Dataset Information

Genome annotation of Anopheles gambiae using mass spectrometry-derived data.

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.

SUBMITTER: Kalume DE

PROVIDER: S-EPMC1249570 | biostudies-literature | 2005

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genome annotation of Anopheles gambiae using mass spectrometry-derived data.

Kalume Dário E DE Peri Suraj S Reddy Raghunath R Zhong Jun J Okulate Mobolaji M Kumar Nirbhay N Pandey Akhilesh A

BMC genomics 20050919

<h4>Background</h4>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 ...[more]

PMID: 16171517

Similar Datasets

Project description:BackgroundGenome sequencing of Anopheles gambiae was completed more than ten years ago and has accelerated research on malaria transmission. However, annotation needs to be refined and verified experimentally, as most predicted transcripts have been identified by comparative analysis with genomes from other species. The mosquito midgut-the first organ to interact with Plasmodium parasites-mounts effective antiplasmodial responses that limit parasite survival and disease transmission. High-throughput Illumina sequencing of the midgut transcriptome was used to identify new genes and transcripts, contributing to the refinement of An. gambiae genome annotation.ResultsWe sequenced ~223 million reads from An. gambiae midgut cDNA libraries generated from susceptible (G3) and refractory (L35) mosquito strains. Mosquitoes were infected with either Plasmodium berghei or Plasmodium falciparum, and midguts were collected after the first or second Plasmodium infection. In total, 22,889 unique midgut transcript models were generated from both An. gambiae strain sequences combined, and 76% are potentially novel. Of these novel transcripts, 49.5% aligned with annotated genes and appear to be isoforms or pre-mRNAs of reference transcripts, while 50.5% mapped to regions between annotated genes and represent novel intergenic transcripts (NITs). Predicted models were validated for midgut expression using qRT-PCR and microarray analysis, and novel isoforms were confirmed by sequencing predicted intron-exon boundaries. Coding potential analysis revealed that 43% of total midgut transcripts appear to be long non-coding RNA (lncRNA), and functional annotation of NITs showed that 68% had no homology to current databases from other species. Reads were also analyzed using de novo assembly and predicted transcripts compared with genome mapping-based models. Finally, variant analysis of G3 and L35 midgut transcripts detected 160,742 variants with respect to the An. gambiae PEST genome, and 74% were new variants. Intergenic transcripts had a higher frequency of variation compared with non-intergenic transcripts.ConclusionThis in-depth Illumina sequencing and assembly of the An. gambiae midgut transcriptome doubled the number of known transcripts and tripled the number of variants known in this mosquito species. It also revealed existence of a large number of lncRNA and opens new possibilities for investigating the biological function of many newly discovered transcripts.

Dataset Information

Genome annotation of Anopheles gambiae using mass spectrometry-derived data.

Publications

Genome annotation of Anopheles gambiae using mass spectrometry-derived data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets