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Predicting chromatin organization using histone marks.

Huang J, Marco E, Pinello L, Yuan GC - Genome Biol. (2015)

Bottom Line: To aid experimental effort and to understand the determinants of long-range chromatin interactions, we have developed a computational model integrating Hi-C and histone mark ChIP-seq data to predict two important features of chromatin organization: chromatin interaction hubs and topologically associated domain (TAD) boundaries.Cell-type specific histone mark information is required for prediction of chromatin interaction hubs but not for TAD boundaries.Our predictions provide a useful guide for the exploration of chromatin organization.

View Article: PubMed Central - PubMed

Affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA. jhuang@jimmy.harvard.edu.

ABSTRACT
Genome-wide mapping of three dimensional chromatin organization is an important yet technically challenging task. To aid experimental effort and to understand the determinants of long-range chromatin interactions, we have developed a computational model integrating Hi-C and histone mark ChIP-seq data to predict two important features of chromatin organization: chromatin interaction hubs and topologically associated domain (TAD) boundaries. Our model accurately and robustly predicts these features across datasets and cell types. Cell-type specific histone mark information is required for prediction of chromatin interaction hubs but not for TAD boundaries. Our predictions provide a useful guide for the exploration of chromatin organization.

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Overview of chromatin interaction hubs. a Definition of chromatin interaction hubs. Chromatin anchors are ranked based on the frequency of significant interactions and classified into four group: Hubs, Median, Low, None. b DNA sequence of hubs. The average PhastCons conservation score and GC Content ratio (left-y-axis) within chromatin anchors is normalized against the genomic background. TSS proximity (right-y-axis) is represented by the distance to the closest TSS. c Enrichment of the super-enhancers in IMR90 cells. Chromatin anchors in each group are further divided into two subgroups are according the distance to their closest TSS, Proximal (<100 kb) and Distal (> = 100 kb). d Functional enrichment analysis using GREAT. e Enrichment of the SNPs in GWAS catalog. Chromatin anchors in each group are further divided into two subgroups according the distance to their closest TSS, Proximal (<100 kb) and Distal (> = 100 kb)
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Fig1: Overview of chromatin interaction hubs. a Definition of chromatin interaction hubs. Chromatin anchors are ranked based on the frequency of significant interactions and classified into four group: Hubs, Median, Low, None. b DNA sequence of hubs. The average PhastCons conservation score and GC Content ratio (left-y-axis) within chromatin anchors is normalized against the genomic background. TSS proximity (right-y-axis) is represented by the distance to the closest TSS. c Enrichment of the super-enhancers in IMR90 cells. Chromatin anchors in each group are further divided into two subgroups are according the distance to their closest TSS, Proximal (<100 kb) and Distal (> = 100 kb). d Functional enrichment analysis using GREAT. e Enrichment of the SNPs in GWAS catalog. Chromatin anchors in each group are further divided into two subgroups according the distance to their closest TSS, Proximal (<100 kb) and Distal (> = 100 kb)

Mentions: We analyzed a public, high-resolution Hi-C dataset by Jin et al. [11], obtained from IMR90 cells, a human fetal lung fibroblast cell line. In their study, the Hi-C data was normalized by adapting a method previously developed by Yaffe and Tanay [18] to further incorporate normalized distance and fragment size jointly [11]. Then, by applying a peak calling algorithm, Jin et al. identified a total of 1,116,312 statistically significant chromatin interactions among 518,032 chromatin anchors at 5–10 kb resolution by combining multiple consecutive restriction fragments [11]. Based on these significant chromatin interactions, we ranked the chromatin anchors according to interaction frequency and classified them into 4 groups (Fig. 1a and Additional file 1: Figure S1A). The “Hubs” group, containing top 10 % of chromatin anchors; the “None” group (~55 %) contains chromatin anchors without significant interactions; and the rest was divided into two roughly equal-sized groups, named the “Median” group and the “Low” group, respectively.Fig. 1


Predicting chromatin organization using histone marks.

