Core et al devised and implemented a method termed global run-on sequencing, or GRO-seq, to map and quantify transcriptionally engaged RNA polymerases in a genome-wide fashion [28].
These asymmetric patterns correlated with the enhancer activities measured using global run-on sequencing (GRO-seq) data.
Recently, two technologies, the genome-wide nuclear run-on sequencing (GRO-seq) and native elongating transcript sequencing (NET-seq), have been described to study nascent transcripts.
Furthermore, studies using global run-on sequencing demonstrate that genes that have stalled Pol II express low, but significant levels of full-length transcripts (Core et al, 2008).
We have developed an analytical pipeline called groHMM for annotating primary transcripts using global nuclear run-on sequencing (GRO-seq) data.
We investigated the enhancer activities of these potential regulatory using the global run-on sequencing (GRO-seq) data in HeLa cells [ 39].
Publically available data on E2-stimulated gene expression were used from [ 3], where Global Run-On sequencing was applied to assess gene transcription after 0-, 10-, 40-, and 160-min E2 treatment.
Similarly, the position and orientation of RNAP and therefore the effective transcription rate can be determined by global run-on sequencing (GRO-Seq) [ 22], an analogous technique to ribosomal profiling that targets actively transcribing RNAPs.
As RNA-seq measures the steady state of RNA in the cell, and does not necessarily reflect active transcription, we added an analysis of global run-on sequencing (GRO-seq) data generated previously for IMR-90 cells [ 60].
We then determined transcription rates by measuring RNA polymerase II (Pol II) occupancy (Rpb3 chromatin immunoprecipitation sequencing (ChIP-seq); Adelman et al., 2005) and nascent RNA polymerase output via global run-on sequencing (GRO-seq; Figures S2A and S2B; Core et al., 2008).
