Recent advances in sequencing techniques that measure nascent transcripts and that reveal the positioning of RNA polymerase II (Pol II) have shown that the pausing of Pol II in promoter-proximal regions and its release to initiate a phase of productive elongation are key steps in transcription regulation. Moreover, after the release of Pol II from the promoter-proximal region, elongation rates are highly dynamic throughout the transcription of a gene, and vary on a gene-by-gene basis. Interestingly, Pol II elongation rates affect co-transcriptional processes such as splicing, termination and genome stability. Increasing numbers of factors and regulatory mechanisms have been associated with the steps of transcription elongation by Pol II, revealing that elongation is a highly complex process. Elongation is thus now recognized as a key phase in the regulation of transcription by Pol II.

Production of mRNA depends critically on the rate of RNA polymerase II (Pol II) elongation. To dissect Pol II dynamics in mouse ES cells, we inhibited Pol II transcription at either initiation or promoter-proximal pause escape with Triptolide or Flavopiridol, and tracked Pol II kinetically using GRO-seq. Both inhibitors block transcription of more than 95% of genes, showing that pause escape, like initiation, is a ubiquitous and crucial step within the transcription cycle. Moreover, paused Pol II is relatively stable, as evidenced from half-life measurements at ∼3200 genes. Finally, tracking the progression of Pol II after drug treatment establishes Pol II elongation rates at over 1000 genes. Notably, Pol II accelerates dramatically while transcribing through genes, but slows at exons. Furthermore, intergenic variance in elongation rates is substantial, and is influenced by a positive effect of H3K79me2 and negative effects of exon density and CG content within genes.DOI: http://dx.doi.org/10.7554/eLife.02407.001

We provide a protocol for precision nuclear run-on sequencing (PRO-seq) and its variant, PRO-cap, which map the location of active RNA polymerases (PRO-seq) or transcription start sites (TSSs) (PRO-cap) genome-wide at high resolution. The density of RNA polymerases at a particular genomic locus directly reflects the level of nascent transcription at that region. Nuclei are isolated from cells and, under nuclear run-on conditions, transcriptionally engaged RNA polymerases incorporate one or, at most, a few biotin-labeled nucleotide triphosphates (biotin-NTPs) into the 3′ end of nascent RNA. The biotin-labeled nascent RNA is used to prepare sequencing libraries, which are sequenced from the 3′ end to provide high-resolution positional information for the RNA polymerases. PRO-seq provides much higher sensitivity than ChIP-seq, and it generates a much larger fraction of usable sequence reads than ChIP-seq or NET-seq (native elongating transcript sequencing). Similarly to NET-seq, PRO-seq maps the RNA polymerase at up to base-pair resolution with strand specificity, but unlike NET-seq it does not require immunoprecipitation. With the protocol provided here, PRO-seq (or PRO-cap) libraries for high-throughput sequencing can be generated in 4–5 working days. The method has been applied to human, mouse, Drosophila melanogaster and Caenorhabditis elegans cells and, with slight modifications, to yeast.

Most disease-associated genetic variants are noncoding, making it challenging to design experiments to understand their functional consequences. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer the downstream effects of disease-associated variants, but most of these variants remain unexplained. The analysis of DNA methylation, a key component of the epigenome, offers highly complementary data on the regulatory potential of genomic regions. Here we show that disease-associated variants have widespread effects on DNA methylation in trans that likely reflect differential occupancy of trans binding sites by cis-regulated transcription factors. Using multiple omics data sets from 3,841 Dutch individuals, we identified 1,907 established trait-associated SNPs that affect the methylation levels of 10,141 different CpG sites in trans (false discovery rate (FDR) < 0.05). These included SNPs that affect both the expression of a nearby transcription factor (such as NFKB1, CTCF and NKX2-3) and methylation of its respective binding site across the genome. Trans methylation QTLs effectively expose the downstream effects of disease-associated variants.