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Genetic variability and population structure in Melipona
scutellaris (Hymenoptera: Apidae) from Bahia, Brazil,
based on molecular markers
Mara Tavares, Bruno Almeida, Paulo Passamani, Samuel Paiva, Helder
Resende, Lucio O. Campos, Rogério O. Alves, Ana Waldschmidt
To cite this version:
Genetic variability and population structure in
Melipona
scutellaris (Hymenoptera: Apidae) from Bahia, Brazil,
based on molecular markers
Mara Garcia TAVARES1,Bruno S. ALMEIDA2,Paulo Z. PASSAMANI1,Samuel R. PAIVA3, Helder C. RESENDE1,Lucio Antonio de O. CAMPOS1,Rogério Marcos de O. ALVES4,
Ana M. WALDSCHMIDT2
1
Departamento de Biologia Geral, Universidade Federal de Viçosa, 36570000, Viçosa, Minas Gerais, Brazil 2
Departamento de Ciências Biológicas, Universidade Estadual de Sudoeste da Bahia, 45200000, Jequié, Bahia, Brazil
3
Embrapa Recursos Genéticos e Biotecnologia, 70770000, Brasília, Distrito Federal, Brasil 4
Instituto Federal de Educação, Ciência e Tecnologia Baiano, 4172000, Salvador, Bahia, Brasil
Received 27 November 2012– Revised 2 May 2013 – Accepted 26 June 2013
Abstract– Melipona scutellaris is an important pollinator in natural and cultured areas from northeastern Brazil. Therefore, the goal of this work was to investigate the genetic diversity and population structure of M. scutellaris within its Bahia range, relating putative geographical influences on population dynamics. A total of 111 colonies from 13 municipalities in Bahia from sea level up to 1,011 m of altitude were sampled. Five species-specific codominant (microsatellites) and ten dominant (ISSR) primers were amplified, yielding from 2 to 13 alleles and 94 bands, respectively. The mean genetic diversity (He) was 0.50 for microsatellites and 0.33
for ISSR markers. AMOVA revealed that most of genetic variation is found within localities (82.6 % for microsatellites and 73.6 % for ISSR), and UPGMA and Bayesian analysis revealed the formation of two genetic groups related to altitude. Therefore, conservation strategies should take altitude variation into consideration to assure the genetic integrity of M. scutellaris.
conservation / ISSR / microsatellites / population genetics / stingless bee
1. INTRODUCTION
Melipona scutellaris (Latreille) is a stingless bee that inhabits hot and moist forests in northeastern Brazil, being found in the states of Bahia, Alagoas, Ceara, Pernambuco, Paraiba, Sergipe, and Rio Grande do Norte (Camargo and Pedro2008). Within this range, this species has been intensively raised because of high-quality honey production, the high number of
workers in colonies, and a well-established culture methodology.
However, as habitats have undergone severe disturbances caused by deforestation, use of in-secticides. and increased crop and pasture areas, the number of natural colonies of M. scutellaris has been decreasing. In this context, studies on the genetic variability and population structure of M. scutellaris may provide important data to support strategies to help its conservation and management. Morphological analysis demonstrated that M. scutellaris from the Bahia state could be clustered into three groups, related to the altitude of the sampling site (Nunes et al. 2007). According to
Corresponding author: A.M. Waldschmidt, [email protected]
Manuscript editor: Marina Meixner
these authors, the altitude might act as a geographic barrier to gene flow among populations.
Carvalho-Zilse et al. (2009) analyzed popula-tions of M. scutellaris from bee keepers in the Brazilian states of Pernambuco, Alagoas, Sergipe, and Bahia, and found an absence of genetic structure among populations, with higher genetic variability within groups than among them. This result was related to the intense activity of bee keepers who commonly exchange colonies.
To verify the levels of population structure and variability of M. scutellaris and their putative relationship with altitude range, genetic studies using species-specific microsatellite and ISSR markers were carried out in samples of this species from different regions of Bahia state.
2. MATERIALS AND METHODS 2.1. Biological material and DNA extraction
A total of 111 adult workers (1 per colony) of Melipona scutellaris were obtained from beekeepers, who maintained colonies in their homes, farms, meliponaries, and forests, from 13 locations in the Brazilian state of Bahia (TableI; Figure1). Genomic
DNA from the head and mesothorax was extracted according to Fernandes-Salomão et al. (2005).
