Cargando…
The Transcriptional Network Structure of a Myeloid Cell: A Computational Approach
Understanding the general principles underlying genetic regulation in eukaryotes is an incomplete and challenging endeavor. The lack of experimental information regarding the regulation of the whole set of transcription factors and their targets in different cell types is one of the main reasons to...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5651161/ https://www.ncbi.nlm.nih.gov/pubmed/29119102 http://dx.doi.org/10.1155/2017/4858173 |
_version_ | 1783272843476205568 |
---|---|
author | Espinal-Enríquez, Jesús González-Terán, Daniel Hernández-Lemus, Enrique |
author_facet | Espinal-Enríquez, Jesús González-Terán, Daniel Hernández-Lemus, Enrique |
author_sort | Espinal-Enríquez, Jesús |
collection | PubMed |
description | Understanding the general principles underlying genetic regulation in eukaryotes is an incomplete and challenging endeavor. The lack of experimental information regarding the regulation of the whole set of transcription factors and their targets in different cell types is one of the main reasons to this incompleteness. So far, there is a small set of curated known interactions between transcription factors and their downstream genes. Here, we built a transcription factor network for human monocytic THP-1 myeloid cells based on the experimentally curated FANTOM4 database where nodes are genes and the experimental interactions correspond to links. We present the topological parameters which define the network as well as some global structural features and introduce a relative inuence parameter to quantify the relevance of a transcription factor in the context of induction of a phenotype. Genes like ZHX2, ADNP, or SMAD6 seem to be highly regulated to avoid an avalanche transcription event. We compare these results with those of RegulonDB, a highly curated transcriptional network for the prokaryotic organism E. coli, finding similarities between general hallmarks on both transcriptional programs. We believe that an approach, such as the one shown here, could help to understand the one regulation of transcription in eukaryotic cells. |
format | Online Article Text |
id | pubmed-5651161 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-56511612017-11-08 The Transcriptional Network Structure of a Myeloid Cell: A Computational Approach Espinal-Enríquez, Jesús González-Terán, Daniel Hernández-Lemus, Enrique Int J Genomics Research Article Understanding the general principles underlying genetic regulation in eukaryotes is an incomplete and challenging endeavor. The lack of experimental information regarding the regulation of the whole set of transcription factors and their targets in different cell types is one of the main reasons to this incompleteness. So far, there is a small set of curated known interactions between transcription factors and their downstream genes. Here, we built a transcription factor network for human monocytic THP-1 myeloid cells based on the experimentally curated FANTOM4 database where nodes are genes and the experimental interactions correspond to links. We present the topological parameters which define the network as well as some global structural features and introduce a relative inuence parameter to quantify the relevance of a transcription factor in the context of induction of a phenotype. Genes like ZHX2, ADNP, or SMAD6 seem to be highly regulated to avoid an avalanche transcription event. We compare these results with those of RegulonDB, a highly curated transcriptional network for the prokaryotic organism E. coli, finding similarities between general hallmarks on both transcriptional programs. We believe that an approach, such as the one shown here, could help to understand the one regulation of transcription in eukaryotic cells. Hindawi 2017 2017-09-30 /pmc/articles/PMC5651161/ /pubmed/29119102 http://dx.doi.org/10.1155/2017/4858173 Text en Copyright © 2017 Jesús Espinal-Enríquez et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Espinal-Enríquez, Jesús González-Terán, Daniel Hernández-Lemus, Enrique The Transcriptional Network Structure of a Myeloid Cell: A Computational Approach |
title | The Transcriptional Network Structure of a Myeloid Cell: A Computational Approach |
title_full | The Transcriptional Network Structure of a Myeloid Cell: A Computational Approach |
title_fullStr | The Transcriptional Network Structure of a Myeloid Cell: A Computational Approach |
title_full_unstemmed | The Transcriptional Network Structure of a Myeloid Cell: A Computational Approach |
title_short | The Transcriptional Network Structure of a Myeloid Cell: A Computational Approach |
title_sort | transcriptional network structure of a myeloid cell: a computational approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5651161/ https://www.ncbi.nlm.nih.gov/pubmed/29119102 http://dx.doi.org/10.1155/2017/4858173 |
work_keys_str_mv | AT espinalenriquezjesus thetranscriptionalnetworkstructureofamyeloidcellacomputationalapproach AT gonzalezterandaniel thetranscriptionalnetworkstructureofamyeloidcellacomputationalapproach AT hernandezlemusenrique thetranscriptionalnetworkstructureofamyeloidcellacomputationalapproach AT espinalenriquezjesus transcriptionalnetworkstructureofamyeloidcellacomputationalapproach AT gonzalezterandaniel transcriptionalnetworkstructureofamyeloidcellacomputationalapproach AT hernandezlemusenrique transcriptionalnetworkstructureofamyeloidcellacomputationalapproach |