Customized MethylC-Capture Sequencing to Evaluate Variation in the Human Sperm DNA Methylome Representative of Altered Folate Metabolism

Chan, Donovan; Shao, Xiaojian; Dumargne, Marie-Charlotte; Aarabi, Mahmoud; Maguire, Simon; Kwan, Tony; Bailey, Janice L.; Robaire, Bernard; Kimmins, Sarah; Gabriel, Maria C. San; Zini, Armand; Librach, Clifford; Moskovtsev, Sergey I.; Grundberg, Elin; Bourque, Guillaume; Pastinen, Tomi; Trasler, Jacquetta M.

doi:10.1289/ehp4812

Cited by 27 publications

(42 citation statements)

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“…We utilized our previously characterized sperm capture panel [ 20 ] to enrich bisulphite sequencing coverage to regions variable in human sperm. We targeted 20–30 × coverage of each (n = 94) donor sample.…”

Section: Resultsmentioning

confidence: 99%

“…Notwithstanding the strong replication of earlier results, it is intriguing that most of our genome-wide-significant CpGs (> 99.5%) lie in regions not reported previously. We note that only 4.7% of the CpGs associated with aging in our dataset are actually represented on the Illumina 450 K microarray, explaining much of the new discovery stemming from the “dynamic sperm methylome” we specifically targeted by the capture methylome assay [ 20 ]. Overall, our results suggest pervasive influence of aging in shaping sperm methylome patterns.…”

Section: Resultsmentioning

confidence: 99%

“…Earlier studies on sperm DNA methylation were mostly focussed on imprinted loci [ 14 – 16 ]. Only a few studies have examined DNA methylation in human sperm on a genome-wide basis [ 17 – 20 ].…”

Section: Introductionmentioning

confidence: 99%

“…However, these arrays provide limited coverage of the epigenome, are biased toward genic and CpG-rich regions, and are not specific for the sperm epigenome. MethylC-capture sequencing (MCC-seq) was developed for targeted assessment of DNA methylation in a tissue-specific manner [ 29 ], and further customized to target human sperm epigenome with enrichment of sequences of interest in both genic and intergenic regions [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

“…The objective of the present study was to identify changes in human sperm DNA methylome as a function of paternal age and fertility status using our previously characterized sperm capture panel [ 20 ] in order to enrich bisulfite sequencing coverage to regions of variable and/or dynamic DNA methylation. We also included analyses of the relationship between paternal age and fertility status with total serum and bioavailable testosterone concentrations, serum FSH level, high density lipoprotein (HDL), and metabolic parameters as well as smoking.…”

Section: Introductionmentioning

confidence: 99%

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High-resolution analyses of human sperm dynamic methylome reveal thousands of novel age-related epigenetic alterations

et al. 2020

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Background Children of aged fathers are at a higher risk of developing mental disorders. Alterations in sperm DNA methylation have been implicated as a potential cause. However, age-dependent modifications of the germ cells’ epigenome remain poorly understood. Our objective was to assess the DNA methylation profile of human spermatozoa during aging. Results We used a high throughput, customized methylC-capture sequencing (MCC-seq) approach to characterize the dynamic DNA methylation in spermatozoa from 94 fertile and infertile men, who were categorized as young, 48 men between 18–38 years or old 46 men between 46–71 years. We identified more than 150,000 age-related CpG sites that are significantly differentially methylated among 2.65 million CpG sites covered. We conducted machine learning using our dataset to predict the methylation age of subjects; the age prediction accuracy based on our assay provided a more accurate prediction than that using the 450 K chip approach. In addition, we found that there are more hypermethylated (62%) than hypomethylated (38%) CpG sites in sperm of aged men, corresponding to 798 of total differential methylated regions (DMRs), of which 483 are hypermethylated regions (HyperDMR), and 315 hypomethylated regions (HypoDMR). Moreover, the distribution of age-related hyper- and hypomethylated CpGs in sperm is not random; the CpG sites that were hypermethylated with advanced age were frequently located in the distal region to genes, whereas hypomethylated sites were near to gene transcription start sites (TSS). We identified a high density of age-associated CpG changes in chromosomes 4 and 16, particularly HyperDMRs with localized clusters, the chr4 DMR cluster overlaps PGC1α locus, a protein involved in metabolic aging and the chr16 DMR cluster overlaps RBFOX1 locus, a gene implicated in neurodevelopmental disease. Gene ontology analysis revealed that the most affected genes by age were associated with development, neuron projection, differentiation and recognition, and behaviour, suggesting a potential link to the higher risk of neurodevelopmental disorders in children of aged fathers. Conclusion We identified thousands of age-related and sperm-specific epigenetic alterations. These findings provide novel insight in understanding human sperm DNA methylation dynamics during paternal aging, and the subsequently affected genes potentially related to diseases in offspring.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%