







































 

 

 
35 

© 2025 Conscientia Beam. All Rights Reserved. 

Phylogeny of Trichoplusia ni (Lepidoptera: Noctuidae) 18S and 5S ribosomal RNA gene 
sequence   

 

 

 Hanan Salah El-
Din Taha 

 

Central Agricultural Pesticide Laboratory, Agricultural Research Center-
Dokki-Giza, Egypt. 
Email: Hanansalah412@yahoo.com  

 
 ABSTRACT 
 
Article History 
Received: 7 November 2024 
Revised: 9 April 2025 
Accepted: 18 April 2025 
Published: 14 May 2025 
 

Keywords 
18 S 
5S 
Phylogeny 
Ribosomal RNA 
Sequence alignment 
Trichoplusia ni. 

 
Trichoplusia ni Hübner, a cabbage looper belonging to the Noctuidae family of 
Lepidoptera, is a highly varied agricultural pest. It is essential to use partial sequences of 
nuclear DNA, 18S, and 5S ribosomal genes to isolate and analyze the phylogenetic 
relationships within T. ni and other insect species families and orders using distinct gene 
markers. T. DNA. After being extracted and sequenced using primers, Clustal W 
alignment and NCBI BLAST were completed. Members of the 18S BLAST lineage 
sequences are classified according to the order Coleoptera and the family Coccinellidae. 
A total of 2461 positions are occupied by the 33 sequences that were chosen for the final 
dataset. In the final dataset, 19 nucleotide sequences totaling 1935 positions were chosen 
from the taxonomy asset of 5S BLASTed lineages, which included members of the order 
Hymenoptera and the family Chalcidoidea. For both genes, phylogenetic analyses were 
performed using the Maximum Composite Likelihood model (ML), which aids in the 
construction of phylogenetic relationships at various taxonomic levels of trees, provides 
phylogenetic insights for understanding relationships between closer clades, and 
explains some significant regions of substitution rates appropriate for changing 
evolutionarily distant taxa. 
 

Contribution/Originality: Molecular phylogenetic studies and evolutionary biology have garnered more 

attention recently. They contribute to the knowledge of the traits of foraging behavior and insect 

resurgence, such as host specificity, transmission patterns, genetic diversity, and natural enemies. There 

aren't many known phylogenetic analyses of insect ribosomal RNA searches. 

 

1. INTRODUCTION 

In Egypt, 160 different crops and vegetables, including cotton, are vulnerable to attacks by the highly 

polyphagous cabbage looper, Trichoplusia ni Hübner (Lepidoptera: Noctuidae), which is regarded as a 

significant agricultural pest of tomato, eggplant, zucchini, and other members of the Cruscus family [1]. 

Larvae consume vast amounts of plant leaves and fruits, which leads to population growth and crop damage 

[2]. The potential for control failure is caused by the economic damage at the lower threshold. The most 

common issue with this pest is the variation in the intensity of insecticide resistance development by 

location. Some substitutes, such as pyrethroids, Bacillus thuringiensis, and neem, are still effective, 

particularly when used in the early stages of larval development, when the high pest resistance status 

indicates polygenic inheritance or multiple resistance mechanisms [3, 4]. The recently suggested 

insecticide products for the control of cabbage loopers necessitate careful planning for resistance 

Current Research in Agricultural Sciences 
2025 Vol. 12, No. 1, pp. 35-48 
ISSN(e): 2312-6418 
ISSN(p): 2313-3716 
DOI: 10.18488/cras.v12i1.4210 
© 2025 Conscientia Beam. All Rights Reserved. 

 
 
 

 
 
 
 

 

 
 
 
 

mailto:Hanansalah412@yahoo.com
https://orcid.org/0000-0002-8735-0606
https://www.doi.org/10.18488/cras.v12i1.4210


Current Research in Agricultural Sciences, 2025, 12(1): 35-48 

 

 
36 

© 2025 Conscientia Beam. All Rights Reserved. 

management strategies, choices regarding acquisition, and the preservation of the new insecticide's 

effectiveness [5]. Five to seven generations of cabbage loopers are produced annually. Temperature and 

thresholds impact development and reproduction; in winter, reproduction is lower (10–12 °C), but in 

summer, it is higher (40°C), where this pest overwinters as a pupa. For two to three weeks, larvae feed on 

leaves and fruit, but tomato crop damage is uncommon. Weekly scouting to find a 5 percent defoliation 

threshold is necessary for efficient management, followed by effective insecticide, Natwick and Lopez [6]. 

Large DNA sequence data sets for biological research on the pattern of mitochondrial and nuclear gene 

evolution in animal, insect, or plant genomes are made available by advances in molecular biology 

techniques and sequencing. These developments also aid in the construction of phylogenetic relationships 

at various taxonomic levels [7]. A popular tool for examining the molecular evolution of multigene families 

is ribosomal DNA (rDNA). The two primary types of rDNA genes found in eukaryotes are 5S rDNA and 

45S rDNA repeats, which encode rRNA and are highly conserved gene products found in all cells. 

According to Zhao et al. [8], the 5S rDNA gene is a unit made up of a gene transcription region (120 bp) 

and a non-transcribed spacer (NTS), whereas the 45S rDNA in animals contains 18S, 5.8S, 28S, and spacers 

(IGS, ITS1, and ITS2) [8]. Additionally, many insects' mitochondrial genes, including 16S and COI, have 

been studied [9, 10], The availability of the 18S rRNA molecule is used to provide phylogenetic gestures 

for perceptive closer clade relationships and to explain some significant regions of substitution rates 

appropriate for changing evolutionarily distant taxa, Wu, et al. [11]. The study of evolutionary 

relationships between species, taxa, individuals, or genes/proteins is known as phylogeny. In order to 

predict phylogenetic affiliations between molecular characters of the nucleotide data and align appropriate 

sequences to achieve similarity, it is crucial to determine homology as soon as possible [12-14]. Individual 

base positions are aligned to maximize overall position resemblance across the sequence [15]. More than 

a thousand different insect species can be found in Egypt. They all belong to a limited number of orders 

that share certain traits, despite their differences in size and shape [16, 17]. The previous T organization 

system. The kingdom Animalia, phylum Arthropoda, subphylum Hexapoda, class Insecta, order 

