The Making and Breaking of RNAs: Dynamics of Rhythmic RNA Expression in Mammals

A Comparative Study of Algorithms Detecting Differential Rhythmicity in Transcriptomic Data

Rhythmic transcripts play pivotal roles in driving the daily oscillations of various biological processes. Genetic or environmental disruptions can lead to alterations in the rhythmicity of transcripts, ultimately impacting downstream circadian outputs, including metabolic processes and even behavior. To statistically compare the differences in transcript rhythms between 2 or more conditions, several algorithms have been developed to analyze circadian transcriptomic data, each with distinct features. In this study, we compared the performance of 7 algorithms that were specifically designed to detect differential rhythmicity (DODR, LimoRhyde, CircaCompare, compareRhythms, diffCircadian, dryR, and RepeatedCircadian). We found that even when applying the same statistical threshold, these algorithms yielded varying numbers of differentially rhythmic transcripts, most likely because each algorithm defines rhythmic and differentially rhythmic transcripts differently. Nevertheless, the output for the differential phase and amplitude were identical between dryR and compareRhyhms, and diffCircadian and CircaCompare, while the output from LimoRhyde2 was highly correlated with that from diffCircadian and CircaCompare. Because each algorithm has unique requirements for input data and reports different information as an output, it is crucial to ensure the compatibility of input data with the chosen algorithm and assess whether the algorithm's output fits the user's needs when selecting an algorithm for analysis.

Coordination of rhythmic RNA synthesis and degradation orchestrates 24- and 12-h RNA expression patterns in mouse fibroblasts

Circadian RNA expression is essential to ultimately regulate a plethora of downstream rhythmic biochemical, physiological, and behavioral processes. Both transcriptional and posttranscriptional mechanisms are considered important to drive rhythmic RNA expression; however, the extent to which each regulatory process contributes to the rhythmic RNA expression remains controversial. To systematically address this, we monitored RNA dynamics using metabolic RNA labeling technology during a circadian cycle in mouse fibroblasts. We find that rhythmic RNA synthesis is the primary contributor of 24-h RNA rhythms, while rhythmic degradation is more important for 12-h RNA rhythms. These rhythms were predominantly regulated by Bmal1 and/or the core clock mechanism, and the interplay between rhythmic synthesis and degradation has a significant impact in shaping rhythmic RNA expression patterns. Interestingly, core clock RNAs are regulated by multiple rhythmic processes and have the highest amplitude of synthesis and degradation, presumably critical to sustain robust rhythmicity of cell-autonomous circadian rhythms. Our study yields invaluable insights into the temporal dynamics of both 24- and 12-h RNA rhythms in mouse fibroblasts.

A comparative study of algorithms detecting differential rhythmicity in transcriptomic data

Rhythmic transcripts play pivotal roles in driving the daily oscillations of various biological processes. Genetic or environmental disruptions can lead to alterations in the rhythmicity of transcripts, ultimately impacting downstream circadian outputs, including metabolic processes and even behavior. To statistically compare the differences in transcript rhythms between two or more conditions, several algorithms have been developed to analyze circadian transcriptomic data, each with distinct features. In this study, we compared the performance of seven algorithms that were specifically designed to detect differential rhythmicity. We found that even when applying the same statistical threshold, these algorithms yielded varying numbers of differentially rhythmic transcripts. Nevertheless, the set of transcripts commonly identified as differentially rhythmic exhibited substantial overlap among algorithms. Furthermore, the phase and amplitude differences calculated by these algorithms displayed significant correlations. In summary, our study highlights a high degree of similarity in the results produced by these algorithms. Furthermore, when selecting an algorithm for analysis, it is crucial to ensure the compatibility of input data with the specific requirements of the chosen algorithm and to assess whether the algorithm's output fits the needs of the user.

Coordination of rhythmic RNA synthesis and degradation orchestrates 24-hour and 12-hour RNA expression patterns in mouse fibroblasts

Circadian RNA expression is essential to ultimately regulate a plethora of downstream rhythmic biochemical, physiological, and behavioral processes. Both transcriptional and post-transcriptional mechanisms are considered important to drive rhythmic RNA expression, however, the extent to which each regulatory process contributes to the rhythmic RNA expression remains controversial. To systematically address this, we monitored RNA dynamics using metabolic RNA labeling technology during a circadian cycle in mouse fibroblasts. We find that rhythmic RNA synthesis is the primary contributor of 24 hr RNA rhythms, while rhythmic degradation is more important for 12 hr RNA rhythms. These rhythms were predominantly regulated by Bmal1 and/or the core clock mechanism, and interplay between rhythmic synthesis and degradation has a significant impact in shaping rhythmic RNA expression patterns. Interestingly, core clock RNAs are regulated by multiple rhythmic processes and have the highest amplitude of synthesis and degradation, presumably critical to sustain robust rhythmicity of cell-autonomous circadian rhythms. Our study yields invaluable insights into the temporal dynamics of both 24 hr and 12 hr RNA rhythms in mouse fibroblasts.

Timing without coding: How do long non-coding RNAs regulate circadian rhythms?

Long non-coding RNAs (lncRNAs) are a new class of regulatory RNAs that play important roles in disease development and a variety of biological processes. Recent studies have underscored the importance of lncRNAs in the circadian clock system and demonstrated that lncRNAs regulate core clock genes and the core clock machinery in mammals. In this review, we provide an overview of our current understanding of how lncRNAs regulate the circadian clock without coding a protein. We also offer additional insights into the challenges in understanding the functions of lncRNAs and other unresolved questions in the field. We do not cover other regulatory ncRNAs even though they also play important roles; readers are highly encouraged to refer to other excellent reviews on this topic.