Diurnal RNAPII-tethered chromatin interactions are associated with rhythmic gene expression in rice

Background The daily cycling of plant physiological processes is speculated to arise from the coordinated rhythms of gene expression. However, the dynamics of diurnal 3D genome architecture and their potential functions underlying the rhythmic gene expression remain unclear. Results Here, we reveal the genome-wide rhythmic occupancy of RNA polymerase II (RNAPII), which precedes mRNA accumulation by approximately 2 h. Rhythmic RNAPII binding dynamically correlates with RNAPII-mediated chromatin architecture remodeling at the genomic level of chromatin interactions, spatial clusters, and chromatin connectivity maps, which are associated with the circadian rhythm of gene expression. Rhythmically expressed genes within the same peak phases of expression are preferentially tethered by RNAPII for coordinated transcription. RNAPII-associated chromatin spatial clusters (CSCs) show high plasticity during the circadian cycle, and rhythmically expressed genes in the morning phase and non-rhythmically expressed genes in the evening phase tend to be enriched in RNAPII-associated CSCs to orchestrate expression. Core circadian clock genes are associated with RNAPII-mediated highly connected chromatin connectivity networks in the morning in contrast to the scattered, sporadic spatial chromatin connectivity in the evening; this indicates that they are transcribed within physical proximity to each other during the AM circadian window and are located in discrete “transcriptional factory” foci in the evening, linking chromatin architecture to coordinated transcription outputs. Conclusion Our findings uncover fundamental diurnal genome folding principles in plants and reveal a distinct higher-order chromosome organization that is crucial for coordinating diurnal dynamics of transcriptional regulation.

The hepatocyte insulin receptor is required to program rhythmic gene expression and the liver clock

SUMMARYIn mammalian cells, gene expression is rhythmic and sensitive to various environmental and physiological stimuli. A circadian clock system helps to anticipate and synchronize gene expression with daily stimuli including cyclic light and food intake, which control the central and peripheral clock programs, respectively. Food intake also regulates insulin secretion. How much insulin contributes to the effect of feeding on the entrainment of the clock and rhythmic gene expression remains to be investigated.An important component of insulin action is mediated by changes in insulin receptor (IR)-dependent gene expression. In the liver, insulin at high levels controls the transcription of hundreds of genes involved in glucose homeostasis to promote energy storage while repressing the expression of gluconeogenic genes. In type 2 diabetes mellitus (T2DM), selective hepatic insulin resistance impairs the inhibition of hepatic glucose production while promoting lipid synthesis. This pathogenic process promoting hyperlipidemia as well as non-alcoholic fatty liver diseases.While several lines of evidence link such metabolic diseases to defective control of circadian homeostasis, the hypothesis that IR directly synchronizes the clock has not been studied in vivo. Here, we used conditional hepatocyte-restricted gene deletion to evaluate the role of IR in the regulation and oscillation of gene expression as well as in the programming of the circadian clock in adult mouse liver.

Systematic analysis of differential rhythmic liver gene expression mediated by the circadian clock and feeding rhythms

The circadian clock and feeding rhythms are both important regulators of rhythmic gene expression in the liver. To further dissect the respective contributions of feeding and the clock, we analyzed differential rhythmicity of liver tissue samples across several conditions. We developed a statistical method tailored to compare rhythmic liver messenger RNA (mRNA) expression in mouse knockout models of multiple clock genes, as well as PARbZip output transcription factors (Hlf/Dbp/Tef). Mice were exposed to ad libitum or night-restricted feeding under regular light–dark cycles. During ad libitum feeding, genetic ablation of the core clock attenuated rhythmic-feeding patterns, which could be restored by the night-restricted feeding regimen. High-amplitude mRNA expression rhythms in wild-type livers were driven by the circadian clock, but rhythmic feeding also contributed to rhythmic gene expression, albeit with significantly lower amplitudes. We observed that Bmal1 and Cry1/2 knockouts differed in their residual rhythmic gene expression. Differences in mean expression levels between wild types and knockouts correlated with rhythmic gene expression in wild type. Surprisingly, in PARbZip knockout mice, the mean expression levels of PARbZip targets were more strongly impacted than their rhythms, potentially due to the rhythmic activity of the D-box–repressor NFIL3. Genes that lost rhythmicity in PARbZip knockouts were identified to be indirect targets. Our findings provide insights into the diurnal transcriptome in mouse liver as we identified the differential contributions of several core clock regulators. In addition, we gained more insights on the specific effects of the feeding–fasting cycle.

