Int J Biol Sci 2007; 3(3):132-152. doi:10.7150/ijbs.3.132 This issue


Advances in Swine Transcriptomics

Christopher K. Tuggle1 2 3, Yanfang Wang2, Oliver Couture2 3

1. Center for Integrated Animal Genomics, Iowa State University, Ames IA, USA
2. Department of Animal Science, Iowa State University, Ames IA, USA
3. Interdepartmental Genetics, Iowa State University, Ames, IA, USA

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Tuggle CK, Wang Y, Couture O. Advances in Swine Transcriptomics. Int J Biol Sci 2007; 3(3):132-152. doi:10.7150/ijbs.3.132. Available from

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The past five years have seen a tremendous rise in porcine transcriptomic data. Available porcine Expressed Sequence Tags (ESTs) have expanded greatly, with over 623,000 ESTs deposited in Genbank. ESTs have been used to expand the pig-human comparative maps, but such data has also been used in many ways to understand pig gene expression. Several methods have been used to identify genes differentially expressed (DE) in specific tissues or cell types under different treatments. These include open screening methods such as suppression subtractive hybridization, differential display, serial analysis of gene expression, and EST sequence frequency, as well as closed methods that measure expression of a defined set of sequences such as hybridization to membrane arrays and microarrays. The use of microarrays to begin large-scale transcriptome analysis has been recently reported, using either specialized or broad-coverage arrays. This review covers published results using the above techniques in the pig, as well as unpublished data provided by the research community, and reports on unpublished Affymetrix data from our group. Published and unpublished bioinformatics efforts are discussed, including recent work by our group to integrate two broad-coverage microarray platforms. We conclude by predicting experiments that will become possible with new anticipated tools and data, including the porcine genome sequence. We emphasize that the need for bioinformatics infrastructure to efficiently store and analyze the expanding amounts of gene expression data is critical, and that this deficit has emerged as a limiting factor for acceleration of genomic understanding in the pig.

Keywords: transcriptomics, microarray, porcine, quantitative PCR, bioinformatics