Biological rhythms play a fundamental role in the physiology and behavior of most living organisms. Rhythmic circadian expression of clock-controlled genes is orchestrated by a molecular clock that relies on interconnected negative feedback loops of transcription regulators. Here we show that the circadian clock exerts its function also through the regulation of mRNA translation. Namely, the circadian clock influences the temporal translation of a subset of mRNAs involved in ribosome biogenesis by controlling the transcription of translation initiation factors as well as the clock-dependent rhythmic activation of signaling pathways involved in their regulation. Moreover, the circadian oscillator directly regulates the transcription of ribosomal protein mRNAs and ribosomal RNAs. Thus the circadian clock exerts a major role in coordinating transcription and translation steps underlying ribosome biogenesis. Most living organisms on earth present biological rhythms that play a fundamental role in the coordination of their physiology and behavior. The discovery of the molecular circadian clock gives important insight into the mechanisms involved in the generation of these rhythms. Indeed, this molecular clock orchestrates the rhythmic transcription of clock-controlled genes involved in different aspects of metabolism, for example lipid, carbohydrate, and xenobiotic metabolisms in the liver. However, we show here that the circadian clock could also exert its function through the coordination of mRNA translation. Namely, the circadian clock influences the temporal translation of a subset of mRNAs by controlling the expression and activation of translation initiation factors, as well as the clock-dependent rhythmic activation of signaling pathways involved in their regulation. These rhythmically translated mRNAs are mainly involved in ribosome biogenesis, an energy consuming process, which has to be gated to a period when the cell resources are less limited. Moreover, the role of the circadian oscillator in this process is highlighted by its direct regulation of the transcription of ribosomal protein mRNAs and ribosomal RNAs. Thus our findings suggest that the circadian clock exerts a major role in coordinating transcription and translation steps underlying ribosome biogenesis.

Interactions of cell-autonomous circadian oscillators with diurnal cycles govern the temporal compartmentalization of cell physiology in mammals. To understand the transcriptional and epigenetic basis of diurnal rhythms in mouse liver genome-wide, we generated temporal DNA occupancy profiles by RNA polymerase II (Pol II) as well as profiles of the histone modifications H3K4me3 and H3K36me3. We used these data to quantify the relationships of phases and amplitudes between different marks. We found that rhythmic Pol II recruitment at promoters rather than rhythmic transition from paused to productive elongation underlies diurnal gene transcription, a conclusion further supported by modeling. Moreover, Pol II occupancy preceded mRNA accumulation by 3 hours, consistent with mRNA half-lives. Both methylation marks showed that the epigenetic landscape is highly dynamic and globally remodeled during the 24-hour cycle. While promoters of transcribed genes had tri-methylated H3K4 even at their trough activity times, tri-methylation levels reached their peak, on average, 1 hour after Pol II. Meanwhile, rhythms in tri-methylation of H3K36 lagged transcription by 3 hours. Finally, modeling profiles of Pol II occupancy and mRNA accumulation identified three classes of genes: one showing rhythmicity both in transcriptional and mRNA accumulation, a second class with rhythmic transcription but flat mRNA levels, and a third with constant transcription but rhythmic mRNAs. The latter class emphasizes widespread temporally gated posttranscriptional regulation in the mouse liver. In mammalian organs such as the liver, many metabolic and physiological processes occur preferentially at specific times during the 24-hour daily cycle. The timing of these rhythmic functions depends on a complex interplay between the endogenous circadian clock and environmental timing cues relayed through the master circadian clock in the suprachiasmatic nucleus, or via feeding rhythms. These rhythms can be implemented on several regulatory levels, and here we aimed at a better understanding of the transcriptional and epigenetic changes that regulate diurnal rhythms. We performed genome-wide analysis of the locations of RNA polymerase II (Pol II) and the epigenetic histone modifications H3K4me3 and H3K36me3 at specific times of day, relating these data to mRNA expression levels. Our analyses show that Pol II transcriptional rhythms are biphasic in mouse liver, having predominant peak activities in the morning and evening. Moreover, dynamic changes in histone marks lag transcription rhythms genome-wide, indicating that the epigenetic landscape can be remodeled during the 24-hour cycle. Finally, a quantitative analysis of temporal Pol II and mRNA accumulation profiles indicates that posttranscriptional regulation significantly contributes to the amplitude and phase of mRNA accumulation profiles. While many studies have analyzed how transcription and chromatin states are modified during irreversible cell differentiation processes, our work highlights how these states can evolve reversibly in a system exhibiting periodicity in time.

