BIN overlap confirms transcontinental distribution of pest aphids (Hemiptera: Aphididae).

DNA barcoding is highly effective for identifying specimens once a reference sequence library is available for the species assemblage targeted for analysis. Despite the great need for an improved capacity to identify the insect pests of crops, the use of DNA barcoding is constrained by the lack of a well-parameterized reference library. The current study begins to address this limitation by developing a DNA barcode reference library for the pest aphids of Pakistan. It also examines the affinities of these species with conspecific populations from other geographic regions based on both conventional taxonomy and Barcode Index Numbers (BINs). A total of 809 aphids were collected from a range of plant species at sites across Pakistan. Morphological study and DNA barcoding allowed 774 specimens to be identified to one of 42 species while the others were placed to a genus or subfamily. Sequences obtained from these specimens were assigned to 52 BINs whose monophyly were supported by neighbor-joining (NJ) clustering and Bayesian inference. The 42 species were assigned to 41 BINs with 38 showing BIN concordance. These species were represented on BOLD by 7,870 records from 69 countries. Combining these records with those from Pakistan produced 60 BINs with 12 species showing a BIN split and three a BIN merger. Geo-distance correlations showed that intraspecific divergence values for 49% of the species were not affected by the distance between populations. Forty four of the 52 BINs from Pakistan had counterparts in 73 countries across six continents, documenting the broad distributions of pest aphids.

Introduction

Although aphids (Hemiptera: Aphididae) are important plant pests, their life stage diversity and phenotypic plasticity have constrained the development of effective taxonomic keys in the past [1,2]. With over 5,000 described species, the Aphididae represents the largest family within the Aphidoidea [3]. Most pest aphids belong to the subtribe Aphidina which includes 670 described species so far [3,4]. Nearly 100 aphid species have been listed as serious agricultural pests; they damage more than 300 plant species [5,6], and lower crop yield by direct feeding and by transmitting viral diseases [7].

Sibling species complexes are common in many pest aphids [8]. Very often, these species are morphologically identical but genetically distinct [9]. They often include anholocyclic biotypes (= clones) with differing host preferences and varying competency for disease transmission [10,11]. Species identification is so challenging that taxonomic keys are either ineffective or only useful for a particular geographic area or taxonomic group [12]. These deficits have prompted the search for alternative approaches for identification such as protein profiling [13] and the use of DNA sequence data [14,15]. However, the later approach has gained stronger uptake due to its universal applicability, low cost, and strong performance [16].

Past studies have demonstrated that DNA-based approaches can enable both specimen identification and the clarification of putative cryptic species complexes [17,18]. Diverse mitochondrial and nuclear genes have been used individually and in combination to discriminate insect species [19-21]. Although multigene analyses are valuable in resolving complex taxonomic situations and essential for phylogenetic reconstructions [22,23], it has seen little application in routine identifications [18]. By contrast, DNA barcoding [24] employs a 658 base pair (bp) segment of a single mitochondrial gene, cytochrome c oxidase I, to discriminate animal species. Because of its ease of application, DNA barcoding has become the most popular approach for the identification of specimens in diverse insect groups including aphids [25-32]. Its effortless integration with high-throughput sequencing workflows has made DNA barcoding an effective tool for large-scale pest diagnosis, biosurveillance, and biodiversity assessments [33-35].

The application of DNA barcoding requires bioinformatics support and a comprehensive reference library [36]. The Barcode of Life Data System (BOLD– www.boldsystems.org) [37] meets the former need and currently includes more than six million barcode records from animals. Most of these records are from insects (5.2 million) and 49,000 of them derive from aphids (accessed 3 July 2019). All barcode sequences meeting quality criteria receive a Barcode Index Number (BIN) [38]. BINs are an effective species proxy because they correspond closely with species designated through morphological study [39,40]. As a result, BINs are now routinely employed for biodiversity assessments, counting species, analyzing cryptic species complexes, and assessing species ranges [41-43]. All these developments have generated considerable interest in DNA barcoding, leading to the development of well-parameterized reference barcode libraries for some groups at continental and global scales [32,44-48].

Although the DNA barcode library for insects is still incomplete, it is already highly valuable for identifying various pest species and assessing their distributions [29,45,49-52]. However, the lack of reference sequences constrains the utility of DNA barcoding in many situations. Although barcode coverage for the aphid fauna of some countries is extensive [46,53,54], DNA barcoding studies in other nations, including Pakistan, for these pest species are limited. The current study addresses this gap by generating a barcode reference library for the pest aphids of Pakistan, and by using BINs to reveal their links to aphid assemblages in other regions.

Materials and methods

Ethics statement

No specific permissions were required for this study. The study did not involve endangered or protected species.

Aphids were sampled from 123 plant species representing 33 families at 87 sites in Pakistan (Fig 1, S1 Table) during 2010–2013. These sites included agricultural settings, nurseries, national parks, botanical gardens, natural forests, and disturbed habitats. Based on GPS coordinates, the collection sites were rendered using SimpleMappr.net (Fig 1). Aphids were collected by either beating foliage above a white paper sheet or by removing them from their host plant with a camel hair brush [55]. Collections were transferred into Eppendorf tubes prefilled with 95% ethanol and stored at -20°C until analysis.

Fig 1

Collection sites for aphids in Pakistan.

The map was generated by www.simplemappr.net using GPS coordinates.

Identification

Aphids were identified using standard taxonomic keys [55,56]. Morphological characters were examined with a Labomed CZM6 stereomicroscope (Labo America) equipped with an ocular micrometer. Each specimen was identified to species-level based on morphology. This identification was later validated by DNA barcode sequence matches on BOLD.

