Taxon Sampling and Morphological Identification

All the specimens were collected and stored in 95% ethanol during 2008–2012, and kept at -20 °C until processed. In each case, adults were examined using various characters described by Mound et al. 1996; Moritz et al. 2004. Prior to molecular work, all the thrips species were morphologically identified. In total, 151 thrips specimens representing 8 species were used for CO-I sequencing in this study (Table 1) and other sequences were retrieved from BOLD and NCBIGenBank (see Supplementary Table 1). A summary of the current scientific classification of each thysanopteran species is given in Supplementary Table 2. These supplementary tables are available online in Florida Entomologist 97(4) (2014) at  http://purl.fcla.edu/fcla/entomologist/browse.

DNA Isolation and Polymerase Chain Reaction (PCR)

A single specimen of each species of Thrips was digested overnight at 60 °C in lysis solution (10 mM Tris-HCl- pH-7.60, 20 mM NaCl, 100 mM Na₂ EDTA- pH-8.0, 1% Sarkosyl and 0.1 mg/mL proteinase K). DNA was extracted from the supernatant employing a non-destructive method (Mound and Morris, 2007a); while at the same time voucher specimens were mounted on glass slides and deposited with the National Pusa Collection (NPC), Indian Agricultural Research Institute (IARI), New Delhi, India. Standard protocols were employed for Polymerase Chain Reaction (PCR), cloning and sequencing (Hajibabaei et al. 2006).

Table 1.

Analysed samples of thrips species from the current study with descriptions of the sampling locations, Genbank accession numbers, names of thrips species and host plants, dates and voucher specimen details.

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Table 2.

Intraspecific K2P genetic divergence among thrips species.

PCR was performed in a thermal cycler (ABIApplied Biosystems, Veriti, USA) using the following cycling parameters; an initial denaturation step at 94 °C for 5 min followed by 35 cycles at 94 °C for 30 s, an annealing step at 48 °C for 45 s, an extension step at 72 °C for 45 s and a final extension step at 72 °C for 20 min using the CO-I specific primers: LCO-1490 ; 5′-GGT CAA CAA ATC ATA AAG ATA TTG G-3′ and HCO-2198; 5′- TAA ACT TCA GGG TGA CCA AAA AAT CA-3′ (Hebert et al. 2003a; Hebert et al. 2003b). The total reaction volume of 25 µL contained 10 µM of each primer, 2.5 µL of 10X buffer, 2.5 mM MgCl₂, 0.25 mM of each dNTP and 1.0 U of Taq DNA polymerase (Fermentas Life Sciences, United Kingdom). The amplified products were resolved on 1.2% agarose gel, stained with ethidium bromide (10µg/mL) and visualized in a gel documentation system (UVP).

Sequencing and Sequence analyses

Each PCR product was purified using Gel extraction Kit (NucleospinR Extract II, Macherey Nagel, Germany), cloned by ligation into PTZ57R/T vector (Fermentas Life Sciences, UK) and used to transform competent Escherichia coli (DH5á) cells. Blue- White colony, selection was carried out and plasmids were isolated using GenJET™ plasmid MiniPrep kit (Fermentas Life Sciences, United Kingdom), according to the manufacturer's protocol from the overnight culture of positive clones cultured in Luria Broth. Sequencing was performed in an automated sequencer (ABI prismR 3730 XL DNA Analyzer; Applied Biosystems, USA) using M13 universal primers, in both forward and reverse directions. A homology search was done using NCBI-BLAST ( http://blast.ncbi.nlm.nih.gov/) and sequence alignment was performed using BioEdit version 7.0.9.0 (Hall et al. 1999). In this study, we analyzed all the available thrips CO-I sequences from NCBI-GenBank for understanding and determining the intraspecific variations in each species (Meyer et al. 2005). All the sequences generated from this study are available at BOLD ( www.barcodingoflife.com) and in NCBI-GenBank. The complete details such as Thrips species, host plants, date of collection and voucher specimen number are given in Supplementary Table 1 along with the NCBI-GenBank extracted sequences.

CO-I sequences were aligned using the Clustal W program integrated in BioEdit.7.0 (Hall et al. 1999). The sequences were further analyzed employing MEGA.5.0 (Kumar et al. 1993) to obtain conspecific and congeneric distances, whilst Neighbor-Joining trees were constructed employing the Kimura-2-parameter (K2P) distance model (Kimura et al. 1980; Saitou et al. 1987). Node support were assessed with 1000 bootstrap pseudoreplicates.

