Motif signatures of transcribed enhancers

Handle URI:
http://hdl.handle.net/10754/625498
Title:
Motif signatures of transcribed enhancers
Authors:
Kleftogiannis, Dimitrios ( 0000-0003-1086-821X ) ; Ashoor, Haitham ( 0000-0003-2527-0317 ) ; Zarokanellos, Nikolaos; Bajic, Vladimir B. ( 0000-0001-5435-4750 )
Abstract:
In mammalian cells, transcribed enhancers (TrEn) play important roles in the initiation of gene expression and maintenance of gene expression levels in spatiotemporal manner. One of the most challenging questions in biology today is how the genomic characteristics of enhancers relate to enhancer activities. This is particularly critical, as several recent studies have linked enhancer sequence motifs to specific functional roles. To date, only a limited number of enhancer sequence characteristics have been investigated, leaving space for exploring the enhancers genomic code in a more systematic way. To address this problem, we developed a novel computational method, TELS, aimed at identifying predictive cell type/tissue specific motif signatures. We used TELS to compile a comprehensive catalog of motif signatures for all known TrEn identified by the FANTOM5 consortium across 112 human primary cells and tissues. Our results confirm that distinct cell type/tissue specific motif signatures characterize TrEn. These signatures allow discriminating successfully a) TrEn from random controls, proxy of non-enhancer activity, and b) cell type/tissue specific TrEn from enhancers expressed and transcribed in different cell types/tissues. TELS codes and datasets are publicly available at http://www.cbrc.kaust.edu.sa/TELS.
KAUST Department:
Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Biological and Environmental Sciences and Engineering (BESE) Division; Red Sea Research Center (RSRC)
Citation:
Kleftogiannis D, Ashoor H, Zarokanellos N, Bajic VB (2017) Motif signatures of transcribed enhancers. Available: http://dx.doi.org/10.1101/188557.
Publisher:
Cold Spring Harbor Laboratory
Issue Date:
14-Sep-2017
DOI:
10.1101/188557
Type:
Working Paper
Sponsors:
The research reported in this manuscript was supported by the base funding grant No. BAS/1/1606-01-01 of the King Abdullah University of Science and Technology (KAUST) to VBB.
Additional Links:
http://www.biorxiv.org/content/early/2017/09/13/188557
Appears in Collections:
Red Sea Research Center (RSRC); Other/General Submission; Computational Bioscience Research Center (CBRC); Biological and Environmental Sciences and Engineering (BESE) Division; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorKleftogiannis, Dimitriosen
dc.contributor.authorAshoor, Haithamen
dc.contributor.authorZarokanellos, Nikolaosen
dc.contributor.authorBajic, Vladimir B.en
dc.date.accessioned2017-09-21T09:25:34Z-
dc.date.available2017-09-21T09:25:34Z-
dc.date.issued2017-09-14en
dc.identifier.citationKleftogiannis D, Ashoor H, Zarokanellos N, Bajic VB (2017) Motif signatures of transcribed enhancers. Available: http://dx.doi.org/10.1101/188557.en
dc.identifier.doi10.1101/188557en
dc.identifier.urihttp://hdl.handle.net/10754/625498-
dc.description.abstractIn mammalian cells, transcribed enhancers (TrEn) play important roles in the initiation of gene expression and maintenance of gene expression levels in spatiotemporal manner. One of the most challenging questions in biology today is how the genomic characteristics of enhancers relate to enhancer activities. This is particularly critical, as several recent studies have linked enhancer sequence motifs to specific functional roles. To date, only a limited number of enhancer sequence characteristics have been investigated, leaving space for exploring the enhancers genomic code in a more systematic way. To address this problem, we developed a novel computational method, TELS, aimed at identifying predictive cell type/tissue specific motif signatures. We used TELS to compile a comprehensive catalog of motif signatures for all known TrEn identified by the FANTOM5 consortium across 112 human primary cells and tissues. Our results confirm that distinct cell type/tissue specific motif signatures characterize TrEn. These signatures allow discriminating successfully a) TrEn from random controls, proxy of non-enhancer activity, and b) cell type/tissue specific TrEn from enhancers expressed and transcribed in different cell types/tissues. TELS codes and datasets are publicly available at http://www.cbrc.kaust.edu.sa/TELS.en
dc.description.sponsorshipThe research reported in this manuscript was supported by the base funding grant No. BAS/1/1606-01-01 of the King Abdullah University of Science and Technology (KAUST) to VBB.en
dc.publisherCold Spring Harbor Laboratoryen
dc.relation.urlhttp://www.biorxiv.org/content/early/2017/09/13/188557en
dc.rightsThe copyright holder for this preprint is the author/funder. It is made available under a CC-BY-NC 4.0 International license.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en
dc.titleMotif signatures of transcribed enhancersen
dc.typeWorking Paperen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
dc.contributor.departmentRed Sea Research Center (RSRC)en
dc.eprint.versionPre-printen
dc.contributor.institutionCentre for Evolution and Cancer, Division of Molecular Pathology, The Institute of Cancer Research (ICR), London, SW7 3R, United Kingdomen
kaust.authorAshoor, Haithamen
kaust.authorZarokanellos, Nikolaosen
kaust.authorBajic, Vladimir B.en
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