DNA barcoding

Front-end processing, including specimen sorting, arraying, databasing, and imaging was performed at the Insect Molecular Biology Laboratory, National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad. Individual specimens were placed into 96-well format in a microplate pre-filled with 30 μl of 95% ethanol in each well. Each specimen was photographed dorsally using a 12 megapixel Olympus μ-9000 camera (Olympus America Inc., USA) mounted on a stereomicroscope. Specimen metadata (collection information and taxonomy) and images were submitted to BOLD under the project MAAPH, “Barcoding Aphid Species of Pakistan”. DNA extraction, PCR amplification, and sequencing were carried out at Centre for Biodiversity Genomics at Guelph. DNA extraction followed Ivanova et al. [57] with voucher recovery protocol [58]. PCR amplification of the COI-5′ (barcode region) [24] was performed using primer pair C_LepFolF (forward) and C_LepFolR (reverse) (http://ccdb.ca/site/wp-content/uploads/2016/09/CCDB_PrimerSets.pdf) in 12.5 μL reactions that included standard PCR ingredients [59] and 2 μL of DNA template. The thermocycling regime was: 94°C (1 min), 5 cycles at 94°C (40 s), 45°C (40 s), 72°C (1 min); 35 cycles at 94°C (40 s), 51°C (40 s), 72°C (1 min); and a final extension at 72°C (5 min). PCR success was verified by analyzing the amplicons on 2% agarose E-gel® 96 system (Invitrogen Inc.). Specimens which failed to amplify in the first round of PCR were re-run with primers LepF2_t1 (TGTAAAACGACGGCCAGTAATCATAARGATATYGG) [60] and LepR1 using the same PCR conditions. PCR products were sequenced bidirectionally on an Applied Biosystems 3730XL DNA Analyzer using the BigDye Terminator Cycle Sequencing Kit (v3.1) (Applied Biosystems). Sequences were edited using CodonCode Aligner (CodonCode Corporation, USA), and translated on MEGA v6 [61] to confirm they were free of stop codons, and submitted to BOLD. The specimen metadata and sequences generated in this study are available on BOLD in the dataset DS-MAAPH. Vouchers were deposited at the Insect Museum, NIBGE, Faisalabad, Pakistan (with sample ID prefix NIBGE) and at the Centre for Biodiversity Genomics, Guelph, ON, Canada (with ID prefix BIOUG).

Data analysis

All barcode sequences were compared with those on BOLD and GenBank to ascertain sequence similarities. Sequence matches on BOLD were obtained using the “Identification Engine” tool whereas nBLAST (http://www.ncbi.nlm.nih.gov/blast/) was used on GenBank. All sequences meeting quality standards (>500 bp, <1% ambiguous bases, no stop codon or contamination flag) were assigned to a BIN [38] (as of 18 January 2019). BIN discordance and BIN overlap reports were generated using analytical tools on the BOLD workbench. As a test of the reliability of species discrimination, the presence or absence of a ‘barcode gap’ [62] among species was determined on BOLD. A species was considered distinct when its maximum intraspecific distance was less than the distance to its nearest neighbor (NN).

ClustalW nucleotide alignments [63] and neighbor-joining (NJ) analysis [63] were conducted in MEGA6. The NJ analysis employed the Kimura-2-Parameter (K2P) [64] distance model, with pairwise deletion of missing sites, and 1000 non-parametric bootstrap [65] replicates for the nodal support. Bayesian inference was performed in MrBayes v3.2.0 [66] employing the Markov Chain Monte Carlo (MCMC) technique. This analysis was based on representative sequences from 67 aphid haplotypes in the dataset extracted using DNaSP v5.10 [67] with Diaphorina citri (Hemiptera: Psyllidae) as outgroup. The data were partitioned in two ways; i) a single partition with parameters estimated across all codon positions, ii) a codon-partition in which each codon position was allowed different parameter estimates. The evolution of sequences was modelled by the GTR+Γ model independently for the two partitions using the ‘‘unlink” command in MrBayes, and the best model was selected using FindModel (www.hiv.lanl.gov/cgi-bin/findmodel/findmodel.cgi). The analyses were run for 10 million generations using four chains with sampling every 1000 generations. Bayesian posterior probabilities were calculated from the sample points once the MCMC algorithm converged. Convergence was defined as the point where the standard deviation of split frequencies was less than 0.002 and the PSRF (potential scale reduction factor) approached 1, and both runs converged to a stationary distribution after the burn-in (by default, the first 25% of samples were discarded). Each run produced 100001 samples of which 75001 samples were included. The trees generated through this process were visualized using FigTree v1.4.0.

BOLD was searched for barcode records for the 42 species encountered in this study. The resultant records were examined for BIN assignment [38] and used in a geo-distance correlation analysis to examine the relationship between geographic and genetic distance in each species. Two methods were employed in the latter analysis; the Mantel Test [68] was used to examine the relationship between geographic (km) and genetic (K2P) distance matrices, while the second approach compared the spread of the minimum spanning tree of collection sites and maximum intra-specific divergence [69]. The relationship between geographic and intraspecific distances was analyzed for each species with at least one individual from three or more sites. BINs recovered from Pakistan were also used in BIN-overlap analysis on BOLD to ascertain the incidence of unique BINs in a region, and to estimate overlap in BIN composition.

Results

Morphological analysis facilitated by the barcode data enabled identification of most specimens (774/809) and revealed 42 species, each representing an important crop pest (S1 Table). Another 32 specimens could be placed to a genus while the remaining three could only be assigned to a subfamily (Aphidinae). Overall, the 809 specimens included representatives of 30 genera and five subfamilies (Aphidinae, Calaphidinae, Chaitophorinae, Eriosomatinae, Lachninae) of the Aphididae (S2 Table). Members of the Aphidinae were dominant (n = 780) as the other four subfamilies were represented by just 29 specimens with Chaitophorinae and Lachninae each contributing one specimen (S2 Table). Among the determined genera, Aphis was most common one (n = 306), and was represented by eight identified and three undetermined species. Furthermore, Myzus was the second most frequent genus (n = 170), but it was only represented by one species, Myzus persicae. Rhopalosiphum, the third most abundant (83) genus, was represented by three major pest species (R. maidis, R. padi, R. rufiabdominale). Two species (Aphis astragalina, Periphyllus lyropictus) represented first records for Pakistan whereas two others (Lipaphis pseudobrassicae, Sarucallis kahawaluokalani) were known, but were recorded as Lipaphis erysimi and Tinocallis kahawaluokalani.