Lepidoptera, family Noctuidae, subfamily Plusiinae, and tribe Argyrogrammatini are among the 

hierarchical categories that comprise insect taxonomic orders. Therefore, it is urgent to create phylogenetic 

trees and align multiple sequences using software in order to perform evolutionary relationship or 

phylogeny analysis on some sequences of various holometabolous insect species that are divided into three 

assemblages: (Neuropterida) includes neuroptera, megalopteran, raphidoptera, strepsiptera, and 

coleoptera, and (Hymenopterioida) includes hymenoptera and panopridae includes (Siphonaptera, diptera, 

trichoptera, lepidoptera, and mecoptera.) Additionally, it is necessary to estimate evolutionary distances, 

build trees, test tree reliability, work with genes and domains, test for selection, manage taxa with groups, 

compute sequence statistics, and construct likelihood trees, and compare the results using all five different 

methods [14, 18]. These techniques include Minimum-Evolution, Neighbour-Joining, and Maximum 

Likelihood (ML). Nevertheless, UPGMA was one of two cluster analysis methods Sayers et al. [19]. 

 

2. MATERIALS AND METHODS 

2.1. Insect Sources and DNA Extraction of Larvae 

A few Trichoplusia ni Hubner larvae were transferred to Cairo University's molecular biology labs after 

being collected from tomato plants. About 0–5 ml of CTAB buffer was prepared in accordance with the 

CTAB DNA extraction protocol, which was used to complete the extraction process according to Doyle 

and Doyle [20]. 

 

 



Current Research in Agricultural Sciences, 2025, 12(1): 35-48 

 

 
37 

© 2025 Conscientia Beam. All Rights Reserved. 

2.2. Polymerase Chain Reaction Procedure Preparations 

After thawing, gently vortex and quickly centrifuge DreamTaq Green PCR Master Mix (2X). 

Additionally, for each 50 μl reaction, place a thin-walled PCR tube on ice and add the following ingredients: 

DreamTaq Green PCR Master Mix (2X) 25 μl, Forward primer 2 μl, Reverse primer 2 μl, Template DNA 

4 μl, Nuclease-free water 17 μl, and Total volume 50 μl. After adjusting the volume, sample vortexing and 

gentle spinning were performed. The following suggested thermal cycling conditions were used for the 

PCR procedures: initial denaturation at 95°C for 5 minutes for one cycle, denaturation at 95°C for 30 

seconds for 40 cycles, annealing at 65°C for 30 seconds for 40 cycles, extension at 72°C for 30 seconds for 

40 cycles, and final extension at 72°C for 10 minutes for one cycle. 

Table 1 Sequences of the primers used for PCR amplification and sequencing. 

 

Table 1. Primer used in the amplification. 

Gene  Primer 
name 

Primer sequence  Length 
bp 

GC MW Annealing 
temp 

18S  5- AGTACGGTGAAACCGCGAAA 
Reverse: TTTCGCGGTTTCACCGTACT 

20 50 % 6246 56.7 

5S  5-AAGTGTACTCATTCCGATTACGG 
Reverse: 
CCGTAATCGGAATGAGTACACTT 

23 43.47 % 7101 54.4 

 

2.3. Sequencing Procedure 

As previously mentioned, two primers were used to sequence the purified PCR. The Big Dye 

Terminator Cycle Sequencing Kit v3.1 (Applied Biosystems, USA) was used for the sequencing process. 

The Macrogen company's Applied Biosystems model 3730 automated DNA sequencing system was used 

to resolve the sequencing products. 

 

2.4. Phylogenetic Analysis: Sequence Alignment and Phylogenetic Tree 

The National Center for Biotechnology Information's (NCBI) BLAST algorithm databases were used to compare 

the T ni 18s and 5s rRNA nucleotide sequences obtained from the sequencing company with those of other insects 

(Tables 2,3). aligning multiple sequences with the Thompson et al. [21] was completed, after which Mega 11 software 

built phylogenetic trees and carried out all phylogenetic analysis [22].  

 

3. RESULTS AND DISCUSSIONS 

3.1. The 18S, 5s rRNA Phylogenetic Analysis 

Partial nuclear DNA, 18S, and 5S ribosomal gene sequences were used to investigate the evolutionary 

relationships between lineage groups of the cabbage looper T. ni. In a separate analysis, phylogenetic 

relationships between insect lineage families and orders were inferred. Members of the taxonomy of 18S 

blasted lineage sequences belong to the family Coccinellidae and the order Coleoptera. Additionally, the 

member of the 5S blasted lineage belonged to the family Chalcidoidea, order Hymenoptera. The 

examination of T's 18S rRNA molecular data set included 33 nucleotide sequences from the ClustalW 

alignment that were then blasted against the PCR-generated native sequence. The final dataset contained 

2646 positions in total. First, second, third, and noncoding codon positions were included. There were 

nineteen nucleotide sequences in the 5S rRNA analysis. The final dataset contained 1935 positions in total. 

For both genes, phylogenetic analyses were performed using the (ML) (Table 6). Every sequence pair's 

ambiguous positions were eliminated. Alignment and evolutionary analyses were performed to calculate 

different statistical quantities of nucleotide sequences. Table 2 lists the species information for the 18S 

rRNA sequences that have been aligned, and Table 3 lists the 5S rRNA sequences that have been aligned. 



Current Research in Agricultural Sciences, 2025, 12(1): 35-48 

 

 
38 

© 2025 Conscientia Beam. All Rights Reserved. 

