Molecular characterization of fall armyworm, Spodoptera frugiperda (J. E. Smith) using mitochondrial COI gene infesting sorghum in Gujarat region

Introduction

Often referred to as "jowar" or "milo," sorghum, Sorghum bicolor, is a highly droughttolerant, adaptable cereal grain and staple food. Sorghum is a major crop in Asian and African nations like Nigeria and India, where it is used to create bread and porridges. In many underdeveloped and semiarid areas, sorghum is the main source of human nutrition and energy (Rooney and Waniska, 2000) [15] . About 52.80 million tonnes of sorghum were produced worldwide in 2023-2024. With 4.40 million tonnes of sorghum planted on 3.97 million hectares in 2023-2024, India ranks fourth in the world for overall sorghum production. The majority of the sorghum was produced during the rabi season. The Government of India's third advance estimate for 2023-2024 states that the sorghum crop will yield 47.42 lakh tonnes, up from 38.14 lakh tonnes in 2022-2023 (Anon., 2023) [1] . In various Indian agroecosystems, it is home to around 150 insect species. According to Nwanze et al. (1995), the sorghum midge, shoot fly, and stem borer have become important pests in India and are responsible for around 32 percent of production loss. The autumn armyworm, S. frugiperda (J. E. Smith), is a newly introduced pest that poses a serious danger to global cereal production and is reducing sorghum yield by 70 percent (Venkateswarlu et al., 2018; Harrison et al., 2019) [17,5] . Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), the tropical American bug known as the fall armyworm (FAW), is an invasive pest that results in large financial losses. This harmful pest might seriously injure about 100 plant species from 27 families, including the maize crop and other graminaceous crops like millet, sorghum, rice, wheat and sugarcane (Goergen et al., 2016) [3] . Sorghum, the second most affected crop after maize, is severely harmed by fall army worms, which are polyphagous and highly destructive parasites. It has been determined that yield losses from twelve maize producing countries range from 8.30 to 20.60 million tons per year. This pest has been found on maize crops in several areas of the states of Telangana and Andhra Pradesh since July 2018. In October of 2018, fall armyworm was observed on sorghum and bajra. In the fields of the agricultural research station in Ananthapuramu, 30 percent of the bajra and 70 percent of the sorghum were damaged (Venkateswarlu et al., 2018; Harrison et al., 2019) [17,5] . This species is well-known for its wide host range, fast rate of reproduction, tolerance to traditional pesticides and adaptability to a variety of circumstances. Depending on the host plant's desire, FAW is composed of two strains: the rice strain and the corn strain. These strains differ genetically, with a large proportion of genomic divergence, yet having comparable morphologies. With two dominant strains, "C" and "R", the FAW has developed into a super pest. While the rice strain "R" primarily targets rice and other grasses, the corn strain "C" affects maize, sorghum and cotton. (Venkateswarlu et [17,5,4] . Because of the intraspecific and interspecific variation among FAW strains, precise strain identification is essential in field studies of FAW populations. The two strains of FAW are mainly distinguished by polymorphisms in the mitochondrial gene cytochrome c oxidase (Nagoshi, 2010) [10] . Because most invaded areas have few haplotypes and limited genetic diversity, which may indicate a recent introduction from a common source of the FAW population, monitoring of the crops at risk in these areas may be impacted (Nagoshi et al., 2018 & Nagoshi et al., 2020) [11,12] . Molecular genetic markers are one of the most reliable methods to differentiate between the many strains of FAW, even though their morphometric traits can be evaluated based on the shapes of their wings. As a result, DNA-based methods provide a dependable and all-purpose identification tool that may be applied throughout life. As a result, DNA barcoding is increasingly being recommended and used globally to identify invasive species. To identify species that are important from an ecological and economic perspective, a portion of the mitochondrial cytochrome c oxidase subunit 1 (COI) gene is used during the barcoding process. (Venkateswarlu et al., 2018; Harrison et al., 2019; Ramos-Hernández et al., 2023) [17,5,14] . FAW is a global concern because it could jeopardize the lives and food security of many small-scale farmers in Asia and India. The purpose of this study was to increase research on the genetic diversity of FAW populations in south Gujarat. The current work uses COX I gene sequences to describe the genetic diversity of S. frugiperda populations obtained from four different sorghum growing areas spanning different agroclimatic zones of Gujarat. It is anticipated that these discoveries will aid in the creation of sustainable management plans, population monitoring, and more precise pest identification.

Materials and Methods

Sample Collection and Preservation

S. frugiperda larvae were gathered as specimens from four sorghum-growing sites spread across different Gujarat agroclimatic zones during the trial periods of 2024-2025. At the height of the infestation in the kharif of 2024-2025, the following sites were chosen for the study at Main Sorghum Research Station (MSRS), NAU, Surat and one farmer field each from Surat, Tapi and Junagadh district. For molecular analysis, representative specimens were preserved in 70% ethanol and stored at-20 °C until DNA extraction. (Babu et al., 2019; Ramos-Hernández et al., 2023) [2,14] .