2.2. Microsatellites markers
The DNA fragments were amplified using five microsatellites primers specifically designed for M. scutellaris. The PCRs were carried out with 10 ng of genomic DNA, 1× buffer, 0.2 M of each primer, 0.1 mM of each dNTP, 1.5 mM MgCl2, and 1U de Taq polimerase
( Go Taq Promega). Each forward primer was labeled with fluorescence 6-FAM (6-carboxy-fluorescein), HEX (hexacloro-6-carboxy-fluorescein) or NED (fluo-rescein benzoxanthene) (TableII). Amplifications were performed at an initial denaturation step of 94 °C/4 min, followed by 40 cycles of 93 °C/40s, specific annealing temperature of each primer/50s, and elongation step 72 °C/40s. Subsequently it was performed a final extension of 72 °C/5 min. PCR products were submitted for a capillary electrophoresis in an ABI 3100 genetic analyzer (Applied Biosystems). Allelic sizes were scored with the addition of 1 μL of freshly prepared ROX-labeled size standard (Brondani and Grattapaglia
2001) and the allele calling was performed using the GeneScan and Genotyper software (Applied Biosystems).
Table I. Sampled localities, geographic coordinates, altitude, and number of analyzed colonies ofMelipona scutellaris.
Locality/code Latitude Longitude Altitude (m) NS NI
Camaçari/CM 12°41'51''S 38°19'27''W 36 8 8
Itanagra/IT 12°15'47''S 38°22'76''W 44 – 4
Pojuca/PO 12°25'50''S 38°19'40''W 60 8 9
Catu/CT 12°21'11''S 38°22'44''W 100 5 12
Cruz das Almas/CA 12°40'12''S 39°06'07''W 220 4 –
Ruy Barbosa/RB 12°17'02''S 40°29'38''W 368 14 14 Amargosa/AM 13°00'03''S 39°37'10''W 900 – 9 Andaraí/AN 12°48'26''S 41°19'53''W 405 13 11 Mundo Novo/MN 12°03'02''S 40°29'43''W 500 39 14 Lafaiete Coutinho/LC 13°39'21''S 40°12'45''W 558 8 9 Lajedo do Tabocal/LT 13°28'30''S 40°13'23''W 875 2 2 Maracás/MA 13°26'28''S 40°25'51''W 877 6 10 Morro do Chapéu/MC 11°33'00''S 41°09'22''W 1,011 3 9 Total 110 111
NS Sampled number of colonies analyzed using SSR, NI sampled number of colonies analyzed using ISSR
2.3. ISSR markers
The amplifications by ten ISSR primers (TableII) were carried out with 10 ng of genomic DNA, 1× buffer, 1.5 mM MgCl2, 1U Taq polymerase (Biotools),
2.5 mM of each dNTP, and 0.10 μM of a single primer. Amplification reactions encompassed a first denaturation at 94ºC/3 min, followed by 40 cycles at 92ºC/1 min, 53ºC/2 min, 72ºC/ 2 min and a final extension step at 72ºC/7 min. All reactions included a negative control containing all PCR components but DNA and a positive control to confrim the reproducibil-ity of bands. Afterwards, the amplification products were run by electrophoresis in 1.2 % agarose gel immersed in TBE 1× (Tris-Borate 90 mM, EDTA 1 mM; pH 8.0). The bands were visualized and photodocumented using L-Pix EX system (Loccus Biotechnology).
