Bespoke knowledge graph and KnetMiner for sorghum and sugarcane

Filling the knowledge gaps to help compare, prioritize, and access information of potential traits

It’s likely unsurprising that plant scientists in the sugar industry are interested in finding targets to increase yield. They normally do this by investigating multiple traits which are controlled by multiple genes. Sadly, no system currently exists to compare, prioritize, and access the potential traits information. Highlighting the importance of finding these traits, other crops have made advances in yield by the selection and manipulation of traits via molecular marker platforms, gene-editing methods, and the production of genetically modified plants. A resource on the genes underlying traits would give a head start to researchers, potentially providing a framework for prioritizing future research.

The creation of a compendium of sugarcane traits and their associated genes would enable the assessment of sugarcane traits to be examined as a whole, rather than examining individual traits, for the first time. This would improve the lack of clarity in the field, providing gene information for various traits, and potentially highlighting gaps in knowledge. Additionally, this would help replace the time and cost needed for independent projects to review traits of interest, prior to being able to initiate experiments for trait manipulation.

Our client used initially the Wheat KnetMiner to explore various traits and gene-gene interactions, finding it to provide highly detailed information that would otherwise take hours, if not days, to independently identify. As a result, they asked us to create a knowledge network for sugarcane. In a POC study, the KnetMiner team have done exactly that. They have created a bespoke knowledge network to help our client identify the most relevant traits, genes, and interacting biological information, so they can sooner initiate experiments to improve sugarcane yield. This was achieved using data from sorghum as it shares a high degree of synteny with sugarcane, in addition to the small publicly available data for sugarcane.

If you’re interested in working with us to create a bespoke knowledge network, get in touch with us here.