Electron microscopy for Tomato chlorosis crinicirus (ToCV) particles, histopathological effects and bioinformatics prediction of viral proteins

Electron microscopy for Tomato chlorosis crinicirus (ToCV) particles, histopathological effects and bioinformatics prediction of viral proteins | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Electron microscopy for Tomato chlorosis crinicirus (ToCV) particles, histopathological effects and bioinformatics prediction of viral proteins Wael S. El-Araby, Khaled A. El-Dougdoug, Badawy A. Othman, Allam A. Megahed This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6985991/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The field trials for detection of ToCV on tomato yield in Egypt should be assess by using protein prediction results for the development of specific ToCV antisera kits. The current study aims to characterize the morphology of ToCV particles by investigating their infection effects on tomato plants histopathology and and predicting viral proteins using bioinformatics. Results ToCV particles exhibit a filamentous, flexible structure measuring approximately 850 nm, as determined using the tissue dip preparation method. Tomato leaves infected with ToCV displayed significant cytopathic effects on tissue and cells. The mesophyll tissue cells had thin cell walls, distorted membranes, and deformed nuclei, chloroplasts, and mitochondria. They also had relatively tiny intercellular spaces. Ultrathin sections revealed that infected tomato leaf cells exhibited deformed cell walls and organelles, including nucleus, chloroplasts, mitochondria, and large vacuoles. The cell wall showed irregular sedimentation, while mitochondria had a degenerated envelope. The nucleus appeared small and damaged. Cytoplasmic alterations included abnormal chloroplasts, mitochondria, and nuclei, as well as overall cellular abnormalities. ToCV infection caused leaf chlorosis, with varying degrees of tissue and cellular alterations. Healthy leaves exhibited a flat lamina and concave petioles. Gene prediction of ToCV-(+) ssRNA genomic segments genome involved identifying sub-sequences of bases that encode proteins and determining the percentage of trees in the involved taxa cluster. Conclusion The first tree (s) specific to the guiding search were recorded automatically using the Neighbor-Joining method via BioNJ algorithms, applying a matrix of pairwise distances calculated using the Maximum Composite Likelihood (MCL) method. The topology was then refined by selecting the structure with the highest log-likelihood score. ToCV tomato histopathological electron microscopy protein prediction bioinformatics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Tomato ( Lycopersicon esculentum L.) is one of the most economically important vegetable crops grown in Egypt and worldwide. Its global production was approximately 180.8 million tons in 2019, generating an income of 93.9 billion US dollars in 2018 [ 1 ]. Tomatoes rank as the sixth most important vegetable crop after potatoes, with a current global production of about 6,245,787 million tons. They are a rich source of essential micro- and macronutrients vital to human health [ 2 ]. Tomato plants are susceptible to several phytopathogens, including viruses, virus-like particles (Viroids), virus-like organisms (Phytoplasma), bacteria, nematodes and fungi, all of which significantly impact yield and quality production [ 3 ]. Among these, viruses are major constraints to tomato production, with more than 45 viral diseases reported in tomatoes. Virus transmission varies depending on the species and can occur through mechanical wounds, biological vectors, or both [ 4 ]. The most common viruses affecting tomato plants in Egypt include Tomato mosaic virus (ToMV) [ 5 , 6 ], Tomato spotted wilt virus (TSWV) [ 7 ], Tomato ring spot virus (ToRSV) [ 8 ], Tomato yellow leaf curl virus (TYLCV) [ 9 ], Tomato bushy stunt virus (ToBSV) [ 10 ], and ToCV [ 11 , 12 ]. ToCV belongs to the genus Crinivirus within the family Closteroviridae and is transmitted by whiteflies. ToCV particles are filamentous, measuring approximately 850 nm in length [ 13 – 15 ]. Since its initial discovery in the United States in 1996, ToCV has been detected in 38 other countries and territories [ 13 ], including Taiwan [ 16 ], Portugal [ 17 ], Taiwan [ 16 ], Spain [ 18 ], Greece [ 19 ], Italy [ 20 ], Puerto Rico (USA) [ 21 ], South Africa [ 22 ], Morocco [ 23 ], Réunion (FR) [ 24 ], France [ 25 ], Cyprus [ 26 ], Lebanon [ 27 ], Mexico [ 28 ], Hungary [ 29 ], Mayotte (FR) [ 30 ], China [ 31 ], The Netherlands [ 32 ], Sudan [ 33 ], Uruguay [ 34 ], Korea [ 15 ], Brazil [ 35 ], Pakistan [ 36 ], Cuba [ 37 ], Kenya [ 38 ], Turkey [ 39 ], Panama [ 40 ], Costa Rica [ 41 ], Nigeria [ 42 ], Mauritius [ 43 ], Tunisia [ 44 ], Japan [ 45 ], Jordan [ 46 ], Indonesia [ 47 ], Saudi Arabia [ 48 ], the United Kingdom [ 49 ], and Egypt [ 11 , 12 ]. The symptoms of ToCV infection in tomatoes include interveinal chlorotic yellow patches, which initially appear on the lower leaves and progressively spread to the upper foliage. Bronzing and reddish spots are often observed within the yellow patches. Infected leaves become thickened and brittle, with slightly curled upward margins. Although ToCV-infected tomato plants may not always exhibit clear symptoms, fruit ripening is significantly delayed, and severe flower abortion occurs, leading to economic losses [ 50 ]. In artificially inoculated Nicotiana clevelandii plants, phloem companion cells exhibit an increase in cytoplasmic vesicles, where virus particles are frequently observed. Ultrastructural studies later in the infection process reveal cytoplasmic and organelle degeneration in phloem companion cells, with virus particles aggregating into large bundles [ 51 ]. ToCV has two biotypes (A and B) with a bipartite (+) ssRNA, with RNA1 measuring 8595 nt and RNA2 measuring 8247 nt, containing four and nine ORFs, respectively [13–15). RNA1 encodes proteins involved in viral replication and gene silencing suppression, while RNA2 encodes proteins associated with whitefly transmission, membrane attachment, virus encapsidation, gene silencing suppression, and cell-to-cell movement. ORF1a encodes a multifunctional protein with helicase, methyltransferase, and protease domains, while ORF1b encodes an RNA-dependent RNA polymerase (RdRp) [ 52 ]. ORF2 encodes the p22 protein, which is a potent RNA silencing suppressor with prolonged local activity [ 53 ]. Bioinformatics, or computational biology, is an evolving field that utilizes next-generation sequencing for biological data analysis and interpretation. Structural bioinformatics focuses on analyzing and predicting the three-dimensional structures of biological macromolecules using experimentally solved structures and computational models [ 54 ]. Sequence analysis in bioinformatics presents challenges due to high computational costs associated with deep learning models, which rely on complex network architectures and large model sizes [ 55 ]. Protein tertiary (3D) structure, determined by folding of secondary structures, is crucial for protein function. Assessing the quality of predicted models is essential for further functional research [ 56 ]. A motif is a short DNA or protein sequence that plays a critical role in the biological function of the sequence in which it resides [ 57 ]. Computational methods have been developed to identify, characterize, and search for sequence motifs and domains in proteins. These conserved regions are essential for protein classification and functional annotation [ 58 ]. Domain and motif prediction algorithms are instrumental in identifying remote homologs in databases, with PSI-BLAST being a widely used tool for profiles-based database searches [ 59 ]. The Conserved Domain Database (CDD) creates alignment models of sequence fragments, aligning them with protein 3D structure boundaries, modeling conserved cores, and annotating functional features [ 60 ]. Motif databases classify proteins, assign functions, and identify structural relationships. Some databases use regular expressions, such as the Protein Sites and Patterns Database (PROSITE) and Emotif, while others, such as the Protein Fingerprint Database (PRINTS), Aligned Blocks of Conserved Sequences (BLOCKS), Protein Families Database (Pfam), Protein Domain Database (ProDom), and Simple Modular Architecture Research Tool (SMART), rely on profile-based methods [ 61 ]. Protein information is categorized into primary, composite, secondary, and pattern databases, each addressing different aspects to enhance structure prediction strategies [ 62 ]. Structure prediction bridges the gap between available sequences and experimentally determined structures, aiding in understanding of protein functions in medicine, pharmacology, and biotechnology through computational approaches [ 63 ]. The current study aims to characterize ToCV particles morphology by investigating its effects on tomato plant histopathology. Additionally, the study involves gene prediction of the ToCV genome sequence by identifying sub-sequences of nucleotide bases that encode proteins. Materials and methods Virus isolate The pure single isolate of ToCV was obtained from [ 1 ] and maintained in tomato plants ( S. lycopersicum cv. Aliasa F1) as a ToCV-propagative host in the Virology Laboratory at Agric. Microbiol. Department sited in Faculty of Agriculture of Ain Shams University in Egypt for further studies. Determination of virus morphology A 10 µL droplet of the supernatant from clarified infectious sap was prepared by low-speed centrifugation at 6000 rpm for 15 min. The sample was placed on a carbon-coated nickel grid, stained with 2% uranyl acetate (pH 7.0) for 30 min, and directly examined using a JOEL JEM-1400 transmission electron microscope (TEM) at an accelerating voltage of 80 kV at the Fungal Center, Al-Azhar University, Cairo. Light microscopy of ToCV cytopathic effects Leaflet middle lamina sections (1 cm²), including the midrib, were collected from five ToCV-infected tomato leaves and five healthy (control) leaves. These samples were excised from infected foliage at the seventh nodes and from healthy leaves at approximately 21 days of age. All samples were fixed and preserved in formalin-acetic acid (FAA) and 70% ethanol following the protocol described by [ 64 ]. The prepared sections were examined under a light microscope. Transmission electron microscopy of ToCV cytopathic effects Five leaf samples (1 mm² each) from ToCV-infected and five from healthy (control) tomato plants were processed for ultrathin sectioning following the standard protocol described by [ 65 ]. Each sample was fixed in 2% glutraldhyde in 0.1 M sodium cacodylate buffer (pH 7.2) and subjected to vacuum treatment for 1–4 minutes every 15 minutes over 2 hours on ice. Before vacuum treatment, floating samples were carefully submerged using pointed metal pokers. The samples were then rinsed in 0.1 M sodium cacodylate buffer (pH 7.2) for 45 minutes, with buffer changes at 15-minute and 30-minute intervals. Further fixation was performed using 1% osmium tetroxide in sodium cacodylate buffer under intermittent vacuum treatment and poking for 1.5 hours, followed by additional rinsing in sodium cacodylate buffer. The samples were dehydrated through a graded ethanol series (35%, 50%, 70%, 80%, 95%, and two rounds of 100%) for 60 minutes each. Ultrathin sections (90 nm thick) were cut using a Leica EM-UC6 ultramicrotome and mounted on copper grids (400 mesh). Sections were double-stained with 2% uranyl acetate for 10 minutes, followed by lead citrate staining for 5 minutes, as described by Nasr-Eldin et al. , (2018). The sections were examined using a JEOL JEM-1400 TEM at an accelerating voltage of 75 kV at the Electron Microscope Unit, Al-Azhar University, Cairo. Gene prediction The nucleotide sequence of ToCV (GenBank accession code ON951644.1) [ 1 ] was analyzed bioinformatically for protein prediction using GeneMark.hmm (version 3.25) program. The generalized Viterbi algorithm was used to determine the most probable coding/non-coding sequences. To evaluate the accuracy for GeneMarkS-2, the predicted genes were assessed using Clusters of Orthologous Groups(COG) classification, proteomics methods, and N-terminal protein sequencing [ 67 ]. The statistical significance for the score and length of an open reading frame (ORF) was calculated for putative genes using the Hidden Markov Model (HMM). The scoring system assessed similarity based on a substitution matrix and gap penalty, with global and local alignment strategies employing the dot matrix, dynamic programming, or word optimization. The Needleman-Wunsch and Smith-Waterman global pairwise alignment algorithms were used for database similarity searches and multiple sequence alignment. Multiple sequence alignments were conducted using BIOEDIT 7.2 software, while Clustal Omega was used for phylogenetic analysis. Predicted genes were analyzed using Neighbor-joining, Maximum Likelihood, Minimum-Evolution, and Maximum Parsimony methods [ 68 ]. Domain prediction The statistical significance for the score and length of an open reading frame (ORF) was calculated for putative genes using the Hidden Markov Model (HMM). The scoring system assessed similarity based on a substitution matrix and gap penalty, with global and local alignment strategies employing the dot matrix, dynamic programming, or word optimization. The Needleman-Wunsch and Smith-Waterman global pairwise alignment algorithms were used for database similarity searches and multiple sequence alignment. Multiple sequence alignments were conducted using BIOEDIT 7.2 software, while Clustal Omega was used for phylogenetic analysis. Predicted genes were analyzed using Neighbor-joining, Maximum Likelihood, Minimum-Evolution, and Maximum Parsimony methods [ 69 ]. Statistical analysis Variance analysis and mean separation were performed following the methodologies described by [ 70 , 71 ]. Results Virus morphology ToCV particles exhibit helical symmetry and a flexible filamentous shape, measuring approximately 850 nm in length at 80000X magnification. These characteristics were determined by transmission electron microscopy using the tissue-dip preparation method (Fig. 1 ). Cytopathological effects in light microscopy Tomato plants infected with Tomato chlorosis virus ( ToCV ), with tomato as the primary host, exhibited varying degrees of reaction, primarily manifesting as leaf chlorosis. Cytopathic alterations in leaf tissues and cells were analyzed to assess the infection’s impact. Inoculated tomato plants showed significant reductions in leaf lamina characteristics (Table 1 ). The upper epidermis (16.76%) consisted of tubular parenchyma cells, while palisade parenchyma cells (49.15%) were cylindrical and formed two well-filled layers, unlike in healthy plants. Additionally, the spongy parenchyma was larger, consisting of two to three layers with a substantial number of intercellular spaces, which were reduced by 36.55% (Fig. 2 B). Histological sections revealed concave lamina formation, compacted upper and lower epidermis, and smaller cells compared to healthy tissues. Many stomata were observed on the lower epidermis, and multicellular hairs were arranged in 2–3 rows. Furthermore, mesophyll cells displayed multiple layers with no detectable intercellular spaces (Fig. 2 B). A significant reduction in petiole characteristics was also observed in infected tomato plants (Table 1 ). In contrast, petiole thickness increased by 21.97%, including epidermal thickness (33.33%), collenchyma (40.79%), parenchyma (29.57%), fibers (36.00%), vascular tissue, xylem number (19.26%), xylem thickness (26.53%), vascular bundle number (16.13%), xylem diameter (12.50%), phloem thickness inside (57.38%), phloem thickness outside (54.35%), and pith diameter (42.43%) (Fig. 3 B). Compared to healthy leaves, infected leaves exhibited concave petioles in light microscopy sections (Fig. 3 B). In contrast, a light micrograph of healthy tomato leaves revealed a nearly flat lamina (Fig. 2 A). The upper and lower epidermal cells were barrel-shaped, with the lower epidermal cells being slightly larger. The thin-walled epidermal cells contained numerous hairs. Table 1 Anatomical parameters of transverse sections of lamina and petiole of healthy and ToCV infected leaf infected tomato plant. Anatomical parameters Healthy Infected ** Reduction is relative to ToCV infection% Tomato leave lamina Hairs Length (um * ) 182.00 165.00 a 9.34 a Number Upper 2.00 3.00 b -50.00 b Lower 3.00 4.00 b -33.33 b Cockatiel thickness (um) Upper 12.40 7.50 c 39.52 c Lower 10.50 6.40 c 39.05 c Upper epidermis (um) 5.18 4.15 a 16.76 a Lower epidermis (um) 3.12 10.20 b 17.03 b Palisade tissue thickness (um) 70.60 35.90 c 49.15 c Spongy tissue thickness (um) 67.30 42.70 c 36.55 c Vascular tissue thickness (um) 475.00 424.00 b 10.74 b Vascular bundle diameter Length (um) 275.00 250.00 b 9.09 b Width (um) 262.00 235.00 b 10.31 b Xylem Thickness (um) 115.00 95.00 c 17.39 c Number of vascular 52.00 42.00 b 19.23 b Diameter of vascular (um) 38.00 32.00 b 15.79 b Phloem Thickness inside (um) 102.00 45.00 c 55.88 c Thickness outside (um) 95.00 32.00 b 66.32 b Fiber thickness (um) 135.00 124.00 b 8.15 b Main vein thickness (um) 1325.00 117.40 c 91.14 c Blade thickness (um) 645.00 472.00 a 26.82 a Tomato leave petiole Cockatiel thickness (um) 13.20 10.30 b 21.97 b Epidermis thickness (um) 39.00 26.00 c 33.33 c Collenchyma thickness (um) 76.00 45.00 b 40.79 b Parenchyma thickness (um) 345.00 243.00 a 29.57 a Fiber thickness (um) 75.00 48.00 b 36.00 b Vascular tissue Xylem Number 675.00 545.00 c 19.26 c Thickness (um) 98.00 72.00 c 26.53 c Number of vascular 62.00 52.00 c 16.13 c Diameter of vascular (um) 48.00 42.00 c 12.50 c Phloem Thickness inside (um) 122.00 52.00 c 57.38 c Thickness outside (um) 92.00 42.00 c 54.35 c Pith diameter (um) 1242.00 715.00 c 42.43 c Cross-section diameter (um) 4275.00 3325.00 a 22.22 a Mean values within columns followed by the same letter are not significantly different at P ≤ 0.05. * um = Micrometer. ** Reduction % =Healthyـinfected/healthy X 100 Cytopathological effects in electron microscopy Ultrathin of ToCV-infected tomato leaf tissues revealed extensive destruction of mesophyll and palisade cells ( Fig. 5 B, C). Mesophyll and palisade cells appeared rounded with relatively large intercellular spaces (Fig. 5 A, B, C). Some infected cells