FBIP: Identification of viruses infecting indigenous ornamental bulbous plants in South Africa using NGS

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The data in this occurrence resource has been published as a Darwin Core Archive (DwC-A), which is a standardized format for sharing biodiversity data as a set of one or more data tables. The core data table contains 89 records.

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How to cite

Researchers should cite this work as follows:

Gazendam I (2019): FBIP: Identification of viruses infecting indigenous ornamental bulbous plants in South Africa using NGS. v1.0. South African National Biodiversity Institute. Dataset/Occurrence. http://ipt.sanbi.org.za/iptsanbi/resource?r=agricultural&v=1.0

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Researchers should respect the following rights statement:

The publisher and rights holder of this work is South African National Biodiversity Institute. This work is licensed under a Creative Commons Attribution (CC-BY) 4.0 License.

GBIF Registration

This resource has been registered with GBIF, and assigned the following GBIF UUID: 25be374b-8318-4a8c-ae3c-7ae592233afb.  South African National Biodiversity Institute publishes this resource, and is itself registered in GBIF as a data publisher endorsed by South African Biodiversity Information Facility.

Keywords

Virus; Ornamental bulbous plants; Next Generation Sequencing; Ornithogalum; Lacenalia; Eucomis; Specimen

Contacts

Geographic Coverage

Gauteng (Hekpoort, Roodeplaat, Boekenhoudskloof)

Taxonomic Coverage

Most viruses identified to species level and few to genus level

Temporal Coverage

Project Data

There are critical gaps in the knowledge of new and existing virus diversity in indigenous ornamental bulbous plants in South Africa. This project aims to determine the viromes of unknown viruses and local genetic variants of known viruses of indigenous ornamental bulbous plants in South Africa. Four related species (Ornithogalum, Lachenalia, Eucomis and Veltheimia) will be investigated. Classical virus detection and identification are biased in that they all rely on prior knowledge of possible viruses present. Next generation sequencing (NGS) provides an efficient method to determine the entire virus population (virome) of plant organs, whole plants or even entire fields in an unbiased way.

The personnel involved in the project:

Sampling Methods

1. Sample infected flower material for virus discovery and identification. 2. Identify RNA viruses infecting flower material. 3. Investigate phylogeny of South African strains of identified viruses.

Method step description:

1. 1. Sample infected flower material for virus discovery and identification. 1.1 The occurrence and identity of viruses affecting Ornithogalum, Lachenalia, Eucomis and Veltheimia, growing in their natural habitat and propagated ex situ will be investigated. 1.2 Collections of plants will be linked to their flowering season. This may affect the starting time of the project. Ornithogalum and Lachenalia are winter crops, with virus symptoms visible from May to September. Similarly, the best time for Veltheimia is from March to August. Eucomis is a summer crop and can be sampled from November to March. Sample collections will proceed in the coming flowering season. 1.2.1 Symptomatic leaves from Ornithogalum and Lachenalia cultivars maintained at ARC-VOP will be collected. (ARC-VOP) 1.2.2 Virus-infected Lachenalia plants will be obtained from Afriflowers and the Nieuwoudtville flower bulb nursery. (Afriflowers) 1.2.3 Virus-infected Eucomis and Veltheimia plants will be obtained from Afriflowers. (Afriflowers) 1.2.4 A source of wild Ornithogalum plants will be included from the collaborator at SU. (SU) 1.2.5 Lachenalia plants growing in their natural habitat will be collected. (SU) 1.2.6 At least five collections at each locality of each plant species will be made 1.2.7 Collections of plants will be made with the appropriate permits. (SU) 1.3 Plant samples will be indexed according to the date, species, collection locality, and symptom expression details. This database will be stored in an electronic format in a Microsoft Excel spreadsheet. (VOP & SU) {month 1-3} 1.4 Collected growing symptomatic individuals, where available, will be maintained in a greenhouse at ARC-VOP harbouring the National Disease Asset Collection. Virus isolates are maintained by annual re-infection of virus-free plant material of the same species, using optimised mechanical infection methods and buffers (Afreen et al., 2010; Hull 2009). Bulbs are harvested at the end of the growing season and re-planted, since the plants are vegetatively propagated. (VOP) {month 4-12} 1.5 Virus isolates (as plant extracts) will be maintained in ultra-low temperature (-80°C) storage as part of the National Disease Asset Collection of ARC-VOP. (VOP) {month 5-12} 2. Identify RNA viruses infecting flower material The genome sequences of RNA viruses present in infected plant samples will be determined by RNAseq using an Illumina next generation sequencing (NGS). Samples will probably be infected by multiple viruses, therefore individual virus and virus variant genome sequences will be assembled from the NGS data using established bioinformatics pipelines. Only RNA viruses will be investigated in this study. The steps for RNAseq to identify plant RNA viruses are as follows: 2.1 Isolate dsRNA from virus-infected plant samples. Optimisation of existing methods to accommodate the polysaccharide-rich nature of ornamental leaf samples will be done. The isolated dsRNA represents the replicating genome of RNA plant viruses. (VOP & SU) {month 4-5} 2.2 cDNA synthesis and sequencing library construction. (SU & BTP) {month 6} 2.3 Illumina HiSeq2500 paired-end sequencing of 125bp reads of viral metagenome, generating 2GB of data per sample. (BTP) {month 7} 2.4 De novo assembly of contigs by ordering overlapping RNA sequence reads into contiguous stretches (contigs), using CLC Bio Genomics workbench. (VOP, SU & BTP) {month 8} 2.5 Subject contigs to Blastn, Blastx and Blastp analysis against appropriate GenBank databases. (VOP, SU & BTP) {month 8-9} 2.6 Remove eukaryotic contigs, representing plant RNA sequences. (VOP, SU & BTP) {month 8-9} 2.7 Identify contigs of viral origin through comparison with other virus sequences available on public databases, such as Genbank. (VOP, SU & BTP) {month 8-9} 2.8 Align virus contigs to published virus scaffolds that are available on genome databases, such as Genbank, for e.g. OrMV (Wylie et al., 2013). (VOP, SU & BTP) {month 8-9} 2.9 Construct final virus consensus sequences (full genomes) from contigs. (VOP, SU & BTP) {month 10-11} 2.10 Predict open reading frames (ORF), mature peptides and domains with internet software tools (e.g. NCBI CCD, InterProScan) and by identity after alignment with characterised virus sequences. (VOP, SU & BTP) {month 10-11} 2.11 Deposit full genome sequences of viruses to Genbank and make available to SANBI in required format (VOP) {month 12} 3. Investigate phylogeny of South African strains of identified viruses 3.1 Identify and download related virus genome sequences available on public databases, such as Genbank (VOP & SU) {month 8-11} 3.2 Align nucleotide (nt) and amino acid (aa) sequences of viral polyproteins with characterised virus sequences using ClustalW. (VOP & SU) {month 8-11} 3.3 Calculate pair-wise identities between virus sequences from aligned nt and aa sequences. (VOP & SU) {month 12} 3.4 Construct phylogenetic trees from aa sequences using Mega6 (Tamura et al, 2013). (VOP & SU) {month 12} 3.5 Deduce phylogenetic relatedness of South African strains to other viruses (VOP & SU) {month 12}

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