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Regulation of chromatin states involves the dynamic interplay between different histone modifications to control gene expression. Recent advances have enabled mapping of histone marks in single cells, but most methods are constrained to profile only one histone mark per cell. Here, we present an integrated experimental and computational framework, scChIX-seq (single-cell chromatin immunocleavage and unmixing sequencing), to map several histone marks in single cells. scChIX-seq multiplexes two histone marks together in single cells, then computationally deconvolves the signal using training data from respective histone mark profiles. This framework learns the cell-type-specific correlation structure between histone marks, and therefore does not require a priori assumptions of their genomic distributions. Using scChIX-seq, we demonstrate multimodal analysis of histone marks in single cells across a range of mark combinations. Modeling dynamics of in vitro macrophage differentiation enables integrated analysis of chromatin velocity. Overall, scChIX-seq unlocks systematic interrogation of the interplay between histone modifications in single cells.

Recent advances have enabled mapping of histone modifications in single cells1–12, but current methods are constrained to profile only one histone modification per cell. Here we present an integrated experimental and computational framework, scChIX (single-cell chromatin immunocleavage and unmixing), to map multiple histone modifications in single cells. scChIX multiplexes two histone modification profiles together in single cells, then computationally deconvolves the signal using training data from respective histone modification profiles. We first validate this method using purified blood cells and show that although the two repressive marks, H3K27me3 and H3K9me3, are generally mutually exclusive, the transitions between the two regions can vary between cell types. Next we apply scChIX to a heterogenous cell population from mouse bone marrow to generate linked maps of active (H3K4me1) and repressive (H3K27me3) chromatin landscapes in single cells, where coordinates in the active modification map correspond to coordinates in the repressive map. Linked analysis reveals that immunoglobulin genes in the Igkv region are in a repressed chromatin state in pro-B cells, but become activated in B cells. Overall, scChIX unlocks systematic interrogation of the interplay between histone modifications in single cells.

SUMMARYPost-translational histone modifications modulate chromatin packing to regulate gene expression. How chromatin states, at euchromatic and heterochromatic regions, underlie cell fate decisions in single cells is relatively unexplored. We develop sort assisted single-cell chromatin immunocleavage (sortChIC) and map active (H3K4me1 and H3K4me3) and repressive (H3K27me3 and H3K9me3) histone modifications in hematopoietic stem and progenitor cells (HSPCs), and mature blood cells in the mouse bone marrow. During differentiation, HSPCs acquire distinct active chromatin states that depend on the specific cell fate, mediated by cell type-specifying transcription factors. By contrast, most regions that gain or lose repressive marks during differentiation do so independent of cell fate. Joint profiling of H3K4me1 and H3K9me3 demonstrates that cell types within the myeloid lineage have distinct active chromatin but share similar myeloid-specific heterochromatin-repressed states. This suggests hierarchical chromatin regulation during hematopoiesis: heterochromatin dynamics define differentiation trajectories and lineages, while euchromatin dynamics establish cell types within lineages.

The circadian clock is an endogenous and self-sustained oscillator that anticipates daily environmental cycles and coordinates physiology accordingly. While rhythmic gene expression of circadian genes is well-described in populations of cells, the single-cell mRNA dynamics of multiple core-clock genes remain largely unknown. Here we use single molecule fluorescence in-situ hybridization (smFISH) at multiple time points to measure pairs of core-clock transcripts, Rev-erbα (Nr1d1), Cry1 and Bmal1, in mouse fibroblasts at single-molecule resolution. The mean mRNA level oscillates over 24 hours for all three genes, but mRNA numbers show considerable spread between cells. While transcript number scales with cell size for all genes, gene-to-gene correlations of mRNA number depends on the gene pair. To account for these features of the data, we develop a probabilistic model for multivariate smFISH mRNA counts that quantifies changes in transcriptional bursting across genes and over circadian time. We identify a mixture model of negative binomials as the preferred model of the mRNA count distributions, which accounts for cell-to-cell heterogeneity, notably in cell size. The paired count data and modelling allows the decomposition of mRNA variability into distinct noise sources, showing that circadian clock time contributes only a small fraction of the total variability in mRNA number between cells. Thus, our results highlight the intrinsic biological challenges in estimating circadian phase from single-cell mRNA counts and suggest that circadian phase in single cells is encoded post-transcriptionally.

