Maximizing the potential for sustainable and durable resistance to the wheat yellow rust pathogen

Lead Research Organisation: John Innes Centre
Department Name: Crop Genetics

Abstract

Context of the research
Wheat provides approximately 20% of the calories and protein we consume each day and is a major staple across much of the developing world. As the world population continues to increase, the sustainability of wheat yields must be improved by minimizing losses produced by pathogens. Wheat yellow rust, caused by the fungus Puccinia striiformis (Pst), was recently dubbed one of "wheat's worst enemies" and continues to be a major threat to global food security. This disease is an historical and continuing threat to wheat production, capable of significant reductions in both grain quality and yield in susceptible varieties. The appearance of new and more aggressive Pst strains at the beginning of the 21st century and their rapid spread pose an increasing global threat to wheat production, and have resulted in severe yield losses in recent years.
The most economic and environmentally sustainable way to fight yellow rust is by developing wheat varieties that are genetically resistant to the disease. To date, scientist and breeders have deployed resistance genes into agriculture, but with little or no knowledge as to how the pathogen will adapt or respond to them. This inherently 'blind' and inefficient approach has meant that few genes have remained effective in controlling the disease over time. Basically our lack of knowledge of the pathogen's biology and characteristics has meant that we've been fighting with one hand tied behind our backs.

Aims and objectives
Recent innovations in sequencing technologies, combined with increased knowledge of pathogens in other species, provide us with the unprecedented opportunity to start understanding what makes yellow rust such a devastating disease. We propose to use these new technologies to access the complete DNA sequence of multiple strains of the yellow rust pathogen. We will sequence the most current Pst strains from Africa, India and the UK and also go back in time by sequencing historic collections of yellow rust. These strains, which until now have been stored in the cold, tell the story of how the pathogen has changed in history to become more aggressive and overcome wheat varieties that were thought at the time to be resistant. Sequencing will allow us to identify these changes at the DNA level. Understanding and interpreting these changes will provide the context of how wheat varieties and the fungus have co-evolved across three continents. This information will constitute a very powerful framework to identify wheat genes that will stand a better chance at maintaining their resistance against yellow rust in the future. We will use this knowledge to characterize and introduce new sources of yellow rust resistance into modern wheat varieties which are adapted to the different environments. Through this work, we also seek to create new partnerships between researchers and enhance the scientific capabilities of all partners.

Potential applications and benefits
This project will provide insight into how the wheat yellow rust pathogen has evolved to overcome previously effective wheat resistance genes and use this information to develop more sustainable strategies for the future. We will work with local breeders to deploy these new resistance genes which will lead to the development of locally adapted wheat varieties with improved potential to maintain resistance in farmers' fields. These improved varieties will have profound implications from a social, economic and environmental perspective. These varieties should improve the sustainability of food crop production systems and contribute to the alleviation of hunger and poverty of small-holder farmers by reducing the risk of crop failure, increasing profit margins, reducing fungicide applications, protecting yield, and extending the life of varieties which farmers have adopted. These varieties should ultimately translate into increased food security and opportunities to improve farmer income.

Technical Summary

Wheat provides 20% of the calories consumed by humankind and is a major staple across Africa and Asia. Wheat yellow rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most devastating diseases of wheat worldwide and the appearance of new and more aggressive races has resulted in severe yield losses in recent years. The most sustainable strategy to manage yellow rust is to breed broad-spectrum disease resistance into wheat. To date, resistance genes have been identified, bred, and deployed in agriculture without detailed knowledge of the effectors they are sensing, an inherently 'blind' and inefficient approach. Central to the development of more effective breeding strategies is a better understanding of Pst pathogenicity, virulence factors, and their evolution. However, progress in these areas has been slow and hampered by the lack of Pst genome sequence information. The overall aim of this proposal is to understand the molecular basis of Pst pathogenicity and exploit this information to design effective breeding strategies that maximize the potential for durable disease resistance in the field. The objectives of this proposal are to:
1. Establish a Pst population genomics platform
2. Characterize the pathogenicity arsenal of Pst
3. Evaluate Triticeae germplasm for Pst resistance
4. Fine map and deploy resistance genes which maximize potential for durable resistance
5. Develop and enhance scientific capabilities of Southern partners

This project will provide insight into how the wheat yellow rust pathogen has overcome previously effective R genes, identify and catalogue the effector repertoires of Pst, and identify closely linked markers for R genes with potential for durable resistance. This will lead to the development of locally adapted wheat varieties with improved potential to express durable resistance in the field, improving the sustainability of food crop production systems for small holder farmers.

