Next Article in Journal
An Assessment Model for Agricultural Databases: The Arthropod Pesticide Resistance Database as a Case Study
Previous Article in Journal
Evidence of Cuticle Chemicals of Heortia vitessoides (Lepidoptera: Crambidae) Larvae Influencing the Aggregation Behavior of Conspecific Larvae
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Insects
Volume 15
Issue 10
10.3390/insects15100748
insects-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Molecular Markers for Analyses of Genetic Diversity within the Anastrepha fraterculus Complex with Emphasis on Argentine Populations

by
Ludvik M. Gomulski
1,
María Teresa Vera
2,
Silvia B. Lanzavecchia
3,
Riccardo Piccinno
1,
Giulia Fiorenza
1,
Daniel De Luca
1,
Beatriz N. Carrizo
4,
Juan Pedro R. Bouvet
5,
Valeria A. Viana
5,
Carlos Cárceres
6,
Walther Enkerlin
6,
Anna R. Malacrida
1 and
Giuliano Gasperi
1,*
1
Department of Biology and Biotechnology, University of Pavia, 27100 Pavia, Italy
2
Facultad de Agronomía, Zootecnia y Veterinaria, Universidad Nacional de Tucumán, Tucumán T4100, Argentina
3
Laboratorio de Insectos de Importancia Agronómica, Instituto de Genética Ewald A. Favret (INTA), Buenos Aires B1713, Argentina
4
Estación Experimental Agrícola Famaillá, Instituto Nacional de Tecnología Agropecuaria (INTA), Tucumán T4132, Argentina
5
Grupo de Protección Vegetal, EEA Concordia, Instituto Nacional de Tecnología Agropecuaria (INTA), Entre Ríos E3200, Argentina
6
Insect Pest Control Section, Joint FAO/IAEA Centre, 1400 Vienna, Austria
*
Author to whom correspondence should be addressed.
Insects 2024, 15(10), 748; https://doi.org/10.3390/insects15100748
Submission received: 23 August 2024 / Revised: 17 September 2024 / Accepted: 25 September 2024 / Published: 27 September 2024
(This article belongs to the Section Insect Molecular Biology and Genomics)
Browse Figures
Versions Notes

Abstract

:

Simple Summary

The South American fruit fly Anastrepha fraterculus (Wiedmann) is found from northern Mexico to northern Argentina, where it causes damage to many different wild and cultivated fruits. It is a not a single species, but a complex of practically identical species. Eight morphological types (morphotypes) have been identified. To facilitate the identification of the species, alternative, non-morphological methods, such as those based on genome sequences, are necessary. The sterile insect technique is an efficient method used to combat these pests, which involves the release of many sterile male insects into the wild. Mass-reared sterile field-released males mate with females, which lay inviable eggs, thereby reducing the population. This approach is only successful when the released males are sexually compatible with the females of the target population. Hence, accurate identification is necessary for its success. We evaluated the use of the internal transcribed spacer 2 (ITS2) sequence for discriminating members of the A. fraterculus cryptic species complex and a related species, Anastrepha schultzi Blanchard. The ITS2 sequence successfully discriminated between different morphotypes and provides a basis for the development of keys for discrimination of the species within the complex. ITS2 also represents an important marker for the poorly studied species A. schultzi.

Abstract

The South American fruit fly Anastrepha fraterculus (Wiedmann) has a vast range extending from northern Mexico, through Central America, to South America where it is an extremely polyphagous pest of wild and cultivated fruits. It is a complex of cryptic species currently composed of eight recognised morphotypes: “Mexican”, “Venezuelan”, “Andean”, “Peruvian”, “Ecuadorian”, and the three Brazilian morphotypes “Brazilian-1”, “Brazilian-2”, and “Brazilian-3”. Molecular markers that can identify the member species of the complex are crucial for the implementation of effective pest control measures, such as the sterile insect technique. The object of this study was to evaluate the use of the internal transcribed spacer 2 (ITS2) sequence for discriminating several members of the A. fraterculus cryptic species complex (Mexican, Peruvian, and Brazilian-1) and a related species, Anastrepha schultzi Blanchard. The analysis highlighted significant genetic differentiation between the evaluated morphotypes, allowed their discrimination within the A. fraterculus cryptic species complex, and provided new insights into their genetic relationships. The ITS2 marker provides a basis for the development of taxonomic keys for the discrimination of the cryptic taxa within the A. fraterculus cryptic species complex. ITS2 also represents an important marker for the poorly studied species A. schultzi.

1. Introduction

Accurate species identification is essential for effective pest eradication programmes. This can be especially difficult when rapid species radiation has produced several closely related cryptic species. Among the true fruit flies (Diptera: Tephritidae), and within the genus Anastrepha, the fraterculus species group includes at least 34 species [1,2]. One member of the fraterculus species group, A. fraterculus (Wiedemann), is commonly referred to as the South American fruit fly. This extremely polyphagous pest of cultivated fruits, has a vast range extending from northern Mexico to South America [3,4,5]. Anastrepha fraterculus has long been known to be a cryptic species complex, with Stone [6,7], in 1942, describing extensive morphological variation throughout its range. Numerous studies using a variety of characteristics including egg morphology, karyotype, isozymes, multivariate analysis, and mating compatibility have identified eight forms, morphotypes, or putative species in the cryptic species complex [3,8,9,10,11,12,13,14,15,16,17]. Three of the morphotypes are Brazilian: “Brazilian-1”, which also includes populations from Argentina, Paraguay, Boliva, and highland southeastern Peru, “Brazilian-2”, and “Brazilian-3”. The other morphotypes are “Mexican”, including populations from Mexico, Costa Rica, Colombia, Guatemala, and Panama; “Venezuelan”, from the lowlands of Venezuela and the Caribbean; “Andean”, from the highlands of Venezuela and Colombia; “Ecuadorian”, from the highlands of Ecuador and Peru; and “Peruvian”, from the lowlands of Peru and Ecuador and southern Colombia [8,18].
The identification of these distinct morphotypes within the range of A. fraterculus stimulated the search for correlated molecular markers. The development of such markers is crucial for identifying the target species, allowing effective pest control measures, such as the sterile insect technique (SIT), to be implemented. The SIT is an environmentally friendly strategy involving the inundation of an area with sterile male insects. These males mate with wild females, thereby reducing the population. This approach yields significant results when the released males belong to the same species or strain as the target population. However, it becomes ineffective if the sterile and target populations are not of the same species or if their mating behaviour is incompatible. Hence, accurate identification is pivotal for the success of this method.
Among the molecular markers previously studied was the mitochondrial cytochrome oxidase I gene (COI). This gene is well conserved at the intraspecific level, but often differs sufficiently between species to define interspecific boundaries [19]. Although COI has been shown to discriminate many species within the genus Anastrepha, it is unable to resolve many members of the fraterculus species group [20,21], and even less so members of the A. fraterculus cryptic species complex. A more promising molecular marker, the ribosomal internal transcribed spacer 1 (ITS1), was analysed by Sutton and colleagues from wild samples of the A. fraterculus cryptic species complex from Argentina, Bolivia, Peru, Ecuador, Colombia, Brazil, Venezuela, Guatemala, and Mexico [18]. The authors identified four non-randomly distributed ITS1 sequence groups, consistent with the known morphotypes [18]. Prezotto and colleagues [8] used a combined analysis of ITS1 and morphometric data to discriminate six members of the A. fraterculus cryptic species complex (Brazilian-1, Brazilian-2, Brazilian-3, Peruvian, Andean, and Mexican) and found that morphometric characterisation based on female wing shape was highly congruent with genetic data obtained through ITS1 analysis, which revealed specific sequences for each morphotype. Scally and colleagues [22] used nine loci (seven nuclear and two mitochondrial) and found incongruences between the nuclear and mitochondrial datasets, which they hypothesised was a result of introgression to which mitochondrial markers are more susceptible. Barr and colleagues [23], using a fragment of the ribosomal internal transcribed spacer 2 (ITS2) sequence, were able to distinguish Anastrepha suspensa (Loew) from other species of Anastrepha, including members of the fraterculus cryptic species complex, indicating the utility of the ITS2 marker for Anastrepha species identification. Selivon and colleagues [12] used an integrated analysis of multiple biological characteristics (mitotic chromosomes, ITS1, mating behaviour, and wing shape) on three morphotypes of the A. fraterculus cryptic species complex present in Brazil (Brazil-1, Brazil-2, and Brazil-3), and found morphotype-specific differences in the sex chromosomes and ITS1 sequences. The ITS1 sequence has also recently been successfully used in a phylogeographical analysis that considered individuals from 73 localities in 10 countries across the Americas [24].
The objective of this study is to evaluate the use of a larger fragment comprising part of the 5.8S ribosomal gene, the ITS2A sequence, the 2S sequence, the ITS2 sequence, and part of the 28S ribosomal gene for discriminating members of the A. fraterculus cryptic species complex. We also include samples of another member of the fraterculus species group, A. schultzi Blanchard. This species has, to date, been found only in Peru and Argentina, where it competes with A. fraterculus for resources [25]. Anastrepha schultzi can be distinguished from members of the A. fraterculus cryptic species complex using the morphology of the genitalia, but very limited information is available on this species. At the time of writing (July 2024), only 15 sequences are available for A. schultzi in GenBank. Our aim is to derive information on the genetic status of these flies and on their relationship with the A. fraterculus cryptic species complex.