The 809 barcode sequences provided two or more records for 36 of the 42 species and single records for the rest (Tables 1 and S1). Maximum K2P divergence values within species ranged from 0–3.6% (mean = 0.1%), whereas distance values within genera were between 0.8–10.3% (mean = 7.4%), and within family (Aphididae) 3.7–17.3% (mean = 9.6%) (Table 1). Barcode gap analysis examined the ability of barcodes to discriminate the 42 named species. With the exception of one species (Aphis gossypii), where the maximum intraspecific distance (3.6%) overlapped with A. affinis, the maximum intraspecific distance for each species was less than its NN distance (Fig 2A, Fig 2B). This pattern did not change with increased sample size (Fig 2C).

Table 1

Sequence divergence (K2P) in the COI barcode region for aphid species from Pakistan with more than three specimens, genera with three or more species, and families with three or more genera.

This analysis only considers specimens that were assigned to a Linnaean species.

Distance class	n	Taxa	Comparisons	Min (%)	Mean (%)	Max (%)
Within Species	764	36	30756	0	0.1	3.6
Within Genus	434	6	32305	0.8	7.4	10.3
Within Family	770	1	233004	3.7	9.6	17.3

Fig 2

Barcode gap analysis for species of aphids with three or more specimens collected in Pakistan. NN = nearest neighbor.

Nearly all sequences (801/809) fulfilled the criteria for a BIN assignment, and they were placed in 52 BINs. The 774 specimens of the 42 species were assigned to 41 BINs; 38 showed BIN concordance (species members = BIN members), one species (Rhopalosiphum padi) was split (AAA9899, ACF2924), and two species (Aphis affinis, A. gossypii) were merged (AAA3070), while another, Aphis astragalina lacked a BIN assignment due to its low quality sequence (410 bp, 9 Ns). The 32 specimens lacking a species assignment were placed in 9 BINs–three for Aphis and one for each of the other six genera (Acyrthosiphon, Capitophorus, Forda, Hyalopterus, Macrosiphoniella, Schizaphis). The three specimens only identified to a subfamily were assigned to two BINs. NJ analysis (Fig 3) and Bayesian inference (BI) (Fig 4) supported the monophyly of each of the 52 BINs. The NJ and BI also discriminated the species or genera that either lacked (Aphis astragalina) or shared BINs (Aphis gossypii, A. affinis), as they formed distinct branches on the NJ and BI trees (Fig 3, Fig 4).

Fig 3

NJ analysis of COI-5′ sequences from species/BINs of aphids from Pakistan.

Bootstrap values (%) (1,000 replicates) are shown above the branches (values <50% are not shown) while the scale bar shows K2P distances. The node for each species/BIN with multiple specimens was collapsed to a vertical line or triangle, with the horizontal depth indicating the level of intraspecific divergence. BIN numbers are shown for species with only family- or genus-level identification or those split into two BINs.

Fig 4

Phylogenetic analysis of aphid species/BINs from Pakistan based on COI-5ʹ sequences.

The tree was estimated using Bayesian inference. Posterior probabilities are indicated at nodes. The analysis was based on representative sequences from 67 aphid haplotypes in the dataset that were extracted using DnaSP v5.10 (Librado and Rozas 2009). Taxa are followed by the BINs and haplotype numbers. Diaphorina citri (BOLD:AAT8865) was employed as outgroup.

Geo-distance correlation analysis for 37 species was conducted by including an additional 5,067 sequences from conspecific individuals deposited on BOLD. This analysis showed that intraspecific divergences in 49% of the species were not affected by expanding analysis to consider their entire ranges (Mantel test, P>0.01) (Table 2). The other 51%, that were affected by geographic range, included six species with BIN splits and eight with intraspecific divergence higher than >2%. The distributional patterns of aphids detected in Pakistan were further analyzed by examining BIN overlap between Pakistan and other countries, a comparison that involved 9,905 barcode records assigned to the 52 BINs. This analysis showed that 27 of the 52 BINs were recorded from four or more continents while eight were unique to Pakistan (Table 3). Except for Acyrthosiphon malvae and Uroleucon sonchi, all named species (40) analyzed in this study already had barcode records from multiple countries and continents (Table 3).

Table 2

Geographic (km) and genetic (K2P) distance correlation analysis for 42 aphid species from Pakistan combined with conspecifics from 69 other countries.

Species	Record Count	BINs	Linear Regression R2	Gen Dist Max	Geo Dist Max	Mantel R2	Mantel P value
Acyrthosiphon malvae	54	2	0.13	4.8	18675	0.13	0.01
Acyrthosiphon pisum	205	1	0.01	1.7	19312	0.01	0.05
Aphis affinis	8	1	0.18	0.2	356	0.18	0.04
Aphis astragalina	37	1	0.71	0.8	10789	0.71	0.01
Aphis craccivora	420	1	0.09	1.4	19417	0.00	0.01
Aphis fabae	426	1	0.01	2.5	19456	0.01	0.01
Aphis gossypii	362	1	0.00	3.9	19369	0.00	0.8
Aphis nasturtii	38	1	0.48	1.6	11656	0.48	0.01
Aphis nerii	99	1	0.02	1.2	19110	0.02	0.01
Aphis spiraecola	277	2	0.00	3.1	19355	0.00	0.2
Aulacorthum solani	118	1	0.13	2.0	19291	0.13	0.01
Baizongia pistaciae	5	2	0.48	4.4	5967	0.48	0.23
Brachycaudus cardui	54	1	0.17	0.9	11929	0.17	0.01
Brachycaudus helichrysi	108	4	0.01	3.1	19426	0.01	0.01
Brevicoryne brassicae	166	2	0.02	6.3	19178	0.02	0.04
Chromaphis juglandicola	11	1	0.52	0.8	10908	0.52	0.01
Hyadaphis coriandri	13	1	0.40	1.4	685	0.40	0.01
Hyalopterus pruni	151	3	0.06	6.6	16867	0.06	0.01
Hyperomyzus lactucae	87	1	0.05	0.3	19474	0.05	0.02
Hysteroneura setariae	53	1	0.04	1.9	15843	0.04	0.01
Lipaphis pseudobrassicae	91	2	0.12	3.6	18212	0.13	0.01
Macrosiphoniella sanborni	5	1	0.01	0.2	15935	0.01	0.43
Macrosiphum euphorbiae	198	1	0.14	1.6	19482	0.14	0.01
Macrosiphum rosae	80	1	0.00	1.2	19379	0.00	0.14
Melanaphis donacis	7	1	0.16	0.2	6092	0.16	0.35
Melanaphis sacchari	225	1	0.02	1.9	18400	0.02	0.01
Myzus persicae	322	1	0.00	2.2	19234	0.00	0.68
Nearctaphis bakeri	70	2	0.04	6.8	11961	0.04	0.09
Periphyllus lyropictus	33	1	0.00	0.2	11002	0.00	0.92
Rhodobium porosum	7	1	0.08	0.2	12350	0.08	0.1
Rhopalosiphum maidis	63	1	0.00	2.0	18405	0.00	0.40
Rhopalosiphum padi	1189	2	0.30	5.0	19841	0.29	0.01
Rhopalosiphum rufiabdominale	18	1	0.03	0.2	15787	0.03	0.99
Sitobion avenae	314	1	0.02	4.6	18405	0.00	0.01
Tetraneura nigriabdominalis	41	2	0.16	8.6	16534	0.16	0.01
Therioaphis trifolii	470	2	0.00	13.0	18823	0.00	0.33
Uroleucon sonchi	45	2	0.11	2.3	19003	0.11	0.03
Acyrthosiphon gossypii	5	1	N/A	N/A	N/A	N/A	N/A
Brachyunguis harmalae	8	1	N/A	N/A	N/A	N/A	N/A
Cinara tujafilina	8	1	N/A	N/A	N/A	N/A	N/A
Sarucallis kahawaluokalani	10	1	N/A	N/A	N/A	N/A	N/A
Schizaphis rotundiventris	5	1	N/A	N/A	N/A	N/A	N/A

