SLAMseq
Cohesin-dependent and independent mechanisms support chromosomal contacts between promoters and enhancers
Michiel J. Thiecke, Gordana Wutz, Matthias Muhar, Wen Tang, Stephen Bevan, Valeriya Malysheva, Roman Stocsits, Tobias Neumann, Johannes Zuber, Peter Fraser, Stefan Schoenfelder, Jan-Michael Peters, Mikhail Spivakov
It is currently assumed that 3D chromosomal organisation plays a central role in transcriptional control. However, recent evidence shows that steady-state transcription of only a minority of genes is affected by depletion of architectural proteins such as cohesin and CTCF. Here, we have used Capture Hi-C to interrogate the dynamics of chromosomal contacts of all human gene promoters upon rapid architectural protein degradation. We show that promoter contacts lost in these conditions tend to be long-range, with at least one interaction partner localising in the vicinity of topologically associated domain (TAD) boundaries. In contrast, many shorter-range chromosomal contacts, particularly those that connect active promoters with each other and with active enhancers remain unaffected by cohesin and CTCF depletion. We demonstrate that the effects of cohesin depletion on nascent transcription can be explained by changes in the connectivity of their enhancers. Jointly, these results provide a mechanistic explanation to the limited, but consistent effects of cohesin and CTCF on steady-state transcription and point towards the existence of alternative enhancer-promoter pairing mechanisms that are independent of these proteins.
Features SLAMseq Metabolic RNA Labeling Kit for RNA-Seq and QuantSeq 3’ mRNA-Seq Library Prep Kit FWD for Illumina
Rapid and scalable profiling of nascent RNA with fastGRO
Elisa Barbieri, Connor Hill, Mathieu Quesnel-Vallieres, Yoseph Barash, Alessandro Gardini
Genome-wide profiling of nascent RNA has become a fundamental tool to study transcription regulation. Over the past decade, next-generation sequencing has fostered development of a handful of techniques (i.e. GRO-seq, PRO-seq, TT-seq and NET-seq) that map unprocessed transcripts originating from both the coding and the noncoding portion of the genome. Unlike steady-state RNA sequencing, nascent RNA profiling mirrors the real-time activity of RNA Polymerases and provides an accurate readout of transcriptome-wide variations that occur during short time frames (i.e. response to external stimuli or rapid metabolic changes). Some species of nuclear RNAs, albeit functional, have a short half-life and can only be accurately gauged by nascent RNA techniques (i.e. lincRNAs and eRNAs). Furthermore, these techniques capture uncapped post-cleavage RNA at termination sites or promoter-associated antisense RNAs, providing a unique insight into RNAPII dynamics and processivity.
Here we present a run-on assay with 4s-UTP labelling, followed by reversible biotinylation and affinity purification via streptavidin. Our protocol allows streamlined sample preparation within less than 3 days. We named the technique fastGRO (fast Global Run-On). We show that fastGRO is highly reproducible and yields a more complete and extensive coverage of nascent RNA than comparable techniques. Importantly, we demonstrate that fastGRO is scalable and can be performed with as few as 0.5×10^6 cells.
Features SLAMseq Metabolic RNA Labeling Kit for RNA-Seq and SENSE mRNA-Seq Library Prep Kit
WDR5 is a conserved regulator of protein synthesis gene expression
Audra F Bryan, Jing Wang, Gregory C Howard, Alissa D Guarnaccia, Chase M Woodley, Erin R Aho, Eric J Rellinger, Brittany K Matlock, David K Flaherty, Shelly L Lorey, Dai H Chung, Stephen W Fesik, Qi Liu, April M Weissmiller, William P Tansey
WDR5 is a highly-conserved nuclear protein that performs multiple scaffolding functions in the context of chromatin. WDR5 is also a promising target for pharmacological inhibition in cancer, with small molecule inhibitors of an arginine-binding pocket of WDR5 (the ‘WIN’ site) showing efficacy against a range of cancer cell lines in vitro. Efforts to understand WDR5, or establish the mechanism of action of WIN site inhibitors, however, are stymied by its many functions in the nucleus, and a lack of knowledge of the conserved gene networks—if any—that are under its control. Here, we have performed comparative genomic analyses to identify the conserved sites of WDR5 binding to chromatin, and the conserved genes regulated by WDR5, across a diverse panel of cancer cell lines. We show that a specific cohort of protein synthesis genes (PSGs) are invariantly bound by WDR5, demonstrate that the WIN site anchors WDR5 to chromatin at these sites, and establish that PSGs are bona fide, acute, and persistent targets of WIN site blockade. Together, these data reveal that WDR5 plays a predominant transcriptional role in biomass accumulation and provide further evidence that WIN site inhibitors act to repress gene networks linked to protein synthesis homeostasis.
