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16 August 2021 Use of ITS-1 to Identify Bactrocera dorsalis and Bactrocera occipitalis (Diptera: Tephritidae): A Case Study Using Flies Trapped in California from 2008 to 2018
Norman B. Barr, Martin Hauser, Jennifer Belcher, David Salinas, Erin Schuenzel, Peter Kerr, Stephen Gaimari
Author Affiliations +
Abstract

Molecular methods are necessary to diagnose immature life stages of the agricultural pest fruit fly Bactrocera dorsalis (Hendel), and are useful to corroborate identifications based on adults because morphological variation within the species can overlap with congeners. DNA sequencing of the nuclear ribosomal internal transcribed spacer 1 (ITS-1) has been adopted by the International Plant Protection Convention as an internationally accepted method to distinguish between the 2 pestiferous fruit fly species Bactrocera dorsalis and Bactrocera carambolae (Drew & Hancock). Reported ITS-1 sequences also are distinct and diagnostically informative to distinguish several other Bactrocera species related to B. dorsalis. In this study, we applied DNA sequencing of ITS-1 to a collection of 513 adult flies trapped in California, USA, in the yr 2008 to 2018. Internal transcribed spacer 1 sequences were successfully recovered from 504 (98%) of these flies. One fly had an ITS-1 sequence that matched B. occipitalis (Bezzi) records. Re-examination of that fly using cytochrome c oxidase I, elongation factor 1-alpha, and morphology supports it as the second record of B. occipitalis trapped in California. The other 503 flies had ITS-1 sequences consistent with B. dorsalis. Six unique ITS-1 sequences (or DNA types) were observed in the collection of 503 B. dorsalis. Three of the ITS-1 sequences (types A, B, and C) were present in 84% of the 503 flies and match ITS-1 records reported in prior publications on B. dorsalis. The other 3 sequences (types D, E, and F) observed in 4% of the 503 B. dorsalis have not been reported in publications. Ambiguous nucleotides were observed from 12% of the 503 B. dorsalis flies, precluding designation of a sequence type. Including the 3 new types from the current study, a total of 15 unique ITS-1 sequences now are known for B. dorsalis. The study, therefore, documents additional intraspecific variation of ITS-1 that aids in future applications for species identification.

Accurate identification of agricultural pests that are trapped during surveillance or intercepted during inspections provides important information that may be used for trend and risk analysis (Garzón-Orduña et al. 2020; Lyal & Miller 2020). For example, identification of intercepted insects may be used to evaluate high risk pathways, and the level of diagnosis of these intercepted insects (e.g., to species, genus, or family level) may impact interpretation of the data (Liebhold et al. 2006). Identification of a specimen to species is necessary to examine its provenance. Population genetic studies require knowledge of species identity to complete source estimation based on correct pest distribution records and reference data (Barr et al. 2014b). Failure to identify a species correctly would result in less-than-optimal decision making regarding surveillance and management (Lyal & Miller 2020). For example, Clarke and Schutze (2014) review an instance when failure to quickly recognize the presence of the fly Bactrocera musae (Tryon) (Diptera: Tephritidae) on the Gazelle Peninsula of East New Britain, Papua New Guinea, contributed to its spread.

Fruit flies in the family Tephritidae include some of the world's most destructive agricultural pests and several of these species share similar, overlapping, or identical morphology, thereby impeding or precluding reliable morphological identification (DeMeyer et al. 2015). Species that appear nearly identical still may exhibit different behaviors, host ranges, tolerances, and physiologies (Gilchrist & Ling 2006; Condon et al. 2008; Gómez-Cendra et al. 2016; Virgilio et al. 2019). These factors are important when determining sensitivities to attractants, predicting demographic parameters for life expectancy and degree d models, generating lists of affected hosts in a quarantine, and effectively deploying the proper species and lab strains in sterile insect technique programs (DeMeyer et al. 2015). In cases where morphology of the adult or immature life stage is insufficient to complete an identification, molecular techniques often are employed as alternative diagnostic methods (Armstrong et al. 1997; Armstrong & Cameron 2000). Unfortunately, molecular methods are not available for all economically important fruit fly species.

The oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), is an invasive pest capable of using a wide range of fruits and vegetables as hosts to complete its development (Clarke et al. 2005; Vargas et al. 2015; McQuate & Liquido 2017; USDA 2020). Native within a wide distribution in Asia (Drew & Hancock 1994; Clarke et al. 2019), its specific ancestral range is the subject of ongoing molecular genetic investigations (Aketarawong et al. 2007; Wan et al. 2012; Krosch et al. 2013). It has successfully invaded many tropical and subtropical regions around the world in the past century where it causes significant economic damage (Stephens et al. 2007; Vargas et al. 2015; Steck et al. 2019). This pest has the potential to spread further within countries where it is present currently (Wang et al. 2014; Qin et al. 2019).

Traditionally, identification of Bactrocera species is focused on col- or characters and wing patterns, with less emphasis on morphological structures like the male genitalia, female aculeus, and setal patterns (Drew & Hardy 1981; Drew & Romig 2013, 2016). Although B. dorsalis possesses variable color patterns, this is not true for all species in the genus (Leblanc et al. 2015; IPPC 2019). Bactrocera dorsalis has been the subject of numerous taxonomic and systematic investigations because of its similar appearance and close genetic relationship to other members of its genus (Krosch et al. 2013; San Jose et al. 2013; Boykin et al. 2014). Recently, these studies have resulted in several other species being placed in synonymy with B. dorsalis (Drew & Romig 2013; Schutze et al. 2015a, 2017). Bactrocera dorsalis is a member of a species complex that includes several important pests (Clarke et al. 2005). That complex is named the “Bactrocera dorsalis complex,” but to avoid confusion with the species, it will be referred to hereafter as the “dorsalis complex.” The dorsalis complex is an informal taxonomic grouping of over 75 species (Clarke et al. 2005; Doorenweerd et al. 2018) that do not form a monophyletic lineage (Leblanc et al. 2015). Unlike cryptic species complexes (Clarke & Schutze 2014), many of the species of the dorsalis complex are distinguishable using adult morphology. However, there are several species within the complex that are very difficult to distinguish from B. dorsalis itself. High morphological variation and in-tergradation of character states among B. dorsalis, and some species of the dorsalis complex, can make reliable identification using keys and descriptions very difficult, even for scientists with taxonomic expertise and experience working with the group (e.g., Drew & Romig 2016; IPPC 2019).

