Comparison of low and high dose ionising radiation using topological analysis of gene coexpression networks

<p>Abstract</p> <p>Background</p> <p>The growing use of imaging procedures in medicine has raised concerns about exposure to low-dose ionising radiation (LDIR). While the disastrous effects of high dose ionising radiation (HDIR) is well documented, the detrimental effec...

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Main Authors: Ray Monika, Yunis Reem, Chen Xiucui, Rocke David M
Format: Article
Language:English
Published: BMC 2012-05-01
Series:BMC Genomics
Online Access:http://www.biomedcentral.com/1471-2164/13/190
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spelling doaj-99af742e501248e2a6e77be9c7ae66d22020-11-25T02:26:01ZengBMCBMC Genomics1471-21642012-05-0113119010.1186/1471-2164-13-190Comparison of low and high dose ionising radiation using topological analysis of gene coexpression networksRay MonikaYunis ReemChen XiucuiRocke David M<p>Abstract</p> <p>Background</p> <p>The growing use of imaging procedures in medicine has raised concerns about exposure to low-dose ionising radiation (LDIR). While the disastrous effects of high dose ionising radiation (HDIR) is well documented, the detrimental effects of LDIR is not well understood and has been a topic of much debate. Since little is known about the effects of LDIR, various kinds of wet-lab and computational analyses are required to advance knowledge in this domain. In this paper we carry out an “upside-down pyramid” form of systems biology analysis of microarray data. We characterised the global genomic response following 10 cGy (low dose) and 100 cGy (high dose) doses of X-ray ionising radiation at four time points by analysing the topology of gene coexpression networks. This study includes a rich experimental design and state-of-the-art computational systems biology methods of analysis to study the differences in the transcriptional response of skin cells exposed to low and high doses of radiation.</p> <p>Results</p> <p>Using this method we found important genes that have been linked to immune response, cell survival and apoptosis. Furthermore, we also were able to identify genes such as BRCA1, ABCA1, TNFRSF1B, MLLT11 that have been associated with various types of cancers. We were also able to detect many genes known to be associated with various medical conditions.</p> <p>Conclusions</p> <p>Our method of applying network topological differences can aid in identifying the differences among similar (eg: radiation effect) yet very different biological conditions (eg: different dose and time) to generate testable hypotheses. This is the first study where a network level analysis was performed across two different radiation doses at various time points, thereby illustrating changes in the cellular response over time.</p> http://www.biomedcentral.com/1471-2164/13/190
collection DOAJ
language English
format Article
sources DOAJ
author Ray Monika
Yunis Reem
Chen Xiucui
Rocke David M
spellingShingle Ray Monika
Yunis Reem
Chen Xiucui
Rocke David M
Comparison of low and high dose ionising radiation using topological analysis of gene coexpression networks
BMC Genomics
author_facet Ray Monika
Yunis Reem
Chen Xiucui
Rocke David M
author_sort Ray Monika
title Comparison of low and high dose ionising radiation using topological analysis of gene coexpression networks
title_short Comparison of low and high dose ionising radiation using topological analysis of gene coexpression networks
title_full Comparison of low and high dose ionising radiation using topological analysis of gene coexpression networks
title_fullStr Comparison of low and high dose ionising radiation using topological analysis of gene coexpression networks
title_full_unstemmed Comparison of low and high dose ionising radiation using topological analysis of gene coexpression networks
title_sort comparison of low and high dose ionising radiation using topological analysis of gene coexpression networks
publisher BMC
series BMC Genomics
issn 1471-2164
publishDate 2012-05-01
description <p>Abstract</p> <p>Background</p> <p>The growing use of imaging procedures in medicine has raised concerns about exposure to low-dose ionising radiation (LDIR). While the disastrous effects of high dose ionising radiation (HDIR) is well documented, the detrimental effects of LDIR is not well understood and has been a topic of much debate. Since little is known about the effects of LDIR, various kinds of wet-lab and computational analyses are required to advance knowledge in this domain. In this paper we carry out an “upside-down pyramid” form of systems biology analysis of microarray data. We characterised the global genomic response following 10 cGy (low dose) and 100 cGy (high dose) doses of X-ray ionising radiation at four time points by analysing the topology of gene coexpression networks. This study includes a rich experimental design and state-of-the-art computational systems biology methods of analysis to study the differences in the transcriptional response of skin cells exposed to low and high doses of radiation.</p> <p>Results</p> <p>Using this method we found important genes that have been linked to immune response, cell survival and apoptosis. Furthermore, we also were able to identify genes such as BRCA1, ABCA1, TNFRSF1B, MLLT11 that have been associated with various types of cancers. We were also able to detect many genes known to be associated with various medical conditions.</p> <p>Conclusions</p> <p>Our method of applying network topological differences can aid in identifying the differences among similar (eg: radiation effect) yet very different biological conditions (eg: different dose and time) to generate testable hypotheses. This is the first study where a network level analysis was performed across two different radiation doses at various time points, thereby illustrating changes in the cellular response over time.</p>
url http://www.biomedcentral.com/1471-2164/13/190
work_keys_str_mv AT raymonika comparisonoflowandhighdoseionisingradiationusingtopologicalanalysisofgenecoexpressionnetworks
AT yunisreem comparisonoflowandhighdoseionisingradiationusingtopologicalanalysisofgenecoexpressionnetworks
AT chenxiucui comparisonoflowandhighdoseionisingradiationusingtopologicalanalysisofgenecoexpressionnetworks
AT rockedavidm comparisonoflowandhighdoseionisingradiationusingtopologicalanalysisofgenecoexpressionnetworks
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