Planned Impact

The most important impact of this research is the molecular understanding of the pathogenicity of the wheat yellow rust fungus, Puccinia striiformis (Pst); the identification and genetic characterization of resistance sources with broad spectrum recognition specificities; and the deployment of these resistances into high value breeding lines using tightly linked genetic markers. This project will lead to the development of locally adapted wheat varieties with improved potential to express durable resistance in the field compared to traditional breeding approaches. Beneficiaries will include wheat breeders globally, the public sector programmes in Ethiopia, Kenya and India, and small-holder farmers in developing countries, via more sustainable crop productions systems associated with genetically resistant varieties. These beneficiaries will gain from this research by several means, all of which are centred on more sustainable crop production practices.

The identification and functional profiling of resistance genes with broad spectrum recognition specificities will allow breeders to deploy strategic gene combinations in their new varieties. This will have important benefits for breeders who will be able to extend the life of desirable varieties as they should remain resistant over longer periods of time. The delivery of tightly linked genetic markers will also make this process more efficient and will enable them to build pre-breeding germplasm or parental lines with stacked gene combinations.

At the same time, this will benefit small scale farmers who will be able to adopt and grow varieties with less risk of crop failure due to the appearance of new Pst races. These broad-spectrum resistant varieties will also reduce fungicide applications while protecting yield. This will benefit farmers directly by reducing or even avoiding exposure to fungicides and will translate into increasing income by reducing production costs associated to these applications and protecting/increasing yields. In many cases, farmers cannot afford fungicides, so genetic resistance is the only viable option to avoid crop failure.

The national breeding and science programmes from all countries involved will benefit by the investment in infrastructure and capacity development activities which are included in this project. We strongly believe in the forging of mutually beneficial partnerships and that training the next-generation of crop scientist is a key element in establishing these links that will secure long term relations. This proposal brings together a unique combination of disciplines that will provide an exciting training ground for a cadre of excellent young scientists. The resulting innovation and training will provide the next generation of skilled crop scientist, with benefits beyond the immediate outcomes of this project.

In summary, the combination of these factors will help enhance food security, develop more sustainable agriculture practices, increase opportunities for small scale farmers to improve their income, and establish long-term working relationships between the different partners involved.

Publications

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publication icon
Bevan MW (2013) Genomics reveals new landscapes for crop improvement. in Genome biology

 
Title Additional file 3: of The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression 
Description Expression data (Transcripts per million (TPM) values) for significantly differentially expressed genes was normalized and clustered into sets of genes with qualitatively similar expression profiles using the mini batch k-means algorithm, resulting in 7 clusters for wheat. (EPS 1612Â kb) 
Type Of Art Film/Video/Animation 
Year Produced 2016 
URL https://springernature.figshare.com/articles/figure/Additional_file_3_of_The_host-pathogen_interacti...
 
Title Additional file 3: of The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression 
Description Expression data (Transcripts per million (TPM) values) for significantly differentially expressed genes was normalized and clustered into sets of genes with qualitatively similar expression profiles using the mini batch k-means algorithm, resulting in 7 clusters for wheat. (EPS 1612Â kb) 
Type Of Art Film/Video/Animation 
Year Produced 2016 
URL https://springernature.figshare.com/articles/figure/Additional_file_3_of_The_host-pathogen_interacti...
 
Title Additional file 4: of The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression 
Description Expression data (TPM values) for significantly differentially expressed genes was normalized and clustered into sets of genes with qualitatively similar expression profiles using the mini batch k-means algorithm, resulting in 8 clusters for PST. (EPS 18763Â kb) 
Type Of Art Film/Video/Animation 
Year Produced 2016 
URL https://springernature.figshare.com/articles/figure/Additional_file_4_of_The_host-pathogen_interacti...
 
Title Additional file 4: of The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression 
Description Expression data (TPM values) for significantly differentially expressed genes was normalized and clustered into sets of genes with qualitatively similar expression profiles using the mini batch k-means algorithm, resulting in 8 clusters for PST. (EPS 18763Â kb) 
Type Of Art Film/Video/Animation 
Year Produced 2016 
URL https://springernature.figshare.com/articles/figure/Additional_file_4_of_The_host-pathogen_interacti...
 
Title Additional file 5: of The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression 
Description Expression dynamics of all the genes in the predicted defensome compared using Monte Carlo simulations drawn from the null model of uniformly distributed gene vectors. (EPS 1858Â kb) 
Type Of Art Film/Video/Animation 
Year Produced 2016 
URL https://springernature.figshare.com/articles/figure/Additional_file_5_of_The_host-pathogen_interacti...
 
Title Additional file 5: of The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression 
Description Expression dynamics of all the genes in the predicted defensome compared using Monte Carlo simulations drawn from the null model of uniformly distributed gene vectors. (EPS 1858Â kb) 
Type Of Art Film/Video/Animation 
Year Produced 2016 
URL https://springernature.figshare.com/articles/figure/Additional_file_5_of_The_host-pathogen_interacti...
 
Description • We have sequenced gDNA of 52 PST isolates from Europe (34), East Africa (9), India (4), Pakistan (2) and China (3) at ~50x coverage.

• We have sequenced 9 time points (x3 reps) for an infection time course with UK PST isolate. We have used this data to re-annotate the gene models to make best use of the transcriptome data. The more in-depth analysis of this data is currently on-going.

• We have evaluated over 500 Watkins accessions for yellow, leaf and stem rust in East-Africa, India and UK. Based on the phenotypic evaluations we have chosen 39 accessions of high priority due to their strong resistance or due to the consistent moderate resistance across regions. These 39 accessions have been crossed to AvocetS to develop mapping populations to be screened within objective 4. A subset of the populations (5) will be available to screen as F2:3 families in 2014, whereas the rest are being developed by single seed descent into populations

• We conducted a 5-day "soft-skills" workshop in Njoro in late August 2014. The workshop was a great success as evaluated by the 15 participants. These included SCPRID PhD students, several Kenyan PhD and MSc students, and members of other SCPRID projects (PEARL awardee; SPCRID striga project).

• We have trained 5 PhD students within the project.

• We have cloned three yellow rust resistance genes (Yr5, Yr7 and YrSP). This is the first characterisation of all-stage yellow rust resistance genes from bread wheat. We resolve the relationship between these three genes, a 45-year question in the field, by showing that Yr5 and YrSP are two alleles of the same genes, whereas Yr7 is a closely related paralog to Yr5/YrSP. All three immune receptors share the presence of an 'integrated domain'. This work suggests that different pathogen recognition specificities could be engineered through genome editing of these novel gene architectures.
Exploitation Route Markers and gene knowledge being used by breeders.
Sectors Agriculture

Food and Drink

 
Description The technology developed in this grant has now been implemented within the ADHB and Defra funded UK Cereal Pathogen Virulence Survey (UKCPVS) as part of the monitoring of wheat rust diseases.
First Year Of Impact 2015
Sector Agriculture, Food and Drink
Impact Types Societal

Economic

 
Description Workshop on Soft Skills, BGRI Meeting
Geographic Reach Multiple continents/international 
Policy Influence Type Influenced training of practitioners or researchers
Impact Workshop on Soft Skills, BGRI Meeting
 
Description Leveraging genetic innovations for accelerated breeding of climate resilient and nutritious crops
Amount £1,300,000 (GBP)
Organisation Foreign Commonwealth and Development Office (FCDO) 
Sector Public
Country United Kingdom
Start 01/2024 
End 12/2026
 
Description Strategic Training Award for Research Skills
Amount £100,000 (GBP)
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 02/2018 
End 02/2020
 
