Applied Computational Tools for Crop Genome Research

Applied Computational Tools for Crop Genome Research

A major goal of agricultural biotechnology is the discovery of genes or genetic loci which are associated with characteristics beneficial to crop production. This knowledge of genetic loci may then be applied to improve crop breeding. Agriculturally important genes may also benefit crop production through transgenic technologies. Recent years have seen an application of high throughput technologies to agricultural biotechnology leading to the production of large amounts of genomic data. The challenge today is the effective structuring of this data to permit researchers to search, filter and importantly, make robust associations within a wide variety of datasets. At the Plant Biotechnology Centre, Primary Industries Research Victoria in Melbourne, Australia, we have developed a series of tools and computational pipelines to assist in the processing and structuring of genomic data to aid its application to agricultural biotechnology resear-ch. These tools include a sequence database, ASTRA, for the processing and annotation of expressed sequence tag data. Tools have also been developed for the discovery of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) molecular markers from large sequence datasets. Application of these tools to Brassica research has assisted in the production of genetic and comparative physical maps as well as candidate gene discovery for a range of agronomically important traits.