Abstract

<p>Abstract</p> <p>Background</p> <p>New strategies for high-throughput sequencing are constantly appearing, leading to a great increase in the number of completely sequenced genomes. Unfortunately, computational genome annotation is out of step with this progress. Thus, the accurate annotation of these genomes has become a bottleneck of knowledge acquisition.</p> <p>Results</p> <p>We exploited a proteogenomic approach to improve conventional genome annotation by integrating proteomic data with genomic information. Using <it>Shigella flexneri </it>2a as a model, we identified total 823 proteins, including 187 hypothetical proteins. Among them, three annotated ORFs were extended upstream through comprehensive analysis against an in-house N-terminal extension database. Two genes, which could not be translated to their full length because of stop codon 'mutations' induced by genome sequencing errors, were revised and annotated as fully functional genes. Above all, seven new ORFs were discovered, which were not predicted in <it>S. flexneri </it>2a str.301 by any other annotation approaches. The transcripts of four novel ORFs were confirmed by RT-PCR assay. Additionally, most of these novel ORFs were overlapping genes, some even nested within the coding region of other known genes.</p> <p>Conclusions</p> <p>Our findings demonstrate that current <it>Shigella </it>genome annotation methods are not perfect and need to be improved. Apart from the validation of predicted genes at the protein level, the additional features of proteogenomic tools include revision of annotation errors and discovery of novel ORFs. The complementary dataset could provide more targets for those interested in <it>Shigella </it>to perform functional studies.</p

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