The NCBI blast plus identity and E value were displayed in Tables 2 and 3, along with the accession 

number, distances, homogeneity, divergence, and insect species names and orders. The Disparity Index 

test (Homogeneity of Substitution Patterns test Between Sequences or the net composition bias) is one of 

the results of phylogeny analysis [23, 24]. It is used to understand shifts in mutational patterns and 

selective pressures if sequences and species evolve with heterogeneous patterns, as well as the role of base 

composition biases between sequences and the probability that the null hypothesis will be rejected if 

sequences with the same pattern have evolved of substitution. P-values less than 0.05 are considered 

significant, according to the Monte Carlo test's estimations (500 replicates). According to Tajima and Nei 

[25], the number of nucleotide substitutions per site between two homologous DNA sequences is an 

estimate of the evolutionary change of DNA sequences caused by nucleotide substitution, deletion, and 

insertion. The pattern of change accumulation was calculated using the evolutionary distance, and the 

amino acid sequence data indicate that deletions and insertions are significantly less common in the coding 

regions of globin genes than in the noncoding regions. Actually, there is no issue when there are few 

nucleotide substitutions per site. In order to measure the impact of insertion and deletion on the 

evolutionary change of DNA sequences, Gamma was introduced. 

 

Table 2. List of different insect 18S ribosomal RNA sequences (Practically from the order Coleoptera, family Coccinellidae) obtained from 
NCBI-BLAST sequences, identity from 99.55 to 97.81, accession number, homogeneity, divergence, and distance between all taxa and T.ni 
PCR-generated sequence. 

N. Species name E-value Identity Length Accession n. Distance Hom Div.h 

1 Rodolia sp.  3.00E-112 99.55 1857 KP829195.1 0.919 0.226 0.273 
2 Monocoryna sp.  3.00E-112 99.55 1866 KP829165.1 0.910 0.190 0.294 
3 Epilachna borealis 3.00E-112 99.55 1848 KP123077.1 0.900 0.240 0.234 
4 Toxotoma forsteri 3.00E-112 99.55 1848 KP123017.1 0.900 0.192 0.234 

5 
Neoneuromus 
ignobilis 

3.00E-112 99.55 7345923 CP092098.1 
0.900 0.172 0.328 

6 Rhyzobius hilura 3.00E-112 99.55 1823 EF209861.1 0.923 0.346 0.099 

7 
Neohermes 
californicus 

3.00E-112 99.55 1676 EU815261.1 
0.919 0.232 0.206 

8 Parainocellia bicolor 3.00E-112 99.55 2097 EU815245.1 0.913 0.204 0.266 

9 
Austroneurorthus 
brunneipennis 

3.00E-112 99.55 2461 EU815229.1 
0.925 0.202 0.237 

10 Strigocis opacicollis 3.00E-112 99.55 820 FM877872.1 0.925 0.198 0.279 
11 Hyperaspidini sp. 3.00E-112 99.55 1768 EU145620.1 0.916 0.296 0.148 
12 Negha meridionalis 3.00E-112 99.55 2071 AY521865.1 0.881 0.008 1.578 

13 
Meropathus 
zelandicus 

3.00E-105 97.82 601 LT990835.1 
0.920 0.226 0.262 

14 
Neostylopyga 
rhombifolia 

3.00E-105 98.24 1842 KP986337.1 
0.916 0.302 0.154 

15 
Ametastegia 
equiseti 

4.00E-111 99.1 25643224 OZ022392.1 
0.888 0.000 1.643 

16 
Libethra 
strigiventris 

3.00E-105 98.23 1823 MN925370.1 
0.921 0.220 0.258 

17 
Adelphydraena 
orchymonti 

3.00E-105 97.82 601 HM588578.1 
0.918 0.176 0.333 

18 Meropathus sp.  3.00E-105 97.82 1791 EF214162.1 0.900 0.012 1.356 

19 
Neuroperlopsis 
patris 

3.00E-105 97.41 1996 EF622699.1 
0.894 0.000 1.695 

20 Desertaclopus lucasi 1.00E-104 97.81 1845 MG924409.1 0.921 0.174 0.341 
21 Mikado sp.  1.00E-104 97.81 620 LR742672.1 0.916 0.132 0.424 

22 
Hydraena 
paeminosa 

1.00E-104 98.65 622 LR742669.1 
0.933 0.182 0.286 

23 Scirtoidea sp. 1.00E-104 97.81 1921 KX092894.1 0.949 0.166 0.331 

24 
Belohina 
inexpectata 

1.00E-104 97.81 1917 OR754010.1 
0.921 0.112 0.430 

25 Satonius sp. 1.00E-104 97.81 1067 KP419279.1 0.913 0.122 0.448 

https://www.ncbi.nlm.nih.gov/nucleotide/KP829195.1?report=genbank&log$=nucltop&blast_rank=1&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/KP829165.1?report=genbank&log$=nucltop&blast_rank=2&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/KP123077.1?report=genbank&log$=nucltop&blast_rank=4&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/KP123017.1?report=genbank&log$=nucltop&blast_rank=7&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/CP092098.1?report=genbank&log$=nucltop&blast_rank=8&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/EF209861.1?report=genbank&log$=nucltop&blast_rank=9&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/EU815261.1?report=genbank&log$=nucltop&blast_rank=10&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/EU815245.1?report=genbank&log$=nucltop&blast_rank=11&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/EU815229.1?report=genbank&log$=nucltop&blast_rank=12&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/FM877872.1?report=genbank&log$=nucltop&blast_rank=13&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/EU145620.1?report=genbank&log$=nucltop&blast_rank=16&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/AY521865.1?report=genbank&log$=nucltop&blast_rank=17&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/LT990835.1?report=genbank&log$=nucltop&blast_rank=17&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/KP986337.1?report=genbank&log$=nucltop&blast_rank=19&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/OZ022392.1?report=genbank&log$=nucltop&blast_rank=19&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/MN925370.1?report=genbank&log$=nucltop&blast_rank=20&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/HM588578.1?report=genbank&log$=nucltop&blast_rank=21&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/EF214162.1?report=genbank&log$=nucltop&blast_rank=22&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/EF622699.1?report=genbank&log$=nucltop&blast_rank=23&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/MG924409.1?report=genbank&log$=nucltop&blast_rank=24&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/LR742672.1?report=genbank&log$=nucltop&blast_rank=25&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/LR742669.1?report=genbank&log$=nucltop&blast_rank=26&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/KX092894.1?report=genbank&log$=nucltop&blast_rank=27&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/OR754010.1?report=genbank&log$=nucltop&blast_rank=28&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/KP419279.1?report=genbank&log$=nucltop&blast_rank=29&RID=BPYCMG8X016


Current Research in Agricultural Sciences, 2025, 12(1): 35-48 

 

 
39 

© 2025 Conscientia Beam. All Rights Reserved. 

