Dataset Information

Phosphoproteome analysis of Drosophila melanogaster embryos.

ABSTRACT: Protein phosphorylation is a key regulatory event in most cellular processes and development. Mass spectrometry-based proteomics provides a framework for the large-scale identification and characterization of phosphorylation sites. Here, we used a well-established phosphopeptide enrichment and identification strategy including the combination of strong cation exchange chromatography, immobilized metal affinity chromatography, and high-accuracy mass spectrometry instrumentation to study phosphorylation in developing Drosophila embryos. In total, 13,720 different phosphorylation sites were discovered from 2702 proteins with an estimated false-discovery rate (FDR) of 0.63% at the peptide level. Because of the large size of the data set, both novel and known phosphorylation motifs were extracted using the Motif-X algorithm, including those representative of potential ordered phosphorylation events.

SUBMITTER: Zhai B

PROVIDER: S-EPMC3063950 | biostudies-literature | 2008 Apr

REPOSITORIES: biostudies-literature

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Phosphoproteome analysis of Drosophila melanogaster embryos.

Zhai Bo B Villén Judit J Beausoleil Sean A SA Mintseris Julian J Gygi Steven P SP

Journal of proteome research 20080308 4

Protein phosphorylation is a key regulatory event in most cellular processes and development. Mass spectrometry-based proteomics provides a framework for the large-scale identification and characterization of phosphorylation sites. Here, we used a well-established phosphopeptide enrichment and identification strategy including the combination of strong cation exchange chromatography, immobilized metal affinity chromatography, and high-accuracy mass spectrometry instrumentation to study phosphory ...[more]

PMID: 18327897

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Project description:BACKGROUND:The formation of matured and individual sperm involves a series of molecular and spectacular morphological changes of the developing cysts in Drosophila melanogaster testis. Recent advances in RNA Sequencing (RNA-Seq) technology help us to understand the complexity of eukaryotic transcriptomes by dissecting different tissues and developmental stages of organisms. To gain a better understanding of cellular differentiation of spermatogenesis, we applied RNA-Seq to analyse the testis-specific transcriptome, including coding and non-coding genes. RESULTS:We isolated three different parts of the wild-type testis by dissecting and cutting the different regions: 1.) the apical region, which contains stem cells and developing spermatocytes 2.) the middle region, with enrichment of meiotic cysts 3.) the basal region, which contains elongated post-meiotic cysts with spermatids. Total RNA was isolated from each region and analysed by next-generation sequencing. We collected data from the annotated 17412 Drosophila genes and identified 5381 genes with significant transcript accumulation differences between the regions, representing the main stages of spermatogenesis. We demonstrated for the first time the presence and region specific distribution of 2061 lncRNAs in testis, with 203 significant differences. Using the available modENCODE RNA-Seq data, we determined the tissue specificity indices of Drosophila genes. Combining the indices with our results, we identified genes with region-specific enrichment in testis. CONCLUSION:By multiple analyses of our results and integrating existing knowledge about Drosophila melanogaster spermatogenesis to our dataset, we were able to describe transcript composition of different regions of Drosophila testis, including several stage-specific transcripts. We present searchable visualizations that can facilitate the identification of new components that play role in the organisation and composition of different stages of spermatogenesis, including the less known, but complex regulation of post-meiotic stages.

Dataset Information

Phosphoproteome analysis of Drosophila melanogaster embryos.

Publications

Phosphoproteome analysis of Drosophila melanogaster embryos.

Similar Datasets

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