2.4. Statistical analysis
For the microsatellites markers, the program TFPGA v.1.3 (Yeah et al. 1999) was used to calculate the following estimators of genetic diversity: allele frequen-cy, mean allele number/locus (A), expected (He) and
observed (Ho) heterozygosities, genetic distance among
T able II. Characteristics of the five microsatellites loci and ten ISSR primers utilized for the analyzes of Melipona scutellaris. Loci Repeat motif Primer sequences (5 ’-3 ’)T a (ºC) Allele size range (bp) KH o He SSR Mscut3 (A T A)4 F: NED ACTGCGACTTGCCAGCA TTC R: CTCGCGACACGCGA TTTCCA 69 90 –93 2 0.37 0.49 Mscut13 (AAA T)4 F: NED GGGAAAA TGT AGAAAGCT A G R: AACGCACGAAAA TTTGTCGT 64 96 –128 8 0.54 0.77 Mscut14 (ACC)8 F: HEX GA TCCGAGGACGA TCGCGTC R: CCGGGCGT AGCA T AAGTCAG 65 1 1 4– 129 5 0.85 0.59 Mscut18 (GA)28 F: FA M CCA TTCGCCGT A TTCGCGAA R: TGTCGAGGTGT AAGTGCTGG 57 209 –249 13 0.61 0.89 Mscut22 (GT A T)1 1 F : NED TTCCCT A TGT ACGAGCACCG R: ACACGCGGTGCA T ACA T ACG 62 145 –153 3 0.17 0.25 ISSR 0.32 a 0.33 a UBC 808 (AGA)3 (GAG)2 AGAGAGAGAGAGAGAGC 53 — 12 UBC809 (AGA)3 (GAG)3 AGAGAGAGAGAGAGAGG 53 — 11 UBC 81 1 (GAG)3 (AGA)2 GAGAGAGGAGAGAGAC 53 — 12 UBC 812 (GAG)3 (AGA)2 GAGAGAGAGAGAGAGAA 53 — 9 UBC 834 (AGA)3 (GAG)2 AGAGAGAGAGAGAGAGYT 53 — 8 UBC 827 (ACA)3 (CAC)2 ACACACACACACACACG 53 — 7 UBC 825b (ACA)3 (CAC)2 ACACACACACACACACT 53 — 8 UBC 889 (CA T)2 (GGT)2 CA TGGTGTTGGTCA TTGTTCCA 53 — 8 UBC 857 (ACA)3 (CAC)2 ACACACACACACACACYG 53 — 6 UBC 888 (CAC)2 (ACA)2 BDBCACACACACACACA 53 — 13 F and R Forwa rd an d reverse prim ers, respectively ,Ta annea ling temp eratur e, k numb er of alleles, Ho obse rved hete rozygo sity ,He expecte d hetero zygosi ty a Mean expec ted and observe d hete rozygo sity for all IS SR loci.
frequencies. In this analysis, the number of K populations (where K value is unknown) ranged from 1 to 11 with 10 runs in each K. A burn-in of 505iterations and 105 MCMC (Markov chain Monte Carlo) iterations were used, assuming admixture and independent allele frequen-cies. The results from STRUCTURE were analyzed via STRUCTURE HARVESTER Web v.0.6.9 according to Evanno et al. (2005) to determine the number of groups.
In the case of ISSR loci, the software TFPGA v.1.3 (Yeah et al. 1999) was used to calculate the genetic diversity (He), the percentage of polymorphic loci, and
UPGMA grouping. AMOVA (Excoffier et al. 1992) partitioned in two hierarchical levels (within and among localities), the structure index (ΦST), genetic distance
matrix and Mantel’s test were obtained using ARLEQUIN 3.5 (Schneider et al. 2000), and the reliability of the data was tested by 1,000 bootstrap replications. The Bayesian analysis of genetic diversity (HB) and population structure (ΦB) was obtained using the software HICKORY 1.1 (Holsinger et al.2002). The matrix of geographical distance was generated and plotted using DIVA-GIS 7.5 (Hijmans et al.2001). In the cluster analysis using STRUCTURE v.2.3.3 (Falush et al.2007), the parameters were: K from 1 to 12 with 20 runs for each k, burn-in of 104 iterations, followed by 104MCMC iterations assuming correlated allele frequencies and admixture model. These results were analyzed using STRUCTURE HARVESTER Web v.0.6.9 (Evanno et al.2005).
3. RESULTS
3 .1. Po ly mor phism a nd p opulation variability
In the five microsatellite loci analyzed in this study, the number of alleles ranged from 2 (Mscut3) to 13 (Mscut18) (mean: 6.2) (TableII). The allelic frequency observed in these loci can be seen in Table III. Private alleles were found in samples from Camaçari (Mscut18/J and Mscut22/ C), Catú (Mscut13/B), Maracás (Mscut14/A), and Mundo Novo (Mscut13/C, I and Mscut18/A). Genotype frequencies showed that individual samples were in Hardy–Weinberg equilibrium (P<0.05) for most of the studied loci (TableIII).
The expected (He) and observed
heterozygos-ities (Ho) among samples ranged from 0.32 to
0.69 (mean: 0.50) and from 0.27 to 0.70 (mean: 0.47), respectively.
The ten ISSR primers yielded 94 bands, with 77.65 % of polymorphic loci (polymorphism criterion of 99 %). The mean number of bands per primer was 9.4. The primer UBC-888 pro-duced the highest number of fragments (13), while UBC-857 resulted in the lowest fragment number (6). Unbiased genetic diversity (He) (Nei 1978),
assuming Hardy–Weinberg equilibrium was 0.33 and genetic diversity (HB) was 0.30.
