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

CRY associated proteins modulate circadian transcription by regulating CRY stability

Circadian clocks have evolved in all light sensitive organisms from cyanobacteria to mammals. These timing systems allow the organism to adjust their physiology and behavior to the geo-physical time. In mammals the circadian clocks exist in virtually all body cells, but the system function in a hierarchical manner in which the master pacemaker in the suprachiasmatic nucleus (SCN) sets the pace of the subsidiary peripheral oscillators. SCN is a small, approximately 10 000-20 000 cells, neuroendocrine gland in the hypothalamus. The SCN receives a direct photic input from the retina through the retino-hypothalamic tract and transmits this information to the oscillators in the periphery using neuronal and humoral signals. The molecular clock both in the SCN and in the peripheral oscillators is thought to consist of negative transcriptional and translational feedback loops. The PAS domain basic helix-loop-helix transcription factors BMAL1 and CLOCK bind to the promoters and transactivate two cryptochrome (cry) and two period (per) genes. Once CRY and PER proteins reach the threshold concentration they translocate into the nucleus and inhibit the activity of BMAL1-CLOCK heterodimer and repress their own genes. In addition, Bmal1 is rhythmically activated and repressed by orphan nuclear receptors RORs and REV-ERB? respectively in the interconnecting loop. Post-translational modifications such as phosphorylation, acetylation, sumoylation, and ubiquitination play an important role in fine-tuning the oscillator to measure 24 hour periodicity. The regulation of CRY protein stability and accumulation is particularly important for functional circadian oscillator. CRYs are ubiquitinated by the SCF-FBXL3 ubiquitin E3-ligase in timely regulated manner and subsequently degraded by the proteasome

CAVIN-3 regulates circadian period length and PER:CRY protein abundance and interactions.

In mammals, transcriptional autorepression by Period (PER) and Cryptochrome (CRY) protein complexes is essential for the generation of circadian rhythms. We have identified CAVIN-3 as a new, cytoplasmic PER2-interacting protein influencing circadian clock properties. Thus, CAVIN-3 loss- and gain-of-function shortened and lengthened, respectively, the circadian period in fibroblasts and affected PER:CRY protein abundance and interaction. While depletion of protein kinase Cδ (PKCδ), a known partner of CAVIN-3, had little effect on circadian gene expression, CAVIN-3 required the PKCδ-binding site to exert its effect on period length. This suggests the involvement of yet uncharacterized protein kinases. Finally, CAVIN-3 activity in circadian gene expression was independent of caveolae

BMAL1 footprints indicate temporally changing protein–DNA complexes, consistent with binding of a heterotetramer to DNA.

<p>A. Genomic profiles of DNase I cuts around double E-boxes with a spacer of 6 bp (E1-E2 sp6). We selected <i>n</i> = 249 E1-E2 sp6 motifs overlapping a BMAL1 chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) peak and show the average of profiles for loci classified as bound by the mixture model (posterior probability >0.5). At ZT6, we observed that nucleotides around both E-boxes are protected. In contrast, at ZT18, the width of the protected region is reduced by approximately half, with the second E-box no longer protected from digestion. The signals are anchored to the motif position. Orientation of sites and signals is according to the best match to the E1-E2 sp6 motif. In <i>Bmal1</i>^<i>-/-</i>, only one E-box appears occupied. B. Width (left-side <i>y</i>-axis, green) of the protected region in WT and in <i>Bmal1</i>^<i>-/-</i> mice for E1-E2 sp6 motifs occupied by BMAL1. Fraction of predicted occupied sites is shown in blue (right-side <i>y</i>-axis). C. Two views of the 3-D computational model of the CLOCK:BMAL1 heterotetramer showing two heterodimers of CLOCK:BMAL1 occupying an E1-E2 sp6 site. The two heterodimers are shown in green and blue, while darker green and darker blue correspond to BMAL1 and lighter colors to CLOCK proteins. Information content along the DNA strands is shown in grey with highly constrained nucleotides of the motif in red. D. Zoom on the interacting residuals on the PAS-B domain of CLOCK implicated in the heterotetramer formation.</p

Distal DNase I Hypersensitive Sites (DHSs) help identify diurnally active transcription regulators.

