PlabiPD - Leveraging Big Data for Plant Research

How best to profit from the growing mass of next generation omics data is a major challenge faced by the scientific community. With PlabiPD, we are tackling this challenge. We are currently focusing our attention on model and crop plants thereby serving both the scientific and breeding community. We have integrated the available crop genomes together with manual and literature annotation data into PlabiPD, the successor of GABIPD, which is hosted at the research center Jülich. By moving the database to the research center it is thus possible to provide sustainable long term hosting.

Our experience in developing next generation pipeline tools during the sequencing and assembly of Solanum pennellii - such as Trimmomatic or MapMan - has been employed to devise novel ways to analyse, visualize and present large datasets. To best profit from this expertise, the protein data from multiple plant species was clustered within the database using the Markov Cluster Algorithm. Subsequently, manually curated data from Arabidopsis stemming from the Aramemnon database as well as from model and crop plants originating from the MapMan project was used to annotate the clustered proteins. Users are thus able to find orthologous proteins in the other crop plants based on high quality manual annotations. Additional information such as protein coding regions along with conserved domains (Pfam) are also presented in a user friendly interface. Links from individual genes provide direct access to extended information hosted on the species-specific websites.