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Peromyscus maniculatus DNAm Data

ABSTRACT: Kinship relationships between parents affect offspring fitness. Beyond its effects in heterozygosity or its impact in deleterious alleles that can be reduced to homozygosity and decrease the individuals’ fitness, the consequences of parental relatedness in the offspring remain understudied. By leveraging the availability of detailed pedigrees of captive Peromyscus we explored how parental relatedness impacts the methylome and the epigenetic age estimation of the offspring. Global CpG methylation analysis showed that parental relatedness positively impacts lifespan expectancy and reduces epigenetic aging, contributing about 13% of variation in epigenetic age estimation. Global hypermethylation due to relatedness was considerably higher than hypomethylation, was more pronounced in the male offspring, and mainly affected chromosomal loci associated with development. A relatedness-associated methylation signature was described that predicts parental relatedness with high accuracy, providing the proof of concept that kinship relationships can be inferred by epigenetic analyses. These findings identify parental relatedness as a modifier of epigenetic aging and global methylation, suggesting that kinship relations should be considered when epigenetic, and potentially transcriptomic data are interpreted in the context of aging and of other pathophysiological processes.

ORGANISM(S): Rattus norvegicus Mus musculus Peromyscus maniculatus bairdii Homo sapiens

PROVIDER: GSE314002 | GEO | 2025/12/23

REPOSITORIES: GEO

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Project description:Environmental challenges experienced by an organism can have multiple effects at an individual level, with recent work also suggesting these challenges may affect their unexposed offspring. In a time of rapid environmental change, understanding whether environmental challenges experienced by organisms could increase the fitness of future generations to survive these same stressors, is critically needed. Low dissolved oxygen is a common environmental challenge that aquatic organisms encounter, resulting in numerous physiological, phenotypic, and epigenetic changes. In this study, we use zebrafish (Danio rerio) as a model to investigate how paternal hypoxia experience impacts subsequent progeny. Males were exposed to moderate hypoxia (11-13 kPA) for 2 weeks, bred to create an F1 generation, and progeny underwent an acute hypoxia (0-1 kPA) tolerance assay. Using time to loss of equilibrium and loss of equilibrium frequency as measured of hypoxia resistance, we show that paternal exposure to hypoxia endow offspring with a greater tolerance to acute hypoxia, compared to offspring of unexposed males, though there are strong family x treatment effects. In addition to phenotypic alternations, we also investigated changes in gene expression in offspring. We conducted RNA-Seq on whole fry and detected 91 differentially expressed genes, including two hemoglobin genes that are significantly upregulated by more than 4-fold in the offspring of hypoxia exposed males. Moreover, the offspring which maintained equilibrium the longest showed the greatest upregulation in hemoglobin expression. Paternal exposures to physiological challenges are thus able to impact the phenotype and gene expression of their unexposed progeny. We conducted whole genome bisulfite sequencing (WGBS) on the sperm of parental males to assess whether changes in progeny phenotype and gene expression are underpinned by changes in DNA methylation. While we observed coupling of methylation levels in the parental sperm and gene expression in progeny overall, we did not detect differential methylation at any of the differentially expressed genes, suggesting that another epigenetic mechanism is responsible for the observed changes in gene expression. Overall, our findings suggest that a ‘memory’ of past hypoxia exposure is maintained and that this environmentally induced information is transferred to subsequent generations, pre-acclimating progeny to cope with hypoxic conditions.

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Peromyscus maniculatus DNAm Data

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