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14 ERA-CAPS: Mechanistic Analysis of Quantitative Disease Resistance in Brassica by Associative Transcriptomics

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

Abstract

Brassica napus, a major world-wide crop, comprises a range of crop types including oilseed rape (OSR), grown for edible and industrial oil, biodiesel, protein for animal feed as well as leaf and root vegetables. Diseases are a major factor limiting production, a threat increasing due to climate change and the imminent withdrawal of agrochemicals in Europe. Improved disease control is an urgent priority and breeders are increasingly using quantitative disease resistance (QDR), which is considered broad-spectrum and durable.

This research will identify the most useful QDR genes for OSR breeding and understand the mechanisms behind this to enable predictions of their effectiveness and durability. Our consortium combines the leading expertise on the major OSR pathogens, the latest research on defence mechanisms of resistance and expertise in association genetics to identify effective QDR genes. Our industrial partner, KWS, will provide expertise on deployment of QDR in the field and on the development of genetic markers for molecular breeding of improved OSR varieties.

We will identify resistance to the most important pathogens of OSR: Sclerotinia sclerotiorum, Verticillium spp, Leptosphaeria maculans, Alternaria brassicicola, Pyrenopeziza brassicae, and the model pathogens Pseudomonas syringae and Botrytis cinerea. A panel of 192 diverse B. napus lines will be screened for resistance against these pathogens in controlled environments and at KWS field trial sites. Schools will contribute in a 'citizen science' project and evaluate resistance at locations throughout Europe. In the same lines, we will quantify induced defence responses to conserved pathogen-associated molecular patterns (PAMPs). We will also quantify salicylic acid, lignin, phenylpropanoid, glucosinolate, and indole metabolites that are implicated in resistance mechanisms. Using association transcriptomics, we will identify resistance gene loci against multiple pathogens and understand how this relates to metabolite production and PAMP-triggered immunity.

To test hypotheses about their contribution to resistance, we include studies on specific genes. Whilst glucosinolates contribute to resistance they can reduce the quality of seed. GTR1 and GTR2 are transporters in Arabidopsis that control the allocation of glucosinolates to seeds. We will test gtr1 gtr2 mutants for fitness and create gtr TILLING mutants in Brassica rapa (B. napus A genome) to measure the glucosinolate partitioning between leaves and seed. The work could enable development of OSR with high leaf glucosinolate content for resistance, without compromising seed quality. We will introduce tomato receptor Ve1 into B. napus and assess its ability to mediate resistance against Verticillium wilt.

This research will lead to more sustainable production of OSR, with higher productivity through lower vulnerability to biotic stress and less reliance on chemical inputs.

Technical Summary

Oilseed rape (OSR, Brassica napus) is a major crop worldwide, producing edible oil, biodiesel and protein for animal feed. Diseases are a major factor limiting OSR production and improved control is an urgent priority. Breeders are increasingly using quantitative disease resistance (QDR) which is considered broad-spectrum and durable. This proposal addresses the current gap in our knowledge which is the identification of the most useful QDR for breeding.

The first layer of active defence in plants is based on the perception of pathogen (or microbe) associated molecular patterns (PAMPs/MAMPs) leading to PAMP-triggered immunity (PTI). PAMPs are essential molecules, conserved in entire kingdoms of microbes, and are recognised by pattern recognition receptors (PRRs) in plants. Within ERA-PG (PRR-CROP) we developed methods for studying PTI in Brassica crops.

We will identify gene loci contributing to QDR against the most important pathogens of OSR using the novel method of associative transcriptomics (AT), developed at JIC in B. napus by the Bancroft group. Using a 'B. napus diversity panel' of 192 diverse lines we will quantify resistance to the most important pathogens: Sclerotinia sclerotiorum, Verticillium spp, Leptosphaeria maculans, Alternaria brassicicola, Pyrenopeziza brassicae, Pseudomonas syringae and Botrytis cinerea. We will quantify induced defence responses to PAMPs and measure salicylic acid, lignin, phenylpropanoid, glucosinolate, and indole metabolites that are implicated in resistance mechanisms. Using AT, we will identify resistance gene loci against multiple pathogens and understand how this relates to metabolite production and PAMP-triggered immunity. We will also investigate glucosinolate partitioning between leaves and seed using mutants of GTR1 and GTR2 transporters and introduce tomato receptor Ve1 into B. napus and assess its ability to mediate resistance against Verticillium wilt.

Planned Impact

Production of oilseed rape is rapidly increasing in the EU, where it provides the primary source of edible oil, biodiesel and high-protein animal feed. OSR is at risk from diseases which currently account for losses of 10-20%. With imminent EU restrictions on the use of fungicides, the breakdown of R-genes and climate change, novel approaches to disease control are essential and the aim of this timely project. The economy will benefit because plant breeders will be able to develop new varieties with improved resistance, strengthening Europe's leadership in sustainable agriculture. Farmers will become more competitive with new varieties that they can grow with reduced inputs. Advisors, consultants and levy boards which fund strategic research will benefit through new knowledge about the most appropriate lines to select. The environment will benefit because there will be reduced inputs, and more efficient use of fertilizers and land. This will also benefit policymakers through reducing the carbon footprint and helping governments achieve climate change mitigation (Hughes, et al. 2011). Society will benefit through improved environment and economy and production of safer food. This project stimulates innovation through application of advanced technology to agriculture, contributes to job creation, and provides an exciting training opportunity for the next generation of crop scientists who will further strengthen the European bio-economy.

