Search bioRxiv⌕ Search

Biology subjects

Carrell, D. T.

Publications and source records attributed to Carrell, D. T..

2 recordsLinked to original sources

Paternal cigarette smoke alters DNA methylation in sperm and gene expression in offspring brain

Paternal cigarette smoke (CS) exposure is associated with increased risk of behavioral disorders and cancer in offspring, but the mechanism has not been identified. This study used mouse models to evaluate: 1) what impact paternal CS exposure has on sperm DNA methylation (DNAme), 2) whether sperm DNAme changes persist after CS exposure ends, 3) the degree to which DNAme and gene expression changes occur in offspring and 4) the mechanism underlying impacts of CS exposure. We demonstrate that CS exposure induces sperm DNAme changes that are partially corrected within 28 days of removal from CS exposure. Additionally, paternal smoking causes changes in neural DNAme and gene expression in offspring. Remarkably, the effects of CS exposure are largely recapitulated in oxidative stress-compromised Nrf2-/- mice and their offspring, independent of paternal smoking. These results demonstrate that paternal CS exposure impacts offspring phenotype and that oxidative stress underlies CS induced heritable epigenetic changes.

genetics↗

Germ line aging and regional epigenetic instability: age prediction using human sperm DNA methylation signatures

BackgroundThe relationship between aging and epigenetic profiles has been highlighted in many recent studies. Models using somatic cell methylomes to predict age have been successfully constructed. However, gamete aging is quite distinct and as such age prediction using sperm methylomes is ineffective with current techniques.\n\nResultsWe have produced a model that utilizes human sperm DNA methylation signatures to predict chronological age by utilizing methylation array data from a total of 329 samples. The dataset used for model construction includes infertile patients, sperm donors, and individuals from the general population. Our model is capable of accurately predicting age with an R2 of 0.928 in our test data set. We additionally investigated the repeatability of prediction by processing the same sample on 6 different arrays and found very robust age prediction with an average standard deviation of only 0.877 years. Additionally, we found that smokers have approximately 5% increased age profiles compared to never smokers.\n\nConclusionsThe predictive model described herein was built to offer researchers the ability to assess \"germ line age\" by accessing sperm DNA methylation signatures at genomic regions affected by age. Our data suggest that this model can predict an individuals chronological age with a high degree of accuracy regardless of fertility status and with a high degree of repeatability. Additionally, our data appear to show age acceleration patterns as a result of smoking suggesting that the aging process in sperm may be impacted by environmental factors, though this effect appears to be quite subtle.

genetics↗