Next Article in Journal
Diel Rhythmicity of Field Responses to Synthetic Pheromone Lures in the Pine Sawyer Monochamus saltuarius
Previous Article in Journal
The Impact of Climate Change on Agricultural Insect Pests
Previous Article in Special Issue
Border Habitat Effects on Captures of Halyomorpha halys (Hemiptera: Pentatomidae) in Pheromone Traps and Fruit Injury at Harvest in Apple and Peach Orchards in the Mid-Atlantic, USA
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Genetic Relationship of Fall Armyworm (Spodoptera frugiperda) Populations That Invaded Africa and Asia

1
Department of Applied Biosciences, College of Agriculture and Life Sciences, Kyungpook National University, Daegu 41566, Korea
2
Department of Zoology, Faculty of Life Sciences, University of Ilorin, Ilorin 240212, Nigeria
3
Department of Plants Protection, Ministry of Agriculture, Kinshasa 8722, Democratic Republic of the Congo
4
Ministry of Agriculture Animal Industry and Fisheries, Entebbe P.O. Box 102, Uganda
5
National Biological Control, Kibaha 30031, Tanzania
6
Department of Applied Sciences, Mutare Polytechnic College, Mutare P.O. Box 640, Zimbabwe
7
Center for Industrial Entomology, Hariharbhawan, Lalitpur 44700, Nepal
8
Department of Entomology, Patuakhali Science and Technology University, Dumki, Patuakhali 8602, Bangladesh
9
Plant Protection Research Institute, Ha Noi 04, Vietnam
10
Jejudo Agricultural Research and Extension Services, Jejudo 63556, Korea
11
College of Agriculture and Life Sciences, Chonnam National University, Gwangju 61186, Korea
12
Xenotype, Daejeon 34912, Korea
13
Plant Quarantine Technology Center, Animal and Plant Quarantine Agency, Gimcheon 39660, Korea
14
Institute of Plant Medicine, Kyungpook National University, Daegu 41566, Korea
*
Author to whom correspondence should be addressed.
Insects 2021, 12(5), 439; https://doi.org/10.3390/insects12050439
Submission received: 14 March 2021 / Revised: 25 April 2021 / Accepted: 11 May 2021 / Published: 12 May 2021
(This article belongs to the Special Issue Improving Invasive Insect Species Management)

Abstract

:

Simple Summary

Since 2016, the fall armyworm, an important economic pest native to tropical and subtropical regions of the Western Hemisphere, has invaded Africa and further spread rapidly into most Asian countries. The fall armyworm is highly polyphagous, but two of its major strains, the corn and the rice strains, cause severe damage in the Western Hemisphere. However, the invaded populations in Africa and Asia mostly infested the corn fields. Studies on the genetic identity of the species using two molecular markers, one nuclear gene and one mitochondrial gene, showed that the major genetic group is a heterogeneous hybrid of males from the corn strain and females from the rice strain. Moreover, a minor group of homogenous individuals from the corn strain but no homogenous individuals from the rice strain were also detected. A geographic distribution analysis at the subpopulation level indicated similar genetic diversity in Africa and Asia, suggesting fall armyworm in Africa spread into Asia without significant genetic change.

Abstract

The fall armyworm, Spodoptera frugiperda, is an important agricultural pest native to tropical and subtropical regions of the Western Hemisphere, and has invaded Africa and further spread into most countries of Asia within two years. Here, we analyzed the genetic variation of invaded populations by comparing the nucleotide sequences of two genes: the nuclear Z-chromosome linked gene triose phosphate isomerase (Tpi) and the mitochondrial gene cytochrome oxidase subunit I (COI) of 27 specimens collected in Africa (DR Congo, Tanzania, Uganda, and Zimbabwe) and Asia (Bangladesh, Korea, Nepal, and Vietnam). The results revealed that 25 specimens were from a heterogeneous hybrid (Tpi-corn strain and COI-rice strain; Tpi-C/COI-R) of the corn strain male and rice strain female, but two specimens were from a homogenous corn strain (Tpi-corn strain and COI-corn strain; Tpi-C/COI-C). The further analysis of the fourth exon and the fourth intron sequences of the Tpi gene identified at least four subgroups of the corn strain. These four genetic subgroups were identified in Africa and Asia, suggesting no significant genetic change due to the rapid migration within two years. Our study provides essential information for understanding the genetic diversity of fall armyworm in new habitats.

1. Introduction

The fall armyworm (FAW) Spodoptera frugiperda (J. E. Smith, 1797) (Lepidoptera: Noctuidae) is an important agricultural pest native in tropical and subtropical regions of the Western Hemisphere [1]. Due to the lack of diapause mechanism, FAW cannot overwinter in the northern areas over Florida and Texas of the United States, but they can disperse across thousands of kilometers into the north in the growing season [2]. In 2016, its invasion into Western Africa was first reported and it rapidly spread into most Sub-Saharan Africa countries [3,4,5,6]. In 2018–2019, the invasion into India was firstly reported and further spread into most Asia-Pacific countries, including Korea, Japan, and Australia, within an year [7,8,9,10,11,12,13,14]. The enormous migratory power of the FAW is a severe threat to new habitats in Africa and Asia and poses as a significant concern related to the potential economic damage of crop plants [15,16,17].
The FAW is a polyphagous species, consuming at least 353 species of plants, and it is a significant pest of corn, rice, and forage grasses [18,19]. Pashley et al. [20] showed at least two host plant strains in the southeastern United States: one of them feeding on corn, cotton, and sorghum (corn strain, C-strain) and the other feeding on rice and various pasture grasses, preferentially (rice strain; R-strain) [18,21,22]. The two FAW strains are morphologically indistinguishable and are distributed in sympatric patterns [23]. Further studies identified their different genetic characteristics in mating behaviors and zygotic reproductive incompatibility [24,25], pheromone composition [26], and differential susceptibility in xenobiotics [27].
Molecular markers can be used to diagnose the genetic identity of each strain of FAW [28,29]. Polymorphic variation of mitochondrial cytochrome oxidase subunit I (COI) gene sequence was identified between C- and R- strains but was not always consistent with host plant preference [30,31]. For example, some populations collected from the cornfields possess an R-strain marker in the COI gene. The group of Nagoshi and collaborators developed another genetic marker using a nuclear triosephosphate isomerase (Tpi) gene linked with Z-chromosome [32,33]. Therefore, the Tpi gene is hemizygous in females (ZW), whereas in males it is either homozygous or heterozygous (ZZ) [32]. Two genotypes, Tpi-C and Tpi-R, were identified on different host plants in the Western Hemisphere [31,32]. The group of Nagoshi and collaborators found that significant corn field populations are a hybrid (Tpi-C/COI-R) that possesses a nuclear Tpi-C marker but a mitochondrial COI-R marker. This finding indicates that the host plant preference of the hybrid is associated with the nuclear Tpi marker rather than the mitochondrial COI marker [34]. Therefore, it suggests that the Tpi gene is a suitable molecular marker compared with the COI gene to identify the FAW genetic characteristics associated with the host plant preference of the species.
Here, we assessed the genetic variation of FAW specimens collected from eight African and Asian countries based on a Tpi gene and compared with their variation of COI gene markers. Moreover, we discussed the relationship between genetic diversity and the potential population dynamic of FAW populations that invaded the new African and Asian habitats.