Temporal control of physiology requires the interplay between gene networks involved in daily timekeeping and tissue function across different organs. How the circadian clock interweaves with tissue-specific transcriptional programs is poorly understood. Here we dissected temporal and tissue-specific regulation at multiple gene regulatory layers by examining mouse tissues with an intact or disrupted clock over time. Integrated analysis uncovered two distinct regulatory modes underlying tissue-specific rhythms: tissue-specific oscillations in transcription factor (TF) activity, which were linked to feeding-fasting cycles in liver and sodium homeostasis in kidney; and co-localized binding of clock and tissue-specific transcription factors at distal enhancers. Chromosome conformation capture (4C-Seq) in liver and kidney identified liver-specific chromatin loops that recruited clock-bound enhancers to promoters to regulate liver-specific transcriptional rhythms. Furthermore, this looping was remarkably promoter-specific on the scale of less than ten kilobases. Enhancers can contact a rhythmic promoter while looping out nearby nonrhythmic alternative promoters, confining rhythmic enhancer activity to specific promoters. These findings suggest that chromatin folding enables the clock to regulate rhythmic transcription of specific promoters to output temporal transcriptional programs tailored to different tissues.

The timing and duration of sleep results from the interaction between a sleep-wake driven, or homeostatic, process (S) and a circadian process (C), and involves changes in gene expression and genomic regulation. Unraveling the respective contributions of S and C, and their interaction, to transcriptional and epigenomic regulatory dynamics requires sampling over time under unperturbed conditions and conditions of perturbed sleep. Here, we profiled mRNA expression and chromatin accessibility in the cerebral cortex of mice over a three-day period, including a 6-hour sleep deprivation (SD) on day two. Mathematical modeling established that a large proportion of rhythmic genes are actually governed by Process S with varying degrees of interaction with Process C, sometimes working in opposition. Remarkably, SD causes long-term effects on gene expression dynamics, outlasting phenotypic recovery, most strikingly illustrated by a dampening of the oscillation of most core clock genes, including Bmal1, suggesting that enforced wakefulness directly impacts the molecular clock machinery. Chromatin accessibility proved highly plastic and dynamically affected by SD. Distal regions, rather than promoters, display dynamics corresponding to gene transcription, implying that changes in mRNA expression result from constantly accessible promoters under the influence of distal enhancers or repressors. Srf was predicted as a transcriptional regulator driving immediate response, suggesting that Srf activity mirrors the build-up and release of sleep pressure. Our results demonstrate that a single, short SD has long-term aftereffects at the genomic regulatory level. Such effects might accumulate with repeated sleep restrictions, thereby contributing to their adverse health effects.Significance statementWhen and how long we sleep is determined by the time-of-day and how long we have been awake, which are tracked molecularly by a circadian and a sleep-wake driven process, respectively. We measured the long-term consequences of a short-term sleep deprivation (SD) on gene expression and regulation in the mouse brain, and used mathematical models to determine the relative contributions of the circadian and sleep-wake driven processes. We find that many genes, including most of the genes that constitute the molecular circadian clock, are perturbed by SD long after the mice ceased showing behavioral signs of sleep loss. Our results have implications for human health, given the high prevalence of insufficient and poor quality sleep in our contemporary society.