2. Materials and Methods

2.1. Samples and DNA Extraction

The samples used in this study included five laboratory strains and twelve wild-collected samples. The laboratory strains, indicated by their capitalised names, were TEOCELO (derived from Teocelo, Veracruz State, Mexico), a representative of the Mexican morphotype; LA MOLINA (derived from La Molina, Lima Province, Perú), a representative of Peruvian morphotype 1; VACARIA (derived from Vacaria, Rio Grande do Sul State, Brazil) and HORCO MOLLE (derived from Horco Molle, San Miguel de Tucumán, Tucumán Province, Argentina), representatives of Brazilian morphotype 1; and PIRACICABA (derived from Piracicaba, Sao Paulo State, Brazil), considered to be a representative of Brazilian morphotype 1.
The wild-captured samples were Horco Molle-W and Horco Molle-P collected from tropical walnuts (Juglans australis Griseb) and peaches (Prunus persica (L.) Batsch), respectively, at Horco Molle, San Miguel de Tucumán, Tucumán Province, Argentina; Tolombón-Pr from pears (Pyrus communis L.), at Tolombón, Salta Province, Argentina; Cafayate-P from peaches at Cafayate, Salta Province, Argentina; Yala-W from tropical walnuts at Yala, Jujuy Province, Argentina; Yuto-G from guava (Psidium guajava L.) at Yuto, Jujuy Province, Argentina; Concordia-G from guava at Concordia, Entre Ríos Province, Argentina; Bella-Vista-G from guava at Bella-Vista, Corrientes Province, Argentina; Oberá-G from guava, at Oberá, Misiones Province, Argentina; and Ampimpa-P from peaches, Tucumán Province, Argentina. Two samples of another species, Anastrepha schultzi, were also considered: Horco-Molle-W-schultzi from tropical walnuts at Horco Molle, San Miguel de Tucumán, Tucumán Province, Argentina, and Yala-W-schultzi from tropical walnuts at Yala, Jujuy Province, Argentina (Figure 1; Table 1). All of the laboratory and wild samples were supplied as ethanol-preserved specimens from the International Atomic Energy Agency (IAEA), Seibersdorf, Austria. The laboratory colony samples were sent to the Department of Biology and Biotechnology, University of Pavia, Italy, in 2019.
DNA was extracted from whole male and female individuals of the laboratory strains. In the case of wild-caught specimens, DNA was extracted from two to three legs so that the morphological identification of the otherwise intact specimens, preserved individually in ethanol at the University of Pavia, could be re-evaluated if necessary. The alcohol-preserved whole specimens or legs were rinsed for 15 min in distilled water and then processed using the Baruffi method [26], and resuspended in TE (10 mM Tris–HCl, pH8, 1 mM EDTA). The DNA was quantified using a Nanodrop ND-1000 spectrophotometer (Nano-drop Technologies Inc., Wilmington, DE, USA) and then diluted in water to a concentration of ~5 ng/µL.

2.2. ITS2 Marker Characterisation

Sequences covering parts of the 5.8S, ITS2, and 28S nuclear ribosomal DNA region of A. fraterculus (GenBank accession numbers AY775552.1, AF210891.2, KT594240.1–KT594243.1, KT594245.1, and KT594002.1–KT594006.1; Garma & Haymer, unpublished; Sonvico et al. unpublished; [22]) were aligned to the corresponding nuclear ribosomal DNA region of A. suspensa (GenBank accession DQ279855.1; [27]) and the Mediterranean fruit fly, Ceratitis capitata (Wiedemann) (GenBank accessions AF189691.2 and KC177754.1; [28,29]) to identify the limits of the 5.8S ribosomal gene, the initial portion of the ITS2 sequence, and part of the 28S ribosomal gene in A. fraterculus. Specific PCR primers were designed in the identified 5.8S region (A.fra5.8Sf: 5′ CACATGAACATCGACATTTTGAAC 3′) and in the 28S region (A.fra28Sr TTTAATATAACTCAATGACTTGCACA) using Primer 3 [30] (Table S1).
PCR amplifications were performed using the AccuPrime Taq DNA Polymerase High Fidelity Kit (Life Technologies SrL, Monza, Italy) using the following cycle conditions: 94 °C for 2 min, 30 cycles at 94 °C for 30 s, 55 °C for 30 s, 72 °C for 1 min 40 s, and a final extension at 72 °C for 10 min using the A.fra5.8Sf and A.fra28Sr rDNA primers. Reactions were performed in a volume of 25 µL with approximately 5 ng DNA, 60 mM Tris-SO4 pH 8.9, 18 mM (NH4)2SO4, 2 mM MgSO4, 200 µM dNTP, 20 pmol of each primer, and 1 unit of AccuPrime Taq DNA polymerase. Amplification products were electrophoresed on 1.5% agarose gels together with a 100 bp ladder (Life Technologies SrL) and visualised using Ethidium bromide staining under UV illumination.
The amplification products were cloned using the TOPO TA cloning kit (Invitrogen, Monza, Italy) and both strands of multiple clones were sequenced using Sanger sequencing chemistry (Macrogen Europe, Amsterdam, Netherlands). The sequences were assembled using CLC Main Workbench 6.9.1 (CLC bio, Aarhus, Denmark) and the resulting sequences were again aligned with the corresponding nuclear ribosomal DNA region of C. capitata (AF189691.2 and KC177754.1; [28,29]) and A. suspensa (DQ279855.1; [27]). These alignments permitted the identification of the 5.8S/ITS2A/2S/ITS2/28S junction positions.
Having identified the limits of the ITS2 sequence, primers were designed to amplify a smaller amplification product containing 22 bp of 5.8S ribosomal gene, the ITS2A sequence, the 2S sequence, the ITS2 sequence, and 80 bp of the 28S ribosomal gene (excluding primer sequences). The primers chosen were the original 5.8S forward primer (A.fra5.8Sf: 5′ CACATGAACATCGACATTTTGAAC 3′) and a new reverse primer A.fraITS2r: 5′ TTTTCGCTCGCCGCTACTAA 3′ within the 28S gene (Table S1).
Using this new pair of primers, PCR amplifications were performed using Taq DNA polymerase (Life Technologies SrL) using the following cycle conditions: 94 °C for 2 min, 30 cycles at 94 °C for 30 s, 56 °C for 30 s, 72 °C for 1 min, and a final extension at 72 °C for 10 min. Reactions were performed in a volume of 25 µL with approximately 5 ng DNA, 20 mM Tris-HCl pH 8.4, 50 mM KCl, 1.5 mM MgCl2, 200 µM dNTP, 20 pmol of each primer, and 1 unit of Taq DNA polymerase. Amplification products were electrophoresed on 1.5% agarose gels together with a 100 bp ladder (Life Technologies SrL) and visualised using Ethidium bromide staining under UV illumination. Amplification products were cloned using the TOPO TA cloning kit (Invitrogen) and both strands of multiple clones were sequenced (Macrogen Europe).

