Helium

The ability to predict and visualize the inheritance of genes that facilitate resistance to pathogens or any other commercially important characteristic is crucially important to experimental plant genetics and commercial plant breeding programmes. Derivation of this information by traditional molecular techniques is expensive and time-consuming, even with developments in high-throughput technologies over the past five years. This is especially true in industrial settings where, due to time constraints relating to growing seasons, many thousands of plant lines may need to be screened quickly, efficiently and economically every year.

There is, however, a cognitive limitation conceptualising large pedigree structures. While it may not be achievable or indeed necessary to understand every mating relationship between related individuals or lines, an overall picture can lead to insight into the data and any patterns it may contain. This can also aid in the identification of problems within datasets when coupled with expert domain knowledge. Tools that provide the ability to pull these data types together, and integrate with pedigree structure, will facilitate breeders and researchers to make more informed decisions relating to suitable plant lines to use in subsequent crossings. It is imperative that we develop more suitable crops to meet both the population imposed mandate for increased yield/production and adaptation to a changing global climate.