Spodoptera spp. (Lepidoptera: Noctuidae) are highly polyphagous pests that inflict serious damage to a wide spectrum of crops. The ability of Spodoptera spp. to thrive on diverse host plants is an adaptive advantage for their survival in the ecosystem, which is achieved by its high mobility, fecundity and capacity to develop resistance to wide spectrum of chemical insecticides. In this study, we present molecular diversity and phylogenetic relationship of S. litura (Fabricius) and S. exigua (Hübner) inferred from mitochondrial cytochrome oxidase-I (COI). Alignment of the sequences of COI from various life stages of the 2 species of Spodoptera shows that the molecular identification is independent of life stages and polymorphism of the target species. Maximum likelihood analyses of S. litura, S. exigua and S. mauritia (Boisduval) reveal that there exist significant variations among these. Spodoptera exigua showed intraspecific variations with respect to different geographic locations. Present study proves the utility of COI for identification of S. litura and S. exigua irrespective of their life stages, and also draws inferences on the phylogenetic relationships between the 3 pest species.
The genus Spodoptera (Lepidoptera: Noctuidae) occurs throughout the warmer regions of the world (Mitchell 1979). The tobacco cutworm, Spodoptera litura (Fabricius), is a polyphagous pest of diverse vegetable and field crops; it is known to damage more than 120 species worldwide (Thomas et al. 1969; Knipling 1980). The species is native to Asia and is distributed throughout tropical and temperate regions of Asia, Australia, Africa, the Middle East, southern Europe, and the Pacific Islands. The high insecticide resistance combined to high adult dispersal and migration capacity allows S. litura to utilize various types of host plants including tobacco, castor, groundnut, maize, cotton and rice to a number of grain legumes and vegetable crops (Sparks 1979; Johnson 1988). In India S. exigua (Hübner) is a serious pest of jute and tobacco. It is commonly known as beet armyworm and one of the important crop pests in the tropics. Using diagnostic morphological keys requires microscopic examination of adult male genital structures, a tedious procedure when screening large numbers, and one that requires substantial sample preparation and undamaged specimens (Pogue 2002). Unambiguous keys are frequently not available for females or immature stages, and substantial overlap in host range and attraction to pheromone blends limit the use of behavioral criteria (Meagher et al. 2008). Therefore, finding an alternative method to supplement morphometric analyses is of practical interest for the identification of Spodoptera complex.
DNA barcoding has been proposed as a molecular method for assigning individual specimens to known species (Hebert et al. 2003). The barcode involves DNA sequence analysis of a portion (typically between 600–900 bp) of the mitochondrial gene cytochrome c oxidase subunit I (COI).Most of the molecular work was concentrated on S. frugiperda (Levy et al. 2002; Meagher & Gallo-Meagher 2003; Nagoshi & Meagher 2003; Prowell et al. 2004; Martinelli et al. 2006), which is a Western Hemisphere species. Recently, population genetic structure of S. litura from 6 Korean and 5 Chinese localities using COI and internal transcribed spacer 2 (ITS2) were studied and results revealed absence of genetic variance between Korean and Chinese populations (Wan et al. 2011). Nagoshi et al. (2011) analyzed DNA sequences from a portion of the COI region from 5 Spodoptera spp. (S. frugiperda, S. eridania (Stoll), S. exigua, S. dolichos (Fabricius) and S. pulchella (Herrich-Schäffer)) native to Florida along with 2 potentially invasive species, S. littoralis (Boisduval) and S. litura to show feasibility of using DNA barcodes for identifying these species. The objective of this study was to assess the applicability of DNA barcoding to Spodoptera species from India. The results were assessed for the likelihood of barcode gaps sufficient to discriminate the native from the foreign populations and thereby justify the expansion of the barcode databases for these and other related species. The potential role of DNA barcoding in monitoring the species at all lifecycle stages has also been exemplified.
Materials and Methods
For the present study, the samples S. exigua and S. litura were collected from cotton field of Indian Agricultural Research Institute, New Delhi, India during Sep 2012. The stock cultures were maintained in transparent jars with fresh cotton leafs and bolls with enough aeration. Adults were examined for accurate species identity through dissecting the genitalia and using these, pure cultures were maintained from the freshly emerged adults for only 1 generation. Samples of eggs, first to fourth larval instar, pupa, adult male and female were drawn from the F1 of culture for DNA isolation.
