项目编号: | BB/M017753/1
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项目名称: | A Systems Approach to Disease Resistance Against Necrotrophic Fungal Pathogens |
作者: | Carol Wagstaff
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承担单位: | University of Reading
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批准年: | 2014
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开始日期: | 2015-01-07
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结束日期: | 2018-30-06
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资助金额: | GBP35830
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资助来源: | UK-BBSRC
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项目类别: | Research Grant
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国家: | UK
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语种: | 英语
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特色学科分类: | Agri-environmental science
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英文摘要: | The fungal pathogens Botrytis cinerea and Sclerotinia sclerotiorum have broad host ranges and cause serious disease on many horticultural crops. Both fungi can cause substantial losses on field-grown and protected lettuce crops, an industry worth almost £200 M annually in the UK. B. cinerea is a particular problem post-harvest, whereas S. sclerotiorum can result in up to 50% crop loss pre-harvest. Chemical control is problematic as few effective compounds are available, the number of sprays is restricted and timing is difficult. Moreover, the fungicides are medium to high risk for development of resistance. Development of durable resistance in the crop is a more sustainable solution, but has been an intransigent problem for lettuce breeders. The objective of this proposal is to demonstrate that a novel approach to breeding for pathogen resistance is possible.
We will apply genomic and systems biology (computational) approaches in lettuce, and combine this with quantitative genetics studies to identify novel genes for increasing the resistance of lettuce to both B. cinerea and S. sclerotiorum. This will provide a foundation to develop similar resistance to these pathogens in other horticultural crops.
We have two hypotheses we want to test. Firstly, that we can identify genes which confer resistance to both B. cinerea and S. sclerotiorum, two necrotrophic fungal pathogens. Genome sequencing of these fungi has indicated they share a range of genes associated with infection and colonization of plants, hence host resistance mechanisms against one pathogen might also confer resistance to the other.
Secondly, we want to test the feasibility of applying systems biology research into horticultural crop species. We have used systems biology approaches to generate network models of how genes interact during the defence response of Arabidopsis to infection by B. cinerea. We combined large-scale gene expression data with mathematical modelling to predict the key resistance enes. In this work, we will carry out network analysis of the lettuce defence response and test whether the same genes are involved in disease resistance, and/or whether the hub genes in the network are important. This is a completely new approach to crop improvement, relying on gene-gene interactions during defence against pathogen infection. We will also look for conservation of disease resistance genes in tomato and Brassica, key crops affected by these pathogens.
At the same time we will employ a more traditional quantitative genetic analysis to identify regions of the lettuce genome that influence resistance against both of these pathogens. We will screen nearly 100 lettuce accessions and cross accessions with the greatest resistance to a standard cultivar to generate mapping populations. A pre-existing mapping population (known to be segregating for disease resistance) will be screened for disease resistance to both B. cinerea and S. scerotiorum to identify important genomic regions for these traits.
Finally we will integrate our quantitative genetic analysis and results from network analysis to generate lettuce lines and markers for use in breeding programmes. This project is possible because of the lettuce genome sequence that is available, as well as the extensive lettuce germplasm and genetic and genomic resources that Warwick has generated. The work will be exploited primarily through A.L.Tozer to develop lettuce varieties with increased resistance to B. cinerea and S. sclerotiorum fungal pathogens. |
资源类型: | 项目
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标识符: | http://119.78.100.158/handle/2HF3EXSE/101341
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Appears in Collections: | 科学计划与规划 气候变化与战略
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作者单位: | University of Reading
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Recommended Citation: |
Carol Wagstaff. A Systems Approach to Disease Resistance Against Necrotrophic Fungal Pathogens. 2014-01-01.
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