![]() GRO-seq yields an exact footprint of already engaged RNA polymerase by building upon the strengths of a 40-year-old assay ( Gariglio et al., 1974, 1981). Global run-on sequencing (GRO-seq) was the first genome-wide technique developed to probe nascent transcription genome-wide ( Core et al., 2008). Nascent transcripts represent the small RNA fraction (>0.5% of total RNA content in a cell) that is actively synthesized and still associated with RNA polymerase. To overcome limitations of RNA-seq, several groups have developed high-throughput methods that tap into the so-called “nascent” fraction of cellular RNA ( Wissink et al., 2019). For instance, biologically active enhancer RNAs (eRNAs) and other lincRNA species are hardly represented in conventional transcriptomic data ( Lai and Shiekhattar, 2014 Gardini and Shiekhattar, 2015). Lastly, there are low-abundant and poorly stable RNA species that fall below the RNA-seq detection threshold. There are multiple, critical, regulatory steps and checkpoints all along the transcription cycle that cannot be discerned with the resolution offered by RNA-seq ( Adelman and Lis, 2012 Kwak and Lis, 2013 Proudfoot, 2016). Additionally, transcription by RNA polymerase II (RNAPII) is not a steady and passive process of ribonucleotide chain assembly. Therefore, RNA-seq alone is insufficient to infer the accurate transcriptional activity of any given gene. Both RNA processing and stability are highly regulated in every cell type ( Schoenberg and Maquat, 2012 Pai and Luca, 2019 Yamada and Akimitsu, 2019). Steady-state RNA levels are the ultimate result of synthesis rate, RNA processing, and RNA stability. First, traditional RNA-seq measures steady-state, mostly cytoplasmic, RNA species. Regardless the specific protocol of choice, there are several limitations to these widely used RNA-sequencing (RNA-seq) techniques. ![]() Adaptor ligation and PCR-based amplification convert the original pool of RNAs into a sequencing-ready library that will generate quantitative transcriptomic profiles ( Stark et al., 2019). Usually, RNA is extracted from crude cell extracts via acidic phenol-chloroform precipitation and either reverse transcribed with oligo(dT) or subjected to ribosomal RNA depletion, first, followed by reverse transcription using a pool of short random oligos (thus avoiding the polyadenylation bias). In slightly more than a decade, next-generation sequencing (NGS) technology has revolutionized the field of transcription by allowing precision mapping of most RNA species, from mRNAs to large intergenic noncoding RNAs (lincRNAs). Importantly, we demonstrate that fastGRO is scalable and can be performed with as few as 0.5 × 10 6 cells. We show that fastGRO is highly reproducible and yields a more complete and extensive coverage of nascent RNA than comparable techniques can. We named the technique fastGRO (fast Global Run-On). Our protocol allows streamlined sample preparation within less than 3 days. Here, we present a run-on assay with 4-thio ribonucleotide (4-S-UTP) labeling, followed by reversible biotinylation and affinity purification via streptavidin. Furthermore, nascent RNA-seq detects post-cleavage RNA at termination sites and promoter-associated antisense RNAs, providing insights into RNA polymerase II (RNAPII) dynamics and processivity. Some species of nuclear RNAs (i.e., large intergenic noncoding RNAs and eRNAs) have a short half-life and can only be accurately gauged by nascent RNA techniques. Unlike steady-state RNA-sequencing (RNA-seq), nascent RNA profiling mirrors real-time activity of RNA polymerases and provides an accurate readout of transcriptome-wide variations. Genome-wide profiling of nascent RNA has become a fundamental tool to study transcription regulation.
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