Characterization of DNA methylation clock algorithms applied to diverse tissue types.

Background: DNA methylation (DNAm) data from human samples has been leveraged to develop "epigenetic clock" algorithms that predict age and other aging-related phenotypes. Some DNAm clocks were trained using DNAm obtained from blood cells, while other clocks were trained using data from diverse tissue/cell types. To assess how DNAm clocks perform across non-blood tissue types, we applied DNAm algorithms to DNAm data generated from 9 different human tissue types.

Differential DNA methylation in the benign and cancerous prostate tissue of African American and European American men.

Background: African American (AA) men are at increased risk of prostate cancer (PCa) compared to men of European ancestry (EA). Biological mechanisms, including epigenetics, likely contribute to this disparity, but prior studies have been limited by sample size, candidate gene approaches, or lack of epigenome-wide DNA methylation (DNAm) data.

Methods: To improve our understanding of these mechanisms, we compared DNAm features distinguishing tumor and paired histologically benign tissue from 76 AA and 75 EA PCa patients.

Alternative splicing induces sample-level variation in gene-gene correlations.

Background: The vast majority of genes in the genome are multi-exonic, and are alternatively spliced during transcription, resulting in multiple isoforms for each gene. For some genes, different mRNA isoforms may have differential expression levels or be involved in different pathways. Bulk tissue RNA-seq, as a widely used technology for transcriptome quantification, measures the total expression (TE) levels of each gene across multiple isoforms in multiple cell types for each tissue sample.