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CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation
Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory ‘grammar’, or preferred arrangement of binding sites, th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3384346/ https://www.ncbi.nlm.nih.gov/pubmed/22422836 http://dx.doi.org/10.1093/nar/gks235 |
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author | Nikulova, Anna A. Favorov, Alexander V. Sutormin, Roman A. Makeev, Vsevolod J. Mironov, Andrey A. |
author_facet | Nikulova, Anna A. Favorov, Alexander V. Sutormin, Roman A. Makeev, Vsevolod J. Mironov, Andrey A. |
author_sort | Nikulova, Anna A. |
collection | PubMed |
description | Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory ‘grammar’, or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices. Given regulatory regions of orthologous and/or co-regulated genes, CORECLUST constructs a CRM model by revealing the conserved rules that describe the relative location of binding sites. The constructed model may be consequently used for the genome-wide prediction of similar CRMs, and thus detection of co-regulated genes, and for the investigation of the regulatory grammar of the system. Compared with related methods, CORECLUST shows better performance at identification of CRMs conferring muscle-specific gene expression in vertebrates and early-developmental CRMs in Drosophila. |
format | Online Article Text |
id | pubmed-3384346 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-33843462012-06-28 CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation Nikulova, Anna A. Favorov, Alexander V. Sutormin, Roman A. Makeev, Vsevolod J. Mironov, Andrey A. Nucleic Acids Res Methods Online Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory ‘grammar’, or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices. Given regulatory regions of orthologous and/or co-regulated genes, CORECLUST constructs a CRM model by revealing the conserved rules that describe the relative location of binding sites. The constructed model may be consequently used for the genome-wide prediction of similar CRMs, and thus detection of co-regulated genes, and for the investigation of the regulatory grammar of the system. Compared with related methods, CORECLUST shows better performance at identification of CRMs conferring muscle-specific gene expression in vertebrates and early-developmental CRMs in Drosophila. Oxford University Press 2012-07 2012-03-15 /pmc/articles/PMC3384346/ /pubmed/22422836 http://dx.doi.org/10.1093/nar/gks235 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Online Nikulova, Anna A. Favorov, Alexander V. Sutormin, Roman A. Makeev, Vsevolod J. Mironov, Andrey A. CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation |
title | CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation |
title_full | CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation |
title_fullStr | CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation |
title_full_unstemmed | CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation |
title_short | CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation |
title_sort | coreclust: identification of the conserved crm grammar together with prediction of gene regulation |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3384346/ https://www.ncbi.nlm.nih.gov/pubmed/22422836 http://dx.doi.org/10.1093/nar/gks235 |
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