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Dr. Mohamed Nasr-Eldin :: Publications:

Title:
Partial Genome Detection, Characterization of TYLCV (MZ546492) Infecting Tomato Plants and siRNA Sequences Detection for Alternative Control Strategy
Authors: Abd ElRahman H, Nasr-Eldin MA, Abo-Elmaaty SA, Abdelwahed MA, ElHefnawi M, Elfiky AM, Soliman ES
Year: 2024
Keywords: Not Available
Journal: Egyptian Journal of Botany
Volume: 64
Issue: 1
Pages: 211-223
Publisher: The National Information and Documentation Center (NIDOC), which is affiliated to the Academy of Scientific Research and Technology
Local/International: International
Paper Link:
Full paper Not Available
Supplementary materials Not Available
Abstract:

Tomato yellow leaf curl disease (TYLCD) is a significant limitation factor in tomato crops and ranks among the top 10 plant viruses affecting the production of many crops, particularly tomatoes, leading to considerable economic losses without an efficient control strategy till now. In this study, PCR technique was used to amplify partial sequences (670 bp) of tomato yellow leaf curl virus (TYLCV) genome, specifically spanning the trans-activator protein (C2), replication enhancer protein (C3) genes, as well as partial parts of replication (Rep) and coat protein (CP) genes. These sequences were obtained from naturally infected tomato plants collected from different governorates in Egypt. The DNA sequence analyses of the current Egyptian isolate was annotated and deposited in the GenBank with an accession ID MZ546492, revealing high nucleotide sequence identities (99.3 %) to TYLCV isolates in the GenBank. The transmission and host range assays confirmed that the whitefly is the sole transmitter, and tomatoes, zucchini, cucumber, pepper, jimsonweed, and common bean as a host for TYLCV. To explore alternative control strategies, an in-silico approach was employed to generate the possible siRNA-producing sequences that could be used to knock down TYLCV in infected plants.The current findings support the development of a rapid, reliable, and robust molecular detection and identification tool of TYLCV in tomato germplasm to ensure the safe and sustainable production of TYLCV-free tomatoes. Additionally, in silico analysis indicated the possibility of using siRNA to control TYLCV.

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