Dataset Information

Predicting chromatin organization using histone marks.

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.

SUBMITTER: Huang J

PROVIDER: S-EPMC4549084 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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Predicting chromatin organization using histone marks.

Huang Jialiang J Marco Eugenio E Pinello Luca L Yuan Guo-Cheng GC

Genome biology 20150814

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 feature ...[more]

PMID: 26272203

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Project description:Most oral cancers arise from oral potentially malignant lesions, which show varying grades of dysplasia. Risk of progression increases with increasing grade of dysplasia; however, risk prediction among oral low-grade dysplasia (LGD), that is, mild and moderate dysplasia can be challenging as only 5%-15% transform. Moreover, grading of dysplasia is subjective and varies with the area of the lesion being biopsied. To date, no biomarkers or tools are used clinically to triage oral LGDs. This study uses a combination of DNA ploidy and chromatin organization (CO) scores from cells obtained from lesion brushings to identify oral LGDs at high-risk of progression. A total of 130 lesion brushings from patients with oral LGDs were selected of which 16 (12.3%) lesions progressed to severe dysplasia or cancer. DNA ploidy and CO scores were analyzed from nuclear features measured by our in-house DNA image cytometry (DNA-ICM) system and used to classify brushings into low-risk and high-risk. A total of 57 samples were classified as high-risk of which 13 were progressors. High-risk DNA brushing was significant for progression (P = 0.001) and grade of dysplasia (P = 0.004). Multivariate analysis showed high-risk DNA brushing showed 5.1- to 8-fold increased risk of progression, a stronger predictor than dysplasia grading and lesion clinical features. DNA-ICM can serve as a non-invasive, high-throughput tool to identify high-risk lesions several years before transformation. This will help clinicians focus on such lesions whereas low-risk lesions may be spared from unnecessary biopsies.Prevention Relevance: DNA ploidy and chromatin organization of cells collected from oral potentially malignant lesions (OPMLs) can identify lesions at high-risk of progression several years prior. This non-invasive test would enable clinicians to triage high-risk (OPMLs) for closer follow-up while low-risk lesions can undergo less frequent biopsies reducing burden on healthcare resources.

Dataset Information

Predicting chromatin organization using histone marks.

Publications

Predicting chromatin organization using histone marks.

Similar Datasets

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