Dawn- and dusk-phased circadian transcription rhythms coordinate anabolic and catabolic functions in Neurospora

Background: Circadian clocks control rhythmic expression of a large number of genes in coordination with the 24 hour day-night cycle. The mechanisms generating circadian rhythms, their amplitude and circadian phase are dependent on a transcriptional network of immense complexity. Moreover, the contribution of post-transcriptional mechanisms in generating rhythms in RNA abundance is not known. Results: Here, we analyzed the clock-controlled transcriptome of Neurospora crassa together with temporal profiles of elongating RNA polymerase II. Our data indicate that transcription contributes to the rhythmic expression of the vast majority of clock-controlled genes (ccgs) in Neurospora. The ccgs accumulate in two main clusters with peak transcription and expression levels either at dawn or dusk. Dawn-phased genes are predominantly involved in catabolic and dusk-phased genes in anabolic processes, indicating a clock-controlled temporal separation of the physiology of Neurospora. Genes whose expression is strongly dependent on the core circadian activator WCC fall mainly into the dawn-phased cluster while rhythmic genes regulated by the glucose-dependent repressor CSP1 fall predominantly into the dusk-phased cluster. Surprisingly, the number of rhythmic transcripts increases about twofold in the absence of CSP1, indicating that rhythmic expression of many genes is attenuated by the activity of CSP1. Conclusions: The data indicate that the vast majority of transcript rhythms in Neurospora are generated by dawn and dusk specific transcription. Our observations suggest a substantial plasticity of the circadian transcriptome with respect to the number of rhythmic genes as well as amplitude and phase of the expression rhythms and emphasize a major role of the circadian clock in the temporal organization of metabolism and physiology

Combinatorial Control of Light Induced Chromatin Remodeling and Gene Activation in Neurospora

Light is an important environmental cue that affects physiology and development of Neurospora crassa. The light-sensing transcription factor (TF) WCC, which consists of the GATAfamily TFs WC1 and WC2, is required for light-dependent transcription. SUB1, another GATA-family TF, is not a photoreceptor but has also been implicated in light-inducible gene expression. To assess regulation and organization of the network of light-inducible genes, we analyzed the roles of WCC and SUB1 in light-induced transcription and nucleosome remodeling. We show that SUB1 co-regulates a fraction of light-inducible genes together with the WCC. WCC induces nucleosome eviction at its binding sites. Chromatin remodeling is facilitated by SUB1 but SUB1 cannot activate light-inducible genes in the absence of WCC. We identified FF7, a TF with a putative O-acetyl transferase domain, as an interaction partner of SUB1 and show their cooperation in regulation of a fraction of light-inducible and a much larger number of non light-inducible genes. Our data suggest that WCC acts as a general switch for light-induced chromatin remodeling and gene expression. SUB1 and FF7 synergistically determine the extent of light-induction of target genes in common with WCC but have in addition a role in transcription regulation beyond light-induced gene expression

Transcription Factors in Light and Circadian Clock Signaling Networks Revealed by Genomewide Mapping of Direct Targets for Neurospora White Collar Complex

Light signaling pathways and circadian clocks are inextricably linked and have profound effects on behavior in most organisms. Here, we used chromatin immunoprecipitation (ChIP) sequencing to uncover direct targets of the Neurospora crassa circadian regulator White Collar Complex (WCC). The WCC is a blue-light receptor and the key transcription factor of the circadian oscillator. It controls a transcriptional network that regulates ∼20% of all genes, generating daily rhythms and responses to light. We found that in response to light, WCC binds to hundreds of genomic regions, including the promoters of previously identified clock- and light-regulated genes. We show that WCC directly controls the expression of 24 transcription factor genes, including the clock-controlled adv-1 gene, which controls a circadian output pathway required for daily rhythms in development. Our findings provide links between the key circadian activator and effectors in downstream regulatory pathways

Combinatorial Control of Light Induced Chromatin Remodeling and Gene Activation in <i>Neurospora</i>

