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.