Deciphering transcription factor binding patterns from genome-wide high density ChIP-chip tiling array data

BMC Proceedings

Proceedings

Krishna Murthy R Karuturi¹  Juntao Li¹  Jianhua Liu²  Majid Eshaghi²  Lei Zhu² 

[1] Computational & Systems Biology, Genome Institute of Singapore, 60 Biopolis Street, (S)138672, Singapore;Systems Biology, Genome Institute of Singapore, 60 Biopolis Street, (S)138672, Singapore;

关键词: Transcription Start Site;    Signal Region;    H2O2 Treatment;    Binding Pattern;    Tiling Array;   

DOI  :  10.1186/1753-6561-5-S2-S8

来源: Springer

【 摘 要 】

BackgroundThe binding events of DNA-interacting proteins and their patterns can be extensively characterized by high density ChIP-chip tiling array data. The characteristics of the binding events could be different for different transcription factors. They may even vary for a given transcription factor among different interaction loci. The knowledge of binding sites and binding occupancy patterns are all very useful to understand the DNA-protein interaction and its role in the transcriptional regulation of genes.ResultsIn the view of the complexity of the DNA-protein interaction and the opportunity offered by high density tiled ChIP-chip data, we present a statistical procedure which focuses on identifying the interaction signal regions instead of signal peaks using moving window binomial testing method and deconvolving the patterns of interaction using peakedness and skewness scores. We analyzed ChIP-chip data of 4 different DNA interacting proteins including transcription factors and RNA polymerase in fission yeast using our procedure. Our analysis revealed the variation of binding patterns within and across different DNA interacting proteins. We present their utility in understanding transcriptional regulation from ChIP-chip data.ConclusionsOur method can successfully detect the signal regions and characterize the binding patterns in ChIP-chip data which help appropriate analysis of the ChIP-chip data.

【 授权许可】

Unknown   
© Li 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.