<div><p>Light is an important environmental cue that affects physiology and development of <i>Neurospora crassa</i>. The light-sensing transcription factor (TF) WCC, which consists of the GATA-family TFs WC1 and WC2, is required for light-dependent transcription. SUB1, another GATA-family TF, is not a photoreceptor but has also been implicated in light-inducible gene expression. To assess regulation and organization of the network of light-inducible genes, we analyzed the roles of WCC and SUB1 in light-induced transcription and nucleosome remodeling. We show that SUB1 co-regulates a fraction of light-inducible genes together with the WCC. WCC induces nucleosome eviction at its binding sites. Chromatin remodeling is facilitated by SUB1 but SUB1 cannot activate light-inducible genes in the absence of WCC. We identified FF7, a TF with a putative O-acetyl transferase domain, as an interaction partner of SUB1 and show their cooperation in regulation of a fraction of light-inducible and a much larger number of non light-inducible genes. Our data suggest that WCC acts as a general switch for light-induced chromatin remodeling and gene expression. SUB1 and FF7 synergistically determine the extent of light-induction of target genes in common with WCC but have in addition a role in transcription regulation beyond light-induced gene expression.</p></div

Light- and WCC-dependent nucleosome eviction is transcription independent.

<p><b>A</b>. Line graphs showing the averaged nucleosome occupancy in transcribed genes and promoters of all annotated <i>Neurospora</i> genes (n = 9733) in <i>wt</i>, Δ<i>sub1</i> and Δ<i>wc2</i> strains in dark (red) and 20 min (blue) after light-exposure of cultures. The center of the +1 nucleosome (nucleosome overlapping the annotated transcription start site) was used for alignment of sequence coverage of MNase-resistant fragments >100bp. <b>B</b>. Wig file showing the nucleosome position and occupancy at the <i>rds1</i> promoter in <i>wt</i>, Δ<i>sub1</i> and Δ<i>wc2</i> strains in the dark and after light-exposure. MNase-WC2 ChIP-seq (blue) is shown below the nucleosome signals. Numbers on the ChIP-seq panels show the maximum read coverage shown in the wig file. <b>C</b>. ChIP-PCR analysis showing H2A occupancy in the dark and 20 min after light exposure at the binding sites of WCC and SUB1 in the <i>rds1</i> promoter. ChIP was performed by immunoprecipitation with H2A antibody (± SEM, n = 4). a<i>ctin</i> gene was used for normalization. <i>wt</i> dark level was set to 1. <b>D</b>. Transcription-independent light-induced nucleosome eviction at WCC binding sites (BS). Four examples (wig files) of nucleosome position and occupancy at WCC BS in <i>wt</i>, Δ<i>sub1</i> and Δ<i>wc2</i> strains are shown. WCC binding (TAP-WC2 ChIP-seq) is shown above the nucleosome signals. The positions of GATC motifs are shown in the lower panels. Numbers on the ChIP-seq panels indicate the maximum nucleosome coverage shown in the Wig file. Regions used for ChIP-PCR analysis are indicated by black lines. <b>E</b>. ChIP-PCR analysis showing H2A occupancy in the regions shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005105#pgen.1005105.g004" target="_blank">Fig. 4D</a>. Occupancy of H2A was determined by immunoprecipitation with H2A antibody (± SEM, n = 4). a<i>ctin</i> gene was used for normalization. w<i>t</i> dark level was set to 1.</p

FF7 interacts weakly with SUB1 and co-regulates light-inducible and non light-inducible genes.

<p><b>A-B</b>. Western blots showing co-immunoprecipitation (co-IP) of <b>(A)</b> SUB1 with FF7_FLAG-HIS and <b>(B)</b> FF7_FLAG-HIS with SUB1. FLAG antibody was used for FF7_FLAG-HIS IP and α-SUB1 antibody was used for SUB1 IP. The asterisks (*) indicate cross-reactions of the FLAG antibody. <b>C</b>. FF7 binding motifs identified by MEME. The top 200 binding sites identified by FF7 ChIP-seq were used for the motif analysis. The upper motif is found in 117 / 200 binding sites whereas the lower motif is found in 36 / 200 binding sites. <b>D</b>. Occurrence of the major FF7 motif at FF7 binding sites. The grey area shows the occupancy of FF7 binding sites determined by ChIP-seq. The red line shows the occurrence of the FF7 binding motif “t/c AAGCG c/a”. <b>E</b>. Wig file showing MNase-WC2, SUB1 and FF7 ChIP-seq signals at the <i>rds1</i> promoter. Numbers on the ChIP-seq panels correspond the maximum coverage shown in the wig file. <b>F</b>. Venn-diagram showing the overlap between SUB1, WC2 and FF7 ChIP-seq signals. <b>G</b>. Heat-map showing light-inducible genes with significantly lower RNA levels in Δ<i>sub1</i> and in Δ<i>ff7</i> strains in comparison to <i>wt</i>. <b>H</b>. Wig file (left panel) showing the nucleosome position and occupancy at the <i>rds1</i> promoter in <i>wt</i> and Δ<i>ff7</i> strains in the dark and after light-exposure. The MNase-WC2 ChIP-seq (blue) is shown below the nucleosome signals. Numbers on the ChIP-seq panels show the maximum coverage shown in the wig file. ChIP-PCR analysis (right panel) of H2A occupancy at the binding sites of WCC and SUB1 at <i>rds1</i> promoter in the dark and 20 min after light-exposure (± SEM, n = 4). a<i>ctin</i> DNA was used for normalization. w<i>t</i> dark level was set to 1. <b>I</b>. Nucleosome occupancy at binding sites of WCC (n = 92) and in Δ<i>ff7</i> in dark (dotted lines) and 20 min after light-exposure (solid lines).</p

