The detection of Citrus tristeza virus genetic variants using pathogen specific electronic probes

[摘要] ENGLISH ABSTRACT: Citrus tristeza virus (CTV), a complex pathogen of citrus spp., is endemic to South Africa and has been responsible for great losses locally and internationally. CTV causes severe stem pitting in grapefruit, which forms an important sector of South Africa's citrus production and export market. The limited understanding of CTV's ability to cause severe disease in one host while no symptoms in another restricts the implementation of effective management strategies. The conservation of plant biosecurity relies on the rapid identification of pathogenic organisms including viruses. While there are many molecular assays available for the detection of plant viruses, these are often limited in their ability to test for multiple viruses simultaneously. However, with next-generation sequencing (NGS) based metagenomic analysis it is possible to detect multiple viruses within a sample, including low-titre and novel viruses, at the same time. Conventional NGS data analysis has computational limitations during contig assembly and similarity searches in sequence databases, which prolongs the time required for a diagnostic result. In this study, an alternative targeted method was explored for the simultaneous detection of 11 recognised citrus viruses in NGS data using electronic probes (e-probes). E-probes were designed, optimised and screened against raw, unassembled NGS data in order to minimise the bioinformatic processing time required. The e-probes were able to accurately detect their cognate viruses in simulated datasets, without any false negatives or positives. The efficiency of the e-probe based approach was validated with NGS datasets generated from different RNA preparations: dsRNA from 'Mexican' lime infected with different CTV genotypes, dsRNA from field samples, as well as small RNA and total RNA from grapefruit infected with the CTV T3 genotype. A set of probes were made publically available that is able to accurately detect CTV in NGS data irrespective of which genotype the plants are infected with. The results were confirmed by performing de novo assemblies of the high quality read datasets and subsequent BLAST analyses. This sequence based detection method eliminates the need for NGS data assembly, ultimately reducing the virus-detection turnaround time.

[发布机构] Stellenbosch University