Neighbor Joining Analysis

The CO-I dataset resulted in a single NJ tree representing 151 thrips species, which formed distinct haplotype clusters (Fig. 1). The intraspecific and intrageneric sequence divergence ranged from 0.0 to 7.91% and 8.65% to 31.15%, respectively (Table 2 and Table 3, respectively). This discrete barcoding gap between intra and inter specific distances (Hebert et al. 2004) allowed us to clearly distinguish all the thrips species employed in this study. Besides being direct pests, many of the thrips species are known to vector Tospoviruses (Mound et al. 1996). In this regard, it is important to analyze the diversity within thrips species such as, Thrips palmi, T. tabaci, Frankliniella occidentalis, Scirtothrips dorsalis, F. schultzei, Thrips hawaeiinsis, S. perseae and Chirothrips manicatus, etc. For the first time, we were able to record the existence of possible cryptic species within 2 Thrips spp. viz. T. hawaiiensis and S. perseae along with previously reported cryptic species viz., T. palmi (Rebijith et al. 2011; Glover et al. 2010), T. tabaci (Brunner et al. 2004), F. occidentalis (Rugman- Jones et al. 2010), S. dorsalis (Rebijith et al. 2011; Kadirvel et al. 2013) based on the ‘CO-I- 10X barcoding Rule' proposed by Hebert et al. 2004. All of them were supported by the calculated intra and inter specific genetic divergence (Table. 4) for different sub clusters as shown in Fig. 2 (A – F).

Thrips palmi

Thrips palmi was represented by 145 specimens forming 2 lineages. One lineage (n = 102) was consisted of the Indian T. palmi population collected from various host plants, and the second lineage (n = 43) represented the world population with T. palmi representatives from China, Dominican Republic, Thailand, Japan and United Kingdom. There was much less variation (0.4% to 0.7%) within these lineages, however 8.2% difference (hereafter, D) was observed between them (Fig. 2A, Table 4), which is indicative of geographically isolated cryptic species.

Thrips tabaci

A total of 146 of T. tabaci specimens were analyzed and found to form 2 clades. The first clade comprised a T. tabaci population representing various geographical locations across the globe from different host plants. However, the second clade represented a population collected only from the tobacco plant, Nicotiana tabacum. As an indicator of cryptic species, there was less variation evident within these clades (0.3% to 0.9%), whereas 9.0% D observed between them (Fig. 2B, Table 4).

Scirtothrips dorsalis

Scirtothrips dorsalis was represented by 39 specimens forming 4 lineages, among which no perfect lineages - neither with geographical locations nor host associated genetic differences - were formed. However, very little variation (0 to 0.96%) was observed within these lineages, and 1.84% to 10.07% D observed between them, which was indicative of the cryptic speciation in S. dorsalis (Fig. 2C, Table 4).

Frankliniella occidentalis

Frankliniella occidentalis was represented by 224 specimens, which formed 5 lineages of which none was > 500 bp in length. However, the genetic variation within and between the major 2 clades were 0 to 0.10% and 1.11 to 6.2%, respectively (Fig. 2D, Table 4).

Thrips hawaiiensis

Thrips hawaiiensis was represented by 22 specimens forming 5 lineages (Fig. 2E) with genetic variation 0 to 0.5% within these lineages and 3.4% to 9.5% between them (Table 4).

Scirtothrips perseae

Scirtothrips perseae was represented by 47 specimens forming 3 lineages, of which the first, second and third were represented by 6, 4 and 37 specimens respectively, with intra and inter subcluster values ranging from 0.07% to 0.91% and 5.1 to 11.6%, respectively (Fig. 2F, Table 4).

Genetic Divergence

DNA barcoding has become an important tool in species identification, and has improved our ability to understand diversity among populations through to higher level taxa (Puckridge et al. 2013). Researchers employed a 2% genetic divergence cutoff value for species identification. However, many exceptional cases are reported with lower interspecific genetic divergences, yet most of the cases were still able to be correctly dissected out amongst most of the species (Pfannenstiel et al. 2008). By employing this 2% cutoff criterion for species delimitation, we aptly identified all thrips species in this study.

The mean K2P genetic distance values found for conspecific and congeneric comparison were 3.5% and 17.3% respectively, which were found to be on par with previous studies (Glover et al. 2010). Additionally, we analyzed a large number of closely related species, e.g., species of Genus Thrips, our observed mean congeneric divergence value was slightly smaller than in previous studies (Glover et al. 2010). This could be either due to the possible recent species radiation of Thrips similar to that of fresh water fish fauna (Albert et al. 2011; Bermingham et al. 1998; Montoya- Burgos et al. 2003), or the possible evolutionary rate variation of CO-I among different species employed in this study.

