TY - JOUR
T1 - Identifying Novel Transcriptional Regulators with Circadian Expression
AU - Schick, Sandra
AU - Becker, Kolja
AU - Thakurela, Sudhir
AU - Fournier, David
AU - Hampel, Mareike Hildegard
AU - Legewie, Stefan
AU - Tiwari, Vijay K
N1 - Copyright © 2016, American Society for Microbiology. All Rights Reserved.
PY - 2016/2/15
Y1 - 2016/2/15
N2 - 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.
AB - 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.
KW - Animals
KW - Circadian Rhythm
KW - Computer Simulation
KW - Epigenesis, Genetic
KW - Fibroblasts/metabolism
KW - Gene Expression Profiling
KW - Gene Regulatory Networks
KW - Mice
KW - Models, Genetic
KW - NIH 3T3 Cells
KW - RNA, Long Noncoding/genetics
KW - Transcription Factors/genetics
KW - Transcriptional Activation
U2 - 10.1128/MCB.00701-15
DO - 10.1128/MCB.00701-15
M3 - Journal article
C2 - 26644408
SN - 0270-7306
VL - 36
SP - 545
EP - 558
JO - Molecular and Cellular Biology
JF - Molecular and Cellular Biology
IS - 4
ER -