N. Species name E-value Identity Length Accession n. Distance Hom Div.h 
26 Nycteus infumatus 1.00E-104 97.81 1868 KP419194.1 0.913 0.120 0.448 

27 
Clytra 
quadripunctata 

1.00E-104 97.81 1883 KP762945.1 
0.923 0.120 0.542 

28 Labidostomis lucida 1.00E-104 97.81 1916 KP762940.1 0.913 0.108 0.448 
29 Lachnaia gallaeca 1.00E-104 97.81 1915 KP762933.1 0.913 0.108 0.448 

30 
Smaragdina 
rufimana 

1.00E-104 97.81 1883 KP762874.1 
0.913 0.168 0.448 

31 
Trigonogenium 
angulosum 

1.00E-104 97.81 1865 KM364119.1 
0.926 0.158 0.445 

32 
Paragrilus 
aeraticollis 

1.00E-104 97.81 1748 KM364075.1 
0.933 0.130 0.464 

Note: Div=Interspecific genetic divergence, H=heterogeneity  and Hom=Homogeneity. 

 

Table 3. List of different insect 5s ribosomal RNA sequences (Practically from order Hymenoptera, family Calcidoidae) attained from NCBI-
blast information, identity from 89.72 to 88.79, accession number, distance, homogeneity and divergence. 

N. Species name E-value % Identity Length Accession n. Dist Homo Div. 

1 Phymastichus coffea 3.00E-28 89.72 1915 XR_009302357.1 0.441 0.022 0.647 
2 Nasonia vitripennis 1.00E-26 88.79 1915 XR_004228347.1 0.559 0.010 0.772 
3 Coruna clavata 1.00E-26 88.79 897 KY887836.1 0.559 0.012 0.772 
4 Asaphes vulgaris 1.00E-26 88.79 897 KY887833.1 0.559 0.004 0.772 
5 Alloxysta victrix 1.00E-26 88.79 893 KY887822.1 0.559 0.018 0.772 
6 Aphelinus varipes 1.00E-26 88.79 892 KY887812.1 0.559 0.018 0.772 
7 Praon necans 1.00E-26 88.79 903 KY873372.1 0.559 0.014 0.772 
8 Ephedrus plagiator 1.00E-26 88.79 904 KY873354.1 0.559 0.012 0.772 
9 Kerria yunnanensis 1.00E-26 88.79 568 JQ365156.1 0.559 0.006 0.772 
10 Ephuta sp. 1.00E-26 88.79 737 EF473894.1 0.559 0.010 0.772 
11 Sphaeropthalma 

coaequalis 1.00E-26 88.79 730 EF473891.1 0.559 0.016 0.772 
12 Odontophotopsis 

melicausa 1.00E-26 88.79 731 EF473889.1 0.559 0.006 0.772 
13 Dasymutilla 

subhyalina 1.00E-26 88.79 731 EF473888.1 0.559 0.010 0.772 
14 Aprostocetus 

purpureus 1.00E-26 88.79 1775 JQ359003.1 0.559 0.018 0.772 

15 
Trichogramma 
platneri 1.00E-26 88.79 1900 JN623531.1 0.500 0.012 0.713 

16 Podagrion sp. 1.00E-26 88.79 1895 JN623524.1 0.559 0.016 0.772 
17 Tetracampe sp. 1.00E-26 88.79 1268 JN623512.1 0.559 0.022 0.772 
18 Foersterella reptans 1.00E-26 88.79 1898 JN623511.1 0.559 0.012 0.772 

19 
Signiphora 
dipterophaga 1.00E-26 88.79 1901 JN623482.1 0.441 0.022 0.647 

 

Table 5 displays the maximum composite ML of the nucleotide substitution pattern as well as the rates 

of various transitional and transversional substitutions for both genes. A = 24.06 percent, T/U = 24.22 

percent, C = 23.92 percent, and G = 27.79 percent are the nucleotide frequencies of the 18S alignment. For 

purines, the transition/transversion rate ratio is k1 = 23.918; for pyrimidines, it is K2 = 291.494. R = 

[A*G*k1 + T*C*k2]/[(A+G) * (T+C)] is the overall transition/transversion bias, or R = 73.714. 

