Genomic Study of RNA Polymerase II and III SNAPc-Bound Promoters Reveals a Gene Transcribed by Both Enzymes and a Broad Use of Common Activators

SNAP(c) is one of a few basal transcription factors used by both RNA polymerase (pol) II and pol III. To define the set of active SNAP(c)-dependent promoters in human cells, we have localized genome-wide four SNAP(c) subunits, GTF2B (TFIIB), BRF2, pol II, and pol III. Among some seventy loci occupied by SNAP(c) and other factors, including pol II snRNA genes, pol III genes with type 3 promoters, and a few un-annotated loci, most are primarily occupied by either pol II and GTF2B, or pol III and BRF2. A notable exception is the RPPH1 gene, which is occupied by significant amounts of both polymerases. We show that the large majority of SNAP(c)-dependent promoters recruit POU2F1 and/or ZNF143 on their enhancer region, and a subset also recruits GABP, a factor newly implicated in SNAP(c)-dependent transcription. These activators associate with pol II and III promoters in G1 slightly before the polymerase, and ZNF143 is required for efficient transcription initiation complex assembly. The results characterize a set of genes with unique properties and establish that polymerase specificity is not absolute in vivo

Transcriptional regulatory logic of the diurnal cycle in the mouse liver.

Many organisms exhibit temporal rhythms in gene expression that propel diurnal cycles in physiology. In the liver of mammals, these rhythms are controlled by transcription-translation feedback loops of the core circadian clock and by feeding-fasting cycles. To better understand the regulatory interplay between the circadian clock and feeding rhythms, we mapped DNase I hypersensitive sites (DHSs) in the mouse liver during a diurnal cycle. The intensity of DNase I cleavages cycled at a substantial fraction of all DHSs, suggesting that DHSs harbor regulatory elements that control rhythmic transcription. Using chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq), we found that hypersensitivity cycled in phase with RNA polymerase II (Pol II) loading and H3K27ac histone marks. We then combined the DHSs with temporal Pol II profiles in wild-type (WT) and Bmal1-/- livers to computationally identify transcription factors through which the core clock and feeding-fasting cycles control diurnal rhythms in transcription. While a similar number of mRNAs accumulated rhythmically in Bmal1-/- compared to WT livers, the amplitudes in Bmal1-/- were generally lower. The residual rhythms in Bmal1-/- reflected transcriptional regulators mediating feeding-fasting responses as well as responses to rhythmic systemic signals. Finally, the analysis of DNase I cuts at nucleotide resolution showed dynamically changing footprints consistent with dynamic binding of CLOCK:BMAL1 complexes. Structural modeling suggested that these footprints are driven by a transient heterotetramer binding configuration at peak activity. Together, our temporal DNase I mappings allowed us to decipher the global regulation of diurnal transcription rhythms in the mouse liver

Quantifying ChIP-seq data:A spiking method providing an internal reference for sample-to-sample normalization

Chromatin immunoprecipitation followed by deep sequencing (ChIP-seq) experiments are widely used to determine, within entire genomes, the occupancy sites of any protein of interest, including, for example, transcription factors, RNA polymerases, or histones with or without various modifications. In addition to allowing the determination of occupancy sites within one cell type and under one condition, this method allows, in principle, the establishment and comparison of occupancy maps in various cell types, tissues, and conditions. Such comparisons require, however, that samples be normalized. Widely used normalization methods that include a quantile normalization step perform well when factor occupancy varies at a subset of sites, but may miss uniform genome-wide increases or decreases in site occupancy. We describe a spike adjustment procedure (SAP) that, unlike commonly used normalization methods intervening at the analysis stage, entails an experimental step prior to immunoprecipitation. A constant, low amount from a single batch of chromatin of a foreign genome is added to the experimental chromatin. This "spike" chromatin then serves as an internal control to which the experimental signals can be adjusted. We show that the method improves similarity between replicates and reveals biological differences including global and largely uniform changes

Defining the RNA polymerase III transcriptome: Genome-wide localization of the RNA polymerase III transcription machinery in human cells