Isoform-specific regulation of rhythmic gene expression by alternative polyadenylation

Alternative polyadenylation (APA) generates transcript isoforms with different 3′ ends. Differences in polyadenylation sites usage, which have been associated with diseases like cancer, regulate mRNA stability, subcellular localization, and translation. By characterizing APA across the 24-hour day in mouse liver, here we show that rhythmic gene expression occurs largely in an APA isoform-specific manner, and that hundreds of arrhythmically expressed genes surprisingly exhibit a rhythmic APA isoform. The underlying mechanisms comprise isoform-specific post-transcriptional regulation, transcription factor driven expression of specific isoform, co-transcriptional recruitment of RNA binding proteins that regulate mRNA cleavage and polyadenylation, and, to a lesser extent, cell subtype-specific expression. Remarkably, rhythmic expression of specific APA isoforms generates 24-hour rhythms in 3′ UTR length, with shorter UTRs in anticipation of the mouse active phase. Taken together, our findings demonstrate that cycling transcriptomes are regulated by APA, and suggest that APA strongly impacts the rhythmic regulation of biological functions.

Genome-wide correlation analysis to identify amplitude regulators of circadian transcriptome output

Cell-autonomous circadian system, consisting of core clock genes, generates near 24-h rhythms and regulates the downstream rhythmic gene expression. While it has become clear that the percentage of rhythmic genes varies among mouse tissues, it remains unclear how this variation can be generated, particularly when the clock machinery is nearly identical in all tissues. In this study, we sought to characterize circadian transcriptome datasets that are publicly available and identify the critical component(s) involved in creating this variation. We found that the relative amplitude of 13 genes and the average level of 197 genes correlated with the percentage of cycling genes. Of those, the correlation of Rorc in both relative amplitude and the average level was one of the strongest. In addition, the level of Per2AS, a novel non-coding transcript that is expressed at the Period 2 locus, was also linearly correlated, although with a much lesser degree compared to Rorc. Overall, our study provides insight into how the variation in the percentage of clock-controlled genes can be generated in mouse tissues and suggests that Rorc and potentially Per2AS are involved in regulating the amplitude of circadian transcriptome output.

A clock in mouse cones contributes to the retinal oscillator network and to synchronization of the circadian system

Multiple circadian clocks dynamically regulate mammalian physiology. In retina, rhythmic gene expression serves to align vision and tissue homeostasis with daily light changes. Photic input is relayed to the suprachiasmatic nucleus to entrain the master clock, which matches behaviour to environmental changes. Circadian organization of the mouse retina involves coordinated, layer-specific oscillators, but so far little is known about the cone photoreceptor clock and its role in the circadian system. Using the cone-only Nrl-/- mouse model we show that cones contain a functional self-sustained molecular clockwork. By bioluminescence-combined imaging we also show that cones provide substantial input to the retinal clock network. Furthermore, we found that light entrainment and negative masking in cone-only mice are subtly altered and that constant light displayed profound effects on their central clock. Thus, our study demonstrates the contribution of cones to retinal circadian organisation and their role in finely tuning behaviour to environmental conditions.

Genome-wide correlation analysis reveals Rorc as potential amplitude regulator of circadian transcriptome output

Cell-autonomous circadian system, consisting of core clock genes, generates near 24-hour rhythms and regulates the downstream rhythmic gene expression. While it has become clear that the percentage of rhythmic genes varies among mouse tissues, it remains unclear how this variation can be generated, particularly when the clock machinery is nearly identical in all tissues. In this study, we sought to characterize circadian transcriptome datasets that are publicly available and identify the critical component(s) involved in creating this variation. We found that the relative amplitude of 13 genes and the average level of 197 genes correlated with the percentage of cycling genes. Of those, the correlation of Rorc in both relative amplitude and the average level was one of the strongest. In addition, the level of Per2AS, a novel non-coding transcript that is expressed at the Period 2 locus, was also linearly correlated, although with a much lesser degree compared to Rorc. Overall, our study provides insight into how the variation in the percentage of clock-controlled genes can be generated in mouse tissues and suggests that Rorc and potentially Per2AS are involved in regulating the amplitude of circadian transcriptome output.

Methods detecting rhythmic gene expression are biologically relevant only for strong signal