In California, a trapping program for B. dorsalis and other exotic fruit flies is ongoing to support early detection of pests. The first reported B. dorsalis in the state was collected in 1960 and the pest has been trapped there in most yr since 1966. The California Department of Food and Agriculture's Plant Pest Diagnostics Laboratory routinely identifies suspect B. dorsalis specimens as “B. dorsalis group” based on morphology. This designation is a pragmatic definition to support California State eradication efforts. This group includes B. dorsalis, Bactrocera carambolae Drew & Hancock, Bactrocera caryeae (Kapoor), Bactrocera kandiensis Drew & Hancock, Bactrocera raiensis Drew & Hancock, and Bactrocera occipitalis (Bezzi) (all Diptera: Tephritidae). These 6 species share similar morphology and are all attracted to methyl eugenol. Molecular methods to identify B. dorsalis and these related species have been explored but diagnosis of these pests has not been completely resolved using DNA (Jiang et al. 2014).

DNA sequencing of the mitochondrial cytochrome c oxidase I (COI) gene has proved useful to distinguish B. dorsalis from other Bactrocera species that are not closely related (Armstrong & Ball 2005; Jiang et al. 2014; Leblanc et al. 2015). However, closely related species in the B. dorsalis group often cannot be diagnosed using COI alone because species share identical sequences or overlap in sequence variation (Armstrong & Ball 2005; Frey et al. 2013; Jiang et al. 2014; San Jose et al. 2018). Examination of nuclear ribosomal internal transcribed spacer (ITS) DNA has been useful in discriminating some closely related species (Armstrong et al. 1997; Armstrong & Cameron 2000; Boykin et al. 2014), and a method to separate B. dorsalis and B. carambolae using ITS-1 sequences has been adopted by the International Plant Protection Convention (IPPC 2019).

In this study, all fruit flies trapped in California over an 11-yr period from 2008 to 2018 and identified as B. dorsalis group were analyzed using ITS-1 DNA sequencing. The specific goals were to (1) measure success rate of the ITS-1 protocol when applied to field trapped fruit flies in California, (2) identify captured flies to species using both genetic and morphological examination, and (3) document variation in ITS-1 for flies with B. dorsalis-like sequence identities. Documenting protocol performance and observed ITS-1 variation for B. dorsalis will support future use of the method.

Materials and Methods

SAMPLES AND DNA EXTRACTIONS

A total of 513 adult fruit flies were trapped in California from 2008 to 2018 and morphologically identified to the B. dorsalis group at the California Department of Food and Agriculture's Plant Pest Diagnostics Laboratory by Martin Hauser, Jason Leathers, Peter Kerr, and Stephen Gaimari. This includes all 159 flies collected from 2008 to 2012 that were previously analyzed by Barr et al. (2014a) to compare COI sequences. The first fly detection in 2008 was in Jun and the last detection in 2018 was in Nov. A leg from each fly was used for nucleic acid extraction. Legs were removed from flies at the California Department of Food and Agriculture laboratory immediately after identification, then shipped to the Plant Protection and Quarantine laboratory in Edinburg, Texas, USA, for DNA extraction upon arrival, or storage at –20 °C until DNA extraction was performed within a wk of arrival. Flies collected between 2008 and 2012 had been processed previously for the Barr et al. (2014a) study using either KingFisher Flex model 711 (ThermoFisher Scientific Inc., San Jose, California, USA) 96-well plate-based magnetic bead extraction instrument and InviMag Tissue DNA Mini Kit/KF96 (STRATEC Molecular, Berlin, Germany) or DNeasy Blood and Tissue Kit (Qiagen, Valencia, California, USA) following the description of Barr et al. (2012). Legs of flies collected in 2013 to 2018 were extracted using the DNeasy method either at the Texas Plant Protection and Quarantine laboratory or at the California Department of Food and Agriculture laboratory. Vouchers of all flies are maintained at the California Department of Food and Agriculture laboratory and collection information is provided in Table S1.

PCR AND DNA SEQUENCING OF ITS-1

Polymerase chain reaction (PCR) was performed on DNA extractions using the primers ITS7 (5-GAATTTCGCATACATTGTAT) (Boykin et al. 2014) and ITS6 (5-AGCCGAGTGATCCACCGCT) (Armstrong & Cameron 2000). Reactions were performed in 25 µL volumes containing 1 µL of template (or water), 2.5 µL 10X buffer (Takara Bio Inc., Kyoto, Japan), 2 µL dNTP (2.5 mM each, Takara Bio Inc.), 0.125 µL Ex Taq HS DNA polymerase (5U per µL, Takara Bio Inc.), 1 µL primer ITS7 (10 µM), 1 µL primer ITS6 (10 µM), and 17.375 µL sterile water. Amplifications were performed in Applied Biosystems (Foster City, California, USA) GeneAmp PCR system 9700. Cycling conditions for amplification were 3 min of denaturation at 94 °C followed by 35 cycles of 20 s at 94 °C, 30 s at 60 °C, 60 s at 72 °C, and a final extension step for 5 min at 72 °C.

Polymerase chain reaction products were visualized using 1.2% agarose gels of TAE buffer (BioRad, Hercules, California, USA) prestained with ethidium bromide (Sigma-Aldrich, St. Louis, Missouri, USA). The size of products was compared to TriDye 100 base pairs ladder (New England Biolabs, Beverly, Massachusetts, USA) to inspect fragment size for the expected 500 base pairs amplicon of B. dorsalis. Polymerase chain reaction products were purified with ExoSAP-IT (USB Corp., Cleveland, Ohio, USA) prior to DNA sequencing. The amplicons were sequenced using the two PCR primers and ABI BigDye® Terminator v.3.1 chemistry at commercial centers Functional Biosciences (Madison, Wisconsin, USA) or GeneWiz (South Plainfield, New Jersey, USA). All sequences were edited and assembled into contigs using the program Sequencher v5 (Genecodes, Ann Arbor, Michigan, USA) and aligned using MEGA7 (Kumar et al. 2016).

ANALYSIS OF SEQUENCES

A reference data set of 220 B. dorsalis ITS-1 sequences was compiled from GenBank records including 133 records from Boykin et al. (2014), 80 records from Schutze et al. (2015b), 4 records from the Philippines (MK184640, MK184649, MK184685, MK184691), and 3 records of flies collected in Italy and identified as B. dorsalis by Nugnes et al. (2018) (MK158099–MK158101). The Accession numbers are: KC446776–KC446780, KC446782–KC446785, KC446792–KC446805, KC446807–KC446816, KC446818–KC446835, KC446856–KC446870, KC446891–KC446893, KC446895–KC446897, KC446899, KC446901–KC446904, KC446906–KC446937, KC446938–KC446952, KC446973–KC446980, KC446982, KM453329–KM453348, KM453349–KM453368, KM453369–KM453372, KM453373–KM453382, KM453391–KM453397, KM453398–KM45407, KM453408–KM453416, MK158099–MK158101, MK184640, MK184649, MK184685, and MK184691.

