Abstract:Understanding the complex network that regulates transcription elongation requires the quantitative analysis of RNA polymerase II (Pol II) activity in a wide variety of regulatory environments. We performed native elongating transcript sequencing (NET-seq) in 41 strains of S. cerevisiae lacking known elongation regulators, including RNA processing factors, transcription elongation factors, chromatin modifiers, and remodelers. We found that the opposing effects of these factors balance transcription elongation … Show more
“…29 Steady-state RNA-seq data and RNAPII profiling through NET-seq showed that paf1Δ cells exhibit widespread transcriptional misregulation of coding genes and upregulation of antisense transcripts, particularly for Set2 Repressible Antisense Transcripts (SRATs). [30][31][32] This is consistent with the loss of Set2-dependent H3 K36me3 in paf1∆, and also ctr9∆, mutants. 11,[30][31][32] While it is apparent that Paf1C broadly impacts gene expression and chromatin states, technological limitations have confounded interpretations of its functions.…”
Section: Introductionsupporting
confidence: 83%
“…[30][31][32] This is consistent with the loss of Set2-dependent H3 K36me3 in paf1∆, and also ctr9∆, mutants. 11,[30][31][32] While it is apparent that Paf1C broadly impacts gene expression and chromatin states, technological limitations have confounded interpretations of its functions. Many previous studies have relied on stable null alleles, which allow cumulative effects to accrue.…”
Section: Introductionsupporting
confidence: 83%
“…30–32 This is consistent with the loss of Set2-dependent H3 K36me3 in paf1Δ , and also ctr9Δ , mutants. 11,30–32…”
Section: Introductionsupporting
confidence: 81%
“…29 Steady-state RNA-seq data and RNAPII profiling through NET-seq showed that paf1Δ cells exhibit widespread transcriptional misregulation of coding genes and upregulation of antisense transcripts, particularly for Set2 Repressible Antisense Transcripts (SRATs). 30–32 This is consistent with the loss of Set2-dependent H3 K36me3 in paf1Δ , and also ctr9Δ , mutants. 11,30–32…”
Paf1C is a highly conserved protein complex with critical functions during eukaryotic transcription. Previous studies have shown that Paf1C is multi-functional, controlling specific aspects of transcription, ranging from RNAPII processivity to histone modifications. However, it is unclear how specific Paf1C subunits directly impact transcription and coupled processes. We have compared conditional depletion to steady-state deletion for each Paf1C subunit to determine the direct and indirect contributions to gene expression in Saccharomyces cerevisiae. Using nascent transcript sequencing, RNAPII profiling, and modeling of transcription elongation dynamics, we have demonstrated direct effects of Paf1C subunits on RNAPII processivity and elongation rate and indirect effects on transcript splicing and repression of antisense transcripts. Further, our results suggest that the direct transcriptional effects of Paf1C cannot be readily assigned to any particular histone modification. This work comprehensively analyzes both the immediate and extended roles of each Paf1C subunit in transcription elongation and transcript regulation.
