Biotin-Genomic Run-On (Bio-GRO): A High-Resolution Method for the Analysis of Nascent Transcription in Yeast

High-Resolution Deep Sequencing of Nascent Transcription in Yeast with BioGRO-seq

RNA biogenesis in eukaryotic cells is a tightly regulated multilayered process in which a diverse set of players act in an orchestrated manner via complex molecular interactions to secure the initial flow of gene expression. Transcription from DNA to RNA is the essential first step in RNA biogenesis, and consists of three main phases: initiation, elongation, and termination. In each phase, transcription factors act on RNA polymerases to modulate their passage along the DNA template in a very precise manner, governed by molecular mechanisms, some of which are not yet fully understood. Genome-scale run-on-based methodologies have been developed with the aim of mapping the position of transcriptionally engaged RNA polymerases. Among them, the BioGRO methodology has been instrumental in advancing our understanding of the transcriptional dynamics in yeast. Here we take the previously known BioGRO method further by coupling it with deep sequencing. BioGRO-seq maps elongating RNA polymerases along the genome with strand specificity and single-nucleotide resolution. BioGRO-seq profiling provides insights into the biogenesis and regulation of not just the canonical protein-coding transcriptome, but also into the often more challenging to study noncoding and unstable transcriptome.

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

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.

Xrn1 influence on gene transcription results from the combination of general effects on elongating RNA pol II and gene-specific chromatin configuration

mRNA homoeostasis is favoured by crosstalk between transcription and degradation machineries. Both the Ccr4-Not and the Xrn1-decaysome complexes have been described to influence transcription. While Ccr4-Not has been shown to directly stimulate transcription elongation, the information available on how Xrn1 influences transcription is scarce and contradictory. In this study we have addressed this issue by mapping RNA polymerase II (RNA pol II) at high resolution, using CRAC and BioGRO-seq techniques in Saccharomyces cerevisiae. We found significant effects of Xrn1 perturbation on RNA pol II profiles across the genome. RNA pol II profiles at 5' exhibited significant alterations that were compatible with decreased elongation rates in the absence of Xrn1. Nucleosome mapping detected altered chromatin configuration in the gene bodies. We also detected accumulation of RNA pol II shortly upstream of polyadenylation sites by CRAC, although not by BioGRO-seq, suggesting higher frequency of backtracking before pre-mRNA cleavage. This phenomenon was particularly linked to genes with poorly positioned nucleosomes at this position. Accumulation of RNA pol II at 3' was also detected in other mRNA decay mutants. According to these and other pieces of evidence, Xrn1 seems to influence transcription elongation at least in two ways: by directly favouring elongation rates and by a more general mechanism that connects mRNA decay to late elongation.

The yeast exoribonuclease Xrn1 and associated factors modulate RNA polymerase II processivity in 5' and 3' gene regions

mRNA levels are determined by the balance between mRNA synthesis and decay. Protein factors that mediate both processes, including the 5'-3' exonuclease Xrn1, are responsible for a cross-talk between the two processes that buffers steady-state mRNA levels. However, the roles of these proteins in transcription remain elusive and controversial. Applying native elongating transcript sequencing (NET-seq) to yeast cells, we show that Xrn1 functions mainly as a transcriptional activator and that its disruption manifests as a reduction of RNA polymerase II (Pol II) occupancy downstream of transcription start sites. By combining our sequencing data and mathematical modeling of transcription, we found that Xrn1 modulates transcription initiation and elongation of its target genes. Furthermore, Pol II occupancy markedly increased near cleavage and polyadenylation sites in xrn1Δ cells, whereas its activity decreased, a characteristic feature of backtracked Pol II. We also provide indirect evidence that Xrn1 is involved in transcription termination downstream of polyadenylation sites. We noted that two additional decay factors, Dhh1 and Lsm1, seem to function similarly to Xrn1 in transcription, perhaps as a complex, and that the decay factors Ccr4 and Rpb4 also perturb transcription in other ways. Interestingly, the decay factors could differentiate between SAGA- and TFIID-dominated promoters. These two classes of genes responded differently to XRN1 deletion in mRNA synthesis and were differentially regulated by mRNA decay pathways, raising the possibility that one distinction between these two gene classes lies in the mechanisms that balance mRNA synthesis with mRNA decay.

Measuring RNA polymerase activity genome-wide with high-resolution run-on-based methods

The biogenesis of RNAs is a multi-layered and highly regulated process that involves a diverse set of players acting in an orchestrated manner throughout the transcription cycle. Transcription initiation, elongation and termination factors act on RNA polymerases to modulate their movement along the DNA template in a very precise manner, more complex than previously anticipated. Genome-scale run-on-based methodologies have been developed to study in detail the position of transcriptionally-engaged RNA polymerases. Genomic run-on (GRO), and its many variants and refinements made over the years, are helping the community to address an increasing amount of scientific questions, spanning an increasing range of organisms and systems. In this review, we aim to summarize the most relevant high throughput methodologies developed to study nascent RNA by run-on methods, compare their main features, advantages and limitations, while putting them in context with alternative ways of studying the transcriptional process.