exhibited deformed cell walls and damaged organelles, including nuclei, chloroplasts, mitochondria, and vacuoles (Fig. 5 A, B, C). The cell wall showed irregular sedimentation, aberrations, and degradation (Fig. 5 B, C). Mitochondria exhibited a degenerated envelope, with disrupted cristae and membranes (Fig. 5 F, G). The nucleus appeared small or destructed with dark-stain chromatin aggregates and a deformed (Fig. 5 A, B, H). Additional abnormalities included monomorphic cells, ruptured cytoplasmic and tonoplast membranes, and space formation (Fig. 5 A). Plasmatic induction of the cytoplasm resulted in space formation between the cell wall and cytoplasmic membrane (Fig. 5 A), along with the emergence of plasmodesmata (Fig. 5 B). Electron micrographs showed various cytoplasmic alterations, including a high number of abnormal chloroplasts, mitochondria, nuclei, and other cellular anomalies. Virus particles were observed surrounding the nucleus and within the cytoplasm (Fig. 5 B, C, D, E, F, G, H, K). The upper and lower epidermal cells were of similar size, but the lower epidermis appeared distorted. The sub-epidermal parenchyma is made up of 1 layer specific to compacted cells that is thicker than those in healthy plants. The mesophyll tissue presented to be abundant in chloroplasts, and a group of paranchymal and chlorenchymal cells had holes. In contrast to healthy skin, the top epidermis is made up of tubular paranchyma cells that are coated in a thin layer of cuticle. Tomato cells infected with ToCV revealed various cytoplasmic alterations, including the existence of a significant number of aberrant chloroplasts, mitochondria, nuclei, and cellular abnormalities. In contrast, electron micrographs of ultrathin sections from healthy leaf cells showed normal mesophyll cells with relatively small or absent intercellular spaces, containing intact organelles such as the cell wall, nucleus, nucleolus, chloroplasts, mitochondria, and vacuole (Fig. 4 ). The mesophyll cell structure remained well-preserved, with normal nuclei and mitochondria. However, ToCV-infected cells exhibited distorted, bulging chloroplasts with a disrupted membrane system. Gene prediction and proteomic analysis Gene prediction of the ToCV (+) ssRNA genome involved identifying sub-sequences encoding proteins and analyzing their phylogenetic clustering. The RNA-1 segment was 8,530 nucleotides (nt) long and contained four open reading frames (ORFs), along with a 302-nt and a 191-nt non-coding region at the 3′ end. ORF-1a was 5,838 nt long (1,945 amino acids), while ORF-1b spanned nucleotides 6,212–7,657. RNA-2 was 8,220 nt long, containing eight ORFs and a 214-nt 3′ untranslated region. ORF-2 was located at nucleotides 732–2,396, ORF-3 at 2,406–2,609, and ORF-4 at 2,561–4,114. ORF-5 (4,096–4,332 nt) encoded a putative 9-kDa protein (P9), while ORF-6 (4,332–5,105 nt) encoded a 29-kDa coat protein (Fig. 6 , Table 2 ). Table 2 Database of identification genes and proteins in NCBI of the complete nucleotide sequences of the isolated ToCV genome. Id ORF name Nucleotide length Protein id Protein length Domain1 Domain2 RNA1 LC775118 ORF1a 5838 BEL36645.1 1945 Viral methyltransferase (pfam01660) Viral_helicase1 LC775237.1 ORF1b 1446 BEO88560.1 481 RNA-dependent RNA polymerase (PF00978.24) - LC775279.1 P22 582 BEO88671.1 193 No domain - LC775280.1 P5 156 BEO88672.1 51 No domain - RNA2 LC778246.1 Hsp70 1664 BES66841.1 208 Hsp70 (PF00012.23) - LC778247.1 P8 204 BES66842.1 67 No domain - LC778248.1 P59 1554 BES66843.1 517 Viral_Hsp90 (PF03225.17) - LC778251.1 P9 237 BES66844.1 78 No domain - LC778252.1 WSE 774 BES66845.1 257 Closter_coat (PF01785.20) - LC778303.1 ORF7 2010 BES66846.1 669 No domain - LC778304 P27 699 BES66847.1 232 No domain - LC778305.1 P7 198 BES66848.1 65 NO domain - * The bipartite genome of the ToCV isolate was classified into three clade groups: Clade 1 (red), Clade 2 (blue), and Clade 3 (green). The two RNA segments were associated with distinct clades corresponding to J1, JN2, and YG isolates (purple) (Fig. 6 ). On RNA-1, four ORFs were identified, including P22, which functions as a gene silencing suppressor, replication-associated proteins, and P6, a putative protein with a transmembrane domain. RNA-2 encodes CP (coat protein), Hsp70h (heat shock protein homolog 70), CPm (minor coat protein), and additional putative proteins P8, P9, P27, and P7. Gene prediction was conducted using intrinsic and extrinsic methods to identify sub-sequences encoding proteins. Intrinsic methods differentiated between exons and introns, while extrinsic methods identified similarities between genomic sequences and proteins. Several software programs predicted gene sequences with over 80% accuracy. CRITICA, introduced by Badger and Olsen, combined computational prediction with experimental validation. AUGUSTUS, based on a Hidden Markov Model, improved accuracy for segmented genomic sequences. JIGSAW automated gene structure prediction, achieving 92% sensitivity and 72% specificity. Molecular phylogenetic analysis of the predicted ToCV amino acid sequence (accession number WEG90037.1) was conducted using the National Center for Biotechnology Information (NCBI) (Fig. 7 ). Discussion The Tomato chlorosis virus (ToCV) particles are filamentous, measuring approximately 850 nm in length at 80,000X magnification as observed through transmission electron microscopy. ToCV belongs to the Closteroviridae family, which includes the genus Crinivirus . Members of this genus are transmitted by whiteflies and possess a bipartite genome consisting two (+) ssRNA genomic segments, each independently encapsidated in filamentous particles [14]. Tomato leaves infected with ToCV exhibited significant cytopathic effects on tissue and cells as observed in light microscopy. The mesophyll tissues of infected leaves displayed thin cell walls, few chlorenchyma-free cells, distorted membranes, and deformed organelles, including nuclei, chloroplasts, and mitochondria, compared to healthy tissues. Additionally, the intercellular spaces were relatively small. Infected leaves also exhibited concave petioles in light microscopy images, in contrast to the nearly flat lamina of healthy tomato leaves. In healthy leaves, the lower epidermal cells were slightly larger than the upper epidermal cells. The thin-walled epidermal cells, which contained numerous hairs, were also more structured in healthy samples. Ultrathin sections of ToCV-infected tomato leaf tissues examined under an electron microscope revealed severe cytopathological effects. Some mesophyll and palisade cells exhibited deformed organelles, including the cell wall, nucleus, chloroplasts, mitochondria, and large vacuoles. Mitochondria displayed a degenerated envelope, with disrupted cristae and membranes. Additional abnormalities included monomorphic cells, ruptured cytoplasmic and tonoplast membranes, and space formation. Infected tomato cells also showed various cytoplasmic alterations, including a significant number of aberrant chloroplasts, mitochondria, nuclei, and other cellular abnormalities. Our findings align with those of [14, 51] whose reported similar cytopathic effects in ToCV-infected leaves such as chloroplast deformation and increased cytoplasmic vesicles. Electron micrograph of ultrathin sections from healthy leaf cells displayed normal mesophyll cells with relatively narrow or absent intercellular spaces, containing intact organelles such as the cell wall, nucleus, nucleolus, chloroplasts, mitochondria, and vacuole. In contrast, ToCV-infected tomato plants exhibited a reduction in petiole characteristics. These observations are consistent with findings from previous research [ 72 , 73 ]; which documented cytological deformations in chloroplasts following infections with with Citrus cachexia viroid (Ccavd) and Citrus exocortis viroid (CEVd) or Cucumber mosaic virus (CMV). Infected mesophyll cells showed structural degradation, and while organelles such as nuclei and mitochondria appeared relatively intact, chloroplasts were distorted and exhibited bulging structures with a disrupted membrane system. The cytoplasm of infected cells contained numerous flexible, virus-like particles dispersed throughout the cytosol or arranged in bundles, potentially linked to Fig mosaic virus (FMV) [ 65 ]. The ultrastructural characteristics of healthy leaf cells, as observed in electron micrographs, confirmed the presence of normal organelles and an overall well-preserved cellular architecture. The current observed cytopathological alterations, including nuclear degradation and mitochondrial disruption, suggest severe impairment of cellular metabolism, likely affecting photosynthesis and nutrient transport in infected plants. In this study, gene prediction and proteomic analysis revealed that RNA-1 is 8,530 nucleotides (nt) in length, comprising four open reading frames (ORFs), including a 302-nt untranslated leader sequence at the 5′ end and a 191-nt non-coding region at the 3′ end. ORF-1a, spanning 5,838 nt and encoding 1,945 amino acids (aa), is located between nucleotides 304 and 6,141. It encodes a 221-kDa multifunctional protein that contains methyltransferase, protease, and helicase domains. ORF-1b, situated between nucleotides 6,212 and 7,657, encodes a 59-kDa RNA-dependent RNA polymerase (RdRp). This protein is likely expressed through a + 1 ribosomal frameshift, a mechanism common among Closteroviridae members. These findings are consistent with [ 74 ]. Furthermore, all eight motifs identified align the results findings by [ 75 ], which characterized ORFs 1a and 1b as encoding proteins essential for viral replication. ORF-2 (nucleotides 7,664–8,245) encodes a 22-kDa protein (P22) that functions as a suppressor of gene silencing [ 53 ]. ORF-3, located at the 3′ terminus of RNA-1 (nucleotides 8,265–8,420), encodes a 6-kDa transmembrane protein (P6), similar to those found in other Crinivirus species [ 76 ]. BLAST analysis of the Egyptian ToCV RNA-1 sequence (accession no. LC791014) revealed a 98–99% sequence identity with Florida isolates (accession nos. NC_007340 and AY903447) from the USA. RNA-2, spanning 8,220 nt, contains a 237-nt 5′ untranslated leader sequence and a 214-nt 3′ untranslated region, encoding eight ORFs. ORF-2 (nucleotides 732–2,396) encodes a 61.9-kDa heat shock protein 70 homolog (Hsp70h), a conserved protein among Crinivirus species that facilitates virus synthesis, cell-to-cell movement, and likely virion tail formation. ORF-3 (nucleotides 2,406–2,609) encodes a predicted 8-kDa protein of unknown function. ORF-4 (nucleotides 2,561–4,114) encodes a 59-kDa protein (P59) that contributes to virion tail assembly and movement. ORF-5 (nucleotides 4,096–4,332) encodes a 9-kDa protein (P9) with no identified function. ORF-6 (nucleotides 4,332–5,105) encodes a 29-kDa coat protein, which encapsidates a major portion of ToCV virions. Additionally, ORF-7 (nucleotides 5,111–7,120) encodes a 76-kDa minor coat protein (CPm), which is involved in virion tail formation and cell-to-cell movement. Our amino acid analysis supports the involvement of a 27-kDa protein (P27) in vector transmission of Lettuce infectious yellows virus (LIYV), as predicted for ORF-8 (nucleotides 7,124–7,822). This ORF represents a conserved region among Crinivirus members, although the amino acid sequence similarity varies significantly among species [ 76 ]. ORF-9 (nucleotides 7,831–8,028) encodes a 7-kDa transmembrane protein (P7) of unknown function, specific to ToCV. BLAST analysis of RNA-2 from the Egyptian ToCV isolate (accession no. LC794715) showed a 99% sequence identity with isolates from Florida (USA), South Korea, and China (accession nos. NC_007341, KP114534, and KC709510, respectively). The non-coding regions of RNA-2 displayed a higher degree of sequence conservation than those of RNA-1. The developmentary history was deduced by utilizing the ultimate probability method depending on the Tamura-Nei model [ 77 ]. The trees percentage in which the linked taxa clustered with each other is presented hereafter the branches. Primary tree(s) for the guiding screening were gained automatically by using Neighbor-Join and BioNJ algorithms to a template of pairwise remoteness rated using the Maximum Composite Likelihood (MCL) process and afterwards opting the topology with eminent log likelihood rating. The tree is depicted to standard, with branch lengths estimated in the numeral of substitutions/site [ 78 ]. The resulting phylogenetic tree illustrates the clustering of ToCV isolates into three clades: red for Clade 1, blue for Clade 2, and green for Clade 3. Furthermore, the two genomic segments, RNA-1 and RNA-2, were associated with different clades, specifically JN1, JN2, and YG isolates. The bipartite genome structure of ToCV was mapped, with ORFs encoding a gene silencing suppressor (P22), a predicted transmembrane protein (P6), and replication proteins on RNA-1. RNA-2 encodes a coat protein, Hsp70h, a minor coat protein (CPm), and six additional proteins. This study applied gene prediction methodologies, including intrinsic and extrinsic approaches, to identify protein-coding sequences. These findings align with previous computational analyses and molecular phylogenetic studies, further confirming the genetic structure and evolutionary relationships of ToCV. Gene prediction involves finding sub-sequences of bases which encode proteins. The intrinsic methods differentiate between exons and introns, while extrinsic methods find similarities between genomic sequences and proteins. Several software programs predict the gene sequences with over 80% accuracy. Coding Region Identification Tool Invoking Comparative Analysis (CRITICA), introduced by Badger and Olsen, combines. The DNA sequences in comparative analysis versus with non-comparative methods, making it suitable for analyzing novel genomes. [ 79 ] analyze the full gene structure in different organisms, combining statistical properties and potential function signals of coding sequences. The CEM method identifies conserved the protein sequences by comparing the pairs of DNA sequences, detecting putative exon pairs, and chaining pairs of putative exons together. GAZE uses a dynamic programming algorithm to predict complete gene structures. [ 80 ] uses a website extreme specific to homology-based gene predicting, calculating the alignment of input DNA sequences and searching for conserved splicing signals via start/stop codons around sequence similarity regions. The gene prediction tool based on Hidden Markov Models (AUGUSTUS), based on a hidden Markov model, achieves rise accuracy on segmented genomic sequences while not using on longer sequences of genes. Integrates multiple gene prediction sources (JIGSAW), automates predicting gene structure from multiple sources, with sensitivity and specificity of 92 and 72% respectively [ 81 ]. Molecular phylogenetic analysis of ToCV deduced amino acids using the NCBI as obtained in current investigation as accession number WEG90037.1. The similarity % for trees in the involved taxa cluster grouped is explained following to the branches. The first tree (s) specific to the guiding search was recorded automatically through using Neighbor-Join via BioNJ algorithms to a matrix of together distances calculated by MCL path and directly fine choosing the topology with magnate log likelihood rate. The tree is detected to the matrix, through branch lengths estimated in the number of alternatives/site. The analysis containing 18 nucleotide sequences [ 68 ]. Conclusion The ToCV particles have filamentous flexibility shape as 850 nm. Tomato leaves infected with ToCV exhibited significant cytopathic effects on tissue and cells. The mesophyll tissues had thin cell walls, few chlorenchyma-free cells, distorted membranes, cell nuclei, chloroplasts, and mitochondria. The cellular of mesophyll tissues in ultrathin sections had thin cell walls, distorted membranes, cell nuclei, chloroplasts, and mitochondria. Cytoplasmic alterations include aberrant chloroplasts, mitochondria, nuclei, and cellular abnormalities compared to healthy leaves that have a flat lamina and concave petioles. Gene prediction of ToCV genome sequence involves finding sub-sequences of bases which encode proteins and the percentage of trees in the involved taxa cluster grouped. ToCV isolate were clustered to 3 clades for bi-partite RNA genome; the first RNA consist of 4 ORFs while the second composed 3 ORFs and other 6 deduced proteins. Future research directions based on our protein prediction results include the development of specific monoclonal and polyclonal antisera kits for ToCV detection in agricultural quarantine settings. Additionally, field trials should be conducted to assess the long-term impact of ToCV on tomato yield in Egypt. Abbreviations ToCV Tomato chlorosis crinicirus , TEM Transmission electron microscope, FAA formalin acetic acid CDD Conserved Domain Database PROSITE Protein Sites and Patterns Database PRINTS Protein Fingerprint Database BLOCKS Aligned Blocks of Conserved Sequences Pfam Protein Families Database ProDom Protein Domain Database SMART Simple Modular Architecture Research Tool HMM Hidden Markov Model COG Clusters of Orthologous Groups, SBVS Structure Base Virtual Screening, ORF Open Reading Frame, MCL Maximum Composite Likelihood NCBI National Center for Biotechnology Information CRITICA Coding Region Identification Tool Invoking Comparative Analysis AUGUSTUS The gene prediction tool based on Hidden Markov Models JIGSAW Integrates multiple gene prediction sources. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Availability of data and materials Competing interests No potential Competing of interest was reported by the authors. Acknowledgement Acknowledgment to Virus and Phytoplasma Research Dept., Plant Pathol. Research Institute, ARC, Giza (P.B.12619), Egypt, and Faculty of Agriculture, Ain Shams University, 68-Hadayek Shoubra, Shubra El-Khaimah, (P.B.11241), Cairo, Egypt for their support of this study. Funding There is no funds, grants, or other support were received during the preparation of this manuscript. Author Contribution Wael S. El-Araby responsible for the majority of the experimental work, data collection, data analysis, and writing the manuscript. Khaled A. El-Dougdoug contributed to the design of the study, and analysis. Likely assisted in manuscript revision. Badawy A. Othman responsible for data collection, data analysis, and writing the manuscript and handling manuscript submission. Allam A. Megahed providing guidance on the study design and data interpretation, as well as contributing to manuscript writing and revision. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgement Acknowledgment to Virus and Phytoplasma Research Dept, Plant Pathol. Research Institute, ARC, Giza (P.B.12619), Egypt, and Faculty of Agriculture, Ain Shams University, 68-Hadayek Shoubra, Shubra El-Khaimah, (P.B.11241), Cairo, Egypt for their support of this study. References El-Araby WS, El-Attar AK, Othman BA, El-Dougdoug KA. Frequency incidence of Tomato chlorosis virus and Tomato yellow leaf curl virus affecting tomato Plants. Arab Universities J Agricultural Sci. 2023;31(2):1–16. DOI: 0009-0008-7945-7447. FAO-STAT. Statistics Division of the Food and Agricultural Organization of the United Nations. Available Online at: http://www.fao.org/faostat/en/ Accessed December 31, 2021. Campos MD, Félix MDR, Patanita M, Materatski P, Varanda C. High throughput sequencing unravels tomato-pathogen interactions towards a sustainable plant breeding. Hortic Res. 2021;8:171. https://doi.org/10.1038/s41438-021-00607-x . Rivarez MPS, Vučurović A, Mehle N, Ravnikar M, Kutnjak D. Global advances in tomato virome research: Current status and the impact of high-throughput sequencing. Front Microbiol. 2021;12:1–22. https://doi.org/10.3389/fmicb.2021.671925 . Megahed AA, El-Dougdoug KA, Othman BA, Lashin SM, Ibrahim MA, Sofy AR. Induction of resistance in tomato plants against Tomato mosaic tobamovirus using beneficial microbial isolates. Pak J Biol Sci. 2013;16:385–90. http://scialert.net/abstract/?doi=pjbs.2013.385.390 . Sofy AR, Sofy MR, Hamed AA, Dawoud RA, Alnaggar AEM, Soliman AM, et al. Ameliorating the adverse effects of Tomato mosaic tobamovirus infecting tomato plants in Egypt by boosting immunity in tomato plants using zinc oxide nanoparticles. Molecules. 2021;26(5):1337:1–18. https://doi.org/10.3390/molecules26051337 . El-Attar AK, EL-Shazly MA, Mokbel SA. Characterization of a novel asymptomatic isolate of Tomato spotted wilt virus , infects chrysanthemum plants in Egypt. J Virological Sci. 2017;2(1):17–31. Darwish HS, El-Banna OM, Abbas MS, Waziri HM, Awad MA. Induction of Tomato ring spot virus resistant plants using the chemical mutagens (NaN 3 and EMS). J Virological Sci. 2020;7:1–18. Zaid N, Younis HA, Deraz S. Molecular studies on Tomato Yellow Leaf Curl Virus in Infected Tomato and Pepper Plants. J Adv Agricultural Researches. 2021;26(3):213–24. https://dx.doi.org/10.21608/jalexu.2021.96238.1007 . Ali AS, Fattouh FA, Fathy RM. Physiological responses to infection by Tomato bushy stunt virus in different host plants. Int J Agric Crop Sci (IJACS). 2015;8(4):541–51. http://ijagcs.com/wp-content/uploads/2015/05/541-551.pdf . Abdel-Salam AMM, Rezk AA, Dawoud RA. Biochemical, serological, molecular and natural host studies on Tomato Chlorosis Virus in Egypt. Pak J Biol Sci. 2019;22(2):83–94. https://scialert.net/fulltext/?doi=pjbs.2019 . .83.94&org=11. Amer MA, Ibrahim YE, Kheder AA, Hamed AH, Farrag AA, Al-Saleh MA. Confirmation incidence of Tomato chlorosis virus naturally infecting tomato crop in Egypt. Intl J Agric Biol. 2020;23(5):963–9. 10.17957/IJAB/15.1375 . Wisler GC, Duffus JE, Liu HY, Li RH. A new white?y-transmitted virus infecting tomato from Florida. Phytopathology., Kiss ZA, Medina V, Falk BW. Crinivirus replication and host interactions. Front Microbiol. 2013;4(99):1–11. https://doi.org/10.3389/fmicb.2013.00099 Lee YJ, Kil EJ, Kwak HR, Kim M, Seo JK, Lee S, et al. Phylogenetic characterization of Tomato chlorosis virus population in Korea: Evidence of reassortment between isolates from different origins. Plant Pathol J. 2018;34(3):199–207. https://doi.org/10.5423/PPJ.OA.10.2017.0220 . Tsai WS, Shih SL, Green SK, Hanson P. First report of the occurrence of Tomato chlorosis virus and Tomato infectious chlorosis virus in Taiwan. Plant Dis. 2004;88(3):311. https://doi.org/10.1094/PDIS.2004.88.3.311B . Louro D, Accotto GP, Vaira AM. Occurrence and diagnosis of Tomato chlorosis virus in Portugal. Eur J Plant Pathol. 2000;106:589–92. https://doi.org/10.1023/A:1008738130592 . Navas-Castillo J, Camero R, Bueno M, Moriones E. Severe yellowing outbreaks in tomato in Spain associated with infections of Tomato chlorosis virus . Plant Dis. 2000;84(8):835–7. https://doi.org/10.1094/PDIS.2000.84.8.835 . Dovas CI, Katis NI, Vgelis AD. Multiplex detection of criniviruses associated with epidemics of a yellowing disease of tomato in Greece. Plant Dis. 2002;86(12):1345–9. https://doi.org/10.1094/PDIS.2002.86.12.1345 . Accotto GP, Vaira AM, Vecchiati M, Finetti Sialer MM, Gallitelli D, Davino M. First report of Tomato chlorosis virus in Italy. Plant Dis. 2001;85(11):1208. https://doi.org/10.1094/PDIS.2001.85.11.1208C . Wintermantel WM, Polston JE, Escudero J, Paoli ER. First report of Tomato chlorosis virus in Puerto Rico. Plant Dis. 2001;85(2):228. https://doi.org/10.1094/PDIS.2001.85.2.228B . Jones DR. Pest risk analysis for. Tomato chlorosis virus. York: Central Science Laboratory; 2001. Hanafi A. Invasive species. A real challenge to IPM in the Mediterranean region? EWSN Newsl. 2002;13:4. Delatte H, Naze F, Cottineau JS, Lefeuvre P, Hostachy B, Reynaud B, et al. Occurrence of Tomato chlorosis virus on tomato in Réunion Island. Plant Pathol. 2006;55(2):289. https://doi.org/10.1111/j.1365-3059.2005.01279.x . Dalmon A, Bouyer S, Cailly M, Girard M, Lecoq H, Debiez C, et al. First report of Tomato chlorosis virus and Tomato infectious chlorosis virus in tomato crops in France. Plant Dis. 2005;89(11):1243. https://doi.org/10.1094/PD-89-1243C . Papayiannis LC, Ioannou N, Dovas CI, Maliogka VI, Katis NI. First report of Tomato chlorosis virus on tomato crops in Cyprus. Plant Pathol. 2006;55(4):567. 10.1111/j.1365-3059.2006.01423.x . Abou-Jawdah Y, El Mohtar C, Atamian H, Sobh H. First report of Tomato chlorosis virus in Lebanon. Plant Dis. 2006;90(3):378. https://doi.org/10.1094/PD-90-0378C . Alvarez-Ruiz P, Jimenez CG, Leyva‐López NE, Méndez‐Lozano J. First report of Tomato chlorosis virus infecting tomato crops in Sinaloa, Mexico. Plant Pathol. 2007;56(6):1043–1043. https://doi.org/10.1111/j.1365-3059.2007.01626.x . Bese G, Boka K, Krizbai L, Takacs A. First report of Tomato chlorosis virus in tomato from Hungary. Plant Dis. 2011;95(3):363. https://doi.org/10.1094/PDIS-07-10-0539 . Massé D, Lefeuvre P, Delatte H, Abdoul Karime AL, Hostachy B, Reynaud B, et al. Tomato chlorosis virus : First report in Mayotte Island. Plant Pathol. 2008;57(2):388. https://doi.org/10.1111/j.1365-3059.2007.01760.x . Zhao RN, Wang R, Wang N, Fan ZF, Zhou T, Shi YC, et al. First report of Tomato chlorosis virus in China. Plant Dis. 2013;97(8):1123. https://doi.org/10.1094/PDIS-12-12-1163-PDN . EPPO. First report of Tomato chlorosis virus in The Netherlands. EPPO Reporting Service. 2018a;2018/037. Fiallo-Olivé E, Hamed AA, Moriones E, Navas-Castillo J. First report of Tomato chlorosis virus infecting tomato in Sudan. Plant Dis. 2011;95(12):1592. https://doi.org/10.1094/PDIS-08-11-0631 . Arruabarrena A, Rubio L, González-Arcos M, Maeso D, Sánchez-Campos S, Fonseca MDN, et al. First report of Solanum sisymbriifolium and S. americanum as natural weed hosts of Tomato chlorosis virus (genus Crinivirus ) in South America. Plant Dis. 2015;99(6):895. https://doi.org/10.1094/PDIS-12-14-1315-PDN . Barbosa JC, Teixeira APM, Moreira AG, Camargo LEA, Bergamin Filho A, Kitajima EW, et al. First report of Tomato chlorosis virus infecting tomato crops in Brazil. Plant Dis. 2008;92(12):1709. https://doi.org/10.1094/PDIS-92-12-1709C . Raza A, Shakeel MT, Umar UUD, Tahir MN, Hassan AA, Katis NI, et al. First report of Tomato chlorosis virus infecting tomato in Pakistan. Plant Dis. 2020;104(7):2036. https://doi.org/10.1094/PDIS-12-19-2732-PDN . Martíne-Zzubiaur Y, Fiallo-Olivé E, Carrillo-Tripp J, Rivera-Bustamante R. First report of Tomato chlorosis virus infecting tomato in single and mixed infections with Tomato yellow leaf curl virus in Cuba. Plant Dis. 2008;92(5):836. https://doi.org/10.1094/PDIS-92-5-0836C . Kimathi RH, Wilisiani F, Mashiko T, Neriya Y, Miinda AE, Nishigawa H, et al. First report of Tomato chlorosis virus infecting tomato in Kenya. Scientific African. 2020;7:e00286. https://ui.adsabs.harvard.edu/link_gateway/2020SciAf… K/doi:10.1016/j.sciaf.2020.e00286. Çevik B, Erkiş G. First report of Tomato chlorosis virus in Turkey. Plant Pathol. 2008;57(4):767. https://doi.org/10.1111/j.1365-3059.2007.01795.x . Galipienso L, Elvira-González L, Velasco L, Herrera-Vásquez JA, Rubio L. Detection of persistent viruses by high-throughput sequencing in tomato and pepper from Panama: Phylogenetic and evolutionary studies. Plants. 2021;10(11):2295. https://doi.org/10.3390/plants10112295 . Castro RM, Hernandez E, Mora F, Ramirez P, Hammond RW. First report of Tomato chlorosis virus in tomato in Costa Rica. Plant Dis. 2009;93(9):970. https://doi.org/10.1094/PDIS-93-9-0970A . Mohammed IU, Yakub AM, Yusuf I, Muhammad A, Navas-Castillo J, Fiallo-Olivé E. First report of Tomato chlorosis virus infecting tomato in Nigeria. Plant Dis. 2018;102(1):257. https://doi.org/10.1094/PDIS-07-17-1099-PDN . Lett JM, Hoareau M, Reynaud B, Saison A, Hostachy B, Lobin K, et al. First report of Tomato chlorosis virus in tomato on Mauritius Island. Plant Dis. 2009;93:111. https://doi.org/10.1094/PDIS-93-1-0111A . Mnari-Hattab M, Zammouri S, Salleh W, Hdider C, Hajlaoui MR. First report of severe yellowing outbreaks on tomato in Tunisia associated with Tomato chlorosis virus infection. New Disease Rep. 2014;30(1):3. https://doi.org/10.5197/j.2044-0588.2014.030.003 . Hirota T, Natsuaki T, Murai T, Nishigawa H, Niibori K, Goto K, et al. Yellowing disease of tomato caused by Tomato infectious chlorosis virus newly recognized in Japan. J Gen Plant Pathol. 2003;69(1):61–4. https://doi.org/10.1007/s10327-002-0015-x . Salem NM, Mansour AN, Abdeen AO, Araj S, Khrfan WI. First report of Tomato chlorosis virus infecting tomato crops in Jordan. Plant Dis. 2015;99(9):1286. https://doi.org/10.1094/PDIS-01-15-0130-PDN . Suastika G, Hartono S, Nishigawa H, Natsuaki T. Yellowing disease outbreaks in tomato in Indonesia associated with infection of Tomato chlorosis virus and Tomato infectious chlorosis virus . J Int Soc Southeast Asian Agricultural Sci. 2011;17:233. Al-Saleh MA, Al-Shahwan IM, Shakeel MT, Amer MA, Orfanidou CG, Katis NI. First report of Tomato chlorosis virus (ToCV) in tomato crops in Saudi Arabia. Plant Dis. 2014;98(11):1590–1. https://doi.org/10.1094/PDIS-05-14-0443-PDN . EPPO. First report of Tomato chlorosis virus in United Kingdom. EPPO Reporting Service. 2018b;2018/129. Solórzano-Morales A, Barboza N, Hernández E, Mora-Umaña F, Ramírez P, Hammond RW. Newly discovered natural hosts of Tomato chlorosis virus in Costa Rica. Plant Dis. 2011;95(4):497. https://doi.org/10.1094/PDIS-11-10-0836 . Wisler GC, Duffus JE, Liu HY, Li RH. Ecology and epidemiology of whitefly-transmitted closteroviruses. Plant Dis. 1998;82(3):270–80. https://doi.org/10.1094/PDIS.1998.82.3.270 . Wintermantel WM, Wisler GC, Anchieta AG, Liu HY, Karasev AV, Tzanetakis IE. The complete nucleotide sequence and genome organization of Tomato chlorosis virus . Arch Virol. 2005;150:2287–98. 10.1007/s00705-005-0571-4 . Cañizares MC, Navas-Castillo J, Moriones E. Multiple suppressors of RNA silencing encoded by both genomic RNAs of the crinivirus, Tomato chlorosis virus . Virology. 2008;379(1):168–74. http://doi.org/10.1016/j.virol.2008.06.020 . Pereira J, Simpkin AJ, Hartmann MD, Rigden DJ, Keegan RM, Lupas AN. High-accuracy protein structure prediction in CASP14. Proteins. 2021;89(12):1687–99. https://doi.org/10.1002/prot.26171 . Yang W, Liu Y, Xiao C. Deep metric learning for accurate protein secondary structure prediction, Knowledge-Based Systems. Knowl Based Syst. 2022;242:0950–7051. https://doi.org/10.1016/j.knosys.2022.108356 . Singh A, Kaushik R, Mishra A, Shanker A, Jayaram B. ProTSAV: A protein tertiary structure analysis and validation server. Biochim Biophys Acta. 2015;1864(1):11–9. https://doi.org/10.1016/j.bbapap.2015.10.004 . Statello L, Guo CJ, Chen LL, Huarte M.. Gene regulation by long non-coding RNAs and its biological functions. Nat Rev Mol Cell Biol. 2021;22(2):96–118. https://doi.org/10.1038/s41580-020-00315-9 . Grant CE, Bailey TL, Noble WS. FIMO: Scanning for occurrences of a given motif. Bioinformatics. 2011;27(7):1017–8. https://doi.org/10.1093/bioinformatics/btr064 . Porto WF, Pires AS, Franco OL. Computational tools for exploring sequence databases as a resource for antimicrobial peptides. Biotechnol Adv. 2017;35(3):337–49. https://doi.org/10.1016/j.biotechadv.2017.02.001 . Marchler-Bauer A, Derbyshire MK, Gonzales NR, Lu S, Chitsaz F, Geer LY, et al. CDD: NCBI's conserved domain database. Nucleic Acids Res. 2015;43(D1):D222–6. https://doi.org/10.1093/nar/gku1221 . Lian X, Yang X, Yang S, Zhang Z. Current status and future perspectives of computational studies on human-virus protein-protein interactions. Brief Bioinform. 2021;22(5):bbab029. https://doi.org/10.1093/bib/bbab029 . Notredame C, Higgins DG, Heringa J, T-Coffee. A novel method for fast and accurate multiple sequence alignment. J Mol Biol. 2000;302(1):205–17. https://doi.org/10.1006/jmbi.2000.4042 . Branco I, Choupina A. Bioinformatics: new tools and applications in life science and personalized medicine. Appl Microbiol Biotechnol. 2021;105(3):937–51. https://doi.org/10.1007/s00253-020-11056-2 . Liu C, Li Y, Xu L, Chen Z, He N. Variation in leaf morphological, stomatal, and anatomical traits and their relationships in temperate and subtropical forests. Sci Rep. 2019;9(5803):1–8. https://doi.org/10.1038/s41598-019-42335-2 . Martelli GP. Graft-transmissible diseases of grapevines-handbook for detect in and diagnosis. Rome: FAO Publication Division; 1993. Nasr-Eldin MA, Othman BA, Megahed AA, El-Masry SS, Faiesal AA. Physiological, cytological and molecular analysis of PVY NTN -infected potato cultivars. Egypt J Experimental Biology (Botany). 2018;14(1):171–85. https://www.ejmanager.com/mnstemps/15/151519330872.pdf?t=1554029194 . Lomsadze A, Gemayel K, Tang S, Borodovsky M. Modeling leaderless transcription and atypical genes results in more accurate gene prediction in prokaryotes. Genome Res. 2018;28(7):1079–89. 10.1101/gr.230615.117 . Epub 2018 May 17. PMID: 29773659; PMCID: PMC6028130. Tamura K, Stecher G, Kumar S. Mol Biol Evol. 2021;38(7):3022–7. https://doi.org/10.1093/molbev/msab120 . MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Letunic I, Khedkar S, Bork P. Recent updates, new developments and status in 2020. Nucleic Acids Res. 2021;49(D1):D458–60. https://doi.org/10.1093/nar/gkaa937 . SAS Institute Inc. SAS/STAT User’s Guide. Version 6. Volume 2, 12th ed. North Carolina, USA: SAS Institute, Inc. Cary; 1996. p. 846. https://support.sas.com/documentation/onlinedoc/91pdf/sasdoc_91/stat_ug_7313.pdf . Bailey NTJ. The use of t-test for small samples. In: Bailey NTJ, editor. Statistical Methods in Biology. Cambridge: Cambridge University Press; 1997. pp. 50–60. https://doi.org/10.1017/CBO9781139170840 . Megahed AA, El-Dougdoug KA, Othman BA, Lashin SM, Ibrahim MA, Sofy AR. A new Egyptian satellite strain of Cucumber mosaic cucumovirus . Int J Virol. 2012;8(3):240–57. http://scialert.net/abstract/?doi=ijv.2012.240.257 . Khalil RR, Bassiouny FM, El-Dougdoug KA, Abo-Elmaty S, Yousef MS. A dramatic physiological and anatomical changes of tomato plants infecting with Tomato yellow leaf curl germinivirus . Int J Agric Sustain. 2014;10(5):1213–29. Lozano G, Moriones E, Navas-Castillo J. Complete sequence of the RNA1 of a European isolate of Tomato chlorosis virus . Arch Virol. 2007;152:839–41. https://doi.org/10.1007/s00705-006-0886-9 . Koonin EV, Mushegian AR, Galperin MY, Walker DR. Comparison of archaeal and bacterial genomes: Computer analysis of protein sequences predicts novel functions and suggests a chimeric origin for the archaea. Mol Microbiol. 1997;25(4):619–37. https://doi.org/10.1046/j.1365-2958.1997.4821861.x . Lozano G, Fortes IM, García-Cano E, Fernández-Muñoz R, Moriones E, Navas-Castillo J. El virus del amarilleo del tomate ( Tomato chlorosis virus , ToCV): una amenaza más para los cultivos protegidos de tomate y pimiento. Agrícola Vergel. 2006;293:263–8. Tamura K, Nei M. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol Biol Evol. 1993;10(3):512–26. https://doi.org/10.1093/oxfordjournals.molbev.a040023 . Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: Molecular evolutionary genetics analysis version 6.0. Mol Biol Evol. 2013;30(12):2725–9. https://doi.org/10.1093/molbev/mst197 . Milanesi L, D‟Angelo D, Rogozin LB. GeneBuilder: Interactive in silico prediction of gene structure. Bioinformatics. 1999;12(7/8):612–21. Taher L, Rinner O, Garg S, Sczyrba A, Brudno M, Batzoglou S, et al. homology-based gene prediction. Bioinformatics. 2003;19(12):1575–7. https://doi.org/10.1093/bioinformatics/btg181 . Sharma R, Kaushik A, Gene Prediction. Rev Gene. 2011;1(4):1436–40. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6985991","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":507036242,"identity":"eb837fe9-117e-4086-9a1f-865553e90867","order_by":0,"name":"Wael S. El-Araby","email":"","orcid":"","institution":"Virus and Phytoplasma Research Department, Plant Pathology Research Institute, Agricultural Research Center, Giza (P.B.12619), Egypt","correspondingAuthor":false,"prefix":"","firstName":"Wael","middleName":"S.","lastName":"El-Araby","suffix":""},{"id":507036243,"identity":"43b7aaf9-2bc4-4e57-9916-7007cfd7f797","order_by":1,"name":"Khaled A. El-Dougdoug","email":"","orcid":"","institution":"Agricultural Microbiology Dept, Faculty of Agriculture, Ain Shams University, 68-Hadayek Shoubra, Shubra El-Khaimah, (P.B.11241), Cairo, Egypt","correspondingAuthor":false,"prefix":"","firstName":"Khaled","middleName":"A.","lastName":"El-Dougdoug","suffix":""},{"id":507036244,"identity":"37015dd4-820e-4bce-8ef0-f5178bd4976a","order_by":2,"name":"Badawy A. Othman","email":"","orcid":"","institution":"Agricultural Microbiology Dept, Faculty of Agriculture, Ain Shams University, 68-Hadayek Shoubra, Shubra El-Khaimah, (P.B.11241), Cairo, Egypt","correspondingAuthor":false,"prefix":"","firstName":"Badawy","middleName":"A.","lastName":"Othman","suffix":""},{"id":507036245,"identity":"87c6232d-ee2c-4015-9202-c727f1df8fe5","order_by":3,"name":"Allam A. Megahed","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYDACduYGKKOBgZk4LcyMUC08B0jWIpFApBb+ZsbGTzcY7uTzz3xj+LmgwoaBv707Aa8WicOMzdI5DM8sZ9zOMZaecSaNQeLM2Q34rTnM2ADUctjAQDrHQJq37TCDgUQufi3yQFt+g7VInjH+TZQWg8OMbRBbJHjMiLPFEKjFGqRF4kxamTXPmTQegn6RO958+DZIC3/74c23eSps5Pjbewl4HwQY/4FIDgMQyUNYOQKwPyBF9SgYBaNgFIwgAAAmfkC5pp5L9wAAAABJRU5ErkJggg==","orcid":"","institution":"Agricultural Botany Dept. (Plant Pathology), Faculty of Agriculture, Damietta University, New Damietta, (P.B.34517), Egypt","correspondingAuthor":true,"prefix":"","firstName":"Allam","middleName":"A.","lastName":"Megahed","suffix":""}],"badges":[],"createdAt":"2025-06-26 18:53:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6985991/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6985991/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90531150,"identity":"8f75defb-f9e0-4bff-8d56-480c7c2a3e0f","added_by":"auto","created_at":"2025-09-03 18:28:43","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":69022,"visible":true,"origin":"","legend":"\u003cp\u003eImage showing flexible rod shape of ToCV particles by transmission electron microscopy using tissue dot (Dip-preparation) method.