Huang J, Marco E, Pinello L, Yuan GC - Genome Biol. (2015)

Overview of chromatin interaction hubs. a Definition of chromatin interaction hubs. Chromatin anchors are ranked based on the frequency of significant interactions and classified into four group: Hubs, Median, Low, None. b DNA sequence of hubs. The average PhastCons conservation score and GC Content ratio (left-y-axis) within chromatin anchors is normalized against the genomic background. TSS proximity (right-y-axis) is represented by the distance to the closest TSS. c Enrichment of the super-enhancers in IMR90 cells. Chromatin anchors in each group are further divided into two subgroups are according the distance to their closest TSS, Proximal (<100 kb) and Distal (> = 100 kb). d Functional enrichment analysis using GREAT. e Enrichment of the SNPs in GWAS catalog. Chromatin anchors in each group are further divided into two subgroups according the distance to their closest TSS, Proximal (<100 kb) and Distal (> = 100 kb)
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Fig1: Overview of chromatin interaction hubs. a Definition of chromatin interaction hubs. Chromatin anchors are ranked based on the frequency of significant interactions and classified into four group: Hubs, Median, Low, None. b DNA sequence of hubs. The average PhastCons conservation score and GC Content ratio (left-y-axis) within chromatin anchors is normalized against the genomic background. TSS proximity (right-y-axis) is represented by the distance to the closest TSS. c Enrichment of the super-enhancers in IMR90 cells. Chromatin anchors in each group are further divided into two subgroups are according the distance to their closest TSS, Proximal (<100 kb) and Distal (> = 100 kb). d Functional enrichment analysis using GREAT. e Enrichment of the SNPs in GWAS catalog. Chromatin anchors in each group are further divided into two subgroups according the distance to their closest TSS, Proximal (<100 kb) and Distal (> = 100 kb)
Mentions: We analyzed a public, high-resolution Hi-C dataset by Jin et al. [11], obtained from IMR90 cells, a human fetal lung fibroblast cell line. In their study, the Hi-C data was normalized by adapting a method previously developed by Yaffe and Tanay [18] to further incorporate normalized distance and fragment size jointly [11]. Then, by applying a peak calling algorithm, Jin et al. identified a total of 1,116,312 statistically significant chromatin interactions among 518,032 chromatin anchors at 5–10 kb resolution by combining multiple consecutive restriction fragments [11]. Based on these significant chromatin interactions, we ranked the chromatin anchors according to interaction frequency and classified them into 4 groups (Fig. 1a and Additional file 1: Figure S1A). The “Hubs” group, containing top 10 % of chromatin anchors; the “None” group (~55 %) contains chromatin anchors without significant interactions; and the rest was divided into two roughly equal-sized groups, named the “Median” group and the “Low” group, respectively.Fig. 1

Bottom Line: To aid experimental effort and to understand the determinants of long-range chromatin interactions, we have developed a computational model integrating Hi-C and histone mark ChIP-seq data to predict two important features of chromatin organization: chromatin interaction hubs and topologically associated domain (TAD) boundaries.Cell-type specific histone mark information is required for prediction of chromatin interaction hubs but not for TAD boundaries.Our predictions provide a useful guide for the exploration of chromatin organization.

View Article: PubMed Central - PubMed

Affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, 02215, USA. jhuang@jimmy.harvard.edu.

ABSTRACT
Genome-wide mapping of three dimensional chromatin organization is an important yet technically challenging task. To aid experimental effort and to understand the determinants of long-range chromatin interactions, we have developed a computational model integrating Hi-C and histone mark ChIP-seq data to predict two important features of chromatin organization: chromatin interaction hubs and topologically associated domain (TAD) boundaries. Our model accurately and robustly predicts these features across datasets and cell types. Cell-type specific histone mark information is required for prediction of chromatin interaction hubs but not for TAD boundaries. Our predictions provide a useful guide for the exploration of chromatin organization.

Show MeSH