Analysis of rRNA synthesis using quantitative transcription run-on (qTRO) in yeast

Comparative transcriptional analyses require appropriate and precise normalization. Here we describe a modified transcription run-on (TRO) method, named quantitative TRO (qTRO), that allows quantification of nascent transcription activity. The most critical improvement it introduces is a new standardization method for RNA isolation and hybridization steps, enabling transcription activity quantification and comparative biological analysis. We used this technique with chromatin immunoprecipitation to investigate RNA polymerase I (RNAPI) transcription activity and its rDNA gene profiles in Saccharomyces cerevisiae. We designed a set of new oligonucleotide probes complementary to nascent ribosomal RNA (rRNA) transcripts and standardized their hybridization strength. The qTRO method could be successfully implemented to study RNAPI transcription in response to oxidative stress and in two mutant strains with impaired rRNA synthesis.

Subtracting the sequence bias from partially digested MNase-seq data reveals a general contribution of TFIIS to nucleosome positioning

BACKGROUND

TFIIS stimulates RNA cleavage by RNA polymerase II and promotes the resolution of backtracking events. TFIIS acts in the chromatin context, but its contribution to the chromatin landscape has not yet been investigated. Co-transcriptional chromatin alterations include subtle changes in nucleosome positioning, like those expected to be elicited by TFIIS, which are elusive to detect. The most popular method to map nucleosomes involves intensive chromatin digestion by micrococcal nuclease (MNase). Maps based on these exhaustively digested samples miss any MNase-sensitive nucleosomes caused by transcription. In contrast, partial digestion approaches preserve such nucleosomes, but introduce noise due to MNase sequence preferences. A systematic way of correcting this bias for massively parallel sequencing experiments is still missing.

RESULTS

To investigate the contribution of TFIIS to the chromatin landscape, we developed a refined nucleosome-mapping method in Saccharomyces cerevisiae. Based on partial MNase digestion and a sequence-bias correction derived from naked DNA cleavage, the refined method efficiently mapped nucleosomes in promoter regions rich in MNase-sensitive structures. The naked DNA correction was also important for mapping gene body nucleosomes, particularly in those genes whose core promoters contain a canonical TATA element. With this improved method, we analyzed the global nucleosomal changes caused by lack of TFIIS. We detected a general increase in nucleosomal fuzziness and more restricted changes in nucleosome occupancy, which concentrated in some gene categories. The TATA-containing genes were preferentially associated with decreased occupancy in gene bodies, whereas the TATA-like genes did so with increased fuzziness. The detected chromatin alterations correlated with functional defects in nascent transcription, as revealed by genomic run-on experiments.

CONCLUSIONS

The combination of partial MNase digestion and naked DNA correction of the sequence bias is a precise nucleosomal mapping method that does not exclude MNase-sensitive nucleosomes. This method is useful for detecting subtle alterations in nucleosome positioning produced by lack of TFIIS. Their analysis revealed that TFIIS generally contributed to nucleosome positioning in both gene promoters and bodies. The independent effect of lack of TFIIS on nucleosome occupancy and fuzziness supports the existence of alternative chromatin dynamics during transcription elongation.

Topological organization and dynamic regulation of human tRNA genes during macrophage differentiation

Background

The human genome is hierarchically organized into local and long-range structures that help shape cell-type-specific transcription patterns. Transfer RNA (tRNA) genes (tDNAs), which are transcribed by RNA polymerase III (RNAPIII) and encode RNA molecules responsible for translation, are dispersed throughout the genome and, in many cases, linearly organized into genomic clusters with other tDNAs. Whether the location and three-dimensional organization of tDNAs contribute to the activity of these genes has remained difficult to address, due in part to unique challenges related to tRNA sequencing. We therefore devised integrated tDNA expression profiling, a method that combines RNAPIII mapping with biotin-capture of nascent tRNAs. We apply this method to the study of dynamic tRNA gene regulation during macrophage development and further integrate these data with high-resolution maps of 3D chromatin structure.

Results

Integrated tDNA expression profiling reveals domain-level and loop-based organization of tRNA gene transcription during cellular differentiation. tRNA genes connected by DNA loops, which are proximal to CTCF binding sites and expressed at elevated levels compared to non-loop tDNAs, change coordinately with tDNAs and protein-coding genes at distal ends of interactions mapped by in situ Hi-C. We find that downregulated tRNA genes are specifically marked by enhanced promoter-proximal binding of MAF1, a transcriptional repressor of RNAPIII activity, altogether revealing multiple levels of tDNA regulation during cellular differentiation.

Conclusions

We present evidence of both local and coordinated long-range regulation of human tDNA expression, suggesting the location and organization of tRNA genes contribute to dynamic tDNA activity during macrophage development.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-017-1310-3) contains supplementary material, which is available to authorized users.