2. Materials and Methods

2.1. Collection

The FAW larvae were collected from corn fields (Zea mays L.) in Gyeongsan, Gyeongbuk Province, and adult moths were caught using the sex pheromone traps (GreenAgrotech, Gyeongsan, Korea) in Jeju Island of Korea from 2019 to 2020. Other specimens were obtained as larvae and adults from corn plants at various locations in Africa (DR Congo, Tanzania, Uganda, and Zimbabwe) and Asia (Bangladesh, Korea, Nepal, and Vietnam) from October 2017 to August 2020 (Figure 1; Table 1). In the field, FAW was identified based on the morphological characteristics of larva and adults. Specimens were stored 70% ethanol. Then, the vials were stored at −20 °C until further analysis.

2.2. DNA Preparation

Genomic DNA was extracted from a portion of each specimen and homogenized using the pure link genomic DNA mini kit (Invitrogen, Carlsbad, CA, USA). The specimens were placed in a 1.5 mL centrifuge tube containing 180 µL of digestion buffer and 20 µL of proteinase K (50 µg/mL) and then incubated at 55 °C for 4 h. The DNA samples were extracted and purified using genomic spin columns, as described in the kit. DNA concentration was determined using a NanoPhotometer™ (Implen GmbH, Schatzbogen, Germany).

2.3. Polymerase Chain Reaction (PCR) Amplification

PCR was performed in a total reaction volume of 30 µL, containing 15 µL SolgTM 2 × Taq PreMix (Solgent, Daejeon, Korea), 2 µL of each primer (10 pmol/µL), 3 μL of the DNA solution, and 8 μL distilled water. A partial sequence (444 bp) of the Tpi gene was amplified using the primer pair TPI412F (5′-CCGGACTGAAGGTTATCGCTTG-3′) and TPI1140R (5′-GCGGAAGCATTCGCTGACAACC-3′) [15], whereas the partial sequence (658 bp) of the COI gene was amplified using the primer pair LCO1490 (5′-GGTCAACAAATCATAAAGATATTGG-3′) and HCO2198 (5′-TAAACTTCAGGGTGACCAAAAAATCA-3′) [35]. The reaction mixtures were amplified under the following conditions: Tpi gene (initial denaturation at 94 °C for 1 min; followed by 33 cycles of 92 °C for 30 s, 56 °C for 45 s, and 72 °C for 45 s; and a final segment of 72 °C for 3 min], and mtCOI (initial denaturation at 92 °C for 5 min; followed by 35 cycles 92 °C for 60 s, 55 °C for 60 s, and 72 °C for 60 s; and a final extension at 72 °C for 5 min in SimpliAmp 96-Well Thermal Cycler [Applied Biosystems, Foster City, CA, USA]). The PCR products were separated using a 1% agarose gel electrophoresis, stained with ethidium bromide solution, and visualized under ultraviolet (UV) light. The amplified PCR products were excised from the gel and purified using the Wizard® PCR Preps DNA Purification System (Wizard® SV Gel, Promega Co., Madison, WI, USA).

2.4. DNA Sequence Analysis

The purified DNA was sequenced using the BigDye® Terminator Cycle Sequencing Kit and ABI Prism 3730XL DNA Analyzer (50 cm capillary) (DNA Sequencer) (Applied Biosystems, Foster City, CA, USA) at the Solgent Sequencing Facility (Solgent Co., Daejeon, Korea). The GenBank database in the National Center for Biotechnology Information (NCBI) was searched using the BLAST algorithm [36], and the nucleotide sequences were aligned using CLUSTAL W [37].

2.5. Phylogenetic Analysis

A phylogenetic tree for the COI gene was constructed using the maximum likelihood method implemented in MEGA 6.0 software [38] with reference sequences obtained in the GenBank. We used 1000 bootstrap replicates to test the robustness of each of the phylogeny with the Hasegawa–Kishnio–Yano (HKY850) model and gamma distribution rate of variation among sites [39].

2.6. Characterization of the Tpi and COI Gene Segments

Single nucleotide substitutions of Tpi and COI genes were used for strain diagnostic markers. The Tpi gene was designated by a “g” (genomic), whereas the COI gene was designated by an “m” (mitochondria followed by gene name, base pairs number from the predicted translational start site). In both Tpi and COI genes, we aligned our FAW specimen sequences with the previously identified NCBI sequences of C-strain and R-strain FAW in CLUSTAL W to find polymorphic nucleotides to identify both the C and R strains. Nagoshi et al. [15] reported various polymorphic nucleotides in the exon (Tpi-E4) and intron region (Tpi-I4) of the Tpi gene to identify the C- and R-strains. The gTpi183 (C for C-strain, T for R-strain) is used to identify C- and R-strains [15]. Both gTpi192 and gTpi198 were used to identify subgroups (Tpi-Ca1, Tpi-Ca2, and Tpi-Ca1/Ca2) of C-strain. In addition, various polymorphic nucleotides in Tpi-I4 were used to identify genetic variation of FAW.

2.7. Genetic Analyses

Genetic parameters, such as the number of segregating sites, haplotype numbers, haplotype diversity, nucleotide diversity, theta/site, and Tajima’s D [40], were analyzed using the DnaSP software v.5.10 [41,42]. The TCS software v.1.21 was used to generate the haplotype network [43]. We excluded the Kor-1 specimen, the hybrid of Tpi-Ca1/Ca2, from all genetic analyses with the Tpi gene.