PCR AMPLIFICATION AND SEQUENCING
The DNAeasy Blood and Tissue Kit (Quiagen GmbH, Germany) method was used to extract DNA from 1–3 legs of each adult, and from eggs (10 eggs/egg mass), larvae and pupae. The DNA the method provided by Fukova et al. (2008) was followed. The voucher specimens of these and of those used for mtCO1 analysis are deposited with the National Pusa Collection (NPC), Division of Entomology, Indian Agricultural Research Institute, New Delhi, India. The genomic DNA was visualized using 0.8% agarose gel and quantified by fluorometer using standard procedures. Depending upon the concentration, the DNA samples were diluted with molecular gradient water to get a working solution of 10–30 ng/µL. A portion of the total DNA was preserved in glycerol (10%) in -80 °C for future reference purposes. The mtCO1 region was amplified using LCO 1480 and HCO 1298 (Folmer et al. 1994). The optimized PCR conditions (per 25 µL) using Taq DNA polymerase (Fermentas Inc., USA) were 2.5 µL of 10 × PCR buffer with 2 µL of 25 mM MgCl2, 0.5 µL of 10 mM dNTPs, 0.5 µL each of forward and reverse primer, IU of Taq, 17 µL of UltraPure water (Invitrogen). Thermocycler conditions were as follows: initial denaturation for 5 min at 94 °C followed by 35 cycles of denaturing for 30 sec at 94 °C, annealing for 40 s at 54 °C and extension time of 40 s at 72 °C, with a final extension for 5 min at 72 °C. PCR products were visualized on agarose gel after electrophoresis. Single bands were purified using a QIAquick PCR purification kit (Quiagen GmbH, Germany). Purified PCR products were sequenced directly in both directions using an automated sequencer (ABI prism® 3730 XL DNA Analyzer; Applied Biosystems, USA) at Scigenomics Lab, Cochin, India. All sequences were aligned using BioEdit 4.0 program, using ClustalW 1.8 (Thompson et al. 1994). The sequences were used in BLAST search to confirm the sequence identity. The alignment was further analyzed employing MUSCLE in MEGA 5.0.
SEQUENCE DIVERSITY AND PHYLOGENETIC ANALYSIS
Overall 63 sequences of S. litura (34), S. exigua (24) and S. mauritia (5), were used in diversity analysis. The number of haplotypes (h) and nucleotide (π) diversities for the populations of each Spodoptera sp. were estimated using the software DnaSP 5.10.01 (Librado & Rozas 2009). Sequence divergences among S. litura and S. exigua individuals were calculated using the Kimura 2-Parameter distance model (Kimura 1980) and graphically displayed in Maximum Likelihood (ML) tree by the program MEGA 5.05 (Tamura et al. 2011). Tree robustness was evaluated by bootstrapping (Felsenstein 1985) with 2,000 replicates and S. mauritia, obtained from NCBI GenBank was used as the outgroup.
Mitochondrial cytochrome oxidase 1 sequencing yielded a 650 bp fragment from the egg, larva, pupa and adults of S. litura and S. exigua. A comparison of the triplicate sequence showed no evidence of mismatch which showed no sequencing errors. A total fragment of 650 bp of the COI was analyzed from all life stages. Evidence of nuclear copies was not found, which was supported by the absence of a stop codon within the sequence, and base composition was similar with no indels. The 8 sequences generated in the study were deposited in the NCBI GenBank (Table 1). Pairwise alignment of S .litura and S. exigua showed variation in 45 nucleotides out of 645 bp amounting to 7% (Fig. 1).
Blast search for the sequences showed the highest hits for the respective species. Multiple sequences of COI were aligned using Clustal W (BioEdit 4.0,). These results on COI sequences in addition to corroborating the ones already available in the NCBI GenBank, also provided confirmation that stage specific identification of S. litura and S. exigua is possible with the data generated in this study.
