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      Computational characterization of chromatin domain boundary-associated genomic elements

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      Nucleic Acids Research
      Oxford University Press

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          Abstract

          Topologically associated domains (TADs) are 3D genomic structures with high internal interactions that play important roles in genome compaction and gene regulation. Their genomic locations and their association with CCCTC-binding factor (CTCF)-binding sites and transcription start sites (TSSs) were recently reported. However, the relationship between TADs and other genomic elements has not been systematically evaluated. This was addressed in the present study, with a focus on the enrichment of these genomic elements and their ability to predict the TAD boundary region. We found that consensus CTCF-binding sites were strongly associated with TAD boundaries as well as with the transcription factors (TFs) Zinc finger protein (ZNF)143 and Yin Yang (YY)1. TAD boundary-associated genomic elements include DNase I-hypersensitive sites, H3K36 trimethylation, TSSs, RNA polymerase II, and TFs such as Specificity protein 1, ZNF274 and SIX homeobox 5. Computational modeling with these genomic elements suggests that they have distinct roles in TAD boundary formation. We propose a structural model of TAD boundaries based on these findings that provides a basis for studying the mechanism of chromatin structure formation and gene regulation.

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          Most cited references20

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          Three-dimensional disorganization of the cancer genome occurs coincident with long-range genetic and epigenetic alterations

          A three-dimensional chromatin state underpins the structural and functional basis of the genome by bringing regulatory elements and genes into close spatial proximity to ensure proper, cell-type–specific gene expression profiles. Here, we performed Hi-C chromosome conformation capture sequencing to investigate how three-dimensional chromatin organization is disrupted in the context of copy-number variation, long-range epigenetic remodeling, and atypical gene expression programs in prostate cancer. We find that cancer cells retain the ability to segment their genomes into megabase-sized topologically associated domains (TADs); however, these domains are generally smaller due to establishment of additional domain boundaries. Interestingly, a large proportion of the new cancer-specific domain boundaries occur at regions that display copy-number variation. Notably, a common deletion on 17p13.1 in prostate cancer spanning the TP53 tumor suppressor locus results in bifurcation of a single TAD into two distinct smaller TADs. Change in domain structure is also accompanied by novel cancer-specific chromatin interactions within the TADs that are enriched at regulatory elements such as enhancers, promoters, and insulators, and associated with alterations in gene expression. We also show that differential chromatin interactions across regulatory regions occur within long-range epigenetically activated or silenced regions of concordant gene activation or repression in prostate cancer. Finally, we present a novel visualization tool that enables integrated exploration of Hi-C interaction data, the transcriptome, and epigenome. This study provides new insights into the relationship between long-range epigenetic and genomic dysregulation and changes in higher-order chromatin interactions in cancer.
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            The Sp-family of transcription factors.

            G Suske (1999)
            GC-boxes and related motifs are frequently occurring DNA-elements present in many promoters and enhancers. In contrast to other elements it was generally thought that the transcription factor Sp1 is the only factor acting through these motifs. The cloning of paralogous genes of the Sp1 factor uncovered the existence of a small protein family consisting of Sp1, Sp2, Sp3 and Sp4. All four proteins exhibit very similar structural features. They contain a highly conserved DNA-binding domain composed of three zinc fingers close the C-terminus and serine/threonine- and glutamine-rich domains in their N-terminal regions. The high degree of structural conservation between these four proteins suggested that they do exert similar functions. Molecular, genetic and biochemical analyses, however, demonstrated that Sp2, Sp3 and Sp4 are not simply functional equivalents of Sp1. Here, I will summarize and discuss recent advances which have been made towards understanding the mode of action and biological function of individual family members.
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              Scikit-learn: Machine learning in Python

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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                13 October 2017
                23 August 2017
                23 August 2017
                : 45
                : 18
                : 10403-10414
                Affiliations
                Department of Bio and Brain Engineering, KAIST, Daejeon, Republic of Korea
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +82 42 350 4317; Fax: +82 42 350 4310; Email: kds@ 123456kaist.ac.kr
                Article
                gkx738
                10.1093/nar/gkx738
                5737353
                28977568
                c82b133c-81e1-4ac2-ace2-c62c9b99d3bd
                © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 14 August 2017
                : 18 July 2017
                : 03 January 2017
                Page count
                Pages: 12
                Categories
                Computational Biology

                Genetics
                Genetics

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