Summary
- Profile Type
- Technology offer
- POD Reference
- TOGB20240322023
- Term of Validity
- 22 March 2024 - 22 March 2025
- Company's Country
- United Kingdom
- Type of partnership
- Commercial agreement with technical assistance
- Targeted Countries
- All countries
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General information
- Short Summary
- Utilising primarily RNA -Seq data and other omics in their AI engine, a UK startup identifies highly predictive biomarkers and generates prediction models for complex agricultural traits such as nitrogen-use efficiency, pesticide efficacy, and drought tolerance. Further applications will follow in animal husbandry etc. Commercial agreements with technical assistance are being sought with breeding, chemical, gene editing companies with pre-existing R&D capabilities.
- Full Description
-
Understanding the inner workings of agricultural plants and animals is important not just for breeding for varieties with bigger yields. The complex relation between the genetic makeup, the environment and the phenotype would allow for better breeding but also better agri tech, feed, chemicals etc. As the pressure is mounting on breeders, conventional DNA-based methodologies may no longer suffice.
A UK startup spun out from the prestigious Earlham Institute has made a significant leap beyond convention to utilise complex gene regulatory interactions and environmental influences. By identifying biomarker signatures from AI-driven analyses of RNA-Seq data, they provide highly accurate models for predicting traits influenced by numerous genes and fluctuating environmental conditions. This innovation addresses the significant challenges encountered by breeders and agrochemical companies in the development and understanding of complex traits.
A current project focusses on predicting complex traits associated with crop protection products. Utilising RNA-Seq data from glasshouse environments, the models forecast how these traits will perform in the field, bridging a traditional gap in agricultural research.
The platform enhances the trait prediction workflow, merging accuracy, scalability, and ease of use with real-time analysis, thereby empowering rapid, strategic agricultural decisions. With its general capacity to analyse large omics datasets, the technology serves a broad spectrum of applications.
Potential Applications:
• Crop Breeding: it enables predictive phenotyping of complex traits where DNA markers would struggle, accelerating the creation of superior crop varieties and livestock breeds.
• Agrochemicals: the platform identifies biomarkers associated with pesticide efficacy and other traits, enabling companies to predict the efficacy of new chemical compounds.
• Gene Editing: The biomarkers identified make potential candidates for gene editing to improve trait performance and the models can be used to predict the phenotypic effect after gene edits are made.
• Livestock Breeding: Using the platform, livestock breeding companies can predict complex traits such as disease resistance, feed efficiency, and overall health, contributing to the development of healthier and more productive breeds.
Generalisable AI capabilities adapt the methodology to various agricultural domains, from crops to livestock, handling the dense information contained within RNA-Seq and other omics datasets.
The company now offers commercial agreements with technical assistance to companies with existing R&D in breeding, agri chemicals, biostimulants, gene editing . - Advantages and Innovations
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Precision and Accuracy: the AI-driven method surpasses cutting-edge methods in accuracy, crucial for informed decisions in breeding and development.
Adaptability: the versatile platform is applicable across agricultural sectors as well as all crop and livestock species.
Predictive Capability: it predicts complex phenotypic traits unattainable with DNA markers, broadening predictive possibilities.
Efficiency in Selection: the platform enhances the product selection and breeding processes, quickly and accurately identifying top candidates. - Stage of Development
- Available for demonstration
- Sustainable Development Goals
- Goal 2: Zero Hunger
Partner Sought
- Expected Role of a Partner
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• Type of Partner Sought: forward-thinking companies within the agritech domain, including but not limited to, crop and livestock breeding, agrochemical, gene editing, and biostimulant companies. They are likely to be mid to large-scale with significant R&D capabilities.
• Specific Activity of Partner Sought: Ideal partners are those involved in the cutting-edge of breeding, agricultural input development, specifically looking to enhance trait or product selection processes, and are eager to embrace innovative AI solutions for complex trait prediction.
• Role of Partner Sought: to actively participate in pilot projects, supplying necessary RNA-Seq data and phenotypic trait data, and collaborating closely in the refinement and validation of the predictive modelling capabilities. - Type and Size of Partner
- Big companySME 50 - 249SME 11-49
- Type of partnership
- Commercial agreement with technical assistance
Dissemination
- Technology keywords
- 06003001 - Bioinformatics07001006 - Pesticides07001004 - Crop Production
- Market keywords
- 08001022 - Agricultural chemicals04008 - Genetic Engineering09005 - Agriculture, Forestry, Fishing, Animal Husbandry & Related Products
- Targeted countries
- All countries