The 220 record reference data set was aligned with ITS-1 records generated for the California flies. Unique genetic types of ITS-1 from the aligned sequences were identified using DNAsp v5.10 (Librado & Rozas 2009) treating gaps as characters and MEGA7 to visually confirm differences. The number of flies per unique type were recorded to measure the frequency of ITS-1 diversity. The ITS-1 sequences of California flies were submitted to GenBank: MT602638–MT603141. The accession codes are provided in Table S1 for each specimen.

SPECIES IDENTIFICATION USING ITS-1

Following the methods reported in ISPM27 (IPPC 2019), the ITS-1 sequences of California flies were compared to those of B. carambolae (58 records, Boykin et al. 2014) and B. dorsalis (220 records) from GenBank to determine (1) if the sequences were 99% identical to these species, and (2) if a 44-base pairs insertion characteristic of B. carambolae (e.g., KC446737) was present. Absence of the insertion supports identification of a fly as B. dorsalis or possibly another closely related species. The flies that were less than 99% similar to B. dorsalis using NCBI BLAST ( https://blast.ncbi.nlm.nih.gov) (Johnson et al. 2008) were examined further for best sequence match in the GenBank database.

PCR AND SEQUENCING OF OTHER GENES

In order to further examine genetic similarity of fruit flies in the study, a subset of California flies also was amplified and sequenced for the COI gene and elongation factor 1-alpha (EF1α) gene. Primers for sequencing the first half of the COI gene used for DNA barcoding were LCO-1490 (5-GGTCAACAAATCATAAAGATATTGG) and HCO-2198 (5-TAAACTTCAGGGTGACCAAAAAATCA) (Folmer et al. 1994). Those primers for the 3-prime region (aka C3p790 fragment in Barr et al. 2014a) were HCO-2198rc (5-TGATTTTTTGGTCACCCTGAAGTTTA) (San Jose et al. 2013) and PAT-K508 (aka TL2-N-3014) (5-TCCAATGCACTA-ATCTGCCATATTA) (Simon et al. 1994). Primers for amplification and sequencing a fragment of the EF1α gene were M46-1 (5-CAGGAAAC-GCTATGACCGAGGAAATYAARAAGGAAG) and M4rc (5-TGTAAAACGAC-GGCCAGTACAGCVACKGTYTGYCTCATRTC) (Cho et al. 1995). Reactions for 2 COI fragments and EF1α were performed each in 25 µL volumes as described for ITS-1. Cycling conditions for amplification of COI fragments were 3 min at 94 °C followed by 39 cycles of 20 s at 94 °C, 20 s at 53 °C, 30 s at 72 °C, and a final extension of 5 min at 72 °C. Cycling conditions for amplification of EF1α fragment were 3 min at 94 °C followed by 39 cycles of 60 s at 94 °C, 60 s at 55 °C, 60 s at 72 °C, and a final extension of 5 min at 72 °C. Gels were inspected and sequencing was performed using the aforementioned methods for ITS-1. Further details on the COI and EF1α protocols are available in Barr et al. (2014a) and San Jose et al. (2013), respectively. The COI (MT597040–MT597049, MT597056) and EF1α (MT602095–MT602100) sequences generated in the study were submitted to GenBank.

PHYLOGENETIC ANALYSIS

The COI and EF1α data generated from California fruit flies were aligned with published records to examine similarity to B. dorsalis and closely related species. These records were from publications of San Jose et al. (2013) and Leblanc et al. (2015) with additional COI submissions of flies from the Philippines (MT597041–MT597049). Excluding flies from California, the COI (C3p790) data set included 93 records: Bactrocera cacuminata (Hering) (Diptera: Tephritidae) (n = 10), B. occipitalis (n = 6), B. raiensis (n = 1), Bactrocera thailandica Drew & Hancock (Diptera: Tephritidae) (n = 14), Bactrocera tuberculata (Bezzi) (Diptera: Tephritidae) (n = 4), B. musae (Tryon) (n = 1), B. kandiensis (n = 1), B. dorsalis (n = 47), and B. carambolae (n = 9). Excluding flies from California, the EF1α data set included 61 records: B. cacuminata (n = 2), B. occipitalis (n = 2), B. raiensis (n = 1), B. thailandica (n = 2), B. tuberculata (n = 4), B. kandiensis (n = 1), B. dorsalis (n = 40), and B. carambolae (n = 9). MEGA7 (Kumar et al. 2016) was used to align sequences, test goodness-of-fit to models of evolution for each alignment using Bayesian Information Criterion and reconstruct Maximum Likelihood trees. The model was selected as lowest Bayesian Information Criterion value from a Maximum Likelihood search of 24 models starting from a Neighbor Joining tree and using moderate branch swapping option and inclusion of all sites. The Tamura “1992” and Jukes & Cantor models (Nei & Kumar 2000) were selected for COI and EF1α, respectively. The heuristic Maximum Likelihood tree search started with Neighbor Joining tree followed by extensive option of Subtree-Pruning-Re-grafting (SPR level 5) and strong branch swap filter. Bootstrap values were calculated by performing 100 replicates of heuristic search. Trees were rooted using B. tuberculata based on its position as sister to the clade including species of interest in the study (Leblanc et al. 2015; San Jose et al. 2018). Branch values below 60% bootstrap support were not shown.

MORPHOLOGICAL RE-EXAMINATION OF FLIES

Because fruit flies are identified initially as “B. dorsalis group” by the California Department of Food and Agriculture lab, specimens whose ITS-1 sequences did not match B. dorsalis ITS-1 records were re-examined for morphological characteristics based on reference collections and published resources (Drew & Hardy 1981; Drew & Romig 2013, 2016; Leblanc et al 2015; IPPC 2019). In addition, flies were inspected for absence of microtrichia on the thorax along longitudinal middle strip from the anterior margin of the thorax. This characteristic of B. occipitalis was first noted by Eric Fisher (unpublished) and subsequently used by California Department of Food and Agriculture.