Cistrome analysis of WCC and SUB1.

<p><b>A</b>. Heat-map showing the light-induced WCC occupancy at 92 binding sites identified by both, MNase-WC2 ChIP-seq and TAP-WC2 ChIP-seq. 5 kb region covering the binding sites are shown. Left panel: WCC binding in the dark. Right panel: WCC binding 30 min after light-exposure. <b>B</b>. Occurrence of tandem GATC motifs with the indicated spacing at WCC binding sites. 300 bp DNA regions covering the peaks of 92 highly confident WCC binding sites were analyzed. The dashed line corresponds to the occurrence of tandem GATC motifs in a set of randomly chosen 300 bp regions. <b>C</b>. Potential light response elements (LREs) at WCC binding sites contain multiple GATC motifs. GATC motifs in WCC binding sites of the indicated genes are shown. <i>frq</i>_<i>as</i>: <i>frq</i> antisense [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005105#pgen.1005105.ref019" target="_blank">19</a>]. <i>vvd</i>_<i>prox</i> and <i>vvd</i>_<i>dis</i>: proximal and distal WCC binding sites in <i>vvd</i> promoter (<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005105#pgen.1005105.s008" target="_blank">S2 Table</a>). <b>D</b>. Distribution of tandem GATC motifs with < 30 bp spacing at WCC binding sites. The grey area represents the sequence coverage of the WCC ChIP (MNase-WC2 ChIP, 30 min) at the highly confident 92 WCC binding sites. The red line shows the occurrence of tandem GATC motifs. <b>E</b>. Heat-map showing the SUB1 occupancy at binding sites. Left panel: SUB1 binding in the dark. Right panel: SUB1 binding 30 min after light-exposure. <b>F</b>. SUB1 binding motifs identified by MEME are shown. The major sequence motif shown in the upper panel is found in 171 sites. The GTA-rich motifs shown in the lower left and right panels are present in 82 and 63 sites, respectively. <b>G</b>. Distribution of the major SUB1 binding motif (a/cGAT-x6-a/cTGc/t) at SUB1 binding sites. The grey area represents the sequence coverage of the SUB1 ChIP (SUB1 30 min) at 617 SUB1 binding sites. The red line shows the occurrence of the SUB1 binding motif.</p

Light promotes WCC dependent nucleosome eviction at WCC binding sites.

<p><b>A</b>. Nucleosome occupancy at binding sites of WCC (n = 92) and in <i>wt</i> (red), Δ<i>sub1</i> (green) and Δ<i>wc2</i> (blue) strains in dark (dotted lines) and 20 min after light-exposure (solid lines). <b>B</b>. Nucleosome occupancy at binding sites of WCC for SUB1-dependent (upper panel) and SUB1-independent (lower panel) light induced nucleosome loss. <i>wt</i> (red) and Δ<i>sub1</i> (green) strains in dark (dotted lines) and 20 min after light-exposure (solid lines) are shown. <b>C</b>. Nucleosome occupancy at binding sites of SUB1 (n = 617) in <i>wt</i> (red), Δ<i>sub1</i> (green) and Δ<i>wc2</i> (blue) strains in dark (dotted lines) and 20 min after light-exposure (solid lines).</p

A Combined Computational and Genetic Approach Uncovers Network Interactions of the Cyanobacterial Circadian Clock