Genomic DNA Isolation

A modified CTAB approach was used to extract the genomic DNA of S. frugiperda obtained from four separate locations. Proteinase K and RNase treatments were followed by chloroform: isoamyl alcohol purification and isopropanol precipitation. DNA purity (A260/A280) was evaluated using NanoDrop spectrophotometry, and DNA integrity was verified by 0.8 percent agarose gel electrophoresis. Samples were kept for further molecular analysis at-20 °C. ( [14,8,6] .

PCR amplification and purification

Universal primers were used to amplify mitochondrial COX I areas in accordance with procedures by Nagoshi et al. (2018) [11] , Babu et al. (2019) [2] and Kalaria et al. (2025) [6] . The master mix, primers, DNA template, and nuclease-free water were all included in each 25 μl PCR reaction. The cycling program consisted of initial denaturation at 94 °C for 1 min, 30 cycles of 94 °C for 35 s, 58 °C for 50 s, and 72 °C for 50 s, followed by a final extension at 72 °C for 5 min. Ethidium bromide-stained 2 percent agarose gels were used to confirm amplicons. The Sanger technique was used to sequence the PCR products after they were purified using ethanol-sodium acetate precipitation and resuspended in Hi-DiTM formamide. After being trimmed and aligned, highquality reads were utilized for molecular analysis. ( [16,9,14,6] .

DNA Sequence assembly and phylogenetic tree analysis COX I readings were cleaned in BioEdit v7, processed in MEGA 12, and put together into consensus sequences using Sequencher v5.3. Accession numbers were allocated to validated sequences that were submitted to NCBI GenBank, and identities were verified using BLASTn (≥98% similarity) (Mohapatra et al., 2023; Kalaria et al., 2025) [9,6] . ClustalW alignments were used to examine barcode gap and genetic divergence. Maximum Likelihood was used to infer phylogenetic relationships (MEGA 12, 1000 bootstraps) (Sathyan, et al [16,9,14,6] .

Submission to the Barcode of Life Data System (BOLD)

The Barcode of Life Data System received COX I sequences, metadata, photos, and trace files in order to facilitate international data exchange and precise species identification by DNA barcoding analysis (Kalaria et al., 2025) [6] .

Results and Discussion

Specimen collection and Molecular identification of S. frugiperda Using COX I Genes

To gather S. frugiperda larvae, field surveys were carried out in four main sorghum-growing localities in Gujarat: MSRS, NAU, Surat and one farmer field each from Surat, Tapi and Junagadh district. Mature, fully developed larvae were gathered at random from several fields, preserved in 70 percent alcohol, and their geographic location longitude and [14] . Maize fields infested by fall armyworm were surveyed and fall armyworm larvae were collected from maize growing area of middle Gujarat at peak infestation level in kharif 2021 and rabi 2021-22 (Mohapatra et al., 2023) [9] .

Genomic DNA Extraction and PCR amplification

For molecular analysis, specimens were kept at-20 °C and maintained in 70 percent ethanol ( ) [6] . [11,2] . In line with S. frugiperda investigations, clear, distinct bands on 2 percent agarose gels (Fig 5) validated primer specificity and PCR efficiency (Nagoshi et al., 2020) [12] . All loci produced high-quality bidirectional reads when sequenced using gene-specific primers and the BDT v3.1 Cycle Sequencing Kit on an ABI 3730xl Genetic Analyzer, offering a solid foundation for phylogenetic and genetic diversity analysis. [14] and Kalaria et al. (2025) [6] also reported a single, thick and transparent band with amplicons of roughly 700 bp is produced by molecular characterisation of the barcoding COI region of the S. frugiperda discovered in Tabasco. Similarly Mohapatra et al. (2023) [9] and Lebody et al.( 2024) [8] also reported PCR amplification resulted in a ~700 bp fragment among 33 FAW strains utilizing cytochrome oxidase (COX1) sequences.

DNA Sequence Assembly

BLASTn-verified consensus sequences constructed in Sequencher v5. [9,8,6] . All sequences were submitted to GenBank using the following accession numbers: JPV156122.1, PV156132.1, PV156480.1, PV156481.1, PV156447.1, PV156448.1, PV156493.1, and PV156519.1.

Phylogenetic Analysis and Genetic Distance

Using Maximum Likelihood in MEGA12, phylogenetic relationships between S. frugiperda populations from different Gujarat agro climatic zones were deduced from COX I sequences (Kumar et al., 2024) [7] . Under the Kimura 2-parameter model, validated by Neighbor-Joining with 1000 bootstraps (Fig 6). [14] . Mohapatra et al.

(2023) [9] performed phylogeny analysis used consensus sequences from S. frugiperda population characterized under different strains in maize. Similarly, phylogenic analysis reported as 'C' strain of FAW collected from maize, sweet corn and sorghum crops in India (Sathyan, et al., 2022) [16] . Phylogenetic analysis suggests that the primary sources of Spodoptera frugiperda in Egypt likely stem from both Asian and African origins (Lebody et al., 2024) [8] .

DNA Barcode Submission to BOLD

The Barcode of Life Data System (BOLD) received specimen-level metadata, including as taxonomy, sequences, trace files, and photos of S. frugiperda from four Gujarat regions. For accurate identification and comparison analysis, COX I barcodes were created and unique process IDs were assigned ( [6] . timeframes. These studies have potential for regional and national S. frugiperda pest management strategies and are useful for evaluating genetic diversity.

References

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