Summary The circadian clock and associated feeding rhythms have a profound impact on metabolism and the gut microbiome. To what extent microbiota reciprocally affect daily rhythms of physiology in the host remains elusive. Here, we analyzed transcriptome and metabolome profiles of male and female germ-free mice. While mRNA expression of circadian clock genes revealed subtle changes in liver, intestine, and white adipose tissue, germ-free mice showed considerably altered expression of genes associated with rhythmic physiology. Strikingly, the absence of the microbiome attenuated liver sexual dimorphism and sex-specific rhythmicity. The resulting feminization of male and masculinization of female germ-free animals is likely caused by altered sexual development and growth hormone secretion, associated with differential activation of xenobiotic receptors. This defines a novel mechanism by which the microbiome regulates host metabolism., Graphical Abstract, Highlights • The microbiome is required for sexual dimorphism in gene expression and metabolism • Most already-described changes in GF mice are hallmarks of a feminized metabolism • Altered sexual maturation and GH secretion cause the damping of sexual dimorphism • Microbiota-derived metabolites and ghrelin likely drive these alterations, Physiology is dynamic over the day and different between sexes. Weger et al. show that the microbiome play a key role in sustaining these sex differences in gene expression and metabolism by ensuring proper sexual maturation and growth hormone secretion. Microbiota-derived metabolites and ghrelin likely drive these sexually dimorphic dynamics.

Mammalian physiology resonates with the daily changes in the external environment, allowing processes such as rest–activity cycles, metabolism, and body temperature to synchronize with daily changes in the surroundings. Studies have identified the molecular underpinnings of robust oscillations in gene expression occurring over the 24-h day, but how acute or chronic perturbations modulate gene expression rhythms, physiology, and behavior is still relatively unknown. In this issue of Genes & Development, Hong and colleagues (pp. 1367–1379) studied how acute and chronic inflammation interacts with the circadian clock. They found that NF-κB signaling can modify chromatin states and modulate expression of genes in the core clock network as well as circadian locomotor behavior. Interestingly, a high-fat diet (HFD) fed to mice also triggers this inflammation pathway, suggesting that cross-regulatory circuits link inflammation, HFD, and the circadian clock.

Circadian rhythms in physiology and behavior evolved to resonate with daily cycles in the external environment. In mammals, organs orchestrate temporal physiology over the 24-h day, which requires extensive gene expression rhythms targeted to the right tissue. Although a core set of gene products oscillates across virtually all cell types, gene expression profiling across tissues over the 24-h day showed that rhythmic gene expression programs are tissue specific. We highlight recent progress in uncovering how the circadian clock interweaves with tissue-specific gene regulatory networks involving functions such as xenobiotic metabolism, glucose homeostasis, and sleep. This progress hinges on not only comprehensive experimental approaches but also computational methods for multivariate analysis of periodic functional genomics data. We emphasize dynamic chromatin interactions as a novel regulatory layer underlying circadian gene transcription, core clock functions, and ultimately behavior. Finally, we discuss perspectives on extending the knowledge of the circadian clock in animals to human chronobiology.

Significance Rhythms in gene expression propelled by the circadian clock and environmental signals are ubiquitous across cells and tissues. In particular, in mouse tissues, thousands of transcripts show oscillations with a period of 24 hours. Keys question are how such rhythms propagate and eventually exert functions, but also how these are generated. Here, we developed a mathematical model based on total RNA-seq to classify genes according to the respective contributions of transcriptional and posttranscriptional regulation toward mRNA expression profiles. We found that about one-third of rhythmically accumulating mRNA are under posttranscriptional regulation. Such regulation is only partially dependent on the circadian clock, showing that systemic pathways and feeding patterns contribute important posttranscriptional control of gene expression in liver., The mammalian circadian clock coordinates physiology with environmental cycles through the regulation of daily oscillations of gene expression. Thousands of transcripts exhibit rhythmic accumulations across mouse tissues, as determined by the balance of their synthesis and degradation. While diurnally rhythmic transcription regulation is well studied and often thought to be the main factor generating rhythmic mRNA accumulation, the extent of rhythmic posttranscriptional regulation is debated, and the kinetic parameters (e.g., half-lives), as well as the underlying regulators (e.g., mRNA-binding proteins) are relatively unexplored. Here, we developed a quantitative model for cyclic accumulations of pre-mRNA and mRNA from total RNA-seq data, and applied it to mouse liver. This allowed us to identify that about 20% of mRNA rhythms were driven by rhythmic mRNA degradation, and another 15% of mRNAs regulated by both rhythmic transcription and mRNA degradation. The method could also estimate mRNA half-lives and processing times in intact mouse liver. We then showed that, depending on mRNA half-life, rhythmic mRNA degradation can either amplify or tune phases of mRNA rhythms. By comparing mRNA rhythms in wild-type and Bmal1−/− animals, we found that the rhythmic degradation of many transcripts did not depend on a functional BMAL1. Interestingly clock-dependent and -independent degradation rhythms peaked at distinct times of day. We further predicted mRNA-binding proteins (mRBPs) that were implicated in the posttranscriptional regulation of mRNAs, either through stabilizing or destabilizing activities. Together, our results demonstrate how posttranscriptional regulation temporally shapes rhythmic mRNA accumulation in mouse liver.