2.3. Data Analyses: Variability and Differentiation

The sequences were aligned using MAFFT version 7 [31] using the Q-INS-i strategy. Using this alignment, the ITS2 nucleotide diversity and haplotype diversity [32] parameters were determined using the program ARLEQUIN 3.5 [33] based on pairwise difference distance matrix and significance-tested using 10,000 permutations (all remaining parameters given default values). An analysis of molecular variance (AMOVA) [33] was performed using ARLEQUIN 3.5 to hierarchically partition genetic diversity within populations and between populations, and within and among individuals within populations and between populations based on the pairwise difference distance matrix and significance-tested using 10,000 permutations (all remaining parameters were given default values).
Principal component analysis (PCA) was performed using the method of Konishi and colleagues [34]. Phylogenetic analyses of the sample ITS2 sequences were performed using Maximum Likelihood (IQ-TREE v. 2.3.4) [35] using the model determined within the ModelFinder option [36], and Bayesian methods (MrBayes 3.2.7a) [37] using the model identified by modeltest-ng v. 0.1.7 [38].

3. Results

3.1. Characterisation of the ITS2 Locus

The manual alignment of the available sequences in GenBank covering parts of the 5.8S, ITS2, and 28S nuclear ribosomal DNA region of A. fraterculus (AY775552.1, AF210891.2, KT594240.1–KT594243.1, KT594245.1, and KT594002.1–KT594006.1) resulted in two non-contiguous sequences of 1268 bp and 337 bp that included part of the 5.8S ribosomal gene, the initial portion of the ITS2 sequence, and part of the 28S ribosomal gene. These sequences were used to design the first set of specific primers (A.fra5.8Sf and A.fra28Sr) that amplified fragments from HORCO MOLLE and TEOCELO genomic DNA that once sequenced produced fragments of 1329–1335 bp (excluding primer sequences), consisting of part of 5.8S (22 bp), the ITS2A sequence (30 bp), the 2S sequence (30 bp), and the ITS2 sequence (435–436 bp in TEOCELO, and 440–441 bp in HORCO MOLLE) and 812 bp of 28S (Figure 2; the ten sequences, five from each strain, have been deposited in GenBank with accession numbers PQ111866-PQ111875).
These sequences permitted the design of a primer, A.fraITS2r, that, together with the original A.fra5.8Sf primer, amplified a smaller amplification product of about 641–647 bp that, after excluding the primer sequences, included 22 bp of 5.8S ribosomal gene, the ITS2A sequence, the 2S sequence, the ITS2 sequence, and 80 bp of the 28S ribosomal gene (Figure 2).
In total, 151 ITS2 sequences were obtained from 62 individual flies from the laboratory strains and from the wild population samples (Table 2). The sequences were named according to their origin, the sex of the individual, the individual number, and a letter indicating the clone, i.e., “Concordia M2c” indicates the third clone derived from a male individual no. 2 from the Concordia sample. The ITS2 sequences, complete with flanking regions (but excluding primers), ranged from 580 bp (TEOCELO) to 607 bp (Horco Molle-P). The sequences had a low content of GC nucleotides (20.04–20.54%), similar to that of the same region in C. capitata (23.9% GC, AF189691.2). The sequences have been deposited in GenBank with accession numbers PQ111876–PQ112026.
The MAFFT alignment of the 152 sequences (including the A. suspensa DQ279855.1 sequence) was 638 bp in length.

3.2. ITS2 Sequence Variability

The presence of sequence haplotypes was determined using ARLEQUIN 3.5. All of the samples analysed contained multiple ITS2 sequence haplotypes, ranging from 15 haplotypes from six individuals in Ampimpa-P, to two haplotypes from a single individual from Horco Molle-W. Within three of the samples, LA MOLINA, VACARIA, and A. schultzi Horco Molle-W, all sequences obtained represented different haplotypes. Taken together, the 151 sequences obtained from the 62 individuals analysed represented a total of 97 different sequence haplotypes (Table 2).
Estimates of haplotype diversity and nucleotide diversity derived from the sequences obtained from the laboratory and wild samples indicated that the samples were similar in their levels of variability. The haplotype diversity values were high, ranging from 0.70 in Tolombón to 1.00 in the LA MOLINA and VACARIA strains and the Horco Molle A. schultzi sample. The sequences derived from laboratory strain TEOCELO (Mexican morphotype) displayed a higher level of nucleotide diversity (π = 0.020) compared to the other laboratory strains (π = 0.005–0.008) and the wild samples (π = 0.001–0.008) (Table 2).
The molecular analysis of variance (AMOVA) including both the laboratory and wild samples of A. fraterculus indicated that there was a significantly greater proportion of variation among the samples (69.83%) than within the samples (30.17%) (Table 3). The A. schultzi samples were excluded from this analysis as they do not pertain to the A. fraterculus cryptic species complex.
When the AMOVA also considered variation within individuals, it was apparent that the contribution of the within-individual variation (21.25%) was greater than that of the within-sample variation (11.11%) (Table 4).
Grouping the samples with respect to their nominal morphotype classification, as indicated in Table 1, showed that most variation (75.58%) was found among morphotypes; a substantial amount of variation was present within the morphotypes (9.83%), whereas 14.58% was present within the samples (Table 5).
Finally, grouping the PIRACICABA haplotypes within the Peruvian morphotype, rather than with the Brazilian-1 morphotypes (see Sample Differentiation section, below) showed a much higher level of variation (84.67%) among morphotypes. Very little, though significant, variation was present within morphotypes (0.36%), whereas the remaining 14.97% variation was present within samples (Table 6).