3.2. Genetic structure
Considering the microsatellites markers, the genetic distances among samples ranged from 0.044 (Camaçari and Pojuca) to 0.702 (Camaçari and Andaraí), determining the formation of two groups in the cluster analysis. Based on the defined cutting point in the dendrogram, the first group comprised the samples located at low altitudes (36–220 m), near Salvador and the Recôncavo region (Cruz das Almas). The second group included the samples from inner parts of Bahia state situated at medium to high altitudes. Within this latter group, two subgroups could be noted, one formed by samples from altitudes ranging from 368 to 500 m, and the other with samples from higher altitudes (558–1,011 m) (Figure2a). The high FSTvalue found (0.22) corroborates this
genetic differentiation among samples from low and medium/high altitudes.
The UGPMA grouping based on ISSR markers resulted essentially in the same two clusters (Figure2c). The first one encompassed the colonies from central-northern (Ruy Barbosa, Morro do Chapéu, and Mundo Novo) and central-southern (Andaraí, Lafaiete Coutinho, Lajedo do Tabocal, Maracás, and Amargosa) regions in Bahia, ranging from 368 to 1,011 m of altitude. The second cluster, in turn, included the populations nearby Salvador (Catú, Itanagra, Camaçari, and Pojuca), from 36 to 100 m above sea level. However, the bootstrap values found were low and require further sampling within colonies of M. scutellaris.
Table III. Allele frequencies estimated for the five microsatellites loci isolated fromMelipona scutellaris. Allele Loci
Mscut3 Mscut13 Mscut14 Mscut18 Mscut22
A 0.5693 0.1520 0.0500a,b 0.0050a,b 0.8563 B 0.4307 0.0049a,b 0.0200b 0.0350b 0.1322 C 0.0833a 0.0750 0.0900 0.0115a D 0.3578 0.2900 0.0300b E 0.2402 0.5650 0.1300 F 0.0147b 0.0550b G 0.1373 0.0700 H 0.0098a,b 0.0450b I 0.1400 J 0.2100a K 0.0350b L 0.1050 M 0.0500b a
Presence of private allele.
b
Loci in Hardy–Weinberg equilibrium (p<0.05)
81 64 74 68 69 66 40 76 66 Camaçari Pojuca Cruz das Almas Catú Andaraí Mundo Novo Ruy Barbosa Lajedo do Tabocal Morro do Chapéu Lafaiete Coutinho Maracás P R O B A B I L I T Y POPULATION CM PO CTCA RB AN MN LF LTMAMC Mundo Novo Andaraí Ruy Barbosa Lafaiete Coutinho Catú Itanagra Camaçari Pojuca Maracás Lajedo do Tabocal Amargosa Morro do Chapéu 92 93 80 38 45 14 30 64 68 42 P R O B A B I L I T Y POPULATION CT IT P0 CM LC MA LTAM RB MN AN MC
a
b
c
d
Figure 2. Unweighted pair–group method using an arithmetic average (UPGMA) dendrogram and Bayesian clustering of Melipona scutellaris populations from Bahia state, based on microsatellites (a, b) and ISSR (c, d) data, revealing two genetic groups (k=2). In The STRUCTURE cluster analyses, the vertical lines indicate the individuals and the colors show the allele frequencies. Population abbreviations are defined in TableI.
HARVESTER Web (Figure 2b, d) confirms the results from UPGMA. Mantel’s test showed significativa association between geographic dis-tance and dissimilarity values (r=0.17, P<0.001). Two-hierarchical AMOVA showed that 17.4 % of the total genetic variation estimated from microsatellites was among samples, whereas 82.6 % was due to intrapopulational variation. Similarly, a higher percentage of variation (73.6 %) was observed within samples by ISSR markers (TableIV). The AMOVA,ΦST(0.264, P<0.001)
and the genetic structure based on Bayesian analysis (θB=0.30) confirmed the genetic differ-entiation.
4. DISCUSSION
In this study, both dominant (ISSR) and codom-inant (microsatellites) markers yielded similar re-sults of low levels of genetic diversity (He=0.33
and 0.50, respectively). Several authors have reported reduced genetic variation in other stingless bee species using species-specific microsatellite primers. For instance, Lopes et al. (2010) observed He=0.43 for M. rufiventris and He=0.38 for M.
mondury.