Prioritizing molecular alterations that act as drivers of cancer remains a crucial bottleneck in therapeutic development. Here we introduce HIT'nDRIVE, a computational method that integrates genomic and transcriptomic data to identify a set of patient-specific, sequence-altered genes, with sufficient collective influence over dysregulated transcripts. HIT'nDRIVE aims to solve the “random walk facility location” (RWFL) problem in a gene (or protein) interaction network, which differs from the standard facility location problem by its use of an alternative distance measure: “multihitting time,” the expected length of the shortest random walk from any one of the set of sequence-altered genes to an expression-altered target gene. When applied to 2200 tumors from four major cancer types, HIT'nDRIVE revealed many potentially clinically actionable driver genes. We also demonstrated that it is possible to perform accurate phenotype prediction for tumor samples by only using HIT'nDRIVE-seeded driver gene modules from gene interaction networks. In addition, we identified a number of breast cancer subtype-specific driver modules that are associated with patients’ survival outcome. Furthermore, HIT'nDRIVE, when applied to a large panel of pan-cancer cell lines, accurately predicted drug efficacy using the driver genes and their seeded gene modules. Overall, HIT'nDRIVE may help clinicians contextualize massive multiomics data in therapeutic decision making, enabling widespread implementation of precision oncology.

Mammals have evolved an internal timing system, the circadian clock, which synchronizes physiology and behavior to the daily light and dark cycles of the Earth. The master clock, located in the suprachiasmatic nucleus (SCN) of the brain, takes fluctuating light input from the retina and synchronizes other tissues to the same internal rhythm. The molecular clocks that drive these circadian rhythms are ticking in nearly all cells in the body. Efforts in systems chronobiology are now being directed at understanding, on a comprehensive scale, how the circadian clock controls different layers of gene regulation to provide robust timing cues at the cellular and tissue level. In this review, we introduce some basic concepts underlying periodicity of gene regulation, and then highlight recent genome-wide investigations on the propagation of rhythms across multiple regulatory layers in mammals, all the way from chromatin conformation to protein accumulation.

Background Genomic analyses of hundreds of prostate tumors have defined a diverse landscape of mutations and genome rearrangements, but the transcriptomic effect of this complexity is less well understood, particularly at the individual tumor level. We selected a cohort of 25 high-risk prostate tumors, representing the lethal phenotype, and applied deep RNA-sequencing and matched whole genome sequencing, followed by detailed molecular characterization. Results Ten tumors were exposed to neo-adjuvant hormone therapy and expressed marked evidence of therapy response in all except one extreme case, which demonstrated early resistance via apparent neuroendocrine transdifferentiation. We observe high inter-tumor heterogeneity, including unique sets of outlier transcripts in each tumor. Interestingly, outlier expression converged on druggable cellular pathways associated with cell cycle progression, translational control or immune regulation, suggesting distinct contemporary pathway affinity and a mechanism of tumor stratification. We characterize hundreds of novel fusion transcripts, including a high frequency of ETS fusions associated with complex genome rearrangements and the disruption of tumor suppressors. Remarkably, several tumors express unique but potentially-oncogenic non-ETS fusions, which may contribute to the phenotype of individual tumors, and have significance for disease progression. Finally, one ETS-negative tumor has a striking tandem duplication genotype which appears to be highly aggressive and present at low recurrence in ETS-negative prostate cancer, suggestive of a novel molecular subtype. Conclusions The multitude of rare genomic and transcriptomic events detected in a high-risk tumor cohort offer novel opportunities for personalized oncology and their convergence on key pathways and functions has broad implications for precision medicine. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0426-y) contains supplementary material, which is available to authorized users.