Results

SEQUENCING SUCCESS AND ITS-1 ALIGNMENT

The ITS-1 protocol generated sequence data for 504 of the 513 flies in the study. Although sequencing success was high, 52 of the 504 flies failed to sequence using both primer directions and were confirmed by sequencing the product twice using the same primer (i.e., the consensus of the 2 sequencing reads were from unidirectional data) (Table S1). DNA sequencing of internal transcribed spacers may be problematic because of secondary structures, A+T rich segments, and regions of nucleotide repeats (Whiting 2002; Sutton et al. 2015). These factors could have contributed to our observed failures. Primer sequencing failure for flies was confirmed by repeating those sequencing reactions and observing failure for a second time.

Table 1.

Fifteen ITS-1 types reported for Bactrocera dorsalis reporting length of sequence in alignment, the variable sites, and character states for each type.

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The expected fragment size of B. dorsalis ITS-1 is 500 base pairs using the ITS7 + ITS6 primers: 39 bases for primers and 461 bases in between primers. After trimming the data of primers and sites at ends that were of low confidence, the sequences were aligned. One sequence (MT603053, fly 16V457) from the California data set had several base differences and was removed from the alignment (see below). The resulting alignment of 723 suspect B. dorsalis sequences (503 California flies and 220 reference samples from National Center for Biotechnology Information) was 424 base pairs in length. The alignment includes sequences with insertions-deletions, and actual lengths of each sequence varied from 416 to 420 bases. The alignment included 15 unique types that were labelled as A to O (Table 1). The types reported from the California study and National Center for Biotechnology Information records were labeled A–C, the types reported only from the California study were labeled types D–F, and the types reported only in National Center for Biotechnology Information records were labeled G–O. The variation in the data set is characterized by 8 base substitution sites and 6 insertions-deletions of 1 or 3 base sites in length (Table 1).

Of the 723 flies with sequences, 74 flies had an ambiguous call at a site that is used to distinguish the 15 specific types. Consequently, these are tracked as ambiguous sequences for intraspecific variation analysis (Table 2). Excluding the ambiguous data, just 3 types represent nearly 90% of the flies: A (76.7%), B (8.4%), and C (4.7%) (Table 2).

IDENTIFICATION USING ITS-1

The 503 California fruit flies included in the alignment have ITS-1 sequences > 99% similar to B. dorsalis sequences. These flies did not include the 44 base pairs insertion that is used to diagnose B. carambolae. These flies are consistent with determination as B. dorsalis. The California fly 16V457 (collected 26 Jul 2016 in San Martin, Santa Clara County, PDR# SJ0P06327463, BX160805-004) that was removed from the alignment because of noted differences is < 98% similar to B. dorsalis records. The best match for this specimen to B. dorsalis was to GenBank record KJ545133.1 at 97.61% (search performed on 13 Apr 2019). The fly is a 100% match to ITS-1 sequences from B. occipitalis.

Table 2.

The frequencies of the 15 ITS-1 types recorded for Bactrocera dorsalis according to data sets.

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ANALYSIS OF COI

The COI DNA barcode sequence of 16V457 (MT597056) is > 99% match to records of B. occipitalis and B. dorsalis. A search of Barcode of Life Data System records ( http://www.boldsystems.org/) did not return a species identification for the query but the highest match was B. occipitalis. Similar results were obtained when comparing the 3′ segment of COI (MT597040). The Maximum Likelihood COI tree also grouped 16V457 with B. occipitalis (Fig. 1). Five additional B. dorsalis flies from California also were included in the analysis because of high similarity with B. occipitalis COI records. These 5 flies had the X135–X137 haplotypes (KF801433-35) reported by Barr et al. (2014a). These grouped with 16V457 as well, but COI is not considered a reliable diagnostic for these 2 species.

ANALYSIS OF EF1α

The phylogenetic tree of the EF1α gene also supports placement of fly 16V457 (MT602100) with B. occipitalis (Fig. 2). In contrast, the 5 specimens collected in California in 2009 and 2010 with COI sequences similar to B. occipitalis have EF1α sequences (MT602095–MT602099) that group them in B. dorsalis. The bootstrap branch support for the B. occipitalis clade is 74%. In comparison to ITS-1, the EF1α data set includes few individuals of this species (n = 2) making identification less certain. But the data suggest 16V457 is B. occipitalis.

MORPHOLOGICAL RE-EXAMINATION

The specimen genetically identified as B. occipitalis was re-examined for morphological characteristics to confirm that identification. While studying reference specimens in the California Department of Food and Agriculture insect collection, a second pinned Californian specimen of B. occipitalis from 1983 was discovered and included in the morphological analyses. The first Californian record of B. occipitalis is a male collected in Cupertino, Santa Clara County, on 20 Sep 1983 (Fig. 3, Voucher CSCA 74602). This specimen was identified as B. occipitalis by Eric Fisher, the California Department of Food and Agriculture dipterist at the time, and confirmed by R.I. Drew in 1999. The 1983 B. occipitalis did not generate ITS-1 sequence data and was not included in the molecular analysis.

The 2 California-collected fruit fly specimens were compared with several B. occipitalis individuals from the Philippines as well as other species of the dorsalis group with characters from the literature. The California specimens fit the morphological concept of B. occipitalis: the apical wing band is bleeding over R2+3 (Fig. 4), the ocellar bristles are without dark spots around their bases, and the dark markings on tergite IV are rectangular. The most notable characteristic is the absence of microtrichia on the thorax of B. occipitalis, forming a polished longitudinal middle strip from the anterior margin of the thorax to at least the transversal suture (Fig. 5). In most other dorsalis group species, this area is covered in dense microtrichia.

The 5 flies with ITS-1 and EF1α sequences matching B. dorsalis were re-examined as well because of their similarity to COI sequences found in B. occipitalis. Images of 1 male (California Department of Food and Agriculture voucher 09E332) and 2 females (California Department of Food and Agriculture voucher 10F724, 09D379) are provided in Supplemental Figure S2. The relevant characteristics for B. dorsalis are expressed weakly in the male (09E332) but are visible and are found also in the other 2 males (09D261 and 10F809). Morphology of these flies is largely consistent with B. dorsalis but also exhibits character states that are rarely found in this species. For example, the costal band overlapping R2+3, the dark dorsoapical markings on the protibia, the apically darkened meso- and metafemur, the darkened apical 3 tarsal segments, and the broad lateral yellow markings on the thorax are atypical for B. dorsalis. Atypical patterns such as these have been seen before in B. dorsalis specimens (C. Doorenweerd and L. Leblanc, personal communication). The aculeus of the female is more elongate (2 mm) than in typical B. dorsalis specimens but falls within the range for this species (IPPC 2019).