3.3. Sample Differentiation

The results of the principal component analysis (Figure 3) clearly show the differentiation among the three A. fraterculus morphotypes and the A. schultzi samples. The samples belonging to the Brazilian-1 morphotype cluster together and are separated from the Mexican and Peruvian/PIRACICABA morphotype samples by the first axis (13.8%). The Mexican and Peruvian/PIRACICABA clusters are separated by the second axis (9.7%). The Peruvian/PIRACICABA and A. schultzi samples are distinct but closely associated, and are only partially separated by the third axis (5.8%).
ModelFinder within IQ-TREE v.2.3.4 identified the HKY+F [39] as the best-fit model and this was used to obtain the optimal Maximum Likelihood tree. A total of 100,000 ultrafast bootstrap replications [40] were performed with the -bnni option, which reduces the risk of overestimated bootstrap support values due to severe model violations. For the Bayesian analysis, Modeltest-ng v. 0.1.7 [38] identified the HKY model [39] as being the most appropriate model of sequence evolution, and this choice was confirmed in MrBayes by sampling sample across the entire general time reversible (GTR) model space in the Bayesian Markov chain Monte Carlo (MCMC) analysis [41].
Both the Maximum Likelihood and Bayesian trees (Figure 4 and Figure 5, respectively) share very similar topologies in displaying the relationships among the ITS2 haplotypes isolated from individuals belonging to the different samples of the A. fraterculus morphotypes and from A. schultzi.
In both trees with an A. suspensa outgroup, the Brazilian-1 haplotypes from the Argentine HORCO MOLLE strain from the wild Horco-Molle individuals from the walnut and peach hosts, from Yala, Ampipa, Bellavista, Cafayate, Concordia, Oberá, Yuto, and Tolombón, and the haplotypes from the Brazilian VACARIA strain do not form a cluster. The first cluster comprises the PIRACICABA strain haplotypes and the LA MOLINA sequences (Peruvian morphotype). The second cluster comprises the haplotype sequences from A. schultzi. Finally, the third cluster contains the haplotypes from the TEOCELO strain (Mexican morphotype).
In both the Bayesian and Maximum Likelihood trees, the three clusters are supported by moderately high to high posterior probability and bootstrap values, respectively. Several of the clusters are subdivided, for example, the Mexican cluster with subclusters supported by bootstrap values of 87 and 97, respectively. However, as haplotypes derived from the same individual fly fall in both clusters (TEOCELO M6a in one subcluster and TEOCELO M6b in the other), these subclusters cannot represent different taxonomic entities. In both trees, identical haplotypes were represented by a single representative sequence. Haplotype sharing is indicated by the presence of strain/population-specific symbols next to the name of the representative haplotype sequence name in Figure 4 and Figure 5.

4. Discussion

The findings of this study highlight significant genetic differentiation within the A. fraterculus cryptic species complex. The use of the ITS2 molecular marker allowed for detailed discrimination between different morphotypes and provided new insights into their genetic relationships. The ITS2 marker provides a basis for the development of taxonomic keys for the discrimination of at least some of the cryptic taxa within the A. fraterculus cryptic species complex. Furthermore, the A. schultzi samples appear to be related to those of the A. fraterculus Peruvian/PIRACICABA cluster.

4.1. Much Hidden Variation Is Present among and within the Morphotypes

The significant genetic variation among samples, as indicated by the molecular analysis of variance (AMOVA), highlights the underlying genetic architecture of the A. fraterculus cryptic species complex. A high degree of variability within the A. fraterculus cryptic species complex was also detected using a large set of microsatellite markers [42]. Grouping the samples with respect to their morphotype classification (AMOVA, Table 6) showed that most (almost 85%) of the variation was found among the morphotypes, less than 1% of the variation was present within the morphotypes, and the remaining 15% of the variation was present within the samples. The A. schultzi samples displayed a high degree of variability, with haplotype diversity estimates similar to those of their sympatric A. fraterculus counterparts in Horco Molle and Yala. This high level of variation in A. fraterculus and in A. schultzi underscores the importance of using accurate molecular markers for effective species identification and subsequent pest management strategies.
The principal component analysis (PCA) and phylogenetic analyses further supported the genetic differentiation among the morphotypes. The PCA clearly separated the Brazilian-1 morphotype from the Mexican and Peruvian/PIRACICABA morphotypes, while the Peruvian/PIRACICABA and A. schultzi samples were closely associated but distinct. Whether the genetic affinity of A. schultzi with the A. fraterculus Peruvian morphotype suggests a common ancestral origin is an open question. It is noteworthy, however, that A. schultzi was detected for the first time in Peru [43].
The phylogenetic trees, constructed using both Maximum Likelihood and Bayesian methods, displayed similar topologies and provided strong support for the clustering of haplotypes according to their respective morphotypes.
As in a recent study on members of the A. fraterculus cryptic species complex based on ITS1 sequences [24], we observed high levels of haplotype diversity and low levels of nucleotide diversity (π), which is indicative of small populations that have recently undergone expansion [44].

4.2. Genetic Differentiation and Morphotype Classification

One of the most surprising results was the clustering of the PIRACICABA strain haplotypes with those of the LA MOLINA Peruvian morphotype, rather than with haplotypes pertaining to the Brazilian-1 morphotype. Indeed, one haplotype represented by PIRACICABA M1a in both the ML and Bayesian trees is shared within both the LA MOLINA and PIRACICABA strains. Conventionally, the PIRACICABA strain has been classified as part of the Brazilian-1 morphotype. This differentiation of PIRACICABA with respect to the Brazilian-1 morphotype haplotypes is supported by earlier studies that reported prezygotic incompatibility between PIRACICABA and other Brazilian-1 populations from Vacaria and Tucumán [15,16], as well as differences in pheromone emission and morphometric characteristics [15,45]. These discrepancies question the classification of the PIRACICABA strain as pertaining to the Brazilian-1 morphotype and, instead, suggest a closer affinity to the Peruvian morphotype. It should also be noted that since both PIRACICABA and LA MOLINA are long-established laboratory strains, bottlenecks during the adaptation process may have favoured, in both cases, the prevalence of certain haplotypes. To better understand the relationships between PIRACICABA and LA MOLINA or other Brazilian-1 morphotype populations, new field collections are required.
This result, in conjunction with the A. schultzi clustering, provides new evidence of possible hybridisation events between ancestral populations (different morphotypes and/or closely related species) followed by a later dispersion and a recent population expansion [46,47]. These evolutionary events might be linked to anthropic activities affecting the host crops of fruit flies [47] involving ecological niche diversification and leading to local adaptation [24]. A more comprehensive sampling across Brazil should help resolve some discrepancies and identify unconclusive relationships among members of the A. fraterculus cryptic species complex and closely related species.

4.3. Implications for Pest Control

The ability to correctly differentiate between A. fraterculus morphotypes is crucial for developing targeted pest control measures. The sterile insect technique (SIT) is particularly dependent on accurate species identification, as misidentification can lead to ineffective control measures. Therefore, the development and application of molecular markers such as ITS2 can aid in the development of more effective and targeted control programmes, reducing the risk of incompatibility and enhancing pest control efficacy. This is particularly important as previously undetected morphotypes may be present in poorly characterised populations. Indeed, a recent phylogenomic analysis that included samples from uncharacterised populations identified a previously undescribed morphotype from Puerto Maldonado, Peru [46]. The Argentine populations analysed in this study were all confirmed to pertain to the same taxonomic entity, the Brazilian-1 morphotype. This is important supporting information for the efficient application of species-specific control programmes, such as the SIT, in Argentina.

