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Open Access Research article

Genome annotation of Anopheles gambiae using mass spectrometry-derived data

Dário E Kalume1, Suraj Peri12, Raghunath Reddy14, Jun Zhong1, Mobolaji Okulate3, Nirbhay Kumar3* and Akhilesh Pandey1*

Author Affiliations

1 McKusick-Nathans Institute of Genetic Medicine and Department of Biological Chemistry and Oncology, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA

2 Department of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, DK-5230, Denmark

3 Department of Molecular Microbiology and Immunology, Johns Hopkins Malaria Research Institute, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA

4 Institute of Bioinformatics, Discoverer Unit 1, 7th Floor International Tech Park Ltd., Whitefield Road, Bangalore – 560 066, India

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BMC Genomics 2005, 6:128  doi:10.1186/1471-2164-6-128

Published: 19 September 2005

Abstract

Background

A large number of animal and plant genomes have been completely sequenced over the last decade and are now publicly available. Although genomes can be rapidly sequenced, identifying protein-coding genes still remains a problematic task. Availability of protein sequence data allows direct confirmation of protein-coding genes. Mass spectrometry has recently emerged as a powerful tool for proteomic studies. Protein identification using mass spectrometry is usually carried out by searching against databases of known proteins or transcripts. This approach generally does not allow identification of proteins that have not yet been predicted or whose transcripts have not been identified.

Results

We searched 3,967 mass spectra from 16 LC-MS/MS runs of Anopheles gambiae salivary gland homogenates against the Anopheles gambiae genome database. This allowed us to validate 23 known transcripts and 50 novel transcripts. In addition, a novel gene was identified on the basis of peptides that matched a genomic region where no gene was known and no transcript had been predicted. The amino termini of proteins encoded by two predicted transcripts were confirmed based on N-terminally acetylated peptides sequenced by tandem mass spectrometry. Finally, six sequence polymorphisms could be annotated based on experimentally obtained peptide sequences.

Conclusion

The peptide sequences from this study were mapped onto the genomic sequence using the distributed annotation system available at Ensembl and can be visualized in the context of all other existing annotations. The strategy described in this paper can be used to correct and confirm genome annotations and permit discovery of novel proteins in a high-throughput manner by mass spectrometry.