Using next-generation sequencing methods for phosphine resistance diagnostics development
Publication Type | Presentation | |
Year of Publication | 2009 | |
Authors | Schlipalius, D.; Tuck, A.; Jagdeesan, R.; Kaur, R.; Collins, P.; Ebert, P. | |
Meeting Name | CRCNPB Science Exchange 2009 | |
Meeting Start Date | 22 - 24 September 2009 | |
Meeting Location | Sunshine Coast | |
Abstract |
Developing a gene-based diagnostic tool for a trait like phosphine resistance presents the formidable task of identifying as little as a single causative nucleotide change present in a highly polymorphic genetic background. The advent of next-generation sequencing methods, such as the Roche GS-FLX system and the Illumina Genome Analyser (GAII) system have made it possible to get very large amounts of sequence data from non-model organisms and specific strains of organisms in a relatively short time. This has made it possible to sequence whole transcriptomes and whole genomes from specific strains and to rapidly scan for polymorphisms that associate with particular traits of interest in any given organism. We have used this approach to target candidate genes for fumigant (phosphine) resistance in two pest insect species of stored grains, Tribolium castaneum and Rhyzopertha dominica, one of which has a reference genome and one which previously had almost no genome sequence information associated with it. To date, we have resequenced the genome from selected resistant T. castaneum, generating 3.5Gb, or approximately 15x coverage of the genome, in a single sequencing run. We have identified two regions that appear to associate with resistance and are currently working on confirming the candidate genes identified. We have also sequenced the transcriptome (the expressed gene sequences) from resistant and sensitive R. dominica and are currently analysing the detected sequence polymorphisms between these strains. While we have used next-generation sequencing for targeting pesticide resistance, it should be noted that a similar approach could potentially be used to target any trait of interest in almost any organism. Given the speed in increase of sequence data acquisition, in the future traits that differ subtly between strains of diseases or pests such as virulence or disease resistance could be identified with relative ease. | |
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