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Combinatorial chromatin modification patterns in the human genome revealed by subspace clustering.

Ucar D, Hu Q, Tan K - Nucleic Acids Res. (2011)

Bottom Line: We identify 843 combinatorial patterns that recur at >0.1% of the genome.A total of 19 chromatin modifications are observed in the combinatorial patterns, 10 of which occur in more than half of the patterns.We also identify combinatorial modification signatures for eight classes of functional DNA elements.

View Article: PubMed Central - PubMed

Affiliation: Department of Internal Medicine, University of Iowa, Iowa City, 52242 Iowa, USA.

ABSTRACT
Chromatin modifications, such as post-translational modification of histone proteins and incorporation of histone variants, play an important role in regulating gene expression. Joint analyses of multiple histone modification maps are starting to reveal combinatorial patterns of modifications that are associated with functional DNA elements, providing support to the 'histone code' hypothesis. However, due to the lack of analytical methods, only a small number of chromatin modification patterns have been discovered so far. Here, we introduce a scalable subspace clustering algorithm, coherent and shifted bicluster identification (CoSBI), to exhaustively identify the set of combinatorial modification patterns across a given epigenome. Performance comparisons demonstrate that CoSBI can generate biclusters with higher intra-cluster coherency and biological relevance. We apply our algorithm to a compendium of 39 genome-wide chromatin modification maps in human CD4(+) T cells. We identify 843 combinatorial patterns that recur at >0.1% of the genome. A total of 19 chromatin modifications are observed in the combinatorial patterns, 10 of which occur in more than half of the patterns. We also identify combinatorial modification signatures for eight classes of functional DNA elements. Application of CoSBI to epigenome maps of different cells and developmental stages will aid in understanding how chromatin structure helps regulate gene expression.

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Combinatorial chromatin modifications of promoters associated with highly expressed and silent genes in human T cells. Biclusters associated with highly expressed and silent genes are shown at top right and bottom left, respectively. Each curve represents the cumulative distribution of expression levels of a set of genes whose promoters are associated with chromatin modification biclusters. Gene expression levels in log scale is represented by x-axis and y-axis represents the fraction of genes in the biclusters that are expressed at higher levels than the corresponding x-axis values.
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Figure 6: Combinatorial chromatin modifications of promoters associated with highly expressed and silent genes in human T cells. Biclusters associated with highly expressed and silent genes are shown at top right and bottom left, respectively. Each curve represents the cumulative distribution of expression levels of a set of genes whose promoters are associated with chromatin modification biclusters. Gene expression levels in log scale is represented by x-axis and y-axis represents the fraction of genes in the biclusters that are expressed at higher levels than the corresponding x-axis values.

Mentions: Next we focused on promoter biclusters whose target genes are either highly expressed or silent in human CD4+ T cells based on the gene expression profiles generated by Schones et al. (25). To do so, for each bicluster, we computed the median expression level of all genes associated with the promoters in the bicluster. We then chose top 10 biclusters with highest median expression levels and bottom 10 biclusters with lowest median expression level (see ‘Materials and Methods’ section for details). They were regarded as being associated with highly expressed and silent genes in T cells. By examining the chromatin modification patterns of these two groups of promoters, we made several interesting observations regarding the relationship of gene expression and combinatorial patterns of chromatin modifications at gene promoters. Most strikingly, we observed that silent genes can also be associated with acetylations, despite the fact that acetylation is generally regarded as an activating modification (Figure 6). Previously, activating methylation but not acetylation marks have been observed at the promoters of silent genes poised for activation (39–41). Our finding with acetylation is consistent with the result of a more recent study by Barski et al. (42). By examining genome-wide histone modification profiles and gene expression during CD4+ T-cell activation, Barski et al. found that activating acetylations were already in place for a majority of inducible genes, even though the genes were silent in resting cells. Similarly, genes that were silenced upon T-cell activation retained positive chromatin modifications even after being silenced. Two mechanisms have been proposed by the authors to explain the presence of activating acetylation marks at silent genes: de novo poising of silent genes for future expression or as a memory of past transcription. Additional experiments will be needed to determine if either or both mechanisms are responsible for this phenomenon.Figure 6.


Combinatorial chromatin modification patterns in the human genome revealed by subspace clustering.

Ucar D, Hu Q, Tan K - Nucleic Acids Res. (2011)

Combinatorial chromatin modifications of promoters associated with highly expressed and silent genes in human T cells. Biclusters associated with highly expressed and silent genes are shown at top right and bottom left, respectively. Each curve represents the cumulative distribution of expression levels of a set of genes whose promoters are associated with chromatin modification biclusters. Gene expression levels in log scale is represented by x-axis and y-axis represents the fraction of genes in the biclusters that are expressed at higher levels than the corresponding x-axis values.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3105409&req=5

Figure 6: Combinatorial chromatin modifications of promoters associated with highly expressed and silent genes in human T cells. Biclusters associated with highly expressed and silent genes are shown at top right and bottom left, respectively. Each curve represents the cumulative distribution of expression levels of a set of genes whose promoters are associated with chromatin modification biclusters. Gene expression levels in log scale is represented by x-axis and y-axis represents the fraction of genes in the biclusters that are expressed at higher levels than the corresponding x-axis values.
Mentions: Next we focused on promoter biclusters whose target genes are either highly expressed or silent in human CD4+ T cells based on the gene expression profiles generated by Schones et al. (25). To do so, for each bicluster, we computed the median expression level of all genes associated with the promoters in the bicluster. We then chose top 10 biclusters with highest median expression levels and bottom 10 biclusters with lowest median expression level (see ‘Materials and Methods’ section for details). They were regarded as being associated with highly expressed and silent genes in T cells. By examining the chromatin modification patterns of these two groups of promoters, we made several interesting observations regarding the relationship of gene expression and combinatorial patterns of chromatin modifications at gene promoters. Most strikingly, we observed that silent genes can also be associated with acetylations, despite the fact that acetylation is generally regarded as an activating modification (Figure 6). Previously, activating methylation but not acetylation marks have been observed at the promoters of silent genes poised for activation (39–41). Our finding with acetylation is consistent with the result of a more recent study by Barski et al. (42). By examining genome-wide histone modification profiles and gene expression during CD4+ T-cell activation, Barski et al. found that activating acetylations were already in place for a majority of inducible genes, even though the genes were silent in resting cells. Similarly, genes that were silenced upon T-cell activation retained positive chromatin modifications even after being silenced. Two mechanisms have been proposed by the authors to explain the presence of activating acetylation marks at silent genes: de novo poising of silent genes for future expression or as a memory of past transcription. Additional experiments will be needed to determine if either or both mechanisms are responsible for this phenomenon.Figure 6.

Bottom Line: We identify 843 combinatorial patterns that recur at >0.1% of the genome.A total of 19 chromatin modifications are observed in the combinatorial patterns, 10 of which occur in more than half of the patterns.We also identify combinatorial modification signatures for eight classes of functional DNA elements.

View Article: PubMed Central - PubMed

Affiliation: Department of Internal Medicine, University of Iowa, Iowa City, 52242 Iowa, USA.

ABSTRACT
Chromatin modifications, such as post-translational modification of histone proteins and incorporation of histone variants, play an important role in regulating gene expression. Joint analyses of multiple histone modification maps are starting to reveal combinatorial patterns of modifications that are associated with functional DNA elements, providing support to the 'histone code' hypothesis. However, due to the lack of analytical methods, only a small number of chromatin modification patterns have been discovered so far. Here, we introduce a scalable subspace clustering algorithm, coherent and shifted bicluster identification (CoSBI), to exhaustively identify the set of combinatorial modification patterns across a given epigenome. Performance comparisons demonstrate that CoSBI can generate biclusters with higher intra-cluster coherency and biological relevance. We apply our algorithm to a compendium of 39 genome-wide chromatin modification maps in human CD4(+) T cells. We identify 843 combinatorial patterns that recur at >0.1% of the genome. A total of 19 chromatin modifications are observed in the combinatorial patterns, 10 of which occur in more than half of the patterns. We also identify combinatorial modification signatures for eight classes of functional DNA elements. Application of CoSBI to epigenome maps of different cells and developmental stages will aid in understanding how chromatin structure helps regulate gene expression.

Show MeSH
Related in: MedlinePlus