Characterization of the agent causing a new disease in leek (Allium ampeloprasum var-borrum) fields by RNA-Seq
A new disease, in this report called emergent disease in leeks (EDL), that affects leek (Allium ampeloprasum var. porrum) fields was discovered in the Segovia in 2011. This EDL is characterized by the development of abnormalities, which includes root geotropism and deformation, and leaves and bulb d...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2019 |
| País: | España |
| Institución: | Universitat Oberta de Catalunya (UOC) |
| Repositorio: | O2, repositorio institucional de la UOC |
| OAI Identifier: | oai:openaccess.uoc.edu:10609/88786 |
| Acceso en línea: | http://hdl.handle.net/10609/88786 |
| Access Level: | acceso abierto |
| Palabra clave: | porro RNA-Seq virus leek puerro Bioinformatics -- TFM Bioinformàtica -- TFM Bioinformática -- TFM |
| Sumario: | A new disease, in this report called emergent disease in leeks (EDL), that affects leek (Allium ampeloprasum var. porrum) fields was discovered in the Segovia in 2011. This EDL is characterized by the development of abnormalities, which includes root geotropism and deformation, and leaves and bulb discoloration. The etiology of the disease is currently unknown, but the symptoms are associated with the infection of systemic biotrophic pathogens like viruses and phytoplasmas. With the goal of identifying pathogens causing EDL, total RNA was extracted from leaves of healthy leek plants grown in a greenhouse facility and infected plants showing symptoms of the disease. Five pools were prepared by mixing total RNA: four from infected ones (Sick1, Sick2, Sick3, and Sick4) and one from control samples pool C- (Control) that were sent for sequencing. We analyzed the NGS data to identify the microorganisms associated with diseased leek plants. The most important steps of this analysis were: control of the quality of raw reads, trimming the adapter sequences and selection of the contigs present in the infected pools and not in the healthy ones. We took only a sample of 10 percent of the reads to avoid problems with lack of computational resources. Finally, the sequences of interest were analyzed to identify the possible pathogens present. The results showed the presence of phytoplasmas and other microorganisms as possible pathogens associated with the disease. |
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