N/A: Data for the correlation analysis was missing.

Table 3

Occurrence of 52 pest aphid BINs across six continents and their association with Linnaean species on the Barcode of Life Data System (BOLD).

BIN	Countries	Continents	(Number) and names of the associated species
AAA3070	44	6	(35) Aphis affinis, A. aliena, A. argrimoniae, A. cf. frangulae, A. chloris, A. cisticola, A. clerodendri, A. confusa, A. crepidis, A. egomae, A. frangulae, A. gossypii, A. hieracii, A. hypericiphaga, A. hypochoeridis, A. idaei, A. leontodontis, A. lichtensteini, A. longirostrata, A. madderae, A. mamonthovae, A. monardae, A. nivalis, A. oestlundi, A. origani, A. parietariae, A. punicae, A. ruborum, A. sedi, A. serpylli, A. sumire, A. taraxacicola, A. teucrii, A. viticis
AAA3759	15	6	(1) Therioaphis trifolii
AAA4183	29	6	(1) Aphis spiraecola
AAA5565	31	6	(9) Aphis fabae, A. solanella, A. hederae, A. ilicis, A. viburni, A. newtoni, A. fukii, A. lambersi, A. seselii
AAA6213	19	6	(13) Macrosiphum albifrons, M. cerinthiacum, M. cholodkovskyi, M. corydalis, M. daphnidis, M. euphorbiae, M. gaurae, M. gei, M. hellebori, M. impatientis, M. sileneum, M. valerianae, M. zionense
AAA7683	22	6	(1) Myzus persicae
AAA9899	16	4	(1) Rhopalosiphum padi
AAB1787	19	6	(1) Acyrthosiphon pisum
AAB2572	16	5	(2) Aulacorthum solani, Macrosiphum gei
AAB4239	20	4	(3) Macrosiphum rosae, M. funestum, Sitobion rosivorum
AAB4894	17	5	(1) Sitobion avenae
AAB6874	10	5	(6) Ericaphis scammelli, E. fimbriata, Rhodobium porosum, Wahlgreniella nervata, W. vaccinii, W. arbuti
AAB7937	30	6	(8) Aphis craccivora, A. masoni, A. intybi, A. rumicis, A. spiraecola, A. tirucallis, A. coronillae, A. fabae
AAB8566	20	5	(2) Hyperomyzus lactucae, H. carduellinus
AAB9726	14	6	(1) Brachycaudus helichrysi
AAC1165	13	5	(2) Brachycaudus cardui, B. lateralis
AAC1372	22	6	(1) Aphis nerii
AAC1374	8	3	(5) Aphis nasturtii, A. davletshinae, A. umbrella, A. althaeae, A. cf. rostella
AAD0145	18	6	(1) Brevicoryne brassicae
AAD0902	4	3	(1) Nearctaphis bakeri
AAD4538	12	6	(1) Rhopalosiphum maidis
AAD9153	11	6	(2) Lipaphis pseudobrassicae, L. erysimi
AAE2497	13	5	(1) Hysteroneura setariae
AAG3896	14	5	(1) Tetraneura nigriabdominalis
AAG6658	6	3	(1) Chromaphis juglandicola
AAH2863	4	3	(1) Periphyllus lyropictus
AAI0406	13	5	(1) Rhopalosiphum rufiabdominale
AAI4332	3	2	(NA) Identified to genus–Aphis
AAI7650	2	1	(1) Baizongia pistaciae
AAK5331	3	2	(1) Hyadaphis coriandri
AAK7235	22	5	(2) Melanaphis sacchari, M. japonica
AAM0964	7	4	(2) Macrosiphoniella yomogifoliae, M. abrotani
AAN2425	5	4	(1) Macrosiphoniella sanborni
AAN4898	2	2	(1) Brachyunguis harmalae
AAO7083	6	3	(1) Cinara tujafilina
AAP9276	5	3	(NA) Identified to genus–Schizaphis
AAX9332	4	3	(1) Sarucallis kahawaluokalani
AAY6004	4	2	(1) Melanaphis donacis
ACD8115	2	1	(1) Hyalopterus pruni
ACF2924	11	6	(1) Rhopalosiphum padi
ACI9922	5	3	(NA) Identified to genus–Capitophorus
ACO4203	4	2	(1) Schizaphis rotundiventris
ACO5373	2	1	(1) Hyalopterus pruni
ACS1400	2	1	(1) Acyrthosiphon gossypii
ABY0239	1	1	(NA) Identified to genus–Aphis
ACP3887	1	1	(NA) Identified to genus–Forda
ACS1208	1	1	(NA) Identified to genus–Acyrthosiphon
ACS1445	1	1	(1) Acyrthosiphon malvae
ACS2175	1	1	(NA) Identified to subfamily–Aphidinae
ACT3010	1	1	(NA) Identified to subfamily–Aphidinae
ACV1458	1	1	(1) Uroleucon sonchi
ACV6041	1	1	(NA) Identified to genus–Aphis