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6985991/v1/8e200c768336999e30ee4a0c.jpg"},{"id":90531157,"identity":"f9fc0007-0d7d-4011-a694-bce795e73c9a","added_by":"auto","created_at":"2025-09-03 18:28:43","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":99869,"visible":true,"origin":"","legend":"\u003cp\u003eLight micrograph of tomato leaves cross-section, (A) healthy Leaf and (B) ToCV showing different changes in cells and tissues 45 days post-infection. H: hairs; Vp: vascular bundle; Up upper epidermis; S: spongy; Lp: lower epidermis and M: mesophyll (400 X).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6985991/v1/6e6dabb9c60d04b5258b2114.jpg"},{"id":90532060,"identity":"6f74c9e6-cb43-47a9-b5cd-8691621d32bf","added_by":"auto","created_at":"2025-09-03 18:44:43","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":159666,"visible":true,"origin":"","legend":"\u003cp\u003eLight micrograph of tomato leaves petiole cross-section, (A) healthy Leaf and (B) ToCV showing different changes in cells and tissues 45 days post-infection. Ep = Epidermis, H=Hair, Pa= Parenchyma, VB = vascular bundle, Ph = Phloem and X= Xylem (500 X).\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6985991/v1/fd4b2deb01ec5c24a36e7c37.jpg"},{"id":90531154,"identity":"96d3f3d3-ff7d-4880-bb41-1b58e3a06efe","added_by":"auto","created_at":"2025-09-03 18:28:43","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":41414,"visible":true,"origin":"","legend":"\u003cp\u003ePhotoelectron micrograph showing ultrathin sections of tomato healthy leaf cells, Nucleus (N), Nuclei (Ni), Chloroplasts (Ch) starch (St), Thylakoid membrane (Th); Mitochondria (M) and Vacuole (V.C.), Cytoplasm (Cy) Intersperse (I.S.) and Cell wall (C.W.). (6000x and 12000x).\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6985991/v1/1cc3118de403965c16caf1f5.jpg"},{"id":90531156,"identity":"8b68c2b3-e7ef-4f6c-a8b6-7c703ebfe234","added_by":"auto","created_at":"2025-09-03 18:28:43","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":107904,"visible":true,"origin":"","legend":"\u003cp\u003ePhoto electron micrograph showing ultrathin sections of tomato ToCV infected leaf cells (A, B, C, D. E. F. G. H and K) showed deformed mesophyll cells with deformed organelles, Chloroplasts (Ch); Cell wall (Cw), Cell (Ce), Inclusion body (I.B.), Interspaces (I.S.), Mitochondria (M), Nucleus (N), nuclei (Ne), Plasmalemasomes (P.L.) and Space (S) Virus (V), Vassals (Vs) and Vacuole (Vc) (5000, 6000, 8000, and 20000 X).\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6985991/v1/eb375c115684c6d14b1afb5f.jpg"},{"id":90532059,"identity":"a58ea78e-4702-497a-ac30-7016e29b0153","added_by":"auto","created_at":"2025-09-03 18:44:43","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":80819,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic diagram of bi-partite genome organization of isolated ToCV, Gene composition RNA1 and RNA2 reference and outcome.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6985991/v1/c2eec944e807e53c1173b318.jpg"},{"id":90531372,"identity":"4431350d-5b0b-4e94-8872-c98490fba282","added_by":"auto","created_at":"2025-09-03 18:36:43","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":34411,"visible":true,"origin":"","legend":"\u003cp\u003eMolecular phylogenetic tree based on predicted partial amino acids sequences from ToCV isolate comparing to others from NCBI-GenBank.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6985991/v1/b075a04afecd5a3382d1d06b.jpg"},{"id":91624448,"identity":"4268255c-3ac5-4b00-a7f1-407e16175eb6","added_by":"auto","created_at":"2025-09-18 12:02:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1636767,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6985991/v1/a38cd8e5-b287-4ec8-9355-38c791b6e1fb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Electron microscopy for Tomato chlorosis crinicirus (ToCV) particles, histopathological effects and bioinformatics prediction of viral proteins","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTomato (\u003cem\u003eLycopersicon esculentum\u003c/em\u003e L.) is one of the most economically important vegetable crops grown in Egypt and worldwide. Its global production was approximately 180.8\u0026nbsp;million tons in 2019, generating an income of 93.9\u0026nbsp;billion US dollars in 2018 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Tomatoes rank as the sixth most important vegetable crop after potatoes, with a current global production of about 6,245,787\u0026nbsp;million tons. They are a rich source of essential micro- and macronutrients vital to human health [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Tomato plants are susceptible to several phytopathogens, including viruses, virus-like particles (Viroids), virus-like organisms (Phytoplasma), bacteria, nematodes and fungi, all of which significantly impact yield and quality production [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Among these, viruses are major constraints to tomato production, with more than 45 viral diseases reported in tomatoes. Virus transmission varies depending on the species and can occur through mechanical wounds, biological vectors, or both [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The most common viruses affecting tomato plants in Egypt include \u003cem\u003eTomato mosaic virus\u003c/em\u003e (ToMV) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], \u003cem\u003eTomato spotted wilt virus\u003c/em\u003e (TSWV) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], \u003cem\u003eTomato ring spot virus\u003c/em\u003e (ToRSV) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], \u003cem\u003eTomato yellow leaf curl virus\u003c/em\u003e (TYLCV) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], \u003cem\u003eTomato bushy stunt virus\u003c/em\u003e (ToBSV) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], and ToCV [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eToCV belongs to the genus Crinivirus within the family Closteroviridae and is transmitted by whiteflies. ToCV particles are filamentous, measuring approximately 850 nm in length [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Since its initial discovery in the United States in 1996, ToCV has been detected in 38 other countries and territories [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], including Taiwan [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e16\u003c/span\u003e], Portugal [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e17\u003c/span\u003e], Taiwan [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e16\u003c/span\u003e], Spain [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e18\u003c/span\u003e], Greece [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e19\u003c/span\u003e], Italy [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e20\u003c/span\u003e], Puerto Rico (USA) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e21\u003c/span\u003e], South Africa [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e22\u003c/span\u003e], Morocco [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e23\u003c/span\u003e], R\u0026eacute;union (FR) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e24\u003c/span\u003e], France [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e25\u003c/span\u003e], Cyprus [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e26\u003c/span\u003e], Lebanon [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e27\u003c/span\u003e], Mexico [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e28\u003c/span\u003e], Hungary [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e29\u003c/span\u003e], Mayotte (FR) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e30\u003c/span\u003e], China [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e31\u003c/span\u003e], The Netherlands [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e32\u003c/span\u003e], Sudan [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e33\u003c/span\u003e], Uruguay [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e34\u003c/span\u003e], Korea [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e15\u003c/span\u003e], Brazil [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e35\u003c/span\u003e], Pakistan [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e36\u003c/span\u003e], Cuba [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e37\u003c/span\u003e], Kenya [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e38\u003c/span\u003e], Turkey [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e39\u003c/span\u003e], Panama [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e40\u003c/span\u003e], Costa Rica [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e41\u003c/span\u003e], Nigeria [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e42\u003c/span\u003e], Mauritius [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e43\u003c/span\u003e], Tunisia [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e44\u003c/span\u003e], Japan [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e45\u003c/span\u003e], Jordan [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e46\u003c/span\u003e], Indonesia [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e47\u003c/span\u003e], Saudi Arabia [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e48\u003c/span\u003e], the United Kingdom [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e49\u003c/span\u003e], and Egypt [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The symptoms of ToCV infection in tomatoes include interveinal chlorotic yellow patches, which initially appear on the lower leaves and progressively spread to the upper foliage. Bronzing and reddish spots are often observed within the yellow patches. Infected leaves become thickened and brittle, with slightly curled upward margins. Although ToCV-infected tomato plants may not always exhibit clear symptoms, fruit ripening is significantly delayed, and severe flower abortion occurs, leading to economic losses [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. In artificially inoculated \u003cem\u003eNicotiana clevelandii\u003c/em\u003e plants, phloem companion cells exhibit an increase in cytoplasmic vesicles, where virus particles are frequently observed. Ultrastructural studies later in the infection process reveal cytoplasmic and organelle degeneration in phloem companion cells, with virus particles aggregating into large bundles [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eToCV has two biotypes (A and B) with a bipartite (+) ssRNA, with RNA1 measuring 8595 nt and RNA2 measuring 8247 nt, containing four and nine ORFs, respectively [13\u0026ndash;15). RNA1 encodes proteins involved in viral replication and gene silencing suppression, while RNA2 encodes proteins associated with whitefly transmission, membrane attachment, virus encapsidation, gene silencing suppression, and cell-to-cell movement. ORF1a encodes a multifunctional protein with helicase, methyltransferase, and protease domains, while ORF1b encodes an RNA-dependent RNA polymerase (RdRp) [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. ORF2 encodes the p22 protein, which is a potent RNA silencing suppressor with prolonged local activity [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Bioinformatics, or computational biology, is an evolving field that utilizes next-generation sequencing for biological data analysis and interpretation. Structural bioinformatics focuses on analyzing and predicting the three-dimensional structures of biological macromolecules using experimentally solved structures and computational models [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Sequence analysis in bioinformatics presents challenges due to high computational costs associated with deep learning models, which rely on complex network architectures and large model sizes [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Protein tertiary (3D) structure, determined by folding of secondary structures, is crucial for protein function. Assessing the quality of predicted models is essential for further functional research [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. A motif is a short DNA or protein sequence that plays a critical role in the biological function of the sequence in which it resides [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Computational methods have been developed to identify, characterize, and search for sequence motifs and domains in proteins. These conserved regions are essential for protein classification and functional annotation [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eDomain and motif prediction algorithms are instrumental in identifying remote homologs in databases, with PSI-BLAST being a widely used tool for profiles-based database searches [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. The Conserved Domain Database (CDD) creates alignment models of sequence fragments, aligning them with protein 3D structure boundaries, modeling conserved cores, and annotating functional features [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Motif databases classify proteins, assign functions, and identify structural relationships. Some databases use regular expressions, such as the Protein Sites and Patterns Database (PROSITE) and Emotif, while others, such as the Protein Fingerprint Database (PRINTS), Aligned Blocks of Conserved Sequences (BLOCKS), Protein Families Database (Pfam), Protein Domain Database (ProDom), and Simple Modular Architecture Research Tool (SMART), rely on profile-based methods [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Protein information is categorized into primary, composite, secondary, and pattern databases, each addressing different aspects to enhance structure prediction strategies [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Structure prediction bridges the gap between available sequences and experimentally determined structures, aiding in understanding of protein functions in medicine, pharmacology, and biotechnology through computational approaches [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. The current study aims to characterize ToCV particles morphology by investigating its effects on tomato plant histopathology. Additionally, the study involves gene prediction of the ToCV genome sequence by identifying sub-sequences of nucleotide bases that encode proteins.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eVirus isolate\u003c/h2\u003e\u003cp\u003eThe pure single isolate of ToCV was obtained from [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] and maintained in tomato plants (\u003cem\u003eS. lycopersicum\u003c/em\u003e cv. Aliasa F1) as a ToCV-propagative host in the Virology Laboratory at Agric. Microbiol. Department sited in Faculty of Agriculture of Ain Shams University in Egypt for further studies.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDetermination of virus morphology\u003c/h3\u003e\n\u003cp\u003eA 10 \u0026micro;L droplet of the supernatant from clarified infectious sap was prepared by low-speed centrifugation at 6000 rpm for 15 min. The sample was placed on a carbon-coated nickel grid, stained with 2% uranyl acetate (pH 7.0) for 30 min, and directly examined using a JOEL JEM-1400 transmission electron microscope (TEM) at an accelerating voltage of 80 kV at the Fungal Center, Al-Azhar University, Cairo.\u003c/p\u003e\n\u003ch3\u003eLight microscopy of ToCV cytopathic effects\u003c/h3\u003e\n\u003cp\u003eLeaflet middle lamina sections (1 cm\u0026sup2;), including the midrib, were collected from five ToCV-infected tomato leaves and five healthy (control) leaves. These samples were excised from infected foliage at the seventh nodes and from healthy leaves at approximately 21 days of age. All samples were fixed and preserved in formalin-acetic acid (FAA) and 70% ethanol following the protocol described by [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. The prepared sections were examined under a light microscope.\u003c/p\u003e\n\u003ch3\u003eTransmission electron microscopy of ToCV cytopathic effects\u003c/h3\u003e\n\u003cp\u003eFive leaf samples (1 mm\u0026sup2; each) from ToCV-infected and five from healthy (control) tomato plants were processed for ultrathin sectioning following the standard protocol described by [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Each sample was fixed in 2% glutraldhyde in 0.1 M sodium cacodylate buffer (pH 7.2) and subjected to vacuum treatment for 1\u0026ndash;4 minutes every 15 minutes over 2 hours on ice. Before vacuum treatment, floating samples were carefully submerged using pointed metal pokers. The samples were then rinsed in 0.1 M sodium cacodylate buffer (pH 7.2) for 45 minutes, with buffer changes at 15-minute and 30-minute intervals. Further fixation was performed using 1% osmium tetroxide in sodium cacodylate buffer under intermittent vacuum treatment and poking for 1.5 hours, followed by additional rinsing in sodium cacodylate buffer. The samples were dehydrated through a graded ethanol series (35%, 50%, 70%, 80%, 95%, and two rounds of 100%) for 60 minutes each. Ultrathin sections (90 nm thick) were cut using a Leica EM-UC6 ultramicrotome and mounted on copper grids (400 mesh). Sections were double-stained with 2% uranyl acetate for 10 minutes, followed by lead citrate staining for 5 minutes, as described by Nasr-Eldin \u003cem\u003eet al.\u003c/em\u003e, (2018). The sections were examined using a JEOL JEM-1400 TEM at an accelerating voltage of 75 kV at the Electron Microscope Unit, Al-Azhar University, Cairo.\u003c/p\u003e\n\u003ch3\u003eGene prediction\u003c/h3\u003e\n\u003cp\u003eThe nucleotide sequence of ToCV (GenBank accession code ON951644.1) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] was analyzed bioinformatically for protein prediction using GeneMark.hmm (version 3.25) program. The generalized Viterbi algorithm was used to determine the most probable coding/non-coding sequences. To evaluate the accuracy for GeneMarkS-2, the predicted genes were assessed using Clusters of Orthologous Groups(COG) classification, proteomics methods, and N-terminal protein sequencing [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. The statistical significance for the score and length of an open reading frame (ORF) was calculated for putative genes using the Hidden Markov Model (HMM). The scoring system assessed similarity based on a substitution matrix and gap penalty, with global and local alignment strategies employing the dot matrix, dynamic programming, or word optimization. The Needleman-Wunsch and Smith-Waterman global pairwise alignment algorithms were used for database similarity searches and multiple sequence alignment. Multiple sequence alignments were conducted using BIOEDIT 7.2 software, while Clustal Omega was used for phylogenetic analysis. Predicted genes were analyzed using Neighbor-joining, Maximum Likelihood, Minimum-Evolution, and Maximum Parsimony methods [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eDomain prediction\u003c/h2\u003e\u003cp\u003eThe statistical significance for the score and length of an open reading frame (ORF) was calculated for putative genes using the Hidden Markov Model (HMM). The scoring system assessed similarity based on a substitution matrix and gap penalty, with global and local alignment strategies employing the dot matrix, dynamic programming, or word optimization. The Needleman-Wunsch and Smith-Waterman global pairwise alignment algorithms were used for database similarity searches and multiple sequence alignment. Multiple sequence alignments were conducted using BIOEDIT 7.2 software, while Clustal Omega was used for phylogenetic analysis. Predicted genes were analyzed using Neighbor-joining, Maximum Likelihood, Minimum-Evolution, and Maximum Parsimony methods [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e69\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eVariance analysis and mean separation were performed following the methodologies described by [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e71\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eVirus morphology\u003c/h2\u003e\u003cp\u003eToCV particles exhibit helical symmetry and a flexible filamentous shape, measuring approximately 850 nm in length at 80000X magnification. These characteristics were determined by transmission electron microscopy using the tissue-dip preparation method (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eCytopathological effects in light microscopy\u003c/h2\u003e\u003cp\u003eTomato plants infected with \u003cem\u003eTomato chlorosis virus\u003c/em\u003e (\u003cem\u003eToCV\u003c/em\u003e), with tomato as the primary host, exhibited varying degrees of reaction, primarily manifesting as leaf chlorosis. Cytopathic alterations in leaf tissues and cells were analyzed to assess the infection\u0026rsquo;s impact. Inoculated tomato plants showed significant reductions in leaf lamina characteristics (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The upper epidermis (16.76%) consisted of tubular parenchyma cells, while palisade parenchyma cells (49.15%) were cylindrical and formed two well-filled layers, unlike in healthy plants. Additionally, the spongy parenchyma was larger, consisting of two to three layers with a substantial number of intercellular spaces, which were reduced by 36.55% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Histological sections revealed concave lamina formation, compacted upper and lower epidermis, and smaller cells compared to healthy tissues. Many stomata were observed on the lower epidermis, and multicellular hairs were arranged in 2\u0026ndash;3 rows. Furthermore, mesophyll cells displayed multiple layers with no detectable intercellular spaces (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). A significant reduction in petiole characteristics was also observed in infected tomato plants (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In contrast, petiole thickness increased by 21.97%, including epidermal thickness (33.33%), collenchyma (40.79%), parenchyma (29.57%), fibers (36.00%), vascular tissue, xylem number (19.26%), xylem thickness (26.53%), vascular bundle number (16.13%), xylem diameter (12.50%), phloem thickness inside (57.38%), phloem thickness outside (54.35%), and pith diameter (42.43%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Compared to healthy leaves, infected leaves exhibited concave petioles in light microscopy sections (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In contrast, a light micrograph of healthy tomato leaves revealed a nearly flat lamina (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The upper and lower epidermal cells were barrel-shaped, with the lower epidermal cells being slightly larger. The thin-walled epidermal cells contained numerous hairs.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnatomical parameters of transverse sections of lamina and petiole of healthy and ToCV infected leaf infected tomato plant.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eAnatomical parameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eHealthy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eInfected\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003csup\u003e**\u003c/sup\u003eReduction is relative to ToCV infection%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"19\" rowspan=\"20\"\u003e\u003cp\u003eTomato leave lamina\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c3\" namest=\"c2\" rowspan=\"3\"\u003e\u003cp\u003eHairs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLength (um\u003csup\u003e*\u003c/sup\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e182.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e165.00 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e9.34 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUpper\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.00 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-50.00 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLower\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.00 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-33.33 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" morerows=\"1\" nameend=\"c4\" namest=\"c2\" rowspan=\"2\"\u003e\u003cp\u003eCockatiel thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUpper\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.50 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e39.52 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLower\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.40 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e39.05 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eUpper epidermis (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e5.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.15 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e16.76 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eLower epidermis (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e3.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10.20 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e17.03 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003ePalisade tissue thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e70.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e35.90 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e49.15 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eSpongy tissue thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e67.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e42.70 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e36.55 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eVascular tissue thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e475.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e424.00 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e10.74 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e\u003cp\u003eVascular bundle diameter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLength (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e275.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e250.00 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e9.09 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWidth (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e262.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e235.00 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e10.31 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c3\" namest=\"c2\" rowspan=\"3\"\u003e\u003cp\u003eXylem\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e115.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e95.00 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e17.39 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber of vascular\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e52.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e42.00 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e19.23 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDiameter of vascular (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e38.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e32.00 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e15.79 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c3\" namest=\"c2\" rowspan=\"2\"\u003e\u003cp\u003ePhloem\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThickness inside (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e102.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e45.00 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e55.88 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThickness outside (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e95.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e32.00 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e66.32 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eFiber thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e135.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e124.00 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e8.15 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eMain vein thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1325.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e117.40 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e91.14 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eBlade thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e645.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e472.00 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e26.82 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"12\" rowspan=\"13\"\u003e\u003cp\u003eTomato leave\u003c/p\u003e\u003cp\u003epetiole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eCockatiel thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e13.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10.30 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e21.97 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eEpidermis thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e39.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26.00 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e33.33 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eCollenchyma thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e76.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e45.00 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e40.79 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eParenchyma thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e345.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e243.00 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e29.57 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eFiber thickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e75.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e48.00 b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e36.00 b\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eVascular tissue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eXylem\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e675.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e545.00 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e19.26 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThickness (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e98.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e72.00 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e26.53 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNumber of vascular\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e62.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e52.00 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e16.13 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDiameter of vascular (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e48.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e42.00 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e12.50 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003ePhloem\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThickness inside (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e122.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e52.00 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e57.38 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThickness outside (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e92.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e42.00 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e54.35 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003ePith diameter (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e1242.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e715.00 c\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e42.43 c\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eCross-section diameter (um)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e4275.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3325.00 a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e22.22 a\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003eMean values within columns followed by the same letter are not significantly different at P\u0026thinsp;\u0026le;\u0026thinsp;0.05.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e*\u003c/sup\u003e um\u0026thinsp;=\u0026thinsp;Micrometer.\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e**\u003c/sup\u003e Reduction % =Healthyـinfected/healthy X 100\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eCytopathological effects in electron microscopy\u003c/h2\u003e\u003cp\u003eUltrathin of ToCV-infected tomato leaf tissues revealed extensive destruction of mesophyll and palisade cells \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, C). Mesophyll and palisade cells appeared rounded with relatively large intercellular spaces (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, B, C). Some infected cells exhibited deformed cell walls and damaged organelles, including nuclei, chloroplasts, mitochondria, and vacuoles (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, B, C). The cell wall showed irregular sedimentation, aberrations, and degradation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, C). Mitochondria exhibited a degenerated envelope, with disrupted cristae and membranes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eF, G). The nucleus appeared small or destructed with dark-stain chromatin aggregates and a deformed (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, B, H). Additional abnormalities included monomorphic cells, ruptured cytoplasmic and tonoplast membranes, and space formation (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePlasmatic induction of the cytoplasm resulted in space formation between the cell wall and cytoplasmic membrane (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), along with the emergence of plasmodesmata (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Electron micrographs showed various cytoplasmic alterations, including a high number of abnormal chloroplasts, mitochondria, nuclei, and other cellular anomalies. Virus particles were observed surrounding the nucleus and within the cytoplasm (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eB, C, D, E, F, G, H, K). The upper and lower epidermal cells were of similar size, but the lower epidermis appeared distorted. The sub-epidermal parenchyma is made up of 1 layer specific to compacted cells that is thicker than those in healthy plants. The mesophyll tissue presented to be abundant in chloroplasts, and a group of paranchymal and chlorenchymal cells had holes. In contrast to healthy skin, the top epidermis is made up of tubular paranchyma cells that are coated in a thin layer of cuticle. Tomato cells infected with ToCV revealed various cytoplasmic alterations, including the existence of a significant number of aberrant chloroplasts, mitochondria, nuclei, and cellular abnormalities.\u003c/p\u003e\u003cp\u003eIn contrast, electron micrographs of ultrathin sections from healthy leaf cells showed normal mesophyll cells with relatively small or absent intercellular spaces, containing intact organelles such as the cell wall, nucleus, nucleolus, chloroplasts, mitochondria, and vacuole (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The mesophyll cell structure remained well-preserved, with normal nuclei and mitochondria. However, ToCV-infected cells exhibited distorted, bulging chloroplasts with a disrupted membrane system.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eGene prediction and proteomic analysis\u003c/h2\u003e\u003cp\u003eGene prediction of the ToCV (+) ssRNA genome involved identifying sub-sequences encoding proteins and analyzing their phylogenetic clustering. The RNA-1 segment was 8,530 nucleotides (nt) long and contained four open reading frames (ORFs), along with a 302-nt and a 191-nt non-coding region at the 3\u0026prime; end. ORF-1a was 5,838 nt long (1,945 amino acids), while ORF-1b spanned nucleotides 6,212\u0026ndash;7,657.