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Improved use of germplasm collections with the aid of novel methodologies for integration, analysis and presentation of genetic datasets

Gene banks have been documenting enormous amounts of genetic material. In the near future, new genetic information will be generated when large collections are fingerprinted for numerous molecular markers to get a detailed description of the diversity at the molecular level. This explosion of data will pose serious problems on data access and analysis but the proposed project will solve these. The result will be a more informative and cost-effective germplasm management and exploitation system for the benefit of agriculture in the European Union and worldwide. To achieve this, a multi-disciplinary consortium of world leaders in (bio)informatics, statistical genetics, genebanks and marker technology was formed, and then end-users from the international genebank and breeding community were added.

The main objective of the project is to develop and evaluate an integrative information system with new analysis methods that reveal the relationships between large-scale molecular marker data, phenotypic traits and environmental data in order to establish a necessary, more productive, better informed and cost-effective germplasm management and exploitation system for the benefit of agriculture in the EU and worldwide.
The objective will be reached via the following scientific and technical elements:
1) Integration of large amounts of data
The aim is to develop a state-of-the-art, web-based system for storing and accessing large amounts of molecular genetic data, trait data and passport data from genebanks. This information will be linked to genomic and other biological databases, which will ensure an optimal coordination of data sources within the EU and internationally.
2) Asking biological questions of the data
The aim is to develop a simple yet powerful querying mechanism, which is a prerequisite of a user-friendly germplasm management system. The querying tools will be particularly important for large gene bank datasets, where users cannot be expected to scroll through prohibitively long lists of data items. These tools will provide news ways of pinpointing items of special interest quickly and efficiently, and of asking new complex queries across the boundaries of available databases.
3) Getting answers to the questions
The aim is to upgrade the current methods of analysis suited for small-scale data sizes. This will mean that an end-user can analyse the huge amount of data available. Novel, powerful strategies and methods of analysis will be invented so that the end-user gets answers to traditional questions but also to the new (molecular genetic) questions, which it has not been possible to ask before.
4) Visualise the results
The aim is to develop new ways to display the results from analyses of large datasets, so that the end-user has greater access to the different layers of information and output related to the question asked.
5) Study properties of the strategies developed
The aim is to assess the degree to which the different strategies will be efficient, precise and suited to a scientific as well as an end-user point of view, by studying the aspects of population genetics theoretically via computer simulation and practically via real data available to, or generated in, the project.
6) Coordination of GENE-MINE
The aim is to coordinate and optimise the quality of scientific progress, timing and budgeting of the project and dissemination of the results.

Many components of a software system for the integration, querying, analysis and
visualisation of germplasm data have been designed and built. The Lactuca subproject has delivered both products and research conclusions. Full details are available on the project website.


Scientist responsible for the project

P.O. BOX 16
6700 AA Wageningen
Netherlands (The) - NL

Phone: +31 317 477078
Fax: +31 317 418094


Project ID QLRT-1999-30722
Organisation Plant Research International B.V.
Area 5.1.1
Start date 01 January 2001
Duration (months) 36
Total cost 2 091 233 €
Total EC contribution   1 011 088 €
Status Ongoing
Web address of the project

The partners

  • National Center for Genome Resources, United States (The) - US

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