Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

Computational Resources for Biofuel Feedstock Species

2008 Awardee

Investigators: C. Robin Buell and Kevin Childs

Institution: Michigan State University

Non-Technical Summary: While current production of ethanol as a biofuel relies on starch and sugar inputs, it is anticipated that sustainable production of ethanol for biofuel use will utilize lignocellulosic feedstocks. Candidate plant species to be used for lignocellulosic ethanol production include a large number of species within the Grass, Pine and Birch plant families. For these biofuel feedstock species, there are variable amounts of genome sequence resources available, ranging from complete genome sequences (e.g. sorghum, poplar) to transcriptome data sets (e.g. switchgrass, pine). These data sets are not only dispersed in location but also disparate in content. It will be essential to leverage and improve these genomic data sets for the improvement of biofuel feedstock production. Using computational approaches, we will improve the level of our understanding of important biofuel feedstock species on a genome level thereby providing critical resources for engineering plants for biofuel production.

Objectives: The objectives of this proposal are to provide computational tools and resources for data-mining genome sequence/annotation and large-scale functional genomic datasets available for biofuel feedstock species. We will create a Bioenergy Feedstock Genomics Resource that provides a web-based portal or “clearing house” for genomic data for plant species relevant to biofuel feedstock production. We will provide additional computational analyses of these data to facilitate a genomic approach to improved biofuel feedstock production.

Approach: We will centralize and then provide uniform annotation of genomic data for biofuel feedstock species through our Bioenergy Feedstock Genomics Resource. To improve our understanding of gene function, we will use comparative approaches in which sequence similarity is used to cross-annotate genes among plant species. Model plant species will be included in the comparative analyses to leverage the wealth of information and resources currently available. We will generate new hypotheses regarding gene function using a systems biology approach with biofuel feedstock species from the Grass family.

Project Contact
Name: C Robin Buell
Department of Plant Biology
Michigan State University
East Lansing MI 48824
Phone: (517) 353 5597
Fax: (517) 353 1926
Email: [email protected]