“…29 Steady-state RNA-seq data and RNAPII profiling through NET-seq showed that paf1Δ cells exhibit widespread transcriptional misregulation of coding genes and upregulation of antisense transcripts, particularly for Set2 Repressible Antisense Transcripts (SRATs). [30][31][32] This is consistent with the loss of Set2-dependent H3 K36me3 in paf1∆, and also ctr9∆, mutants. 11,[30][31][32] While it is apparent that Paf1C broadly impacts gene expression and chromatin states, technological limitations have confounded interpretations of its functions.…”
Section: Introductionsupporting
confidence: 83%
“…[30][31][32] This is consistent with the loss of Set2-dependent H3 K36me3 in paf1∆, and also ctr9∆, mutants. 11,[30][31][32] While it is apparent that Paf1C broadly impacts gene expression and chromatin states, technological limitations have confounded interpretations of its functions. Many previous studies have relied on stable null alleles, which allow cumulative effects to accrue.…”
Section: Introductionsupporting
confidence: 83%
“…30–32 This is consistent with the loss of Set2-dependent H3 K36me3 in paf1Δ , and also ctr9Δ , mutants. 11,30–32…”
Section: Introductionsupporting
confidence: 81%
“…29 Steady-state RNA-seq data and RNAPII profiling through NET-seq showed that paf1Δ cells exhibit widespread transcriptional misregulation of coding genes and upregulation of antisense transcripts, particularly for Set2 Repressible Antisense Transcripts (SRATs). 30–32 This is consistent with the loss of Set2-dependent H3 K36me3 in paf1Δ , and also ctr9Δ , mutants. 11,30–32…”
Paf1C is a highly conserved protein complex with critical functions during eukaryotic transcription. Previous studies have shown that Paf1C is multi-functional, controlling specific aspects of transcription, ranging from RNAPII processivity to histone modifications. However, it is unclear how specific Paf1C subunits directly impact transcription and coupled processes. We have compared conditional depletion to steady-state deletion for each Paf1C subunit to determine the direct and indirect contributions to gene expression in Saccharomyces cerevisiae. Using nascent transcript sequencing, RNAPII profiling, and modeling of transcription elongation dynamics, we have demonstrated direct effects of Paf1C subunits on RNAPII processivity and elongation rate and indirect effects on transcript splicing and repression of antisense transcripts. Further, our results suggest that the direct transcriptional effects of Paf1C cannot be readily assigned to any particular histone modification. This work comprehensively analyzes both the immediate and extended roles of each Paf1C subunit in transcription elongation and transcript regulation.
“…Finally, in at least some cases, it is clear that elongation rates are not only indirectly influenced by structural features of DNA, RNA, or chromatin, but are actively regulated in response to various cellular stimuli, with dysregulation of elongation rates potentially contributing to disease progression [14].Other studies have focused specifically on pausing of Pol II. Aside from the pronounced pausing that occurs proximal to the promoter, many, typically more subtle, pause sites occur within gene bodies, and, in the aggregate, these sites have a major effect on the dynamics of transcription elongation [16][17][18][19] (see also [20] for a recent study in yeast). These gene-body pause sites replicate well across experiments but vary substantially in their density across genes; they also occur in divergent antisense transcripts and enhancer RNAs as well as in gene bodies [18].…”
Across all branches of life, transcription elongation is a crucial, regulated phase in gene expression. Many recent studies in eukaryotes have focused on the regulation of promoter-proximal pausing of RNA Polymerase II (Pol II), but rates of productive elongation also vary substantially throughout the gene body, both within and across genes. Here, we introduce a probabilistic model for systematically evaluating potential determinants of the local elongation rate based on nascent RNA sequencing (NRS) data. Our model is derived from a unified model for both the kinetics of Pol II movement along the DNA template and the generation of NRS read counts at steady state. It allows for a continuously variable elongation rate along the gene body, with the rate at each nucleotide defined by a generalized linear relationship with nearby genomic and epigenomic features. High-dimensional feature vectors are accommodated through a sparse-regression extension. We show with simulations that the model allows accurate detection of associated features and accurate prediction of local elongation rates. In an analysis of public PRO-seq and epigenomic data, we identify several features that are strongly associated with reductions in the local elongation rate, including DNA methylation, splice sites, RNA stem-loops, CTCF binding sites, and several histone marks, including H3K36me3 and H4K20me1. By contrast, low-complexity sequences and H3K79me2 marks are associated with increases in elongation rate. In an analysis of DNAk-mers, we find that cytosine nucleotides are strongly associated with reductions in local elongation rate, particularly when preceded by guanines and followed by adenines or thymines. Increases in elongation rate are associated with thymines and A+T-richk-mers. These associations are generally shared across cell types, and by considering them our model is effective at predicting features of held-out PRO-seq data. Overall, our analysis is the first to permit genome-wide predictions of relative nucleotide-specific elongation rates based on complex sets of genomic and epigenomic covariates. We have made predictions available for the K562, CD14+, MCF-7, and HeLa-S3 cell types in a UCSC Genome Browser track.
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