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Decoding the genome with an integrative analysis tool: Combinatorial CRM Decoder
The identification of genome-wide cis-regulatory modules (CRMs) and characterization of their associated epigenetic features are fundamental steps toward the understanding of gene regulatory networks. Although integrative analysis of available genome-wide information can provide new biological insig...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3177223/ https://www.ncbi.nlm.nih.gov/pubmed/21724599 http://dx.doi.org/10.1093/nar/gkr516 |
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author | Kang, Keunsoo Kim, Joomyeong Chung, Jae Hoon Lee, Daeyoup |
author_facet | Kang, Keunsoo Kim, Joomyeong Chung, Jae Hoon Lee, Daeyoup |
author_sort | Kang, Keunsoo |
collection | PubMed |
description | The identification of genome-wide cis-regulatory modules (CRMs) and characterization of their associated epigenetic features are fundamental steps toward the understanding of gene regulatory networks. Although integrative analysis of available genome-wide information can provide new biological insights, the lack of novel methodologies has become a major bottleneck. Here, we present a comprehensive analysis tool called combinatorial CRM decoder (CCD), which utilizes the publicly available information to identify and characterize genome-wide CRMs in a species of interest. CCD first defines a set of the epigenetic features which is significantly associated with a set of known CRMs as a code called ‘trace code’, and subsequently uses the trace code to pinpoint putative CRMs throughout the genome. Using 61 genome-wide data sets obtained from 17 independent mouse studies, CCD successfully catalogued ∼12 600 CRMs (five distinct classes) including polycomb repressive complex 2 target sites as well as imprinting control regions. Interestingly, we discovered that ∼4% of the identified CRMs belong to at least two different classes named ‘multi-functional CRM’, suggesting their functional importance for regulating spatiotemporal gene expression. From these examples, we show that CCD can be applied to any potential genome-wide datasets and therefore will shed light on unveiling genome-wide CRMs in various species. |
format | Online Article Text |
id | pubmed-3177223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-31772232011-09-21 Decoding the genome with an integrative analysis tool: Combinatorial CRM Decoder Kang, Keunsoo Kim, Joomyeong Chung, Jae Hoon Lee, Daeyoup Nucleic Acids Res Methods Online The identification of genome-wide cis-regulatory modules (CRMs) and characterization of their associated epigenetic features are fundamental steps toward the understanding of gene regulatory networks. Although integrative analysis of available genome-wide information can provide new biological insights, the lack of novel methodologies has become a major bottleneck. Here, we present a comprehensive analysis tool called combinatorial CRM decoder (CCD), which utilizes the publicly available information to identify and characterize genome-wide CRMs in a species of interest. CCD first defines a set of the epigenetic features which is significantly associated with a set of known CRMs as a code called ‘trace code’, and subsequently uses the trace code to pinpoint putative CRMs throughout the genome. Using 61 genome-wide data sets obtained from 17 independent mouse studies, CCD successfully catalogued ∼12 600 CRMs (five distinct classes) including polycomb repressive complex 2 target sites as well as imprinting control regions. Interestingly, we discovered that ∼4% of the identified CRMs belong to at least two different classes named ‘multi-functional CRM’, suggesting their functional importance for regulating spatiotemporal gene expression. From these examples, we show that CCD can be applied to any potential genome-wide datasets and therefore will shed light on unveiling genome-wide CRMs in various species. Oxford University Press 2011-09 2011-06-30 /pmc/articles/PMC3177223/ /pubmed/21724599 http://dx.doi.org/10.1093/nar/gkr516 Text en © The Author(s) 2011. 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 Kang, Keunsoo Kim, Joomyeong Chung, Jae Hoon Lee, Daeyoup Decoding the genome with an integrative analysis tool: Combinatorial CRM Decoder |
title | Decoding the genome with an integrative analysis tool: Combinatorial CRM Decoder |
title_full | Decoding the genome with an integrative analysis tool: Combinatorial CRM Decoder |
title_fullStr | Decoding the genome with an integrative analysis tool: Combinatorial CRM Decoder |
title_full_unstemmed | Decoding the genome with an integrative analysis tool: Combinatorial CRM Decoder |
title_short | Decoding the genome with an integrative analysis tool: Combinatorial CRM Decoder |
title_sort | decoding the genome with an integrative analysis tool: combinatorial crm decoder |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3177223/ https://www.ncbi.nlm.nih.gov/pubmed/21724599 http://dx.doi.org/10.1093/nar/gkr516 |
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