Fig. 1.

ML tree (log likelihood –2782.3671) of C3p790 fragment of COI gene based on the Tamura model with Gamma distributed rates and Invariant sites (T92+G+I). The California fly (16V457) with Bactrocera occipitalis ITS-1 sequence is marked with an open circle dot. Five flies trapped in California that have ITS-1 sequences that match Bactrocera dorsalis and reported in Barr et al. (2014a) are marked with black dots. Operational Taxonomic Units and branches are collapsed for species in clades. The collapsed B. dorsalis clade includes both B. dorsalis and B. carambolae records.

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Discussion

In this study we have demonstrated that the ITS-1 sequencing protocol was successful at generating data from 504 of the 513 flies trapped in California. Of the 504 flies with amplified product, nearly 90% were successfully sequenced using both primers. These data indicate that the protocol is appropriate for DNA analysis of flies collected in trapping programs. Of the flies with ITS-1 sequences, the currently available reference Bactrocera ITS-1 records support B. dorsalis as the identification for 503 flies. To further support that identification, additional records for less studied pests will be needed to document variation for a wider range of species.

One fly (16V457) of the 504 that were successfully sequenced had an ITS-1 sequence that matched B. occipitalis. Morphological examination confirmed this identity. This represents the second record of B. occipitalis in the state. The first detection of B. occipitalis was a single fly trapped in 1983. The time period between detections (1983 and 2016) indicates the fly did not establish in North America.

In 1997, a fly trapped in California (voucher 1187308) was morphologically identified as B. carambolae by Eric Fisher, and corroborated by R.I. Drew and Martin Hauser. This is the only record of the invasive pest in the state. Unfortunately, we could not successfully extract DNA from the specimen, likely due to its age. Based on ITS-1 data, B. carambolae has not been trapped in California in the 11 yr examined in our study nor from flies collected in 2019 to 2020 (N. Barr, unpublished). The molecular methods described here for ITS-1 analysis were applied also to flies trapped in Florida during the 2015 to 2016 outbreak of B. dorsalis (Steck et al. 2019) to provide confirmation that B. carambolae flies were not present in those detections (N. Barr, unpublished).

Fig. 2.

ML tree (log likelihood –1370.3141) of elongation factor 1-alpha (EF1α) gene based on Jukes-Cantor model. The California fly (16V457) with Bactrocera occipitalis ITS-1 sequence is marked with an open circle dot. Five flies trapped in California that have ITS-1 sequences that match Bactrocera dorsalis and reported in Barr et al. (2014a) are marked with black dots.

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Fig. 3.

Image of first Bactrocera occipitalis trapped in California in 1983.

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The ability of B. carambolae and B. dorsalis to hybridize under laboratory conditions (Schutze et al. 2013, 2015a) and possibly in nature (Ebina & Ohto 2006; Delomen et al. 2013; Jalani et al. 2014) could complicate use of the ITS-1 genetic identification method because of introgression. Schutze et al. (2015b) also reported evidence of hybridization between B. dorsalis and B. kandiensis. We did not detect evidence of hybrids based on amplification because only 1 size product of ITS-1 was visible and sequenced in the fruit flies studied. However, we did not screen flies for evidence of introgression at other regions of the genome. Methods using single nucleotide polymorphisms could be applied to the issue of introgression between species (e.g., Anderson et al. 2018) but have not been developed for B. dorsalis.

Although the COI gene is not suitable for distinguishing B. dorsalis from certain closely related species, the 16V457 fly identified as B. occipitalis using ITS-1 had a COI sequence that is common for B. occipitalis specimens. Review of other flies in our data set with COI sequences similar to B. occipitalis records demonstrates some limitations of that approach to screening for B. occipitalis. Five of the flies trapped in California between 2008 and 2012 had COI sequences that are common to B. occipitalis specimens, but these flies were supported as B. dorsalis based on ITS-1 and EF1α sequences. These 5 had morphologies similar to but atypical for B. dorsalis and clearly were different from B. occipitalis.

As more B. dorsalis complex specimens from additional global collections are sequenced for ITS-1, EF1α, COI, and other genes under investigation (e.g., San Jose et al. 2013; Krosch et al. 2017), the utility of these reference datasets can be confirmed and eventually become formalized as aids to identifiers. The sequences analyzed in this study provided useful information to question or corroborate morphological identifications. The ITS-1 results were used to select specimens for re-examination using morphology and other genes. However, not all pest species related to B. dorsalis have genetic profiles for ITS-1 or other DNA markers. For example, ITS-1 records for the pests B. caryeae and Bactrocera pyrifoliae Drew & Hancock (Diptera: Tephritidae) are lacking. Based on ITS-1 data available from other Bactrocera species, it is reasonable to assume the ITS-1 sequences of these pests will not be identical to B. dorsalis sequences. However, that assumption needs be tested. Furthermore, lack of records for these known pests complicates interpretation of any new ITS-1 sequences that are generated from intercepted immature flies. Adult specimens still should be examined using morphological methods (e.g., IPPC 2019) to identify these pests.

Fig. 4.

Image of wing of fly (16V457) with Bactrocera occipitalis ITS-1 sequence.

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The ability to distinguish the exotic species B. carambolae, B. occipitalis, and B. dorsalis is significant because it provides accurate data used to track new introductions, track the spread of invasions, determine the true number of flies contributing to a quarantine threshold, and adjust life cycle models appropriately as new exotic fruit flies are found. Identification of species and genetic variants helps to determine if a newly detected fly is part of an existing or an independent infestation. This information then is used to calculate degree d models for tracking local eradication efforts. The results of our current study support inclusion of the majority of trapped flies in California from 2008 to 2018 in future population genetic and pest distribution studies of B. dorsalis.

Fig. 5.

Images of thoraces of the fly (16V457) with Bactrocera occipitalis ITS-1 sequence and a Bactrocera dorsalis fly. Areas without microtrichia are highlighted in green in the smaller pictures.

