Obtaining accurate translations from expressed sequence tags

Abstract

The genomes of an increasing number of species are being investigated through the generation of expressed sequence tags (ESTs). However, ESTs are prone to sequencing errors and typically define incomplete transcripts, making downstream annotation difficult. Annotation would be greatly improved with robust polypeptide translations. Many current solutions for EST translation require a large number of full-length gene sequences for training purposes, a resource that is not available for the majority of EST projects. As part of our ongoing EST programs investigating these "neglected" genomes, we have developed a polypeptide prediction pipeline, prot4EST. It incorporates freely available software to produce final translations that are more accurate than those derived from any single method. We describe how this integrated approach goes a long way to overcoming the deficit in training data. © 2009 Humana Press, a part of Springer Science+Business Media, LLC.