Navigating Between Crop Phenotype and Genome: Approaches to Describing, Integrating and Comparing Data

It took nearly 15 years and resource-intensive multi-national effort to sequence the wheat genome. Translating this information into new added-value cultivars requires a concerted approach to data management and accessibility. Although genetic analysis continues to underpin dissection of trait phenotypes, it appears that relatively little effort has been focused on aligning the genome with existing genetic and trait data from a wide range of wheat populations. Developing a consistent platform to navigate between datasets that integrate conventional linkage map and QTL data with the reference genome will enhance pre-breeding efforts. Based on available wheat online databases and other information resources, there appear to be some critical gaps in i) establishment and adoption of agreed nomenclature standards and data registries; ii) collation and curation of disparate datasets with sufficient meta-data to reduce ambiguity and ensure consistent quality iii) provision of tools for trait dataset entry, navigation between phenotype and genome, statistical analysis and visualization. We have surveyed existing sources of wheat linkage maps and QTL datasets, and carried out a pilot study to implement data curation. We used the open-source CropStoreDB platform, which provides a robust generic schema linking plant populations, trials, phenotypic traits, loci and genome markers alongside guidelines for a wide range of nomenclature conventions. This also provides a framework for linking to more recent trait datasets generated for GWAS analysis. Adoptiing and extending this approach will maximize the information able to be derived from the reference wheat genome.