The low genetic variability of hymenopterans, particularly in Meliponini, is associated with genetic, biological, and environmental aspects, such as the mating system in which a queen mates with a single male (Strassmann 2001), small effective size (Graur1985), swarming strategies (new colonies are established closed to mother colony) that favor inbreeding, and limited dis-persal of species (Nogueira-Neto 1954). These traits are intensified in fragmented landscapes that also restrain the bees’ dispersal and nesting abilities (Lopes et al.2010).
In agreement with the abovementioned in-ferences, AMOVA revealed a reduced gene flow among studied populations in as much as the higher percentage of variation was found within samples (82.6 % for microsatellites and 73.6 % for ISSR) than among samples. Moreover, the presence of exclusive alleles in populations from Camaçari (Mscut18/J and Mscut22/C) and Mundo Novo (Mscut13/C, I and Mscut18/A) reinforce the interpopulation structure.
Similarly, the allele distribution among popula-tions shows that M.scutellaris is genetically struc-tured. For example, the allele A from locus Mscu14 and alleles C and H from locus Mscut13 were exclusively present in samples from medium to high altitudes (227–1,100 m). On the other hand, the allele B from locus Mscut13 and alleles J and C from locus Mscut22 were detected only in low altitude samples (36–220 m).
The genetic structure index (ΦST: 0.528 for
microsatellites, 0.264 andθB=0.30 for ISSR; P< 0.001), Bayesian analysis using STRUCTURE (K = 2), and UPGMA showed a remarkable genetic structure, separating the samples in two large groups. The first group comprised the colonies from 36 to 220 m and the second cluster was composed of samples from 368 to 1,100 m above sea level. Such a division is similar to the grouping reported by Nunes et al. (2007) based on morphometric data in M. scutellaris.
Mantel’s test showed a positive and significant correlation (r=0.17, P<0.001) between geographic and genetic distances, i.e., the more distant the samples are located, the higher their genetic differentiation. The highest value of genetic distance (0.702) was observed between Camaçari (coastal region) and Andaraí (countryside of Bahia), while
Table IV. Analysis of molecular variance (AMOVA) and degrees of freedom (df) for microsatellites and ISSR markers in samples of Melipona scutellaris from Bahia.
SSR ISSR p value
Source of variation df % variation F statistic df % variation F statistic
Among localities 1 17.39 ΦST= 0.528 11 26.41 ΦST=0.264 <0.001
the lowest distance (0.044) was found between coastal populations (Camaçari and Pojuca).
Nevertheless, whether or not altitude plays a key role in the dispersal of stingless bee popula-tions remains an open question. Indeed, the genetic divergence reported here might be closely related to peculiar climate conditions of each locality within the altitude range. This combination of environmental features could act as a barrier to gene flow among samples.
Under this perspective, the municipalities at coastal regions are characterized by a humid to subhumid weather, with mean temperatures from 19 to 25ºC and high annual rainfall index, up to 2,001 mm/year. Inversely, the localities within middle to high altitudes are in semiarid region with subhumid to dry climate, mean temperature of 20–26º C and rainfall lower than 1,200 mm/year (SEI 2007; Alves et al. 2012). In fact, the differential temperature, humidity, rainfall, and levels of secondary com-pounds along altitude gradients might influence the distribution of organisms, mainly insects (Carneiro et al.1995).
Therefore, evaluating the genetic structure of M. scutellaris populations within different alti-tudes and environmental conditions is essential for defining effective management and conser-vation policies, once genetically differentiated populations have been reported.
ACKNOWLEDGMENTS
The authors are grateful to Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB), Fundação de Amparo à Pesquisa do estado de Minas Gerais (FAPEMIG), and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for the financial support. We also thank Dr. Paulo Roberto Antunes de Mello Affonso for suggestions on the manuscript, and Dr. Leonardo Lopes Bhering, and Dr. Cosme Damião Cruz from Universidade Federal de Viçosa for statistical assistance using the software GENES.
