The differential disease regulome

BMC Genomics

Methodology Article

Finn Drabløs¹  Geir K Sandve²  Knut Liestøl³  Eivind Hovig⁴  Halfdan Rydbeck⁵  Ingrid K Glad⁶  Sveinung Gundersen⁷  Trevor Clancy⁷  Eivind Tøstesen⁸  Morten Johansen⁸  Vegard Nygaard⁸  Marit Holden⁹  Lars Holden⁹  Egil Ferkingstad⁹  Arnoldo Frigessi^1,10 

[1] Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway;Department of Informatics, University of Oslo, Blindern, 0316, Oslo, Norway;Department of Informatics, University of Oslo, Blindern, 0316, Oslo, Norway;Centre for Cancer Biomedicine, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, 0310, Oslo, Norway;Department of Informatics, University of Oslo, Blindern, 0316, Oslo, Norway;Department of Tumor Biology, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, 0310, Oslo, Norway;Statistics For Innovation, Norwegian Computing Center, 0314, Oslo, Norway;Institute for Medical Informatics, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, 0310, Oslo, Norway;Department of Informatics, University of Oslo, Blindern, 0316, Oslo, Norway;Statistics For Innovation, Norwegian Computing Center, 0314, Oslo, Norway;Centre for Cancer Biomedicine, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, 0310, Oslo, Norway;Department of Mathematics, University of Oslo, Blindern, 0316, Oslo, Norway;Department of Tumor Biology, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, 0310, Oslo, Norway;Institute for Medical Informatics, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, 0310, Oslo, Norway;Statistics For Innovation, Norwegian Computing Center, 0314, Oslo, Norway;Statistics For Innovation, Norwegian Computing Center, 0314, Oslo, Norway;Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Blindern, 0317, Oslo, Norway;

关键词: Histone Modification;    Transcription Factor Binding;    Transcription Factor Binding Site;    Binding Location;    Transcription Factor Motif;   

DOI  :  10.1186/1471-2164-12-353

 received in 2011-01-28, accepted in 2011-07-07,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundTranscription factors in disease-relevant pathways represent potential drug targets, by impacting a distinct set of pathways that may be modulated through gene regulation. The influence of transcription factors is typically studied on a per disease basis, and no current resources provide a global overview of the relations between transcription factors and disease. Furthermore, existing pipelines for related large-scale analysis are tailored for particular sources of input data, and there is a need for generic methodology for integrating complementary sources of genomic information.ResultsWe here present a large-scale analysis of multiple diseases versus multiple transcription factors, with a global map of over-and under-representation of 446 transcription factors in 1010 diseases. This map, referred to as the differential disease regulome, provides a first global statistical overview of the complex interrelationships between diseases, genes and controlling elements. The map is visualized using the Google map engine, due to its very large size, and provides a range of detailed information in a dynamic presentation format.The analysis is achieved through a novel methodology that performs a pairwise, genome-wide comparison on the cartesian product of two distinct sets of annotation tracks, e.g. all combinations of one disease and one TF.The methodology was also used to extend with maps using alternative data sets related to transcription and disease, as well as data sets related to Gene Ontology classification and histone modifications. We provide a web-based interface that allows users to generate other custom maps, which could be based on precisely specified subsets of transcription factors and diseases, or, in general, on any categorical genome annotation tracks as they are improved or become available.ConclusionWe have created a first resource that provides a global overview of the complex relations between transcription factors and disease. As the accuracy of the disease regulome depends mainly on the quality of the input data, forthcoming ChIP-seq based binding data for many TFs will provide improved maps. We further believe our approach to genome analysis could allow an advance from the current typical situation of one-time integrative efforts to reproducible and upgradable integrative analysis. The differential disease regulome and its associated methodology is available at http://hyperbrowser.uio.no.

【 授权许可】

Unknown   
© Sandve et al; licensee BioMed Central Ltd. 2011. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.