However, the estimated ratio (R) value for 5S is 0.53, which is the number of transitional substitutions to 

that of transversional substitutions. Rates and patterns of substitution were calculated using the Tamura et 

al. [26] as well as the Takahashi and Nei [27]. A = 25.00 percent, T/U = 25.00 percent, C = 25.00 percent, 

and G = 25.00 percent are the nucleotide frequencies. A tree topology was automatically calculated for ML 

value estimation. The gamma shape parameter was 139.2826 and the ML for the 18-second computation 

was -14371.636; for the 5-second computation, the ML was -4097.380. A total of 1935 positions and 19 

nucleotide sequences were included in the final dataset for this analysis.  

https://www.ncbi.nlm.nih.gov/nucleotide/KP419194.1?report=genbank&log$=nucltop&blast_rank=30&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/KP762945.1?report=genbank&log$=nucltop&blast_rank=31&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/KP762940.1?report=genbank&log$=nucltop&blast_rank=32&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/KP762933.1?report=genbank&log$=nucltop&blast_rank=33&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/KP762874.1?report=genbank&log$=nucltop&blast_rank=40&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/KM364119.1?report=genbank&log$=nucltop&blast_rank=43&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/KM364075.1?report=genbank&log$=nucltop&blast_rank=44&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/XR_009302357.1?report=genbank&log$=nucltop&blast_rank=1&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/XR_004228347.1?report=genbank&log$=nucltop&blast_rank=3&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/KY887836.1?report=genbank&log$=nucltop&blast_rank=13&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/KY887833.1?report=genbank&log$=nucltop&blast_rank=14&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/KY887822.1?report=genbank&log$=nucltop&blast_rank=16&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/KY887812.1?report=genbank&log$=nucltop&blast_rank=21&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/KY873372.1?report=genbank&log$=nucltop&blast_rank=27&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/KY873354.1?report=genbank&log$=nucltop&blast_rank=28&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/JQ365156.1?report=genbank&log$=nucltop&blast_rank=34&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/EF473894.1?report=genbank&log$=nucltop&blast_rank=30&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/EF473891.1?report=genbank&log$=nucltop&blast_rank=31&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/EF473889.1?report=genbank&log$=nucltop&blast_rank=32&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/EF473888.1?report=genbank&log$=nucltop&blast_rank=33&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/JQ359003.1?report=genbank&log$=nucltop&blast_rank=35&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/JN623531.1?report=genbank&log$=nucltop&blast_rank=36&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/JN623524.1?report=genbank&log$=nucltop&blast_rank=37&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/JN623512.1?report=genbank&log$=nucltop&blast_rank=38&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/JN623511.1?report=genbank&log$=nucltop&blast_rank=39&RID=BPZA2VJU016
https://www.ncbi.nlm.nih.gov/nucleotide/JN623482.1?report=genbank&log$=nucltop&blast_rank=40&RID=BPZA2VJU016


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The compositional distance is correlated with the number of differences between sequences. Non-

uniformity of evolutionary rate differences among sites was modeled by using a discrete gamma 

distribution (+G) with 5 rate categories and by assuming that a certain fraction of sites is evolutionarily 

invariable (+I). Mean evolutionary rates in these categories were 0.88, 0.95, 1.00, 1.04, and 1.12 

substitutions per site. The sites showing a rate < 1 are evolving slower than average, and those with a rate 

> 1 are evolving faster than average. The gamma distribution (ʎ) can be specified by the coefficient of 

variation of the substitution rate (CV), where the smaller the CV, the higher ʎ. Actually, analysis of ML 

results that gave the lowest BIC scores (Bayesian Information Criterion) is considered to describe the best 

substitution pattern (Table 6). For each model, AICc value (Akaike Information Criterion, corrected), ML 

value (lnL), and the number of parameters, including branch lengths are also presented in Table 6. 

Estimates of the gamma shape parameter, fraction of invariant sites, and transition/transversion bias (R) 

are shown for each model. The nucleotide frequencies of the 18s rRNA found in Table 6 and rates of base 

substitutions (r) for each nucleotide pair found in Table 6, with the sum of r-values made equal to 100. The 

difference in base composition bias per site (relative frequencies of the four nucleotides) is in Table 6; also, 

the twenty amino acid residues (amino acid composition) were attained computationally. 

 

Table 4. Different in ML models of the 18s and 5s rRNA gene using one of the most parsimonious trees topology fits. 

No. Blasred 18s  r RNA  sequences ML Blasted 5s sequences ML 

Model BIC AICc lnL R Model BIC AICc lnL R 

1 TN93+G 27737.48 27123.59 -13492.70 1.262 K2+G 8502.82 8207.70 -4066.78 2.670 
2 TN93+G+I 27748.45 27125.67 -13492.74 1.265 T92+G 8511.61 8208.51 -4066.18 2.668 
3 GTR+G 27757.79 27117.21 -13486.51 1.260 K2+G+I 8514.44 8211.34 -4067.60 2.586 
4 GTR+G+I 27768.75 27119.28 -13486.54 1.263 T92+G+I 8523.24 8212.17 -4067.01 2.585 
5 K2+G 27781.00 27202.69 -13536.26 1.231 HKY+G 8526.68 8207.64 -4063.74 2.687 
6 T92+G 27782.15 27194.94 -13531.39 1.240 TN93+G 8526.71 8199.69 -4058.77 2.688 
7 T92+G+I 27793.02 27196.92 -13531.38 1.242 HKY+G+I 8538.56 8211.54 -4064.69 2.600 
8 K2+G+I 27803.93 27216.73 -13542.28 1.492 TN93+G+I 8538.90 8203.91 -4059.87 2.600 
9 HKY+G 27808.17 27203.18 -13533.50 1.259 GTR+G 8550.61 8199.68 -4055.75 2.664 