The consortium is in an exceptional position to achieve impact, with its established strong links with the European breeding industry, farmers, policy makers and the wider agricultural community. We will meet at least annually to review progress and agree knowledge transfer activities. We will regularly present our work at established dissemination events such as the annual OREGIN, Brassica Research Community and Cereals' meetings, where most of the European breeding industry and levy board stakeholders such as HGCA are present. We will disseminate results to industry at the Business Council at the Faculty of Biology and Environmental Protection (Lodz), and at the Polish Federation of Biotechnology. We will write popular articles for the trade press such as Farmers Guardian and Farmers Weekly, publish our research in open-access scientific journals and present our results to academics at international conferences such as the Molecular Plant-Microbe Interactions meeting, Eucarpia and Crucifer Genetics Workshop. We will present our work to the public at events such as the annual Friends of John Innes Centre crop walk and the Fascination of Plants day at Wageningen UR. With a 'Sparking Impact' award, CR is working with the Knowledge Exchange and Commercialisation team at JIC on delivery of scientific output through social media, enabling us to reach and quantify new audiences. We will reach schoolchildren to convey the excitement of plant science as a University and career option. We will work with the Teacher Scientist Network to deliver an impact module in 'citizen science' to augment our research on resistance at locations in each member country. Results from this will be disseminated by TSN and the members of this consortium.

Publications

10 25 50
 
Description Oilseed rape (OSR, Brassica napus L.) is a major crop grown worldwide for production of edible and industrial oil, biodiesel and protein containing animal feed. Several diseases may threaten or limit the production and crop protection measures are not always sufficient to safeguard harvests. The aim of the research was to identify and characterise resistance to the most important diseases of OSR so that varieties can be improved. The focus of the project was on Quantitative Disease Resistance (QDR) as this is expected to provide durable control. Using a collection of genetically diverse cultivars, we screened for resistance to the most important diseases of OSR: Sclerotinia, Light leaf Spot, Phoma stem canker, Verticillium, Grey mould and the model bacterial pathogen, Pseudomonas syringae. We also measured immune and biochemical responses in the plants to determine the potential mechanisms of resistance and the underlying genes contributing to this. The results were used to perform a genome-wide association study (GWAS) based on expressed genes known as 'associative transcriptomics'. The analysis enabled the identification of gene loci contributing to disease resistance and provides indications about the underlying mechanisms for this. We are keen to encourage the next generation of scientists and established a programme for schools in several locations throughout Europe as part of our project. The schools received seed from our collection of OSR cultivars and performed measurements of growth and development under different conditions. This is the first comprehensive analysis of QDR to multiple diseases in OSR and the potential mechanisms involved.
Exploitation Route The work will enable associations between QDR to different pathogens to be investigated and provide new insight into the biochemical responses and immunity mechanisms involved. This will provide the basis for develop breeding markers for durable, broad-spectrum resistance to OSR diseases. This will enable more efficient and reduced use of chemical pesticides which will improve OSR production and benefit the environment. To develop the project further, we have obtained 'Innovation Funding' from the Knowledge Exchange and Commercialisation department at JIC to establish a strategy for commercialisation of the research. With this, we are focussing on developing genetic markers for Light Leaf spot which is currently the most important disease of oilseed rape in the UK. We also obtained BBSRC funds for a Flexible Interchange Project (FLIP) with CN Seeds Ltd, enabling the transfer of knowledge to the company so that they could establish a pathology lab for screening disease resistance in their commercial breeding programme. We have also received funding for a BBSRC international Flexible Interchange Project (I-FLIP) to establish a collaboration between CN Seeds Ltd and Sarba Shrestha Seeds Ltd (SSS) in Nepal. This will enable them to develop quality control procedures for their seed production facility in Nepal. The I-FLIP project started in April 2019, and at the time of this reporting all the objectives have been met. We had a visit from Sarba Shrestha Seeds Ltd to the John Innes Centre to learn about methods in seed pathology and for quality assurance. The JIC team also visited SSS in Nepal to meet with farmers and other customers. We also visited the Agriculture and Forestry University in Chitwan, Nepal, to explore potential future areas for collaboration.

We are developing a MetaGWAS analysis to test associations between traits studied in MAQBAT. This is highly innovative, but could only be initiated towards the end of the project when most of the data had been obtained. This analysis is currently in progress with separate projects and funding. Moreover, new genomic data has become available during the project which means that we can achieve results more effectively that we could at the start of the project. Consequently, we expect the full impact of the project, including publications, will be realized in the three years following completion of MAQBAT. We have re-engaged in discussions with KWS, our partner in MAQBAT, to develop a research proposal for continuing some of our research to iprove resistance to Light Leaf Spot. This proposal has been submitteed to the UKRI/BBSRC Follow-on-Funding scheme.

The MAQBAT project involved research partners in Germany, Poland, Denmark and the UK including both academic researchers and those from industry. The collaboration has therefore added value to BBSRC research with funding from national agencies in those countries. The collaborative nature of the project has also enhanced the impact of the research by enabling its dissemination widely throughout Europe.