\u003c/p\u003e\u003cp\u003eRNA-2 was 8,220 nt long, containing eight ORFs and a 214-nt 3\u0026prime; untranslated region. ORF-2 was located at nucleotides 732\u0026ndash;2,396, ORF-3 at 2,406\u0026ndash;2,609, and ORF-4 at 2,561\u0026ndash;4,114. ORF-5 (4,096\u0026ndash;4,332 nt) encoded a putative 9-kDa protein (P9), while ORF-6 (4,332\u0026ndash;5,105 nt) encoded a 29-kDa coat protein (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDatabase of identification genes and proteins in NCBI of the complete nucleotide sequences of the isolated ToCV genome.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eId\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eORF name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNucleotide length\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eProtein id\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eProtein length\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDomain1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003eDomain2\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRNA1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC775118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eORF1a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5838\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBEL36645.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1945\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eViral methyltransferase\u003c/p\u003e\u003cp\u003e(pfam01660)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eViral_helicase1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC775237.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eORF1b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1446\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBEO88560.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e481\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eRNA-dependent RNA polymerase\u003c/p\u003e\u003cp\u003e(PF00978.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC775279.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e582\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBEO88671.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eNo domain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC775280.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBEO88672.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eNo domain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRNA2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC778246.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHsp70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1664\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBES66841.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eHsp70\u003c/p\u003e\u003cp\u003e(PF00012.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC778247.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBES66842.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eNo domain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC778248.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1554\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBES66843.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e517\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eViral_Hsp90\u003c/p\u003e\u003cp\u003e(PF03225.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC778251.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e237\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBES66844.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eNo domain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC778252.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWSE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e774\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBES66845.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e257\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eCloster_coat\u003c/p\u003e\u003cp\u003e(PF01785.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC778303.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eORF7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBES66846.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e669\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eNo domain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC778304\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e699\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBES66847.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e232\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eNo domain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLC778305.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eP7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBES66848.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eNO domain\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003e*\u003c/sup\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe bipartite genome of the ToCV isolate was classified into three clade groups: Clade 1 (red), Clade 2 (blue), and Clade 3 (green). The two RNA segments were associated with distinct clades corresponding to J1, JN2, and YG isolates (purple) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). On RNA-1, four ORFs were identified, including P22, which functions as a gene silencing suppressor, replication-associated proteins, and P6, a putative protein with a transmembrane domain. RNA-2 encodes CP (coat protein), Hsp70h (heat shock protein homolog 70), CPm (minor coat protein), and additional putative proteins P8, P9, P27, and P7.\u003c/p\u003e\u003cp\u003eGene prediction was conducted using intrinsic and extrinsic methods to identify sub-sequences encoding proteins. Intrinsic methods differentiated between exons and introns, while extrinsic methods identified similarities between genomic sequences and proteins. Several software programs predicted gene sequences with over 80% accuracy. CRITICA, introduced by Badger and Olsen, combined computational prediction with experimental validation. AUGUSTUS, based on a Hidden Markov Model, improved accuracy for segmented genomic sequences. JIGSAW automated gene structure prediction, achieving 92% sensitivity and 72% specificity. Molecular phylogenetic analysis of the predicted ToCV amino acid sequence (accession number WEG90037.1) was conducted using the National Center for Biotechnology Information (NCBI) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe \u003cem\u003eTomato chlorosis virus\u003c/em\u003e (ToCV) particles are filamentous, measuring approximately 850 nm in length at 80,000X magnification as observed through transmission electron microscopy. ToCV belongs to the \u003cem\u003eClosteroviridae\u003c/em\u003e family, which includes the genus \u003cem\u003eCrinivirus\u003c/em\u003e. Members of this genus are transmitted by whiteflies and possess a bipartite genome consisting two (+) ssRNA genomic segments, each independently encapsidated in filamentous particles [14]. Tomato leaves infected with ToCV exhibited significant cytopathic effects on tissue and cells as observed in light microscopy. The mesophyll tissues of infected leaves displayed thin cell walls, few chlorenchyma-free cells, distorted membranes, and deformed organelles, including nuclei, chloroplasts, and mitochondria, compared to healthy tissues. Additionally, the intercellular spaces were relatively small. Infected leaves also exhibited concave petioles in light microscopy images, in contrast to the nearly flat lamina of healthy tomato leaves. In healthy leaves, the lower epidermal cells were slightly larger than the upper epidermal cells. The thin-walled epidermal cells, which contained numerous hairs, were also more structured in healthy samples.\u003c/p\u003e\u003cp\u003eUltrathin sections of ToCV-infected tomato leaf tissues examined under an electron microscope revealed severe cytopathological effects. Some mesophyll and palisade cells exhibited deformed organelles, including the cell wall, nucleus, chloroplasts, mitochondria, and large vacuoles. Mitochondria displayed a degenerated envelope, with disrupted cristae and membranes. Additional abnormalities included monomorphic cells, ruptured cytoplasmic and tonoplast membranes, and space formation. Infected tomato cells also showed various cytoplasmic alterations, including a significant number of aberrant chloroplasts, mitochondria, nuclei, and other cellular abnormalities. Our findings align with those of [14, 51] whose reported similar cytopathic effects in ToCV-infected leaves such as chloroplast deformation and increased cytoplasmic vesicles.\u003c/p\u003e\u003cp\u003eElectron micrograph of ultrathin sections from healthy leaf cells displayed normal mesophyll cells with relatively narrow or absent intercellular spaces, containing intact organelles such as the cell wall, nucleus, nucleolus, chloroplasts, mitochondria, and vacuole. In contrast, ToCV-infected tomato plants exhibited a reduction in petiole characteristics. These observations are consistent with findings from previous research [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e73\u003c/span\u003e]; which documented cytological deformations in chloroplasts following infections with with \u003cem\u003eCitrus cachexia viroid\u003c/em\u003e (Ccavd) and \u003cem\u003eCitrus exocortis viroid\u003c/em\u003e (CEVd) or Cucumber mosaic virus (CMV). Infected mesophyll cells showed structural degradation, and while organelles such as nuclei and mitochondria appeared relatively intact, chloroplasts were distorted and exhibited bulging structures with a disrupted membrane system. The cytoplasm of infected cells contained numerous flexible, virus-like particles dispersed throughout the cytosol or arranged in bundles, potentially linked to \u003cem\u003eFig mosaic virus\u003c/em\u003e (FMV) [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. The ultrastructural characteristics of healthy leaf cells, as observed in electron micrographs, confirmed the presence of normal organelles and an overall well-preserved cellular architecture. The current observed cytopathological alterations, including nuclear degradation and mitochondrial disruption, suggest severe impairment of cellular metabolism, likely affecting photosynthesis and nutrient transport in infected plants.\u003c/p\u003e\u003cp\u003eIn this study, gene prediction and proteomic analysis revealed that RNA-1 is 8,530 nucleotides (nt) in length, comprising four open reading frames (ORFs), including a 302-nt untranslated leader sequence at the 5\u0026prime; end and a 191-nt non-coding region at the 3\u0026prime; end. ORF-1a, spanning 5,838 nt and encoding 1,945 amino acids (aa), is located between nucleotides 304 and 6,141. It encodes a 221-kDa multifunctional protein that contains methyltransferase, protease, and helicase domains. ORF-1b, situated between nucleotides 6,212 and 7,657, encodes a 59-kDa RNA-dependent RNA polymerase (RdRp). This protein is likely expressed through a\u0026thinsp;+\u0026thinsp;1 ribosomal frameshift, a mechanism common among \u003cem\u003eClosteroviridae\u003c/em\u003e members. These findings are consistent with [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Furthermore, all eight motifs identified align the results findings by [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e75\u003c/span\u003e], which characterized ORFs 1a and 1b as encoding proteins essential for viral replication. ORF-2 (nucleotides 7,664\u0026ndash;8,245) encodes a 22-kDa protein (P22) that functions as a suppressor of gene silencing [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. ORF-3, located at the 3\u0026prime; terminus of RNA-1 (nucleotides 8,265\u0026ndash;8,420), encodes a 6-kDa transmembrane protein (P6), similar to those found in other \u003cem\u003eCrinivirus\u003c/em\u003e species [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. BLAST analysis of the Egyptian ToCV RNA-1 sequence (accession no. LC791014) revealed a 98\u0026ndash;99% sequence identity with Florida isolates (accession nos. NC_007340 and AY903447) from the USA. RNA-2, spanning 8,220 nt, contains a 237-nt 5\u0026prime; untranslated leader sequence and a 214-nt 3\u0026prime; untranslated region, encoding eight ORFs. ORF-2 (nucleotides 732\u0026ndash;2,396) encodes a 61.9-kDa heat shock protein 70 homolog (Hsp70h), a conserved protein among \u003cem\u003eCrinivirus\u003c/em\u003e species that facilitates virus synthesis, cell-to-cell movement, and likely virion tail formation. ORF-3 (nucleotides 2,406\u0026ndash;2,609) encodes a predicted 8-kDa protein of unknown function. ORF-4 (nucleotides 2,561\u0026ndash;4,114) encodes a 59-kDa protein (P59) that contributes to virion tail assembly and movement. ORF-5 (nucleotides 4,096\u0026ndash;4,332) encodes a 9-kDa protein (P9) with no identified function. ORF-6 (nucleotides 4,332\u0026ndash;5,105) encodes a 29-kDa coat protein, which encapsidates a major portion of ToCV virions. Additionally, ORF-7 (nucleotides 5,111\u0026ndash;7,120) encodes a 76-kDa minor coat protein (CPm), which is involved in virion tail formation and cell-to-cell movement. Our amino acid analysis supports the involvement of a 27-kDa protein (P27) in vector transmission of \u003cem\u003eLettuce infectious yellows virus\u003c/em\u003e (LIYV), as predicted for ORF-8 (nucleotides 7,124\u0026ndash;7,822). This ORF represents a conserved region among \u003cem\u003eCrinivirus\u003c/em\u003e members, although the amino acid sequence similarity varies significantly among species [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e76\u003c/span\u003e]. ORF-9 (nucleotides 7,831\u0026ndash;8,028) encodes a 7-kDa transmembrane protein (P7) of unknown function, specific to ToCV. BLAST analysis of RNA-2 from the Egyptian ToCV isolate (accession no. LC794715) showed a 99% sequence identity with isolates from Florida (USA), South Korea, and China (accession nos. NC_007341, KP114534, and KC709510, respectively). The non-coding regions of RNA-2 displayed a higher degree of sequence conservation than those of RNA-1.\u003c/p\u003e\u003cp\u003eThe developmentary history was deduced by utilizing the ultimate probability method depending on the Tamura-Nei model [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. The trees percentage in which the linked taxa clustered with each other is presented hereafter the branches. Primary tree(s) for the guiding screening were gained automatically by using Neighbor-Join and BioNJ algorithms to a template of pairwise remoteness rated using the Maximum Composite Likelihood (MCL) process and afterwards opting the topology with eminent log likelihood rating. The tree is depicted to standard, with branch lengths estimated in the numeral of substitutions/site [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. The resulting phylogenetic tree illustrates the clustering of ToCV isolates into three clades: red for Clade 1, blue for Clade 2, and green for Clade 3. Furthermore, the two genomic segments, RNA-1 and RNA-2, were associated with different clades, specifically JN1, JN2, and YG isolates. The bipartite genome structure of ToCV was mapped, with ORFs encoding a gene silencing suppressor (P22), a predicted transmembrane protein (P6), and replication proteins on RNA-1. RNA-2 encodes a coat protein, Hsp70h, a minor coat protein (CPm), and six additional proteins. This study applied gene prediction methodologies, including intrinsic and extrinsic approaches, to identify protein-coding sequences. These findings align with previous computational analyses and molecular phylogenetic studies, further confirming the genetic structure and evolutionary relationships of ToCV.\u003c/p\u003e\u003cp\u003eGene prediction involves finding sub-sequences of bases which encode proteins. The intrinsic methods differentiate between exons and introns, while extrinsic methods find similarities between genomic sequences and proteins. Several software programs predict the gene sequences with over 80% accuracy. Coding Region Identification Tool Invoking Comparative Analysis (CRITICA), introduced by Badger and Olsen, combines. The DNA sequences in comparative analysis versus with non-comparative methods, making it suitable for analyzing novel genomes. [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e79\u003c/span\u003e] analyze the full gene structure in different organisms, combining statistical properties and potential function signals of coding sequences. The CEM method identifies conserved the protein sequences by comparing the pairs of DNA sequences, detecting putative exon pairs, and chaining pairs of putative exons together. GAZE uses a dynamic programming algorithm to predict complete gene structures. [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e80\u003c/span\u003e] uses a website extreme specific to homology-based gene predicting, calculating the alignment of input DNA sequences and searching for conserved splicing signals via start/stop codons around sequence similarity regions. The gene prediction tool based on Hidden Markov Models (AUGUSTUS), based on a hidden Markov model, achieves rise accuracy on segmented genomic sequences while not using on longer sequences of genes. Integrates multiple gene prediction sources (JIGSAW), automates predicting gene structure from multiple sources, with sensitivity and specificity of 92 and 72% respectively [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Molecular phylogenetic analysis of ToCV deduced amino acids using the NCBI as obtained in current investigation as accession number WEG90037.1. The similarity % for trees in the involved taxa cluster grouped is explained following to the branches. The first tree (s) specific to the guiding search was recorded automatically through using Neighbor-Join via BioNJ algorithms to a matrix of together distances calculated by MCL path and directly fine choosing the topology with magnate log likelihood rate. The tree is detected to the matrix, through branch lengths estimated in the number of alternatives/site. The analysis containing 18 nucleotide sequences [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe ToCV particles have filamentous flexibility shape as 850 nm. Tomato leaves infected with ToCV exhibited significant cytopathic effects on tissue and cells. The mesophyll tissues had thin cell walls, few chlorenchyma-free cells, distorted membranes, cell nuclei, chloroplasts, and mitochondria. The cellular of mesophyll tissues in ultrathin sections had thin cell walls, distorted membranes, cell nuclei, chloroplasts, and mitochondria. Cytoplasmic alterations include aberrant chloroplasts, mitochondria, nuclei, and cellular abnormalities compared to healthy leaves that have a flat lamina and concave petioles. Gene prediction of ToCV genome sequence involves finding sub-sequences of bases which encode proteins and the percentage of trees in the involved taxa cluster grouped. ToCV isolate were clustered to 3 clades for bi-partite RNA genome; the first RNA consist of 4 ORFs while the second composed 3 ORFs and other 6 deduced proteins. Future research directions based on our protein prediction results include the development of specific monoclonal and polyclonal antisera kits for ToCV detection in agricultural quarantine settings. Additionally, field trials should be conducted to assess the long-term impact of ToCV on tomato yield in Egypt.