A key challenge in cancer genomics is the identification and prioritization of genomic aberrations that potentially act as drivers of cancer. In this paper we introduce HIT'nDRIVE, a combinatorial method to identify aberrant genes that can collectively influence possibly distant "outlier" genes based on what we call the "random-walk facility location" RWFL problem on an interaction network. RWFL differs from the standard facility location problem by its use of "multi-hitting time", the expected minimum number of hops in a random walk originating from any aberrant gene to reach an outlier. HIT'nDRIVE thus aims to find the smallest set of aberrant genes from which one can reach outliers within a desired multi-hitting time. For that it estimates multi-hitting time based on the independent hitting times from the drivers to any given outlier and reduces the RWFL to a weighted multi-set cover problem, which it solves as an integer linear program ILP. We apply HIT'nDRIVE to identify aberrant genes that potentially act as drivers in a cancer data set and make phenotype predictions using only the potential drivers - more accurately than alternative approaches.

Post-translational histone modifications modulate chromatin activity to affect gene expression. How chromatin states underlie lineage choice in single cells is relatively unexplored. We develop sort-assisted single-cell chromatin immunocleavage (sortChIC) and map active (H3K4me1 and H3K4me3) and repressive (H3K27me3 and H3K9me3) histone modifications in the mouse bone marrow. During differentiation, hematopoietic stem and progenitor cells (HSPCs) acquire active chromatin states mediated by cell-type-specifying transcription factors, which are unique for each lineage. By contrast, most alterations in repressive marks during differentiation occur independent of the final cell type. Chromatin trajectory analysis shows that lineage choice at the chromatin level occurs at the progenitor stage. Joint profiling of H3K4me1 and H3K9me3 demonstrates that cell types within the myeloid lineage have distinct active chromatin but share similar myeloid-specific heterochromatin states. This implies a hierarchical regulation of chromatin during hematopoiesis: heterochromatin dynamics distinguish differentiation trajectories and lineages, while euchromatin dynamics reflect cell types within lineages.

The circadian clock in animals orchestrates widespread oscillatory gene expression programs, which underlie 24-h rhythms in behavior and physiology. Several studies have shown the possible roles of transcription factors and chromatin marks in controlling cyclic gene expression. However, how daily active enhancers modulate rhythmic gene transcription in mammalian tissues is not known. Using circular chromosome conformation capture (4C) combined with sequencing (4C-seq), we discovered oscillatory promoter–enhancer interactions along the 24-h cycle in the mouse liver and kidney. Rhythms in chromatin interactions were abolished in arrhythmic Bmal1 knockout mice. Deleting a contacted intronic enhancer element in the Cryptochrome 1 (Cry1) gene was sufficient to compromise the rhythmic chromatin contacts in tissues. Moreover, the deletion reduced the daily dynamics of Cry1 transcriptional burst frequency and, remarkably, shortened the circadian period of locomotor activity rhythms. Our results establish oscillating and clock-controlled promoter–enhancer looping as a regulatory layer underlying circadian transcription and behavior.