3. Results

3.1. Analysis of the Tpi Gene Sequence

The partial nucleotide sequence (444 bp), including 166 bp of the fourth exon (Tpi-E4) and 278 bp of the fourth intron (Tpi-I4) region of the Tpi gene, was determined from the 27 specimens of the FAW specimens collected from eight different African and Asian countries. Single nucleotide polymorphism (SNP) characteristics of the Tpi gene were analyzed separately in Tpi-E4 and Tpi-I4 regions (Figure 2).
In the Tpi-E4 region, the gTpi183 of all 27 specimens was C, but not T, which indicated that all of them were the corn strain. Furthermore, nucleotides of both the gTpi192 and the gTpi198 consisted of three different types, such as C and C, T and T, and Y (C/T) and Y (C/T), which indicates the three subgroups of corn strain, Tpi-Ca1, Tpi-Ca2, and Tpi-Ca1/Ca2, respectively (Figure 2). The heterozygote Tpi-Ca1/Ca2 specimen (Kor-1) was identified only from Jeju, Korea, in 2019.
In the Tpi-I4 region, among 17 polymorphic nucleotides, we found three different polymorphic sequences of Tpi-C in our samples but did not identified Tpi-R sequences reported by Nagoshi et al. [15]. Ten polymorphic nucleotides (31, 38, 53, 55, 58, 70, 77, 87, 96, and 148) were identified between Tpi-Ca1 and Tpi-Ca2 subgroups. Among them, the nucleotide 148 was distinct polymorphic nucleotide between Tpi-Ca2a and Tpi-Ca2b. In addition, nucleotide variation within subgroup was identified in some specimens of Tpi-Ca1 and Tpi-Ca2b but was not detected in Tpi-Ca2a. For example, in Tpi-Ca1 subgroup, Kor-1 and Tan-1 specimens were substituted the nucleotides 70 and 96 into “C” but Con-11 specimen was substituted only the nucleotide 96 into “C”. In Tpi-Ca2b, three types of variation in the nucleotides 87 and 96 were identified, for example, T and T, T and C, and C and T, respectively. Moreover, in the Tpi-Ca1/Ca2 heterozygote specimen, all ten polymorphic nucleotides were heterozygous into S (C/G), M (C/A), W (A/T), and Y (C/T). Therefore, our 27 specimens were classified into four subgroups as Tpi-Ca1a, Tpi-Ca2a, Tpi-Ca2b, and Tpi-Ca1/Tpi-Ca2.
The SNP pattern of the Tpi gene was analyzed according to geographic distribution (Figure 2). The results showed that each subgroup was distributed in both Africa and Asia. For example, the Tpi-Ca1a subgroup was identified in DR Congo (Con-11, 42), Tanzania (Tan-1, 3), Uganda (Uga-1, 4), and Zimbabwe (Zim-1, 2) in Africa as well as in Nepal (Nep-1, 2, 3), Vietnam (Vie-1, 3), and Korea (Kor-2, 4) in Asia. Tpi-Ca2a was identified in DR Congo (Con-21, 31) and Uganda (Uga-3) in Africa, as well as Vietnam (Vie-2) and Korea (Kor-3) in Asia, whereas Tpi-Ca2b was identified from DR Congo (Con-12, 41), Tanzania (Tan-2, 4) and Uganda (Uga-2) in Africa, as well as Bangladesh (Ban-1) in Asia. The Tpi-Ca1/Tpi-Ca2 was identified only in Korea (Kor-1). The results showed that each subgroup was widely distributed in both continents in a mixed pattern.

3.2. Analysis of the COI Gene Sequence

The partial sequence (658 bp) of the COI gene was determined and phylogenetic relationship was compared with those of previously known sequences from the GenBank database using the maximum likelihood phylogenetic tree (Figure 3). The result showed that 92.6% (25/27) were clustered to the COI-rice strain, whereas only 7.4% (Tan-3, Vie-3; 2/27) specimens were clustered to the COI-corn strain of FAW. All the specimens were collected from the cornfields. All the COI-rice strain sequences (25 specimens) were 100% identical but 98.33–98.48% similar with two sequences of the COI-corn strain (two specimens). Two COI-corn strain specimens were 99.85% identical (Table A1 and Table A3 in Appendix A).
The SNP analysis from the COI gene fragment alignment showed that ten nucleotides (mCOI72, mCOI117, mCOI171, mCOI207, mCOI258, mCOI564, mCOI570, mCOI600, mCOI634, and mCOI663) were different between the corn and the rice strains. Based on this comparison, the specimens Tan-3 and Vie-3 belong to the C-strain, and the remaining specimens belong to the R-strain (Figure 4).

3.3. Genetic Diversity of Tpi and COI Genes of FAW

The nucleotide sequence variation of the Tpi gene was slightly higher in the African specimens (0.23–3.15%) than the Asian specimens (0.23–2.93%), and its variation between Africa and Asia was 0.23–3.38% (Table A2). The numbers of segregating sites, haplotype numbers, haplotype diversity, and nucleotide diversity were higher in Africa than in Asia (Table 2). The nucleotide sequence variation of the COI gene was higher in the Asian specimens (1.67%) than in the African ones (1.52%), and its variation between Africa and Asia was 0.15–1.67% (Table A3). The numbers of segregating sites, haplotype diversity, and nucleotide diversity were almost similar between African and Asian specimens (Table 2).
The population genetic study of FAW in Africa and Asia was assessed by Tajima’s neutrality test for the Tpi and the COI genes (Table 2). The results showed that Tajima’s D was positive and non-significant for the Tpi gene in both regions, whereas Tajima’s D is negative but significant for the COI gene in both Africa and Asia regions suggesting the recent population expansion.
The evolutionary relationship of both Tpi and COI gene haplotypes from FAW was assessed using the minimum spanning network. In the Tpi gene, 12 haplotypes were identified and separated into two distinct groups, Tpi-Ca1 and Tpi-Ca2, by nine mutational steps (Figure 5A). The Tpi-Ca1 consisted of six haplotypes. Among Tpi-Ca2, two haplotypes (h4 and h7) belong to the subgroup Tpi-Ca2a, whereas four haplotypes (h1, h3, h8, and h11) belong to the subgroup Tpi-Ca2b (Table 3). Some identical haplotypes were identified in both Africa and Asia. For example, the h5, which is the most frequent haplotype, was found in two African (Con-42 and Zim-1) and six Asian specimens (Kor-4, Nep-1, Nep-2, Nep-3, Vie-1, and Vie-3). The h6 haplotype was found in one African (Tan-1) and one Asian specimen (Kor-1). The h4 haplotype was found in three African (Con-21, Con-31, and Uga-3) and one Asian specimen (Vie-2).
Only three haplotypes were identified in the COI gene, and h1 was differed by ten mutational steps with h2 and h3 (Figure 5B). The h1 haplotype contained 25 specimens from Africa and Asia and belonged to COI-R, whereas h2 and h3 haplotypes had a single specimen, Vie-3, and Tan-3, respectively. Both of these haplotypes belonged to the COI-C (Table 4). The haplotype analysis of both Tpi and COI genes indicated that FAW populations invaded in Africa and Asia are genetically diverse at a similar rate.

