Chromatin-driven de novo discovery of DNA binding motifs in the human malaria parasite

BMC Genomics

Methodology Article

Nadia Ponts¹  Karine G Le Roch¹  Stefano Lonardi²  Elena Y Harris² 

[1] Department of Cell Biology and Neuroscience, University of California, 92521, Riverside, (CA), USA;Department of Computer Science and Engineering, University of California, 92521, Riverside, (CA), USA;

关键词: Transcription Start Site;    Transcription Factor Binding Site;    Nucleosome Occupancy;    Position Weight Matrix;    Human Malaria Parasite;   

DOI  :  10.1186/1471-2164-12-601

 received in 2011-06-30, accepted in 2011-12-13,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundDespite extensive efforts to discover transcription factors and their binding sites in the human malaria parasite Plasmodium falciparum, only a few transcription factor binding motifs have been experimentally validated to date. As a consequence, gene regulation in P. falciparum is still poorly understood. There is now evidence that the chromatin architecture plays an important role in transcriptional control in malaria.ResultsWe propose a methodology for discovering cis-regulatory elements that uses for the first time exclusively dynamic chromatin remodeling data. Our method employs nucleosome positioning data collected at seven time points during the erythrocytic cycle of P. falciparum to discover putative DNA binding motifs and their transcription factor binding sites along with their associated clusters of target genes. Our approach results in 129 putative binding motifs within the promoter region of known genes. About 75% of those are novel, the remaining being highly similar to experimentally validated binding motifs. About half of the binding motifs reported show statistically significant enrichment in functional gene sets and strong positional bias in the promoter region.ConclusionExperimental results establish the principle that dynamic chromatin remodeling data can be used in lieu of gene expression data to discover binding motifs and their transcription factor binding sites. Our approach can be applied using only dynamic nucleosome positioning data, independent from any knowledge of gene function or expression.

【 授权许可】

Unknown   
© Harris 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.