Dataset Information

Transcription-factor-dependent enhancer transcription defines a gene regulatory network for cardiac rhythm.

ABSTRACT: The noncoding genome is pervasively transcribed. Noncoding RNAs (ncRNAs) generated from enhancers have been proposed as a general facet of enhancer function and some have been shown to be required for enhancer activity. Here we examine the transcription-factor-(TF)-dependence of ncRNA expression to define enhancers and enhancer-associated ncRNAs that are involved in a TF-dependent regulatory network. TBX5, a cardiac TF, regulates a network of cardiac channel genes to maintain cardiac rhythm. We deep sequenced wildtype and Tbx5-mutant mouse atria, identifying ~2600 novel Tbx5-dependent ncRNAs. Tbx5-dependent ncRNAs were enriched for tissue-specific marks of active enhancers genome-wide. Tbx5-dependent ncRNAs emanated from regions that are enriched for TBX5-binding and that demonstrated Tbx5-dependent enhancer activity. Tbx5-dependent ncRNA transcription provided a quantitative metric of Tbx5-dependent enhancer activity, correlating with target gene expression. We identified RACER, a novel Tbx5-dependent long noncoding RNA (lncRNA) required for the expression of the calcium-handling gene Ryr2. We illustrate that TF-dependent enhancer transcription can illuminate components of TF-dependent gene regulatory networks.

SUBMITTER: Yang XH

PROVIDER: S-EPMC5745077 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Transcription-factor-dependent enhancer transcription defines a gene regulatory network for cardiac rhythm.

Yang Xinan H XH Nadadur Rangarajan D RD Hilvering Catharina Re CR Bianchi Valerio V Werner Michael M Mazurek Stefan R SR Gadek Margaret M Shen Kaitlyn M KM Goldman Joseph Aaron JA Tyan Leonid L Bekeny Jenna J Hall Johnathon M JM Lee Nutishia N Perez-Cervantes Carlos C Burnicka-Turek Ozanna O Poss Kenneth D KD Weber Christopher R CR de Laat Wouter W Ruthenburg Alexander J AJ Moskowitz Ivan P IP

eLife 20171227

The noncoding genome is pervasively transcribed. Noncoding RNAs (ncRNAs) generated from enhancers have been proposed as a general facet of enhancer function and some have been shown to be required for enhancer activity. Here we examine the transcription-factor-(TF)-dependence of ncRNA expression to define enhancers and enhancer-associated ncRNAs that are involved in a TF-dependent regulatory network. TBX5, a cardiac TF, regulates a network of cardiac channel genes to maintain cardiac rhythm. We ...[more]

PMID: 29280435

Similar Datasets

Project description:Transcription factors (TFs) regulate the expression of target genes, inducing changes in cell morphology or activities needed for cell fate determination and differentiation. The BMP signaling pathway is widely regarded as one of the most important pathways in vertebrate skeletal biology, of which BMP2 is a potent inducer, governing the osteoblast differentiation of bone marrow stromal cells (BMSCs). However, the mechanism by which BMP2 initiates its downstream transcription factor cascade and determines the direction of differentiation remains largely unknown. In this study, we used RNA-seq, ATAC-seq, and animal models to characterize the BMP2-dependent gene regulatory network governing osteoblast lineage commitment. Sp7-Cre; Bmp2fx/fx mice (BMP2-cKO) were generated and exhibited decreased bone density and lower osteoblast number (n > 6). In vitro experiments showed that BMP2-cKO mouse bone marrow stromal cells (mBMSCs) had an impact on osteoblast differentiation and deficient cell proliferation. Osteogenic medium induced mBMSCs from BMP2-cKO mice and control were subjected to RNA-seq and ATAC-seq analysis to reveal differentially expressed TFs, along with their target open chromatin regions. Combined with H3K27Ac CUT&Tag during osteoblast differentiation, we identified 2338 BMP2-dependent osteoblast-specific active enhancers. Motif enrichment assay revealed that over 80% of these elements were directly targeted by RUNX2, DLX5, MEF2C, OASIS, and KLF4. We deactivated Klf4 in the Sp7 + lineage to validate the role of KLF4 in osteoblast differentiation of mBMSCs. Compared to the wild-type, Sp7-Cre; Klf4fx/+ mice (KLF4-Het) were smaller in size and had abnormal incisors resembling BMP2-cKO mice. Additionally, KLF4-Het mice had fewer osteoblasts and decreased osteogenic ability. RNA-seq and ATAC-seq revealed that KLF4 mainly "co-bound" with RUNX2 to regulate downstream genes. Given the significant overlap between KLF4- and BMP2-dependent NFRs and enriched motifs, our findings outline a comprehensive BMP2-dependent gene regulatory network specifically governing osteoblast differentiation of the Sp7 + lineage, in which Klf4 is a novel transcription factor.