10 HKY+G+I 27819.04 27205.15 -13533.49 1.261 GTR+G+I 8566.43 8207.53 -4058.67 2.296 
11 JC+G 28021.11 27451.69 -13661.77 0.500 K2+I 8604.27 8309.14 -4117.51 2.287 
12 JC+G+I 28044.68 27466.37 -13668.10 0.500 T92+I 8613.08 8309.98 -4116.92 2.288 
13 GTR+I 28904.97 28264.40 -14060.10 1.078 TN93+I 8625.82 8298.80 -4108.32 2.348 
14 TN93+I 28911.16 28297.27 -14079.55 1.212 JC+G 8626.20 8339.04 -4133.46 0.500 
15 K2+I 28989.98 28411.67 -14140.76 1.050 HKY+I 8628.42 8309.38 -4114.61 2.289 
16 T92+I 28996.19 28408.99 -14138.41 1.053 JC+G+I 8639.04 8343.91 -4134.89 0.500 
17 HKY+I 29024.60 28419.61 -14141.72 1.056 GTR+I 8652.88 8301.94 -4106.88 2.071 
18 JC+I 29202.05 28632.63 -14252.24 0.500 K2 8678.14 8390.98 -4159.43 2.095 
19 GTR 29733.37 29101.69 -14479.75 0.996 T92 8686.72 8391.59 -4158.73 2.096 
20 TN93 29742.70 29137.70 -14500.76 1.113 TN93 8701.04 8381.99 -4150.92 2.098 
21 K2 29823.80 29254.38 -14563.12 1.137 HKY 8702.36 8391.28 -4156.57 2.096 
22 T92 29834.34 29256.03 -14562.94 1.136 JC+I 8717.71 8430.56 -4179.22 0.500 
23 HKY 29860.28 29264.18 -14565.01 1.137 GTR 8725.76 8382.80 -4148.31 2.107 
24 JC 30015.88 29455.36 -14664.60 0.500 JC 8786.54 8507.36 -4218.62 0.500 

Note: LnL = log likelihood, LRT= likelihood ratio test. 

 

3.2. Parsimony Analysis, Sequence Variation and Nucleotide Composition 

The principle of parsimony states that the most straightforward explanation for the data should be 

chosen. Parsimony in phylogenetic analysis refers to the likelihood that a relationship hypothesis that calls 

for the fewest character changes will be accurate. Additionally, Mega computer software supports the 

maximum-parsimony (MP) method of reconstructing phylogenetic trees. Equal branch lengths in the tree, 

consistency of substitution rates between nucleotides, and consistency of rates across nucleotide sites are 

among the very stringent assumptions about the sequence evolution process that parsimony appears to 

entail. Few species in the data, relatively long interior branches, and similar substitution rates among 

lineages (the existence of an approximate molecular clock) are necessary for the practical analysis of data 



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© 2025 Conscientia Beam. All Rights Reserved. 

in order to meet the requirement of equal branch lengths. However, a small amount of evolution is not 

necessary for the method to work. 

 

Table 5. Number of taxa, characters, and nucleotide frequency and substitution matrix of the 18s and 5s r RNA gene of the most parsimonious 
trees topology fits. 

Gene 
N. of 

sequence 
A% T% C% G% 

Variable 
site 

Pars. 
informative site 

Neocleotid frequency 
18s 

33 0.2435 0.2445 0.246 0.2655 
2646 

68 

Neocleotid frequency 5s 19 0.251 0.2525 0.2385 0.258 1935 40 
Substitution rate 18s  3.84 45.6 44.9 4.2   
Substitution rate 5s   12.66 21.4 19.17 13.44   

 

 

3.3. Variation in 18s and 5s Genes rDNA Sequence  

The intraspecific distance of all species is given in Tables 2 and 3. The minimum intraspecific pairwise 

distance variation was observed between T.ni tested sequence and Trigonogenium angulosum (Accession 

number is KM364119.1 and 1865 in length) was 0.547, and the maximum intraspecific distance was 

calculated between T.ni tested sequence and Monocoryna sp. (Accession number KP829165.1 and 1866 in 

length) was 2.7. Similarly, evolutionary genetic divergence for species discrimination estimated between 

sequences refers to the number of base substitutions per site between sequences, which are in Tables 2 and 

3. The maximum interspecific genetic divergence ranged from 98.78 for Meropathus sp. (Accession number 

EF214162.1 and 1791 length) to 228.7 

5 for Rhyzobius hilura (Accession number EF209861.1 and 1823 length). To attain the phylogenetic 

position of T. ni, the phylogenetic tree was constructed, and topology differences were obtained from some 

trees constructed in this study for 18S and 5S blasted sequences in Figures 1 and 2. Details of the gene 

alignment of T. ni from the Egypt population sequenced and some from China with their sequence variable 

sites and parsimony informative sites were observed. The molecular diversity analysis revealed minute 

intraspecific variation with pairwise genetic distance ranging from 0 to 0%. Pattern heterogeneity ranged 

from 1.0 to 1.0. Interspecific genetic divergence between the two groups (14 Chinese sequences and the 

target Egyptian one) was 0.02. The 15-nucleotide sequence alignment result included 391 selected sites, 

including 247 complete (no gaps, no N), 180 variable (72.9% of complete), and 0 informative (0.0% of 

complete). 

 

Table 6. Test of the homogeneity of substitution patterns between sequences. 

Position  18s r RNA 5s rRNA 

A C G T A C G T 

All position 24.218 23.922 24.048 27.810 25.436 22.764 25.121 26.677 
First position  25.084 24.423 23.729 26.761 27.363 20.963 25.822 25.850 
Second position  24.004 23.493 24.620 27.881 24.197 22.585 24.030 29.186 
Third position 23.566 23.849 23.793 28.790 24.746 24.746 25.510 24.996 
Note: Heterogeneous base composition across species was tested with x2 test statistic. 

Base composition broken down by codon position.  

 

Molecular phylogenetics of lepidopteran datasets created using 18S rRNA nucleotide alignments produced by 

ClustalW between the main Noctuidae lineages, Figure 1. The tree with the highest log likelihood (-44601.14) is 

shown. Initial trees for the heuristic search were obtained automatically by applying Neighbor-Join and BioNJ 

algorithms to a matrix of pairwise distances estimated using the Tamura-Nei model, and then selecting the topology 

with superior log likelihood value. This analysis involved 43 nucleotide sequences of familiar (Agricultural pests) and 

total of 2083 positions in the final dataset. The nucleotide frequencies are A = 25.00%, T/U = 25.00%, C = 25.00%, 

and G = 25.00%. The estimated Transition/Transversion bias (R) is 0.52. BIC=90076.5, AIC=89333.6. And 

https://www.ncbi.nlm.nih.gov/nucleotide/KM364119.1?report=genbank&log$=nucltop&blast_rank=43&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/KP829165.1?report=genbank&log$=nucltop&blast_rank=2&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/EF214162.1?report=genbank&log$=nucltop&blast_rank=22&RID=BPYCMG8X016
https://www.ncbi.nlm.nih.gov/nucleotide/EF209861.1?report=genbank&log$=nucltop&blast_rank=9&RID=9YTPHZFF013


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confidence intervals on phylogenies by the number of bootstrap replicates with 10,000 [28] estimated and tree 

constructed based on the protein-coding amino acid sequences (Figure 3, 4). Nonetheless molecular phylogeny of 5s 

alignment with different orders analysis involved 28 nucleotide sequences and a total of 607 positions. InL=2813.6, 

BIC=5738.8 and BIC= 6084.3. Synonymous and non-synonymous substitution (Silent and amino acid alteration) 

were also calculated according to Nei and Gojobori [29]. It is obtained by counting silent and amino acid-altering 

nucleotide differences. Where the silent amino acid substitution is much higher than the altered and looks similar for 

different genes. The small value refers to there is no more than one nucleotide difference between each pair of 

homologous codons, but the high value refers to the differences is complicated. 

Another alignment with some members of the subfamily Plusiinae 18s rRNA sequences and phylogenetic analysis 

by the ML method was done to generate the evolutionary history. Results indicate that the topology was similar and 

the pairwise genetic distance is the same Figure 5. Many literature producers’ efforts have been made regarding the 

subject of phylogeny as well as insect taxonomy, insect detoxifications, and important insect molecules like specific 

target function encoding proteins such as [30, 31]. Many scientists have proposed some high-quality T. ni genome 

assembly, which contains 14,384 protein-coding genes of the assembly across 31 chromosomes, as Chen et al. [32] and 

Talsania et al. [33]. 



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Table 7. The alignment of many insect orders with the species name and accession number indicates varying degrees of homogeneity, distance, and divergence of substitution. 

N. Species name Order  Family E value % 
Identity 

Length Accession n Dist. Homo Div. 

1 Aedes_aegypti Diptera Culicidae  4.0E-38 82.81 825 HE613439 0.036 1.000 0.000 
2 Aphis_gossypii Hemiptera  Aphidae  1.0E-40 96.43 1163 KF018922 0.036 1.000 0.000 
3 Bemisia_tabaci Homoptera Aleyrodidae  0.009 28.57 506 JQ995259 0.153 1.000 0.000 
4 Bombyx_mori Lepidoptera  Bombicidae  5.0E-43 82.19 1124 KF982847 2.629 0.014 1.871 
5 Cephus_pygmaeuss Coleoptera Cephidae  2.0E-46 98.44 1860 GQ410588 3.357 0.006 2.629 
6 Chilo_suppressalis Lepidoptera Crambidae  1.0E-41 80.82 1914 GQ265912 0.017 1.000 0.000 
7 Chrysoperla_carnea Neuroptera Chrysopidae  2.0E-46 98.44 989 KT204369 0.031 1.000 0.000 
8 Drosophila_melanogaster Diptera Drosophilidae  2.0E-36 79.17 1994 NR_133559 0.031 1.000 0.000 
9 Eniclases_pseudoluteolus Ccoleoptera  Lycidae  8.0E-46 96.88 221 MG871684 0.031 1.000 0.000 
10 Frankliniella_occidentalis Thysanoptera  Thyripidae  2.0E-43 90.91 228 KC512959 0.352 1.000 0.000 
11 Helicoverpa_zea Lepidoptera Noctuidae  4 81.6 21 KT946004 3.065 0.006 2.324 
12 Heliothis_subflexa Lepidoptera  Noctuidae  4 81,5 21 KT946000 0.368 1.000 0.000 
13 Hypera_postica Coleoptera Curculionidae  1.0E-43 89.39 1609 AF389058 0.866 0.306 0.105 
14 Locusta_migratoria Orthoptera Acrididae  1.0E-44 92.42 1893 KM853191 0.085 1.000 0.000 
15 Lycorma_delicatula Hemiptera Erebidae  4.0E-44 95.08 230 KC413787 0.425 1.000 0.000 
16 Macroglenes sp. Hymenoptera  Pirenidae  1E-42 95.31 678 JN623447.1 0.425 1.000 0.000 
17 Musca_domestica Diptera  Muscidae  3E-34 81.25 1943 KC177313 3.980 0.000 3.251 
18 Nala_lividipes Dermaptera  Labidoridae  4 69.6 55 AY707362 5.385 0.000 4.623 
19 Nasonia_vitripennis Hymenoptera   Pteromalidae  2E-11 100 573 MF583329 1.494 0.106 0.749 
20 Neohermes_californicus Megaloptera Corydalidae  1E-47 100 223 CP092098.1 5.235 0.000 4.494 
21 Neoneuromus_ignobilis Megaloptera  Corydalidae  1E-47 100 223 CP092098.1 1.980 0.046 1.235 
22 Nilaparvata_lugen Hemipteran  Delphacidae  4 57.6 135 JN662398 1.729 0.098 0.947 
23 Nomada_panzeri Hymenoptera  Apidae  0.002 100 784 KF512686 1.729 0.078 0.996 
24 Ostrinia_nubilalis Lepidoptera  Crambidae  4 82.4 17 X576726 1.833 0.068 1.059 
25 Tuta absoluta  Lepidoptera Gelichidae 4 68.2 47 MH644412 1.761 0.052 1.041 
26 Parainocellia bicolor Raphidoptera  Inocellidae  1E-47 100 223 EU815245 0.049 1.000 0.000 
27 Phthorimaea_operculella Lepidoptera Gelichidae  4 54.5 99 OL655414 0.757 0.388 0.008 
28 Phytoseiulus_persimilis Acari  Phytosidae  4 59.5 42 U39916 3.429 0.004 2.704 

