Research Article |
Corresponding author: Janisete Silva ( jgs10@uol.com.br ) Corresponding author: Anna Rodolfa Malacrida ( malacrid@unipv.it ) Academic editor: Jorge Hendrichs
© 2015 Mosè Manni, Katia Manuela Lima, Carmela Rosalba Guglielmino, Silvia Beatriz Lanzavecchia, Marianela Juri, Teresa Vera, Jorge Cladera, Francesca Scolari, Ludvik Gomulski, Mariangela Bonnizoni, Giuliano Gasperi, Janisete Silva, Anna Rodolfa Malacrida.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Manni M, Lima KM, Guglielmino CR, Lanzavecchia SB, Juri M, Vera T, Cladera J, Scolari F, Gomulski L, Bonizzoni M, Gasperi G, Silva JG, Malacrida AR (2015) Relevant genetic differentiation among Brazilian populations of Anastrepha fraterculus (Diptera, Tephritidae). In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 157-173. https://doi.org/10.3897/zookeys.540.6713
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We used a population genetic approach to detect the presence of genetic diversity among six populations of A. fraterculus across Brazil. To this aim, we used Simple Sequence Repeat (SSR) markers, which may capture the presence of differentiative processes across the genome in distinct populations. Spatial analyses of molecular variance were used to identify groups of populations that are both genetically and geographically homogeneous while also being maximally differentiated from each other. The spatial analysis of genetic diversity indicates that the levels of diversity among the six populations vary significantly on an eco-geographical basis. Particularly, altitude seems to represent a differentiating adaptation, as the main genetic differentiation is detected between the two populations present at higher altitudes and the other four populations at sea level. The data, together with the outcomes from different cluster analyses, identify a genetic diversity pattern that overlaps with the distribution of the known morphotypes in the Brazilian area.
Anastrepha fraterculus , microsatellites, population genetic differentiation, morphotypes
The South American fruit fly Anastrepha fraterculus Wiedemann (Diptera: Tephritidae) belongs to the fraterculus group, which comprises a total of 34 formally described species (
The nominal species A. fraterculus is widely distributed from the Rio Grande Valley in northern Mexico to central Argentina, infesting over 100 hosts (
A. fraterculus has long been reported to show extensive morphological variation along its geographic distribution (
Genetic studies performed on A. fraterculus populations so far have revealed the following putative biological entities based on geography: an Andean lineage (
Previous genetic studies using DNA sequencing of mitochondrial genes from different populations suggested that both the fraterculus group and the A. fraterculus complex have a recent evolutionary history, and thus molecular markers with a higher power of resolution were required to help understand the specific/subspecific differentiation within and between populations of this group (
From an applied perspective, the correct identification of populations and species is an important step in the implementation of biologically-based control methods such as the Sterile Insect Technique (SIT) against this fruit fly complex (
This paper is centred on the assessment of genetic diversity among A. fraterculus populations from distinct geographic regions across Brazil, most likely belonging to at least three distinct morphotypes (Silva et al. unpubl. data). For this purpose we used highly informative SSR markers, which may capture the presence of eventual differentiative processes across the genome in different populations.
Six populations from three regions across Brazil were sampled from 2007 to 2013 (Table
Field collected samples of Anastrepha fraterculus Brazilian populations.
States | Sample site | Morphotype* | Host | Coordinate | Elevation |
---|---|---|---|---|---|
Rio Grande do Norte (RN) | Monte Alegre | ? | Guava | 6.0678W; 35.3322S | 51.816m |
Bahia (BA) | Una | 3 | Guava | 15.2933W; 39.0753S | 27.737m |
Bahia (BA) | Porto Seguro | ? | Guava | 16.4497W; 39.0647S | 48.768m |
Espírito Santo (ES) | São Mateus | ? | Araçá | 18.7161W; 39.8589S | 35.966m |
São Paulo (SP) | Campos do Jordão | 1 | Raspberry | 22.7394W; 45.5914S | 1627.9m |
Rio Grande do Sul (RS) | Vacaria | 1 | Guava | 28.5122W; 50.9339S | 970.79m |
A total of 171 A. fraterculus individuals collected from the above mentioned populations were assessed for their SSR variability. DNA was extracted from three legs of each single fly using the “DNeasy Blood & Tissue” kit (Qiagen, Valencia, CA) following the standard DNeasy protocol. DNA samples were screened using the following ten microsatellite loci: AfD4, AfD105, AfA7, AfA112, AfA115, AfA120, AfA122, AfA117, AfA10, and AfC103 (
The mean number of alleles (na) and mean null allele frequency (An) (non-amplifying alleles due to changes in the primer binding regions), expected and observed heterozygosity were estimated using GENEPOP version 4.0.7 (
Microsatellite Analyzer (MSA) (
The variability estimates describing the suitability of the ten SSR loci (AfD4, AfD105, AfA7, AfA112, AfA115, AfA120, AfA122, AfA117, AfA10, and AfC103) for detecting the presence of differentiation among the A. fraterculus populations are shown in Table
Microsatellite variability detected across the six Brazilian Anastrepha fraterculus populations.
