Abstract
Organisms adapt their physiology and behavior to the 24-h day-night cycle to which they are exposed. On a cellular level, this is regulated by intrinsic transcriptional-translational feedback loops that are important for maintaining the circadian rhythm. These loops are organized by members of the core clock network, which further regulate transcription of downstream genes, resulting in their circadian expression. Despite progress in understanding circadian gene expression, only a few players involved in circadian transcriptional regulation, including transcription factors, epigenetic regulators, and long noncoding RNAs, are known. Aiming to discover such genes, we performed a high-coverage transcriptome analysis of a circadian time course in murine fibroblast cells. In combination with a newly developed algorithm, we identified many transcription factors, epigenetic regulators, and long intergenic noncoding RNAs that are cyclically expressed. In addition, a number of these genes also showed circadian expression in mouse tissues. Furthermore, the knockdown of one such factor, Zfp28, influenced the core clock network. Mathematical modeling was able to predict putative regulator-effector interactions between the identified circadian genes and may help for investigations into the gene regulatory networks underlying circadian rhythms.