29 Pieris_brassicae Lepidoptera  Pieridae  4e-46 83.56% 248 XR_006754962 1.243 0.178 0.506 
30 Pieris_napi Lepidoptera Pieridae  1E-44 92.42 1893 XR_007118579 1.640 0.094 0.879 
31 Planococcus_ficus Hemipteran  Coccoidae  4 56.2 80 MF952600 1.826 0.058 1.085 
32 Plutella_xylostella Lepidoptera Plutillidae  4 66.7 33 JN410814 0.684 1.000 0.000 
33 Pteromalus_albipennis Hymenoptera  Pteromalidae  4 68,2 44 KC008498 1.798 0.084 1.028 
34 Pulvinaria_psidii Hemiptera Coccoidae  1E-15 96 139 JQ651034 1.239 0.178 0.494 
35 Rodolia_cardinalis Coleopteran  Coccinillidae     GU073726 1.437 0.146 0.684 

https://www.ncbi.nlm.nih.gov/nucleotide/CP092098.1?report=genbank&log$=nucltop&blast_rank=8&RID=9YTPHZFF013
https://www.ncbi.nlm.nih.gov/nucleotide/CP092098.1?report=genbank&log$=nucltop&blast_rank=8&RID=9YTPHZFF013


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N. Species name Order  Family E value % 
Identity 

Length Accession n Dist. Homo Div. 

36 Signiphora_dipterophaga Hymenoptera  Calcidoidae  2E-45 95.31 1901 N623482 3.644 0.004 2.899 
37 Spodoptera_exigua Lepidoptera  Noctuidae     FJ041111 1.081 0.226 0.340 
38 Spodoptera_litura Lepidotera  Noctuidae     JX041469 4.393 0.000 3.640 
39 Tenebrio_molitor Coleoptera  Tenebrionidae  2E-45 95.31 2083 X07801 1.408 0.130 0.614 
41 Tetranychus_urticae Acari  Tetranychidae  4 74.3 27 KP642052 1.413 0.150 0.652 
42 Thrips_tabaci Thysanoptera Thripidae  2.0 20.2 1545 KM877307 3.862 0.002 3.097 
43 Chinese_Trichoplusia_ni Lepidoptera  Noctuidae  2E-46 94.15 247 KY514086.1 2.870 0.010 2.105 



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Table 7 Different levels of homogeneity, distance, and divergence of substitution rate are indicated by the 

alignment of many insect orders with the species name and accession number. 

 

 
Figure 1. Showed alignment of the most identical sequence to the attained sequence of T. ni 18S rRNA protein. 

 

 
Figure 2. Phylogram characterize the phylogenetic relationships among major evolutionary lineages of T. ni were investigated using partial 
sequences of nuclear DNA, 18S. Numbers above branches represent bootstrap values; numbers below branches are posterior probability values. 

 



Current Research in Agricultural Sciences, 2025, 12(1): 35-48 

 

 
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Figure 3. Phylogram characterize the phylogenetic relationships among major evolutionary lineages 
of T. ni were investigated using partial sequences of nuclear DNA, 5S ribosomal protein. Numbers 
above branches represent bootstrap values; numbers below branches are posterior probability values. 

 

 
Figure 4. Phylogram of 18s rRNA of Egyptian T.ni sequence aligned with other insect orders best ML tree of 
phylogenetic analysis. Numbers above branches represent bootstrap values; numbers below branches are posterior 
probability values. 



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Figure 5. Aligned translated sequence of some Chinese T. ni with Egyptian T.ni sequence. 

 

Figure 6. The best ML tree of phylogenetic analysis shows the phylogram of the Egyptian T . ni sequence's 5s 

rRNA aligned with other insect orders. Bootstrap values are represented by numbers above branches, while posterior 

probability values are represented by numbers below branches. 

 

 
Figure 6. Phylogram of 5s rRNA of Egyptian T.ni sequence aligned with other insect orders best ML tree of phylogenetic 
analysis. Numbers above branches represent bootstrap values; numbers below branches are posterior probability values 

 

4. CONCLUSIONS 

The main goal of this study is to realize the phylogenetic relationships among T. ni species and others 

and between evolutionarily closer clades based on 18S rRNA gene markers. From the results, it can be 

concluded that the 18S rRNA gene is useful for differentiation between a variety of insects and the 

agricultural economic moth group. The phylogenetic analysis tool exhibits ease of data handling and 

provides a clear illustration of this subject of molecular research, depending on the structures, the position 

of substitutions, and the necessity of aligning sequences, which are characters determining similarity and 

homology. 

 

 

 

 



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© 2025 Conscientia Beam. All Rights Reserved. 

Funding: This research is supported by Central Agricultural Pesticide Laboratory, Agriculture Research 
Center, Egypt 
Institutional Review Board Statement: The Ethical Committee of Cairo University, Egypt has granted 
DNA lab work approval for this study 
Transparency: The author states that the manuscript is honest, truthful, and transparent, that no key aspects 
of the investigation have been omitted, and that any differences from the study as planned have been clarified. 
This study followed all writing ethics. 
Competing Interests: The author declares that there are no conflicts of interests regarding the publication 
of this paper. 

 

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answerable for any loss, damage or liability etc. caused in relation to/arising out of the use of the content. 

 

https://doi.org/10.1016/s1055-7903(03)00069-1
https://doi.org/10.1093/nar/gkab1112
https://doi.org/10.1128/aem.53.10.2394-2396.1987
https://doi.org/10.1093/nar/22.22.4673
https://doi.org/10.1093/molbev/mst197
https://doi.org/10.1093/molbev/msn067
https://doi.org/10.1093/oxfordjournals.molbev.a040317
https://doi.org/10.1093/molbev/msr121
https://doi.org/10.1093/oxfordjournals.molbev.a026408
https://doi.org/10.1214/ss/1063994980
https://doi.org/10.1093/oxfordjournals.molbev.a040410
https://doi.org/10.21548/44-1-5945
https://doi.org/10.3390/ani13132185