The circadian clock drives extensive temporal gene expression programs controlling daily changes in behavior and physiology. In mouse liver, transcription factors dynamics, chromatin modifications, and RNA Polymerase II (PolII) activity oscillate throughout the 24-hour (24h) day, regulating the rhythmic synthesis of thousands of transcripts. Also, 24h rhythms in gene promoter-enhancer chromatin looping accompany rhythmic mRNA synthesis. However, how chromatin organization impinges on temporal transcription and liver physiology remains unclear. Here, we applied time-resolved chromosome conformation capture (4C-seq) in livers of WT and arrhythmic Bmal1 knockout mice. In WT, we observed 24h oscillations in promoter-enhancer loops at multiple loci including the core-clock genes Period1, Period2 and Bmal1. In addition, we detected rhythmic PolII activity, chromatin modifications and transcription involving stable chromatin loops at clock-output gene promoters representing key liver function such as glucose metabolism and detoxification. Intriguingly, these contacts persisted in clock-impaired mice in which both PolII activity and chromatin marks no longer oscillated. Finally, we observed chromatin interaction hubs connecting neighbouring genes showing coherent transcription regulation across genotypes. Thus, both clock-controlled and clock-independent chromatin topology underlie rhythmic regulation of liver physiology., Author summary In the eukaryotic cell nucleus, DNA loops bring together gene promoters and distal regulatory elements to tune gene expression. To adapt to the 24h periodic changes in the environment, such as light-dark cycles, many organisms on the planet adopted an internal circadian clock encoded genetically. Thus, animal physiology resonates with external cycles. In mouse liver, thousands of genes, including ones belonging to the central clock, lipid and glucose metabolism, as well as detoxification are expressed with a 24h period. Here, we monitored DNA contacts across the circadian cycle involving the promoters of genes playing key roles in the daily physiology of the mouse liver. While the dynamics of some loops oscillates in sync with gene expression along the 24h day, other loops connected daily active regulatory elements to target gene promoters stably over time. Using arrhythmic mutant animals, we demonstrated that the maintenance of such stable loops goes beyond the circadian clock function. Also, we discovered a set of frequently interacting genes having coherent temporal expression regulation in wild type and clock impaired animals. Thus, both dynamic and static DNA contacts underlie the circadian transcription of mouse liver physiology.

Significance When and how long we sleep is determined by the time of day and how long we have been awake, which are tracked molecularly by a circadian and a sleep–wake-driven process, respectively. We measured the long-term consequences of a short-term sleep deprivation on gene expression and regulation in the mouse brain, and used mathematical models to determine the relative contributions of the circadian and sleep–wake-driven processes. We find that many genes, including most of the genes that constitute the molecular circadian clock, are perturbed by sleep deprivation long after the mice ceased showing behavioral signs of sleep loss. Our results have implications for human health, given the high prevalence of insufficient and poor-quality sleep in our contemporary society., The timing and duration of sleep results from the interaction between a homeostatic sleep–wake-driven process and a periodic circadian process, and involves changes in gene regulation and expression. Unraveling the contributions of both processes and their interaction to transcriptional and epigenomic regulatory dynamics requires sampling over time under conditions of unperturbed and perturbed sleep. We profiled mRNA expression and chromatin accessibility in the cerebral cortex of mice over a 3-d period, including a 6-h sleep deprivation (SD) on day 2. We used mathematical modeling to integrate time series of mRNA expression data with sleep–wake history, which established that a large proportion of rhythmic genes are governed by the homeostatic process with varying degrees of interaction with the circadian process, sometimes working in opposition. Remarkably, SD caused long-term effects on gene-expression dynamics, outlasting phenotypic recovery, most strikingly illustrated by a damped oscillation of most core clock genes, including Arntl/Bmal1, suggesting that enforced wakefulness directly impacts the molecular clock machinery. Chromatin accessibility proved highly plastic and dynamically affected by SD. Dynamics in distal regions, rather than promoters, correlated with mRNA expression, implying that changes in expression result from constitutively accessible promoters under the influence of enhancers or repressors. Serum response factor (SRF) was predicted as a transcriptional regulator driving immediate response, suggesting that SRF activity mirrors the build-up and release of sleep pressure. Our results demonstrate that a single, short SD has long-term aftereffects at the genomic regulatory level and highlights the importance of the sleep–wake distribution to diurnal rhythmicity and circadian processes.