Arabidopsis Community Resources For Comparative and Network Analyses

Doreen Ware, Gramene Consortium, KBase Consortium

In 2011, the International Arabidopsis Informatics Consortium (IAIC) developed a white paper that outlines recommendations for establishing a federated model in which a central bioinformatics portal would support integration of globally-generated modules.  In this talk, I will present online resources from two community projects (Gramene and Knowledgebase) that can contribute to support comparative analyses, biological networks, and genotype-to-phenotype relationships using metabolic and functional analyses.

The Gramene (www.gramene.org) project has developed a platform that brings together fragmented information originating from model species by applying various bioinformatics methodologies. This lays the foundation for synthesizing new knowledge applicable not only to the reference plant models, but also to non-model plant species using homology-driven approaches.  The project currently supports the development and stewardship of more than 20 plant genome reference sequences and annotations in the Ensembl 69 framework. This provides a common standard platform for comparative genomic analysis and visualization. The enriched genome annotations include controlled vocabularies to describe metadata and primary data associated with comparative phylogenomics, epigenetics, and population-based phenotypes.  We will be further contributing to the development, implementation, and stewardship of gene networks for Arabidopsis using the Reactome model and via the integration of expression profiling data sets, including the pending surge of RNAseq data for Arabidopsis using the ATLAS (EBI) meta-analysis and annotation pipelines.

KBase (www.kbase.us) is a collaborative effort designed to accelerate our understanding of microbes, microbial communities, and plants in an environment context. It will be a community-driven, extensible and scalable open-source software framework and application system. KBase will offer free and open access to data models and simulations, enabling scientists and researchers to build new knowledge, test hypotheses, design experiments, and share their findings to accelerate the use of predictive biology. Our immediate goal is to have a beta-version completed by February 2013. The plant component will allow users to model genotype-to-phenotype relationships using metabolic and functional networks. Initially, the project will focus on five flagship genomes, including the Arabidopsis model genome.  It will also support the reconstruction of new metabolic and functional networks based on expression profiles, protein-DNA, and protein-protein interactions.  We will provide users with access to collections of experiment datasets together with relevant analytical tools and resources.

This work is supported by NSF IOS-1127112, DOE DE-AC02-06CH11357, USDA 1907-21000-030-00D.