5. Conclusions

This study highlights the utility of the ITS2 region as a molecular marker for delineating the genetic diversity within the A. fraterculus cryptic species complex. The findings underscore the need for ongoing genetic monitoring and the re-evaluation of morphotype classifications to inform pest management strategies. The ITS2 region also represents an important marker for studies of populations of A. schultzi. This is of particular relevance given that A. schultzi is a poorly known species that is closely related to the A. fraterculus cryptic species complex. The ITS2 sequence is one of many molecular markers that can be applied to species discrimination. The ITS2 region, being a relatively fast-evolving sequence, shows limited sequence variation within a species and, often, significant sequence divergence between closely related species [48]. This makes ITS2 valuable for inferring phylogenetic relationships across various taxa, including species complexes [23,49,50,51]. Despite the undoubted utility of the ITS2 region, the use of multiple molecular loci [22], or even entire genomes [46], together with other biological characteristics [12] should be explored as a means of increasing the resolutive power of such studies.
The scope of the current study was largely limited to Argentine populations of the A. fraterculus cryptic species complex. Future research should focus on further refining these, and other, genetic markers, and exploring their applicability to additional morphotypes across broader geographic ranges to improve our knowledge of the origin and adaptive radiation of these cryptic species.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/insects15100748/s1, Table S1: Primer details.

Author Contributions

Conceptualisation, L.M.G., G.G., A.R.M., M.T.V. and C.C.; methodology, validation, supervision, data curation, visualisation, and writing—original draft preparation, L.M.G.; investigation, L.M.G., G.F., R.P. and D.D.L.; resources and samples, G.G., L.M.G., M.T.V., S.B.L., W.E., B.N.C., J.P.R.B. and V.A.V.; writing—review and editing, L.M.G., A.R.M., M.T.V., S.B.L., G.F., R.P., D.D.L., W.E., B.N.C., J.P.R.B., V.A.V., C.C. and G.G. All authors have read and agreed to the published version of the manuscript.

Funding

This work was financially supported by International Atomic Energy Agency Research Contract ITA-22496 and RLA5087 2.1.4 LVP IAEA Purchase Order 202305055.

Data Availability Statement

The sequence data presented in this study have been deposited in GenBank with accession numbers PQ111866-PQ112026.

Acknowledgments

This study was performed within the Food and Agriculture Organization/International Atomic Energy Agency (FAO/IAEA) Research Coordinated Project “Mosca Sudamericana de la fruta Anastrepha fraterculus” and benefited from discussions at IAEA-funded meetings therein.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