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Acknowledgments

We thank our colleagues Terry Todd (US Department of Agriculture), Danny Garza (US Department of Agriculture), Rosita DeLeon (US Department of Agriculture), Grishma Parikh (California Department of Food and Agriculture), and Scott Kinnee (California Department of Food and Agriculture) for their assistance in preparing, shipping, and processing specimens for this study. Luc Leblanc (University of Idaho), Mike San Jose (University of Hawaii), and Camiel Doorenweerd (University of Hawaii) provided helpful feedback on current systematic relationships in the complex and species groupings. We thank Raul Ruiz-Arce (US Department of Agriculture), Corinna Baze-let (US Department of Agriculture), Camiel Doorenweerd (University of Hawaii), James Cilek (Navy Entomology Center of Excellence), and 2 anonymous reviewers for comments that greatly improved the manuscript. This work was made possible, in part, by a Cooperative Agreement with the University of Texas – RGV (AP18PPQS&T00C183) from the US Department of Agriculture Animal and Plant Health Inspection Service. Interpretations of the work may not necessarily express the views of the US Department of Agriculture Animal and Plant Health Inspection Service or the California Department of Food and Agriculture. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture or the California Department of Food and Agriculture.

References Cited

1.

Aketarawong N, Bonizzoni M, Thanaphum S, Gomulski LM, Gasperi G, Malacrida AR, Gugliemino CR. 2007. Inferences on the population structure and colonization process of the invasive oriental fruit fly, Bactrocera dorsalis (Hendel). Molecular Ecology 16: 3522–3532. Google Scholar

2.

Anderson CJ, Oakeshott JG, Tay WT, Gordon KHJ, Zwick A, Walsh TK. 2018. Hybridization and gene flow in the mega-pest lineage of moth, Helicoverpa. Proceedings of the National Academy of Sciences of the United States of America 115: 5034–5039. Google Scholar

3.

Armstrong KF, Ball SL. 2005. DNA barcodes for biosecurity: invasive species identification. Philosophical Transactions of the Royal Society B 360: 1813–1823. Google Scholar

4.

Armstrong KF, Cameron CM. 2000. Species identification of tephritids across a broad taxonomic range using ribosomal DNA, pp. 703–710 In Tan KH [ed.], Area-Wide Control of Fruit Flies and Other Insect Pests. Penerbit Universiti Sains, Penang, Malaysia. Google Scholar

5.

Armstrong KF, Cameron CM, Frampton ER. 1997. Fruit fly (Diptera: Tephritidae) species identification: a rapid molecular diagnostic technique for quarantine application. Bulletin of Entomological Research 87: 111–118. Google Scholar

6.

Barr N, Ruiz-Ace R, Armstrong K. 2014b. Using molecules to identify the source of fruit fly invasions, pp. 321–378 In Shelly T, Epsky N, Jang EB, Reyes-Flores J, Vargas R [eds.], Trapping Tephritid Fruit Flies: Lures, Area-Wide Programs, and Trade Implications. Springer, New York, USA.Barr NB, Islam MS, DeMeyer M, McPheron BA. 2012. Molecular identification of Ceratitis capitata (Diptera: Tephritidae) using DNA sequences of the COI barcode region. Annals of the Entomological Society of America 105: 339–350. Google Scholar

7.

Barr NB, Ledezma LA, Leblanc L, San Jose M, Rubinoff D, Geib S, Fujita B, Bartels DW, Garza D, Kerr P, Hauser H, Gaimari S. 2014a. Genetic diversity of Bactrocera dorsalis (Diptera, Tephritidae) on the Hawaiian Islands: implications for the introduction pathway into California. Journal of Economic Entomology 107: 1946–1958. Google Scholar

8.

Boykin LM, Schutze MK, Krosch MN, Chomic A, Chapman TA, Englezou A, Armstrong KF, Clarke AR, Hailstones D, Cameron SL. 2014. Multi-gene phylogenetic analysis of the south-east Asian pest members of the Bactrocera dorsalis species complex (Diptera: Tephritidae) does not support current taxonomy. Journal of Applied Entomology 138: 235–253. Google Scholar

9.

Cho S, Mitchell A, Regeir JC, Mitter C, Poole RW, Friedlander TP, Zhao SW. 1995. A highly conserved nuclear gene for low-level phylogenetics: elongation factor-1-α recovers morphology-based tree for heliothine moths. Molecular Biology and Evolution 12: 650–656. Google Scholar

10.

Clarke AR, Schultze MK. 2014. The complexities of knowing what it is you are trapping, pp 611–632 In Shelly T, Epsky N, Jang EB, Reyes-Flores J, Vargas R [eds.], Trapping Tephritid Fruit Flies: Lures, Area-Wide Programs, and Trade Implications. Springer, New York, USA. Google Scholar

11.

Clarke AR, Li Z-H, Qin Y-J, Zhao Z-H, Liu L-J, Schutze MK. 2019. Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) is not invasive through Asia: it's been there all along. Journal of Applied Entomology 143: 797–801. Google Scholar

12.

Clarke AR, Armstrong KF, Carmichael AE, Milne JR, Raghu S, Roderick GK, Yeates DK. 2005. Invasive phytophagous pests arising through a recent tropical evolutionary radiation: the Bactrocera dorsalis complex of fruit flies. Annual Review of Entomology 50: 293–319. Google Scholar

13.

Condon M, Adams DC, Bann D, Flaherty K, Gammons J, Johnson J, Lewis ML, Marsteller S, Scheffer SJ, Serna F, Swensen S. 2008. Uncovering tropical diversity: six sympatric cryptic species of Blepharoneura (Diptera: Tephritidae) in flowers of Gurania spinulosa (Cucurbitaceae) in eastern Ecuador. Biological Journal of the Linnean Society 93: 779–797. Google Scholar

14.

DeMeyer M, Clarke AR, Vera MT, Hendrichs J. 2015. Editorial: resolution of cryptic species complexes of tephritid pests to enhance SIT application and facilitate international trade. ZooKeys 540: 1–3. Google Scholar

15.

Delomen MLC, Mendioro MS, Diaz MGQ. 2013. Morphometric analysis and DNA barcoding of fruit flies Bactrocera occipitalis (Bezzi) and B. philippinensis Drew and Hancock (Diptera: Tephritidae) from Cavite and Davao del Norte. Philippine Journal of Science 142: 69–76. Google Scholar

16.

Doorenweerd C, Leblanc L, Norrbom AL, Jose MS, Rubinoff D. 2018. A global checklist of the 932 fruit fly species in the tribe Dacini (Diptera, Tephritidae). ZooKeys 730: 17–54. Google Scholar

17.

Drew RAI, Hancock DL. 1994. The Bactrocera dorsalis complex of fruit flies (Diptera: Tephritidae: Dacinae) in Asia. Bulletin of Entomological Research, Supplement Series 2: 1–68. Google Scholar

18.

Drew RAI, Hardy DE. 1981. Dacus (Bactrocera) opiliae, a new sibling species of the dorsalis complex of fruit flies from northern Australia (Diptera: Tephritidae). Journal of the Australian Entomological Society 20: 131–137. Google Scholar

19.