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eToCV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cem\u003eTomato chlorosis crinicirus\u003c/em\u003e, TEM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTransmission electron microscope, FAA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eformalin acetic acid\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCDD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConserved Domain Database\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePROSITE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProtein Sites and Patterns Database\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePRINTS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProtein Fingerprint Database\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBLOCKS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAligned Blocks of Conserved Sequences\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePfam\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProtein Families Database\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eProDom\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProtein Domain Database\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSMART\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSimple Modular Architecture Research Tool\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHMM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHidden Markov Model\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCOG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eClusters of Orthologous Groups, SBVS\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eStructure Base Virtual Screening, ORF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOpen Reading Frame, MCL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMaximum Composite Likelihood\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNCBI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNational Center for Biotechnology Information\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCRITICA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCoding Region Identification Tool Invoking Comparative Analysis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eAUGUSTUS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eThe gene prediction tool based on Hidden Markov Models\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eJIGSAW\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eIntegrates multiple gene prediction sources.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eAvailability of data and materials\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eNo potential Competing of interest was reported by the authors.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eAcknowledgment to Virus and Phytoplasma Research Dept., Plant Pathol. Research Institute, ARC, Giza (P.B.12619), Egypt, and Faculty of Agriculture, Ain Shams University, 68-Hadayek Shoubra, Shubra El-Khaimah, (P.B.11241), Cairo, Egypt for their support of this study.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThere is no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eWael S. El-Araby responsible for the majority of the experimental work, data collection, data analysis, and writing the manuscript. Khaled A. El-Dougdoug contributed to the design of the study, and analysis. Likely assisted in manuscript revision. Badawy A. Othman responsible for data collection, data analysis, and writing the manuscript and handling manuscript submission. Allam A. Megahed providing guidance on the study design and data interpretation, as well as contributing to manuscript writing and revision. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eAcknowledgment to Virus and Phytoplasma Research Dept, Plant Pathol. Research Institute, ARC, Giza (P.B.12619), Egypt, and Faculty of Agriculture, Ain Shams University, 68-Hadayek Shoubra, Shubra El-Khaimah, (P.B.11241), Cairo, Egypt for their support of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEl-Araby WS, El-Attar AK, Othman BA, El-Dougdoug KA. Frequency incidence of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e and \u003cem\u003eTomato yellow leaf curl virus\u003c/em\u003e affecting tomato Plants. Arab Universities J Agricultural Sci. 2023;31(2):1\u0026ndash;16. DOI: 0009-0008-7945-7447.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFAO-STAT. Statistics Division of the Food and Agricultural Organization of the United Nations. Available Online at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.fao.org/faostat/en/\u003c/span\u003e\u003cspan address=\"http://www.fao.org/faostat/en/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e Accessed December 31, 2021.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCampos MD, F\u0026eacute;lix MDR, Patanita M, Materatski P, Varanda C. High throughput sequencing unravels tomato-pathogen interactions towards a sustainable plant breeding. Hortic Res. 2021;8:171. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41438-021-00607-x\u003c/span\u003e\u003cspan address=\"10.1038/s41438-021-00607-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRivarez MPS, Vučurović A, Mehle N, Ravnikar M, Kutnjak D. Global advances in tomato virome research: Current status and the impact of high-throughput sequencing. Front Microbiol. 2021;12:1\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fmicb.2021.671925\u003c/span\u003e\u003cspan address=\"10.3389/fmicb.2021.671925\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMegahed AA, El-Dougdoug KA, Othman BA, Lashin SM, Ibrahim MA, Sofy AR. Induction of resistance in tomato plants against \u003cem\u003eTomato mosaic tobamovirus\u003c/em\u003e using beneficial microbial isolates. Pak J Biol Sci. 2013;16:385\u0026ndash;90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://scialert.net/abstract/?doi=pjbs.2013.385.390\u003c/span\u003e\u003cspan address=\"http://scialert.net/abstract/?doi=pjbs.2013.385.390\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSofy AR, Sofy MR, Hamed AA, Dawoud RA, Alnaggar AEM, Soliman AM, et al. Ameliorating the adverse effects of \u003cem\u003eTomato mosaic tobamovirus\u003c/em\u003e infecting tomato plants in Egypt by boosting immunity in tomato plants using zinc oxide nanoparticles. Molecules. 2021;26(5):1337:1\u0026ndash;18. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/molecules26051337\u003c/span\u003e\u003cspan address=\"10.3390/molecules26051337\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEl-Attar AK, EL-Shazly MA, Mokbel SA. Characterization of a novel asymptomatic isolate of \u003cem\u003eTomato spotted wilt virus\u003c/em\u003e, infects chrysanthemum plants in Egypt. J Virological Sci. 2017;2(1):17\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDarwish HS, El-Banna OM, Abbas MS, Waziri HM, Awad MA. Induction of \u003cem\u003eTomato ring spot virus\u003c/em\u003e resistant plants using the chemical mutagens (NaN\u003csub\u003e3\u003c/sub\u003e and EMS). J Virological Sci. 2020;7:1\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZaid N, Younis HA, Deraz S. Molecular studies on \u003cem\u003eTomato Yellow Leaf Curl Virus\u003c/em\u003e in Infected Tomato and Pepper Plants. J Adv Agricultural Researches. 2021;26(3):213\u0026ndash;24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://dx.doi.org/10.21608/jalexu.2021.96238.1007\u003c/span\u003e\u003cspan address=\"10.21608/jalexu.2021.96238.1007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAli AS, Fattouh FA, Fathy RM. Physiological responses to infection by \u003cem\u003eTomato bushy stunt virus\u003c/em\u003e in different host plants. Int J Agric Crop Sci (IJACS). 2015;8(4):541\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ijagcs.com/wp-content/uploads/2015/05/541-551.pdf\u003c/span\u003e\u003cspan address=\"http://ijagcs.com/wp-content/uploads/2015/05/541-551.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbdel-Salam AMM, Rezk AA, Dawoud RA. Biochemical, serological, molecular and natural host studies on \u003cem\u003eTomato Chlorosis Virus\u003c/em\u003e in Egypt. Pak J Biol Sci. 2019;22(2):83\u0026ndash;94. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://scialert.net/fulltext/?doi=pjbs.2019\u003c/span\u003e\u003cspan address=\"https://scialert.net/fulltext/?doi=pjbs.2019\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. .83.94\u0026amp;org=11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAmer MA, Ibrahim YE, Kheder AA, Hamed AH, Farrag AA, Al-Saleh MA. Confirmation incidence of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e naturally infecting tomato crop in Egypt. Intl J Agric Biol. 2020;23(5):963\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.17957/IJAB/15.1375\u003c/span\u003e\u003cspan address=\"10.17957/IJAB/15.1375\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWisler GC, Duffus JE, Liu HY, Li RH. A new white?y-transmitted virus infecting tomato from Florida. Phytopathology., Kiss ZA, Medina V, Falk BW. Crinivirus replication and host interactions. Front Microbiol. 2013;4(99):1\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fmicb.2013.00099\u003c/span\u003e\u003cspan address=\"10.3389/fmicb.2013.00099\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee YJ, Kil EJ, Kwak HR, Kim M, Seo JK, Lee S, et al. Phylogenetic characterization of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e population in Korea: Evidence of reassortment between isolates from different origins. Plant Pathol J. 2018;34(3):199\u0026ndash;207. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5423/PPJ.OA.10.2017.0220\u003c/span\u003e\u003cspan address=\"10.5423/PPJ.OA.10.2017.0220\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTsai WS, Shih SL, Green SK, Hanson P. First report of the occurrence of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e and \u003cem\u003eTomato infectious chlorosis virus\u003c/em\u003e in Taiwan. Plant Dis. 2004;88(3):311. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS.2004.88.3.311B\u003c/span\u003e\u003cspan address=\"10.1094/PDIS.2004.88.3.311B\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLouro D, Accotto GP, Vaira AM. Occurrence and diagnosis of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in Portugal. Eur J Plant Pathol. 2000;106:589\u0026ndash;92. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1023/A:1008738130592\u003c/span\u003e\u003cspan address=\"10.1023/A:1008738130592\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNavas-Castillo J, Camero R, Bueno M, Moriones E. Severe yellowing outbreaks in tomato in Spain associated with infections of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e. Plant Dis. 2000;84(8):835\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS.2000.84.8.835\u003c/span\u003e\u003cspan address=\"10.1094/PDIS.2000.84.8.835\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDovas CI, Katis NI, Vgelis AD. Multiplex detection of criniviruses associated with epidemics of a yellowing disease of tomato in Greece. Plant Dis. 2002;86(12):1345\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS.2002.86.12.1345\u003c/span\u003e\u003cspan address=\"10.1094/PDIS.2002.86.12.1345\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAccotto GP, Vaira AM, Vecchiati M, Finetti Sialer MM, Gallitelli D, Davino M. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in Italy. Plant Dis. 2001;85(11):1208. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS.2001.85.11.1208C\u003c/span\u003e\u003cspan address=\"10.1094/PDIS.2001.85.11.1208C\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWintermantel WM, Polston JE, Escudero J, Paoli ER. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in Puerto Rico. Plant Dis. 2001;85(2):228. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS.2001.85.2.228B\u003c/span\u003e\u003cspan address=\"10.1094/PDIS.2001.85.2.228B\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJones DR. Pest risk analysis for. Tomato chlorosis virus. York: Central Science Laboratory; 2001.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHanafi A. Invasive species. A real challenge to IPM in the Mediterranean region? EWSN Newsl. 2002;13:4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDelatte H, Naze F, Cottineau JS, Lefeuvre P, Hostachy B, Reynaud B, et al. Occurrence of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e on tomato in R\u0026eacute;union Island. Plant Pathol. 2006;55(2):289. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-3059.2005.01279.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-3059.2005.01279.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDalmon A, Bouyer S, Cailly M, Girard M, Lecoq H, Debiez C, et al. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e and \u003cem\u003eTomato infectious chlorosis virus\u003c/em\u003e in tomato crops in France. Plant Dis. 2005;89(11):1243. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PD-89-1243C\u003c/span\u003e\u003cspan address=\"10.1094/PD-89-1243C\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePapayiannis LC, Ioannou N, Dovas CI, Maliogka VI, Katis NI. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e on tomato crops in Cyprus. Plant Pathol. 2006;55(4):567. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1365-3059.2006.01423.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-3059.2006.01423.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbou-Jawdah Y, El Mohtar C, Atamian H, Sobh H. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in Lebanon. Plant Dis. 2006;90(3):378. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PD-90-0378C\u003c/span\u003e\u003cspan address=\"10.1094/PD-90-0378C\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlvarez-Ruiz P, Jimenez CG, Leyva‐L\u0026oacute;pez NE, M\u0026eacute;ndez‐Lozano J. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e infecting tomato crops in Sinaloa, Mexico. Plant Pathol. 2007;56(6):1043\u0026ndash;1043. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-3059.2007.01626.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-3059.2007.01626.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBese G, Boka K, Krizbai L, Takacs A. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in tomato from Hungary. Plant Dis. 2011;95(3):363. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-07-10-0539\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-07-10-0539\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMass\u0026eacute; D, Lefeuvre P, Delatte H, Abdoul Karime AL, Hostachy B, Reynaud B, et al. \u003cem\u003eTomato chlorosis virus\u003c/em\u003e: First report in Mayotte Island. Plant Pathol. 2008;57(2):388. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-3059.2007.01760.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-3059.2007.01760.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZhao RN, Wang R, Wang N, Fan ZF, Zhou T, Shi YC, et al. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in China. Plant Dis. 2013;97(8):1123. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-12-12-1163-PDN\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-12-12-1163-PDN\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEPPO. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in The Netherlands. EPPO Reporting Service. 2018a;2018/037.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFiallo-Oliv\u0026eacute; E, Hamed AA, Moriones E, Navas-Castillo J. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e infecting tomato in Sudan. Plant Dis. 2011;95(12):1592. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-08-11-0631\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-08-11-0631\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArruabarrena A, Rubio L, Gonz\u0026aacute;lez-Arcos M, Maeso D, S\u0026aacute;nchez-Campos S, Fonseca MDN, et al. First report of \u003cem\u003eSolanum sisymbriifolium\u003c/em\u003e and \u003cem\u003eS. americanum\u003c/em\u003e as natural weed hosts of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e (genus \u003cem\u003eCrinivirus\u003c/em\u003e) in South America. Plant Dis. 2015;99(6):895. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-12-14-1315-PDN\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-12-14-1315-PDN\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBarbosa JC, Teixeira APM, Moreira AG, Camargo LEA, Bergamin Filho A, Kitajima EW, et al. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e infecting tomato crops in Brazil. Plant Dis. 2008;92(12):1709. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-92-12-1709C\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-92-12-1709C\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRaza A, Shakeel MT, Umar UUD, Tahir MN, Hassan AA, Katis NI, et al. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e infecting tomato in Pakistan. Plant Dis. 2020;104(7):2036. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-12-19-2732-PDN\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-12-19-2732-PDN\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMart\u0026iacute;ne-Zzubiaur Y, Fiallo-Oliv\u0026eacute; E, Carrillo-Tripp J, Rivera-Bustamante R. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e infecting tomato in single and mixed infections with \u003cem\u003eTomato yellow leaf curl virus\u003c/em\u003e in Cuba. Plant Dis. 2008;92(5):836. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-92-5-0836C\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-92-5-0836C\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKimathi RH, Wilisiani F, Mashiko T, Neriya Y, Miinda AE, Nishigawa H, et al. First report of Tomato chlorosis virus infecting tomato in Kenya. Scientific African. 2020;7:e00286. https://ui.adsabs.harvard.edu/link_gateway/2020SciAf\u0026hellip; K/doi:10.1016/j.sciaf.2020.e00286.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e\u0026Ccedil;evik B, Erkiş G. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in Turkey. Plant Pathol. 2008;57(4):767. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-3059.2007.01795.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-3059.2007.01795.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGalipienso L, Elvira-Gonz\u0026aacute;lez L, Velasco L, Herrera-V\u0026aacute;squez JA, Rubio L. Detection of persistent viruses by high-throughput sequencing in tomato and pepper from Panama: Phylogenetic and evolutionary studies. Plants. 2021;10(11):2295. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/plants10112295\u003c/span\u003e\u003cspan address=\"10.3390/plants10112295\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCastro RM, Hernandez E, Mora F, Ramirez P, Hammond RW. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in tomato in Costa Rica. Plant Dis. 2009;93(9):970. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-93-9-0970A\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-93-9-0970A\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMohammed IU, Yakub AM, Yusuf I, Muhammad A, Navas-Castillo J, Fiallo-Oliv\u0026eacute; E. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e infecting tomato in Nigeria. Plant Dis. 2018;102(1):257. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-07-17-1099-PDN\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-07-17-1099-PDN\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLett JM, Hoareau M, Reynaud B, Saison A, Hostachy B, Lobin K, et al. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in tomato on Mauritius Island. Plant Dis. 2009;93:111. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-93-1-0111A\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-93-1-0111A\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMnari-Hattab M, Zammouri S, Salleh W, Hdider C, Hajlaoui MR. First report of severe yellowing outbreaks on tomato in Tunisia associated with \u003cem\u003eTomato chlorosis virus\u003c/em\u003e infection. New Disease Rep. 2014;30(1):3. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5197/j.2044-0588.2014.030.003\u003c/span\u003e\u003cspan address=\"10.5197/j.2044-0588.2014.030.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHirota T, Natsuaki T, Murai T, Nishigawa H, Niibori K, Goto K, et al. Yellowing disease of tomato caused by \u003cem\u003eTomato infectious chlorosis virus\u003c/em\u003e newly recognized in Japan. J Gen Plant Pathol. 2003;69(1):61\u0026ndash;4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10327-002-0015-x\u003c/span\u003e\u003cspan address=\"10.1007/s10327-002-0015-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSalem NM, Mansour AN, Abdeen AO, Araj S, Khrfan WI. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e infecting tomato crops in Jordan. Plant Dis. 2015;99(9):1286. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-01-15-0130-PDN\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-01-15-0130-PDN\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSuastika G, Hartono S, Nishigawa H, Natsuaki T. Yellowing disease outbreaks in tomato in Indonesia associated with infection of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e and \u003cem\u003eTomato infectious chlorosis virus\u003c/em\u003e. J Int Soc Southeast Asian Agricultural Sci. 2011;17:233.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAl-Saleh MA, Al-Shahwan IM, Shakeel MT, Amer MA, Orfanidou CG, Katis NI. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e (ToCV) in tomato crops in Saudi Arabia. Plant Dis. 2014;98(11):1590\u0026ndash;1. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-05-14-0443-PDN\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-05-14-0443-PDN\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEPPO. First report of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in United Kingdom. EPPO Reporting Service. 2018b;2018/129.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSol\u0026oacute;rzano-Morales A, Barboza N, Hern\u0026aacute;ndez E, Mora-Uma\u0026ntilde;a F, Ram\u0026iacute;rez P, Hammond RW. Newly discovered natural hosts of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e in Costa Rica. Plant Dis. 2011;95(4):497. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS-11-10-0836\u003c/span\u003e\u003cspan address=\"10.1094/PDIS-11-10-0836\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWisler GC, Duffus JE, Liu HY, Li RH. Ecology and epidemiology of whitefly-transmitted closteroviruses. Plant Dis. 1998;82(3):270\u0026ndash;80. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1094/PDIS.1998.82.3.270\u003c/span\u003e\u003cspan address=\"10.1094/PDIS.1998.82.3.270\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWintermantel WM, Wisler GC, Anchieta AG, Liu HY, Karasev AV, Tzanetakis IE. The complete nucleotide sequence and genome organization of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e. Arch Virol. 2005;150:2287\u0026ndash;98. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00705-005-0571-4\u003c/span\u003e\u003cspan address=\"10.1007/s00705-005-0571-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCa\u0026ntilde;izares MC, Navas-Castillo J, Moriones E. Multiple suppressors of RNA silencing encoded by both genomic RNAs of the crinivirus, \u003cem\u003eTomato chlorosis virus\u003c/em\u003e. Virology. 2008;379(1):168\u0026ndash;74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://doi.org/10.1016/j.virol.2008.06.020\u003c/span\u003e\u003cspan address=\"10.1016/j.virol.2008.06.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePereira J, Simpkin AJ, Hartmann MD, Rigden DJ, Keegan RM, Lupas AN. High-accuracy protein structure prediction in CASP14. Proteins. 2021;89(12):1687\u0026ndash;99. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/prot.26171\u003c/span\u003e\u003cspan address=\"10.1002/prot.26171\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYang W, Liu Y, Xiao C. Deep metric learning for accurate protein secondary structure prediction, Knowledge-Based Systems. Knowl Based Syst. 2022;242:0950\u0026ndash;7051. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.knosys.2022.108356\u003c/span\u003e\u003cspan address=\"10.1016/j.knosys.2022.108356\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSingh A, Kaushik R, Mishra A, Shanker A, Jayaram B. ProTSAV: A protein tertiary structure analysis and validation server. Biochim Biophys Acta. 2015;1864(1):11\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.bbapap.2015.10.004\u003c/span\u003e\u003cspan address=\"10.1016/j.bbapap.2015.10.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStatello L, Guo CJ, Chen LL, Huarte M.. Gene regulation by long non-coding RNAs and its biological functions. Nat Rev Mol Cell Biol. 2021;22(2):96\u0026ndash;118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41580-020-00315-9\u003c/span\u003e\u003cspan address=\"10.1038/s41580-020-00315-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGrant CE, Bailey TL, Noble WS. FIMO: Scanning for occurrences of a given motif. Bioinformatics. 2011;27(7):1017\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/btr064\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btr064\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePorto WF, Pires AS, Franco OL. Computational tools for exploring sequence databases as a resource for antimicrobial peptides. Biotechnol Adv. 2017;35(3):337\u0026ndash;49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.biotechadv.2017.02.001\u003c/span\u003e\u003cspan address=\"10.1016/j.biotechadv.2017.02.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMarchler-Bauer A, Derbyshire MK, Gonzales NR, Lu S, Chitsaz F, Geer LY, et al. CDD: NCBI's conserved domain database. Nucleic Acids Res. 2015;43(D1):D222\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nar/gku1221\u003c/span\u003e\u003cspan address=\"10.1093/nar/gku1221\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLian X, Yang X, Yang S, Zhang Z. Current status and future perspectives of computational studies on human-virus protein-protein interactions. Brief Bioinform. 2021;22(5):bbab029. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bib/bbab029\u003c/span\u003e\u003cspan address=\"10.1093/bib/bbab029\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNotredame C, Higgins DG, Heringa J, T-Coffee. A novel method for fast and accurate multiple sequence alignment. J Mol Biol. 2000;302(1):205\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1006/jmbi.2000.4042\u003c/span\u003e\u003cspan address=\"10.1006/jmbi.2000.4042\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBranco I, Choupina A. Bioinformatics: new tools and applications in life science and personalized medicine. Appl Microbiol Biotechnol. 2021;105(3):937\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00253-020-11056-2\u003c/span\u003e\u003cspan address=\"10.1007/s00253-020-11056-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLiu C, Li Y, Xu L, Chen Z, He N. Variation in leaf morphological, stomatal, and anatomical traits and their relationships in temperate and subtropical forests. Sci Rep. 2019;9(5803):1\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-019-42335-2\u003c/span\u003e\u003cspan address=\"10.1038/s41598-019-42335-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMartelli GP. Graft-transmissible diseases of grapevines-handbook for detect in and diagnosis. Rome: FAO Publication Division; 1993.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNasr-Eldin MA, Othman BA, Megahed AA, El-Masry SS, Faiesal AA. Physiological, cytological and molecular analysis of PVY\u003csup\u003eNTN\u003c/sup\u003e-infected potato cultivars. Egypt J Experimental Biology (Botany). 2018;14(1):171\u0026ndash;85. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ejmanager.com/mnstemps/15/151519330872.pdf?t=1554029194\u003c/span\u003e\u003cspan address=\"https://www.ejmanager.com/mnstemps/15/151519330872.pdf?t=1554029194\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLomsadze A, Gemayel K, Tang S, Borodovsky M. Modeling leaderless transcription and atypical genes results in more accurate gene prediction in prokaryotes. Genome Res. 2018;28(7):1079\u0026ndash;89. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1101/gr.230615.117\u003c/span\u003e\u003cspan address=\"10.1101/gr.230615.117\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2018 May 17. PMID: 29773659; PMCID: PMC6028130.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTamura K, Stecher G, Kumar S. Mol Biol Evol. 2021;38(7):3022\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/molbev/msab120\u003c/span\u003e\u003cspan address=\"10.1093/molbev/msab120\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. MEGA11: Molecular Evolutionary Genetics Analysis Version 11.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLetunic I, Khedkar S, Bork P. Recent updates, new developments and status in 2020. Nucleic Acids Res. 2021;49(D1):D458\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nar/gkaa937\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkaa937\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSAS Institute Inc. SAS/STAT User\u0026rsquo;s Guide. Version 6. Volume 2, 12th ed. North Carolina, USA: SAS Institute, Inc. Cary; 1996. p. 846. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://support.sas.com/documentation/onlinedoc/91pdf/sasdoc_91/stat_ug_7313.pdf\u003c/span\u003e\u003cspan address=\"https://support.sas.com/documentation/onlinedoc/91pdf/sasdoc_91/stat_ug_7313.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBailey NTJ. The use of t-test for small samples. In: Bailey NTJ, editor. Statistical Methods in Biology. Cambridge: Cambridge University Press; 1997. pp. 50\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/CBO9781139170840\u003c/span\u003e\u003cspan address=\"10.1017/CBO9781139170840\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMegahed AA, El-Dougdoug KA, Othman BA, Lashin SM, Ibrahim MA, Sofy AR. A new Egyptian satellite strain of \u003cem\u003eCucumber mosaic cucumovirus\u003c/em\u003e. Int J Virol. 2012;8(3):240\u0026ndash;57. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://scialert.net/abstract/?doi=ijv.2012.240.257\u003c/span\u003e\u003cspan address=\"http://scialert.net/abstract/?doi=ijv.2012.240.257\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKhalil RR, Bassiouny FM, El-Dougdoug KA, Abo-Elmaty S, Yousef MS. A dramatic physiological and anatomical changes of tomato plants infecting with \u003cem\u003eTomato yellow leaf curl germinivirus\u003c/em\u003e. Int J Agric Sustain. 2014;10(5):1213\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLozano G, Moriones E, Navas-Castillo J. Complete sequence of the RNA1 of a European isolate of \u003cem\u003eTomato chlorosis virus\u003c/em\u003e. Arch Virol. 2007;152:839\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00705-006-0886-9\u003c/span\u003e\u003cspan address=\"10.1007/s00705-006-0886-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKoonin EV, Mushegian AR, Galperin MY, Walker DR. Comparison of archaeal and bacterial genomes: Computer analysis of protein sequences predicts novel functions and suggests a chimeric origin for the archaea. Mol Microbiol. 1997;25(4):619\u0026ndash;37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1046/j.1365-2958.1997.4821861.x\u003c/span\u003e\u003cspan address=\"10.1046/j.1365-2958.1997.4821861.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLozano G, Fortes IM, Garc\u0026iacute;a-Cano E, Fern\u0026aacute;ndez-Mu\u0026ntilde;oz R, Moriones E, Navas-Castillo J. El virus del amarilleo del tomate (\u003cem\u003eTomato chlorosis virus\u003c/em\u003e, ToCV): una amenaza m\u0026aacute;s para los cultivos protegidos de tomate y pimiento. Agr\u0026iacute;cola Vergel. 2006;293:263\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTamura K, Nei M. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol Biol Evol. 1993;10(3):512\u0026ndash;26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/oxfordjournals.molbev.a040023\u003c/span\u003e\u003cspan address=\"10.1093/oxfordjournals.molbev.a040023\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: Molecular evolutionary genetics analysis version 6.0. Mol Biol Evol. 2013;30(12):2725\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/molbev/mst197\u003c/span\u003e\u003cspan address=\"10.1093/molbev/mst197\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMilanesi L, D‟Angelo D, Rogozin LB. GeneBuilder: Interactive \u003cem\u003ein silico\u003c/em\u003e prediction of gene structure. Bioinformatics. 1999;12(7/8):612\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTaher L, Rinner O, Garg S, Sczyrba A, Brudno M, Batzoglou S, et al. homology-based gene prediction. Bioinformatics. 2003;19(12):1575\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/btg181\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btg181\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSharma R, Kaushik A, Gene Prediction. Rev Gene. 2011;1(4):1436\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"ToCV, tomato, histopathological, electron microscopy, protein prediction, bioinformatics","lastPublishedDoi":"10.21203/rs.3.rs-6985991/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6985991/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe field trials for detection of ToCV on tomato yield in Egypt should be assess by using protein prediction results for the development of specific ToCV antisera kits. The current study aims to characterize the morphology of ToCV particles by investigating their infection effects on tomato plants histopathology and and predicting viral proteins using bioinformatics.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eToCV particles exhibit a filamentous, flexible structure measuring approximately 850 nm, as determined using the tissue dip preparation method. Tomato leaves infected with ToCV displayed significant cytopathic effects on tissue and cells. The mesophyll tissue cells had thin cell walls, distorted membranes, and deformed nuclei, chloroplasts, and mitochondria. They also had relatively tiny intercellular spaces. Ultrathin sections revealed that infected tomato leaf cells exhibited deformed cell walls and organelles, including nucleus, chloroplasts, mitochondria, and large vacuoles. The cell wall showed irregular sedimentation, while mitochondria had a degenerated envelope. The nucleus appeared small and damaged. Cytoplasmic alterations included abnormal chloroplasts, mitochondria, and nuclei, as well as overall cellular abnormalities. ToCV infection caused leaf chlorosis, with varying degrees of tissue and cellular alterations. Healthy leaves exhibited a flat lamina and concave petioles. Gene prediction of ToCV-(+) ssRNA genomic segments genome involved identifying sub-sequences of bases that encode proteins and determining the percentage of trees in the involved taxa cluster.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe first tree (s) specific to the guiding search were recorded automatically using the Neighbor-Joining method via BioNJ algorithms, applying a matrix of pairwise distances calculated using the Maximum Composite Likelihood (MCL) method. The topology was then refined by selecting the structure with the highest log-likelihood score.\u003c/p\u003e","manuscriptTitle":"Electron microscopy for Tomato chlorosis crinicirus (ToCV) particles, histopathological effects and bioinformatics prediction of viral proteins","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 18:28:38","doi":"10.21203/rs.3.rs-6985991/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"737ad280-c3a8-4efd-b365-a0f4b07045f5","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-18T11:54:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-03 18:28:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6985991","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6985991","identity":"rs-6985991","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}