A University of Michigan-led team explores regulatory features in islet cells in search of clues to type 2 diabetes. The researchers used a combination of standard RNA sequencing, strand-specific messenger RNA sequencing, genotyping, and/or chromatin immunoprecipitation sequencing to profile dozens of pancreatic islet cell samples, incorporating existing islet sample data into their analyses. Using data for 112 islet samples, they put together maps of cis-expression quantitative trait loci in this cell type, highlighting overlap between type 2 diabetes-associated variants and islet cell-specific regulatory binding sites.
Canadian researchers describe a role for the tumor suppressor p53 in regulating gene expression in mouse cardiac tissue. Using array-based messenger RNA profiling, the researchers tracked cardiac transcriptome patterns in vivo in conditional knockout mice in which p53 could be turned on and off specifically in the heart. From the thousands of gene transcripts that were differentially expressed in these animals, they tracked down gene clusters regulated by p53, including genes related to mitochondrial biogenesis, stress response, and other aspects of heart function.
The Salk Institute for Biological Studies' Joseph Ecker and colleagues introduce an algorithm for predicting regulatory element marks across various tissue types. The "regulatory element prediction based on tissue-specific local epigenetic marks," or REPTILE, tool brings genome-wide DNA methylation profiles together with histone modification marks to identify tissue-specific enhancer patterns — a computational approach the team validated using reporter assays and experiments in mouse and human cell types. "Compared with existing methods," the authors note, "we found that enhancer predictions from REPTILE are more likely to be active in vivo and the predicted locations are more accurate."