Drew RAI, Romig MC. 2013. Tropical Fruit Flies (Tephritidae: Dacinae) of SouthEast Asia: Indomalaya to North-West Australasia. CABI, Wallingfdord, United Kingdom. Google Scholar

20.

Drew RAI, Romig MC. 2016. Keys to the Tropical Fruit Flies (Tephritidae: Dacinae) of South-East Asia. CABI, Wallingford, United Kingdom. Google Scholar

21.

Ebina T, Ohto K. 2006. Morphological characters and PCR-RFLP markers in the interspecific hybrids between Bactrocera carambolae and B. papayae of the B. dorsalis species complex (Diptera: Tephritidae). Research Bulletin of Plant Protection Japan 42: 23–34. Google Scholar

22.

Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R. 1994. DNA primers for amplification of mitochondrial cytochrome c oxidase I from diverse metazoan invertebrates. Molecular Marine Biology and Biotechnology 3: 294–299. Google Scholar

23.

Frey JE, Guillén L, Frey B, Samietz J, Rull J, Aluja M. 2013. Developing diagnostic SNP panels for the identification of true fruit flies (Diptera: Tephritidae) within the limits of CO1-based species delimitation. BMC Evolutionary Biology 13: 106.  https://doi.org/10.1186/1471-2148-13-106 Google Scholar

24.

Garzón-Orduña IJ, Geib SM, Ledezma L, Bremer FT, Barr NB. 2020. Implementing low-cost, high accuracy DNA barcoding from single molecule sequencing to screen larval tephritid fruit flies intercepted at ports of entry. Annals of the Entomological Society of America 113: 288–297. Google Scholar

25.

Gilchrist AS, Ling AE. 2006. DNA microsatellite analysis of naturally occurring colour intermediates between Bactrocera tryoni (Froggatt) and Bactrocera neohumeralis (Hardy) (Diptera: Tephritidae). Australian Journal of Entomology 45: 157–162. Google Scholar

26.

Gómez-Cendra PV, Paulin LE, Orono L, Ovruski SM, Vilardi JC. 2016. Morphometric differentiation among Anastrepha fraterculus (Diptera: Tephritidae) exploiting sympatric alternate hosts. Environmental Entomology 45: 508–517. Google Scholar

27.

IPPC – International Plant Protection Convention. 2019. DP29: Bactrocera dorsalis. Annex to ISPM 27 diagnostic protocols for regulated pests: International Plant Protection Convention.  https://www.ippc.int/en/publications/87022/ (last accessed 19 Mar 2021). Google Scholar

28.

Jalani GSP, Laude RP, Diaz MGQ, Medina CdR, Velasco LRI. 2014. Genetic diversity of natural populations of Bactrocera occipitalis (Bezzi) and B. philippinensis Drew and Hancock (Diptera: Tephritidae) in selected mango producing areas in the Philippines using microsatellites. Agrivita 36: 217–228. Google Scholar

29.

Jiang F, Jin Q, Liang L, Zhang AB, Li ZH. 2014. Existence of species complex largely reduced barcoding success for invasive species of Tephritidae: a case study in Bactrocera spp. Molecular Ecology Resources 14: 1114–1128. Google Scholar

30.

Johnson M, Zaretskaya I, Raytselis Y, Merezhuk Y, McGinnis S, Madden TL. 2008. NCBI BLAST: a better web interface. Nucleic Acids Research 36, Suppl. 2: W5–W9. Google Scholar

31.

Krosch MN, Schutze MK, Strutt F, Clarke AR, Cameroon SL. 2017. A transcrip-tome-based analytical workflow for identifying loci for species diagnosis: a case study with Bactrocera fruit flies (Diptera: Tephritidae). Austral Entomology 58: 395–408. Google Scholar

32.

Krosch MN, Schutze MK, Armstrong KF, Boontop Y, Boykin LM, Chapman TA, Englezou A, Cameron SL, Clarke AR. 2013. Piecing together an integrative taxonomic puzzle: microsatellite, wing shape and aedeagus length analyses of Bactrocera dorsalis s.l. (Diptera: Tephritidae) find no evidence of multiple lineages in a proposed contact zone along the Thai/Malay Peninsula. Systematic Entomology 38: 2–13. Google Scholar

33.

Kumar S, Stecher G, Tamura K. 2016. MEGA7: Molecular Evolutionary Genetics Analysis, version 7.0 for bigger datasets. Molecular Biology and Evolution 33: 1870–1874. Google Scholar

34.

Leblanc L, San Jose M, Barr N, Rubinoff D. 2015. A phylogenetic assessment of the polyphyletic nature and intraspecific color polymorphism in the Bactrocera dorsalis complex (Diptera, Tephritidae). ZooKeys 540: 339–367. Google Scholar

35.

Librado P, Rozas J. 2009. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25: 1451–1452. Google Scholar

36.

Liebhold AM, Work TT, McCullough DG, Cavey JF. 2006. Airline baggage as a pathway for alien insect species invading the United States. American Entomologist 52: 48–54. Google Scholar

37.

Lyal CHC, Miller SE. 2020. Capacity of United States federal government and its partners to rapidly and accurately report the identity (taxonomy) of nonnative organisms intercepted in early detection programs. Biological Invasions 22: 101–127. Google Scholar

38.

McQuate GT, Liquido NJ. 2017. Host plants of invasive tephritid fruit fly species of economic importance. International Journal of Plant Biology and Research 5: 1072.  https://www.jscimedcentral.com/PlantBiology/plantbiology-5-1072.pdf (last accessed 19 Mar 2021). Google Scholar

39.

Nei M, Kumar S. 2000. Molecular Evolution and Phylogenetics. Oxford University Press, New York, USA. Google Scholar

40.

Nugnes F, Russo E, Viggiani G, Bernadro U. 2018. First record of an invasive fruit fly belonging to Bactrocera dorsalis complex (Diptera: Tephritidae) in Europe. Insects 9: 182. https://doi.org/10.3390/insects9040182 (last accessed 19 mar 2021)Google Scholar

41.

Qin Y, Wang C, Zhao Z, Pan X, Li Z. 2019. Climate change impacts on the global potential geographical distribution of the agricultural invasive pest, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae). Climatic Change 155: 145–156. Google Scholar

42.

San Jose M, Leblanc L, Geib SM, Rubinoff D. 2013. An evaluation of the species status of Bactrocera invadens and the systematics of Bactrocera dorsalis (Diptera: Tephritidae) complex. Annals of the Entomological Society of America 106: 684–694. Google Scholar

43.