Locus | na | Min–Max | PIC |
---|---|---|---|
D4a | 7 | 2–5 | 0.56 |
D105a | 15 | 5–11 | 0.72 |
A7a | 13 | 7–11 | 0.83 |
A112a | 18 | 8–12 | 0.82 |
A115a | 14 | 7–12 | 0.80 |
A120a | 15 | 7–13 | 0.88 |
A122a | 12 | 5–9 | 0.74 |
A117a | 11 | 6–9 | 0.77 |
A10a | 13 | 2–11 | 0.44 |
C103a | 11 | 7–9 | 0.80 |
Mean | 12.9 | 5.6–10.2 | 0.74 |
Tests for Hardy-Weinberg equilibrium (HWE) using Fisher’s exact test with the sequential Bonferroni correction (
An estimate of variability distribution in and among the six tested populations (AMOVA) indicates that 90% of the variation occurs within populations while only about 10% of total variation is detected among populations. Indeed as shown in Table
Genetic variability of wild populations of Anastrepha fraterculus from different geographical regions in Brazil estimated using 10 SSRs.
na | He | Ho | FIS | |
---|---|---|---|---|
Una-BA | 7,7 | 0,63 | 0,54 | 0,14 |
Porto Seguro-BA | 8,2 | 0,70 | 0,67 | 0,02 |
Monte Alegre-RN | 7,5 | 0,68 | 0,57 | 0,20 |
São Mateus-ES | 6,3 | 0,66 | 0,66 | 0,08 |
Campos do Jordão-SP | 8,3 | 0,71 | 0,61 | 0,13 |
Vacaria-RS | 8,5 | 0,72 | 0,62 | 0,12 |
Spatial Analysis of Molecular Variance (SAMOVA) for different population partitions.
Number of groups (K) | F CT | P | Population partition |
2 | 0.195 | 0.062 | (Una, Porto Seguro, Monte Alegre, São Mateus), (Campos do Jordão, Vacaria) |
3 | 0.182 | 0.015 | (Una, Porto Seguro, São Mateus), (Monte Alegre), (Campos do Jordão, Vacaria) |
4 | 0.190 | 0.050 | (Una, Porto Seguro, São Mateus), (Monte Alegre), (Campos do Jordão), (Vacaria) |
5 | 0.196 | 0.068 | (Una, Porto Seguro), (São Mateus), (Monte Alegre), (Campos do Jordão), (Vacaria) |
Pairwise-FST values among 6 population samples of Anastrepha fraterculus as derived from Microsatellite Analyser (
Una-BA | Porto Seguro-BA | Monte Alegre-RN | São Mateus-ES | Campos do Jordão-SP | Vacaria-RS | |
---|---|---|---|---|---|---|
Una-BA | - | |||||
Porto Seguro-BA | 0.015 ns | - | ||||
Monte Alegre-RN | 0.020 | 0.012 ns | - | |||
São Mateus-ES | 0.031 | 0.031 | 0.042 | - | ||
Campos do Jordão-SP | 0.163 | 0.127 | 0.130 | 0.160 | - | |
Vacaria-RS | 0.165 | 0.126 | 0.132 | 0.175 | 0.038 | - |
With this paper we initiated, in the polymorphic A. fraterculus complex, an analysis of the underpinning genetic architecture and its interaction with correlated ecological, biological and morphological traits. In this context, we have used microsatellite markers to perform a genetic analysis of populations from a complex ecological area such as Brazil.
Although the chromosomal location of the considered SSR loci remains unknown, the assessed linkage equilibrium between them suggests they are statistically independent and that their variability patterns might reflect genome-wide patterns across populations. The six considered ecogeographic populations are here represented by highly polymorphic samples, which reflect a high degree of intrapopulation genetic diversity. Indeed only 10% of the total variability (AMOVA) is represented by the differences between the six geographic populations, while greater variability was found within populations.
The spatial analysis of genetic diversity indicates that the levels of diversity among the six populations vary significantly on an eco-geographical basis, as indicated by SAMOVA and PCoA data. More than by geographical distance, the genetic differentiation is influenced by altitude. The multivariate analysis of ten microsatellites depicts a structural pattern, which clearly separates populations on climatic distribution both on latitudinal and altitudinal basis. Particularly, altitude seems to represent a differentiating adaptation, as the main genetic differentiation is that detected between the populations present at higher altitudes (Campos de Jordão and Vacaria) and those populations from sea level. Genetic divergence between populations from low and high altitude areas has already been observed for populations within the A. fraterculus complex using isozymes (
One interesting observation, which arises from our data, is that the observed structure of Brazilian populations is entangled with the presence of morphotypes. The actual number of these entities and their respective geographic range are questions that remain to be further elucidated. At the moment three different morphotypes are identified in Brazil (
The population genetic approach, in addition to improving our knowledge of the underpinning genetic architecture of the A. fraterculus complex, is also important from an applied perspective. The overall level of genetic variability and the presence of differentiation that we detected among the Brazilian populations of A. fraterculus constitute an important contribution for any potential future application of SIT for the control of populations of this fruit fly pest in Brazil.
We are grateful to Iara Joachim-Bravo, Adalécio Kovaleski, Adalton Raga, and Miguel Francisco de Souza Jr for providing some of the specimens used in this study and to Roberto A. Zucchi, Keiko Uramoto, and Elton L. Araujo for specimen identification. We thank Jorge Hendrichs for his support for the development of this study and for his comments on an earlier version of this manuscript. Thanks are also due to Carter Robert Miller for reviewing this manuscript. This study had financial support from a FAO/IAEA Research Contract No. 16059 as part of the Coordinated Research Project on “Resolution of cryptic species complexes of tephritid pests to overcome constraints to SIT and international trade” to JGS in which ARM was also involved as a member. Further financial support came from FAO/IAEA Technical Contract No. 16966 to GG. This work is part of the PhD thesis of KLM, which was performed at the Dept. of Biology & Biotechnology, Univ. of Pavia. KLM was a recipient of a doctoral fellowship from Fundação de Amparo à Pesquisa do Estado da Bahia (FAPESB) and a “sandwich fellowship” from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) during her stay at the University of Pavia. JGS is a fellow researcher (grant 305452/2012-6) of the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).