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FunnyBase: a systems level functional annotation of Fundulus ESTs for the analysis of gene expression

Justin E Paschall1, Marjorie F Oleksiak2, Jeffrey D VanWye3, Jennifer L Roach3, J Andrew Whitehead3, Gerald J Wyckoff1, Kevin J Kolell1 and Douglas L Crawford3*

Author Affiliations

1 Division of Molecular Biology and Biochemistry, 5100 Rockhill Rd., University of Missouri-Kansas City 64110, USA

2 Department of Environmental & Molecular Toxicology, North Carolina State University; Raleigh, NC 27695-7633 USA

3 Division of Marine Biology and Fisheries, NIEHS Marine and Freshwater Biomedical Sciences Center, Rosenstiel School of Marine & Atmospheric Science, University of Miami, Miami, FL 33149, USA

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BMC Genomics 2004, 5:96  doi:10.1186/1471-2164-5-96

Published: 20 December 2004



While studies of non-model organisms are critical for many research areas, such as evolution, development, and environmental biology, they present particular challenges for both experimental and computational genomic level research. Resources such as mass-produced microarrays and the computational tools linking these data to functional annotation at the system and pathway level are rarely available for non-model species. This type of "systems-level" analysis is critical to the understanding of patterns of gene expression that underlie biological processes.


We describe a bioinformatics pipeline known as FunnyBase that has been used to store, annotate, and analyze 40,363 expressed sequence tags (ESTs) from the heart and liver of the fish, Fundulus heteroclitus. Primary annotations based on sequence similarity are linked to networks of systematic annotation in Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and can be queried and computationally utilized in downstream analyses. Steps are taken to ensure that the annotation is self-consistent and that the structure of GO is used to identify higher level functions that may not be annotated directly. An integrated framework for cDNA library production, sequencing, quality control, expression data generation, and systems-level analysis is presented and utilized. In a case study, a set of genes, that had statistically significant regression between gene expression levels and environmental temperature along the Atlantic Coast, shows a statistically significant (P < 0.001) enrichment in genes associated with amine metabolism.


The methods described have application for functional genomics studies, particularly among non-model organisms. The web interface for FunnyBase can be accessed at webcite. Data and source code are available by request at