Our view of the RNA polymerase III (Pol III) transcription machinery in mammalian cells arises mostly from studies of the RN5S (5S) gene, the Ad2 VAI gene, and the RNU6 (U6) gene, as paradigms for genes with type 1, 2, and 3 promoters. Recruitment of Pol III onto these genes requires prior binding of well-characterized transcription factors. Technical limitations in dealing with repeated genomic units, typically found at mammalian Pol III genes, have so far hampered genome-wide studies of the Pol III transcription machinery and transcriptome. We have localized, genome-wide, Pol III and some of its transcription factors. Our results reveal broad usage of the known Pol III transcription machinery and define a minimal Pol III transcriptome in dividing IMR90hTert fibroblasts. This transcriptome consists of some 500 actively transcribed genes including a few dozen candidate novel genes, of which we confirmed nine as Pol III transcription units by additional methods. It does not contain any of the microRNA genes previously described as transcribed by Pol III, but reveals two other microRNA genes, MIR886 (hsa-mir-886) and MIR1975 (RNY5, hY5, hsa-mir-1975), which are genuine Pol III transcription units

Genome-Wide Analysis of SREBP1 Activity around the Clock Reveals Its Combined Dependency on Nutrient and Circadian Signals

In mammals, the circadian clock allows them to anticipate and adapt physiology around the 24 hours. Conversely, metabolism and food consumption regulate the internal clock, pointing the existence of an intricate relationship between nutrient state and circadian homeostasis that is far from being understood. The Sterol Regulatory Element Binding Protein 1 (SREBP1) is a key regulator of lipid homeostasis. Hepatic SREBP1 function is influenced by the nutrient-response cycle, but also by the circadian machinery. To systematically understand how the interplay of circadian clock and nutrient-driven rhythm regulates SREBP1 activity, we evaluated the genome-wide binding of SREBP1 to its targets throughout the day in C57BL/6 mice. The recruitment of SREBP1 to the DNA showed a highly circadian behaviour, with a maximum during the fed status. However, the temporal expression of SREBP1 targets was not always synchronized with its binding pattern. In particular, different expression phases were observed for SREBP1 target genes depending on their function, suggesting the involvement of other transcription factors in their regulation. Binding sites for Hepatocyte Nuclear Factor 4 (HNF4) were specifically enriched in the close proximity of SREBP1 peaks of genes, whose expression was shifted by about 8 hours with respect to SREBP1 binding. Thus, the cross-talk between hepatic HNF4 and SREBP1 may underlie the expression timing of this subgroup of SREBP1 targets. Interestingly, the proper temporal expression profile of these genes was dramatically changed in Bmal1−/− mice upon time-restricted feeding, for which a rhythmic, but slightly delayed, binding of SREBP1 was maintained. Collectively, our results show that besides the nutrient-driven regulation of SREBP1 nuclear translocation, a second layer of modulation of SREBP1 transcriptional activity, strongly dependent from the circadian clock, exists. This system allows us to fine tune the expression timing of SREBP1 target genes, thus helping to temporally separate the different physiological processes in which these genes are involved

<i>RNU1</i>, <i>RNU2</i>, and <i>RNU6</i> transcription and factor recruitment during mitosis to G1 phase transition.

<p>(A) Time course of U1 and U6 reporter transcript and U2 and pre-U2 snRNA accumulation after mitosis release. The 5.8S RNA served as an internal control. The time after mitosis release is indicated above each panel. (B) Time course analysis of transcription factor recruitment on various promoter regions. ChIPs were performed at the times indicated (x axis) after mitosis release with antibodies directed against the factors indicated on top of each panel, and analyzed by real time PCR. The analyzed regions are indicated at the upper right of each panel. The control region (Ctrl) is 2 kb upstream of <i>RNU1</i>. The results are expressed relative to input DNA. Two sets of <i>RNU1</i> primers were used: set U1A recognizes <i>U1-1, U1-2, U1-3, U1-8, U1-like-3</i> loci and was used in the top panel; set U1B recognizes <i>U1-2</i> and <i>U1-3</i> loci and was used in the 3 lower panels. The <i>RNU2</i> primers are specific for the <i>RNU2</i> cluster in chr17_unknown, and the <i>RNU6</i> primers for the <i>U6-1</i> locus. (C) Real time PCR analysis of <i>RNU1</i> (top panel, U1A primer set for POLR2B, GTF2B, SNAPC1 and POLR3D ChIPs; and U1B primer set for the other ChIPs) and <i>RNU6</i> (bottom panel) promoters pulled down after ChIP with antibodies against the factors indicated below the panels either at mitosis (1 h after release) or in mid-G1 (7 h after release). The results are expressed relative to mitosis values, which were set at 1 for each factor. Means and error bars were calculated over triplicate PCR analyses. Each experiment was performed at least twice.</p

Depletion of endogenous ZNF143 reduces transcription factor recruitment on the U1 promoter in mid-G1.

