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This article is part of the supplement: Third Annual MCBIOS Conference. Bioinformatics: A Calculated Discovery

Open Access Proceedings

An Automated Method for Rapid Identification of Putative Gene Family Members in Plants

Ronald L Frank1*, Ajay Mane2 and Fikret Ercal2

Author Affiliations

1 Biological Sciences Department, University of Missouri-Rolla, Rolla, Missouri, USA

2 Computer Science Department, University of Missouri-Rolla, Rolla, Missouri, USA

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BMC Bioinformatics 2006, 7(Suppl 2):S19  doi:10.1186/1471-2105-7-S2-S19

Published: 26 September 2006

Abstract

Background

Gene duplication events have played a significant role in genome evolution, particularly in plants. Exhaustive searches for all members of a known gene family as well as the identification of new gene families has become increasingly important. Subfunctionalization via changes in regulatory sequences following duplication (adaptive selection) appears to be a common mechanism of evolution in plants and can be accompanied by purifying selection on the coding region. Such negative selection can be detected by a bias toward synonymous over nonsynonymous substitutions. However, the process of identifying this bias requires many steps usually employing several different software programs. We have simplified the process and significantly shortened the time required by condensing many steps into a few scripts or programs to rapidly identify putative gene family members beginning with a single query sequence.

Results

In this report we 1) describe the software tools (SimESTs, PCAT, and SCAT) developed to automate the gene family identification, 2) demonstrate the validity of the method by correctly identifying 3 of 4 PAL gene family members from Arabidopsis using EST data alone, 3) identify 2 to 6 CAD gene family members from Glycine max (previously unidentified), and 4) identify 2 members of a putative Glycine max gene family previously unidentified in any plant species.

Conclusion

Gene families in plants, particularly that subset where purifying selection has occurred in the coding region, can be identified quickly and easily by integrating our software tools and commonly available contig assembly and ORF identification programs.