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Module 4

Detailed information about module 4

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Module 4 - Tomato Genetic Resources


Module leader: Dani Zamir
This Module aims at the development of mapped genetic resources of tomato. Natural biodiversity is an under-exploited sustainable resource that can enrich the genetic basis of cultivated plants with novel alleles that improve productivity, quality and adaptation. Natural variation related to the EU-SOL traits is largely unexplored and hardly used in current commercial varieties. For this purpose further refinement of mapped introgression lines (ILs) involving the wild tomato species Solanum habrochaites (formerly known as L hirsutum), Solanum pennellii, Solanum chmielewski, Solanum neorickii (formerly known as Lycopersicon parviflorum) and Solanum lycopersicoides will be pursued. A PCR marker based framework will be developed and linked to genetic maps of tomato and potato. Selected variants will be derived from the EMS and Fast Neutron saturation mutagenesis project. A tomato core collection of 1000 accessions representing traditional and modern types for association studies will be constructed. SNP analysis and targeted sequencing will be used for association analysis using target genes defined by EU-SOL partners on the basis of the tomato genome sequence. Phenotyping of ILs, mutants and core collection germplasm will be performed in field and glasshouse multi-sites trials for agricultural traits and dissemination of tissues for the researchers in other modules. Phenotypic data from the entire project will be integrated into a single map based framework and all germplasm resource and fine mapping lines will be curated and distributed to the EU-SOL community. This Module is service-oriented to the benefit of the research groups in Modules 1, 2 and 3, the industrial partners and the global community at large working on the Solanaceae.
Module4


Workpackages in this module:


WP 4.1: Development of mapped genetic resources.
Workpackage leader: Silvana Grandillo


WP 4.2: Construction of a tomato core collection for association studies.
Workpackage leader: Mark van Haaren


WP 4.3:   Phenotyping, bioinformatics and germplasm distribution.
Workpackage leader: Dani Zamir








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