San Jose M, Doorenweerd C, Leblanc L, Barr N, Geib S, Rubinoff D. 2018. Tracking the origins of fly invasions; using mitochondrial haplotype diversity to identify potential source populations in two genetically intertwined fruit fly species (Bactrocera carambolae and Bactrocera dorsalis [Diptera: Tephritidae]). Journal of Economic Entomology: 1–13. Google Scholar

44.

Schutze MK, Jessup A, Ul-Haq I, Vreysen MJB, Wornoayporn V, Vera MT, Clarke AR. 2013. Mating compatibility among four pest members of the Bactrocera dorsalis fruit fly species complex (Diptera: Tephrtidiae). Journal of Economic Entomology 106: 695–707. Google Scholar

45.

Schutze MK, Mahmood K, Pavasovic A, Bo W, Newman J, Clarke AR, Krosch MN, Cameron SL. 2015b. One and the same: integrative taxonomic evidence that Bactrocera invadens (Diptera: Tephritidae) is the same species as the oriental fruit fly Bactrocera dorsalis. Systematic Entomology 40: 472–486. Google Scholar

46.

Schutze MK, Bourtzis K, Cameron SL, Clarke AR, DeMeyer M, Hee AKW, Hendrichs J, Krosch MN, Mwatawala M. 2017. Integrative taxonomy versus taxonomic authority without peer review: the case of the oriental fruit fly, Bactrocera dorsalis (Tephritidae). Systematic Entomology 42: 609–620. Google Scholar

47.

Schutze MK, Aketarawong N, Amornsak W, Armstrong KF, Augustinos AA, Barr N, Bo W, Bourtzis K, Boykin LM, Cáceres C, Cameron SL, Chapman TA, Chinvinijkul S, Chomič A, DeMeyer M, Drosopoulou E, Englezou A, Ekesi S, Gariou-Papalexiou A, Geib SM, Hailstones D, Hasanuzzaman M, Haymer D, Hee AKW, Hendrichs J, Jessup A, Ji Q, Khamis FM, Krosch MN, Leblanc L, Mahmood H, Malacrida AR, Mavragani-Tsipidou P, Mwatawala M, Nishida R, Ona H, Reyes J, Rubinoff D, San Jose M, Shelly TE, Srikachar S, Tan KH, Thanaphum S, Haq I, Vijaysegaran S, Wee SL, Yesmin F, Zacharopoulou A, Clarke AR. 2015a. Synonymization of key pest within the Bactrocera dorsalis species complex (Diptera: Tephritidae): taxonomic changes based on a review of 20 years of the integrative morphological, molecular, cyto-genetic, behavioural, and chemoecological data. Systematic Entomology 40: 456–471. Google Scholar

48.

Simon C, Frati F, Beckenbach A, Crespi B, Liu H, Flook P. 1994. Evolution, weighting, and phylogenetic utility of mitochondrial gene sequences and a compilation of conserved polymerase chain reaction primers. Annals of the Entomological Society of America 87: 651–701. Google Scholar

49.

Steck GJ, Fox AJ, Carrillo D, Dean D, Roda A, Epsky ND, Smith TR. 2019. Oriental fruit fly eradication in Florida 2015–2016: program implementation, unique aspects, and lessons learned. American Entomologist 65: 108–121. Google Scholar

50.

Stephens AEA, Kriticos DJ, Leriche A. 2007. The current and future potential geographical distribution of the oriental fruit fly, Bactrocera dorsalis (Diptera: Tephritidae). Bulletin of Entomological Research 97: 369–378. Google Scholar

51.

Sutton BD, Steck GJ, Norrbom AL, Rodriguez EJ, Srivastava P, Nolazco Alvarado N, Colque F, Yábar Landa E, Lagrava Sánchez JJ, Quisberth E, Arévalo Peñaranda E, Rodriguez Clavijo PA, Alvarez-Baca JK, Guevara Zapata T, Ponce P. 2015. Nuclear ribosomal internal transcribed spacer 1 (ITS1) variation in the Anastrepha fraterculus cryptic species complex (Diptera, Tephritidae) of the Andean region. ZooKeys 540: 175–191. Google Scholar

52.

USDA. 2020. Compendium of Fruit Fly Host Information (CoFFHI), Edition 5.0.  https://coffhi.cphst.org/ (last accessed 19 Mar 2021). Google Scholar

53.

Vargas RI, Piñero JC, Leblanc L. 2015. An overview of pest species of Bactrocera fruit flies (Diptera: Tephritidae) and the integration of biopesticides with other biological approaches for their management with a focus on the Pacific region. Insects 6: 297–318. Google Scholar

54.

Virgilio M, Daneel J-H, Manrakhan A, Delatte H, Meganck K, De Meyer M. 2019. An integrated diagnostic setup for the morphological and molecular identification of the Ceratitis FAR complex (C. anonae, C. fasciventris, C. rosa, C. quilicii, Diptera, Tephritidae). Bulletin of Entomological Research 109: 376–382. Google Scholar

55.

Wan X, Liu Y, Zhang B. 2012. Invasion history of the Oriental fruit fly, Bactrocera dorsalis, in the Pacific-Asia region: two main invasion routes. PLoS ONE 7: e36176. https://doi.org/10.1371/journal.pone.0036176 (last accessed 19 mar 2021)Google Scholar

56.

Wang J, Zeng L, Han Z. 2014. An assessment of cold hardiness and biochemical adaptations for cold tolerance among different geographic populations of the Bactrocera dorsalis (Diptera: Tephritidae) in China. Journal of Insect Science 14: 292.  https://doi.org/10.1093/jisesa/ieu154 (last accessed 19 Mar 2021). Google Scholar

57.

Whiting MF. 2002. High-throughput DNA sequencing for systematics, pp. 328–350 In DeSalle R, Giribet G, Wheeler W [eds.], Methods and Tools in Biosciences and Medicine: Techniques in Molecular Systematics and Evolution. Birkhäuser Verlag, Basel, Switzerland. Google Scholar
Norman B. Barr, Martin Hauser, Jennifer Belcher, David Salinas, Erin Schuenzel, Peter Kerr, and Stephen Gaimari "Use of ITS-1 to Identify Bactrocera dorsalis and Bactrocera occipitalis (Diptera: Tephritidae): A Case Study Using Flies Trapped in California from 2008 to 2018," Florida Entomologist 104(2), 96-106, (16 August 2021). https://doi.org/10.1653/024.104.0205
Published: 16 August 2021
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