For most women of reproductive age, assessing menstrual health and fertility typically involves regular visits to a gynecologist or another clinician. While these evaluations provide critical information on an individual’s reproductive health status, they typically rely on memory-based self-reports, and the results are rarely, if ever, assessed at the population level. In recent years, mobile apps for menstrual tracking have become very popular, allowing us to evaluate the reliability and tracking frequency of millions of self-observations, thereby providing an unparalleled view, both in detail and scale, on menstrual health and its evolution for large populations. In particular, the primary aim of this study was to describe the tracking behavior of the app users and their overall observation patterns in an effort to understand if they were consistent with previous small-scale medical studies. The secondary aim was to investigate whether their precision allowed the detection and estimation of ovulation timing, which is critical for reproductive and menstrual health. Retrospective self-observation data were acquired from two mobile apps dedicated to the application of the sympto-thermal fertility awareness method, resulting in a dataset of more than 30 million days of observations from over 2.7 million cycles for two hundred thousand users. The analysis of the data showed that up to 40% of the cycles in which users were seeking pregnancy had recordings every single day. With a modeling approach using Hidden Markov Models to describe the collected data and estimate ovulation timing, it was found that follicular phases average duration and range were larger than previously reported, with only 24% of ovulations occurring at cycle days 14 to 15, while the luteal phase duration and range were in line with previous reports, although short luteal phases (10 days or less) were more frequently observed (in up to 20% of cycles). The digital epidemiology approach presented here can help to lead to a better understanding of menstrual health and its connection to women’s health overall, which has historically been severely understudied.

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. 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 vaginal ecosystem is closely tied to human health and reproductive outcomes, yet its dynamics in the wake of childbirth remain poorly characterized. Here, we profile the vaginal microbiota and cytokine milieu of participants sampled longitudinally throughout pregnancy and for at least one year postpartum. We show that delivery, regardless of mode, is associated with a vaginal pro-inflammatory cytokine response and the loss of Lactobacillus dominance. By contrast, neither the progression of gestation nor the approach of labor strongly altered the vaginal ecosystem. At 9.5-months postpartum—the latest timepoint at which cytokines were assessed—elevated inflammation coincided with vaginal bacterial communities that had remained perturbed (highly diverse) from the time of delivery. Time-to-event analysis indicated a one-year postpartum probability of transitioning to Lactobacillus dominance of 49.4%. As diversity and inflammation declined during the postpartum period, dominance by L. crispatus, the quintessential health-associated commensal, failed to return: its prevalence before, immediately after, and one year after delivery was 41%, 4%, and 9%, respectively. Revisiting our pre-delivery data, we found that a prior live birth was associated with a lower odds of L. crispatus dominance in pregnant participants—an outcome modestly tempered by a longer ( > 18-month) interpregnancy interval. Our results suggest that reproductive history and childbirth in particular remodel the vaginal ecosystem and that the timing and degree of recovery from delivery may help determine the subsequent health of the woman and of future pregnancies.

Diverse and non- Lactobacillus -dominated vaginal microbial communities are associated with adverse health outcomes such as preterm birth and the acquisition of sexually transmitted infections. Despite the importance of recognizing and understanding the key risk-associated features of these communities, their heterogeneous structure and properties remain ill-defined. Clustering approaches are commonly used to characterize vaginal communities, but they lack sensitivity and robustness in resolving substructures and revealing transitions between potential sub-communities. Here, we address this need with an approach based on mixed membership topic models. Using longitudinal data from cohorts of pregnant and non-pregnant study participants, we show that topic models more accurately describe sample composition, longitudinal changes, and better predict the loss of Lactobacillus dominance. We identify several non- Lactobacillus -dominated sub-communities common to both cohorts and independent of reproductive status. In non-pregnant individuals, we find that the menstrual cycle modulates transitions between and within sub-communities, as well as the concentrations of half of the cytokines and 18% of metabolites. Overall, our analyses based on mixed membership models reveal substructures of vaginal ecosystems which may have important clinical and biological associations.