| Title |
GATA-dependent transcriptional and epigenetic control of cardiac lineage specification and differentiation
|
|---|---|
| Published in |
Cellular and Molecular Life Sciences, July 2015
|
| DOI | 10.1007/s00018-015-1974-3 |
| Pubmed ID | |
| Authors |
Sonia Stefanovic, Vincent M. Christoffels |
| Abstract |
Heart progenitor cells differentiate into various cell types including pacemaker and working cardiomyocytes. Cell-type specific gene expression is achieved by combinatorial interactions between tissue-specific transcription factors (TFs), co-factors, and chromatin remodelers and DNA binding elements in regulatory regions. Dysfunction of these transcriptional networks may result in congenital heart defects. Functional analysis of the regulatory DNA sequences has contributed substantially to the identification of the transcriptional network components and combinatorial interactions regulating the tissue-specific gene programs. GATA TFs have been identified as central players in these networks. In particular, GATA binding elements have emerged as a platform to recruit broadly active histone modification enzymes and cell-type-specific co-factors to drive cell-type-specific gene programs. Here, we discuss the role of GATA factors in cell fate decisions and differentiation in the developing heart. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 67% |
| France | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Turkey | 1 | 2% |
| Netherlands | 1 | 2% |
| Switzerland | 1 | 2% |
| Unknown | 48 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 31% |
| Student > Ph. D. Student | 14 | 27% |
| Student > Bachelor | 5 | 10% |
| Student > Doctoral Student | 3 | 6% |
| Other | 2 | 4% |
| Other | 5 | 10% |
| Unknown | 6 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 25 | 49% |
| Agricultural and Biological Sciences | 8 | 16% |
| Medicine and Dentistry | 6 | 12% |
| Immunology and Microbiology | 1 | 2% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 2% |
| Other | 2 | 4% |
| Unknown | 8 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 July 2015.
All research outputs
#16,031,680
of 23,794,258 outputs
Outputs from Cellular and Molecular Life Sciences
#3,071
of 4,151 outputs
Outputs of similar age
#156,213
of 264,804 outputs
Outputs of similar age from Cellular and Molecular Life Sciences
#43
of 65 outputs
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