Published online 29 November 2006 Nucleic Acids Research, 2007, Vol. 35, Database issue D599–D603 doi:10.1093/nar/gkl936 AgBase: a unified resource for functional analysis in agriculture Fiona M. McCarthy1,2,*, Susan M. Bridges2,3,*, Nan Wang2,3, G. Bryce Magee2,3, W. Paul Williams4, Dawn S. Luthe5 and Shane C. Burgess1,3,6 1Department of Basic Sciences, College of Veterinary Medicine, Mississippi State University, PO Box 6100, Mississippi, MS 39762, USA, 2Institute for Digital Biology, Mississippi State University, MS 39762, USA, 3Department of Computer Science and Engineering, Bagley College of Engineering, PO Box 9637, Mississippi, MS 39762, USA, 4USDA ARS Corn Host Plant Resistance Research Unit, Box 5367, Mississippi, MS 39762, USA, 5Department of Crop and Soil Sciences, The Pennsylvania State University, University Park, PA 16802, USA and 6Mississippi Agricultural and Forestry Experiment Station, Mississippi State University, MS 39762, USA Received August 15, 2006; Revised October 11, 2006; Accepted October 12, 2006 ABSTRACT Analysis of functional genomics (transcriptomics and proteomics) datasets is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation. To facilitate systems biology in these species we have established the curated, web- accessible, public resource ‘AgBase’ (www.agbase. msstate.edu). We have improved the structural annotation of agriculturally important genomes by experimentally confirming the in vivo expression of electronically predicted proteins and by proteo- genomic mapping. Proteogenomic data are avail- able from the AgBase proteogenomics link. We contribute Gene Ontology (GO) annotations and we provide a two tier system of GO annotations for users. The ‘GO Consortium’ gene association file contains the most rigorous GO annotations based solely on experimental data. The ‘Community’ gene association file contains GO annotations based on expert community knowledge (annotations based directly from author statements and submitted anno- tations from the community) and annotations for predicted proteins. We have developed two tools for proteomics analysis and these are freely avail- able on request. A suite of tools for analyzing functional genomics datasets using the GO is avail- able online at the AgBase site. We encourage and publicly acknowledge GO annotations from researchers and provide an online mechanism for agricultural researchers to submit requests for GO annotations. INTRODUCTION Annotation of agricultural genomes The complete sequencing of the human genome resulted in improved sequencing technologies and reduced expenses for whole genome sequencing. Consequently many genome sequencing projects are now underway. Among the agricul- turally important species the chicken and rice genomes are completed (1–3), the bovine genome has a draft assembly available (4) and other agricultural genome sequencing pro- jects (including pig, maize, wheat, soybean and grape) are in progress (5–8). Effective use of these genome sequences to model biological systems requires both structural annota- tion (denoting and demarcating genes and other functional elements) and functional annotation (assigning functions to each genomic element) (9,10). Initial genome structural annotation is done computation- ally either by homology prediction to known genes in other species (‘predicted’ genes) or by using ab initio prediction algorithms that search for speciﬁc patterns indicative of open reading frames (ORFs) (11,12). However, these electro- nic genome structural-annotation methods produce false positive and false negative predictions as high as 70% (13) and commonly misclassify pseudogenes as functional (14). The use of experimental data for genome annotation is criti- cal for conclusive identiﬁcation of the functional sequences within genomes, accurate description of intron/exon struc- tures and determination of the potential protein products from each gene in different tissues and cellular states (15). *To whom correspondence should be addressed. Tel: +1 662 325 5859; Fax: +1 662 325 1031; Email: fmccarthy@cvm.msstate.edu The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors 2006 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.