Transient transcriptome sequencing captures enhancer landscapes immediately after T-cell stimulation

Transcription regulation is poorly understood. Transcriptional enhancers produce enhancer RNAs (eRNAs), a class of transient RNAs, whose function remains mainly unclear. To monitor transcriptional regulation in human cells, rapid changes in enhancer and promoter activity must be captured with high sensitivity and temporal reso- lution. Here I show that the recently established protocol TT-seq (‘transient tran- scriptome sequencing’) can monitor rapid changes in transcription from enhancers and promoters during the immediate response of T-cells to ionomycin and phorbol 12-myristate 13-acetate (PMA). Transient transcriptome sequencing (TT-seq) maps eRNAs and mRNAs every 5 minutes after T-cell stimulation with high sensitivity, and identifies many new primary response genes. TT-seq reveals that the synthesis of 1,601 eRNAs and 650 mRNAs changes significantly within only 15 minutes after stimulation, when standard RNA-seq does not detect differentially expressed genes. Transcription of enhancers that are primed for activation by nucleosome depletion can occur immediately and simultaneously with transcription of target gene promot- ers. My results indicate that enhancer transcription is a good proxy for enhancer regulatory activity in target gene activation, and establish TT-seq as a tool for monitoring the dynamics of enhancer landscapes and transcription programs during cellular responses and differentiation. Additionally, I developed a normalization method for TT-seq that scales labeled and total RNA-seq samples relative to each other, allowing to determine absolute half-lives. The method provides a powerful tool to normalize various samples relative to each other on a global scale, and therefore allows to observe global changes in RNA synthesis and degradation. Taken together, metabolical labeling of RNA followed by kinetic modeling enables to quantify RNA metabolism rates and to detect dynamic changes in enhancer landscapes and RNA expression levels

Transient transcriptome sequencing captures enhancer landscapes immediately after T-cell stimulation

Transcription regulation is poorly understood. Transcriptional enhancers produce enhancer RNAs (eRNAs), a class of transient RNAs, whose function remains mainly unclear. To monitor transcriptional regulation in human cells, rapid changes in enhancer and promoter activity must be captured with high sensitivity and temporal reso- lution. Here I show that the recently established protocol TT-seq (‘transient tran- scriptome sequencing’) can monitor rapid changes in transcription from enhancers and promoters during the immediate response of T-cells to ionomycin and phorbol 12-myristate 13-acetate (PMA). Transient transcriptome sequencing (TT-seq) maps eRNAs and mRNAs every 5 minutes after T-cell stimulation with high sensitivity, and identifies many new primary response genes. TT-seq reveals that the synthesis of 1,601 eRNAs and 650 mRNAs changes significantly within only 15 minutes after stimulation, when standard RNA-seq does not detect differentially expressed genes. Transcription of enhancers that are primed for activation by nucleosome depletion can occur immediately and simultaneously with transcription of target gene promot- ers. My results indicate that enhancer transcription is a good proxy for enhancer regulatory activity in target gene activation, and establish TT-seq as a tool for monitoring the dynamics of enhancer landscapes and transcription programs during cellular responses and differentiation. Additionally, I developed a normalization method for TT-seq that scales labeled and total RNA-seq samples relative to each other, allowing to determine absolute half-lives. The method provides a powerful tool to normalize various samples relative to each other on a global scale, and therefore allows to observe global changes in RNA synthesis and degradation. Taken together, metabolical labeling of RNA followed by kinetic modeling enables to quantify RNA metabolism rates and to detect dynamic changes in enhancer landscapes and RNA expression levels

Determinants of RNA metabolism in the Schizosaccharomyces pombe genome

To decrypt the regulatory code of the genome, sequence elements must be defined that determine the kinetics of RNA metabolism and thus gene expression. Here, we attempt such decryption in an eukaryotic model organism, the fission yeast S. pombe. We first derive an improved genome annotation that redefines borders of 36% of expressed mRNAs and adds 487 non-coding RNAs (ncRNAs). We then combine RNA labeling invivo with mathematical modeling to obtain rates of RNA synthesis and degradation for 5,484 expressed RNAs and splicing rates for4,958 introns. We identify functional sequence elements inDNA and RNA that control RNA metabolic rates and quantifythecontributions of individual nucleotides to RNA synthesis,splicing, and degradation. Our approach reveals distinct kineticsof mRNA and ncRNA metabolism, separates antisense regulation by transcription interference from RNA interference, and provides a general tool for studying the regulatory code of genomes

