Abstract
Recent work has shown that RNA polymerase II-mediated transcription at distal cis-regulatory elements serves as a mark of highly active enhancers. Production of noncoding RNAs at enhancers, termed eRNAs, correlates with higher expression of genes that the enhancer interacts with; hence, eRNAs provide a new tool to model gene activity in normal and disease tissues. Moreover, this unique class of noncoding RNA has diverse roles in transcriptional regulation. Transcribed enhancers can be identified by a common signature of epigenetic marks by overlaying a series of genome-wide chromatin immunoprecipitation and RNA sequencing datasets. A computational approach to filter non-enhancer elements and other classes of noncoding RNAs is essential to not cloud downstream analysis. Here we present a protocol that combines wet and dry bench methods to accurately identify transcribed enhancers genome-wide as well as an experimental procedure to validate these datasets.