4. Discussion

In this study, FAW collected from cornfields of eight African and Asian countries were genetically characterized using molecular markers of both the Tpi and the COI genes. Our Tpi gene analysis showed that all the specimens had the Tpi-C genotype, whereas the COI gene analysis showed that 92.6% had the COI-R and 7.4% had the COI-C genotypes. Therefore, the hybrid (Tpi-C/COI-R) was predominant, but the homogenous corn strain (Tpi-C/COI-C) was a minor genetic group in our survey. This result is similar to previous studies wherein the Tpi gene is a predictable molecular marker compared with the COI gene for the diagnosis of the FAW strain associated with host plant preference [15,16,17,44]. Another study in Myanmar and Southern China indicated that most of the strain is hybrid (Tpi-C/COI-R) [45]. It is worth investigating the nuclear Tpi gene, a more reliable host strain marker compared with the mitochondrial COI marker in invaded populations in Africa and Asia, to prevent further uncertainty on host plant preference analysis.
The genetic variation of both the Tpi and the COI genes showed that Tpi is more diverse compared with COI. Moreover, those values were higher for the African specimens than for the Asian specimens. Our data indicated the African populations of FAW are more diversified compared with the Asian ones, especially in the nuclear Tpi gene. Nagoshi et al. [6] compared the frequency of both the Tpi and the COI haplotype combination in the Western Hemisphere and Africa. The homogeneous corn strain (Tpi-C/COI-C) is predominant in the Western Hemisphere and Western Africa. Both Tpi-C/COI-C and a hybrid strain (Tpi-C/COI-R) are similarly distributed in Central Africa, but a hybrid strain predominates in Eastern Africa. Further studies indicated that the hybrid strain predominates in South Africa and India [15,44]. The rice strain (Tpi-R/COI-R) is found in the Western Hemisphere, but it is rare in Africa [34]. Our data is consistent with previous studies, suggesting that the hybrid strain is predominantly distributed in Africa and Asia while spreading into the east of continents.
Polymorphism of the fourth exon and intron region of the Tpi gene is useful for the subgroup identification of FAW [15,44]. Our analysis showed four subgroups of corn strain, such as Tpi-Ca1a, Tpi-Ca2a, Tpi-Ca2b, and Tpi-Ca1/Tpi-Ca2. Similar profiles are shown in Africa and India, which showed that Tpi-Ca1a is the major group, and other subgroups, such as Tpi-Ca2a and Tpi-Ca2b, are a minor group [15,44]. We found a hybrid (Tpi-Ca1/Tpi-Ca2) of two subgroups only in one region, Jeju, which is an island located in the southern region of Korea. However, this hybrid was already identified in India at a high frequency [44]. This finding indicates the great potential of further invasion of hybrid strain from India into other Asian countries.
The FAW is a highly polyphagous species that feeds on at least 353 species of plants worldwide [19]. However, the FAW that invaded Africa and Asia mostly prefer corns but not rice and other host plants in the fields, although their major genotype is a hybrid, possessing the nuclear corn strain Tpi gene and mitochondrial rice strain COI gene [6]. The genetic characteristic of their corn preference is highly associated with the genetic marker of the Tpi gene compared with the COI gene. Besides, this host plant preference phenotype is not discriminated in the subgroup level, Tpi-Ca1, and Tpi-Ca2. There are no studies on the relationship between Tpi genotype and phenotypic host plant preference. The Tpi gene product acts as an essential metabolic enzyme in glycolysis, which catalyzes the reversible reaction of the triose phosphate isomers, dihydroxyacetone phosphate, and D-glyceraldehyde 3-phosphate in the cytosol [46]. The Tpi C-strain of FAW may have adaptative mechanisms on the feeding, digestion, and metabolic efficiency of corn plants. It is interesting to study the relationship between the genetic mutation of the Tpi gene and metabolic adaptation related to host plant preference.

5. Conclusions

In conclusion, the genetic characterization of the Tpi and the COI genes of African and Asian specimens showed that the Tpi gene is a more suitable molecular marker of host plant preference phenotype compared with the COI gene. From 2016 to 2020, at least four genetic subgroups of the Tpi-corn strain were geographically distributed in Africa and Asia in a similar profile, indicating the limited genetic variation of invaded FAW populations. However, we do not exclude that invaded FAW populations have a great potential to develop genetic adaptations to new environments.

Author Contributions

Conceptualization, R.A., A.A.A., I.K., M.N., S.-J.L., S.-M.K., and K.-Y.L.; methodology, R.A., A.A.A., M.J.M., P.K., K.B.N., M.K.M., Y.K.S., J.S.M.H., T.X.H., H.T.D., J.-H.P., H.-S.H., and K.-Y.L.; formal analysis, R.A.; investigation, Y.K.S., and K.-Y.L.; resources, M.J.M., P.K., K.B.N., M.K.M., Y.K.S., J.S.M.H., T.X.H., H.T.D., J.-H.P., H.-S.H., and K.-Y.L.; writing—original draft preparation, R.A.; writing—review and editing, R.A., I.K., M.N., S.-J.L., S.-M.K., and K.-Y.L.; supervision, K.-Y.L.; project administration, I.K., M.N., S.-J.L., S.-M.K., and K.-Y.L.; funding acquisition, K.-Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Research Program for Exportation Support of Agricultural Products, Animal, and Plant Quarantine Agency, in the Republic of Korea (Grant #Z-1543086-2017-21-01).

Data Availability Statement

The genetic data presented in this study are publicly available on GenBank, and the accession numbers are reported in Table 1.

