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Identification of maize lethal necrosis disease causal viruses in maize and suspected alternative hosts through small RNA profiling

Creator: Tonui, R.
Creator: Masanga, J.
Creator: Kasili, R.
Creator: Runo, S.
Creator: Alakonya, A.
Year: 2020
Language: English
Publisher: Wiley
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Type: Article
Place of Publication: United Kingdom
Pages: 439-450
Issue: 7-8
Volume: 168
DOI: 10.1111/jph.12908
Keywords: Maize Lethal Necrosis Disease
Keywords: MicroRNA
Keywords: Small Interfering RNA
Keywords: Small RNA Sequencing
Description: Maize lethal necrosis disease (MLND) is a devastating viral disease of maize caused by double infection with Maize chlorotic mottle virus (MCMV) and any one of the Potyviridae family members. Management of MLND requires effective resistance screening and surveillance tools. In this study, we report the use of small RNA (sRNA) profiling to detect MLND causal viruses and further the development of alternative detection markers for use in routine surveillance of the disease-causing viruses. Small RNAs (sRNAs) originating from five viruses namely MCMV, Sugarcane mosaic virus (SCMV), Maize streak virus (MSV), Maize-associated totivirus (MATV) and Maize yellow mosaic virus (MYMV) were assembled from infected maize samples collected from MLND hot spots in Kenya. The expression of the identified viral domains was further validated using quantitative real-time PCR. New markers for the detection of some of the MLND causal viruses were also developed from the highly expressed domains and used to detect the MLND-causative viruses in maize and alternative hosts. These findings further demonstrate the potential of using sRNAs especially from highly expressed viral motifs in the detection of MLND causal viruses. We report the validation of new sets of primers for use in detection of the most common MLND causal viruses MCMV and SCMV in East Africa.
Agrovoc: RNA
Related Datasets:
ISSN: 1439-0434
Journal: Journal of Phytopathology

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  • Genetic Resources
    Genetic Resources including germplasm collections, wild relatives, genotyping, genomics, and IP

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