UnlabelledTwo-component systems (TCS) that employ histidine kinases (HK) and response regulators (RR) are critical mediators of cellular signaling in bacteria. In the model cyanobacterium Synechococcus elongatus PCC 7942, TCSs control global rhythms of transcription that reflect an integration of time information from the circadian clock with a variety of cellular and environmental inputs. The HK CikA and the SasA/RpaA TCS transduce time information from the circadian oscillator to modulate downstream cellular processes. Despite immense progress in understanding of the circadian clock itself, many of the connections between the clock and other cellular signaling systems have remained enigmatic. To narrow the search for additional TCS components that connect to the clock, we utilized direct-coupling analysis (DCA), a statistical analysis of covariant residues among related amino acid sequences, to infer coevolution of new and known clock TCS components. DCA revealed a high degree of interaction specificity between SasA and CikA with RpaA, as expected, but also with the phosphate-responsive response regulator SphR. Coevolutionary analysis also predicted strong specificity between RpaA and a previously undescribed kinase, HK0480 (herein CikB). A knockout of the gene for CikB (cikB) in a sasA cikA null background eliminated the RpaA phosphorylation and RpaA-controlled transcription that is otherwise present in that background and suppressed cell elongation, supporting the notion that CikB is an interactor with RpaA and the clock network. This study demonstrates the power of DCA to identify subnetworks and key interactions in signaling pathways and of combinatorial mutagenesis to explore the phenotypic consequences. Such a combined strategy is broadly applicable to other prokaryotic systems.ImportanceSignaling networks are complex and extensive, comprising multiple integrated pathways that respond to cellular and environmental cues. A TCS interaction model, based on DCA, independently confirmed known interactions and revealed a core set of subnetworks within the larger HK-RR set. We validated high-scoring candidate proteins via combinatorial genetics, demonstrating that DCA can be utilized to reduce the search space of complex protein networks and to infer undiscovered specific interactions for signaling proteins in vivo Significantly, new interactions that link circadian response to cell division and fitness in a light/dark cycle were uncovered. The combined analysis also uncovered a more basic core clock, illustrating the synergy and applicability of a combined computational and genetic approach for investigating prokaryotic signaling networks

A Combined Computational and Genetic Approach Uncovers Network Interactions of the Cyanobacterial Circadian Clock

Two-component systems (TCS) that employ histidine kinases (HK) and response regulators (RR) are critical mediators of cellular signaling in bacteria. In the model cyanobacterium Synechococcus elongatus PCC 7942, TCSs control global rhythms of transcription that reflect an integration of time information from the circadian clock with a variety of cellular and environmental inputs. The HK CikA and the SasA/RpaA TCS transduce time information from the circadian oscillator to modulate downstream cellular processes. Despite immense progress in understanding of the circadian clock itself, many of the connections between the clock and other cellular signaling systems have remained enigmatic. To narrow the search for additional TCS components that connect to the clock, we utilized direct-coupling analysis (DCA), a statistical analysis of covariant residues among related amino acid sequences, to infer coevolution of new and known clock TCS components. DCA revealed a high degree of interaction specificity between SasA and CikA with RpaA, as expected, but also with the phosphate-responsive response regulator SphR. Coevolutionary analysis also predicted strong specificity between RpaA and a previously undescribed kinase, HK0480 (herein CikB). A knockout of the gene for CikB (cikB) in a sasA cikA null background eliminated the RpaA phosphorylation and RpaA-controlled transcription that is otherwise present in that background and suppressed cell elongation, supporting the notion that CikB is an interactor with RpaA and the clock network. This study demonstrates the power of DCA to identify subnetworks and key interactions in signaling pathways and of combinatorial mutagenesis to explore the phenotypic consequences. Such a combined strategy is broadly applicable to other prokaryotic systems. IMPORTANCE Signaling networks are complex and extensive, comprising multiple integrated pathways that respond to cellular and environmental cues. A TCS interaction model, based on DCA, independently confirmed known interactions and revealed a core set of subnetworks within the larger HK-RR set. We validated high-scoring candidate proteins via combinatorial genetics, demonstrating that DCA can be utilized to reduce the search space of complex protein networks and to infer undiscovered specific interactions for signaling proteins in vivo. Significantly, new interactions that link circadian response to cell division and fitness in a light/dark cycle were uncovered. The combined analysis also uncovered a more basic core clock, illustrating the synergy and applicability of a combined computational and genetic approach for investigating prokaryotic signaling networks