Correlates of evolutionary rates in the murine sperm proteome

Abstract Background Protein-coding genes expressed in sperm evolve at different rates. To gain deeper insight into the factors underlying this heterogeneity we examined the relative importance of a diverse set of previously described rate correlates in determining the evolution of murine sperm prote...

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Main Authors: Julia Schumacher, Holger Herlyn
Format: Article
Language:English
Published: BMC 2018-03-01
Series:BMC Evolutionary Biology
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12862-018-1157-6
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spelling doaj-76826a19a6c9467489795064c666e95b2021-09-02T12:55:19ZengBMCBMC Evolutionary Biology1471-21482018-03-0118111110.1186/s12862-018-1157-6Correlates of evolutionary rates in the murine sperm proteomeJulia Schumacher0Holger Herlyn1Institute of Organismic and Molecular Evolution, Anthropology, Johannes Gutenberg UniversityInstitute of Organismic and Molecular Evolution, Anthropology, Johannes Gutenberg UniversityAbstract Background Protein-coding genes expressed in sperm evolve at different rates. To gain deeper insight into the factors underlying this heterogeneity we examined the relative importance of a diverse set of previously described rate correlates in determining the evolution of murine sperm proteins. Results Using partial rank correlations we detected several major rate indicators: Phyletic gene age, numbers of protein-protein interactions, and survival essentiality emerged as particularly important rate correlates in murine sperm proteins. Tissue specificity, numbers of paralogs, and untranslated region lengths also correlate significantly with sperm genes’ evolutionary rates, albeit to a lesser extent. Multifunctionality, coding sequence or average intron lengths, and mean expression level have insignificant or virtually no independent effects on evolutionary rates in murine sperm genes. Gene ontology enrichment analyses of three equally sized murine sperm protein groups classified based on their evolutionary rates indicate strongest sperm-specific functional specialization in the most quickly evolving gene class. Conclusions We propose a model according to which slowly evolving murine sperm proteins tend to be constrained by factors such as survival essentiality, network connectivity, and/or broad expression. In contrast, evolutionary change may arise especially in less constrained sperm proteins, which might, moreover, be prone to specialize to reproduction-related functions. Our results should be taken into account in future studies on rate variations of reproductive genes.http://link.springer.com/article/10.1186/s12862-018-1157-6Protein evolutionTissue specificityProtein essentialitySperm proteinsProtein-protein interactionsGene age
collection DOAJ
language English
format Article
sources DOAJ
author Julia Schumacher
Holger Herlyn
spellingShingle Julia Schumacher
Holger Herlyn
Correlates of evolutionary rates in the murine sperm proteome
BMC Evolutionary Biology
Protein evolution
Tissue specificity
Protein essentiality
Sperm proteins
Protein-protein interactions
Gene age
author_facet Julia Schumacher
Holger Herlyn
author_sort Julia Schumacher
title Correlates of evolutionary rates in the murine sperm proteome
title_short Correlates of evolutionary rates in the murine sperm proteome
title_full Correlates of evolutionary rates in the murine sperm proteome
title_fullStr Correlates of evolutionary rates in the murine sperm proteome
title_full_unstemmed Correlates of evolutionary rates in the murine sperm proteome
title_sort correlates of evolutionary rates in the murine sperm proteome
publisher BMC
series BMC Evolutionary Biology
issn 1471-2148
publishDate 2018-03-01
description Abstract Background Protein-coding genes expressed in sperm evolve at different rates. To gain deeper insight into the factors underlying this heterogeneity we examined the relative importance of a diverse set of previously described rate correlates in determining the evolution of murine sperm proteins. Results Using partial rank correlations we detected several major rate indicators: Phyletic gene age, numbers of protein-protein interactions, and survival essentiality emerged as particularly important rate correlates in murine sperm proteins. Tissue specificity, numbers of paralogs, and untranslated region lengths also correlate significantly with sperm genes’ evolutionary rates, albeit to a lesser extent. Multifunctionality, coding sequence or average intron lengths, and mean expression level have insignificant or virtually no independent effects on evolutionary rates in murine sperm genes. Gene ontology enrichment analyses of three equally sized murine sperm protein groups classified based on their evolutionary rates indicate strongest sperm-specific functional specialization in the most quickly evolving gene class. Conclusions We propose a model according to which slowly evolving murine sperm proteins tend to be constrained by factors such as survival essentiality, network connectivity, and/or broad expression. In contrast, evolutionary change may arise especially in less constrained sperm proteins, which might, moreover, be prone to specialize to reproduction-related functions. Our results should be taken into account in future studies on rate variations of reproductive genes.
topic Protein evolution
Tissue specificity
Protein essentiality
Sperm proteins
Protein-protein interactions
Gene age
url http://link.springer.com/article/10.1186/s12862-018-1157-6
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AT holgerherlyn correlatesofevolutionaryratesinthemurinespermproteome
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