  1. Norrbom, A.L.; Zucchi, R.A.; Hernández-Ortiz, V. Phylogeny of the genera Anastrepha and Toxotrypana (Trypetinae: Toxotrypanini) based on morphology. In Fruit Flies (Tephritidae): Phylogeny and Evolution of Behavior; Aluja, M., Norrbom, A., Eds.; CRC Press: Boca Raton, FL, USA, 1999; pp. 299–342. [Google Scholar]
  2. Norrbom, A.L.; Muller, A.; Gangadin, A.; Sutton, B.D.; Rodriguez, E.J.; Savaris, M.; Lampert, S.; Clavijo, P.A.R.; Steck, G.J.; Moore, M.R.; et al. New species and host plants of Anastrepha (Diptera: Tephritidae) primarily from Suriname and Par, Brazil. Zootaxa 2021, 5044, 1–74. [Google Scholar] [CrossRef] [PubMed]
  3. Hernández-Ortiz, V.; Bartolucci, A.F.; Morales-Valles, P.; Frías, D.; Selivon, D. Cryptic species of the Anastrepha fraterculus complex (Diptera: Tephritidae): A multivariate approach for the recognition of South American morphotypes. Ann. Entomol. Soc. Am. 2012, 105, 305–318. [Google Scholar] [CrossRef]
  4. Steck, G. Biochemical systematics and population genetic-structure of Anastrepha fraterculus and related species (Diptera, Tephritidae). Ann. Entomol. Soc. Am. 1991, 84, 10–28. [Google Scholar] [CrossRef]
  5. Steck, G.J. Taxonomic status of Anastrepha fraterculus In The South American Fruit Fly, Anastrepha fraterculus (Wied.): Advances in Artificial Rearing, Taxonomic Status and Biological Studies; IAEA Tech-Doc 1064; International Atomic Energy Agency: Vienna, Austria, 1999; pp. 13–20. [Google Scholar]
  6. Stone, A. The fruit flies of the genus Anastrepha. U.S. Dep. Agric. Misc. Publ. 1942, 439, 1–112. [Google Scholar]
  7. Norrbom, A.L. Host plant database for Anastrepha and Toxotrypana (Diptera: Tephritidae: Toxotrypanini). In Diptera Data Dissemination Disk (CD-ROM) 2; North American Dipterist’s Society: Washington, DC, USA, 2004. [Google Scholar]
  8. Prezotto, L.F.; Perondini, A.L.P.; Hernández-Ortiz, V.; Frías, D.; Selivon, D. What can integrated analysis of morphological and genetic data still reveal about the Anastrepha fraterculus (Diptera: Tephritidae) cryptic species complex? Insects 2019, 10, 408. [Google Scholar] [CrossRef]
  9. Selivon, D.; Perondini, A.L.P. Eggshell morphology in two cryptic species of the Anastrepha fraterculus complex (Diptera: Tephritidae). Ann. Entomol. Soc. Am. 1998, 91, 473–478. [Google Scholar] [CrossRef]
  10. Selivon, D.; Vretos, C.; Fontes, L.; Perondini, A.L.P. New variant forms in the Anastrepha fraterculus complex. In Proceedings of the 6th International Symposium on Fruit Flies of Economic Importance, Stellenbosh, South Africa, 6–10 May 2002; Barnes, B.N., Ed.; Isteg Scientific Publications: Irene, South Africa, 2004; pp. 253–258. [Google Scholar]
  11. Selivon, D.; Perondini, A.L.P.; Morgante, J.S. A genetic-morphological characterization of two cryptic species of the Anastrepha fraterculus complex (Diptera: Tephritidae). Ann. Entomol. Soc. Am. 2005, 98, 367–381. [Google Scholar] [CrossRef]
  12. Selivon, D.; Perondini, A.L.P.; Hernandez-Ortiz, V.; doVal, F.C.; Camacho, A.; Gomes, F.R.; Prezotto, L.F. Genetical, morphological, behavioral, and ecological traits support the existence of three Brazilian species of the Anastrepha fraterculus complex of cryptic species. Front. Ecol. Evol. 2022, 10, 836608. [Google Scholar] [CrossRef]
  13. Rull, J.; Abraham, S.; Kovaleski, A.; Segura, D.F.; Mendoza, M.; Liendo, M.C.; Vera, M.T. Evolution of pre-zygotic and post-zygotic barriers to gene flow among three cryptic species within the Anastrepha fraterculus complex. Entomol. Exp. Et Appl. 2013, 148, 213–222. [Google Scholar] [CrossRef]
  14. Hendrichs, J.; Vera, M.T.; De Meyer, M.; Clarke, A.R. Resolving cryptic species complexes of major tephritid pests. Zookeys 2015, 540, 5–39. [Google Scholar] [CrossRef]
  15. Dias, V.S.; Silva, J.G.; Lima, K.M.; Petitinga, C.S.C.D.; Hernández-Ortiz, V.; Laumann, R.A.; Paranhos, B.J.; Uramoto, K.; Zucchi, R.A.; Joachim-Bravo, I.S. An integrative multidisciplinary approach to understanding cryptic divergence in Brazilian species of the Anastrepha fraterculus complex (Diptera: Tephritidae). Biol. J. Linn. Soc. 2016, 117, 725–746. [Google Scholar] [CrossRef]
  16. Vera, M.T.; Cáceres, C.; Wornoayporn, V.; Islam, A.; Robinson, A.S.; De La Vega, M.H.; Hendrichs, J.; Cayol, J.P. Mating incompatibility among populations of the South American fruit fly Anastrepha fraterculus (Diptera: Tephritidae). Ann. Entomol. Soc. Am. 2006, 99, 387–397. [Google Scholar] [CrossRef]
  17. Devescovi, F.; Abraham, S.; Roriz, A.K.P.; Nolazco, N.; Castañeda, R.; Tadeo, E.; Cáceres, C.; Segura, D.F.; Vera, M.T.; Joachim-Bravo, I.; et al. Ongoing speciation within the Anastrepha fraterculus cryptic species complex: The case of the Andean morphotype. Entomol. Exp. Appl. 2014, 152, 238–247. [Google Scholar] [CrossRef]
  18. Sutton, B.D.; Steck, G.J.; Norrbom, A.L.; Rodriguez, E.J.; Srivastava, P.; Alvarado, N.N.; Colque, F.; Landa, E.Y.; Sánchez, J.J.; Quisberth, E.; et al. Nuclear ribosomal internal transcribed spacer 1 (ITS1) variation in the Anastrepha fraterculus cryptic species complex (Diptera, Tephritidae) of the Andean region. Zookeys 2015, 540, 175–191. [Google Scholar] [CrossRef]
  19. Hebert, P.D.; Cywinska, A.; Ball, S.L.; deWaard, J.R. Biological identifications through DNA barcodes. Proc. Biol. Sci. 2003, 270, 313–321. [Google Scholar] [CrossRef]
  20. Barr, N.B.; Ruiz-Arce, R.; Farris, R.E.; Silva, J.G.; Lima, K.M.; Dutra, V.S.; Ronchi-Teles, B.; Kerr, P.H.; Norrbom, A.L.; Nolazco, N.; et al. Identifying Anastrepha (Diptera; Tephritidae) species using DNA barcodes. J. Econ. Entomol. 2018, 111, 405–421. [Google Scholar] [CrossRef]
  21. Bartolini, I.; Rivera, J.; Nolazco, N.; Olórtegui, A. Towards the implementation of a DNA barcode library for the identification of Peruvian species of Anastrepha (Diptera: Tephritidae). PLoS ONE 2020, 15, e0228136. [Google Scholar] [CrossRef]
  22. Scally, M.; Into, F.; Thomas, D.B.; Ruiz-Arce, R.; Barr, N.B.; Schuenzel, E.L. Resolution of inter and intra-species relationships of the West Indian fruit fly Anastrepha obliqua. Mol. Phylogenet. Evol. 2016, 101, 286–293. [Google Scholar] [CrossRef]
  23. Barr, N.; Ruiz-Arce, R.; Obregón, O.; Shatters, R.; Norrbom, A.L.; Nolazco, N.; Thomas, D. Diagnostic characters within ITS2 DNA support molecular identification of Anastrepha suspensa (Diptera: Tephritidae). Fla. Entomol. 2017, 100, 182–185. [Google Scholar] [CrossRef]
  24. Freilij, D.; Vilardi, J.C.; Gómez-Cendra, P. Rapid cryptic divergence of the Anastrepha fraterculus complex in the Late Pleistocene: A phylogeographical-ecological approach. Biol. J. Linn. Soc. 2024, 142, 21–37. [Google Scholar] [CrossRef]
  25. Blanchard, E.E. Especies Argentinas del género Anastrepha Schiner (sens. lat.) (Diptera: Tephritidae). Rev. Invest. Agric. Buenos Aires 1961, 15, 281–342. [Google Scholar]
  26. Baruffi, L.; Damiani, G.; Guglielmino, C.R.; Bandi, C.; Malacrida, A.R.; Gasperi, G. Polymorphism within and between populations of Ceratitis capitata: Comparison between RAPD and multilocus enzyme electrophoresis data. Heredity 1995, 74 Pt 4, 425–437. [Google Scholar] [CrossRef] [PubMed]
  27. Fritz, A.H. Sequence analysis of nuclear rDNA of Anastrepha suspensa. Ann. Entomol. Soc. Am. 2006, 99, 369–373. [Google Scholar] [CrossRef]
  28. Douglas, L.J.; Haymer, D.S. Ribosomal ITS1 polymorphisms in Ceratitis capitata and Ceratitis rosa (Diptera: Tephritidae). Ann. Entomol. Soc. Am. 2001, 94, 726–731. [Google Scholar] [CrossRef]
  29. Wiegmann, B.M.; Trautwein, M.D.; Winkler, I.S.; Barr, N.B.; Kim, J.W.; Lambkin, C.; Bertone, M.A.; Cassel, B.K.; Bayless, K.M.; Heimberg, A.M.; et al. Episodic radiations in the fly tree of life. Proc. Natl. Acad. Sci. USA 2011, 108, 5690–5695. [Google Scholar] [CrossRef]
  30. Untergasser, A.; Cutcutache, I.; Koressaar, T.; Ye, J.; Faircloth, B.C.; Remm, M.; Rozen, S.G. Primer3—New capabilities and interfaces. Nucleic Acids Res. 2012, 40, e115. [Google Scholar] [CrossRef]
  31. Katoh, K.; Rozewicki, J.; Yamada, K.D. MAFFT online service: Multiple sequence alignment, interactive sequence choice and visualization. Brief. Bioinform. 2019, 20, 1160–1166. [Google Scholar] [CrossRef]
  32. Nei, M. Molecular Evolutionary Genetics; Columbia University Press: New York, NY, USA, 1987. [Google Scholar]
  33. Excoffier, L.; Lischer, H.E. Arlequin suite ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. Mol. Ecol. Resour. 2010, 10, 564–567. [Google Scholar] [CrossRef]
  34. Konishi, T.; Matsukuma, S.; Fuji, H.; Nakamura, D.; Satou, N.; Okano, K. Principal Component Analysis applied directly to Sequence Matrix. Sci. Rep. 2019, 9, 19297. [Google Scholar] [CrossRef]
  35. Minh, B.Q.; Schmidt, H.A.; Chernomor, O.; Schrempf, D.; Woodhams, M.D.; von Haeseler, A.; Lanfear, R. IQ-TREE 2: New models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol. 2020, 37, 1530–1534. [Google Scholar] [CrossRef]
  36. Kalyaanamoorthy, S.; Minh, B.Q.; Wong, T.K.F.; von Haeseler, A.; Jermiin, L.S. ModelFinder: Fast model selection for accurate phylogenetic estimates. Nat. Methods 2017, 14, 587–589. [Google Scholar] [CrossRef] [PubMed]
  37. Ronquist, F.; Teslenko, M.; van der Mark, P.; Ayres, D.L.; Darling, A.; Höhna, S.; Larget, B.; Liu, L.; Suchard, M.A.; Huelsenbeck, J.P. MrBayes 3.2: Efficient Bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 2012, 61, 539–542. [Google Scholar] [CrossRef] [PubMed]
  38. Darriba, D.; Posada, D.; Kozlov, A.M.; Stamatakis, A.; Morel, B.; Flouri, T. ModelTest-NG: A new and scalable tool for the selection of DNA and protein evolutionary models. Mol. Biol. Evol. 2020, 37, 291–294. [Google Scholar] [CrossRef] [PubMed]
  39. Hasegawa, M.; Kishino, H.; Yano, T. Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J. Mol. Evol. 1985, 22, 160–174. [Google Scholar] [CrossRef]
  40. Hoang, D.T.; Chernomor, O.; von Haeseler, A.; Minh, B.Q.; Vinh, L.S. UFBoot2: Improving the ultrafast bootstrap approximation. Mol. Biol. Evol. 2018, 35, 518–522. [Google Scholar] [CrossRef]
  41. Huelsenbeck, J.P.; Larget, B.; Alfaro, M.E. Bayesian phylogenetic model selection using reversible jump Markov chain Monte Carlo. Mol. Biol. Evol. 2004, 21, 1123–1133. [Google Scholar] [CrossRef]
  42. Manni, M.; Lima, K.M.; Guglielmino, C.R.; Lanzavecchia, S.B.; Juri, M.; Vera, T.; Cladera, J.; Scolari, F.; Gomulski, L.; Bonizzoni, M.; et al. Relevant genetic differentiation among Brazilian populations of Anastrepha fraterculus (Diptera, Tephritidae). Zookeys 2015, 540, 157–173. [Google Scholar] [CrossRef]
  43. Schliserman, P.; Ovruski, S.; Colin, C.; Norrbom, A.L.; Aluja, M. First report of Juglans australis (Juglandaceae) as a natural host plant for Anastrepha schultzi (Diptera: Tephritidae) with notes on probable parasitism by Doryctobracon areolatus, D-Brasiliensis, Opius bellus (Braconidae) and Aganaspis pelleranoi (Figitidae). Fla. Entomol. 2004, 87, 597–599. [Google Scholar] [CrossRef]
  44. Rosetti, N.; Remis, M.I. Spatial genetic structure and mitochondrial DNA phylogeography of Argentinean populations of the grasshopper Dichroplus elongatus. PLoS ONE 2012, 7, e40807. [Google Scholar] [CrossRef]
  45. Roriz, A.K.P.; Japyassú, H.F.; Cáceres, C.; Vera, M.T.; Joachim-Bravo, I.S. Pheromone emission patterns and courtship sequences across distinct populations within Anastrepha fraterculus (Diptera-Tephritidae) cryptic species complex. Bull. Entomol. Res. 2019, 109, 408–417. [Google Scholar] [CrossRef]
  46. Congrains, C.; Dupuis, J.R.; Rodriguez, E.J.; Norrbom, A.L.; Steck, G.; Sutton, B.; Nolazco, N.; de Brito, R.A.; Geib, S.M. Phylogenomic analysis provides diagnostic tools for the identification of Anastrepha fraterculus (Diptera: Tephritidae) species complex. Evol. Appl. 2023, 16, 1598–1618. [Google Scholar] [CrossRef] [PubMed]
  47. Diaz, F.; Luís, A.; Lima, A.; Nakamura, A.M.; Fernandes, F.; Sobrinho, J.I.; De Brito, R.A. Evidence for introgression among three species of the Anastrepha fraterculus group, a radiating species complex of fruit flies. Front. Genet. 2018, 10, 359. [Google Scholar] [CrossRef] [PubMed]
  48. Paredes-Esquivel, C.C.; Townson, H. Functional constraints and evolutionary dynamics of the repeats in the rDNA internal transcribed spacer 2 of members of the Anopheles barbirostris group. Parasit Vectors 2014, 7, 106. [Google Scholar] [CrossRef] [PubMed]
  49. Wilkerson, R.C.; Reinert, J.F.; Li, C. Ribosomal DNA ITS2 sequences differentiate six species in the Anopheles crucians complex (Diptera: Culicidae). J. Med. Entomol. 2004, 41, 392–401. [Google Scholar] [CrossRef]
  50. Gomulski, L.; Meiswinkel, R.; Delécolle, J.; Goffredo, M.; Gasperi, G. Phylogenetic relationships of the subgenus Avaritia Fox, 1955 including Culicoides obsoletus (Diptera, Ceratopogonidae) in Italy based on internal transcribed spacer 2 ribosomal DNA sequences. Syst. Entomol. 2005, 30, 619–631. [Google Scholar] [CrossRef]
  51. Boykin, L.; Schutze, M.; Krosch, M.; Chomic, A.; Chapman, T.; Englezou, A.; Armstrong, K.; Clarke, A.; Hailstones, D.; Cameron, S. Multi-gene phylogenetic analysis of south-east Asian pest members of the Bactrocera dorsalis species complex (Diptera: Tephritidae) does not support current taxonomy. J. Appl. Entomol. 2014, 138, 235–253. [Google Scholar] [CrossRef]
Insects 15 00748 g001
Figure 1. Geographic locations of the sites of collections that gave rise to the laboratory strains and of the wild samples considered in the study.
Figure 1. Geographic locations of the sites of collections that gave rise to the laboratory strains and of the wild samples considered in the study.
Insects 15 00748 g001
Insects 15 00748 g002
Figure 2. Scheme of the characterisation of the ribosomal DNA region in Anastrepha fraterculus using sequences of A. fraterculus (red) and A. suspensa (green) available in GenBank. The 18S, ITS1, 5.8S, ITS2A, 2S, ITS2, and 28S regions and the positions of the primers and the amplification products (blue) are shown.
Figure 2. Scheme of the characterisation of the ribosomal DNA region in Anastrepha fraterculus using sequences of A. fraterculus (red) and A. suspensa (green) available in GenBank. The 18S, ITS1, 5.8S, ITS2A, 2S, ITS2, and 28S regions and the positions of the primers and the amplification products (blue) are shown.
Insects 15 00748 g002
Insects 15 00748 g003
Figure 3. Principal component analysis on the ITS2 sequences from the different samples. PC1 vs. PC2 on the left and PC2 vs. PC3 on the right.
Figure 3. Principal component analysis on the ITS2 sequences from the different samples. PC1 vs. PC2 on the left and PC2 vs. PC3 on the right.
Insects 15 00748 g003
Insects 15 00748 g004
Figure 4. Maximum Likelihood tree of the ITS2 sequences from the different samples. Bootstrap numbers (percentage) of 100,000 replications are shown. The presence of haplotype sharing is indicated by strain/population-specific symbols.
Figure 4. Maximum Likelihood tree of the ITS2 sequences from the different samples. Bootstrap numbers (percentage) of 100,000 replications are shown. The presence of haplotype sharing is indicated by strain/population-specific symbols.
Insects 15 00748 g004
Insects 15 00748 g005
Figure 5. Bayesian analysis tree of the ITS2 sequences from the different samples. Values at the nodes are the posterior probabilities of each partition. The presence of haplotype sharing is indicated by strain/population-specific symbols.
Figure 5. Bayesian analysis tree of the ITS2 sequences from the different samples. Values at the nodes are the posterior probabilities of each partition. The presence of haplotype sharing is indicated by strain/population-specific symbols.
Insects 15 00748 g005
Table 1. Details of the Anastrepha samples collected in Argentina.
Table 1. Details of the Anastrepha samples collected in Argentina.
Sample NameLocalityProvinceCoordinatesHost FruitCollection YearMorphotype
A. fraterculusHorco Molle-WHorco MolleTucumán26°48′10″ S 65°19′50″ WWalnut2019Brazilian 1
Horco Molle-PHorco MolleTucumán26°48′10″ S 65°19′50″ WPeach2019Brazilian 1
Ampimpa-PAmpimpaTucumán26°36′44″ S 65°50′31″ WPeach2021Brazilian 1
Tolombón-PrTolombónSalta26°11′04″ S 65°56′25″ WPear2019Brazilian 1
Cafayate-PCafayateSalta24°44′13″ S 65°23′21″ WPeach2019Brazilian 1
Yala-WYalaJujuy24°07′11″ S 65°24′17″ WWalnut2021Brazilian 1
Yuto-GYutoJujuy23°35′01″ S 64°30′25″ WGuava2021Brazilian 1
Concordia-GConcordiaEntre Ríos31°22′37″ S 58°01′01″ WGuava2019Brazilian 1
Bella Vista-GBella VistaCorrientes28°30′46″ S 59°02′31″ WGuava2019Brazilian 1
Oberá-GOberáMisiones27°39′01″ S 55°24′10″ WGuava2019Brazilian 1
A. schultziHorco Molle-WHorco MolleTucumán26°47′34″ S 65°18′58″ WWalnut2019
Yala-WYalaJujuy24°07′11″ S 65°24′17″ WWalnut2021
Table 2. Features of the internal transcribed spacer 2 (ITS2) sequences in the different population samples.
Table 2. Features of the internal transcribed spacer 2 (ITS2) sequences in the different population samples.
TypeSampleMorphotypeIndividuals AnalysedSequences AnalysedHaplotypesLength (bp) 1% GCHaplotype Diversity ± SDNucleotide Diversity ± SD
A. fraterculusTEOCELOMexican61311580–59820.540.962 ± 0.0500.020 ± 0.011
(lab strains)LA MOLINAPeruvian61010599–60320.101.000 ± 0.0450.008 ± 0.005
VACARIABrazilian 1355601–60420.121.000 ± 0.1270.008 ± 0.006
HORCO MOLLEBrazilian 16119602–60520.150.946 ± 0.0660.006 ± 0.004
PIRACICABABrazilian 1487599–60320.080.964 ± 0.0770.005 ± 0.003
A. fraterculusHorco Molle-WBrazilian 1132602–60320.090.667 ± 0.3140.001 ± 0.001
(wild samples)Horco Molle-PBrazilian 1387601–60720.040.964 ± 0.0770.007 ± 0.004
Ampimpa-PBrazilian 161815602–60520.110.980 ± 0.0240.007 ± 0.004
Tolombón-Pr Brazilian 1253599–60320.100.700 ± 0.2180.003 ± 0.003
Cafayate-PBrazilian 1395600–60320.090.722 ± 0.1590.004 ± 0.002
Yala-WBrazilian 1397601–60620.130.917 ± 0.0920.006 ± 0.004
Yuto-GBrazilian 161613600–60520.120.967 ± 0.0360.007 ± 0.004
Concordia-GBrazilian 1387600–60320.070.964 ± 0.0770.007 ± 0.004
Bella Vista-GBrazilian 1397601–60420.140.917 ± 0.0920.006 ± 0.004
Oberá-GBrazilian 1264602–60320.140.867 ± 0.1290.006 ± 0.004
A. schultziHorco Molle-W 244596–60020.521.000 ± 0.1770.006 ± 0.005
(wild samples)Yala-W 398587–60120.500.972 ± 0.0640.008 ± 0.005
Total 6215197 2
1 Length excluding primer sequences. 2 Not the sum of the haplotypes due to haplotype sharing among samples. Haplotype diversity: equivalent to the expected heterozygosity for diploid data. It is defined as the probability that two randomly chosen haplotypes are different in the sample. Nucleotide diversity: the probability that two randomly chosen homologous nucleotide sites are different.
Table 3. Molecular analysis of variance (AMOVA) limited to between and within samples (excluding A. schultzi).
Table 3. Molecular analysis of variance (AMOVA) limited to between and within samples (excluding A. schultzi).
Source of Variationd.f.Sum of SquaresVariance ComponentsPercent of Variationp
Among samples14702.4595.27469.83<0.00001
Within samples123280.3532.28030.17
Total137982.8127.554
Table 4. Molecular analysis of variance (AMOVA) between and within samples, and within individuals (excluding A. schultzi).
Table 4. Molecular analysis of variance (AMOVA) between and within samples, and within individuals (excluding A. schultzi).
Source of Variationd.f.Sum of SquaresVariance ComponentsPercent of Variationp
Among samples14702.4595.10767.63<0.00001
Within samples42150.3530.83911.11<0.00001
Within individuals81130.0001.60521.25<0.00001
Total137982.8127.552
Table 5. Molecular analysis of variance (AMOVA) between and within the nominal morphotypes, and within samples (excluding A. schultzi).
Table 5. Molecular analysis of variance (AMOVA) between and within the nominal morphotypes, and within samples (excluding A. schultzi).
Source of Variationd.f.Sum of SquaresVariance
Components		Percent of Variationp
Among morphotypes2514.79811.81475.58<0.01271
Within morphotypes12187.6601.5379.83<0.00001
Within samples123280.3532.27914.58<0.00001
Total137982.81215.229
Table 6. Molecular analysis of variance (AMOVA) between and within morphotypes (grouping PIRACICABA within the Peruvian morphotype), and within samples (excluding A. schultzi).
Table 6. Molecular analysis of variance (AMOVA) between and within morphotypes (grouping PIRACICABA within the Peruvian morphotype), and within samples (excluding A. schultzi).
Source of Variationd.f.Sum of SquaresVariance
Components		Percent of Variationp
Among morphotypes2669.37512.89584.67<0.00001
Within morphotypes1233.0840.0550.360.01760
Within samples123280.3532.27914.97<0.00001
Total137982.81215.229
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Gomulski, L.M.; Vera, M.T.; Lanzavecchia, S.B.; Piccinno, R.; Fiorenza, G.; De Luca, D.; Carrizo, B.N.; Bouvet, J.P.R.; Viana, V.A.; Cárceres, C.; et al. Molecular Markers for Analyses of Genetic Diversity within the Anastrepha fraterculus Complex with Emphasis on Argentine Populations. Insects 2024, 15, 748. https://doi.org/10.3390/insects15100748