Advantages of DNA Barcoding in Taxonomy

Classical taxonomy employing morphological characters cannot be used for all species of thrips in all life stages because of insufficient phenotypic variation (Brunner et al. 2004). In addition, the presence of unusual morphological forms of species on different hosts, minute size, co-existence of different species on the same host, complex life cycles, color morphs, and parthenogenetic mode of reproduction, etc., add to the difficulties of precise identification. Furthermore, morphological examination of thrips to species requires adult specimens as there are no reliable keys for identification of immature stages, but even these are often difficult for a non-expert to use. In this regard, DNA barcoding can be an added advantage and an effective tool for molecular species identification (Brunner et al. 2004; Glover et al. 2010; Lee et al. 2010), elucidation of biotypes or cryptic species, and host associated genetic differences (Shufran et al. 2000; Brunner et al. 2004) and species discovery (Foottit et al. 2010) in insects. Additionally, DNA barcoding could also be used in the identification of unknown thrips species that co-exist in a cropping system, since one particular Tospovirus disease may sometimes be vectored by more than one species of thrips (Wijkamp et al. 1995; Kadirvel et al. 2013; Amin et al. 1981).

Table 4.

List of species with higher intraspecific k2p divergences.

Fig. 2A.

Neighbor-Joining tree with bootstrap support (2,000 replicates) showing clustering of T. palmi species for CO-I sequences. Two distinct groups can be seen Group-I (Thrips palmi- RWD, represents the T. palmi populations from various countries viz. Japan, China, Dominican Republic, Thailand and U.K.) and Group-II (Thrips palmi- IND, which clearly associated with Indian subcontinent), with 100% bootstrap support.

In the recent past, DNA barcoding has become an effective tool in revealing cryptic and potentially new species, which has increased our knowledge of biodiversity (Rebijith et al. 2013; Puckridge et al. 2013). In this study, 7 species showed conspecific genetic divergence values ≥ 2%, and were subdivided into further sub clusters (Fig. 3 a– h). Hebert et al. (2004) proposed the ‘CO-I DNA 10X barcoding rule', whereby identification of cryptic species is possible if the 2 lineages diverge by 10 times or more the average intra sub cluster variability within these lineages. In this study, such a sub cluster analysis has revealed tight clusters with significant larger mean values (2.57% to 18.02%), and smaller mean values within subclusters (0.00 to 3.28%) (Table 5). Such deep conspecific divergence has been reported previously in DNA barcoding and most of the entities are considered as cryptic species (Handfield & Handfield et al. 2006; Smith et al. 2006; Gomez et al. 2007; Pfenninger et al. 2007; April et al. 2011). The possible reasons for such higher conspecific genetic divergences are (i) representation of a novel species (ii) misidentification of species, and (iii) host/geographic preference of the organism (Brunner et al. 2004). However, according to Shao et al. (2003), the 10X estimation may be too low for Thrips, since they are known to have greater mitochondrial gene rearrangements and molecular evolution.

On the other hand, 2 Thrips species, viz. T. palmi and T. tabaci, require special attention because of their geographic and host associated genetic differences. Thips palmi formed 2 lineages; of which one lineage is unique to India (IND) and second lineage represents the rest of the world (ROW) (Rebijith et al. 2011). Geographic isolation and genetic drift can contribute strongly to intraspecific phylogeographic structure (Avise et al. 1987). Such allopatric lineages reinforce the fact that both these populations (IND and ROW) have independent evolutionary histories, which could be explained by restricted gene flow due to many physical and chemical barriers (April et al. 2011). Whereas in the case of T. tabaci, the 2 biotypes viz. ‘tabaci' and ‘communis', can be clearly distinguished with a character on the abdomen of the second larval stage (Zawirska et al. 1976). Brunner et al. (2004) proved the existence of 3 host associated genetic groups, viz. L1, L2 (Leak plant- ‘communis type' sensu Zawirska) and T (Tobacco plant-‘tabaci type') and proposed that when host fidelity is perfect, reproductive isolation is complete. In recent studies Jacobson et al. (2013) grouped T. tabaci into two entities based on their reproductive mode. However, our results showed 2 lineages, one with tobacco plants and the second is with various host plants such as onion, leak, etc., on par with previous studies (Zawirska et al. 1976; Brunner et al. 2004). In a nutshell, we conclude that all these cases represent cryptic species, but both T. palmi and T. tabaci can be subdivided and are strong candidates for novel species.