Discussion

Prior morphological surveys on the aphids of Pakistan have reported the presence of nearly 300 species [70-72]. Most of this work focused on specific geographic regions [73] or species attacking crops [74,75]. The current study surveyed aphids across major agricultural areas of Pakistan from a wider range of host plants, but primarily aimed to develop a barcode reference library for the fauna for the first time. Prior studies have begun to construct barcode reference libraries for some pest insect groups, such as aphids in Canada [29], leafminers in USA [76], fruit flies in Africa [45], food pests in Korea [49], thrips in Pakistan [28], looper moths in British Columbia [77], and mealybugs in China [52]. These libraries have stimulated the use of DNA barcoding in biosecurity and plant protection programs [78], but their use revealed the need for expanded parameterization of the libraries in order to improve their utility in diagnosing newly encountered species. Barcode libraries for two major pest insect groups in Pakistan, thrips and whiteflies, have progressed well [28,79], but other groups have seen little attention in this country so far. The current study not only expands on the prior efforts by barcoding another group of insect pests but also maps the global presence of pest aphids by using BINs.

Most aphids analyzed in this study were assigned to a species, but 35 specimens could only be determined to genus or subfamily level. In part, this difficulty reflected the fact that many important pest aphids are cryptic species complexes whose members are almost impossible to discriminate using morphological traits only [42] or their identification was beyond our expertise. For example, Aphis gossypii is a particularly challenging species complex [5,13]; it includes at least 18 morphologically indistinguishable species [80] likely explaining its wide range of primary and secondary host plants [81]. In the present study, DNA barcoding separated all eight species of the genus Aphis that were encountered. Although K2P distances between two species pairs; i) A. affinis and A. gossypii (1.4%), ii) A. astragalina and A. craccivora (0.8%) were low, both NJ analysis and Bayesian inference supported the monophyly of each species. The COI divergences in this study are similar to those reported in prior investigations [29,82,83] which reported low sequence divergence between sibling species such as A. gossypii and A. affinis [29].

Prior studies revealed a strong correspondence between BINs and known species [39], in particular when reference specimens are identified by experts [84]. The same pattern was apparent in this study as 38 of 41 species were assigned to a single BIN. There were only two exceptions; R. padi was assigned to two BINs and A. gossypii–A. affinis were assigned to the same BIN. By comparison, when barcode sequences from conspecific specimens from other countries were considered, 12 of the 42 species showed a BIN split, an outcome which likely indicates incorrectly identified specimens [39]. Interestingly, the BIN (AAA3070) shared by specimens of A. gossypii and A. affinis from Pakistan included 31 additional species names when all records for it on BOLD were considered. Misidentifications and overlooked cryptic species may often cause conflicts between BIN and species morphology [85], but this can only be resolved by detailed taxonomic studies [86]. As well, heteroplasmy, hybridization, and incomplete lineage sorting can also cause BIN-morphology conflicts [87,88]. Furthermore, host affinities of sympatric populations, which have been observed in aphids, also expand intraspecific divergence [89], possibly resulting in BIN splits as we observed in R. padi.

Geo-distance correlations showed that the genetic divergence increased with geographic distance in almost half of the aphid species. Interestingly, the inclusion of conspecific sequences from other regions also increased the incidence of BIN splits. Since these analyses included all the conspecific sequences on BOLD, this outcome may reflect taxonomic errors [90]. Although spatial variation in conspecific sequences sometimes leads to increased intraspecific divergence values [91], it is usually too low to reduce the capacity of DNA barcodes to deliver reliable species identifications [47,92].

BINs are valuable in evaluating the geographic range of aphid species because they circumvent taxonomic uncertainties. In addition, BINs are gaining increased use to estimate species numbers [41] and to understand their distributions [52]. This analysis revealed that 27 of the 44 BINs with prior records on BOLD occurred on four or more continents, highlighting the broad ranges of many pest aphids. For example, BINs for Aphis fabae (black bean aphid), A. nerii (oleander aphid), A. craccivora (groundnut aphid), Acyrthosiphon pisum (pea aphid), Brachycaudus helichrysi (plum aphid), Brevicoryne brassicae (cabbage aphid), L. pseudobrassicae (turnip aphid), R. padi (oat aphid), R. maidis (corn aphid), Macrosiphum euphorbiae (potato aphid), M. persicae (peach aphid), and Therioaphis trifolii (alfalfa aphid) were all recorded from six continents. Interestingly, BINs associated with some of these species were also linked with other species on BOLD. For instance, AAA3070 was linked to 33 other species of Aphis while AAA6213 was associated with 13 species of Macrosiphum, and AAA5565 with nine species of Aphis. Although some of these cases may involve BIN sharing by different species [29], most cases likely reflect misidentifications.

The level of BIN overlap between the aphid fauna of Pakistan is much higher (85%) than levels for moths (44%) [93] and spiders (24%) [94]. This difference, may, be due, in part, to the fact that the winged alates of aphids can disperse long distances and their dispersal capacity with the broad availability of the crop plants that they attack [95]. Consequently, the number of aphid species known from Europe has increased by 20% in the last 30 years [96] reflecting their transport on produced fruits [52], coupled with shifting environmental regimes. Reports suggest that with every 1°C increase, some 15 additional aphid species were recorded in Europe [97]. In North America, about 18% of all aphid species are introduced, and nearly half are plant pests [98]. Rapid developments in DNA sequencing are enabling the documentation of pest species and their distribution across the globe, but conflicts between taxonomic assignments and sequences have limited the full utility of these data. Given this difficulty, the BIN system provides an alternative path to document and track the pest species on a planetary scale.