Determining mRNA Stability by Metabolic RNA Labeling and Chemical Nucleoside Conversion
Veronika A. Herzog, Nina Fasching, Stefan L. Ameres
The varying rates at which mRNAs decay are tightly coordinated with transcriptional changes to shape gene expression during development and disease. But currently available RNA sequencing approaches lack the temporal information to determine the relative contribution of RNA biogenesis, processing and turnover to the establishment of steady-state gene expression profiles.
Here, we describe a protocol that combines metabolic RNA labeling with chemical nucleoside conversion by thiol-linked alkylation of 4-thiouridine to determine RNA stability in cultured cells (SLAMseq). When coupled to cost-effective mRNA 3′ end sequencing approaches, SLAMseq determines the half-life of polyadenylated transcripts in a global and transcript-specific manner using untargeted or targeted cDNA library preparation protocols.
We provide a step-by-step instruction for time-resolved mRNA 3′ end sequencing, which augments traditional RNA-seq approaches to acquire the temporal resolution necessary to study the molecular principles that control gene expression.
Features SLAMseq Metabolic RNA Labeling Kit for RNA-Seq, QuantSeq 3’ mRNA-Seq Library Prep Kit FWD for Illumina and QuantSeq-Flex Targeted RNA-Seq Library Prep Kit V2 for Illumina
Mapping Vector Field of Single Cells
Xiaojie Qiu, Yan Zhang, Dian Yang, Shayan Hosseinzadeh, Li Wang, Ruoshi Yuan, Song Xu, Yian Ma, Joseph Replogle, Spyros Darmanis, Jianhua Xing, Jonathan S Weissman
Understanding how gene expression in single cells progress over time is vital for revealing the mechanisms governing cell fate transitions. RNA velocity, which infers immediate changes in gene expression by comparing levels of new (unspliced) versus mature (spliced) transcripts (La Manno et al. 2018), represents an important advance to these efforts. A key question remaining is whether it is possible to predict the most probable cell state backward or forward over arbitrary time-scales. To this end, we introduce an inclusive model (termed Dynamo) capable of predicting cell states over extended time periods, that incorporates promoter state switching, transcription, splicing, translation and RNA/protein degradation by taking advantage of scRNA-seq and the co-assay of transcriptome and proteome. We also implement scSLAM-seq by extending SLAM-seq to plate-based scRNA-seq (Hendriks et al. 2018; Erhard et al. 2019; Cao, Zhou, et al. 2019) and augment the model by explicitly incorporating the metabolic labelling of nascent RNA. We show that through careful design of labelling experiments and an efficient mathematical framework, the entire kinetic behavior of a cell from this model can be robustly and accurately inferred. Aided by the improved framework, we show that it is possible to reconstruct the transcriptomic vector field from sparse and noisy vector samples generated by single cell experiments. The reconstructed vector field further enables global mapping of potential landscapes that reflects the relative stability of a given cell state, and the minimal transition time and most probable paths between any cell states in the state space. This work thus foreshadows the possibility of predicting long-term trajectories of cells during a dynamic process instead of short time velocity estimates. Our methods are implemented as an open source tool, dynamo (https://github.com/aristoteleo/dynamo-release).