Acknowledgments

The authors would like to thank Enago (www.enago.co.kr, accessed on 14 March 2021) for the English language review.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. Accession numbers of Tpi and COI gene sequences of Spodoptera frugiperda from different countries of Africa and Asia their identity searched in the GenBank database.
Table A1. Accession numbers of Tpi and COI gene sequences of Spodoptera frugiperda from different countries of Africa and Asia their identity searched in the GenBank database.
SpecimensHighest Sequence Identity with GenBank Database
Tpi COI
% IdentityAccession
Numbers
Countries% IdentityAccession
Numbers
Countries
Con-1199.77KT336237USA100MT605970India
Con-1299.54KT336239USA100MT605970India
Con-21100KT336239USA100MT605970India
Con-31100KT336239USA100MT605970India
Con-4199.54KT336239USA100MT605970India
Con-42100KT336236USA100MT605970India
Tan-199.54KT336236USA100MT605970India
Tan-299.86KT336239USA100MT605970India
Tan-3100KT336237USA99.85MN541574India
Tan-499.54KT336239USA100MT605970India
Uga-199.77KT336236USA100MT605970India
Uga-299.54KT336229USA100MT605970India
Uga-3100KT336239USA100MT605970India
Uga-499.77KT336237USA100MT605970India
Zim-1100KT336236USA100MT605970India
Zim-2100KT336237USA100MT605970India
Ban-1100KT336229USA100MT605970India
Kor-197.3FO681385France100MT605970India
Kor-299.54KT336236USA100MT605970India
Kor-399.77KT336239USA100MT605970India
Kor-4100KT336236USA100MT605970India
Nep-1100KT336236USA100MT605970India
Nep-2100KT336236USA100MT605970India
Nep-3100KT336236USA100MT605970India
Vie-1100KT336236USA100MT605970India
Vie-2100KT336239USA100MT605970India
Vie-3100KT336236USA100MN541574India
Table A2. Percentage identity matrix of Spodoptera frugiperda Tpi gene analysis from different African and Asian countries.
Table A2. Percentage identity matrix of Spodoptera frugiperda Tpi gene analysis from different African and Asian countries.
SNSpecimens1234567891011121314151617181920212223242526
1Ban-1
2Kor-197.07
3Kor-297.3097.07
4Kor-399.1097.3097.30
5Kor-497.3097.0799.5597.30
6Nep-197.3097.0799.5597.30100.00
7Nep-297.3097.0799.5597.30100.00100.00
8Nep-397.3097.0799.5597.30100.00100.00100.00
9Vie-197.3097.0799.5597.30100.00100.00100.00100.00
10Vie-299.3297.3097.5299.7797.0797.0797.0797.0797.07
11Vie-397.3097.0799.5597.30100.00100.00100.00100.00100.0097.07
12Con-1197.3097.3099.5597.7599.5599.5599.5599.5599.5597.5299.55
13Con-1299.3297.0797.5299.3297.0797.0797.0797.0797.0799.5597.0797.52
14Con-2199.3297.3097.5299.7797.0797.0797.0797.0797.07100.0097.0797.5299.55
15Con-3199.3297.3097.5299.7797.0797.0797.0797.0797.07100.0097.0797.5299.55100.00
16Con-4199.3297.0797.5299.3297.0797.0797.0797.0797.0799.5597.0797.52100.0099.5599.55
17Con-4297.3097.0799.5597.30100.00100.00100.00100.00100.0097.07100.0099.5597.0797.0797.0797.07
18Tan-197.3097.07100.0097.3099.5599.5599.5599.5599.5597.5299.5599.5597.5297.5297.5297.5299.55
19Tan-299.5596.6296.8598.6596.8596.8596.8596.8596.8598.8796.8596.8598.8798.8798.8798.8796.8596.85
20Tan-397.5297.3099.3297.5299.7799.7799.7799.7799.7797.3099.7799.7797.3097.3097.3097.3099.7799.3297.07
21Tan-499.3297.0797.5299.3297.0797.0797.0797.0797.0799.5597.0797.52100.0099.5599.55100.0097.0797.5298.8797.30
22Uga-197.0796.8599.3297.0799.7799.7799.7799.7799.7796.8599.7799.3296.8596.8596.8596.8599.7799.3296.6299.5596.85
23Uga-299.5597.3097.7599.1097.7597.7597.7597.7597.7599.3297.7597.7599.3299.3299.3299.3297.7597.7599.1097.9799.3297.52
24Uga-399.3297.3097.5299.7797.0797.0797.0797.0797.07100.0097.0797.5299.55100.00100.0099.5597.0797.5298.8797.3099.5596.8599.32
25Uga-497.3097.0799.1097.3099.5599.5599.5599.5599.5597.0799.5599.5597.0797.0797.0797.0799.5599.1096.8599.7797.0799.7797.7597.07
26Zim-197.3097.0799.5597.30100.00100.00100.00100.00100.0097.07100.0099.5597.0797.0797.0797.07100.0099.5596.8599.7797.0799.7797.7597.0799.55
27Zim-297.5297.3099.3297.5299.7799.7799.7799.7799.7797.3099.7799.7797.3097.3097.3097.3099.7799.3297.07100.0097.3099.5597.9797.3099.7799.77
Table A3. Percentage identity matrix of Spodoptera frugiperda COI gene analysis from different African and Asian countries.
Table A3. Percentage identity matrix of Spodoptera frugiperda COI gene analysis from different African and Asian countries.
SNSpecimens1234567891011121314151617181920212223242526
1Ban-1
2Kor-1100
3Kor-2100100
4Kor-3100100100
5Kor-4100100100100
6Nep-1100100100100100
7Nep-2100100100100100100
8Nep-3100100100100100100100
9Vie-1100100100100100100100100
10Vie-2100100100100100100100100100
11Vie-398.3398.3398.3398.3398.3398.3398.3398.3398.3398.33
12Con-1110010010010010010010010010010098.33
13Con-1210010010010010010010010010010098.33100
14Con-2110010010010010010010010010010098.33100100
15Con-3110010010010010010010010010010098.33100100100
16Con-4110010010010010010010010010010098.33100100100100
17Con-4210010010010010010010010010010098.33100100100100100
18Tan-110010010010010010010010010010098.33100100100100100100
19Tan-210010010010010010010010010010098.33100100100100100100100
20Tan-398.4898.4898.4898.4898.4898.4898.4898.4898.4898.4899.8598.4898.4898.4898.4898.4898.4898.4898.48
21Tan-410010010010010010010010010010098.3310010010010010010010010098.48
22Uga-110010010010010010010010010010098.3310010010010010010010010098.48100
23Uga-210010010010010010010010010010098.3310010010010010010010010098.48100100
24Uga-310010010010010010010010010010098.3310010010010010010010010098.48100100100
25Uga-410010010010010010010010010010098.3310010010010010010010010098.48100100100100
26Zim-110010010010010010010010010010098.3310010010010010010010010098.48100100100100100
27Zim-210010010010010010010010010010098.3310010010010010010010010098.48100100100100100100

