux. Molecular Ecology Resources, 8, 103–106.
    OpenUrl
  54. ↵
    Schwartz-Filho, D. and Laroca, S. (1999) A comunidade de abelhas silvestres (Hymenoptera, Apoidea) da Ilha das Cobras (Paraná, Brasil) aspectos ecológicos e biogeográficos. Acta Biológica Paranaense, 28, 19–108.
    OpenUrl
  55. ↵
    Silveira, F. A., Melo, G. A. R. and Almeida, E. A. B. (2002) Abelhas Brasileiras: Sistemática e Identificação. Fundação Araucária, Belo Horizonte, MG.
  56. ↵
    Slaa, E. J. (2006) Population dynamics of a stingless bee community in the seasonal dry lowlands of Costa Rica. Insectes Sociaux, 53, 70–79.
    OpenUrl
  57. ↵
    Steiner, J., Harter-Marques, B., Zillikens, A. and Feja, E. P. (2006) Bees of Santa Catarina Island, Brazil - a first survey and checklist (Insecta: Apoidea). Zootaxa, 1220, 1–18.
    OpenUrl
  58. ↵
    Stuchi, A. L. P.B., Ruvolo-Takasusuki, M. C. C. and Toledo, V. A. A. (2008) Análise da genética de populações em abelhas jataí (Tetragonisca angustula Latreille) por meio de isoenzimas. Magistra, 20, 68–77.
    OpenUrl
  59. ↵
    1. C.R.G. Souza,
    2. K. Suguio,
    3. A. M. S. Oliveira &
    4. P.E. Oliveira
    Suguio, K., Angulo, R. J., Carvalho, A. M., Corrêa, A. M., Tomazelli, L. J., Willwock, J. A. and Vital, H. (2005) Paleoníveis do mar e paleolinhas de costa. Quaternário do Brasil (eds C.R.G. Souza, K. Suguio, A. M. S. Oliveira & P.E. Oliveira), pp. 114–129. Associação Brasileira de Estudos do Quaternário, São Paulo.
  60. ↵
    Suguio, K., Tatumi, S. H., Kowata, E. A., Munita, C. S. and Paiva, R. P. (2003) Upper Pleistocene deposits of the Comprida Island (São Paulo State) dated by thermoluminescence method. Anais da Academia Brasileira de Ciências, 75, 91–96.
    OpenUrlGeoRefWeb of Science
  61. ↵
    Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M. and Kumar, S. (2011) MEGA5: Molecular Evolutionary Genetics Analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Molecular Biology and Evolution, 28, 2731–2739.
    OpenUrlCrossRefPubMedWeb of Science
  62. ↵
    Varvio, S.-L., Chakraborty, R. and Nei, M. (1986) Genetic variation in subdivided populations and conservation genetics. Heredity, 57, 189–198.
    OpenUrlCrossRefPubMedWeb of Science
  63. ↵
    van Veen, J. W. and Sommeijer, M. J. (2000a) Colony reproduction in Tetragonisca angustula (Apidae, Meliponini). Insectes Sociaux, 47, 70–75.
    OpenUrl
  64. ↵
    van Veen, J. W. and Sommeijer, M. J. (2000b) Observations on gynes and drones around nuptial flights in the stingless bees Tetragonisca angustula and Melipona beecheii (Hymenoptera, Apidae, Meliponinae). Apidologie, 31, 47–54.
    OpenUrl
  65. ↵
    Velez-Ruiz, R. I., Gonzalez, V. H. and Engel, M. S. (2013) Observations on the urban ecology of the Neotropical stingless bee Tetragonisca angustula (Hymenoptera: Apidae: Meliponini). Journal of Melittology, 15, 1–8.
    OpenUrl
  66. ↵
    Velthuis, H. H. W., Koedam, D. and Imperatriz-Fonseca, V. L. (2005) The males of Melipona and other stingless bees, and their mothers. Apidologie, 36, 169–185.
    OpenUrlCrossRef
  67. ↵
    Weir, B. S. and Cockerham, C. C. (1984) Estimating F-statistics for the analysis of population structure. Evolution, 38, 1358–1370.
    OpenUrlCrossRefPubMedWeb of Science
  68. ↵
    Whitfield, C. W., Behura, S. K., Berlocher, S. H., Clark, A. G., Johnston, J. S., Sheppard, W. S., et al. (2006) Thrice out of Africa: ancient and recent expansions of the honey bee, Apis mellifera. Science, 314, 642–645.
    OpenUrlAbstract/FREE Full Text
  69. ↵
    Wilson, G. A. and Rannala, B. (2003) Bayesian inference of recent migration rates using multilocus genotypes. Genetics, 163, 1177–1191.
    OpenUrlAbstract/FREE Full Text
  70. ↵
    Zanella, F. C. V. (2005) Abelhas da Ilha do Mel: estrutura da comunidade, relações biogeográficas e variação sazonal. História Natural e Conservação da Ilha do Mel (eds M.C.M. Marques & R.M. Britez), pp. 189–208. Editora da UFPR, Curitiba.
Back to top
Posted October 08, 2015.
Download PDF

Supplementary Material

Email
Genetic structure of the stingless bee Tetragonisca angustula
Flávio O. Francisco, Leandro R. Santiago, Yuri M. Mizusawa, Benjamin P. Oldroyd, Maria C. Arias
bioRxiv 026740; doi: https://doi.org/10.1101/026740
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools

Subject Area