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Systematic chromatin state comparison of epigenomes associated with diverse properties including sex and tissue type.

Yen A, Kellis M - Nat Commun (2015)

Bottom Line: By applying ChromDiff to the 127 epigenomes from the Roadmap Epigenomics and ENCODE projects, we provide novel group-wise comparative analyses across sex, tissue type, state and developmental age.Remarkably, we find that distinct sets of epigenomic features are maximally discriminative for different group-wise comparisons, in each case revealing distinct enriched pathways, many of which do not show gene expression differences.Our methodology should be broadly applicable for epigenomic comparisons and provides a powerful new tool for studying chromatin state differences at the genome scale.

View Article: PubMed Central - PubMed

Affiliation: 1] Electrical Engineering and Computer Science Department, Computer Science and Artificial Intelligence Laboratory, MIT, 32 Vassar Street, 32D-524, Cambridge, Massachusetts 02139, USA [2] Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.

ABSTRACT
Epigenomic data sets provide critical information about the dynamic role of chromatin states in gene regulation, but a key question of how chromatin state segmentations vary under different conditions across the genome has remained unaddressed. Here we present ChromDiff, a group-wise chromatin state comparison method that generates an information-theoretic representation of epigenomes and corrects for external covariate factors to better isolate relevant chromatin state changes. By applying ChromDiff to the 127 epigenomes from the Roadmap Epigenomics and ENCODE projects, we provide novel group-wise comparative analyses across sex, tissue type, state and developmental age. Remarkably, we find that distinct sets of epigenomic features are maximally discriminative for different group-wise comparisons, in each case revealing distinct enriched pathways, many of which do not show gene expression differences. Our methodology should be broadly applicable for epigenomic comparisons and provides a powerful new tool for studying chromatin state differences at the genome scale.

No MeSH data available.


Related in: MedlinePlus

X chromsome inactivation distinguishes male and female samples.Comparison of male and female epigenomes identifies (a) 536 distinguishing features that are associated with 369 genes and all 15 chromatin states, where (b) 264 of the 369 genes are located on the X chromosome. (c) 124 of the identified X chromsome genes are mainly quiescent in male samples but weakly repressed or heterochromatic in female cell types (mostly in cluster B), while 56 genes are transcribed in female and male samples (mostly autosomal genes in cluster A), shown here by the most abundant chromatin state for these genes. (d) Expression data for these genes (when available) confirm similar expression levels between male and female samples, as suggested by the chromatin state annotations.
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f2: X chromsome inactivation distinguishes male and female samples.Comparison of male and female epigenomes identifies (a) 536 distinguishing features that are associated with 369 genes and all 15 chromatin states, where (b) 264 of the 369 genes are located on the X chromosome. (c) 124 of the identified X chromsome genes are mainly quiescent in male samples but weakly repressed or heterochromatic in female cell types (mostly in cluster B), while 56 genes are transcribed in female and male samples (mostly autosomal genes in cluster A), shown here by the most abundant chromatin state for these genes. (d) Expression data for these genes (when available) confirm similar expression levels between male and female samples, as suggested by the chromatin state annotations.

Mentions: In our first comparison, we sought epigenomic differences between male and female samples. We found 536 significant epigenomic features (gene–chromatin state combinations) distinguishing male from female samples, which we will call ‘distinguishing features'; these features correspond to 369 genes (that we will refer to as ‘distinguishing genes') and encompass all 15 chromatin states (Fig. 2a). Most distinguishing genes are only associated with 1 feature (only a single chromatin state is significantly different), with the exception of 133 genes that exhibit significant differences in multiple chromatin states, mostly quiescent and weak Polycomb repression (114 of 133 genes) (Fig. 2a).


Systematic chromatin state comparison of epigenomes associated with diverse properties including sex and tissue type.

Yen A, Kellis M - Nat Commun (2015)

X chromsome inactivation distinguishes male and female samples.Comparison of male and female epigenomes identifies (a) 536 distinguishing features that are associated with 369 genes and all 15 chromatin states, where (b) 264 of the 369 genes are located on the X chromosome. (c) 124 of the identified X chromsome genes are mainly quiescent in male samples but weakly repressed or heterochromatic in female cell types (mostly in cluster B), while 56 genes are transcribed in female and male samples (mostly autosomal genes in cluster A), shown here by the most abundant chromatin state for these genes. (d) Expression data for these genes (when available) confirm similar expression levels between male and female samples, as suggested by the chromatin state annotations.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4557131&req=5

f2: X chromsome inactivation distinguishes male and female samples.Comparison of male and female epigenomes identifies (a) 536 distinguishing features that are associated with 369 genes and all 15 chromatin states, where (b) 264 of the 369 genes are located on the X chromosome. (c) 124 of the identified X chromsome genes are mainly quiescent in male samples but weakly repressed or heterochromatic in female cell types (mostly in cluster B), while 56 genes are transcribed in female and male samples (mostly autosomal genes in cluster A), shown here by the most abundant chromatin state for these genes. (d) Expression data for these genes (when available) confirm similar expression levels between male and female samples, as suggested by the chromatin state annotations.
Mentions: In our first comparison, we sought epigenomic differences between male and female samples. We found 536 significant epigenomic features (gene–chromatin state combinations) distinguishing male from female samples, which we will call ‘distinguishing features'; these features correspond to 369 genes (that we will refer to as ‘distinguishing genes') and encompass all 15 chromatin states (Fig. 2a). Most distinguishing genes are only associated with 1 feature (only a single chromatin state is significantly different), with the exception of 133 genes that exhibit significant differences in multiple chromatin states, mostly quiescent and weak Polycomb repression (114 of 133 genes) (Fig. 2a).

Bottom Line: By applying ChromDiff to the 127 epigenomes from the Roadmap Epigenomics and ENCODE projects, we provide novel group-wise comparative analyses across sex, tissue type, state and developmental age.Remarkably, we find that distinct sets of epigenomic features are maximally discriminative for different group-wise comparisons, in each case revealing distinct enriched pathways, many of which do not show gene expression differences.Our methodology should be broadly applicable for epigenomic comparisons and provides a powerful new tool for studying chromatin state differences at the genome scale.

View Article: PubMed Central - PubMed

Affiliation: 1] Electrical Engineering and Computer Science Department, Computer Science and Artificial Intelligence Laboratory, MIT, 32 Vassar Street, 32D-524, Cambridge, Massachusetts 02139, USA [2] Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.

ABSTRACT
Epigenomic data sets provide critical information about the dynamic role of chromatin states in gene regulation, but a key question of how chromatin state segmentations vary under different conditions across the genome has remained unaddressed. Here we present ChromDiff, a group-wise chromatin state comparison method that generates an information-theoretic representation of epigenomes and corrects for external covariate factors to better isolate relevant chromatin state changes. By applying ChromDiff to the 127 epigenomes from the Roadmap Epigenomics and ENCODE projects, we provide novel group-wise comparative analyses across sex, tissue type, state and developmental age. Remarkably, we find that distinct sets of epigenomic features are maximally discriminative for different group-wise comparisons, in each case revealing distinct enriched pathways, many of which do not show gene expression differences. Our methodology should be broadly applicable for epigenomic comparisons and provides a powerful new tool for studying chromatin state differences at the genome scale.

No MeSH data available.


Related in: MedlinePlus