Variabilité génétique et structure de la population de Melipona scutellaris (Hymenoptera: Apidae) de Bahia (Brésil), déterminées à l’aide de marqueurs moléculaires
Conservation des espèces / microsatellites / génétique des populations / abeille sans aiguillon / ISSR
Genetische Variabilität und Populationsstruktur, untersucht anhand molekularer Marker, von Melipona scutellaris (Hymenoptera: Apidae) in Bahia (Brasilien)
N a t u r s c h u t z / I S S R / M i k ro s a t e l l i t e n / Populationsgenetik / stachellose Bienen
REFERENCES
Alves, R.M.O., Carvalho, C.A.L., Souza, B.A., Santos, W.S. (2012) Areas of Natural Occurrence of Melipona scutellaris Latreille, 1811(Hymenoptera: Apidae) in the state of Bahia. An. Acad. Bras. Ciênc. Brazil 84, 679–688 Brondani, R.P.V., Grattapaglia, D. (2001) Cost-effective method to synthesize a fluorescent internal DNA standard for automated fragment sizing. Biotechniques 31, 793–800
Camargo, J.M.F., Pedro, S.R.M. (2008) Meliponini Lepeletier, 1836. In: Moure, J.S., Urban, D., Melo, G.A.R. (eds.) Catalogue of Bees (Hymenoptera, Apoidea) in the Neotropical Region, pp. 272–578. Sociedade Brasileira de Entomologia, Paraná, Brasil Carneiro, M.A.A., Ribeiro, S.P., Fernandes, G.W. (1995) Artrópodes de um gradiente altitudinal na Serra do Cipó. Rev. Bras. Entomol Minas Gerais 39, 597–604
Carvalho-Zilse, G.A., Costa-Pinto, M.F.F., Nunes-Silva, C.G., Kerr, W.E. (2009) Does beekeeping reduce genetic variability in Melipona scutellaris (Apidae, Meliponini)? Gen. Mol. Res. 8, 758–765
Cruz, C.D. (2012) Programa Genes: Aplicativo Computacional em Genética e Estatística. Versão Windows– 2012. Viçosa, UFV
Evanno, G., Regnaut, S., Goudet, J. (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol. Ecol. 14, 2611–2620 Excoffier, L., Smouse, P.E., Quattro, J.M. (1992) Analyses of molecular variance inferred from metric distances among DNA haplotypes: application to human mito-chondrial DNA restriction data. Genetics 131, 479– 491
Falush, D., Stephens, M., Pritchard, J.K. (2007) Infer-ence of population structure using multilocus geno-type data: dominant markers and null alleles. Mol. Ecol. Notes 7, 574–578
Fernandes-Salomão, T.M.F., Rocha, R.B., Campos, L.A.O., Araújo, E.F. (2005) The first internal transcribed spacer (ITS-1) of Melipona species (Hymenoptera: Apidae, Meliponini):
tion and phylogenetic analysis. Insectes Soc. 52, 11– 18
Graur, D. (1985) Gene diversity in Hymenoptera. Evolution 39, 190–199
Hijmans, R.J., Guarino, L., Cruz, M., Rojas, E. (2001) Computer tools for spatial analysis of plant genetic resources data: 1. DIVA-GIS. Plant. Gen. Res. Newsletter 127, 15–19
Holsinger, K.E., Lewis, P.O., Dey, D.K. (2002) A Bayesian approach to inferring population structure from dominant markers. Mol. Ecol. 11, 1157–1164 Lopes, D.M., Campos, L.A.O., Fernandes Salomão,
T.M., Tavares, M.G. (2010) Comparative study on the use of specific and heterologous microsatellite primers in the stingless bees Melipona rufiventris and M. mondury (Hymenoptera, Apidae). Gen. Mol. Biol. 33, 390–393
Nei, M. (1978) Estimation of avarage heterozygosity and genetic distance from a small number of individuals. Genetics 89, 583–590
Nogueira-Neto, P. (1954) Notas bionômicas sobre meliponíneos: III Sobre a enxameagem. Arq. Mus. Nac. 42, 419–451
Nunes, L.A., Costa-Pinto, M.F.F., Carneiro, P.L.S., Pereira, D.G., Waldschmidt, A.M. (2007) Divergência genética em Melipona scutellaris Latreille (Hymenoptera: Apidae) com base em caracteres morfológicos. Biosci. J. 23, 1–9
Schneider, S., Roessli, D., Excoffier, L. (2000) Arlequin version 2.000: A software for population genetic data analysis. Genetics and Biometry Laboratory, University of Geneva, Switzerland
SEI (2007) SIDE- Sistema de Dados Estatísticos [online]
ht tp: //www.sei.ba.gov.br/index.php? option= com_content&view=article&id=113&Itemid=62
(accessed on 10 April 13)
Strassmann, J.E. (2001) The rarity of multiple mating by females in the social Hymenoptera. Insectes Soc. 48, 01–13
Wright, S. (1978) Evolution and the genetics of populations. Variability within and among natu-ral populations. University of Chicago Press, Chicago
