Correlates of evolutionary rates in the murine sperm proteome

Abstract

BackgroundProtein-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.ResultsUsing 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.ConclusionsWe 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.Electronic supplementary materialThe online version of this article (10.1186/s12862-018-1157-6) contains supplementary material, which is available to authorized users.

Nonfertilizing sperm in Lepidoptera show little evidence for recurrent positive selection

“…Other studies have demonstrated that tissue specificity of expression can strongly influence the molecular evolution of reproductive proteins (Schumacher & Herlyn, 2018), in some cases more than mating system (Carnahan-Craig & Jensen-Seaman, 2014). Because our proteomic data did not contain information on tissue specificity on their own, we examined this dynamic with RNA-seq data.…”

Intra-Protein Coevolution Is Increasingly Functional with Greater Proximity to Fertilization

“…In both BODY sets, numerous connections to diverse signaling pathways (e.g., M3K2/MAP3K2, AKT2, TKNK/TAC3) were in accordance with the complexity of the entire organism [Cheng et al, 2000;Sakamoto et al, 2006;Tusset et al, 2012]. Also, the fact that the annotations for SPERM did not contain specificities is unsurprising: After all, many sperm-expressed proteins exert their multiple functions in diverse tissues [Schumacher and Herlyn, 2018]. Nevertheless, SPERM also exhibited clear connections to re-production, as exemplified by TSG10 (TSGA10), which is mainly expressed in sperm tail, and VATE2 (ATP6V1E2; alias VMA4), which participates in acrosomal acidification [Sha et al, 2018;Futai et al, 2019].…”

“…Also, transient PPIs have a lesser conserving effect on sequence evolution than obligate ones [Mintseris and Weng, 2005]. Additionally, higher phyletic age and broader or early onset of expression associate with higher sequence conservation [Zhang and Li, 2004;Good and Nachman, 2005;Toll-Riera et al, 2012;Schumacher and Herlyn, 2018]. Moreover, longer 5′ and 3′ untranslated regions [Worth et al, 2009;Schumacher and Herlyn, 2018] as well as more posttranslational modifications and higher pleiotropy levels [Macek et al, 2008;Jancura and Marchiori, 2012;Schumacher et al, 2013] associate with lowered substitution rates.…”

“…But in general, additional PPIs imply greater functional constraint and thus stron-ger evolutionary conservation [reviewed in Jancura and Marchiori, 2012]. Accordingly, the number of PPIs is a main constraining factor in the evolution of mammalian testicular and sperm proteins too [e.g., Schumacher et al, 2017;Schumacher and Herlyn, 2018].…”

Fertility Relevance Probability Analysis Shortlists Genetic Markers for Male Fertility Impairment

“…Thus, NCBI's OMIM (Online Mendelian Inheritance in Man) already lists more than 200 genetic conditions associated with male infertility, spanning from the most common manifestations to the rarest complex syndromes [Cariati et al, 2019]. However, the number of genes with potential fertility relevance is probably higher as illustrated by more than 6,200 proteins in sperm alone, which may at least partially influence male fertility [Shetty et al, 1999;Johnston et al, 2005;Schumacher et al, 2013;Amaral et al, 2014;Schumacher and Herlyn, 2018]. Beyond that, genes expressed in spermiogenesis stages and somatic testicular cells will play a role in fertility maintenance -and these are many.…”