Some of the results from the project have been pressented at an annula invited lecture series at Imperial college 'Novel Approaches to Durable Disease Resistance in Crop Improvement which is included in the modull' Symbiosis, Immuity and Breeding'.
Sectors Agriculture

Food and Drink

Environment

 
Description Wew have initiated discussions with CIBUS, a company specialising in gene editing technology, about using the findings to control diseaases of oinseed rape. It is too early to have made any economic impact
First Year Of Impact 2022
Sector Agriculture, Food and Drink,Education
Impact Types Societal

Economic

 
Description Accelerated Breeding for Disease Resistance in Commercial Brassicas by Associative Transcriptomics
Amount £113,082 (GBP)
Funding ID BB/N01331X/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 01/2016 
End 12/2017
 
Description Novel pre-breeding germplasm for commercial development of sustainable traits in crops
Amount £201,596 (GBP)
Funding ID BB/V01725X/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 06/2021 
End 04/2022
 
Description Quality Seed for Agriculture and Nutrition in Nepal
Amount £58,417 (GBP)
Funding ID BB/S018972/1 
Organisation Biotechnology and Biological Sciences Research Council (BBSRC) 
Sector Public
Country United Kingdom
Start 03/2019 
End 03/2020
 
Title Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus) 
Description Supplemental datasets associated with publication: Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus) Abstract Crops are affected by several pathogens, but these are rarely studied in parallel to identify common and unique genetic factors controlling diseases. Broad-spectrum quantitative disease resistance (QDR) is desirable for crop breeding as it confers resistance to several pathogen species. Here, we use associative transcriptomics (AT) to identify candidate gene loci associated with Brassica napus QDR to four contrasting fungal pathogens: Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum. We did not identify any loci associated with broad-spectrum QDR to fungal pathogens with contrasting lifestyles. Instead, we observed QDR dependent on the lifestyle of the pathogen-hemibiotrophic and necrotrophic pathogens had distinct QDR responses and associated loci, including some loci associated with early immunity. Furthermore, we identify a genomic deletion associated with resistance to V. longisporum and potentially broad-spectrum QDR. This is the first time AT has been used for several pathosystems simultaneously to identify host genetic loci involved in broad-spectrum QDR. We highlight candidate loci for broad-spectrum QDR with no antagonistic effects on susceptibility to the other pathogens studies as candidates for crop breeding. Summary of data files Table S1 Mean, normalized phenotype data for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Table S2 Full list of single nucleotide polymorphism (SNP) markers and significance levels from genome-wide association (GWA) analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Table S3 Full list of gene expression markers (GEMs) and significance levels from GEM analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Table S4 184 gene expression markers (GEMs) associated with chitin-induced ROS compared with GEMs associated with resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by flg22, and elf18. Lists correspond to Venn diagrams in Fig. 2. Table S5 Enrichment analyses to determine if the number of gene expression markers (GEMs) shared between different lists is greater than the number of GEMs that would be expected by chance (e.g., lists of quantitative disease resistance (QDR) GEMs for two fungal pathogens). Table S6 Results from Weighted Co-expression Gene Network Analysis. Significant modules, significant GEM markers within modules, and GO terms associated with the magenta and black modules are indicated. Table S7 Shared gene expression markers (GEMs) associated with resistance to different pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum). Lists correspond to matrices and Venn diagrams in Fig. 1. Table S8 List of genes in linkage disequilibrium with the top marker for Verticillium longisporum resistance from genome-wide association (GWA) analysis on chromosome A09, the homoeologous region on C08, and their query coverage in Brassica napus reference genotypes Extended description of data files Table S1 Mean, normalized phenotype data for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). These data were used for association transcriptomic analysis. Table S2 Full list of single nucleotide polymorphism (SNP) markers and significance levels from genome-wide association (GWA) analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Each excel tab contains the analyses for a single trait. The best fit model for GWA analysis is indicated in the tab title. Manhattan plots showing marker-trait association are included for data visualization; x-axis indicates SNP location along the chromosome; the y-axis indicates the -log10(p) (P value). Qqplots are included to demonstrate model fit. Table S3 Full list of gene expression markers (GEMs) and significance levels from GEM analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Each excel tab contains the analyses for a single trait. Manhattan plots showing marker-trait association are included for data visualization; x-axis indicates GEM location along the chromosome; the y-axis indicates the -log10(p) (P value). Table S4 184 gene expression markers (GEMs) associated with chitin-induced ROS compared with GEMs associated with resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by flg22, and elf18. Lists correspond to Venn diagrams in Fig. 2. The first tab includes all 184 GEMs associated with chitin-induced ROS. The subsequent tabs include lists of shared GEMs associated with chitin-induced ROS response and each additional trait (quantitative disease resistance (QDR) to each fungal pathogen or additional PAMP-induced ROS responses). The title of each tab indicates the data included in each comparison and the number of shared GEMs. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible. Table S5 Enrichment analyses to determine if the number of gene expression markers (GEMs) shared between different lists is greater than the number of GEMs that would be expected by chance (e.g., lists of quantitative disease resistance (QDR) GEMs for two fungal pathogens). The representation factor is the number of overlapping GEMs divided by the expected number of overlapping GEMs drawn from two independent groups (traits), considering the total number of GEMs sequenced (53884). A representation factor > 1 indicates more overlap than expected of two groups, a representation factor < 1 indicates less overlap than expected, and a representation factor of 1 indicates that the two groups by the number of genes expected for independent groups of genes. Table S6 Results from Weighted Co-expression Gene Network Analysis (WGCNA). The first tab indicates significant modules from WGCNA analysis. Black and magenta modules are associated with antagonistic effects on resistance/susceptibility to all four pathogens. The second tab includes a full list of the GEM markers (Table S3), which are in significant WGCNA modules. The third, fourth and, fifth tabs indicate all significant GEMs in the black module, GO terms associated with GEMs in the black module, and all GO terms associated with the black module, respectively. The sixth, seventh and, eighth tabs indicate all significant GEMs in the magenta module, GO terms associated with GEMs in the magenta module, and all GO terms associated with the magenta module, respectively. Table S7 Shared gene expression markers (GEMs) associated with resistance to different pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum). Lists correspond to matrices and Venn diagrams in Fig. 3. The first tab includes all GEMs associated quantitative disease resistance (QDR) to the fungal pathogens. The subsequent tabs include lists of shared GEMs associated with QDR to two or more fungal pathogens. The title of each tab indicates the data included in each comparison and the number of shared GEMs. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible. Table S8 List of genes in linkage disequilibrium with the top marker for Verticillium longisporum resistance from genome-wide association (GWA) analysis on chromosome A09 (107 genes)(Tab 1) and the homoeologous region on C08 (Tab 2). Their percentage identity and query coverage in Brassica napus reference genotypes Quinta, Tapidor, Westar and Zhongshuang 11 compared to the B. napus pantranscriptome is indicated. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/record/8321694
 
Title Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus) 
Description Supplemental datasets associated with publication: Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus) Abstract Crops are affected by several pathogens, but these are rarely studied in parallel to identify common and unique genetic factors controlling diseases. Broad-spectrum quantitative disease resistance (QDR) is desirable for crop breeding as it confers resistance to several pathogen species. Here, we use associative transcriptomics (AT) to identify candidate gene loci associated with Brassica napus constitutive QDR to four contrasting fungal pathogens: Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum. We did not identify any loci associated with broad-spectrum QDR to fungal pathogens with contrasting lifestyles. Instead, we observed QDR dependent on the lifestyle of the pathogen-hemibiotrophic and necrotrophic pathogens had distinct QDR responses and associated loci, including some loci associated with early immunity. Furthermore, we identify a genomic deletion associated with resistance to V. longisporum and potentially broad-spectrum QDR. This is the first time AT has been used for several pathosystems simultaneously to identify host genetic loci involved in broad-spectrum QDR. We highlight constitutively expressed candidate loci for broad-spectrum QDR with no antagonistic effects on susceptibility to the other pathogens studies as candidates for crop breeding. In conclusion, this study represents and advancement in our understanding if broad-spectrum QDR in B. napus and is a significant resource for the scientific community.   Description of data files Full dataset for input into AT analysis  Full datasets (infection phenotypes for A. brassicicola, B. cinerea, or V.longisporum, ROS measurements for chitin, flg22, or elf18) and link to original P. brassicae dataset. These datasets were used for input into the Associative Transcriptomics pipeline (Nichols, 2022, https://github.com/bsnichols/GAGA. https://zenodo.org/badge/latestdoi/512807075).  Table S1 Mean, normalized phenotype data for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). These data were used for association transcriptomic analysis.  Table S2 Full list of single nucleotide polymorphism (SNP) markers and significance levels from genome-wide association (GWA) analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Each excel tab contains the analyses for a single trait. The best fit model for GWA analysis is indicated in the tab title. Manhattan plots showing marker-trait association are included for data visualization; x-axis indicates SNP location along the chromosome; the y-axis indicates the -log10(p) (P value). Qqplots are included to demonstrate model fit. Table S3 Full list of gene expression markers (GEMs) and significance levels from GEM analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Each excel tab contains the analyses for a single trait. Manhattan plots showing marker-trait association are included for data visualization; x-axis indicates GEM location along the chromosome; the y-axis indicates the -log10(p) (P value).  Table S4 184 gene expression markers (GEMs) associated with chitin-induced ROS compared with GEMs associated with resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by flg22, and elf18. Lists correspond to Venn diagrams in Fig. 2. The first tab includes all 184 GEMs associated with chitin-induced ROS. The subsequent tabs include lists of shared GEMs associated with chitin-induced ROS response and each additional trait (quantitative disease resistance (QDR) to each fungal pathogen or additional PAMP-induced ROS responses). The title of each tab indicates the data included in each comparison and the number of shared GEMs. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible.  Table S5 Enrichment analyses to determine if the number of gene expression markers (GEMs) shared between different lists is greater than the number of GEMs that would be expected by chance (e.g., lists of quantitative disease resistance (QDR) GEMs for two fungal pathogens). The representation factor is the number of overlapping GEMs divided by the expected number of overlapping GEMs drawn from two independent groups (traits), considering the total number of GEMs sequenced (53884). A representation factor > 1 indicates more overlap than expected of two groups, a representation factor < 1 indicates less overlap than expected, and a representation factor of 1 indicates that the two groups by the number of genes expected for independent groups of genes.  Table S6 Results from Weighted Co-expression Gene Network Analysis (WGCNA). The first tab indicates significant modules from WGCNA analysis. Black and magenta modules are associated with antagonistic effects on resistance/susceptibility to all four pathogens. The second tab includes a full list of the GEM markers (Table S3), which are in significant WGCNA modules. The third, fourth and, fifth tabs indicate all significant GEMs in the black module,  GO terms associated with GEMs in the black module, and all GO terms associated with the black module, respectively.  The sixth, seventh and, eighth tabs indicate all significant GEMs in the magenta module,  GO terms associated with GEMs in the magenta module, and all GO terms associated with the magenta module, respectively. Table S7 Shared gene expression markers (GEMs) associated with resistance to different pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum). Lists correspond to matrices and Venn diagrams in Fig. 3. The first tab includes all GEMs associated quantitative disease resistance (QDR) to the fungal pathogens. The subsequent tabs include lists of shared GEMs associated with QDR to two or more fungal pathogens. The title of each tab indicates the data included in each comparison and the number of shared GEMs. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible.  Table S8 List of genes in linkage disequilibrium with the top marker for Verticillium longisporum resistance from genome-wide association (GWA) analysis on chromosome A09 (107 genes)(Tab 1) and the homoeologous region on C08 (Tab 2). Their percentage identity and query coverage in Brassica napus reference genotypes Quinta, Tapidor, Westar and Zhongshuang 11 compared to the B. napus pantranscriptome is indicated. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/doi/10.5281/zenodo.8321693
 
Title Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus) 
Description Supplemental datasets associated with publication: Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus) Abstract Crops are affected by several pathogens, but these are rarely studied in parallel to identify common and unique genetic factors controlling diseases. Broad-spectrum quantitative disease resistance (QDR) is desirable for crop breeding as it confers resistance to several pathogen species. Here, we use associative transcriptomics (AT) to identify candidate gene loci associated with Brassica napus constitutive QDR to four contrasting fungal pathogens: Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum. We did not identify any loci associated with broad-spectrum QDR to fungal pathogens with contrasting lifestyles. Instead, we observed QDR dependent on the lifestyle of the pathogen-hemibiotrophic and necrotrophic pathogens had distinct QDR responses and associated loci, including some loci associated with early immunity. Furthermore, we identify a genomic deletion associated with resistance to V. longisporum and potentially broad-spectrum QDR. This is the first time AT has been used for several pathosystems simultaneously to identify host genetic loci involved in broad-spectrum QDR. We highlight constitutively expressed candidate loci for broad-spectrum QDR with no antagonistic effects on susceptibility to the other pathogens studies as candidates for crop breeding. In conclusion, this study represents and advancement in our understanding if broad-spectrum QDR in B. napus and is a significant resource for the scientific community.   Description of data files Full dataset for input into AT analysis  Full datasets (infection phenotypes for A. brassicicola, B. cinerea, or V.longisporum, ROS measurements for chitin, flg22, or elf18) and link to original P. brassicae dataset. These datasets were used for input into the Associative Transcriptomics pipeline (Nichols, 2022, https://github.com/bsnichols/GAGA. https://zenodo.org/badge/latestdoi/512807075).  Table S1 Mean, normalized phenotype data for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). These data were used for association transcriptomic analysis.  Table S2 Full list of single nucleotide polymorphism (SNP) markers and significance levels from genome-wide association (GWA) analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Each excel tab contains the analyses for a single trait. The best fit model for GWA analysis is indicated in the tab title. Manhattan plots showing marker-trait association are included for data visualization; x-axis indicates SNP location along the chromosome; the y-axis indicates the -log10(p) (P value). Qqplots are included to demonstrate model fit. Table S3 Full list of gene expression markers (GEMs) and significance levels from GEM analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Each excel tab contains the analyses for a single trait. Manhattan plots showing marker-trait association are included for data visualization; x-axis indicates GEM location along the chromosome; the y-axis indicates the -log10(p) (P value).  Table S4 184 gene expression markers (GEMs) associated with chitin-induced ROS compared with GEMs associated with resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by flg22, and elf18. Lists correspond to Venn diagrams in Fig. 2. The first tab includes all 184 GEMs associated with chitin-induced ROS. The subsequent tabs include lists of shared GEMs associated with chitin-induced ROS response and each additional trait (quantitative disease resistance (QDR) to each fungal pathogen or additional PAMP-induced ROS responses). The title of each tab indicates the data included in each comparison and the number of shared GEMs. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible.  Table S5 Enrichment analyses to determine if the number of gene expression markers (GEMs) shared between different lists is greater than the number of GEMs that would be expected by chance (e.g., lists of quantitative disease resistance (QDR) GEMs for two fungal pathogens). The representation factor is the number of overlapping GEMs divided by the expected number of overlapping GEMs drawn from two independent groups (traits), considering the total number of GEMs sequenced (53884). A representation factor > 1 indicates more overlap than expected of two groups, a representation factor < 1 indicates less overlap than expected, and a representation factor of 1 indicates that the two groups by the number of genes expected for independent groups of genes.  Table S6 Results from Weighted Co-expression Gene Network Analysis (WGCNA). The first tab indicates significant modules from WGCNA analysis. Black and magenta modules are associated with antagonistic effects on resistance/susceptibility to all four pathogens. The second tab includes a full list of the GEM markers (Table S3), which are in significant WGCNA modules. The third, fourth and, fifth tabs indicate all significant GEMs in the black module,  GO terms associated with GEMs in the black module, and all GO terms associated with the black module, respectively.  The sixth, seventh and, eighth tabs indicate all significant GEMs in the magenta module,  GO terms associated with GEMs in the magenta module, and all GO terms associated with the magenta module, respectively. Table S7 Shared gene expression markers (GEMs) associated with resistance to different pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum). Lists correspond to matrices and Venn diagrams in Fig. 3. The first tab includes all GEMs associated quantitative disease resistance (QDR) to the fungal pathogens. The subsequent tabs include lists of shared GEMs associated with QDR to two or more fungal pathogens. The title of each tab indicates the data included in each comparison and the number of shared GEMs. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible.  Table S8 List of genes in linkage disequilibrium with the top marker for Verticillium longisporum resistance from genome-wide association (GWA) analysis on chromosome A09 (107 genes)(Tab 1) and the homoeologous region on C08 (Tab 2). Their percentage identity and query coverage in Brassica napus reference genotypes Quinta, Tapidor, Westar and Zhongshuang 11 compared to the B. napus pantranscriptome is indicated. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/doi/10.5281/zenodo.10499917
 
Title Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus) 
Description Supplemental datasets associated with publication: Pathogen lifestyle determines host genetic signature of quantitative disease resistance loci in oilseed rape (Brassica napus) Abstract Crops are affected by several pathogens, but these are rarely studied in parallel to identify common and unique genetic factors controlling diseases. Broad-spectrum quantitative disease resistance (QDR) is desirable for crop breeding as it confers resistance to several pathogen species. Here, we use associative transcriptomics (AT) to identify candidate gene loci associated with Brassica napus constitutive QDR to four contrasting fungal pathogens: Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum. We did not identify any loci associated with broad-spectrum QDR to fungal pathogens with contrasting lifestyles. Instead, we observed QDR dependent on the lifestyle of the pathogen-hemibiotrophic and necrotrophic pathogens had distinct QDR responses and associated loci, including some loci associated with early immunity. Furthermore, we identify a genomic deletion associated with resistance to V. longisporum and potentially broad-spectrum QDR. This is the first time AT has been used for several pathosystems simultaneously to identify host genetic loci involved in broad-spectrum QDR. We highlight constitutively expressed candidate loci for broad-spectrum QDR with no antagonistic effects on susceptibility to the other pathogens studies as candidates for crop breeding. In conclusion, this study represents and advancement in our understanding if broad-spectrum QDR in B. napus and is a significant resource for the scientific community.   Description of data files Full dataset for input into AT analysis  Full datasets (infection phenotypes for A. brassicicola, B. cinerea, or V.longisporum, ROS measurements for chitin, flg22, or elf18) and link to original P. brassicae dataset. These datasets were used for input into the Associative Transcriptomics pipeline (Nichols, 2022, https://github.com/bsnichols/GAGA. https://zenodo.org/badge/latestdoi/512807075).  Table S1 Mean, normalized phenotype data for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). These data were used for association transcriptomic analysis.  Table S2 Full list of single nucleotide polymorphism (SNP) markers and significance levels from genome-wide association (GWA) analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Each excel tab contains the analyses for a single trait. The best fit model for GWA analysis is indicated in the tab title. Manhattan plots showing marker-trait association are included for data visualization; x-axis indicates SNP location along the chromosome; the y-axis indicates the -log10(p) (P value). Qqplots are included to demonstrate model fit. Table S3 Full list of gene expression markers (GEMs) and significance levels from GEM analyses for resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by PAMPS (chitin, flg22, and elf18). Each excel tab contains the analyses for a single trait. Manhattan plots showing marker-trait association are included for data visualization; x-axis indicates GEM location along the chromosome; the y-axis indicates the -log10(p) (P value).  Table S4 184 gene expression markers (GEMs) associated with chitin-induced ROS compared with GEMs associated with resistance to pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum) and ROS response induced by flg22, and elf18. Lists correspond to Venn diagrams in Fig. 2. The first tab includes all 184 GEMs associated with chitin-induced ROS. The subsequent tabs include lists of shared GEMs associated with chitin-induced ROS response and each additional trait (quantitative disease resistance (QDR) to each fungal pathogen or additional PAMP-induced ROS responses). The title of each tab indicates the data included in each comparison and the number of shared GEMs. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible.  Table S5 Enrichment analyses to determine if the number of gene expression markers (GEMs) shared between different lists is greater than the number of GEMs that would be expected by chance (e.g., lists of quantitative disease resistance (QDR) GEMs for two fungal pathogens). The representation factor is the number of overlapping GEMs divided by the expected number of overlapping GEMs drawn from two independent groups (traits), considering the total number of GEMs sequenced (53884). A representation factor > 1 indicates more overlap than expected of two groups, a representation factor < 1 indicates less overlap than expected, and a representation factor of 1 indicates that the two groups by the number of genes expected for independent groups of genes.  Table S6 Results from Weighted Co-expression Gene Network Analysis (WGCNA). The first tab indicates significant modules from WGCNA analysis. Black and magenta modules are associated with antagonistic effects on resistance/susceptibility to all four pathogens. The second tab includes a full list of the GEM markers (Table S3), which are in significant WGCNA modules. The third, fourth and, fifth tabs indicate all significant GEMs in the black module,  GO terms associated with GEMs in the black module, and all GO terms associated with the black module, respectively.  The sixth, seventh and, eighth tabs indicate all significant GEMs in the magenta module,  GO terms associated with GEMs in the magenta module, and all GO terms associated with the magenta module, respectively. Table S7 Shared gene expression markers (GEMs) associated with resistance to different pathogens (Alternaria brassicicola, Botrytis cinerea, Pyrenopeziza brassicae and Verticillium longisporum). Lists correspond to matrices and Venn diagrams in Fig. 3. The first tab includes all GEMs associated quantitative disease resistance (QDR) to the fungal pathogens. The subsequent tabs include lists of shared GEMs associated with QDR to two or more fungal pathogens. The title of each tab indicates the data included in each comparison and the number of shared GEMs. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible.  Table S8 List of genes in linkage disequilibrium with the top marker for Verticillium longisporum resistance from genome-wide association (GWA) analysis on chromosome A09 (107 genes)(Tab 1) and the homoeologous region on C08 (Tab 2). Their percentage identity and query coverage in Brassica napus reference genotypes Quinta, Tapidor, Westar and Zhongshuang 11 compared to the B. napus pantranscriptome is indicated. Predicted Arabidopsis thaliana orthologs and corresponding descriptions are shown where possible. 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/doi/10.5281/zenodo.10500446
 