Title Additional file 1: of The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression 
Description Contains supplementary Tables S1-S21. Microsoft Excel Workbook containing twenty-one worksheets. Table S1: RNA-based sequence alignments against wheat and PST-130 reference genomes, using data from infection of wheat (Vuka) with PST 87/66. Table S2: Depth of coverage when RNA-seq data aligned to previously published PST-130 gene models. Table S3: Depth of coverage when RNA-seq data aligned to PST gene models generated herein. Table S4: Comparison of PST-130 gene models and those generated herein. Table S5: Wheat gene annotations. Table S6: 4,307 wheat triplets mined from Ensembl Plants Triticum aestivum portal. Table S7: 239 triplets identified as wheat core eukaryotic genes. Table S8: Mean correlation of expression vectors and mean relative difference comparing Cufflinks, RSEM, Salmon, and Kallisto. Table S9: Gene expression analysis of susceptible wheat cultivar Vuka infected with PST 87/66. Table S10: Gene expression analysis of a resistant wheat line infected with PST 87/66. Table S11: Gene expression analysis of PST on Vuka . Table S12: KEGG pathway memberships displaying significant enrichment in each cluster for the 7 wheat clusters. Table S13: GO term annotations displaying significant enrichment for the 7 wheat clusters. Table S14: KEGG pathway memberships displaying significant enrichment for the 8 PST clusters. Table S15: GO term annotations displaying significant enrichment for the 8 PST clusters. Table S16: RNA-based sequence alignments against wheat and PST-130, using data from infection of wheat (Avocet line containing Yr5) with PST 87/66. Table S17: Transcripts per million (TPM) values for homologs of the defensome in a susceptible and resistant interaction with PST 87/66. Table S18: TPM values for PST vesicle trafficking components. Table S19: Summary of TPM values for PST vesicle trafficking components. Table S20: TPM values for host genes from a susceptible interaction with PST 87/66. Table S21: TPM values for host genes from a resistant interaction with PST 87/66. (XLSX 35.6 mb) 
Type Of Material Database/Collection of data 
Year Produced 2016 
Provided To Others? Yes  
URL https://springernature.figshare.com/articles/dataset/Additional_file_1_of_The_host-pathogen_interact...
 
Title Additional file 1: of The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression 
Description Contains supplementary Tables S1-S21. Microsoft Excel Workbook containing twenty-one worksheets. Table S1: RNA-based sequence alignments against wheat and PST-130 reference genomes, using data from infection of wheat (Vuka) with PST 87/66. Table S2: Depth of coverage when RNA-seq data aligned to previously published PST-130 gene models. Table S3: Depth of coverage when RNA-seq data aligned to PST gene models generated herein. Table S4: Comparison of PST-130 gene models and those generated herein. Table S5: Wheat gene annotations. Table S6: 4,307 wheat triplets mined from Ensembl Plants Triticum aestivum portal. Table S7: 239 triplets identified as wheat core eukaryotic genes. Table S8: Mean correlation of expression vectors and mean relative difference comparing Cufflinks, RSEM, Salmon, and Kallisto. Table S9: Gene expression analysis of susceptible wheat cultivar Vuka infected with PST 87/66. Table S10: Gene expression analysis of a resistant wheat line infected with PST 87/66. Table S11: Gene expression analysis of PST on Vuka . Table S12: KEGG pathway memberships displaying significant enrichment in each cluster for the 7 wheat clusters. Table S13: GO term annotations displaying significant enrichment for the 7 wheat clusters. Table S14: KEGG pathway memberships displaying significant enrichment for the 8 PST clusters. Table S15: GO term annotations displaying significant enrichment for the 8 PST clusters. Table S16: RNA-based sequence alignments against wheat and PST-130, using data from infection of wheat (Avocet line containing Yr5) with PST 87/66. Table S17: Transcripts per million (TPM) values for homologs of the defensome in a susceptible and resistant interaction with PST 87/66. Table S18: TPM values for PST vesicle trafficking components. Table S19: Summary of TPM values for PST vesicle trafficking components. Table S20: TPM values for host genes from a susceptible interaction with PST 87/66. Table S21: TPM values for host genes from a resistant interaction with PST 87/66. (XLSX 35.6 mb) 
Type Of Material Database/Collection of data 
Year Produced 2016 
Provided To Others? Yes  
URL https://springernature.figshare.com/articles/dataset/Additional_file_1_of_The_host-pathogen_interact...
 
