Uncovering DELLA protein targets in wheat

Understanding how the Green Revolution genes in wheat regulate diverse growth and development processes remains a key challenge in plant research. The gibberellin (GA) hormone influences traits such as cell elongation, nitrogen remobilisation, and disease resistance by triggering the degradation of DELLA proteins - growth repressors that modulate transcriptional networks indirectly.

During the Green Revolution, wheat breeders selected for mutant DELLA proteins resistant to GA-induced degradation, resulting in semi-dwarf plants with improved lodging resistance and higher yields. However, these mutations also introduced trade-offs, such as reduced nitrogen use efficiency and poor seedling emergence. While studies in Arabidopsis and barley suggest DELLA proteins regulate different processes through specific downstream targets, the mechanisms in wheat remain largely unknown.

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THE QUESTION
How do DELLA downstream targets impact NUE and seedling emergence?
Let’s start by breaking up the root question, as answering smaller sets of questions can be simpler.
  • What are the downstream DELLA protein targets that regulate different developmental processes?
  • How do DELLA proteins control these targets within transcriptional networks?

  • Which targets offer the best opportunities for trait-specific improvements?
THE METHOD
Presence of DELLA genes in wheat cultivars
KnetMiner provides an integrated knowledge discovery approach to explore DELLA protein interactions in wheat. By leveraging its AI-driven literature review, cross-species network visualisation, and deep knowledge graphs, researchers can:

- Identify known and predicted DELLA target genes across species.
- Map transcriptional networks affected by DELLA protein stability.
- Discover potential targets for optimising nitrogen use efficiency, cell elongation, and other GA-dependent traits.
- Use KnetMaps to visualise regulatory networks, reducing the complexity of large-scale datasets.
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Further Results
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Conclusion
By applying KnetMiner’s advanced knowledge graph capabilities, researchers can gain new insights into DELLA target genes and their roles in wheat development. This can accelerate breeding strategies aimed at fine-tuning GA responses for improved crop performance while minimising trade-offs. The ability to prioritise candidate genes for experimental validation enables a more targeted approach to breeding higher-yielding, resource-efficient wheat varieties.

Testimonial from use case co-author at Nasa GeneLab

"KnetMiner has been a game-changer for our research. Its intuitive interface made it easy to uncover complex gene interactions we never knew existed. These insights have accelerated our ability to translate fundamental discoveries in Arabidopsis into practical tools for crop improvement. By identifying key genetic markers that are involved in plant response to spaceflight, this will significantly advanced humanities marker-assisted breeding programs and lay the groundwork for more efficient genetic engineering efforts to tailor crops for built environments in low earth orbit and beyond."

Dr. Richard Barker
Project Scientist @ Nasa GeneLab

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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