Sugarcane traits and genes: finding the links with a pilot KnetMiner database

The volume of data from molecular genetic and trait analysis studies has increased exponentially over recent years and now includes multiple databases of results as well as all of the research focussing on single genes, traits or phenotypes. Accessing and making sense of all this information to determine research priorities and to predict the best strategy for experimental success is time consuming, as there is currently no system to connect all data sets. The aim of this project was to develop a pilot database that would start to bring together research results linking traits with genes and gene information to assist industry and researchers. Several database programs in use by other industries were assessed to determine if they were suitable. Following this assessment, a recently developed program that makes connections among the datasets was identified as the best in the field, and a pilot sugarcane version was commissioned. In a major advance on the individual trait-by-trait or gene-by-gene approach, the KnetMiner program can be used to examine multiple traits and trait networks, improving clarity in the field. This will potentially highlight gaps in knowledge, and replace the time and cost needed for independent projects to review individual traits of interest before they are able to initiate laboratory-based experiments for trait manipulation. This project has provided the opportunity to assess a range of options for capturing the data and presenting it in an easily searchable system making linkages among genes, traits and phenotypes. Key words Gene pathway, networks, visualisation