Plant-host family range for aphid species/BINs collected in Pakistan.

(XLSX)

Click here for additional data file.

Identification and BIN assignment of 809 specimens of Aphididae collected from 123 plant hosts in Pakistan.

(XLSX)

Click here for additional data file.

23 Oct 2019

PONE-D-19-19598

BIN overlap confirms transcontinental distribution of pest aphids (Hemiptera: Aphididae)

PLOS ONE

Dear Muhammad Ashfaq,

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Line1-2. Basically the manuscript reports a barcode reference library for some Pakistan aphid species, I don't think it's appropriate to use a title focusing on distribution of pest aphids. Even without a DNA barcoding study, I still can know the geographic distribution patterns of species.

Line19-38. The abstract with many numbers may let readers get confused. The authors may keep main results and numbers only.

Line43, Line44, Line293. The Aphid Species File is a dynamically updating taxonomic reference, so it's not appropriate to cite a version in 2017. And therefore authors need to check the number of species in related groups.

Line165-179. For a DNA barcoding research, the morphologically identification maybe the first step and detail statistics should be placed better in Methods section.

Line215. 'across much of Pakistan', based on the sampling map, I think "much of Pakistan" is inappropriate.

Line225-230. The discussion here may have logic problem. Specimens could only be identified to a genus and especially subfamily levels can be only due to the authors are not familiar with some aphid groups. If you say the reason is about 'cryptic species complexes', meaning at least the samples can be identified genus level based on sequences. And for the cotton aphid example, the authors cited two relatively old references, do you think the information of 'at least 20 morphologically indistinguishable species' is OK now?

One lack of the current version is that, for their own dataset, the authors discuss very little about the 'conflicts between taxonomic assignments and sequences' or 'BIN split' and 'BIN merger' based on biology of related aphids. So the depth of current discussion is not enough.

Another problem is, whether the authors did think about the sequence quality in the BOLD system? Sequence with problem may lead to wrong split or merger. The fact is that BOLD sequences have quality problem for many insect groups. At least, the authors need to mention and discuss their opinion about this.

Reviewer #2: The manuscript “BIN overlap confirms transcontinental distribution of pest aphids” (PONE-D-19-19598) by Naseem and co-authors analyzes 809 DNA barcodes of aphids from Pakistan using the BOLD workbench. Furthermore, they combined their sequence data with already available DNA barcodes, revealing a broad distribution of pest aphids across six continents.

It is obvious that DNA barcoding as well as upcoming metabarcoding approaches using high throughput sequencing technologies will play a more and more important role in order to document and assess biodiversity in the near future. Therefore we need more comprehensive sequence libraries for a correct identification. The topic of this manuscript is interesting and appropriate for PLoS ONE, indicating a relevant application of DNA barcoding in order to identify an economically and ecologically important group of species. However, various concerns remain and have to be corrected before the manuscript is suitable for publication.

High-throughput sequencing technologies will play an essential role in modern biodiversity research. However, no aspects of this topic are discussed so far. Furthermore, I miss a discussion of possible pitfalls of using DNA barcodes and mtDNA in general in terms of specimen identification, e.g., the existence of incomplete lineage sorting, heteroplasmy etc. as part of the introduction or discussion.

Please find some specific comments made via sticky notes on the PDF file of the manuscript.

Reviewer #3: This paper provides valuable data of aphid DNA barcodes. The sampling is limited to Pakistan, but focusses on pest species, increasing the applicative value of the data, especially as most pests have wide distributions. The paper does not contain much scientific novelty besides adding new valuable records to the barcode databases. The paper nicely demonstrates the benefits of BINs in assigning specimens into the same taxonomic units when this is otherwise hampered by misidentifications and taxonomic uncertainties. I recommend the publication after a very minor review. I do not have any major comments, although I find that in some places the authors are close of drawing too strong conclusions based on assumptions. For example, they conclude some issues being because of misidentifications in other works, although they hardly could show this being certainly the case.

I recommend carefully checking the sentences at lines 270-274 as the sentences there do not appear fully clear to me. For example: “…are they use widely crop plants…” (perhaps “as they use…”). Similarly. “…their transport on produce fruits…”” (perhaps: “…their transport on produced fruits…”).

It is my odd hobby to spot glitches in the references. Here we go:

References 24 and 25: One initial perhaps lacking with the author Hebert

Reference 48. Kirichenkoa > Kirichenko

Lines 458-471: line spacing deviates from that of other parts

Reference 89: EXploitation > Expointation (supposedly)

Reference 91: Footit > Foottit

Disclaimer: I am neither Mr Hebert, nor Mrs Kirichenko, nor Mr Foottit.

Additional small glitches:

Line 559: The word “Linnean” has a different font size.

Figure 3: The name “Sarucallis kahawaluokalani” is not italicized

Figure 3: The name “Aphidinae” should not be italicized as being a subfamily-level name.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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Submitted filename: PONE-D-19-19598_R.pdf

Click here for additional data file.

4 Nov 2019

November 4, 2019

PONE-D-19-19598: BIN overlap confirms transcontinental distribution of pest aphids (Hemiptera: Aphididae)

Response to Reviewers

The comments from the Reviewers are included in italics followed by our response.

Reviewer Comments to Author:

Reviewer #1:

COMMENT: Line1-2. Basically the manuscript reports a barcode reference library for some Pakistan aphid species, I don't think it's appropriate to use a title focusing on distribution of pest aphids. Even without a DNA barcoding study, I still can know the geographic distribution patterns of species.

Response: The use of BIN assignments to map the geographic distribution of aphids and other species of pest insects is a key message of our study and this is reflected in the title. We certainly agree with the reviewer that species distributions can be mapped in other ways (e.g. via morphological studies by taxonomists). However, since the taxonomic expertise to correctly identify species is often not available, additional/alternative tools are needed to support species identification. DNA barcoding/BINs meet this need. The utility of the BINs system is further enhanced by the capacity of high-throughput sequencers to support metabarcoding, an approach which allows the species composition of bulk samples to be rapidly assessed.

COMMENT: Line19-38. The abstract with many numbers may let readers get confused. The authors may keep main results and numbers only.

