A circadian gene expression atlas in mammals: implications for biology and medicine

Abstract

To characterize the role of the circadian clock in mouse physiology and behavior, we used RNA-seq and DNA arrays to quantify the transcriptomes of 12 mouse organs over time. We found 43% of all protein coding genes showed circadian rhythms in transcription somewhere in the body, largely in an organ-specific manner. In most organs, we noticed the expression of many oscillating genes peaked during transcriptional "rush hours" preceding dawn and dusk. Looking at the genomic landscape of rhythmic genes, we saw that they clustered together, were longer, and had more spliceforms than nonoscillating genes. Systems-level analysis revealed intricate rhythmic orchestration of gene pathways throughout the body. We also found oscillations in the expression of more than 1,000 known and novel noncoding RNAs (ncRNAs). Supporting their potential role in mediating clock function, ncRNAs conserved between mouse and human showed rhythmic expression in similar proportions as protein coding genes. Importantly, we also found that the majority of best-selling drugs and World Health Organization essential medicines directly target the products of rhythmic genes. Many of these drugs have short half-lives and may benefit from timed dosage. In sum, this study highlights critical, systemic, and surprising roles of the mammalian circadian clock and provides a blueprint for advancement in chronotherapy.

Keywords: chronotherapy; circadian; gene networks; genomics; noncoding RNA.

Fig. 1.

Breakdown of circadian genes and ncRNAs. (A) Number of protein-coding genes in each organ with circadian expression. Blue marks indicate the number of genes with at least one spliceform detected by RNA-seq. Orange marks indicate the number of genes with at least two spliceforms detected by RNA-seq. Blue numbers to the right of each bar list the percentage of protein-coding genes with rhythmic expression in each organ. (B) Distribution of the number of organs in which a protein-coding gene oscillated. (C) Average total number of circadian genes detected as a function of the number of organs sampled. Error bars represent SD. Best-fit model has been overlayed in red. (D) Percentages of each transcript class that did vs. did not oscillate in at least one organ.

Fig. 2.

Parameters of circadian genes across organs. (A) Relationships among organ, oscillation amplitude, and oscillation phase of circadian genes. (Upper Left) Histograms of amplitudes within each organ (number of circadian genes within each amplitude bin is shown on the horizontal axis, grouped by organ). (Upper Right) Histograms of amplitudes within each phase, across all organs. (Lower Right) Histograms of phases within each organ, with summary radial diagrams (number of circadian genes within each phase bin is shown on the vertical axis, grouped by organ). Larger versions of these radial diagrams are included in Fig. S1C for clarity. (Lower Left) Venn diagrams of the identities of the genes that oscillated within a given pair of organs. (B) Ontogenic tree constructed using the average phase differences between each organ pair’s shared circadian genes as the distance metric. Shared genes correspond to the overlapping regions from Venn diagrams in A.

Fig. 3.

Exploring pathways across biological space and time. (A) Expression of the deltex gene Dtx4 in all organs superimposed. (B) Example of pathway components’ timing reflecting function: expression profiles from the heart, for Vegfa and its two receptors Kdr and Flt1. Black arrows highlight times at which Flt1 and Kdr are anti-phased. (C) Example of systemic pathway orchestration segregating in time and space: expression profile of Igf1 in the liver, compared with its downstream target Pik3 in several organs. (D) Example of widespread pathway component synchronization within the same space (organ): expression profiles from the kidney for multiple signaling receptors that activate the PIK3-AKT-MTOR pathway.

Fig. 4.

Circadian disease genes and drug targets. (A) Overlap between circadian genes, known disease-associated genes, and drug targets. Sources for disease genes and drug targets are included in SI Methods. (B) Example of a common drug having an oscillatory gene target: expression profiles for the aspirin target Ptgs1 from heart, lung, and kidney. Traces from these organs for the mir22 host gene, predicted to target Ptgs1, are also shown. (C) Number of PubMed references for circadian vs. noncircadian genes.