Dataset Information

CYCLOPS reveals human transcriptional rhythms in health and disease.

ABSTRACT: Circadian rhythms modulate many aspects of physiology. Knowledge of the molecular basis of these rhythms has exploded in the last 20 years. However, most of these data are from model organisms, and translation to clinical practice has been limited. Here, we present an approach to identify molecular rhythms in humans from thousands of unordered expression measurements. Our algorithm, cyclic ordering by periodic structure (CYCLOPS), uses evolutionary conservation and machine learning to identify elliptical structure in high-dimensional data. From this structure, CYCLOPS estimates the phase of each sample. We validated CYCLOPS using temporally ordered mouse and human data and demonstrated its consistency on human data from two independent research sites. We used this approach to identify rhythmic transcripts in human liver and lung, including hundreds of drug targets and disease genes. Importantly, for many genes, the circadian variation in expression exceeded variation from genetic and other environmental factors. We also analyzed hepatocellular carcinoma samples and show these solid tumors maintain circadian function but with aberrant output. Finally, to show how this method can catalyze medical translation, we show that dosage time can temporally segregate efficacy from dose-limiting toxicity of streptozocin, a chemotherapeutic drug. In sum, these data show the power of CYCLOPS and temporal reconstruction in bridging basic circadian research and clinical medicine.

SUBMITTER: Anafi RC

PROVIDER: S-EPMC5441789 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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CYCLOPS reveals human transcriptional rhythms in health and disease.

Anafi Ron C RC Francey Lauren J LJ Hogenesch John B JB Kim Junhyong J

Proceedings of the National Academy of Sciences of the United States of America 20170424 20

Circadian rhythms modulate many aspects of physiology. Knowledge of the molecular basis of these rhythms has exploded in the last 20 years. However, most of these data are from model organisms, and translation to clinical practice has been limited. Here, we present an approach to identify molecular rhythms in humans from thousands of unordered expression measurements. Our algorithm, cyclic ordering by periodic structure (CYCLOPS), uses evolutionary conservation and machine learning to identify e ...[more]

PMID: 28439010

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Project description:The circadian regulatory network is organized in a hierarchical fashion, with a central oscillator in the suprachiasmatic nuclei (SCN) orchestrating circadian oscillations in peripheral tissues. The nature of the relationship between central and peripheral oscillators, however, is poorly understood. We used the tetOFF expression system to specifically restore Clock function in the brains of Clock(?19) mice, which have compromised circadian clocks. Rescued mice showed normal locomotor rhythms in constant darkness, with activity period lengths approximating wildtype controls. We used microarray analysis to assess whether brain-specific rescue of circadian rhythmicity was sufficient to restore circadian transcriptional output in the liver. Compared to Clock mutants, Clock-rescue mice showed significantly larger numbers of cycling transcripts with appropriate phase and period lengths, including many components of the core circadian oscillator. This indicates that the SCN oscillator overcomes local circadian defects and signals directly to the molecular clock. Interestingly, the vast majority of core clock genes in liver were responsive to Clock expression in the SCN, suggesting that core clock genes in peripheral tissues are intrinsically sensitive to SCN cues. Nevertheless, most circadian output in the liver was absent or severely low-amplitude in Clock-rescue animals, demonstrating that the majority of peripheral transcriptional rhythms depend on a fully functional local circadian oscillator. We identified several new system-driven rhythmic genes in the liver, including Alas1 and Mfsd2. Finally, we show that 12-hour transcriptional rhythms (i.e., circadian "harmonics") are disrupted by Clock loss-of-function. Brain-specific rescue of Clock converted 12-hour rhythms into 24-hour rhythms, suggesting that signaling via the central circadian oscillator is required to generate one of the two daily peaks of expression. Based on these data, we conclude that 12-hour rhythms are driven by interactions between central and peripheral circadian oscillators.

Dataset Information

CYCLOPS reveals human transcriptional rhythms in health and disease.

Publications

CYCLOPS reveals human transcriptional rhythms in health and disease.

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