References

  1. Sparks, A.N. A review of the biology of the fall armyworm. Fla. Entomol. 1979, 62, 82–87. [Google Scholar] [CrossRef]
  2. Luginbill, P. The fall armyworm. Us Dept. Agric. Tech. Bull. 1928, 34, 1–91. [Google Scholar]
  3. Goergen, G.; Kumar, P.L.; Sankung, S.B.; Togola, A.; Tamò, M. First report of outbreaks of the fall armyworm Spodoptera frugiperda (J E Smith) (Lepidoptera, Noctuidae), a new alien invasive pest in West and Central Africa. PLoS ONE 2016, 11, e0165632. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Cock, M.J.W.; Beseh, P.K.; Buddie, A.G.; Cafá, G.; Crozier, J. Molecular methods to detect Spodoptera frugiperda in Ghana, and implications for monitoring the spread of invasive species in developing countries. Sci. Rep. 2017, 7, 4103. [Google Scholar] [CrossRef]
  5. Jacobs, A.; Van Vuuren, A.; Rong, I.H. Characterisation of the fall armyworm (Spodoptera frugiperda J.E. Smith) (Lepidoptera: Noctuidae) from South Africa. Afr. Entomol. 2018, 26, 45–49. [Google Scholar] [CrossRef]
  6. Nagoshi, R.N.; Goergen, G.; Tounou, K.A.; Agboka, K.; Koffi, D.; Meagher, R.L. Analysis of strain distribution, migratory potential, and invasion history of fall armyworm populations in northern Sub-Saharan Africa. Sci. Rep. 2018, 8, 3710. [Google Scholar] [CrossRef] [Green Version]
  7. Ganiger, P.C.; Yeshwanth, H.M.; Muralimohan, K.; Vinay, N.; Kumar, A.R.V.; Chandrashekara, K. Occurrence of the new invasive pest, fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), in the maize fields of Karnataka, India. Curr. Sci. 2018, 115, 621–623. [Google Scholar] [CrossRef]
  8. Sharanabasappa; Chandrashekara, K.; Kalleshwaraswamy, C.M.; Asokan, R.; Maruthi, M.S.; Pavithra, H.B.; Hegbe, K.; Navi, S.; Prabhu, S.T.; Goergen, G.E. First report of the fall armyworm, Spodoptera frugiperda (JE Smith) (Lepidoptera: Noctuidae), an alien invasive pest on maize in India. Pest Manag. Hortic. Ecosyst. 2018, 24, 23–29. [Google Scholar]
  9. Shylesha, A.N.; Jalali, S.K.; Gupta, A.; Varshney, R.; Venkatesan, T.; Shetty, P.; Ojha, R.; Ganiger, P.C.; Navik, O.; Subaharan, K.; et al. Studies on new invasive pest Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae) and its natural enemies. J. Biol. Control 2018, 32, 145–151. [Google Scholar] [CrossRef] [Green Version]
  10. Swamy, H.M.M.; Asokan, R.; Kalleshwaraswamy, C.M.; Sharanabasappa; Prasad, Y.G.; Maruthi, M.S.; Shashank, P.R.; Devi, N.I.; Surakasula, A.; Adarsha, S.; et al. Prevalence of “R” strain and molecular diversity of fall army worm Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) in India. Indian J. Entomol. 2018, 80, 544–553. [Google Scholar] [CrossRef]
  11. Lee, G.; Seo, B.Y.; Lee, J.; Kim, H.; Song, J.H.; Lee, W. First report of the fall armyworm, Spodoptera frugiperda (Smith, 1797) (Lepidoptera: Noctuidae), a new migratory pest in Korea. Korean J. Appl. Entomol. 2020, 59, 73–78. [Google Scholar] [CrossRef]
  12. Vennila, S.; Wang, Z.; Young, K.; Khurana, J.; Cruz, I.; Chen, J.; Reynaud, B.; Delatte, H.; Baufeld, P.; Rajan, R.P.; et al. G20 discussion group on fall armyworm Spodoptera frugiperda (J.E.Smith) [Lepidoptera: Noctuidae]. In Proceedings of the International Workshop on Facilitatng International Research Collaboration on Transboundary Plant Pests, Tsukuba, Japan, 27–29 November 2019. [Google Scholar]
  13. Food and Agriculture Organization Global Action for Fall Armyworm Control. Available online: http://www.fao.org/fall-armyworm/global-action/en/ (accessed on 10 March 2021).
  14. EPPO Spodoptera Frugiperda (LAPHER). Available online: https://gd.eppo.int/taxon/LAPHFR/distribution (accessed on 12 October 2020).
  15. Nagoshi, R.N.; Dhanani, I.; Asokan, R.; Mahadevaswamy, H.M.; Kalleshwaraswamy, C.M.; Sharanabasappa; Meagher, R.L. Genetic characterization of fall armyworm infesting South Africa and India indicate recent introduction from a common source population. PLoS ONE 2019, 14, e0217755. [Google Scholar] [CrossRef] [Green Version]
  16. Nagoshi, R.N.; Nagoshi, B.Y.; Cañarte, E.; Navarrete, B.; Solórzano, R.; Garcés-Carrera, S. Genetic characterization of fall armyworm (Spodoptera frugiperda) in Ecuador and comparisons with regional populations identify likely migratory relationships. PLoS ONE 2019, 14, e0222332. [Google Scholar] [CrossRef]
  17. Nagoshi, R.N.; Goergen, G.; Du Plessis, H.; van den Berg, J.; Meagher, R. Genetic comparisons of fall armyworm populations from 11 countries spanning sub-Saharan Africa provide insights into strain composition and migratory behaviors. Sci. Rep. 2019, 9, 8311. [Google Scholar] [CrossRef] [Green Version]
  18. Pashley, D.P. Host-associated genetic differentiation in fall armyworm (Lepidoptera: Noctuidae): A sibling species complex? Ann. Entomol. Soc. Am. 1986, 79, 898–904. [Google Scholar] [CrossRef]
  19. Montezano, D.G.; Specht, A.; Sosa-Gómez, D.R.; Roque-Specht, V.F.; Sousa-Silva, J.C.; Paula-Moraes, S.V.; Peterson, J.A.; Hunt, T.E. Host plants of Spodoptera frugiperda (Lepidoptera: Noctuidae) in the Americas. Afr. Entomol. 2018, 26, 286–300. [Google Scholar] [CrossRef] [Green Version]
  20. Pashley, D.P.; Johnson, S.J.; Sparks, A.N. Genetic population structure of migratory moths: The fall armyworm (Lepidoptera: Noctuidae). Ann. Entomol. Soc. Am. 1985, 78, 756–762. [Google Scholar] [CrossRef]
  21. Pashley, D.P. Quantitative genetics, development, and physiological adaptation in host strains of fall armyworm. Evolution 1988, 42, 93–102. [Google Scholar] [CrossRef]
  22. Nagoshi, R.N.; Meagher, R.L. Behavior and distribution of the two fall armyworm host strains in Florida. Fla. Entomol. 2004, 87, 440–449. [Google Scholar] [CrossRef]
  23. Dumas, P.; Legeai, F.; Lemaitre, C.; Scaon, E.; Orsucci, M.; Labadie, K.; Gimenez, S.; Clamens, A.L.; Henri, H.; Vavre, F.; et al. Spodoptera frugiperda (Lepidoptera: Noctuidae) host-plant variants: Two host strains or two distinct species? Genetica 2015, 143, 305–316. [Google Scholar] [CrossRef] [Green Version]
