Gene Discovery

We use NLRseek™ and PRRseek™, our proprietary gene discovery platforms, to rapidly and efficiently identify and validate disease resistance genes from broad plant collections.

At a Glance

Crop(s): Any crop, regardless of reference genome
Significant Disease: A broad range
Region(s) Affected: Global
Loss/Costs: Crop diseases/pests account for up to 40% of total global yield loss with economic losses approaching $300 billion/yr
Project Lead: Helen Brabham
Collaborators: The Sainsbury Laboratory, Kaneka Corporation, University of Minnesota

2Blades technician James Houghton inside 2Blades' research lab
2Blades team member observing plant at research lab in Norwich, United Kingdom

The Challenge

Safeguarding the world’s food supply is the challenge of our lifetime. Crop disease and pests are among the most significant threats to our food supply, accounting for an estimated 40% of all global yield loss among major crops. This has existential consequences, ranging from severe undernourishment, political instability, and economic losses approaching $300 billion every year.

Solutions must target commercial agriculture, which produces at large scale, and smallholder farmers in low- and middle-income countries, who play a crucial role in crop production and feeding large populations but often lack access to the latest innovations.

NLRseek™ can identify more genes using fewer resources in a less amount of time compared to conventional methods

The Strategy

We are applying our proprietary gene discovery platforms, NLRseek™ and PRRseek™, to build an unprecedented toolkit comprised of a massive anthology of genes, phenotypic data, and powerful AI tools to rapidly identify and validate disease resistance genes for cereals, legumes, potatoes, and other important crops.

This resistance gene toolkit complements conventional chemical sprays and breeding, which are akin to analog methods, whereas NLRseek™ and PRRseek™ present a large-scale, digital approach to plant breeding.

We have screened a 1,000 gene wheat array against 5 diverse pathogens* and succeeded in identifying and validating hundreds of resistance genes in greenhouse and field trials. To date, results include 19 new genes that protect wheat from deadly stem rust, the cause of epidemics since Roman times, and 82 new genes and counting for wheat stripe rust - a 1,640% increase!

*NLRseek™ has successfully identified and validated genes against the following pathogens:

  1. stem rust (Puccinia graminis f. sp. tritici)

  2. stripe rust (Puccinia striiformis f. sp. tritici)

  3. leaf rust (Puccinia triticina)

  4. wheat blast (Magnaporthe oryzae pathotype Triticum (MoT))

  5. Fusarium head blight (Fusarium graminearum)

Helen Brabham, NLRseek™ Team Lead, examining rust-resistant wheat at our lab in Norwich, United Kingdom

Helen Brabham, NLRseek™ Team Lead, examining rust-resistant wheat at our lab in Norwich, UK.

The Science

As pathogens infect plants, they release effector proteins to suppress plant defenses. Plants have an immune system and contain immune receptors that recognise pathogen invasion. Nucleotide-binding Leucine-rich Repeat (NLR) proteins are plant receptors that recognize effector proteins and trigger a strong immune response. NLRs are highly specific, so finding the right NLR that recognises the variation of effectors within and between pathogen species is a major challenge. Plants with multiple NLR receptors against a pathogen can have strong, long-lasting resistance to disease – protecting crops and reducing the need for crop chemicals.

Many plants succumb to disease as they do not have the right NLRs for major pathogens. Since the earliest days of agriculture, farmers have found they can select resistant plants. Through plant science, we have come to understand that in this way NLRs were bred into crops, and today, with modern breeding tools, individual specific NLRs can be precisely selected and introduced into plants. Still, conventional approaches for identifying functional NLRs are labor-intensive and expensive.

The NLRseek™ program builds on scientific insight from the research group of Dr. Matt Moscou, observing functional NLRs are highly expressed in plant tissues. This functional signature enables rapid prediction of NLR genes using low-cost sequencing technology.

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