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Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions
The spatial organization of the genome influences cellular function, notably gene regulation. Recent studies have assessed the three-dimensional (3D) co-localization of functional annotations (e.g. centromeres, long terminal repeats) using 3D genome reconstructions from Hi-C (genome-wide chromosome...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4797302/ https://www.ncbi.nlm.nih.gov/pubmed/26869583 http://dx.doi.org/10.1093/nar/gkw070 |
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author | Capurso, Daniel Bengtsson, Henrik Segal, Mark R. |
author_facet | Capurso, Daniel Bengtsson, Henrik Segal, Mark R. |
author_sort | Capurso, Daniel |
collection | PubMed |
description | The spatial organization of the genome influences cellular function, notably gene regulation. Recent studies have assessed the three-dimensional (3D) co-localization of functional annotations (e.g. centromeres, long terminal repeats) using 3D genome reconstructions from Hi-C (genome-wide chromosome conformation capture) data; however, corresponding assessments for continuous functional genomic data (e.g. chromatin immunoprecipitation-sequencing (ChIP-seq) peak height) are lacking. Here, we demonstrate that applying bump hunting via the patient rule induction method (PRIM) to ChIP-seq data superposed on a Saccharomyces cerevisiae 3D genome reconstruction can discover ‘functional 3D hotspots’, regions in 3-space for which the mean ChIP-seq peak height is significantly elevated. For the transcription factor Swi6, the top hotspot by P-value contains MSB2 and ERG11 – known Swi6 target genes on different chromosomes. We verify this finding in a number of ways. First, this top hotspot is relatively stable under PRIM across parameter settings. Second, this hotspot is among the top hotspots by mean outcome identified by an alternative algorithm, k-Nearest Neighbor (k-NN) regression. Third, the distance between MSB2 and ERG11 is smaller than expected (by resampling) in two other 3D reconstructions generated via different normalization and reconstruction algorithms. This analytic approach can discover functional 3D hotspots and potentially reveal novel regulatory interactions. |
format | Online Article Text |
id | pubmed-4797302 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47973022016-03-21 Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions Capurso, Daniel Bengtsson, Henrik Segal, Mark R. Nucleic Acids Res Computational Biology The spatial organization of the genome influences cellular function, notably gene regulation. Recent studies have assessed the three-dimensional (3D) co-localization of functional annotations (e.g. centromeres, long terminal repeats) using 3D genome reconstructions from Hi-C (genome-wide chromosome conformation capture) data; however, corresponding assessments for continuous functional genomic data (e.g. chromatin immunoprecipitation-sequencing (ChIP-seq) peak height) are lacking. Here, we demonstrate that applying bump hunting via the patient rule induction method (PRIM) to ChIP-seq data superposed on a Saccharomyces cerevisiae 3D genome reconstruction can discover ‘functional 3D hotspots’, regions in 3-space for which the mean ChIP-seq peak height is significantly elevated. For the transcription factor Swi6, the top hotspot by P-value contains MSB2 and ERG11 – known Swi6 target genes on different chromosomes. We verify this finding in a number of ways. First, this top hotspot is relatively stable under PRIM across parameter settings. Second, this hotspot is among the top hotspots by mean outcome identified by an alternative algorithm, k-Nearest Neighbor (k-NN) regression. Third, the distance between MSB2 and ERG11 is smaller than expected (by resampling) in two other 3D reconstructions generated via different normalization and reconstruction algorithms. This analytic approach can discover functional 3D hotspots and potentially reveal novel regulatory interactions. Oxford University Press 2016-03-18 2016-02-10 /pmc/articles/PMC4797302/ /pubmed/26869583 http://dx.doi.org/10.1093/nar/gkw070 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ 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@oup.com |
spellingShingle | Computational Biology Capurso, Daniel Bengtsson, Henrik Segal, Mark R. Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions |
title | Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions |
title_full | Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions |
title_fullStr | Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions |
title_full_unstemmed | Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions |
title_short | Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions |
title_sort | discovering hotspots in functional genomic data superposed on 3d chromatin configuration reconstructions |
topic | Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4797302/ https://www.ncbi.nlm.nih.gov/pubmed/26869583 http://dx.doi.org/10.1093/nar/gkw070 |
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