Response: Several of the less important numbers were removed from the Abstract.

COMMENT: Line43, Line44, Line293. The Aphid Species File is a dynamically updating taxonomic reference, so it's not appropriate to cite a version in 2017. And therefore authors need to check the number of species in related groups.

Response: Reference [3] has been updated to the format suggested by the database developer.

COMMENT: Line165-179. For a DNA barcoding research, the morphologically identification maybe the first step and detail statistics should be placed better in Methods section.

Response: Detailed statistics were included in the Results section because DNA barcoding was used to support and facilitate the morphological identifications and finalize the species names. We have mentioned this in the first line of the Results.

COMMENT: Line215. 'across much of Pakistan', based on the sampling map, I think "much of Pakistan" is inappropriate.

Response: “across much of Pakistan” has been changed to “major agricultural areas of Pakistan” since the areas covered in this study are mostly agricultural lands and plains.

COMMENT: Line225-230. The discussion here may have logic problem. Specimens could only be identified to a genus and especially subfamily levels can be only due to the authors are not familiar with some aphid groups. If you say the reason is about 'cryptic species complexes', meaning at least the samples can be identified genus level based on sequences. And for the cotton aphid example, the authors cited two relatively old references, do you think the information of 'at least 20 morphologically indistinguishable species' is OK now?

Response: We agree with the reviewer’s comment and have expanded the statement by adding – “or their identification was beyond our expertise”.

About cotton aphid (Aphis gossypii): Citations supporting the morphological complexity of A. gossypii are from 2007 (Blackman & Eastop) and 2014 (Favret). These authors are renowned aphid taxonomists and their conclusions on A. gossypii have not been challenged.

Based on a more recent report (2014), the statement on the number of species in A. gossypii group has been revised and the old citation [76; Stroyan 1984] has been replaced with a new one (Lagos-Kutz et al. 2014).

An old citation on the range of host plants [77, 1955] has been replaced with a more recent report by Singh G, Singh NP, Singh R, Singh G, Singh NP (2014). Food plants of a major agricultural pest Aphis gossypii Glover (Homoptera: Aphididae) from India: An updated checklist. International Journal of Life Sciences Biotechnology and Pharma Research. 2014;3: 1–26.

COMMENT: One lack of the current version is that, for their own dataset, the authors discuss very little about the 'conflicts between taxonomic assignments and sequences' or 'BIN split' and 'BIN merger' based on biology of related aphids. So the depth of current discussion is not enough.

Response: One species in our dataset was assigned to two BINs (BIN split) and two shared a BIN (BIN merger). These cases of BIN-morphology conflicts (split and merger) have now been discussed (lines 377-380; revised manuscript with track changes).

COMMENT: Another problem is, whether the authors did think about the sequence quality in the BOLD system? Sequence with problem may lead to wrong split or merger. The fact is that BOLD sequences have quality problem for many insect groups. At least, the authors need to mention and discuss their opinion about this.

Response: BOLD follows stringent quality criteria and sequences not meeting them (<1% ambiguous bases, no stop codon or contamination flag) are not assigned a BIN. This has already been stated in the Data Analysis section of the Methods. Only high quality, validated sequences were included in the current study.

BOLD is a public resource and allows users to submit sequences and specimen data without prior permission. However, it does provide quality filters that allow users to exclude invalid and poor quality sequences from any analysis.

Reviewer #2:

COMMENT: The manuscript “BIN overlap confirms transcontinental distribution of pest aphids” (PONE-D-19-19598) by Naseem and co-authors analyzes 809 DNA barcodes of aphids from Pakistan using the BOLD workbench. Furthermore, they combined their sequence data with already available DNA barcodes, revealing a broad distribution of pest aphids across six continents.

It is obvious that DNA barcoding as well as upcoming metabarcoding approaches using high throughput sequencing technologies will play a more and more important role in order to document and assess biodiversity in the near future. Therefore we need more comprehensive sequence libraries for a correct identification. The topic of this manuscript is interesting and appropriate for PLoS ONE, indicating a relevant application of DNA barcoding in order to identify an economically and ecologically important group of species. However, various concerns remain and have to be corrected before the manuscript is suitable for publication.

High-throughput sequencing technologies will play an essential role in modern biodiversity research. However, no aspects of this topic are discussed so far. Furthermore, I miss a discussion of possible pitfalls of using DNA barcodes and mtDNA in general in terms of specimen identification, e.g., the existence of incomplete lineage sorting, heteroplasmy etc. as part of the introduction or discussion.

Response: We have added a statement on the integration of DNA barcoding with high-throughput sequencing workflows to the Introduction. A discussion point on the potential shortcomings of DNA barcoding (heteroplasmy, incomplete lineage sorting) has been included in the Discussion.

Please find some specific comments made via sticky notes on the PDF file of the manuscript.

COMMENT: L28: Why 801 and not 809 (see above)?

Response: This difference reflects the fact that only sequences meeting quality standards (>500 bp, <1% ambiguous bases, no stop codon or contamination flag) were assigned a BIN. Eight sequences didn’t meet the BIN standard. This has been clarified on lines 128-129 in the Methods section.

COMMENT: L41: It would be nice to see some images of the analyzed species. Use the options that open access and PLOS ONE offer!

Response: The microscope used for morphological identification of aphids lacked a high quality camera. As a result, most of the images lack the resolution to make morphological characters useful for species assignments. However, as mentioned in the manuscript (line 106), all images taken for the study are accessible on BOLD.

COMMENT: L45: Sounds a little bit to drastic; please change.

Response: “Attack” was changed to “damage”.

COMMENT: L52: Cybertaxonomy per se does not represent an "alternative approach for identification". Instead of this, it focusses on comprehensive descriptions allowing valid identifications (e.g., Organisms, Diversity and Evolution 16: 1-12). Please change this part.

Response: Cybertaxonomy and the related reference have been removed. A new reference on the use of protein profiling for species identification has been added.

Jayaseelan M, Roesler Uwe R. MALDI-TOF MS Profiling-Advances in species identification of pests, parasites, and vectors. Front Cell Infect Microbiol. 2017;7: 184.

