Total RNA-seq to identify pharmacological effects on specific stages of mRNA synthesis

Abstract

Pharmacological perturbation is a powerful tool for understanding mRNA synthesis, but identification of the specific steps of this multi-step process that are targeted by small molecules remains challenging. Here we applied strand-specific total RNA sequencing (RNA-seq) to identify and distinguish specific pharmacological effects on transcription and pre-mRNA processing in human cells. We found unexpectedly that the natural product isoginkgetin, previously described as a splicing inhibitor, inhibits transcription elongation. Compared to well-characterized elongation inhibitors that target CDK9, isoginkgetin caused RNA polymerase accumulation within a broader promoter-proximal band, indicating that elongation inhibition by isoginkgetin occurs after release from promoter-proximal pause. RNA-seq distinguished isoginkgetin and CDK9 inhibitors from topoisomerase I inhibition, which alters elongation across gene bodies. We were able to detect these and other specific defects in mRNA synthesis at low sequencing depth using simple metagene-based metrics. These metrics now enable total-RNA-seq-based screening for high-throughput identification of pharmacological effects on individual stages of mRNA synthesis.

GeneWalk identifies relevant gene functions for a biological context using network representation learning

“…As a final application of GeneWalk, we studied the transcriptional response to the biflavonoid isoginkgetin (IsoG), a plant natural product and putative anti-tumor compound whose mechanism of action remains unknown. IsoG inhibits pre-mRNA splicing in vitro and in vivo 35 and also causes widespread accumulation of PoI II at the 5' ends of genes, indicating an additional role as a Pol II elongation inhibitor 36 . Through DE analysis of NET-seq data obtained from HeLa S3 cells treated with IsoG ( Figure 4A), we identified a total of 2940 genes as differentially transcribed, most of which exhibited upregulated Pol II occupancy ( Figure 4B, FDR=0.001).…”

“…JQ1 and IsoG NET-seq experiments were previously described in 31,36 , respectively, and the data are available in GEO accession number GSE79290 and GSE86857. In brief, MOLT4 cells (two biological replicates per condition) were treated either with JQ1 (1 µM, 2h treatment) or DMSO (negative control).…”

“…), EMBO fellowship ALTF 2016-422 (R.I.), and DARPA grants W911NF-15-1-0544 and W911NF018-1-0124 (P.K.S.). We thank Karine Choquet and Heather Drexler for advice on the previously described mouse RNA-seq differential expression 23 analysis and IsoG NET-seq 36 . We thank Dylan Marshall and other members of the Churchman lab for discussions.…”

Enhancers predominantly regulate gene expression in vivo via transcription initiation

“…We generated polyA+ RNA-seq and scaRNA-seq data sets at 0 hour and 24 hour differentiation time points, representing "early" and "late" erythropoiesis (Edling and Hallberg 2007;Hay et al 2016;McGrath, Catherman, and Palis 2017), to allow for a robust comparison of changes in nascent gene expression and promoter proximal transcription. Nascent RNA was quantified by measuring intronic RNA ( Figure S3A, B and C) derived polyA+ RNA sequencing (Boswell et al 2017;La Manno et al 2018).…”

“…Here, using a newly developed genome-wide assay that measures short capped RNAs (scaRNAseq), we accurately and simultaneously identify TSSs and TPSs from single molecules at high resolution. By comparing scaRNA-seq data with measurements of nascent transcription using mNETseq (Nojima et al 2015) and intronic RNA (Boswell et al 2017;La Manno et al 2018), we find that enhancer-driven transcription, during in vivo differentiation of primary cells, appears to be controlled predominantly via initiation rather than pause-release or elongation. To test this experimentally we investigated the effect of the loss the major enhancers of the well-characterized globin loci on transcriptional initiation and pausing in primary erythroid cells.…”