  24. Pashley, D.P.; Martin, J.A. Reproductive incompatibility between host strains of the fall armyworm (Lepidoptera: Noctuidae). Ann. Entomol. Soc. Am. 1987, 80, 731–733. [Google Scholar] [CrossRef]
  25. Groot, A.T.; Marr, M.; Heckel, D.G.; SchÖfl, G. The roles and interactions of reproductive isolation mechanisms in fall armyworm (Lepidoptera: Noctuidae) host strains. Ecol. Entomol. 2010, 35, 105–118. [Google Scholar] [CrossRef]
  26. Groot, A.T.; Marr, M.; Schöfl, G.; Lorenz, S.; Svatos, A.; Heckel, D.G. Host strain specific sex pheromone variation in Spodoptera frugiperda. Front. Zool. 2008, 5. [Google Scholar] [CrossRef] [Green Version]
  27. Hay-Roe, M.M.; Meagher, R.L.; Nagoshi, R.N. Effects of cyanogenic plants on fitness in two host strains of the fall armyworm (Spodoptera frugiperda). J. Chem. Ecol. 2011, 37, 1314–1322. [Google Scholar] [CrossRef] [PubMed]
  28. Prowell, D.P. Sex linkage and speciation in Lepidoptera. In Endless Forms: Species and Speciation; Howard, D.J., Berlocher, S.H., Eds.; Oxford University Press: Oxford, UK, 1998. [Google Scholar]
  29. Prowell, D.P.; McMichael, M.; Silvain, J.F. Multilocus genetic analysis of host use, introgression, and speciation in host strains of fall armyworm (Lepidoptera: Noctuidae). Ann. Entomol. Soc. Am. 2004, 97, 1034–1044. [Google Scholar] [CrossRef] [Green Version]
  30. Nagoshi, R.N. Improvements in the identification of strains facilitate population studies of fall armyworm subgroups. Ann. Entomol. Soc. Am. 2012, 105, 351–358. [Google Scholar] [CrossRef] [Green Version]
  31. Murúa, M.G.; Nagoshi, R.N.; Santos, D.A.D.; Hay-Roe, M.M.; Meagher, R.L.; Vilardi, J.C. Demonstration using field collections that Argentina fall armyworm populations exhibit strain-specific host plant preferences. J. Econ. Entomol. 2015, 108, 2305–2315. [Google Scholar] [CrossRef] [Green Version]
  32. Nagoshi, R.N. The fall armyworm triose phosphate isomerase (Tpi) gene as a marker of strain identity and interstrain mating. Ann. Entomol. Soc. Am. 2010, 103, 283–292. [Google Scholar] [CrossRef] [Green Version]
  33. Nagoshi, R.N.; Meagher, R.L. Using intron sequence comparisons in the triose phosphate isomerase gene to study the divergence of the fall armyworm host strains. Insect Mol. Biol. 2016, 25, 324–337. [Google Scholar] [CrossRef]
  34. Nagoshi, R.N. Evidence that a major subpopulation of fall armyworm found in the Western Hemisphere is rare or absent in Africa, which may limit the range of crops at risk of infestation. PLoS ONE 2019, 14, e0208966. [Google Scholar] [CrossRef] [Green Version]
  35. Folmer, O.; Black, M.; Hoeh, W.; Lutz, R.; Vrijenhoek, R. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol. Mar. Biol. Biotechnol. 1994, 3, 294–299. [Google Scholar] [CrossRef] [PubMed]
  36. Schäffer, A.A.; Aravind, L.; Madden, T.L.; Shavirin, S.; Spouge, J.L.; Wolf, Y.I.; Koonin, E.V.; Altschul, S.F. Improving the accuracy of PSI-BLAST protein database searches with composition-based statistics and other refinements. Nucleic Acids Res. 2001, 29, 2994–3005. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Thompson, J.D.; Higgins, D.G.; Gibson, T.J. CLUSTAL W (improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice). Nucleic Acids Res. 1994, 22, 4673–4680. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Tamura, K.; Stecher, G.; Peterson, D.; Filipski, A.; Kumar, S. MEGA6: Molecular evolutionary genetics analysis version 6.0. Mol. Biol. Evol. 2013, 30, 2725–2729. [Google Scholar] [CrossRef] [Green Version]
  39. Felsenstein, J. Confidence limits on phylogenies: An approach using the bootstrap. Evolution 1985, 39, 783–791. [Google Scholar] [CrossRef]
  40. Tajima, F. Evolutionary relationship of DNA sequences in finite populations. Genetics 1983, 105, 437–460. [Google Scholar] [CrossRef]
  41. Tajima, F. Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 1989, 123, 585–595. [Google Scholar] [CrossRef]
  42. Librado, P.; Rozas, J. DnaSP v5: A software for comprehensive analysis of DNA polymorphism data. Bioinformatics 2009, 25, 1451–1452. [Google Scholar] [CrossRef] [Green Version]
  43. Clement, M.; Posada, D.; Crandall, K.A. TCS: A computer program to estimate gene genealogies. Mol. Ecol. 2000, 9, 1657–1659. [Google Scholar] [CrossRef] [Green Version]
  44. Nayyar, N.; Gracy, R.G.; Ashika, T.R.; Mohan, G.; Swathi, R.S.; Mohan, M.; Chaudhary, M.; Bakthavatsalam, N.; Venkatesan, T. Population structure and genetic diversity of invasive fall armyworm after 2 years of introduction in India. Sci. Rep. 2021, 11, 7760. [Google Scholar] [CrossRef]
  45. Nagoshi, R.N.; Htain, N.N.; Boughton, D.; Zhang, L.; Xiao, Y.; Nagoshi, B.Y.; Mota-Sanchez, D. Southeastern Asia fall armyworms are closely related to populations in Africa and India, consistent with common origin and recent migration. Sci. Rep. 2020, 10, 1421. [Google Scholar] [CrossRef] [Green Version]
  46. Albery, W.; Knowles, J. Evolution of enzyme function and the development of catalytic efficiency. Biochemistry 1976, 15, 5631–5640. [Google Scholar] [CrossRef]
Figure 1. Map showing the collection sites of Spodoptera frugiperda specimens in the different African and Asian countries.
Figure 1. Map showing the collection sites of Spodoptera frugiperda specimens in the different African and Asian countries.
Insects 12 00439 g001
Figure 2. Polymorphic sites of the Tpi gene segments used for strain identification and haplotype diagnosis of Spodoptera frugiperda collected from different African and Asian countries.
Figure 2. Polymorphic sites of the Tpi gene segments used for strain identification and haplotype diagnosis of Spodoptera frugiperda collected from different African and Asian countries.
Insects 12 00439 g002
