2010 Annual Report
1a.Objectives (from AD-416)
To make use of next-generation sequencing technology to develop a new technique for obtaining robust, codominant genetic markers without the need for prior sequence knowledge or a development phase.
1b.Approach (from AD-416)
Massively parallel pyrosequencing of DNA using the GS FLX (Roche Diagnostics Corp.) platform is directed by synthetic oligonucleotide adaptors ligated onto short (<800 bp) DNA fragments generated at random by mechanical shearing of genomic DNA. However, digestion of genomic DNA with restriction endonucleases, followed by size selection results in a Reduced Representation Library (RRL). Polymorphisms can be identified in an RRL prepared from multiple individuals. Our method extends this concept in a novel way by using two restriction enzymes and incorporating identifier "barcode" sequences into one of the adaptors, allowing sequences to be associated with an individual insect. Careful selection of the enzymes used and the size fraction to be sequenced will control the number of distinct genome locations to be sequenced. The end result will be a set of sequence haplotypes from many loci. Because they are linked to individuals, there is no need to develop a genotyping assay. An excess of sequence reads will allow us to distinguish repetitive elements from single-locus regions. We will apply our new method to the parents and progeny of several Ostrinia nubilalis (European corn borer) families produced from an existing colony at USDA-ARS CICGRU. This will allow us to develop the data analysis tools needed to cluster sequences into loci, filter out repetitive elements, associate sequence reads with individual insects, and identify the haplotypes at each locus. Inheritance patterns of presumed single-copy loci can be observed, allowing identification of problems in filtering out repetitive sequences. Family analysis also will allow us to evaluate the method’s utility for constructing linkage maps. We will test our new method on samples of natural O. nubilalis populations. This will allow us to investigate the potential of our method for studying the population genomics of Lepidoptera, such as identifying genome regions subject to natural selection. We will investigate the applicability of our method to new and emerging lepidopteran pests of agriculture by screening for genetic variation in natural populations of two additional species. One of these, Striacosta albicosta (western bean cutworm) is a major pest of corn of growing importance as it rapidly expands its geographic range across the Corn Belt. The other is a species in the genus Blastobasis, recently identified by the co-PIs as a potentially highly-destructive pest of Panicum virgatum (switchgrass), throughout the Midwest. Switchgrass is an emerging feedstock for biofuel production, the cultivation of which is likely to increase dramatically across the U.S. in the next few years.
Protocols were successfully optimized to prepare DNA samples to generate genetic markers using a new method we developed that is called Sequencing Individuals in Reduced Representation Libraries. The European corn borer was used as the test species. The new method includes a DNA fragment size selection step, and a restriction/ligation reaction step where genomic DNA is completely digested. A preliminary sequencing experiment using a DNA library prepared from progeny from mating siblings of European corn borer is underway. Adjustments to the optimization protocols will be made. The next step will be to test the use of barcode adaptors to tag individual insects, which will be the core test of the application of the new procedure. If successful, this method will vastly improve population studies for insect species. For our use, population genetic studies will be conducted and the genomes of the European corn borer, western bean cutworm, and prairie cordgrass caterpillar will be mapped. These last two species are pest insects with little or no prior genetic information available. Samples of the prairie cordgrass caterpillar are being collected and appropriately stored by collaborators at the University of Illinois for future DNA extraction. Progress of University of Illinois collaborators is monitored through frequent email correspondence and telephone calls initiated by both parties.