Project description:The unfolded protein response (UPR) responds to disruption of endoplasmic reticulum (ER) function by initiating signaling cascades that ultimately culminate in extensive transcriptional regulation. Classically, this regulation includes genes encoding ER chaperones, ER-associated degradation factors, and others involved in secretory protein folding and processing, and is carried out by the transcriptional activators that are produced as a consequence of UPR activation. However, up to half of the mRNAs regulated by ER stress are downregulated rather than upregulated, and the mechanisms linking ER stress and UPR activation to mRNA suppression are poorly understood. To begin to address this issue, we used a "bottom-up" approach to study the metabolic gene regulatory network controlled by the UPR in the liver, because ER stress in the liver leads to lipid accumulation, and fatty liver disease is the most common liver disease in the western world. qRT-PCR profiling of mouse liver mRNAs during ER stress revealed that suppression of the transcriptional regulators C/EBP?, PPAR?, and PGC-1? preceded lipid accumulation, and was then followed by suppression of mRNAs encoding key enzymes involved in fatty acid oxidation and lipoprotein biogenesis and transport. Mice lacking the ER stress sensor ATF6?, which experience persistent ER stress and profound lipid accumulation during challenge, were then used as the basis for a functional genomics approach that allowed genes to be grouped into distinct expression profiles. This clustering predicted that ER stress would suppress the activity of the metabolic transcriptional regulator HNF4?-a finding subsequently confirmed by chromatin immunopreciptation at the Cebpa and Pgc1a promoters. Our results establish a framework for hepatic gene regulation during ER stress and suggest that HNF4? occupies the apex of that framework. They also provide a unique resource for the community to further explore the temporal regulation of gene expression during ER stress in vivo.

Project description:BackgroundGene regulatory networks (GRNs) are models of molecule-gene interactions instrumental in the coordination of gene expression. Transcription factor (TF)-GRNs are an important subset of GRNs that characterize gene expression as the effect of TFs acting on their target genes. Although such networks can qualitatively summarize TF-gene interactions, it is highly desirable to quantitatively determine the strengths of the interactions in a TF-GRN as well as the magnitudes of TF activities. To our knowledge, such analysis is rare in plant biology. A computational methodology developed for this purpose is network component analysis (NCA), which has been used for studying large-scale microbial TF-GRNs to obtain nontrivial, mechanistic insights. In this work, we employed NCA to quantitatively analyze a plant TF-GRN important in floral development using available regulatory information from AGRIS, by processing previously reported gene expression data from four shoot apical meristem cell types.ResultsThe NCA model satisfactorily accounted for gene expression measurements in a TF-GRN of seven TFs (LFY, AG, SEPALLATA3 [SEP3], AP2, AGL15, HY5 and AP3/PI) and 55 genes. NCA found strong interactions between certain TF-gene pairs including LFY???MYB17, AG???CRC, AP2???RD20, AGL15???RAV2 and HY5???HLH1, and the direction of the interaction (activation or repression) for some AGL15 targets for which this information was not previously available. The activity trends of four TFs?-?LFY, AG, HY5 and AP3/PI as deduced by NCA correlated well with the changes in expression levels of the genes encoding these TFs across all four cell types; such a correlation was not observed for SEP3, AP2 and AGL15.ConclusionsFor the first time, we have reported the use of NCA to quantitatively analyze a plant TF-GRN important in floral development for obtaining nontrivial information about connectivity strengths between TFs and their target genes as well as TF activity. However, since NCA relies on documented connectivity information about the underlying TF-GRN, it is currently limited in its application to larger plant networks because of the lack of documented connectivities. In the future, the identification of interactions between plant TFs and their target genes on a genome scale would allow the use of NCA to provide quantitative regulatory information about plant TF-GRNs, leading to improved insights on cellular regulatory programs.

Dataset Information

Transcription-factor-dependent enhancer transcription defines a gene regulatory network for cardiac rhythm.

Publications

Transcription-factor-dependent enhancer transcription defines a gene regulatory network for cardiac rhythm.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets