Controlling Supply, Quality and Waste in Brassica vegetables: Understanding the genetics of maturity to breed varieties in response to climate change

Lead Research Organisation: John Innes Centre
Department Name: Contracts Office


The UK has a strong base in flowering time research, especially in the control of vernalization. From the work of Caroline Dean at the John Innes Centre, and others, much is now known about the genetic pathways regulating vernalization in the model plant Arabidopsis thaliana. Using the Genetic resources developed in Horticulture LINK project HL0186 we will identify the genes controlling vernalization in Brassica and exploit this information to develop tools to speed up the breeding in Brassica vegetable crops.
We will exploit the continually expanding genomic resources in Brassica to map paralogues of key Arabidopsis genes involved in the control of flowering with a focus on known vernalization genes. We will use the most recent developments in the Dean lab to expedite this choice, together with Brassica: Arabidopsis synteny to identify putative candidates underlying QTL mapped under different temperature x time treatments. Identification of candidate genes for selected QTL will be confirmed by co-segregation of alleles with maturity phenotypes in backcross progeny. Early and late alleles of putative candidates will be transformed into appropriate Arabidopsis mutants to test complementation. We will demonstrate the generality of the findings by analysing allelic variation at these loci in current cauliflower varieties and compare this with known vernalization responses. To identify novel, functional allelic variation a wide range of germplasm will be screened at candidate gene loci including the Defra funded Diversity Fixed Foundation Sets (DFFS) for B.oleracea and the wild C genome being produced at Warwick HRI.
Allelic variation at candidate loci will be related to performance under past and present weather patterns. We will use the UKCIP scenarios, and in particular the Weather generator, to model future growing conditions. We will link past and current variety performance to inform future breeding strategies for continuity of production.


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