Molecular Detection and Phylogenetic Characterization of Soybean Mosaic Virus Infecting Soybean (Glycine max L.)
DOI:
https://doi.org/10.37134/jsml.vol14.3.8.2026Keywords:
Soybean mosaic virus, Coat protein gene, RT-PCR, Phylogenetic analysis, SoybeanAbstract
Soybean (Glycine max L.) is one of the world's most important legume crops, valued for its high protein content and extensive applications in food, feed, and industrial products. However, soybean production is frequently threatened by Soybean mosaic virus (SMV), one of the most destructive viral pathogens affecting crop yield and seed quality. This study aimed to detect and molecularly characterize SMV infecting soybean in Uzbekistan. During the 2023 growing season, leaf samples were collected from 35 soybean varieties exhibiting typical virus-like symptoms, including mosaic, yellowing, stunting, and leaf deformation, from the experimental field of the Institute of Genetics and Experimental Plant Biology of the Republic of Uzbekistan. Total RNA was extracted from symptomatic plants and subjected to RT-PCR using SMV-specific primers targeting the coat protein (CP) gene. A DNA fragment of approximately 756 bp was successfully amplified from infected samples, confirming the presence of SMV. The amplified CP gene was sequenced and analyzed to determine its genetic relationship with previously reported SMV isolates. Phylogenetic analysis showed that the Uzbek isolate TH-UZB1 (GenBank accession no. OQ385206.1) clustered closely with Korean SMV isolates and shared high nucleotide identity with the Serbian isolate NDS_21, indicating a high degree of genetic similarity. The molecular detection and characterization of SMV reported in this study provide valuable information on the occurrence and genetic identity of the virus in Uzbekistan. These findings contribute to a better understanding of the genetic diversity of SMV and provide a scientific basis for disease surveillance, resistance breeding, and the development of effective management strategies for sustainable soybean production.
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Copyright (c) 2026 Shuhrat Jumayorov, Tohir Xusanov, Zakhro Akhmedova, Zukhra Kadirova, Abdirasul Vaxobov, Xasan Sagdiyev, Nigora Nazarova, Masudjon Sattarov
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