Feature - Fighting pesticide resistance
Pesticide resistance is becoming more of a problem throughout the world as the use of pesticides continues, and insects evolve to accommodate them.
Consequently, pesticides that were once effective at killing crop pests are now no longer effective, leading to an increase in damaged or destroyed crops.
To try to understand the mechanics of how this resistance develops, a group of researchers led by Richard ffrench-Constant at the University of Exeter in the UK are using the country's National Grid Service.
Wilkinson and his research group are analyzing the transcriptomes of insects that are major crop pests, such as Manduca sexta - the tobacco hornworm moth - as seen in the picture at right. (A transcriptome is the set of all messenger RNA molecules, or "transcripts," that are produced in a population of cells and reflects the genes actively expressed at any given time.)
The entire transcriptome of an insect pest is sequenced using the latest 'Next generation' DNA sequencing technologies. Assembling this sequence data generates more than 40,000 sequences, which are then annotated by comparing them against known protein sequences contained in protein databases such as UniProt.
Wilkinson explained that "sequencing transcriptomes can help scientists to understand how insects develop resistance to pesticides. By looking at changes in genes that code for proteins involved in the metabolic pathways that detoxify pesticides, we can assess how resistant insect strains evolve in the field. In addition, the availability of a fully annotated transcriptome allows us to examine differential gene expression of these pesticide resistance genes, using the recently developed digital transcriptomics technologies."
They also hope that the sequencing of insect transcriptomes will lead to the discovery of new enzymes that could be used industrially for such things as biofuels, fruit juice extraction, or the clarification and treatment of waste water.
The homology searches are performed at NGS using high-throughput NCBI BLAST software. This is a parallel implementation of NCBI BLAST that distributes computational resources through database fragmentation, query segmentation, intelligent scheduling, and parallel Input/Output.
Wilkinson's team are also planning on using mpiBLAST - the freely available, open-source, parallel implementation of NCBI BLAST - which they hope will greatly improve performance while scaling up to hundreds of processors. This should dramatically reduce the length of time required to characterize all of the expressed genes in the insect transcriptomes.
He commented: "Making use of NGS resources has already significantly reduced the time it takes to process our data."