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Deciphering the Sperm RNA Code of Aging with PANDORA-seq

ABSTRACT: Sperm aging impacts male fertility and offspring health, highlighting the need for reliable aging biomarkers to guide reproductive decisions. Using PANDORA-seq, a novel method to comprehensively profile small non-coding RNAs (sncRNAs), we identified an "aging cliff" in mouse sperm RNA profiles-a sharp age-specific transition marked by significant shifts in genomic and mitochondrial tRNA-derived small RNAs (tsRNAs) and rRNA-derived small RNAs (rsRNAs). Notably, rsRNAs embedded in sperm heads exhibited a transformative length shift, with longer rsRNAs increasing and shorter ones decreasing with age, suggesting altered biogenesis with age. Remarkably, this sperm rsRNA length shift was consistently observed in two independent human aging cohorts, highlighting its evolutionary significance. Moreover, a combination of tsRNAs and rsRNAs (tsRNA/rsRNA cocktails) resembling those in aged sperm induced transcriptomic changes in embryonic stem cells, impacting metabolism and neurodegeneration pathways, mirroring the phenotypes observed in offspring of aged sperm. These results reveal new insights of sperm aging, highlighting the conserved rsRNA length shift in mice and humans, with translational potential for fertility and intergenerational health

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE256182 | GEO | 2025/12/04

REPOSITORIES: GEO

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Project description:<h4><strong>BACKGROUND: </strong>Semen quality is negatively correlated with male age and is mainly quantified by a routine semen analysis, which is descriptive and inconclusive. Sperm proteins or semen metabolites are used as the intermediate or end-products, reflecting changes in semen quality, and hold much promise as a new biomarker to predict fertility in advanced-aged males.</h4><h4><strong>OBJECTIVES: </strong>In this study, we sought to assess whether the semen metabolome and proteome of aged males can affect semen quality and serve as biomarkers for predicting semen quality.</h4><p><strong>MATERIALS AND METHODS: </strong>We retrospectively analyzed 12825 males that underwent semen routine analysis to understand the age-dependent changes in sperm quality. To identify the difference between aged and young adults, metabolomics (n=60) analyses of semen and proteomics (n=12) analyses of sperm were conducted. Finally, integrated machine learning of metabolomics was conducted to screen biomarkers to identify aging semen.</p><p><strong>RESULTS:</strong> We discovered that male age was positively correlated with sperm concentration as well as DNA fragmentation index(DFI), and negatively with progressive motile sperm count, total sperm count, sperm volume and progressive sperm motility. The differential metabolites were significantly enriched in various metabolic pathways, and four of these differential metabolites (Pipamperone, 2,2-Bis(hydroxymethyl)-2,2',2''-nitrilotriethanol, Arg-Pro and Triethyl phosphate) were utilized to establish a biomarker panel to identify aging semen. Proteomic analysis showed that differential proteins were significantly enriched in protein digestion and absorption and some energy-related pathways. An integrated analysis of the metabolome and proteome identified differential energy metabolism and oxidative stress-related proteins, which could explain the decreased motility and the increased DFI of aging sperm.</p><p><strong>DISCUSSION AND CONCLUSION:</strong> We provide compelling evidence that the changes in semen metabolome and sperm proteome are related to the decline of semen quality in aged males. Moreover, a biomarker panel based on four metabolites was established to identify aging semen.</p>

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Deciphering the Sperm RNA Code of Aging with PANDORA-seq

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