Sequencing cell-type-specific transcriptomes with SLAM-ITseq
Wayo Matsushima, Veronika A. Herzog, Tobias Neumann, Katharina Gapp, Johannes Zuber, Stefan L. Ameres & Eric A. Miska
Analysis of cell-type-specific transcriptomes is vital for understanding the biology of tissues and organs in the context of multicellular organisms. In this Protocol Extension, we combine a previously developed cell-type-specific metabolic RNA labeling method (thiouracil (TU) tagging) and a pipeline to detect the labeled transcripts by a novel RNA sequencing (RNA-seq) method, SLAMseq (thiol (SH)-linked alkylation for the metabolic sequencing of RNA). By injecting a uracil analog, 4-thiouracil, into transgenic mice that express cell-type-specific uracil phosphoribosyltransferase (UPRT), an enzyme required for 4-thiouracil incorporation into newly synthesized RNA, only cells expressing UPRT synthesize thiol-containing RNA. Total RNA isolated from a tissue of interest is then sequenced with SLAMseq, which introduces thymine to cytosine (T>C) conversions at the sites of the incorporated 4-thiouracil. The resulting sequencing reads are then mapped with the T>C-aware alignment software, SLAM-DUNK, which allows mapping of reads containing T>C mismatches. The number of T>C conversions per transcript is further analyzed to identify which transcripts are synthesized in the UPRT-expressing cells. Thus, our method, SLAM-ITseq (SLAMseq in tissue), enables cell-specific transcriptomics without laborious FACS-based cell sorting or biochemical isolation of the labeled transcripts used in TU tagging. In the murine tissues we assessed previously, this method identified ~5,000 genes that are expressed in a cell type of interest from the total RNA pool from the tissue. Any laboratory with access to a high-throughput sequencer and high-power computing can adapt this protocol with ease, and the entire pipeline can be completed in <5 d.
Adventitious Virus Detection in Cells by High-Throughput Sequencing of Newly Synthesized RNAs: Unambiguous Differentiation of Cell Infection from Carryover of Viral Nucleic Acids
Justine Cheval, Erika Muth, Gaëlle Gonzalez, Muriel Coulpier, Pascale Beurdeley, Stéphane Cruveiller, Marc Eloit
The use of high-throughput sequencing (HTS) to identify viruses in biologicals differs from current molecular approaches, since its use enables an unbiased approach to detection without the need to design specific primers to preamplify target sequences. Its broad range of detection and analytical sensitivity make it an important tool to ensure that biologicals are free from adventitious viruses. Similar to other molecular methods, however, identification of viral sequences in cells by HTS does not prove viral infection, since this could reflect carryover of inert viral sequences from reagents or other sources or the presence of transcriptionally inactive cellular sequences. Due to the broad range of detection associated with HTS, the above can potentially be perceived as a drawback for the testing of pharmaceutical biological products using this method. In order to avoid the identification of inert viral sequences, we present a methodology based on metabolic RNA labeling and sequencing, which enables the specific identification of newly synthesized viral RNAs in infected cells, resulting in the ability to unambiguously distinguish active infection by DNA or RNA viruses from inert nucleic acids. In the present study, we report the ability to differentiate Vero cells acutely infected by a single-stranded positive-sense RNA virus (tick-borne encephalitis virus) from cells which have been in contact with nonreplicating virus particles. Additionally, we also found a laboratory contamination by the squirrel monkey retrovirus of our Vero cell line, which was derived from an Old World (African green) monkey, a type of contamination which until now has been identified only in cells derived from primates from the New World.
SLAM-ITseq: Sequencing cell type-specific transcriptomes without cell sorting
Wayo Matsushima, Veronika A Herzog, Tobias Neumann, Katharina Gapp, Johannes Zuber, Stefan L Ameres, Eric A Miska
Features SLAMseq Metabolic RNA Labeling Kit for RNA-Seq and QuantSeq 3’ mRNA-Seq Library Prep Kit FWD for Illumina
SLAM-seq defines direct gene-regulatory functions of the BRD4-MYC axis
Matthias Muhar, Anja Ebert, Tobias Neumann, Christian Umkehrer, Julian Jude, Corinna Wieshofer, Philipp Rescheneder, Jesse J. Lipp, Veronika A. Herzog, Brian Reichholf, David A. Cisneros, Thomas Hoffmann, Moritz F. Schlapansky, Pooja Bhat, Arndt von Haeseler, Thomas Köcher, Anna C. Obenauf, Johannes Popow, Stefan L. Ameres, Johannes Zuber
Features SLAMseq Metabolic RNA Labeling Kit for RNA-Seq and QuantSeq 3’ mRNA-Seq Library Prep Kit FWD for Illumina
RNA dynamics revealed by metabolic RNA labeling and biochemical nucleoside conversions
Marisa A P Baptista & Lars Dölken
Thiol-linked alkylation of RNA to assess expression dynamics
Veronika A Herzog, Brian Reichholf, Tobias Neumann, Philipp Rescheneder, Pooja Bhat, Thomas R Burkard, Wiebke Wlotzka, Arndt von Haeseler, Johannes Zuber & Stefan L Ameres
Features QuantSeq 3’ mRNA-Seq Library Prep Kit for Illumina and SLAMseq Metabolic RNA Labeling Kit for RNA-Seq