The nycthemeral transcriptome embodies all genes displaying a rhythmic variation of their mRNAs periodically every 24 hours, including but not restricted to circadian genes. In this study, we show that the nycthemeral rhythmicity at the gene expression level is biologically functional and that this functionality is more conserved between orthologous genes than between random genes. We used this conservation of the rhythmic expression to assess the ability of seven methods (ARSER, Lomb Scargle, RAIN, JTK, empirical-JTK, GeneCycle, and meta2d) to detect rhythmic signal in gene expression. We have contrasted them to a naive method, not based on rhythmic parameters. By taking into account the tissue-specificity of rhythmic gene expression and different species comparisons, we show that no method is strongly favored. The results show that these methods designed for rhythm detection, in addition to having quite similar performances, are consistent only among genes with a strong rhythm signal. Rhythmic genes defined with a standard p-value threshold of 0.01 for instance, could include genes whose rhythmicity is biologically irrelevant. Although these results were dependent on the datasets used and the evolutionary distance between the species compared, we call for caution about the results of studies reporting or using large sets of rhythmic genes. Furthermore, given the analysis of the behaviors of the methods on real and randomized data, we recommend using primarily ARS, empJTK, or GeneCycle, which verify expectations of a classical distribution of p-values. Experimental design should also take into account the circumstances under which the methods seem more efficient, such as giving priority to biological replicates over the number of time-points, or to the number of time-points over the quality of the technique (microarray vs RNAseq). GeneCycle, and to a lesser extent empirical-JTK, might be the most robust method when applied to weakly informative datasets. Finally, our analyzes suggest that rhythmic genes are mainly highly expressed genes.Author SummaryTo be active, genes have to be transcribed to RNA. For some genes, the transcription rate follows a circadian rhythm with a periodicity of approximately 24 hours; we call these genes “rhythmic”. In this study, we compared methods designed to detect rhythmic genes in gene expression data. The data are measures of the number of RNA molecules for each gene, given at several time-points, usually spaced 2 to 4 hours, over one or several periods of 24 hours. There are many such methods, but it is not known which ones work best to detect genes whose rhythmic expression is biologically functional. We compared these methods using a reference group of evolutionarily conserved rhythmic genes. We compared data from baboon, mouse, rat, zebrafish, fly, and mosquitoes. Surprisingly, no method was particularly effective. Furthermore, we found that only very strong rhythmic signals were relevant with each method. More precisely, when we use a usual cut-off to define rhythmic genes, the group of genes considered as rhythmic contains many genes whose rhythmicity cannot be confirmed to be biologically relevant. We also show that rhythmic genes mainly contain highly expressed genes. Finally, based on our results, we provide recommendations on which methods to use and how, and suggestions for future experimental designs.

Critical role of deadenylation in regulating poly(A) rhythms and circadian gene expression

The mammalian circadian clock is deeply rooted in rhythmic regulation of gene expression. Rhythmic transcriptional control mediated by the circadian transcription factors is thought to be the main driver of mammalian circadian gene expression. However, mounting evidence has demonstrated the importance of rhythmic post-transcriptional controls, and it remains unclear how the transcriptional and post-transcriptional mechanisms collectively control rhythmic gene expression. A recent study discovered rhythmicity in poly(A) tail length in mouse liver and its strong correlation with protein expression rhythms. To understand the role of rhythmic poly(A) regulation in circadian gene expression, we constructed a parsimonious model that depicts rhythmic control imposed upon basic mRNA expression and poly(A) regulation processes, including transcription, deadenylation, polyadenylation, and degradation. The model results reveal the rhythmicity in deadenylation as the strongest contributor to the rhythmicity in poly(A) tail length and the rhythmicity in the abundance of the mRNA subpopulation with long poly(A) tails (a rough proxy for mRNA translatability). In line with this finding, the model further shows that the experimentally observed distinct peak phases in the expression of deadenylases, regardless of other rhythmic controls, can robustly group the rhythmic mRNAs by their peak phases in poly(A) tail length and in abundance of the subpopulation with long poly(A) tails. This provides a potential mechanism to synchronize the phases of target gene expression regulated by the same deadenylases. Our findings highlight the critical role of rhythmic deadenylation in regulating poly(A) rhythms and circadian gene expression.Author SummaryThe biological circadian clock regulates various bodily functions such that they anticipate and respond to the day-and-night cycle. To achieve this, the circadian clock controls rhythmic gene expression, and these genes ultimately drive the rhythmicity of downstream biological processes. As a mechanism of driving circadian gene expression, rhythmic transcriptional control has attracted the central focus. However, mounting evidence has also demonstrated the importance of rhythmic post-transcriptional controls. Here we use mathematical modeling to investigate how transcriptional and post-transcriptional rhythms coordinately control rhythmic gene expression. We have particularly focused on rhythmic regulation of the length of poly(A) tail, a nearly universal feature of mRNAs that controls mRNA stability and translation. Our model reveals that the rhythmicity of deadenylation, the process that shortens the poly(A) tail, is the dominant contributor to the rhythmicity in poly(A) tail length and mRNA translatability. Particularly, the phase of deadenylation nearly overrides the other rhythmic processes in controlling the phases of poly(A) tail length and mRNA translatability. Our finding highlights the critical role of rhythmic deadenylation in circadian gene expression control.