Abstract
Since the sequencing of the honey bee genome, proteomics by mass spectrometry has become increasingly popular for biological analyses of this insect; but we have observed that the number of honey bee protein identifications is consistently low compared to other organisms [1]. In this dataset, we use nanoelectrospray ionization-coupled liquid chromatography–tandem mass spectrometry (nLC–MS/MS) to systematically investigate the root cause of low honey bee proteome coverage. To this end, we present here data from three key experiments: a controlled, cross-species analyses of samples from Apis mellifera, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Mus musculus and Homo sapiens; a proteomic analysis of an individual honey bee whose genome was also sequenced; and a cross-tissue honey bee proteome comparison. The cross-species dataset was interrogated to determine relative proteome coverages between species, and the other two datasets were used to search for polymorphic sequences and to compare protein cleavage profiles, respectively.
Highlights
Since the sequencing of the honey bee genome, proteomics by mass spectrometry has become increasingly popular for biological analyses of this insect; but we have observed that the number of honey bee protein identifications is consistently low compared to other organisms [1]
We present here data from three key experiments: a controlled, cross-species analyses of samples from Apis mellifera, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Mus musculus and Homo sapiens; a proteomic analysis of an individual honey bee whose genome was sequenced; and a cross-tissue honey bee proteome comparison
The cross-species dataset was interrogated to determine relative proteome coverages between species, and the other two datasets were used to search for polymorphic sequences and to compare protein cleavage profiles, respectively
Summary
Raw data (RAW files), search results (TXT files) Comparison of proteome coverage between species; comparison of honey bee proteome coverage with and without accounting for sequence polymorphisms; comparison of protease activity across honey bee tissues Protein samples were treated with dithiothreitol and iodoacetamide before trypsin digestion. We describe a detailed example of creating a personalized proteome database for a honey bee, and the code provided here can be used to construct a personalized protein database for any organism with known SNPs. The controlled cross-species proteomes dataset is suitable for evolutionary and bioinformatic hypothesis testing. We include the raw mass spectrometry data files for the cross-species comparison, the honey bee whose genome was sequenced, and the cross-tissue comparison. To aid readers in identifying the relevant data files to download from our ProteomeXchange submission
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