Title Additional file 2: of The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression 
Description Annotation of updated PST gene models generated herein. (TSV 21048Â kb) 
Type Of Material Database/Collection of data 
Year Produced 2016 
Provided To Others? Yes  
URL https://springernature.figshare.com/articles/dataset/Additional_file_2_of_The_host-pathogen_interact...
 
Title Additional file 2: of The host-pathogen interaction between wheat and yellow rust induces temporally coordinated waves of gene expression 
Description Annotation of updated PST gene models generated herein. (TSV 21048Â kb) 
Type Of Material Database/Collection of data 
Year Produced 2016 
Provided To Others? Yes  
URL https://springernature.figshare.com/articles/dataset/Additional_file_2_of_The_host-pathogen_interact...
 
Title Darwin: an amino acid sequence collection of complete proteomes from eukaryotes with different phylogenetic affinities (v. 03_2020_137) 
Description Background Every time we find an interesting gene in an organism of interest, the first question is often "how widely is this gene distributed in the eukaryotic kingdom?". Naturally, one could use NCBI BLAST search against the non-redundant sequence database provided by GenBank to answer this question. However, it can be cumbersome to parse the results and assign them to taxonomic units. It is also not straightforward to get an overview of which eukaryotic groups are represented in the results. Top BLAST hits can be crowded with sequences from closely-related organisms making it difficult gain an overview of the overall distribution across eukaryotes. To streamline this process, we developed an in-house database of complete eukaryotic proteomes. We tagged each sequence with a eukaryotic group handle (two-character symbol) and combined them into a single data set searchable by standalone BLAST on one's own computer. We named this data set "Darwin" to reflect the diverse nature of the sequences it contains. Methods We downloaded predicted proteomes in FASTA format from different sources such as GenBank, Joint Genome Institute (Depart of Energy, USA), Broad Institute (Massachusetts Institute of Technology, USA), Phytozome and a number of other specialized websites catering for a specific organism such as the Arabidopsis Information Resource (TAIR), or the Saccharomyces Genome Database (SGD). All the organisms we included in Darwin are listed in Table 1. To reduce redundancy, we took care not to include the same species more than once unless subspecies were known to show wide diversity. Each sequence header was tagged with a eukaryotic group handle composed of two-character symbols (based on Keeling et al., 2005). These handles clearly appear in BLAST output and can be parsed easily. We combined sequences from all proteomes into a single data set and named it "Darwin". Results The current version of Darwin (v. 03_2020_137) contains 2,601,132 amino acid sequences from 137 eukaryotes (Table 1, Data file 1). The sizes of the proteomes were diverse, ranging from ~4000 sequences in some alveolates to 60,000-76,000 in plants. Darwin represents most of the supergroups of eukaryotic kingdom described in Keeling et al., (2005) except those in Rhizaria whose genomes were not available at the time of data set construction. The data set contains larger numbers of proteomes from fungi and plants reflecting areas of interest in our group. Conclusions Darwin is provided as a text fasta file that can be formatted for BLAST searches on standalone computers. The results from the BLAST searches can be parsed to determine how widely a gene of interest is distributed among different eukaryotes. Simple counting of the eukaryotic group handles would also yield an overview of the distribution across taxa. Darwin is also useful for rapidly finding out whether a gene is missing in particular taxa. Reference Keeling PJ, Burger G, Durnford DG, Lang BF, Lee RW, Pearlman RE, Roger AJ, Gray MW (2005) The tree of eukaryotes. Trends Ecol. Evol. 20: 670-676 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://zenodo.org/record/3699563
 
Title Darwin: an amino acid sequence collection of complete proteomes from eukaryotes with different phylogenetic affinities (v. 03_2020_137) 
Description Background Every time we find an interesting gene in an organism of interest, the first question is often "how widely is this gene distributed in the eukaryotic kingdom?". Naturally, one could use NCBI BLAST search against the non-redundant sequence database provided by GenBank to answer this question. However, it can be cumbersome to parse the results and assign them to taxonomic units. It is also not straightforward to get an overview of which eukaryotic groups are represented in the results. Top BLAST hits can be crowded with sequences from closely-related organisms making it difficult gain an overview of the overall distribution across eukaryotes. To streamline this process, we developed an in-house database of complete eukaryotic proteomes. We tagged each sequence with a eukaryotic group handle (two-character symbol) and combined them into a single data set searchable by standalone BLAST on one's own computer. We named this data set "Darwin" to reflect the diverse nature of the sequences it contains. Methods We downloaded predicted proteomes in FASTA format from different sources such as GenBank, Joint Genome Institute (Depart of Energy, USA), Broad Institute (Massachusetts Institute of Technology, USA), Phytozome and a number of other specialized websites catering for a specific organism such as the Arabidopsis Information Resource (TAIR), or the Saccharomyces Genome Database (SGD). All the organisms we included in Darwin are listed in Table 1. To reduce redundancy, we took care not to include the same species more than once unless subspecies were known to show wide diversity. Each sequence header was tagged with a eukaryotic group handle composed of two-character symbols (based on Keeling et al., 2005). These handles clearly appear in BLAST output and can be parsed easily. We combined sequences from all proteomes into a single data set and named it "Darwin". Results The current version of Darwin (v. 03_2020_137) contains 2,601,132 amino acid sequences from 137 eukaryotes (Table 1, Data file 1). The sizes of the proteomes were diverse, ranging from ~4000 sequences in some alveolates to 60,000-76,000 in plants. Darwin represents most of the supergroups of eukaryotic kingdom described in Keeling et al., (2005) except those in Rhizaria whose genomes were not available at the time of data set construction. The data set contains larger numbers of proteomes from fungi and plants reflecting areas of interest in our group. Conclusions Darwin is provided as a text fasta file that can be formatted for BLAST searches on standalone computers. The results from the BLAST searches can be parsed to determine how widely a gene of interest is distributed among different eukaryotes. Simple counting of the eukaryotic group handles would also yield an overview of the distribution across taxa. Darwin is also useful for rapidly finding out whether a gene is missing in particular taxa. Reference Keeling PJ, Burger G, Durnford DG, Lang BF, Lee RW, Pearlman RE, Roger AJ, Gray MW (2005) The tree of eukaryotes. Trends Ecol. Evol. 20: 670-676 
Type Of Material Database/Collection of data 
Year Produced 2020 
Provided To Others? Yes  
URL https://zenodo.org/record/3699564
 
Title Wheat Training 
Description This website provides background information and practical resources to help both budding wheat scientists as well as researchers looking to expand their work into wheat. There is a need to improve crops to feed the world's growing population with the backdrop of climate change. Translation of fundamental plant biology research (e.g. from Arabidopsis thaliana) into crops such as wheat provides a potential route to deal with this challenge. However learning even simple tasks such as growing and crossing wheat plants requires time and effort, while material and methods sections in published articles are often short and cannot substitute teaching aids. This is also true for more complex topics such as the genomics aspect of wheat. 
Type Of Material Database/Collection of data 
Year Produced 2016 
Provided To Others? Yes  
Impact >4,500 sessions from >2,700 users 
URL http://www.wheat-training.com/
 
Description A meeting between CIMMYT and DFW funded by BMGF to discuss collaboration projects 
Organisation International Centre for Maize and Wheat Improvement (CIMMYT)
Country Mexico 
Sector Charity/Non Profit 
PI Contribution I organised a meeting funded by Bill and Melinda Gates Foundation brought together members of the BBSRC's coordinated wheat programme (Designing Future Wheat) with members of CIMMYT (who breed wheat for the resource poor in the developing world), discuss potential opportunities for interaction. These opportunities are taken forward by writing proposals for Newton , GCRF or IWYP funding calls
Collaborator Contribution See above
Impact This interaction is still ongoing between members of BBSRC's coordinated wheat programme (Designing Future Wheat) and researchers within CIMMYT with proposals being written for IWYP and Newton calls
Start Year 2018
 
Description Bayer 
Organisation Bayer
Department Bayer CropScience Ltd
Country United Kingdom 
Sector Private 
PI Contribution Wheat genetics and genomics
Collaborator Contribution Wheat breeding and molecular knowledge
Impact joint projects
Start Year 2012
 
Description Bayer 
Organisation Bayer
Department Bayer CropScience Ltd
Country United Kingdom 
Sector Private 
PI Contribution Wheat genetics and genomics
Collaborator Contribution Wheat breeding and molecular knowledge
Impact joint projects
Start Year 2012
 
Description CGIAR 
Organisation International Center for Agricultural Research in the Dry Areas
Country Syrian Arab Republic 
Sector Charity/Non Profit 
PI Contribution Provide molecular markers for yellow rust and blast resistance genes; provide germplasm with improved traits.
Collaborator Contribution provide field phenotyping and delivery into wheat cultivars
Impact n/a
Start Year 2013
 
Description CGIAR 
Organisation International Centre for Maize and Wheat Improvement (CIMMYT)
Country Mexico 
Sector Charity/Non Profit 
PI Contribution Provide molecular markers for yellow rust and blast resistance genes; provide germplasm with improved traits.
Collaborator Contribution provide field phenotyping and delivery into wheat cultivars
Impact n/a
Start Year 2013
 
Description KWS 
Organisation KWS UK
Country United Kingdom 
Sector Private 
PI Contribution Genetics and genomics
Collaborator Contribution Breeder know how and germplasm
Impact joint projects
Start Year 2009
 
Description Punjab Agricultural University 
Organisation Punjab Aricultural University
Country India 
Sector Academic/University 
PI Contribution Know how on wheat genomics and genetics, training.
Collaborator Contribution Gernplasm, local knowledge
Impact Have helped partners implement marker technology.
Start Year 2011
 
Description RAGT 
Organisation RAGT Seeds
Country United Kingdom 
Sector Private 
PI Contribution Genetics and genomics
Collaborator Contribution Wheat germplasm and know how
Impact Shared projects
Start Year 2009
 
Title GENES ASSOCIATED WITH RESISTANCE TO WHEAT YELLOW RUST 
Description The invention relates to genes associated with disease resistance in plants. According to an aspect of the invention is provided an isolated nucleic acid encoding a nucleotide-binding and leucine-rich repeat (NLR) polypeptide comprising a zinc-finger BED domain, wherein expression of the NLR polypeptide in a plant confers or enhances resistance of the plant to a fungus, for example wheat yellow (stripe) rust fungus Puccinia striiformisi f. sp. tritici. 
IP Reference WO2019197408 
Protection Patent application published
Year Protection Granted 2019
Licensed No
Impact Wheat yellow rust resistance genes.
 
Description Agricultural Industries Confederation 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact Agribusiness Meeting: A step change in plant breeding to achieve a UK competitive advantage
Year(s) Of Engagement Activity 2016
 
Description Australian, UK scientists solve 30-year wheat rust genetics puzzle 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Media (as a channel to the public)
Results and Impact Australian, UK scientists solve 30-year wheat rust genetics puzzle
Year(s) Of Engagement Activity 2018
URL https://www.eurekalert.org/pub_releases/2018-08/uos-aus082418.php
 
Description Borlaug Dialogue 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Supporters
Results and Impact Bolaug Dialogue
Year(s) Of Engagement Activity 2017
 
Description DBT-BBSRC Smart Agriculture Conclave 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Policymakers/politicians
Results and Impact DBT-BBSRC Smart Agriculture Conclave
Year(s) Of Engagement Activity 2017
 
Description Discussion Norman Lamb, MP 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Policymakers/politicians
Results and Impact Discussion Norman Lamb, MP
Year(s) Of Engagement Activity 2017
 
Description Discussion with Gov Office Science 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Policymakers/politicians
Results and Impact Discussion with Gov Office Science
Year(s) Of Engagement Activity 2017
 
Description Gatbsy Plant Science Students 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact Can wheat genomics help alleviate food insecurity?
Year(s) Of Engagement Activity 2017
 
Description JIC Open day 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact JIC Open Day
Year(s) Of Engagement Activity 2018
 
Description Penny Mordaunt, Secretary of State for International Development. 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Policymakers/politicians
Results and Impact Penny Mordaunt, Secretary of State for International Development.
Year(s) Of Engagement Activity 2018
 
Description Rachel Lambert, Senior Livelihoods Adviser, Agriculture Research DFID 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Policymakers/politicians
Results and Impact Rachel Lambert, Senior Livelihoods Adviser, Agriculture Research DFID
Year(s) Of Engagement Activity 2018
 
Description Science and Faith 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact Is it ethical to oppose modern plant breeding technologies
Year(s) Of Engagement Activity 2017