Fig. 2B.

Neighbor-Joining tree with bootstrap support (2,000 replicates) showing clustering of T. tabaci species for CO-I sequences. Two distinct groups can be seen Group-I (Thrips tabaci- ‘tabaci type'- represents the T. tabaci populations from host plant tobacco, Nicotiana tabacum and Group-II (Thrips tabaci- ‘communis type'- which clearly associated with various host plants such as onion, leek, etc.) with 100% bootstrap support.

DNA Barcoding in Biosecurity

One of the major threats to crop production and productivity is the spread of invasive species such as thrips, aphids, whiteflies and planthoppers, etc., within and outside the country. Many of the monitoring programs are challenged by both quantity and quality of materials at the port of entry as well as the taxonomic breadth of intercepted organisms. Furthermore, morphological examination of majority of agricultural invasive pests such as thrips to species level is usually restricted to (i) adult specimens as there are no adequate keys for eggs, larvae or pupae (ii) polymorphism and (iii) sexual forms. At this juncture, CO-I based molecular identification has an added advantage of not being limited by any of the above factors, and DNA barcoding has shown success in discriminating arthropods of quarantine importance such as Tephritidae, Lymantriidae (Armstrong et al. 2005), Spodoptera spp. (Nagoshi et al. 2011), Liriomyza spp. (Scheffer et al. 2006) and Thysanoptera (Qiao et al. 2012). Thus, DNA barcoding can play a vital role in the international bio-security as an additional diagnostic protocol for quarantine pests at the port of entry (FAO 2006). DNA barcoding technique has been employed in New Zealand since 2005 for the identification of Tephritidae and Lymantriidae (Armstrong et al. 2005). Thrips species used in the current study were differentiated on the basis of DNA barcodes, which proved to be an invaluable tool for identification of Thysanoptera invasive insect pests, an approach complementing classical taxonomy. Having all these advantages, DNA barcoding was included as an effective diagnostic tool for invasive insect pest in the International Plant Protection Convention (IPPC) (FAO 2006).

Fig. 2C.

Neighbor-Joining tree with bootstrap support (2,000 replicates) showing clustering of S. dorsalis species for CO-I sequences. Four distinct groups can be seen, among which group-III corresponds to S. dorsalis collected on various host plants from China. Sequences generated from this study formed group I along with other sequences from Japan and Thailand.

Implications of DNA Barcoding for Insect Pest Management

Thrips continue to pose dual problems by either direct feeding or by transmitting plant pathogenic tospoviruses in both field and green house conditions (Mound et al. 1996; Rebijith et al. 2011). Control of thrips with insecticides is a difficult task due to their parthenogenetic mode of reproduction (Rebijith et al. 2013), mode of life cycles (Brunner et al. 2004), etc. Eggs and pupae are protected either in leaf tissue or in soil/leaf litter and the larvae & adults are protected within buds and flowers (Glover et al. 2010). Yet, farmers employ insecticides as a primary control measure for the management of thrips, which could ultimately lead to the insecticide resistance.

Fig. 2D.

Neighbor-Joining tree with bootstrap support (2,000 replicates) showing five distinct clusters for F. occidentalis CO-I sequences. Number in bracket indicates, the individuals formed that cluster.

Fig. 2E.

Neighbor-Joining tree with bootstrap support (2,000 replicates) showing five clusters for T. hawaiiensis CO-I sequences.

Plant disease management requires accurate identification of species to understand the biology, population structure and ecology of the species (Rebijith et al. 2013). In this connection, T. palmi and T. tabaci, which infest watermelon to which they transmit Watermelon Bud Necrosis Virus, WBNV, and onion to which they transmitting Iris Yellow Spot Virus, IYSV, respectively, demand quick control measures using pesticides in order to limit the spread of these most potent viruses. On the other hand, Thrips flavus and Thrips nigropilosus (morphologically very similar to T. palmi and T. tabaci), can be managed effectively by employing biological control agents known as entomopathogenic nematodes (EPNs), such as Thripenema fuscum n. sp. (Asokan and Rebijith, unpublished data).

Reducing unnecessary pesticide usage through proper species identification can save growers money, and reduce chances of development insecticide resistance, as well as be more environmentally protective.