The 63 sequences of S. litura (34), S. exigua (24) and S. mauritia (5)used in diversity analysis led to the following: from 34 COI gene fragments of S. litura 7 haplotypes were identified, with a haplotype diversity (Hd) of 0.647 ± 0.054 and nucleotide diversity (π) of 0.00196 (Table 2). The haplotype frequency and nucleotide diversity within S. litura from different locations was very small. In S. exigua, among 24 COI sequences 10 haplotypes were recognized with 0.873 ± 0.044 haplotype diversity, 0.01286 nucleotide diversity and 28 total numbers of mutations indicating complex genetic variability. Spodoptera mauritia included 5 COI sequences, which gave 2 haplotypes with Hd value 0.400 ± 0.237 and nucleotide diversity of 0.00392.
The Maximum Likelihood tree (ML tree based on Kimura 3 parameter distance at 1,000 iterations) was constructed based on 63 sequences including 34 from S. litura, 24 from S. exigua and 5 from S. mauritia obtained from GenBank and BOLD, and from 4 sequences each of S. litura and of S. exigua from the present study using MEGA 5.0. Based on the ML tree, 3 major clades were recognized which differentiate the 3 Spodoptera spp. (Fig. 2). The S. litura sequences produced a cladogram that did not cluster with sequences from different countries, showing no clear differentiation among the populations. Further, the cladogram revealed that in S. litura clade there were 2 subclades, the first in which our sequences were grouped with populations from Taiwan, Japan, China, Australia; and in the second subclade, populations from India, Taiwan, Bangladesh, Thailand, Pakistan and United Kingdom were grouped. The second clade was S. mauritia, which included populations from Australia and Japan; and because we did not sequence S. mauritia, a population from India was not included. In the S. exigua clade, there were 2 subclades, both supported by a 100% bootstrap value. Subclade1 of S. exigua included individuals only from Australia. Subclade 2 included individuals collected from geographically distant locations, viz., India, Spain, USA, United Kingdom, Germany, Japan and Thailand.
Spodoptera spp. populations analyzed, their countries of origin, and GenBank and BOLD accession codes.
COI gene polymorphism in Spodoptera litura, S. exigua and S. mauritia. Diversity analysis was based on a total of 63 DNA sequences of these three species.
DNA barcoding makes possible the use of specimens from developmental stages where morphological keys for such species are not available or of poor quality. In addition, continued advances in molecular genetic technology will improve the efficiency and economics of barcode analysis, making the screening of even a large number of samples increasingly practical. These benefits combined with the observed applicability of barcode for species assignment in Spodoptera justify efforts to expand the barcoding database to become broader and more representative of relevant domestic and exotic species. The present study has confirmed that the COI barcode sequences from the immature stages are generally consistent with current adult morphological species concepts and are useful tools for species identification.
The ML tree of 3 Spodoptera species revealed that S. litura and S. mauritia are closer compared to S. litura and S. exigua. Further, the Australian population of S. exigua is entirely different from the populations used in the present study. Hence, a molecular study on the populations of these species from various hosts and geographical regions is urgently needed to elucidate the genetic relationships between them. DNA based identification in this group, especially of the immature stages, has the potential to provide a practical approach to pest control and interception activities that require timely and accurate identifications. Our study represents a needed starting point with reference to cutworms, and their molecular characterization towards a stable taxonomy for Spodoptera spp., and for solving intra and interspecific complexities.
Authors gratefully acknowledge the financial support received from the Indian Council of Agricultural Research (ICAR), New Delhi through the XIth Plan Network Project on Insect Biosystematics (NPIB). Our sincere thanks are due to Dr. Suresh Nebapure, Scientist, Division of Entomology, Indian Agricultural Research, New Delhi, India for providing the cultures of the Spodoptera spp.