<p>A. Scheme of the linear model to infer active transcription regulators: transcription factor (TF) motifs in DHSs within a symmetric window around active transcription start sites (TSSs) are used to explain diurnal rhythms in transcription. B. Fraction of explained temporal variance (deviance ratio) in RNA polymerase II (Pol II) loading (at the TSS of all actives genes) for WT and <i>Bmal1</i>^-/- mice, in function of the window size (radius) for DHS inclusion, shows a maximum at around 50 kb. Here, <i>α</i> = 0 was used in the glmnet (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001069#sec015" target="_blank">Materials and methods</a>). C–D. Inferred TF motif activities for WT and in <i>Bmal1</i>^-/- mice shown with amplitudes (distance from center) and peak times (clockwise, ZT0 at the top) using a window size of 50 kb. All 819 (WT) and 629 (<i>Bmal1</i>^-/-) motifs (overlap is 427) with nonzero activities are shown. Note though that most activities are very small and cluster in the center. Certain families of TFs are indicated in colors (full results are provided in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001069#pbio.2001069.s018" target="_blank">S4 Table</a>). Radial scale for activities is arbitrary but comparable in C and D. E. Quantification of western blots for pCREB (Ser 133 phosphorylation) and CREB in WT and <i>Bmal1</i>^<i>-</i>/- genotypes (log₂ (pCREB/CREB)). Nuclear extracts from four independent livers were harvested every 2 h. Both genotypes showed a significant oscillation (<i>p</i> < 0.05, harmonic regression) of the mean signal from the four mice. Though the peak time in <i>Bmal1</i>^-/- mice is delayed by 1.8 h, the comparison of the rhythm in the two genotypes was not significant (<i>p</i> = 0.49, Chow test). Individual blots are shown in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001069#pbio.2001069.s007" target="_blank">S7 Fig</a>.</p

Chromatin accessibility in <i>Bmal1</i>^-/- mice at ZT6 is generally similar as in the Wild-Type (WT) mice but is lower at BMAL1 sites.

<p>A. The <i>Rev-erbα</i> (left) and <i>Gsk3a</i> (right) promoters. DNase I signal (in red) is strongly reduced in <i>Bmal1</i>^-/- mice at sites bound by CLOCK:BMAL1 in WT mice (BMAL1 chromatin immunoprecipitation followed by DNA sequencing (ChIP-seq) signal in blue) in the <i>Rev-erbα</i> promoter but is similar in WT and <i>Bmal1</i>^-/- mice at the <i>Gsk3a</i> promoter that are not bound by BMAL1. The vertical scale is the same for all three DNase I tracks, as well as for both BMAL1 ChiP-seq tracks. Wild-type ZT18 signals are lower (about half) than at ZT6 in both genes but not as low as in the <i>Bmal1</i>^-/- mice. B. Comparison of DNase I signals at ZT6 in <i>Bmal1</i>^-<b>/-</b> versus WT mice. All DNase I hypersensitive sites (DHSs) overlapping BMAL1 ChIP-seq peaks in [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001069#pbio.2001069.ref017" target="_blank">17</a>] are shown (<i>n</i> = 1,555). The dashed lines indicate 4-fold difference. C. Boxplots showing DNase I intensity at the same sites as in B, at peak (ZT6) and trough (ZT18) activities of BMAL1 in the WT, and at ZT6 in <i>Bmal1</i>^-/- mice for all BMAL1-binding sites (green), BMAL1 sites with an associated expression phase between ZT2 and ZT10 (orange), and with a tandem E-box (grey). All pairwise comparisons (within the same color) between either ZT6 versus ZT18 or ZT6 versus ZT6 <i>Bmal1</i>^-/- are significant (<i>p</i> < 0.001). D–E. Same as B–C but using overlap with USF1 ChIP-seq peaks [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.2001069#pbio.2001069.ref074" target="_blank">74</a>] to select DHSs (<i>n</i> = 1,705).</p

A multiplicity of factors contributes to selective RNA polymerase III occupancy of a subset of RNA polymerase III genes in mouse liver

The genomic loci occupied by RNA polymerase (RNAP) III have been characterized in human culture cells by genome-wide chromatin immunoprecipitations, followed by deep sequencing (ChIP-seq). These studies have shown that only ∼40% of the annotated 622 human tRNA genes and pseudogenes are occupied by RNAP-III, and that these genes are often in open chromatin regions rich in active RNAP-II transcription units. We have used ChIP-seq to characterize RNAP-III-occupied loci in a differentiated tissue, the mouse liver. Our studies define the mouse liver RNAP-III-occupied loci including a conserved mammalian interspersed repeat (MIR) as a potential regulator of an RNAP-III subunit-encoding gene. They reveal that synteny relationships can be established between a number of human and mouse RNAP-III genes, and that the expression levels of these genes are significantly linked. They establish that variations within the A and B promoter boxes, as well as the strength of the terminator sequence, can strongly affect RNAP-III occupancy of tRNA genes. They reveal correlations with various genomic features that explain the observed variation of 81% of tRNA scores. In mouse liver, loci represented in the NCBI37/mm9 genome assembly that are clearly occupied by RNAP-III comprise 50 Rn5s (5S RNA) genes, 14 known non-tRNA RNAP-III genes, nine Rn4.5s (4.5S RNA) genes, and 29 SINEs. Moreover, out of the 433 annotated tRNA genes, half are occupied by RNAP-III. Transfer RNA gene expression levels reflect both an underlying genomic organization conserved in dividing human culture cells and resting mouse liver cells, and the particular promoter and terminator strengths of individual genes