Predicting and validating tomato firmness genes.

Fruit firmness significantly influences tomato quality, impacting shelf-life, consumer acceptance, and transportability at full ripeness. The firmness of tomatoes results from intricate physiological changes, including alterations in cell wall structure, internal turgor pressure, and cuticle integrity. As firmness is governed by a network of genes regulating fruit ripening, identifying new genetic determinants remains a complex challenge. KnetMiner, a knowledge graph-based bioinformatics platform, has traditionally validated known gene-trait relationships. This case study examines whether KnetMiner can proactively assist scientists in identifying novel gene associations, moving beyond validation into predictive hypothesis generation.

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THE QUESTION
How does KnetMiner assist scientists in dissecting complex traits to identify key genes?
Let’s start by breaking up the root question, as answering smaller sets of questions can be simpler.
  • How can KnetMiner integrate multiple biological datasets to highlight candidate genes?
  • Can KnetMiner effectively visualise gene associations to facilitate understanding?
  • Does KnetMiner provide robust tools for discovering direct literature-supported gene-trait connections?
  • Can KnetMiner support hypothesis generation even in the absence of direct prior evidence?
THE METHOD
From traits to underlying genes and processes
Scientists can start with relevant trait keywords and leverage KnetMiner's Concept Search feature. Using specific ontology terms related to tomato firmness, researchers can visualise candidate genes associated with firmness on KnetMiner's interactive Genome Map. Further, by employing the Evidence Distance feature, researchers identified 47 tomato genes directly co-occurring with fruit firmness in existing literature. To delve deeper, the Refined Search feature enables enrichment analysis of these 47 genes, examining their linked annotations including related traits, pathways, biological processes, and regulatory interactions.
Hypothesis generation and emerging trends
To explore the predictive capabilities of KnetMiner, scientists searched specifically for the GUN5 gene and any evidence connecting it to fruit firmness. Initially, the knowledge graph displayed a single publication (Xu et al., 2025) confirming GUN5's role in firmness and ripening. This demonstrated KnetMiner's efficiency in identifying and validating p

However, to test KnetMiner's predictive potential further, the recently published link to firmness was deliberately removed from the GUN5 network. By using KnetMiner’s AI Summary feature, researchers analysed literature on GUN5, its orthologs, and interacting genes in other species. This approach produced a targeted summary highlighting gene functions related to fruit quality processes. Such summaries significantly enhance scientists' ability to generate hypotheses, suggesting that even in the absence of direct prior evidence, KnetMiner can effectively facilitate new insights and "Eureka" moments.
Conclusion
KnetMiner proves highly valuable not only for validating existing gene-trait relationships but also for generating new hypotheses. By integrating extensive biological data and employing powerful visualisation and AI-driven summarisation tools, KnetMiner significantly accelerates discovery in plant genomics, particularly for complex traits such as tomato firmness.

Accelerating Tomato Breeding with KnetMiner

Our collaboration with a leading plant breeding company has been instrumental in demonstrating KnetMiner’s capability to advance tomato breeding research. It highlights how our platform proactively identifies and validates key genetic targets. - Keywan Hassani-Pak, Founder and CEO

We’ve worked on these updates alongside the experts who use them most and believe they make KnetMiner a more powerful, user-friendly tool, tailored for those who need results fast.
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‍We welcome any and all positive feedback as we begin rolling out the all New KnetMiner.

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