<p>(A) Immunoblot showing ZNF143 and Tubulin (control) levels during mitosis and mid-G1 phase after treatment with siRNA against Luciferase (Luc, control siRNA) or ZNF143. (B) Real time PCR analysis of <i>RNU1</i> promoter pulled down after ChIP with antibodies against the factors indicated below the panel either after treatment of the cells with siRNA against Luciferase (siLuc, control siRNA) or siRNA against ZNF143 (siZNF143). The values obtained with the siZNF143 treatment are shown relative to those obtained with the siLuc treatment, which were set at 100%. Means and error bars were calculated over triplicate PCR analyses. Each experiment was performed at least twice. The U1A primer set was used for the POLR2B, GTF2B and SNAPC1 ChIPs, the U1B primer set for the other ChIPs.</p

SNAP_c subunits occupancy and proximal promoter motifs.

<p>(A) UCSC browser views of a pol III (<i>tRNAU1</i>) and a pol II (<i>RNU4atac</i>) gene showing occupancy by the factors indicated on the left. The chromosome coordinates are shown on top, the genes present in the region and their orientation at bottom. The y axis shows tag counts. (B) Two examples of non-annotated genomic regions showing occupancy by SNAP_c subunits, GTF2B, and POLR2B. (C) Box plot of BRF2, GTF2B, and SNAP_c subunit positions. For each gene, the position of the peak summit for each SNAP_c subunit relative to the TSS (set at 0) was determined. A median position (black bars in boxes, number in brackets on the y axis) was calculated. For the pol II genes, only the upper two tertiles of each SNAP_c subunit and GTF2B scores were included. The position for each gene is represented by a circle. (D) LOGOs of PSE and TATA box generated by WebLogo with the motifs identified with MEME (alignments in Figures S4 and S5). The top panel shows the PSE LOGO for pol II snRNA genes, the middle panel shows the PSE LOGO for pol III genes, and the bottom panel shows the TATA box LOGO for pol III genes.</p

Activator occupancy and distal promoter motifs.

<p>(A) UCSC browser view of three pol II (<i>RNU4atac</i>, <i>U1-like-5</i>, and <i>Unknown-6</i>) and one pol III (<i>tRNAU1</i>) gene showing occupancy by the factors indicated on the right of each panel. The chromosome coordinates are shown on top, the genes present in the region and their orientation at bottom. The y axis shows tag counts. (B) Promoter region (−400 to +1) of the four genes depicted in (A) with the positions of the GABPA (GA-motif), ZNF143 (SBS), and POU2F1 (octamer) binding sites found by MEME or MAST indicated. The positions of the PSE and TATA box are also shown, and the promoters were aligned according to the PSE position. The crossed-out motifs have either no corresponding peak of occupancy or are not the closest to the peak summit. The orientation of each motif is indicated with an arrow. (C) LOGOs of the ZNF143, POU2F1 (octamer) and GABP binding motifs generated by WebLogo with the motifs located closest to the corresponding factor peak summits (see alignments in Figures S9, S10, S11).</p

Pol II and III occupancy of snRNA genes.

<p>(A) Bar graph showing POLR2B (dark blue), GTF2B (light blue), POLR3D (red), and BRF2 (orange) ChIP-seq scores (y axis) on SNAP_c-occupied genes and the few snRNA genes devoid of SNAP_c (x axis). Genes are ordered by decreasing POLR2B scores for the pol II and <i>RPPH1</i> genes followed by increasing POLR3D scores for the pol III genes. (B) UCSC browser view of <i>RPPH1</i> gene showing POLR2B, POLR3D, GTF2B, and BRF2 occupancy. Y axis: tag counts. (C) POLR2B (light grey) or POLR3D (dark grey) occupancy in cells not treated or treated with 50 µg/ml α-amanitin for 2 or 6 h, as indicated on the x axis. Upper two panels: results are shown as % of input. Lower two panels: POLR2B and POLR3D occupancy without α-amanitin was set at 1.</p