The falling cost of nucleotide sequencing is opening up significant opportunities for crop improvement through plant breeding and increased understanding of plant biology.
Many plant genomes are large and have complex evolutionary histories, making their analysis theoretically challenging and highly demanding of computational resources. Issues include genome size, polyploidy, and the quantity, diversity and dispersed nature of data in need of integration.
transPLANT is a consortium of 11 European partners gathered to address these challenges and to develop a trans-national infrastructure for plant genomic science. Bringing together groups with strengths in data analysis, plant science, computer science, and from the academic and commercial sectors. transPLANT will develop integrated standards and services, undertaking research and development to capitalise on the sequencing revolution across the spectrum of agricultural and model plant species.
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Background
The current landscape for plant informatics infrastructure is patchy, with some excellent resources already in place, while other domains are critically lacking. transPLANT will focus on the areas of greatest need and importance, aiming to bridge gaps and utilise existing resources that already meet the community's needs. Building on the distributed expertise of individual European groups carrying out cutting edge research in plant science informatics, transPLANT will provide integrated services offering access to a diverse variety of data types from a broad range of species.
This will be achieved through a mixture of networking, service and research and technological development activities. The three areas are critically linked. Through the research and technological development, resources for archiving and interpreting data and tools for data analysis and access which will provide essential components of the emerging infrastructure will be developed. In the networking activities, transPLANT partners will engage with each other, the wider plant science community, and other related scientific and informatics infrastructures and communities in order to develop and share standards for the description of data and metadata, which are critical to allow the sharing of information between different resources. Finally, in the service-oriented work packages, we will provide new servers offering public access to the transPLANT resources (for both computational and interactive access), and will provide a single point of access for diverse, dispersed plant genomic data.
transPLANT services will be developed according to a hub-and-spoke model whereby individual resources, representing centres of excellence in particular domains (such as clusters of related species, or particular data types) will continue in their existing roles as community-based custodians of data; but will be able to take part in a two-way data exchange with other partners. These tools will make a common set of reference data available for use by all partners, and support the construction of integrated, interpretative applications on top of the archived data. Critically, the use and development of open, standard technologies for data exchange and access will allow other organisations and consortia to contribute to the transPLANT network; and for all researchers to computationally analyse the transPLANT data; so that the work begun by the project partners will survive as a lasting legacy to the plant science community.
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Project objectives
Interaction with the community
- Arrange a series of networking activities and meetings with experts from related fields, to exploit experiences and explore synergies.
- Engage with the widest possible communities to endorse and develop standards for extant and emerging data types.
- Host a series of training events to familiarise the plant science community with the use of cutting edge tools.
Research and development
- Develop a computational infrastructure for plant genomic science.
- Develop an portal to provide integrated, interactive access to a broad range of databases, services and tools.
- Develop new methods for the large-scale analysis of genotype-phenotype associations.
- Assess and develop new algorithms for genomic analysis.
Databases, search and storage
- Develop and maintain a common set of reference plant genomic data.
- Explore the mechanisms required for the analysis and storage of genomic complexity in plant species.
- Develop a new infrastructure for the archiving of genomic variation.
- Provide a new search engine, integrating reference bioinformatics databases and physical genetic materials.
All services and software developed as part of the project will be available for public use without restriction.
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