Venn analysis as part of a bioinformatic approach to prioritize expressed sequence tags from cardiac libraries.

Abstract

OBJECTIVES We needed to sort expressed sequence tags (ESTs) from human cardiac expression libraries. DESIGN AND METHODS We annotated DNA sequence text files of 35,152 cardiac ESTs using our search and annotation tool called Multiblast.pl. We generated lists of the most prevalent ESTs in each library, and using a novel Venn tool, we grouped ESTs that were common to all or exclusive to particular libraries. RESULTS Hypothetical protein KIAA0553 was expressed 120 times among 917 ESTs from an adult cardiac library (13.1%) compared only once among 8075 ESTs from fetal cardiac libraries (P < 10(-114)), this was confirmed using Northern analysis. We collated biochemical features of KIAA0553 and determined DNA polymorphism frequencies. We also used the Venn tool to specify genes that were uniquely expressed in hypertrophic cardiomyocytes. CONCLUSIONS Annotating ESTs and sorting them using Venn analysis can help specify new candidate disease genes from the current lists of "hypothetical proteins".

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@article{McKinney2004VennAA, title={Venn analysis as part of a bioinformatic approach to prioritize expressed sequence tags from cardiac libraries.}, author={James L McKinney and Duncan J. Murdoch and Jian Wang and John F. Robinson and Chris Biltcliffe and Hafiz M. R. Khan and Paul Michael Walker and Jos{\'e}e Savage and Ilona S. Skerjanc and Robert A Hegele}, journal={Clinical biochemistry}, year={2004}, volume={37 11}, pages={953-60} }