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Identifying Novel Transcriptional Regulators with Circadian Expression.

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.

SUBMITTER: Schick S

PROVIDER: S-EPMC4751687 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Identifying Novel Transcriptional Regulators with Circadian Expression.

Schick Sandra S Becker Kolja K Thakurela Sudhir S Fournier David D Hampel Mareike Hildegard MH Legewie Stefan S Tiwari Vijay K VK

Molecular and cellular biology 20151207 4

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 in ...[more]

PMID: 26644408

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Project description:Transcriptional enhancers integrate the contributions of multiple classes of transcription factors (TFs) to orchestrate the myriad spatio-temporal gene expression programs that occur during development. A molecular understanding of enhancers with similar activities requires the identification of both their unique and their shared sequence features. To address this problem, we combined phylogenetic profiling with a DNA-based enhancer sequence classifier that analyzes the TF binding sites (TFBSs) governing the transcription of a co-expressed gene set. We first assembled a small number of enhancers that are active in Drosophila melanogaster muscle founder cells (FCs) and other mesodermal cell types. Using phylogenetic profiling, we increased the number of enhancers by incorporating orthologous but divergent sequences from other Drosophila species. Functional assays revealed that the diverged enhancer orthologs were active in largely similar patterns as their D. melanogaster counterparts, although there was extensive evolutionary shuffling of known TFBSs. We then built and trained a classifier using this enhancer set and identified additional related enhancers based on the presence or absence of known and putative TFBSs. Predicted FC enhancers were over-represented in proximity to known FC genes; and many of the TFBSs learned by the classifier were found to be critical for enhancer activity, including POU homeodomain, Myb, Ets, Forkhead, and T-box motifs. Empirical testing also revealed that the T-box TF encoded by org-1 is a previously uncharacterized regulator of muscle cell identity. Finally, we found extensive diversity in the composition of TFBSs within known FC enhancers, suggesting that motif combinatorics plays an essential role in the cellular specificity exhibited by such enhancers. In summary, machine learning combined with evolutionary sequence analysis is useful for recognizing novel TFBSs and for facilitating the identification of cognate TFs that coordinate cell type-specific developmental gene expression patterns.

Project description:BackgroundIschemic cardiomyopathy (ICM) is characterized by transcriptomic changes that alter cellular processes leading to decreased cardiac output. Because the molecular network of ICM is largely unknown, the aim of this study was to characterize the role of new transcriptional regulators in the molecular mechanisms underlying the responses to ischemia.MethodsMyocardial tissue explants from ICM patients and control (CNT) subjects were analyzed by RNA-Sequencing (RNA-Seq) and quantitative Real-Time PCR.ResultsEnrichment analysis of the ICM transcriptomic profile allowed the characterization of novel master regulators. We found that the expression of the transcriptional regulators SP100 (-1.5-fold, p < 0.05), CITED2 (-3.8-fold, p < 0.05), CEBPD (-4.9-fold, p < 0.05) and BCL3 (-3.3-fold, p < 0.05) were lower in ICM than in CNT. To gain insights into the molecular network defined by the transcription factors, we identified CEBPD, BCL3, and HIF1A target genes in the RNA-Seq datasets. We further characterized the biological processes of the target genes by gene ontology annotation. Our results suggest that CEBPD-inducible genes with roles in the inhibition of apoptosis are downregulated and that BCL3-repressible genes are involved in the regulation of cellular metabolism in ICM. Moreover, our results suggest that CITED2 downregulation causes increased expression of HIF1A target genes. Functional analysis of HIF1A target genes revealed that hypoxic and stress response genes are activated in ICM. Finally, we found a significant correlation between the mRNA levels of BCL3 and the mRNA levels of both CEBPD (r = 0.73, p < 0.001) and CITED2 (r = 0.56, p < 0.05). Interestingly, CITED2 mRNA levels are directly related to ejection fraction (EF) (r = 0.54, p < 0.05).ConclusionsOur data indicate that changes in the expression of SP100, CITED2, CEBPD, and BCL3 affect their transcription regulatory networks, which subsequently alter a number of biological processes in ICM patients. The relationship between CITED2 mRNA levels and EF emphasizes the importance of this transcription factor in ICM. Moreover, our findings identify new mechanisms used to interpret gene expression changes in ICM and provide valuable resources for further investigation of the molecular basis of human cardiac ischemic response.

Dataset Information

Identifying Novel Transcriptional Regulators with Circadian Expression.

Publications

Identifying Novel Transcriptional Regulators with Circadian Expression.

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