Combining next-generation pyrosequencing with microarray for large scale expression analysis in non-model species.

BACKGROUND: The next generation sequencing technologies provide new options to characterize the transcriptome and to develop affordable tools for functional genomics. We describe here an innovative approach for this purpose and demonstrate its potential also for non-model species. RESULTS: The method we developed is based on 454 sequencing of 3' cDNA fragments from a normalized library constructed from pooled RNAs to generate, through de novo reads assembly, a large catalog of unique transcripts in organisms for which a comprehensive collection of transcripts or the complete genome sequence, is not available. This "virtual transcriptome" provides extensive coverage depth, and can be used for the setting up of a comprehensive microarray based expression analysis. We evaluated the potential of this approach by monitoring gene expression during berry maturation in Vitis vinifera as if no other sequence information was available for this species. The microarray designed on the berries' transcriptome derived from half of a 454 run detected the expression of 19,609 genes, and proved to be more informative than one of the most comprehensive grape microarrays available to date, the GrapeArray 1.2 developed by the Italian-French Public Consortium for Grapevine Genome Characterization, which could detect the expression of 15,556 genes in the same samples. CONCLUSION: This approach provides a powerful method to rapidly build up an extensive catalog of unique transcripts that can be successfully used to develop a microarray for large scale analysis of gene expression in any species, without the need for prior sequence knowledge.

A molecular method to assess Phytophthora diversity in environmental samples.

Current molecular detection methods for the genus Phytophthora are specific to a few key species rather than the whole genus and this is a recognized weakness of protocols for ecological studies and international plant health legislation. In the present study a molecular approach was developed to detect Phytophthora species in soil and water samples using novel sets of genus-specific primers designed against the internal transcribed spacer (ITS) regions. Two different rDNA primer sets were tested: one assay amplified a long product including the ITS1, 5.8S and ITS2 regions (LP) and the other a shorter product including the ITS1 only (SP). Both assays specifically amplified products from Phytophthora species without cross-reaction with the related Pythium s. lato, however the SP assay proved the more sensitive and reliable. The method was validated using woodland soil and stream water from Invergowrie, Scotland. On-site use of a knapsack sprayer and in-line water filters proved more rapid and effective than centrifugation at sampling Phytophthora propagules. A total of 15 different Phytophthora phylotypes were identified which clustered within the reported ITS-clades 1, 2, 3, 6, 7 and 8. The range and type of the sequences detected varied from sample to sample and up to three and five different Phytophthora phylotypes were detected within a single sample of soil or water, respectively. The most frequently detected sequences were related to members of ITS-clade 6 (i.e. P. gonapodyides-like). The new method proved very effective at discriminating multiple species in a given sample and can also detect as yet unknown species. The reported primers and methods will prove valuable for ecological studies, biosecurity and commercial plant, soil or water (e.g. irrigation water) testing as well as the wider metagenomic sampling of this fascinating component of microbial pathogen diversity.