Bio-Protocol (Jun 2021)

Transcriptional Run-on: Measuring Nascent Transcription at Specific Genomic Sites in Yeast

  • Victoria Begley,
  • Lola de Miguel-Jiménez,
  • Sebastián Chávez

DOI
https://doi.org/10.21769/BioProtoc.4064
Journal volume & issue
Vol. 11, no. 12

Abstract

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DNA transcription by RNA polymerases has always interested the scientific community as it is one of the most important processes involved in genome expression. This has led scientists to come up with different protocols allowing analysis of this process in specific locations across the genome by quantitating the amount of RNA polymerases transcribing that genomic site in a cell population. This can be achieved by either detecting the total number of polymerases in contact with that region (i.e., by chromatin immunoprecipitation (ChIP) with anti-RNA polymerase antibodies) or by measuring the number of polymerases that are effectively engaged in transcription in that position. This latter strategy is followed using transcription run-on (TRO), also known as nuclear run-on (NRO), which was first developed in mammalian cells over 40 years ago and has since been adapted to many other different organisms and high-throughput methods. Here, we detail the procedure for performing TRO in Saccharomyces cerevisiae for single genomic regions to study active transcription on a single gene scale. To do so, we wash the cells in the detergent sarkosyl, which prevents new initiations at the promoter level, and then perform an in situ reaction, leading to the radiolabeling of transcripts by RNA polymerases that were already engaged in transcription at the moment of harvesting. By subsequently quantitating the signal of these transcripts, we can determine the level of active transcription in a single gene. This presents a major advantage over other forms of transcription quantitation such as RNA polymerase ChIP, since in the latter, both active and inactive polymerases are measured. By combining both ChIP and TRO, the amount of inactive or paused polymerases on a particular gene can be estimated.Graphic abstract:Transcriptional run-on scheme