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A hidden Markov model for detecting multi-gene chromatin domains
BMC Bioinformatics volume 11, Article number: O5 (2010)
Motivation
Epigenetic regulations are important mechanisms for transcriptional control. There is evidence that neighbouring genes, although not always involved in the same pathways, are still similarly regulated via various histone modifications. Currently, most studies are limited to local epigenetic patterns, whereas methods for analysing large-scale organizations are still lacking.
Methods
We developed a computational approach to detect multi- gene domains with coherent epigenetic patterns. We applied this method to analyse a published ChIP-seq dataset for five different histone modification marks (H3K4me2, H3K4me3, H3K27me3, H3K9me3, H3K36me3) in mouse embryonic stem cells. We first obtained a 5-dimenisinal score for all known genes based on average modification activity in select regions. Then, with hidden Markov models and corresponding algorithms, we were able to determine the most probable domain status of each gene. We find that a three-state hidden Markov model can best describe the data, where the states correspond to active, inactive, and null domains.
Results
This model predicts 339 significantly large multi-gene domains, including known domains such as the olfactory receptor (OR) gene clusters, but also previously uncharacterized domains (Figure 1). We also noted less histone modification variability within each of our domains when compared to randomly selected boundaries. We further validated our predictions against gene expression and Gene Ontology data and found our domains were functionally relevant.
Conclusion
Our method provides a novel approach to analyse large-scale epigenetic patterns. As we continue to apply our method to other cell lines, we will provide important insight into the general structure, organization, and regulation of the mammalian genome.
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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.
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Larson, J., Yuan, G. A hidden Markov model for detecting multi-gene chromatin domains. BMC Bioinformatics 11 (Suppl 10), O5 (2010). https://doi.org/10.1186/1471-2105-11-S10-O5
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DOI: https://doi.org/10.1186/1471-2105-11-S10-O5