Genetic regulation of sperm DNA methylation in cattle through meQTL mapping

通过meQTL定位研究牛精子DNA甲基化的遗传调控

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Abstract

BACKGROUND: DNA methylation (DNAm) plays an important functional role and is influenced by genetic variants known as methylation QTLs (meQTLs). The majority of meQTL studies have been conducted in human blood. Despite its unique landscape, the genetic regulation of sperm DNAm remains largely unexplored. In this study, we leveraged DNAm measured in sperm from 405 Holstein bulls using reduced representation bisulfite sequencing (RRBS) and performed sequence-level genome-wide association studies for 166,985 variable CpGs (s.d. >5%). We reported heritability estimates and have mapped both cis-meQTLs and trans-meQTLs. RESULTS: Heritability estimates ranged from 0 to 1 and averaged 0.26 across all selected CpGs, with 76% of estimates above 0.1. The meQTL mapping revealed that 32.9% of the CpGs had a cis-meQTL, 3.6% had a trans-meQTL and 1.0% had both cis- and trans-meQTLs. The cis-CpGs were located on average 261 kb (absolute mean) from their cis-meQTL top SNPs (defined by the most significant association). MeQTLs were enriched in featured genomic annotations, including regions surrounding transcription start sites and ATAC-seq peaks. We also identified spurious trans-associations by analyzing data across multiple genome assemblies, including the construction of a partial pangenome. Additionally, eight trans-meQTL hotspots, defined as variants associated with at least 30 trans-CpGs, were identified and overlapped with genes involved in epigenetic regulation. Using peripheral blood mononuclear cell DNAm from 54 out of the 405 bulls, we did not observe a similar effect of the trans-meQTL hotspots to that one observed in sperm. CONCLUSIONS: For the first time, meQTLs have been detected and characterized in bovine sperm, contributing to a better understanding of the transmission of paternally inherited DNAm marks. These findings provide useful information for further research aimed at integrating epigenetic information into the prediction of performance traits.

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