TT-seq maps the human transient transcriptome

Pervasive transcription of the genome produces both stable and transient RNAs. We developed transient transcriptome sequencing (TT-seq), a protocol that uniformly maps the entire range of RNA-producing units and estimates rates of RNA synthesis and degradation. Application of TT-seq to human K562 cells recovers stable messenger RNAs and long intergenic noncoding RNAs and additionally maps transient enhancer, antisense, and promoter-associated RNAs. TT-seq analysis shows that enhancer RNAs are short-lived and lack U1 motifs and secondary structure. TT-seq also maps transient RNA downstream of polyadenylation sites and uncovers sites of transcription termination; we found, on average, four transcription termination sites, distributed in a window with a median width of similar to 3300 base pairs. Termination sites coincide with a DNA motif associated with pausing of RNA polymerase before its release from the genome

Periodic mRNA synthesis and degradation co-operate during cell cycle gene expression

During the cell cycle, the levels of hundreds of mRNAs change in a periodic manner, but how this is achieved by alterations in the rates of mRNA synthesis and degradation has not been studied systematically. Here, we used metabolic RNA labeling and comparative dynamic transcriptome analysis (cDTA) to derive mRNA synthesis and degradation rates every 5 min during three cell cycle periods of the yeast Saccharomyces cerevisiae. A novel statistical model identified 479 genes that show periodic changes in mRNA synthesis and generally also periodic changes in their mRNA degradation rates. Peaks of mRNA degradation generally follow peaks of mRNA synthesis, resulting in sharp and high peaks of mRNA levels at defined times during the cell cycle. Whereas the timing of mRNA synthesis is set by upstream DNA motifs and their associated transcription factors (TFs), the synthesis rate of a periodically expressed gene is apparently set by its core promoter. Synopsis image Genome-scale measurement of changes in mRNA synthesis and degradation rates during the yeast cell cycle identifies genes with periodic synthesis and degradation and reveals a tight temporal coupling of both processes. The first high-resolution time series of mRNA synthesis and degradation rates during the cell cycle is presented. A novel statistical algorithm identifies periodically expressed genes and parameters of their temporal profile. The timing of periodic expression is set by upstream DNA motifs and the associated transcription factors, whereas the synthesis rate is set by the core promoter. Sharp and high peaks of mRNA levels are obtained by a temporal coupling of periodic mRNA synthesis and degradation maxima

Evidence for additive and synergistic action of mammalian enhancers during cell fate determination

Enhancer activity drives cell differentiation and cell fate determination, but it remains unclear how enhancers cooperate during these processes. Here we investigate enhancer cooperation during transdifferentiation of human leukemia B-cells to macrophages. Putative enhancers are established by binding of the pioneer factor C/EBPα followed by chromatin opening and enhancer RNA (eRNA) synthesis from H3K4-monomethylated regions. Using eRNA synthesis as a proxy for enhancer activity, we find that most putative enhancers cooperate in an additive way to regulate transcription of assigned target genes. However, transcription from 136 target genes depends exponentially on the summed activity of its putative paired enhancers, indicating that these enhancers cooperate synergistically. The target genes are cell type-specific, suggesting that enhancer synergy can contribute to cell fate determination. Enhancer synergy appears to depend on cell type-specific transcription factors, and such interacting enhancers are not predicted from occupancy or accessibility data that are used to detect superenhancers.Fuinding: Max-Planck-Gesellschaft (Open-access funding), Deutsche Forschungsgemeinschaft (SFB860), Deutsche Forschungsgemeinschaft (SPP1935), Deutsche Forschungsgemeinschaft (SPP2191), European Research Council (693023