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Sökning: WFRF:(Beynon J) > (2015-2019)

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  • Bayram, Helen L., et al. (författare)
  • Cross-species proteomics in analysis of mammalian sperm proteins
  • 2016
  • Ingår i: Journal of Proteomics. - : Elsevier BV. - 1874-3919 .- 1876-7737. ; 135, s. 38-50
  • Tidskriftsartikel (refereegranskat)abstract
    • Many proteomics studies are conducted in model organisms for which fully annotated, detailed, high quality proteomes are available. By contrast, many studies in ecology and evolution are conducted in species which lack high quality proteome data, limiting the perceived value of a proteomic approach for protein discovery and quantification. This is particularly true of rapidly evolving proteins in the reproductive system, such as those that have an immune function or are under sexual selection, and can compromise the potential for cross-species proteomics to yield confident identification. In this investigation we analysed the sperm proteome, from a range of ungulates and rodents, and explored the potential of routine proteomic workflows to yield characterisation and quantification in non-model organisms. We report that database searching is robust to cross-species matching for a mammalian core sperm proteome, comprising 623 proteins that were common to most of the 19 species studied here, suggesting that these proteins are likely to be present and identifiable across many mammalian sperm. Further, label-free quantification reveals a consistent pattern of expression level. Functional analysis of this core proteome suggests consistency with previous studies limited to model organisms and has value as a quantitative reference for analysis of species-specific protein characterisation.Significance: From analysis of the sperm proteome for diverse species (rodents and ungulates) using LC-MS/MS workflows and standard data processing, we show that it is feasible to obtain cross-species matches for a large number of proteins that can be filtered stringently to yield a highly expressed mammalian sperm core proteome, for which label-free quantitative data are also used to inform protein function and abundance.
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