Using bioinformatics to analyse germplasm collections

Guy Davenport, Noel Ellis, Mike Ambrose, Jo Dicks

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


In the last few years, we have seen a growing emphasis on the characterisation of germplasm collections by molecular markers such as microsatellites, AFLPs, SSAPs, RBIPs and SNPs. This emphasis has served to enhance the use of germplasm collections in crop improvement via plant breeding while also aiding the management of collections themselves through an improved understanding of the relationships between accessions and underlying patterns of diversity. With the new data sets becoming available comes the recognition of the role that bioinformatics can play in making the most of the data. The basis of the new bioinformatics infrastructure is databases that enable the association of passport and trait data with molecular markers. Visualisation tools enable us to view large quantities of these data simultaneously and to tease out patterns underlying our data sets. We also need analytical tools to help us search for trait-marker or haplotype-marker associations and to look for patterns of genetic diversity. Most importantly, all of these components should interact in a fluid and intuitive manner such that the developers of germplasm collections and the plant genetics and breeding communities can access and manipulate the data. Here, we focus on the development of new bioinformatics tools for germplasm analysis within two projects: GENE-MINE and GERMINATE. We look at different aspects of our bioinformatics infrastructure, to give a sense of the powerful analyses that bioinformatics can facilitate. Finally, we look forward to bringing together these different areas to the benefit of the plant breeding and genetic resources communities.

Original languageEnglish
Pages (from-to)39-54
Number of pages16
Issue number1
Publication statusPublished - 2004
Externally publishedYes

Bibliographical note

Funding Information:
In the last few years, the JIC Bioinformatics Research Group ( has become a partner in several collaborative projects for the analysis of germplasm collections. These have been driven by a need to understand the genetic complexity of JIC’s own collections but also with a wider goal to share data and tools. Each project contains an element of bioinformatics development, as this is seen to be a vital component in data dissemination and analysis in the current era. The GENE- MINE project ( grew from a meeting on genebanks and comparative genomics held by CGIAR in August 1999. Following the broad discussions held within this meeting, the goals of the GENE-MINE project were formalised, to bring together experts in database development, data querying and visualisation, quantitative methods and computational methods, to develop novel tools for the analysis of germplasm collections characterised by molecular markers. In January 2001, GENE-MINE began with funding from the European Union (EU). The project is a collaboration between several groups: Plant Research International B.V. (PRI, The Netherlands)— including members of Biometris and the Centre for Genetics Resources Netherlands (CGN), JIC, the University of Hohenheim (Germany), the National Center for Genome Resources (NCGR, U.S.), KeyGene N.V. (The Netherlands), the International Plant Genetic Resources Institute (IPGRI, Italy), Palacky´ University Olomouc (Czech Republic), the Research Institute of Crop Production Praha-Ruzyneˇ (RICP, Czech Republic), the Institute of Plant Genetics and Crop Plant Research (IPK, Germany) and the Horticultural Research Institute (HRI, U.K.).

Funding Information:
The TEGERM project (http://www.biocenter. hels began in 2001, also funded by the EU and closely linked to the GENE-MINE project. TE-GERM is developing retrotransposon-based sequence-specific amplified polymorphic (SSAP, Pearce et al., 2000), and retrotransposon-based insertion polymorphisms (RBIP, Flavell et al., 1998) markers for collections of pea, barley, tomato and pepper. The GERMINATE project began in 2002, funded by the UK Biotechnology and Biological Sciences Research Council (BBSRC). GERMINATE, a collaboration between JIC, the University of Dundee, the Scottish Crop Research Institute (SCRI) and the Linnaeus Centre for Bioinformatics (Sweden), bridges the GENE-MINE and TEGERM projects by developing additional software components for the analysis of collections characterised by co-dominant RBIP markers. Within GERMINATE, JIC is committed to ensuring a smooth interface between the GENE-MINE system and the GERMINATE software, the latter including new quantitative methods for the analysis of genetic diversity within RBIP-and microsatellite-characterised germplasm collections. Recently, JIC has gained new EU funding through the Grain Legumes project, which aims to begin in early 2004. This project will include the further development of quantitative methods for genetic diversity within germplasm collections.


  • bioinformatics
  • computational biology
  • data mining
  • data visualisation
  • genetic diversity
  • germplasm collections


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