COMMENT: L70: Keep in mind that BIN assignments on BOLD are constant¬ly updated as new sequences are added, splitting and/or merging individual BINs in light of new data. Therefore, BINs are not written in stone and can change. Therefore it is important to document the specific date of BIN assignment.

Response: The date of the BIN assignment has been documented in the Methods section (line 131).

COMMENT: L76: See also PLoS ONE 9(9) e106940.

Response: Suggested reference (PLoS ONE 9(9) e106940) has been cited.

COMMENT: L113: 94 °C (a gap between the number and °C here and in the following).

Response: Corrected.

COMMENT: L123: What about the deposition of vouchers?

Response: Information on the deposition of vouchers has been added (line 126-128).

COMMENT: L134: Think about updating your MEGA-version. The most recent version is 10!

Response: We thank the Reviewer for this suggestion. We used MEGA v6 just because it has been well tested. We will consider the newer version for our next study.

COMMENT: L223: Please rephrase

Response: Sentence has been rephrased to clarify the statement.

Reviewer #3:

COMMENT: This paper provides valuable data of aphid DNA barcodes. The sampling is limited to Pakistan, but focusses on pest species, increasing the applicative value of the data, especially as most pests have wide distributions. The paper does not contain much scientific novelty besides adding new valuable records to the barcode databases. The paper nicely demonstrates the benefits of BINs in assigning specimens into the same taxonomic units when this is otherwise hampered by misidentifications and taxonomic uncertainties. I recommend the publication after a very minor review. I do not have any major comments, although I find that in some places the authors are close of drawing too strong conclusions based on assumptions. For example, they conclude some issues being because of misidentifications in other works, although they hardly could show this being certainly the case.

Response: We thank the reviewer for these valuable comments and suggestions. Although our sampling program was limited to one nation (Pakistan), we were able to extend the analysis to global scale by exploiting the BIN system. Our statements on issues related to misidentification of species are not meant to diminish the value of morphological identification. We simply highlight the difficulties of gaining reliable morphological identifications in areas where the required taxonomic specialists are lacking.

COMMENT: I recommend carefully checking the sentences at lines 270-274 as the sentences there do not appear fully clear to me. For example: “…are they use widely crop plants…” (perhaps “as they use…”). Similarly. “…their transport on produce fruits…”” (perhaps: “…their transport on produced fruits…”).

Response: These sentences have been corrected.

COMMENT: It is my odd hobby to spot glitches in the references. Here we go:

References 24 and 25: One initial perhaps lacking with the author Hebert

Reference 48. Kirichenkoa > Kirichenko

Lines 458-471: line spacing deviates from that of other parts

Reference 89: EXploitation > Expointation (supposedly)

Reference 91: Footit > Foottit

Response: These references and line spacing have been corrected. Exploitation is the original word used by the authors, so it was not changed.

COMMENT: Additional small glitches:

Line 559: The word “Linnean” has a different font size.

Figure 3: The name “Sarucallis kahawaluokalani” is not italicized

Figure 3: The name “Aphidinae” should not be italicized as being a subfamily-level name.

Response: Corrected.

Submitted filename: Response-to-Reviewers_PONE-D-19-19598.docx

Click here for additional data file.

19 Nov 2019

PONE-D-19-19598R1

BIN overlap confirms transcontinental distribution of pest aphids (Hemiptera: Aphididae)

PLOS ONE

Dear Muhammad,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

We would appreciate receiving your revised manuscript by Dec. 19th, 2019. When you are ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). This letter should be uploaded as separate file and labeled 'Response to Reviewers'.

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Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

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Feng ZHANG, Ph.D.

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: It is nice to see that the authors accepted most comments and/or remarks. Some minor concerns still remain (see sticky notes). After correction, the manuscript should be suitable for publication in PLoS ONE.

Reviewer #3: I like that the authors have carefully addressed both the issues that I myself spotted, but also the issues spotted by the other reviewers. I noticed that one of my own comments was with a mistake. I definitely did not mean to change the word "exploitation" to "expointation" in the reference list, but to remove the double capital in the previous word (EXploitation > Exploitation).

**********

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

Reviewer #3: No

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Submitted filename: PONE-D-19-19598_R1.pdf

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19 Nov 2019

November 19, 2019

PONE-D-19-19598: BIN overlap confirms transcontinental distribution of pest aphids (Hemiptera: Aphididae).

Response to Reviewers

The comments from the Reviewers are included in italics followed by our response.

Reviewer Comments to Author:

Reviewer #2:

COMMENT: It is nice to see that the authors accepted most comments and/or remarks. Some minor concerns still remain (see sticky notes). After correction, the manuscript should be suitable for publication in PLoS ONE.

Response: All the comments, pointed out through sticky notes on the pdf, have been addressed in the revised version.

COMMENT: L137: Which program was used? MUSCLE? You should mention it (inc. giving the reference).

Response: Nucleotide sequence alignment was performed using ClustalW. This has been mentioned, with relevant reference, in the revised version.

COMMENT: L299: Most DOIs and PMIDs are still missing

Response: We have followed the reference style for PLOS ONE. This style does not ask for DOIs and PMIDs when the volume and page numbers are available.

Reviewer #3:

COMMENT: I like that the authors have carefully addressed both the issues that I myself spotted, but also the issues spotted by the other reviewers. I noticed that one of my own comments was with a mistake. I definitely did not mean to change the word "exploitation" to "expointation" in the reference list, but to remove the double capital in the previous word (EXploitation > Exploitation).

Response: The comment has been addressed.

Submitted filename: Response-to-Reviewers_PONE-D-19-19598R1.docx

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25 Nov 2019

BIN overlap confirms transcontinental distribution of pest aphids (Hemiptera: Aphididae)

PONE-D-19-19598R2

Dear Dr. Muhammad Ashfaq,

We are pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it complies with all outstanding technical requirements.

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

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With kind regards,

Feng ZHANG, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

2 Dec 2019

PONE-D-19-19598R2

BIN overlap confirms transcontinental distribution of pest aphids (Hemiptera: Aphididae)

Dear Dr. Ashfaq:

I am pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Feng ZHANG

Academic Editor

PLOS ONE