Canadian Forest Service Publications

Virus genomic cloning, bioinformatics and metagenomics. 2010. Bai, X.; Liu, J.-J.; Hao, X.; Dubeau, C.; Xiang, Y. Pages 71-92 in A. Wang, editor. Principles and Practice of Advanced Technology in Plant Virology. Research Signpost, 37/661 (2), Fort P.O. Trivandrum-695 023, Kerala, India.

Year: 2010

Issued by: Pacific Forestry Centre

Catalog ID: 31847

Language: English

Availability: PDF (request by e-mail)

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The development and application of nucleic acid-based technologies in modern plant virus diagnosis have progressed rapidly because of their high sensitivity and accuracy. This chapter links current plant virus diagnostic practices with existing and emerging genomics tools, and provides an updated overview of several techniques used in plant virus diagnosis, including nucleic acid extraction, genomic cloning, bioinformatics and metagenomics. Plant RNA, viruses without prior sequence information, can be diagnosed by sequencing and newly-developed molecular cloning techniques, such as Single Primer Amplification Technology (SPAT), ligation-anchored PCR (LA-PCR), shotgun cDNA cloning. Rolling-circle amplification (RCA) is a simple and effective method for isolation, cloning and identification of plant viruses with either a single- or double-stranded circular DNA genomes. It has been successfully used in testing of large-scale field samples. Fast expansion of the plant virus genomic information database necessitates bioinformatics becoming a part of plant virus diagnosis. Base calling and assembly, gene finding, sequence similarity search, and phylogenetic analysis are several important procedures used for analysis of sequence data in virus diagnostics. More recently, metagenomics, using direct nucleic acid extraction from uncultured microorganisms, massive genome cloning, high-throughput DNA sequencing, advanced computational algorithm and bioinformatics, provides a new paradigm in plant virus diagnosis by direct detection of all or specific virus populations in a particular ecosystem.