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.circadian | genomics | gene networks | noncoding RNA | chronotherapy C ircadian rhythms are endogenous 24-h oscillations in behavior and biological processes found in all kingdoms of life. This internal clock allows an organism to adapt its physiology in anticipation of transitions between night and day. The circadian clock drives oscillations in a diverse set of biological processes, including sleep, locomotor activity, blood pressure, body temperature, and blood hormone levels (1, 2). Disruption of normal circadian rhythms leads to clinically relevant disorders including neurodegeneration and metabolic disorders (3, 4). In mammals, the molecular basis for these physiological rhythms arises from the interactions between two transcriptional/translational feedback loops (reviewed in ref. 5). Many members of the core clock regulate the expression of other transcripts. These clock-controlled genes mediate the molecular clock's effect on downstream rhythms in physiology.In an effort to map these connections between the core clock and the diverse biological processes it regulates, researchers have devoted significant time and effort to studying transcriptional rhythms (6-10). Although extremely informative, most circadian studies of this nature have analyzed one or two organs by using microarrays, and little work has been done to analyze either clock control at the organism level or regulation of the noncoding transcriptome. To address these gaps in our knowledge, we used RNA-sequencing (RNA-seq) and DNA arrays to profile the transcriptomes of 12 different mouse organs: adrenal gland, aorta, brainstem, brown fat, cerebellum, heart, hypothalamus, ki...

Alternative splicing (AS) can critically affect gene function and disease, yet mapping splicing variations remains a challenge. Here, we propose a new approach to define and quantify mRNA splicing in units of local splicing variations (LSVs). LSVs capture previously defined types of alternative splicing as well as more complex transcript variations. Building the first genome wide map of LSVs from twelve mouse tissues, we find complex LSVs constitute over 30% of tissue dependent transcript variations and affect specific protein families. We show the prevalence of complex LSVs is conserved in humans and identify hundreds of LSVs that are specific to brain subregions or altered in Alzheimer's patients. Amongst those are novel isoforms in the Camk2 family and a novel poison exon in Ptbp1, a key splice factor in neurogenesis. We anticipate the approach presented here will advance the ability to relate tissue-specific splice variation to genetic variation, phenotype, and disease.DOI: http://dx.doi.org/10.7554/eLife.11752.001

The RNA-Seq sequence reads described in the article are deposited at GEO, accession GSE26248.

CircaDB (http://circadb.org) is a new database of circadian transcriptional profiles from time course expression experiments from mice and humans. Each transcript’s expression was evaluated by three separate algorithms, JTK_Cycle, Lomb Scargle and DeLichtenberg. Users can query the gene annotations using simple and powerful full text search terms, restrict results to specific data sets and provide probability thresholds for each algorithm. Visualizations of the data are intuitive charts that convey profile information more effectively than a table of probabilities. The CircaDB web application is open source and available at http://github.com/itmat/circadb.