The DNA methylome of human sperm is distinct from blood with little evidence for tissue-consistent obesity associations

Sperm chromatin: Evaluation, epigenetic signatures and relevance for embryo development and assisted reproductive technology outcomes

Sperm chromatin is distinct from somatic cell chromatin, as a result of extensive remodeling during the final stages of spermatogenesis. In this process, the majority of histones is replaced with protamines. The chromatin is consequently highly condensed and inert, which facilitates protection of the DNA. The sperm epigenomic landscape is shaped by histone retention, histone and protamine modification, DNA methylation, and RNAs. In recent years, sperm chromatin integrity and its epigenetic marks have been increasingly studied, and the constitution of sperm chromatin is steadily being uncovered. This growing body of research prompts assessment of the frequently overlooked involvement of sperm in fertility and embryonic development. Moreover, numerous endogenous and exogenous factors are known to affect sperm chromatin, which may in turn impact the reproductive success. Concerns have been raised about the effects of assisted reproductive technology (ART) on the sperm epigenome, embryonic development and offspring health. This review examines the structure and epigenetic signatures of sperm chromatin in the context of fertility and early embryonic development. Additionally, sperm chromatin evaluation and causes of aberrant integrity are outlined. Building on the knowledge discussed in the current review, future research should aim to elucidate the intricate relationship between all aspects of sperm chromatin and embryo development. This could lead to the uncovering of new targets for treating infertility, as well as the acquisition of much needed insights into the possible reciprocal association between ART and sperm chromatin integrity.

The association between DNA methylation and human height and a prospective model of DNA methylation-based height prediction

As a vital anthropometric characteristic, human height information not only helps to understand overall developmental status and genetic risk factors, but is also important for forensic DNA phenotyping. We utilized linear regression analysis to test the association between each CpG probe and the height phenotype. Next, we designed a methylation sequencing panel targeting 959 CpGs and subsequent height inference models were constructed for the Chinese population. A total of 11,730 height-associated sites were identified. By employing KPCA and deep neural networks, a prediction model was developed, of which the cross-validation RMSE, MAE and R2 were 5.62 cm, 4.45 cm and 0.64, respectively. Genetic factors could explain 39.4% of the methylation level variance of sites used in the height inference models. Collectively, we demonstrated an association between height and DNA methylation status through an EWAS analysis. Targeted methylation sequencing of only 959 CpGs combined with deep learning techniques could provide a model to estimate human height with higher accuracy than SNP-based prediction models.

Improved age estimation from semen using sperm-specific age-related CpG markers

Accurate age estimation from semen has the potential to greatly narrow the pool of unidentified suspects in sexual assault investigations. However, previous efforts utilizing semen age-related CpG (AR-CpG) markers have shown lower accuracy compared to blood AR-CpG-based methods. This discrepancy may be attributed to DNA methylation (DNAm) interferences from "round cells" such as leukocytes and immature sperm cells in semen. This study aimed to develop age calculators based on sperm-specific AR-CpG markers and to achieve performance-improved age estimates from sperm DNA. Through an analysis of publicly available MethylationEPIC microarray data from 90 sperm samples of healthy males aged 22-51 years, we identified 31 sperm-specific AR-CpG markers with absolute Pearson's R values > 0.5 and Benjamini-Hochberg adjusted p values < 0.013. The top 19 AR-CpG markers with the largest absolute R values and beta ranges > 0.10, along with 3 reported semen AR-CpG markers (cg06304190, cg06979108, and cg12837463), were integrated into two methylation SNaPshot panels (Ⅰ and Ⅱ), each containing 11 markers. The 21 qualified AR-CpG markers showed absolute R values ≥ 0.427 in an independent validation cohort of 253 sperm DNA samples (22-67 years), with cg21843517 exhibiting the strongest age correlation (R = 0.853). The optimal models, constructed using sperm DNAm data of the training set (n = 214, 22-67 years) and markers from panel Ⅰ (n = 11), panel Ⅱ (n = 10), or both panels, achieved mean absolute errors (MAEs) of 2.526-4.746, 3.890-5.715, and > 9.800 years on the test sets of sperm (n = 39, 23-64 years), semen (same donors as the sperm test set), and whole blood (n = 40, 22-65 years), respectively. The simplified models incorporating 3, 5, 9, or 14 AR-CpG markers (MAE = 2.918-4.139 years for sperm) still outperformed the Lee et al. original model (MAE = 6.444 years for semen) and the reconstructed panel Lee model (MAE = 6.011 years for sperm). The final models, utilizing all sperm DNAm data (n = 253) and markers from panel Ⅰ, panel Ⅱ, or both panels, yielded mean MAEs of 2.587, 2.766, and 2.200 years, respectively, on the 50 test sets generated by 5 repeats of 10-fold cross-validations. Additionally, multiple markers in both panels demonstrated the ability to discern sperm or semen from blood with 100% accuracy. In summary, our study substantiates the potential of sperm-specific AR-CpG markers for precise age estimation from sperm DNA, providing an improved toolset for forensic investigations.

Quantitative trait locus for calving traits on Bos taurus autosome 18 in Holstein cattle is embedded in a complex genomic region

Although the quantitative trait locus (QTL) on chromosome 18 (BTA18) associated with paternal calving ease and stillbirth in Holstein Friesian cattle and its cross has been known for over 20 years, to our knowledge, the exact causal genetic sequence has yet escaped identification. The aim of this study was to re-examine the region of the published QTL on BTA18 and to investigate the possible reasons behind this elusiveness. For this purpose, we carried out a combined linkage disequilibrium and linkage analysis using genotyping data of 2,697 German Holstein Friesian (HF) animals and subsequent whole-genome sequencing (WGS) data analyses and genome assembly of HF samples. We confirmed the known QTL in the 95% confidence interval of 1.089 Mbp between 58.34 and 59.43 Mbp on BTA18. Additionally, these 4 SNPs in the near-perfect linkage disequilibrium with the QTL haplotype were identified: rs381577268 (on 57,816,137 bp, C/T), rs381878735 (on 59,574,329 bp, A/T), rs464221818 (on 59,329,176 bp, C/T), and rs472502785 (on 59,345,689 bp, T/C). Search for the causal mutation using short and long-read sequences, and methylation data of the BTA18 QTL region did not reveal any candidates though. The assembly showed problems in the region, as well as an abundance of segmental duplications within and around the region. Taking the QTL of BTA18 in Holstein cattle as an example, the data presented in this study comprehensively characterize the genomic features that could also be relevant for other such elusive QTL in various other cattle breeds and livestock species as well.

Inheritance of paternal lifestyles and exposures through sperm DNA methylation

Many different lifestyle factors and chemicals present in the environment are a threat to the reproductive tracts of humans. The potential for parental preconception exposure to alter gametes and for these alterations to be passed on to offspring and negatively affect embryo growth and development is of concern. The connection between maternal exposures and offspring health is a frequent focus in epidemiological studies, but paternal preconception exposures are much less frequently considered and are also very important determinants of offspring health. Several environmental and lifestyle factors in men have been found to alter sperm epigenetics, which can regulate gene expression during early embryonic development. Epigenetic information is thought to be a mechanism that evolved for organisms to pass on information about their lived experiences to offspring. DNA methylation is a well-studied epigenetic regulator that is sensitive to environmental exposures in somatic cells and sperm. The continuous production of sperm from spermatogonial stem cells throughout a man's adult life and the presence of spermatogonial stem cells outside of the blood-testis barrier makes them susceptible to environmental insults. Furthermore, altered sperm DNA methylation patterns can be maintained throughout development and ultimately result in impairments, which could predispose offspring to disease. Innovations in human stem cell-based spermatogenic models can be used to elucidate the paternal origins of health and disease.

Methylation status of VTRNA2-1/nc886 is stable across populations, monozygotic twin pairs and in majority of tissues

Aims & methods: The aim of this study was to characterize the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues.48 datasets, consisting of more than 30 tissues and >30,000 individuals, were used. Results: nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, whereas ∼30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. Conclusion: The nc886 imprint may be established in the oocyte, and, after implantation, the methylation status is stable, excluding a few specific tissues.

Accelerated biological aging in COVID-19 patients

Chronological age is a risk factor for SARS-CoV-2 infection and severe COVID-19. Previous findings indicate that epigenetic age could be altered in viral infection. However, the epigenetic aging in COVID-19 has not been well studied. In this study, DNA methylation of the blood samples from 232 healthy individuals and 413 COVID-19 patients is profiled using EPIC methylation array. Epigenetic ages of each individual are determined by applying epigenetic clocks and telomere length estimator to the methylation profile of the individual. Epigenetic age acceleration is calculated and compared between groups. We observe strong correlations between the epigenetic clocks and individual's chronological age (r > 0.8, p < 0.0001). We also find the increasing acceleration of epigenetic aging and telomere attrition in the sequential blood samples from healthy individuals and infected patients developing non-severe and severe COVID-19. In addition, the longitudinal DNA methylation profiling analysis find that the accumulation of epigenetic aging from COVID-19 syndrome could be partly reversed at late clinic phases in some patients. In conclusion, accelerated epigenetic aging is associated with the risk of SARS-CoV-2 infection and developing severe COVID-19. In addition, the accumulation of epigenetic aging from COVID-19 may contribute to the post-COVID-19 syndrome among survivors.

Epigenetics of Male Infertility: The Role of DNA Methylation

In recent years, a number of studies focused on the role of epigenetics, including DNA methylation, in spermatogenesis and male infertility. We aimed to provide an overview of the knowledge concerning the gene and genome methylation and its regulation during spermatogenesis, specifically in the context of male infertility etiopathogenesis. Overall, the findings support the hypothesis that sperm DNA methylation is associated with sperm alterations and infertility. Several genes have been found to be differentially methylated in relation to impaired spermatogenesis and/or reproductive dysfunction. Particularly, DNA methylation defects of MEST and H19 within imprinted genes and MTHFR within non-imprinted genes have been repeatedly linked with male infertility. A deep knowledge of sperm DNA methylation status in association with reduced reproductive potential could improve the development of novel diagnostic tools for this disease. Further studies are needed to better elucidate the mechanisms affecting methylation in sperm and their impact on male infertility.

Human methylome variation across Infinium 450K data on the Gene Expression Omnibus

While DNA methylation (DNAm) is the most-studied epigenetic mark, few recent studies probe the breadth of publicly available DNAm array samples. We collectively analyzed 35 360 Illumina Infinium HumanMethylation450K DNAm array samples published on the Gene Expression Omnibus. We learned a controlled vocabulary of sample labels by applying regular expressions to metadata and used existing models to predict various sample properties including epigenetic age. We found approximately two-thirds of samples were from blood, one-quarter were from brain and one-third were from cancer patients. About 19% of samples failed at least one of Illumina's 17 prescribed quality assessments; signal distributions across samples suggest modifying manufacturer-recommended thresholds for failure would make these assessments more informative. We further analyzed DNAm variances in seven tissues (adipose, nasal, blood, brain, buccal, sperm and liver) and characterized specific probes distinguishing them. Finally, we compiled DNAm array data and metadata, including our learned and predicted sample labels, into database files accessible via the recountmethylation R/Bioconductor companion package. Its vignettes walk the user through some analyses contained in this paper.