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Sexual dimorphism involves distinct anatomical, physiological, behavioral, and developmental differences between males and females of the same species, influenced by factors prior to conception and during early development. These sex-specific traits contribute to varied phenotypes and individual disease risks within and across generations and understanding them is essential in mammalian studies. Hormones, sex chromosomes, and imprinted genes drive this dimorphism, with over half of quantitative traits in wildtype mice showing sex-based variation. This review focuses on the impact of paternal non-genetic factors on sexual dimorphism. We synthesize current research on how paternal health before conception affects offspring phenotypes in a sex-specific manner, examining mechanisms such as DNA methylation, paternally imprinted genes, sperm RNA, and seminal plasma. Additionally, we explore how paternal influences indirectly shape offspring through maternal behavior, uterine environment, and placental changes, affecting males and females differently. We propose mechanisms modulating sexual dimorphism during development, underscoring the need for sex-specific documentation in animal studies. [ABSTRACT FROM AUTHOR]

Modification of DNA bases plays important roles in the epigenetic regulation of eukaryotic gene expression. Among the different types of DNA methylation, 5-methylcytosine (5mC) is common in higher eukaryotes. Although bisulfite sequencing is the established detection method for this modification, newer methods, such as Oxford nanopore sequencing, have been developed as quick and reliable alternatives. An earlier study using sensitive liquid chromatography tandem mass spectrometry (LC-MS/MS) indicated the presence of 5mC at very low concentration in Saccharomyces cerevisiae . More recently, a comprehensive study of the yeast genome found 40 5mC sites using the computational tool Nanopolish on nanopore sequencing output raw data. In the present study, we are trying to validate the prediction of the 5mC modifications in yeast with Nanopolish and two other nanopore software tools, Tombo and DeepSignal. Using publicly available genome sequencing data, we compared the open-access computational tools, including Tombo, Nanopolish and DeepSignal, for predicting 5mC. Our results suggest that these tools are indeed capable of predicting DNA 5mC modifications at a specific location from Oxford nanopore sequencing data. We also predicted that 5mC present in the S. cerevisiae genome might be located predominantly at the RDN locus of chromosome 12., Competing Interests: The authors declare that there are no conflicts of interest., (© 2022 The Authors.)