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Correlates of evolutionary rates in the murine sperm proteome

Overview of attention for article published in BMC Ecology and Evolution, March 2018
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Title
Correlates of evolutionary rates in the murine sperm proteome
Published in
BMC Ecology and Evolution, March 2018
DOI 10.1186/s12862-018-1157-6
Pubmed ID
Authors

Julia Schumacher, Holger Herlyn

Abstract

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. 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. 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 33%
Researcher 1 11%
Student > Master 1 11%
Unknown 4 44%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 33%
Agricultural and Biological Sciences 1 11%
Unknown 5 56%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 April 2018.
All research outputs
#19,951,180
of 25,382,440 outputs
Outputs from BMC Ecology and Evolution
#3,171
of 3,714 outputs
Outputs of similar age
#253,271
of 344,729 outputs
Outputs of similar age from BMC Ecology and Evolution
#48
of 55 outputs
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