AMA Style

Gomulski LM, Vera MT, Lanzavecchia SB, Piccinno R, Fiorenza G, De Luca D, Carrizo BN, Bouvet JPR, Viana VA, Cárceres C, et al. Molecular Markers for Analyses of Genetic Diversity within the Anastrepha fraterculus Complex with Emphasis on Argentine Populations. Insects. 2024; 15(10):748. https://doi.org/10.3390/insects15100748

Chicago/Turabian Style

Gomulski, Ludvik M., María Teresa Vera, Silvia B. Lanzavecchia, Riccardo Piccinno, Giulia Fiorenza, Daniel De Luca, Beatriz N. Carrizo, Juan Pedro R. Bouvet, Valeria A. Viana, Carlos Cárceres, and et al. 2024. "Molecular Markers for Analyses of Genetic Diversity within the Anastrepha fraterculus Complex with Emphasis on Argentine Populations" Insects 15, no. 10: 748. https://doi.org/10.3390/insects15100748

APA Style

Gomulski, L. M., Vera, M. T., Lanzavecchia, S. B., Piccinno, R., Fiorenza, G., De Luca, D., Carrizo, B. N., Bouvet, J. P. R., Viana, V. A., Cárceres, C., Enkerlin, W., Malacrida, A. R., & Gasperi, G. (2024). Molecular Markers for Analyses of Genetic Diversity within the Anastrepha fraterculus Complex with Emphasis on Argentine Populations. Insects, 15(10), 748. https://doi.org/10.3390/insects15100748

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop