Epigenetic determinants of reproductive potential augment the predictive ability of the semen analysis.

OBJECTIVE: To investigate the power of DNA methylation variability in sperm cells in assessing male fertility potential. DESIGN: Retrospective cohort. SETTING: Fertility care centers. PATIENTS: Male patients seeking infertility treatment and fertile male sperm donors. INTERVENTION: None. MAIN OUTCOME MEASURES: Sperm DNA methylation data from 43 fertile sperm donors were analyzed and compared with the data from 1344 men seeking fertility assessment or treatment. Methylation at gene promoters with the least variable methylation in fertile patients was used to create 3 categories of promoter dysregulation in the infertility treatment cohort: poor, average, and excellent sperm quality. RESULTS: After controlling for female factors, there were significant differences in intrauterine insemination pregnancy and live birth outcomes between the poor and excellent groups across a cumulative average of 2-3 cycles: 19.4% vs. 51.7% (P=.008) and 19.4% vs. 44.8% (P=.03), respectively. Live birth outcomes from in vitro fertilization, primarily with intracytoplasmic sperm injection, were not found to be significantly different among any of the 3 groups. CONCLUSION: Methylation variability in a panel of 1233 gene promoters could augment the predictive ability of semen analysis and be a reliable biomarker for assessing intrauterine insemination outcomes. In vitro fertilization with intracytoplasmic sperm injection appears to overcome high levels of epigenetic instability in sperm.

Tissue-specific DNA methylation variability and its potential clinical value.

Complex diseases have multifactorial etiologies making actionable diagnostic biomarkers difficult to identify. Diagnostic research must expand beyond single or a handful of genetic or epigenetic targets for complex disease and explore a broader system of biological pathways. With the objective to develop a diagnostic tool designed to analyze a comprehensive network of epigenetic profiles in complex diseases, we used publicly available DNA methylation data from over 2,400 samples representing 20 cell types and various diseases. This tool, rather than detecting differentially methylated regions at specific genes, measures the intra-individual methylation variability within gene promoters to identify global shifts away from healthy regulatory states. To assess this new approach, we explored three distinct questions: 1) Are profiles of epigenetic variability tissue-specific? 2) Do diseased tissues exhibit altered epigenetic variability compared to normal tissue? 3) Can epigenetic variability be detected in complex disease? Unsupervised clustering established that global epigenetic variability in promoter regions is tissue-specific and promoter regions that are the most epigenetically stable in a specific tissue are associated with genes known to be essential for its function. Furthermore, analysis of epigenetic variability in these most stable regions distinguishes between diseased and normal tissue in multiple complex diseases. Finally, we demonstrate the clinical utility of this new tool in the assessment of a multifactorial condition, male infertility. We show that epigenetic variability in purified sperm is correlated with live birth outcomes in couples undergoing intrauterine insemination (IUI), a common fertility procedure. Men with the least epigenetically variable promoters were almost twice as likely to father a child than men with the greatest number of epigenetically variable promoters. Interestingly, no such difference was identified in men undergoing in vitro fertilization (IVF), another common fertility procedure, suggesting this as a treatment to overcome higher levels of epigenetic variability when trying to conceive.

A chemical approach to mapping nucleosomes at base pair resolution in yeast.

Most eukaryotic DNA exists in DNA-protein complexes known as nucleosomes. The exact locations of nucleosomes along the genome play a critical role in chromosome functions and gene regulation. However, the current methods for nucleosome mapping do not provide the necessary accuracy to identify the precise nucleosome locations. Here we describe a new experimental approach that directly maps nucleosome center locations in vivo genome-wide at single base pair resolution.