Next Generation Sequencing for Virus Discovery ... · 5- Virus Taxonomy, Classification and...
Transcript of Next Generation Sequencing for Virus Discovery ... · 5- Virus Taxonomy, Classification and...
Figure 5 – Coriander Genome annotation of the novel Potyvirus now named Coriander Potyvirus. Assays were then designed recognising the coat protein sequence for future use in field to test any future coriander.
Figure 1 - The MiSeq Bench top
NG Sequencer. Illumina
Plant viral disease is a constant threat to food security causing significant damage and currently with no treatment. Correct virus identification is crucial to deploy effective control strategies to protect crops. Next Generation Sequencing (NGS) can be used as a universal and unbiased method for virus identification. NGS improves significantly upon limitations of previous methods particularly in speed and generation of information. This technology also allows for assay development and further novel species discovery whilst aiding in food security.
1. Introduction Plant pathology begins by analysing
symptoms, these methods can
significant take time and bias results.
Next Generation Sequencing (NGS)
offers an alternative method to
diagnose plants without bias and
generate new information on the
infection. This poster highlights the use
of the MiSeq along with genomic and
bioinformatics analysis to determine
the cause of disease symptoms,
identify novel viruses, annotate the
genomes of viruses and develop assays
for future use.
Table 1. Highlights the diversity of samples and results from NGS.
Suraj Rai 1,2 Dr Ian Adams2
University of York, Department of Biology, York, YO105DD, UK The Food & Environment Agency , York, YO411LZ , UK
Next Generation Sequencing for Virus Discovery, Identification and Food Security
Overall this poster highlights the success of NGS deployed as virus diagnostic tool. Next Generation Sequencing is an highly useful diagnostic tool for
plant pathology & viral diagnostics5. Crucial aspects are generating a good library, the correct use of
bioinformatics and extra information on the sequenced data. Future analysis must be given in utilising the exome data for
resistance genes.
1- Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng
Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, di Palma F, Birren BW, Nusbaum C, Lindblad-Toh K,
Friedman N, Regev A. Full-length transcriptome assembly from RNA-seq data without a reference genome.
Nat Biotechnol. 2011 May 15;29(7):644-52
2-Huson, DH, Mitra, S, Weber, N, Ruscheweyh, H, and Schuster, SC (2011). Integrative analysis of
environmental sequences using MEGAN4. Genome Research, 21:1552-1560
3-MICHAEL J. ADAMS, JOHN F. ANTONIW AND FREDERIC BEAUDOIN. MOLECULAR PLANT PATHOLOGY (2005),
6, ( 4 ) , 471–487 Overview and analysis of the polyprotein cleavage sites in the family Potyviridae.
5- Virus Taxonomy, Classification and Nomenclature of Viruses, Ninth Report of the International Committee
on Taxonomy of Viruses Editors Andrew M.Q. King, Michael J. Adams, Eric B. Carstens, and Elliot J. Lefkowitz
6- K. Prabha, V. K. Baranwal, R. K. Jain. Indian Journal of Virology May 2013 Applications of Next Generation
High Throughput Sequencing Technologies in Characterization, Discovery and Molecular Interaction of Plant
Viruses
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2. Methods Overview
Figure 3 – Full NGS
Diagnostics workflow.
Unknown Virus RNA Extraction
Virus Identification
3. Results
4. Conclusions & Future Directions
→ Extracting Virus RNA to gain a
quantifiable yield of RNA using
ng/µl, 260/280 ratios and
absorbance peaks.
→ Ligating synthesised cDNA with
adapters to be able to pool samples
and sequence allows us to
multiplex entire batches of
different samples.
→ Sequencing and monitoring to
maintain quality above >30,
alignment of the sequences and
BLAST and MEGAN Tree analysis to
determine viral identity.
A) RNA extraction and purification from diseased samples followed by quantification, ensuring quality.
B) cDNA synthesis, adapter ligations, library enrichment followed by validations, ensuring optimal concentrations.
C) Sample libraries pooling, validation and sequencing.
D) Sequence alignments and bioinformatic analysis for identification.
5. References
Overall the method is designed to
allow for swift processing of
samples to ensure rapid results
whilst also maintaining validity. Figure 2 – Virus Infected Coriander.
Our diseased samples showed a variety of vir infections. Examples in
the Phlox and Coriander are highlighted below*.
A
Figure 4 – Phlox Neighbour-joining tree using 500 boostrap replicates for coat proteins of Mosaic Viruses. Confirms the virus as SpiMV-3.
B
C
D
Sample Identification Result
Phlox Paniculata Spiranthes Mosaic Virus 3*
Coriander Novel Potyvirus CyoPV *
Tarenna D Fungal and Virus Infections
Maize Potential MCMV
Cabbage Potential Varicosavirus
Lantana Camara Potential Fungal Infections