A rapid, sensitive, scalable method for Precision Run-On sequencing (PRO-seq)

Abstract

24Tracking active transcription with the nuclear run-on (NRO) assays has been instrumental in 25 uncovering mechanisms of gene regulation. The coupling of NROs with high-throughput 26 sequencing has facilitated the discovery of previously unannotated or undetectable RNA classes 27 genome-wide. Precision run-on sequencing (PRO-seq) is a run-on variant that maps polymerase 28 active sites with nucleotide or near-nucleotide resolution. One main drawback to this and many 29 other nascent RNA detection methods is the somewhat intimidating multi-day workflow 30 associated with creating the libraries suitable for high-throughput sequencing. Here, we present 31an improved PRO-seq protocol where many of the enzymatic steps are carried out while the 32 biotinylated NRO RNA remains bound to streptavidin-coated magnetic beads. These 33 adaptations reduce time, sample loss and RNA degradation, and we demonstrate that the 34 resulting libraries are of the same quality as libraries generated using the original published 35protocol. The assay is also more sensitive which permits reproducible, high-quality libraries from 36 10 4 -10 5 cells instead of 10 6 -10 7 . Altogether, the improved protocol is more tractable allows for 37 nascent RNA profiling from small samples, such as rare samples or FACS sorted cell 38populations. 39 40

From telomere to telomere: the transcriptional and epigenetic state of human repeat elements

“…AluSx3-WaluSat across four chromosomes (3,13,21,18). MEI (13,22), these data can be used to assess how repetitive elements influence genome structure and function.…”

“…Building upon this resource, we assessed RNA polymerase occupancy using precision run-on sequencing (PRO-seq) (20,21) and CpG methylated sites using Oxford Nanopore long read data (22), both at single-nucleotide resolution, to derive the first transcriptional and epigenetic annotation for major TE classes across a human genome. This comprehensive approach supported phylogenetic and statistical modelling that exposed differential evolutionary patterns for specific repeat types (retroelements, satellites, macrosatellites, composite elements) that are found genome-wide from those found only in specific chromosomal regions, such as centromeres and telomeres.…”

“…Our results indicate a high number of transductions in the human genome with an average of 1.24 events per 1Mbp. Chromosomes 7, 2, 17, 4, and 11 are the most enriched targets with 67, 56, 43, 40, and 39 transduced loci, respectively, whereasChromosomes 19,21,12,8,and 18 have the lowest number of events, with19, 18, 17, 15, …”

Deconvolution of Expression for Nascent RNA Sequencing Data (DENR) Highlights Pre-RNA Isoform Diversity in Human Cells

“…Released nuclei were then centrifuged at 4°C for 5 min at 1000xg, washed with 1 ml of a 1:1 ratio solution of wash buffer and 2X lysis buffer and re-suspended in 50 μl of storage buffer (50mM Tris-CL pH 8.3, 40% glycerol, 5mM MgCl 2 , 0.1 mM EDTA, 2.5 μM DTT, 1X protease inhibitor cocktail) supplemented with 0.2U of SUPERase In RNase Inhibitor. PRO-seq run-on and library preparation was completed following a recently updated protocol (47). Briefly, nuclei were run-on by incubating at 37°C for 5 min in run-on buffer (10 mM Tris-Cl pH 8.0, 5 mM MgCl 2 , 1 mM DTT, 300 mM KCl, 40 μM Biotin-11-CTP, 40 μM Biotin-11-UTP, 40 μM Biotin-11-ATP, 40 μM Biotin-11-GTP, 1% (w/v) Sarkosyl in DEPC H 2 O).…”

Fast-acting chemical tools to delineate causality in transcriptional control

“…Showcasing advances in multi-omics analyses, mathematical intersection of polymerase activity (TT-seq), and occupancy data (mNET-seq) allows inference of gene-specific changes in pause duration and productive initiation frequencies in response to heat shock (Gressel et al, 2019). Streamlined nascent RNA-seq protocols may soon allow recording of nascent transcription trajectories at minute-scale resolution during a perturbation time course (Judd et al, 2020). Statistical analyses could then be used to infer causality in gene-regulatory network rewiring by correlating the emergence of gene signatures over time.…”