Figure 3. The maximum likelihood phylogenetic tree of the COI sequences of Spodoptera frugiperda collected from the different African and Asian countries. The color indicates the COI sequences from collected samples in this study, and the others are reference sequences obtained from the GenBank database. Hasegawa-Kishnio-Yano HKY850 model and gamma distribution rate of variation among sites were implemented to construct the phylogenetic tree in MEGA6.
Figure 3. The maximum likelihood phylogenetic tree of the COI sequences of Spodoptera frugiperda collected from the different African and Asian countries. The color indicates the COI sequences from collected samples in this study, and the others are reference sequences obtained from the GenBank database. Hasegawa-Kishnio-Yano HKY850 model and gamma distribution rate of variation among sites were implemented to construct the phylogenetic tree in MEGA6.
Insects 12 00439 g003
Figure 4. Individual nucleotide differences of the COI gene in the corn and the rice strains of Spodoptera frugiperda. We used 658 bp from 39 to 696 positions of 1,531 bp of S. frugiperda COI gene sequence (MN599981, Korea) from NCBI.
Figure 4. Individual nucleotide differences of the COI gene in the corn and the rice strains of Spodoptera frugiperda. We used 658 bp from 39 to 696 positions of 1,531 bp of S. frugiperda COI gene sequence (MN599981, Korea) from NCBI.
Insects 12 00439 g004
Figure 5. Minimum spanning network of the Tpi gene (A) and the COI gene (B) haplotypes of Spodoptera frugiperda from different African and Asian countries.
Figure 5. Minimum spanning network of the Tpi gene (A) and the COI gene (B) haplotypes of Spodoptera frugiperda from different African and Asian countries.
Insects 12 00439 g005
Table 1. Specimens’ details of Spodoptera frugiperda collected from different African and Asian countries. DR, Democratic Republic.
Table 1. Specimens’ details of Spodoptera frugiperda collected from different African and Asian countries. DR, Democratic Republic.
Regions/
Countries
LocationsSpecimen NamesCollection DatesInsect StagesAccession Numbers
TpiCOI
Africa
DR CongoKatana, KabareCon-1111/29/2018LarvaMT894220MT103350
Miti, KabareCon-1211/29/2018LarvaMT894221MT933052
Minova, KaleheCon-2111/29/2018LarvaMT894222MT933053
Luvungi, UviraCon-3112/15/2018LarvaMT894223MT933054
Sange, UviraCon-4112/15/2018LarvaMT894224MT933055
Nduba, WalunguCon-4212/15/2018LarvaMT894225MT103349
TanzaniaArusha, TengeruTan-11/10/2019LarvaMT894226MT103348
Mlali, MorogoroTan-21/17/2019LarvaMT894227MT933056
Sri, PwaniTan-31/10/2019LarvaMT894228MT933057
Sua, MorogoroTan-41/14/2019LarvaMT894229MT933058
UgandaMbaleUga-11/10/2018LarvaMT894230MT933059
MasindiUga-210/17/2017LarvaMT894231MT933060
KoleUga-310/18/2018LarvaMT894232MT933061
LuweroUga-410/15/2018LarvaMT894233MT933062
ZimbabweHarare research station, HarareZim-12/8/2019LarvaMT894234MT103346
Chipinge, ManicalandZim-22/22/2019LarvaMT894235MT103347
Asia
Bangladesh DhakaBan-18/14/2019LarvaMT894236MT933063
KoreaJejuKor-19/19/2019AdultMT894237MT933064
GyeongsanKor-28/29/2019LarvaMT894238MT103342
GyeongsanKor-36/10/2020LarvaMT894239MT933065
JejuKor-46/9/2020AdultMT894240MT933066
NepalBhakundebesi, KavreNep-19/24/2019LarvaMT894241MT103345
Khumaltar, LalitpurNep-27/30/2019LarvaMT894242MT933067
Khaira, PyathanNep-38/6/2019LarvaMT894243MT933068
VietnamNinh BinhVie-19/30/2019AdultMT894244MT103334
Vinh PhucVie-29/30/2019AdultMT894245MT103335
HanoiVie-39/30/2019LarvaMT894246MT103336
Table 2. Genetic variability analysis of Tpi and COI gene of Spodoptera frugiperda in Africa and Asia.
Table 2. Genetic variability analysis of Tpi and COI gene of Spodoptera frugiperda in Africa and Asia.
GenesRegionsNumber of SequencesSegregating SitesHaplotypesHaplotype
Diversity
Nucleotide
Diversity
Theta/SiteTajima’s D
TpiAfrica1618100.9330.0169110.0121.531362
Asia101450.6670.0116710.0111.11681
COIAfrica161020.1250.00190.005−2.182611 **
Asia111120.1820.003040.006−2.011459 *
* p < 0.05, ** p < 0.01.
Table 3. Specimens and haplotypes of Spodoptera frugiperda Tpi gene.
Table 3. Specimens and haplotypes of Spodoptera frugiperda Tpi gene.
SnSpeamensHaplotypesStrains
1Con-11h2Tpi-Ca1
2Con-42, Kor-4, Nep-1, Nep-2, Nep-3, Vie-1, Vie-3, Zim-1h5
3Kor-2, Tan-1h6
4Tan-3, Zim-2h9
5Uga-1h10
6Uga-4h12
7Con-21, Con-31, Uga-3, Vie-2h4Tpi-Ca2a
8Kor-3h7
9Ban-1h1Tpi-Ca2b
10Con-12, Con-14, Tan-4h3
11Tan-2h8
12Uga-2h11
Table 4. Specimens and haplotypes of Spodoptera frugiperda COI gene.
Table 4. Specimens and haplotypes of Spodoptera frugiperda COI gene.
SnSpeamensHaplotypesStrains
1Ban-1, Kor-1, Kor-2, Kor-3, Kor-4, Nep-1, Nep-2, Nep-3, Vie-1, Vie-2, Con-11, Con-12, Con-21, Con-31, Con-41, Con-42, Tan-1, Tan-2, Tan-4, Uga-1, Uga-2, Uga-3, Uga-4, Zim-1, Zim-2h1COI-R
2Vie-3h2COI-C
3Tan-3h3
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Acharya, R.; Akintola, A.A.; Malekera, M.J.; Kamulegeya, P.; Nyakunga, K.B.; Mutimbu, M.K.; Shrestha, Y.K.; Hemayet, J.S.M.; Hoat, T.X.; Dao, H.T.; et al. Genetic Relationship of Fall Armyworm (Spodoptera frugiperda) Populations That Invaded Africa and Asia. Insects 2021, 12, 439. https://doi.org/10.3390/insects12050439

AMA Style

Acharya R, Akintola AA, Malekera MJ, Kamulegeya P, Nyakunga KB, Mutimbu MK, Shrestha YK, Hemayet JSM, Hoat TX, Dao HT, et al. Genetic Relationship of Fall Armyworm (Spodoptera frugiperda) Populations That Invaded Africa and Asia. Insects. 2021; 12(5):439. https://doi.org/10.3390/insects12050439

Chicago/Turabian Style

Acharya, Rajendra, Ashraf Akintayo Akintola, Matabaro Joseph Malekera, Patrick Kamulegeya, Keneth Benedictor Nyakunga, Munyaradzi Kennedy Mutimbu, Yam Kumar Shrestha, Jahan S. M. Hemayet, Trinh Xuan Hoat, Hang Thi Dao, and et al. 2021. "Genetic Relationship of Fall Armyworm (Spodoptera frugiperda) Populations That Invaded Africa and Asia" Insects 12, no. 5: 439. https://doi.org/10.3390/insects12050439

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

Article Metrics

Back to TopTop