Open Access Research article

A multi-organ transcriptome resource for the Burmese Python (Python molurus bivittatus)

Todd A Castoe1*, Samuel E Fox2, AP Jason de Koning1, Alexander W Poole1, Juan M Daza3, Eric N Smith4, Todd C Mockler2, Stephen M Secor5 and David D Pollock1

Author Affiliations

1 Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO 80045 USA

2 Department of Botany and Plant Pathology and Center for Genome Research and Biocomputing, Oregon State University, Corvallis, OR 97331 USA

3 Instituto de Biologia, Universidad de Antioquia, Medellin, Colombia

4 Department of Biology, University of Texas, Arlington, TX 76019 USA

5 Department of Biological Sciences, University of Alabama, Tuscaloosa, AL 35487 USA

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BMC Research Notes 2011, 4:310  doi:10.1186/1756-0500-4-310

Published: 25 August 2011

Abstract

Background

Snakes provide a unique vertebrate system for studying a diversity of extreme adaptations, including those related to development, metabolism, physiology, and venom. Despite their importance as research models, genomic resources for snakes are few. Among snakes, the Burmese python is the premier model for studying extremes of metabolic fluctuation and physiological remodelling. In this species, the consumption of large infrequent meals can induce a 40-fold increase in metabolic rate and more than a doubling in size of some organs. To provide a foundation for research utilizing the python, our aim was to assemble and annotate a transcriptome reference from the heart and liver. To accomplish this aim, we used the 454-FLX sequencing platform to collect sequence data from multiple cDNA libraries.

Results

We collected nearly 1 million 454 sequence reads, and assembled these into 37,245 contigs with a combined length of 13,409,006 bp. To identify known genes, these contigs were compared to chicken and lizard gene sets, and to all Genbank sequences. A total of 13,286 of these contigs were annotated based on similarity to known genes or Genbank sequences. We used gene ontology (GO) assignments to characterize the types of genes in this transcriptome resource. The raw data, transcript contig assembly, and transcript annotations are made available online for use by the broader research community.

Conclusion

These data should facilitate future studies using pythons and snakes in general, helping to further contribute to the utilization of snakes as a model evolutionary and physiological system. This sequence collection represents a major genomic resource for the Burmese python, and the large number of transcript sequences characterized should contribute to future research in this and other snake species.