- J Felsenstein. 1985. Confidence limits on phylogenies: An approach using the bootstrap. Evolution 39: 783–791. Google Scholar
- OM Folmer , M Black , BW Hoeh , R Lutz , R Vrijenhoek. 1994. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit 1 from diverse metazoan vertebrates. Molecular Marine Biology and Biotechnology 3: 294–299. Google Scholar
- I Fuková , LG Neven , NM Bárcenas , NA Gund , M Dalíková , F Marec. 2009. Rapid assessment of the sex of codling moth Cydia pomonella (Linnaeus) (Lepidoptera: Totricidae) eggs to larvae. Journal of Applied Entomology 133: 249–261. Google Scholar
- PDN Hebert , A Cywinska , SL Ball , JR Dewaard. 2003. Biological identifications through DNA barcodes. Philosophical Transactions of the Royal Society London B: Biological Science 270: 313–321. Google Scholar
- SJ Johnson. 1988. Migration and life history strategy of fall armyworm, Spodoptera frugiperda, in the Western Hemisphere. Insect Science and Its Application 8: 543–549. Google Scholar
- M Kimura. 1980. A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. Journal of Molecular Evolution 16: 111–120. Google Scholar
- EF Knipling. 1980. Regional management of the fall armyworm: a realistic approach? Florida Entomologist 63: 468–480. Google Scholar
- HC Levy , A Garcia-Muruniak , JE Muruniak. 2002. Strain identification of Spodoptera frugiperda (Lepidoptera: Noctuidae) insects and cell line: PCR-RFLP of cytochrome oxidase C subunit I gene. Florida Entomologist 85: 186–190. Google Scholar
- P Lirado , J Rozas. 2009. DnaSP V5: A software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25: 1451–1452. Google Scholar
- S Martinelli , RM Barata , MI Zuch , MC Silva-Filho , C Omoto. 2006. Molecular variability of Spodoptera frugiperda (Lepidoptera: Noctuidae) populations associated to maize and cotton crops in Brazil. Journal of Economic Entomology 99: 519–526. Google Scholar
- RL Meagher , J Brambila , E Hung. 2008. Monitoring for exotic Spodoptera Species (Lepidoptera: Noctuidae) in Florida. Florida Entomologist 91: 517–522. Google Scholar
- RL Meagher , M Gallo-Meagher. 2003. Identifying host strains of fall armyworm (Lepidoptera: Noctuidae) in Florida using mitochondrial markers. Florida Entomologist 86: 450–455. Google Scholar
- ER Mitchell. 1979. Migration by S. exigua and S. frugiperda, North American style (Lepidoptera: Noctuidae). Journal of the Australian Entomological Society 18: 363–372. Google Scholar
- RN Nagoshi , J Brambila , RL Meagher. 2011. Use of DNA barcodes to identify invasive armyworm Spodoptera species in Florida. Journal of Insect Science 11:154. Google Scholar
- RN Nagoshi , RL Meagher. 2003. FR tandem-repeat sequence in fall armyworm (Lepidoptera: Noctuidae) host strains. Annals of the Entomological Society of America 96: 329–335. Google Scholar
- MG Pogue. 2002. A world revision of the genus Spodoptera Guenée (Lepidoptera: Noctuidae). Memoirs of the American Entomological Society 43: 1–202. Google Scholar
- DP Prowell , M McMichael , JF Silvain. 2004. Multilocus genetic analysis of host use, introgression, and speciation in host strains of fall armyworm (Lepidoptera: Noctuidae). Annals of the Entomological Society of America 97: 1034–1044. Google Scholar
- AN Sparks. 1979. A review of the biology of the fall armyworm. Florida Entomologist 62: 82–87. Google Scholar
- K Tamura , D Peterson , N Peterson , G Stecher , M Nei , S Kumar. 2011. MEGA5: Molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Molecular Biology and Evolution 28: 2731–2739. Google Scholar
- MJ Thomas , A Jacob , MRGK Nair. 1969. Host-biology relations of Spodoptera litura (F.) (Lepidoptera: Noctuidae). Indian Journal of Agricultural Science 39: 400–402. Google Scholar
- JD Thompson , DG Higgins , TI Gibson. 1994. CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Research 22: 4673–4680. Google Scholar
- X Wan , J Li , MJ Kim , HC Park , SS Kim , I Kim. 2011. DNA Sequence variation of the tobacco cutworm, Spodoptera litura (Lepidoptera: Noctuidae), determined by mitochondrial A+ T-rich region and nuclear ITS2 sequences. Biochemical Genetics 49: 760–787. Google Scholar
 Supplementary material for this article in Florida Entomologist 98(1) (March 2015) is online at http://purl.fcla.edu/fcla/entomologist/browse