Tropical Plant Pathology

, Volume 43, Issue 6, pp 583–585 | Cite as

Genomic characterisation and evolutionary relationships of groundnut rosette virus from the western highlands of Kenya

  • James M. WainainaEmail author
  • Jagger Harvey
  • Elijah Ateka
  • Timothy Makori
  • David Karanja
  • Monica A. Kehoe
  • Laura M. Boykin
Short Communication


Viral symptomatic groundnut (Arachis hypogaea L.) leaf samples were collected in the heterogeneous agro-ecosystem of the western highlands of Kenya. High throughput RNA sequencing (RNA-Seq) was carried out on total plant RNA using the Illumina HiSeq platform. Subsequently, de novo assembly and sequence similarity searches identified the complete genome of Groundnut rosette virus (GRV). The genome consisted of 4298 nucleotides, encoding three open reading frames (ORF1-ORF3) including an RNA-dependent RNA polymerase gene. A sequence similarity search against GenBank reference sequences matched with 84% identity to a Malawian isolate (Z69910). Bayesian evolutionary relationships using the ORF3 and ORF4 genomic regions clustered the Kenyan isolates within a distinct clade. This study provides the first complete genome of GRV from Kenya and provides a genomic resource for the development of molecular diagnostic tools.


Groundnut rosette virus Tombusviridae Next-generation sequencing Sub-Saharan Africa 



An Australian Award Scholarship by the Department of Foreign Affairs and Trade (DFAT) supports JW, and this work forms part of his PhD research. Fieldwork activities were coordinated through the Cassava Diagnostic project Kenyan node. A Rising Star grant from the Faculty of Science alumni at the University of Western Australia to LMB provided laboratory reagents and consumables. Pawsey Supercomputing Centre provided supercomputer resources for data analysis with funding from the Australian Government and the Government of Western Australia.


  1. Ronquist F, Teslenko M, Van Der Mark P, Ayres DL, Darling A, Höhna S, Larget B, Liu L, Suchard MA, Huelsenbeck JP (2012) Mrbayes 3.2: Efficient bayesian phylogenetic inference and model choice across a large model space. Systematic Biology 61:539–542. CrossRefGoogle Scholar
  2. Kana JR, Gnonlonfin BGJ, Harvey J, Wainaina J, Wanjuki I, Skilton RA, Teguia A (2013) Assessment of aflatoxin contamination of maize, peanut meal and poultry feed mixtures from different agroecological zones in Cameroon. Toxins 5:884–894CrossRefGoogle Scholar
  3. Kehoe MA, Coutts BA, Buirchell BJ, Jones RAC (2014) Plant virology and next generation sequencing: experiences with a potyvirus. PLoS One 9CrossRefGoogle Scholar
  4. King AMQ, Adams MJ, Carstens EB, Lefkowitz EJ (2012) Virus taxonomy. Ninth report of the international committee on taxonomy of viruses. Elsevier/Academic Press, LondonGoogle Scholar
  5. Naidu RA, Kimmins FM, Deom CM, Subrahmanyam P, Chiyembekeza AJ, Van der Merwe PJ (1999) Groundnut rosette: a virus disease affecting groundnut production in sub-Saharan Africa. Plant Disease 83:700–709CrossRefGoogle Scholar
  6. Okello DK, Ugen MA, Tukamuhabwa P, Ochwo M, Odong TL, Adriko J, Kiconco F, Male A, Deom CM (2017) Molecular diagnostics of groundnut rosette disease agents in Uganda: implications on epidemiology and management of groundnut rosette disease. Journal of Plant Breeding and Crop Sciences 9:63–70Google Scholar
  7. Waliyar F, Kumar PL, Ntare BR, Monyo E, Nigam SN, Reddy AS, Osiru M, Diallo, AT (2007) A century of research on groundnut rosette disease and its management. Information Bulletin no. 75. International Crops Research Institute for the Semi-Arid Tropics, PatancheruGoogle Scholar

Copyright information

© Sociedade Brasileira de Fitopatologia 2018

Authors and Affiliations

  1. 1.School of Molecular Sciences and Australian Research Council Centre of Excellence in Plant Energy BiologyUniversity of Western AustraliaPerthAustralia
  2. 2.Feed the Future Innovation Lab for the Reduction of Post-Harvest LossKansas State UniversityKansasUSA
  3. 3.Department of HorticultureJomo Kenyatta University of Agriculture and TechnologyNairobiKenya
  4. 4.Kenya Agricultural and Livestock Research Organization (KARLO)MachakosKenya
  5. 5.Department of Primary Industries and Regional DevelopmentDiagnostic and Laboratory ServiceSouth PerthAustralia

Personalised recommendations