Description CIBUS 
Organisation Cibus
Country United States 
Sector Private 
PI Contribution Initial discussions on use of gene editing for disease resistance
Collaborator Contribution Initial discussions on gene editing for disease resistance in oilseed rape
Impact Too early to say for our project. Howewver, discussions with other researchers at JIC have taken place
Start Year 2022
 
Description Consultancy in Plant Pathology 
Organisation RAGT Seeds
Country United Kingdom 
Sector Private 
PI Contribution consultancy
Collaborator Contribution Knowledge and facilities
Impact the consultancy led to the award of the FLIP grant
Start Year 2014
 
Description Defence induction by Vial 8 
Organisation Arlabion Ltd
Country United Kingdom 
Sector Private 
PI Contribution We performed analysis of a novel compound developed by the company to investigate its role in defence induction for disease control. We produced a report that they used for a patent application
Collaborator Contribution The partners provided the compound and advice about the nature of the chemical and the kind of analyses they required
Impact A report that was used for the patent application
Start Year 2018
 
Description Improving resistnce to Light Leaf Spot in Brassica napus 
Organisation KWS Saat
Country Germany 
Sector Private 
PI Contribution We had discussions about a collaborative project and wrote a propoal that is currently being evaluated by UKRI/BBSRC
Collaborator Contribution They contributed expertise and would provide resources if the project is funded
Impact Too early for any outputs
Start Year 2020
 
Description Improving resistnce to Light Leaf Spot in Brassica napus 
Organisation University of Hertfordshire
Country United Kingdom 
Sector Academic/University 
PI Contribution We had discussions about a collaborative project and wrote a propoal that is currently being evaluated by UKRI/BBSRC
Collaborator Contribution They contributed expertise and would provide resources if the project is funded
Impact Too early for any outputs
Start Year 2020
 
Description Plant stimulants to prime plant immunity 
Organisation Arlabion Ltd
Country United Kingdom 
Sector Private 
PI Contribution We provided our expertise to address a specific research question for the Company
Collaborator Contribution They provided the background and some technical knowledge to the project
Impact A report has been submitted to the company
Start Year 2017
 
Description A taste of Genetic Diversity: demonstration activity for the John Innes Centre open day 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact A demonstration of our research was performed at an open day at the John Innes Centre, involving hands on activities and discussion on the theme of 'a taste of genetic diversity. The activities involved showing how brassicas were used in baby leaf salads, and how heritage barley varieties were used in brewing beer
Year(s) Of Engagement Activity 2017
 
Description Brassica Research Community Conference 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Annual meeting of the Brassica Research Community to provide research updates on relevant topics
Year(s) Of Engagement Activity 2021
 
Description Breeders Day 2018 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact Breeders Day is an annual event to present current research on crop improvement at the John Innes Centre. The 2018 event was focussed on the supply chain, emphasising downstream processing of crops into products
Year(s) Of Engagement Activity 2018
 
Description Conference attendance 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Brassica Research commuity is an informal meeting where researchers can present their latest results to academia and industry
Year(s) Of Engagement Activity 2020
 
Description Disease resistance and immunity in brassicas: presentation to the Chinese Academy of Agricultural Sciences 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Presentation of our research on brassica pathology to the Chinese Academy of Agricultural Sciences. The meeting took place at the John Innes Centre
Year(s) Of Engagement Activity 2017
 
Description Disease resistance and immunity in brassicas: presentation to the Chinese Academy of Agricultural Sciences 2018 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Study participants or study members
Results and Impact The annual meeting held with scientists from the Chinese Academy of Agricultural Sciences to present research updates and potential for collaborative research
Year(s) Of Engagement Activity 2018
 
Description Disease resistance in Brassicas 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Study participants or study members
Results and Impact Annual meeting for the BBSRC project Mechanistic Analysis of Quantitative Disease Resistance in Brassicas by Associative transcriptomics
Year(s) Of Engagement Activity 2015,2016
 
Description Disease resistance research on brassicas 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Industry/Business
Results and Impact Presentations were given to CN Seeds and Clover seeds about research on brassica disease resistance. The work has led to further development of collaborative research with CN Seeds on downy mildew in brassicas for the baby leaf salad market. We also made a successful joint application for GCRF-funded research to develop collaboration between CN Seeds and a seed company in Nepal.
Year(s) Of Engagement Activity 2018
 
Description Fast-Track to Quantitative Disease Resistance in Brassicas 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact This was a presentation it industry as part of the Science for Innovation Showcase at John Innes Centre. This was followed up by formal meetings with industry representative about potential future collaborative research
Year(s) Of Engagement Activity 2018
 
Description GCRF visit with Nepalese Researchers 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact A fact-finding mission to Nepal was undertaken with the aim of developing new collaborations for potential GCRF projects
Year(s) Of Engagement Activity 2017
 
Description Genetic analysis of immune responses in brassicas 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Presentation of research results at the 21st Crucifer Genetics Conference, St Malo, France. The audience was comprised of scientific researchers with a wide range of interests in crucifer genetics
Year(s) Of Engagement Activity 2018
URL https://colloque.inra.fr/brassica2018/
 
Description Immunity in brassicas 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Industry/Business
Results and Impact Presentation to Elsoms, a seed and breeding company interested in collaborative research on oilseed rape improvement, especially in disease resistance
Year(s) Of Engagement Activity 2018
 
Description Improving disease control in brassicaas 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Industry/Business
Results and Impact Meeting with Prime agriculture to present research and explore potential collaborations in the future. Prime Agriculture are consultants in agriculture, with particular focus on agronomy. The work has led to an application to assess research priorities for disease control research in brassicas
Year(s) Of Engagement Activity 2018
 
Description Mechanistic Analysis of Quantitative Disease Resistance in Brassica by Associative Transcriptomics 
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 Workshop on disease resistance in brassicas, leading to further collaborative projects
Year(s) Of Engagement Activity 2015
 
Description Mechanistic Analysis of Quantitative Disease Resistance in Brassica by Associative Transcriptomics 2018 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Study participants or study members
Results and Impact This was the final workshop of MAQBAT to discuss results and plans for publications
Year(s) Of Engagement Activity 2018
 
Description Mechanistic Analysis of Quantitative Disease Resistance in Brassica by Associative Transcriptomics ERA-CAPS workshop 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Presentation at ERA-CAPS meeting, Lisbon
Year(s) Of Engagement Activity 2015
 
Description Mechanistic Analysis of Quantitative Disease Resistance in Brassica by Associative Transcriptomics ERA-CAPS workshop 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Study participants or study members
Results and Impact Annual meeting for Mechanistic Analysis of Quantitative Disease Resistance in Brassicas by Association Transcriptomics. The meeting was organised at the University of Lodz, Poland, and involved presentations by the members of the consortium
Year(s) Of Engagement Activity 2017
URL http://www.eracaps.org/joint-calls/era-caps-funded-projects/era-caps-second-call-2014/mechanistic-an...
 
Description Mechanistic Analysis of Quantitative Disease Resistance in Brassica by Associative Transcriptomics ERA-CAPS workshop 2018 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Study participants or study members
Results and Impact Final workshop for the ERA-CAPS project 'MAQBAT'. This involved presenting research findings to the cohort of investigators funded under the scheme
Year(s) Of Engagement Activity 2018
 
Description Novel Approaches to Durable Disease Resistance in Crop Improvement 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Plenary lecture at the Eurobiotech 2019 conference, Krakow, Poland
Year(s) Of Engagement Activity 2019
 
Description Novel Approaches to Durable Disease Resistance in Crop Improvement 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Postgraduate students
Results and Impact I gave an lecture at Imperial College for the module on Symbiosis, Immunity and Breeding to undergraduate and postgraduate students
Year(s) Of Engagement Activity 2021
 
Description Oilseed rape genetic improvement network 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Attended annual meeting of the oilseed rape genetic improvement network
Year(s) Of Engagement Activity 2016
URL http://www.herts.ac.uk/oregin/about-oregin
 
Description PAMP responses in the Triangle of U 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact presentation of results from the MAQBAT project to update the brassica community about progress with the work. The presentation has enable further discussions about potential future collaborations and project ideas
Year(s) Of Engagement Activity 2018
 
Description Phenotyping oilseed rape (Brassica napus) genotypes during interaction with necrotrophic fungus Alternaria brassicicola. 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Study participants or study members
Results and Impact poster presentation at Vth Polish Genetic Congress, 19-22 September 2016 Lodz, Poland, session Plant Genomics, page 318 abstract no. 30
Year(s) Of Engagement Activity 2016
 
Description Photosynthetic efficiency differs between Brassica napus cultivars that are susceptible or resistant to Alternaria brassicicola. 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Study participants or study members
Results and Impact Poster presentation at the 15th Congress of the Mediterranean Phytopathological Union, 20-23 June 2017, Cordoba, Spain; Phytopathologia Mediterranea 56(2): 278-378 (p. 331)
Year(s) Of Engagement Activity 2017
 
Description Presentation about crop disease resistance 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact presentation of research activities to ICL speciality fertilizers
Year(s) Of Engagement Activity 2016
 
Description Presentation to Novozymes 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Industry/Business
Results and Impact presentation of research to three representatives from Novozymes, a speciality chemicals company based in Denmark
Year(s) Of Engagement Activity 2017
 
Description Role of phytohormone-dependent pathways in susceptible and resistant oilseed rape (Brassica napus) cultivars to Alternaria brassicicola infection. 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact poster presentation at 6th Asian Conference on Plant Pathology "Translation from genomes to disease management", 13-16 September 2017, Jeju South Korea
Year(s) Of Engagement Activity 2017
 
Description presentsation to the Flying Farmers 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact Flying farmers are a group of farmers interested to learn about the latest trends in research. the presentation involved talking to them about our work, and engaging in a discussion with them
Year(s) Of Engagement Activity 2017