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Linking cis-regulatory regions using transcription factor binding signatures Kang, Yueming (Michelle)
Abstract
Linking cooperatively functioning cis-regulatory elements (CREs), specifically enhancers and promoters, is a challenging task. Current strategies include correlation of expression of RNA transcribed from the CREs, experimentally measured chromatin interactions (Promoter Capture Hi-C) or machine learning based computational predictions. However, all three approaches require the availability of experimental data, which is sparse for most cells and tissues. We propose a new similarity metric to link enhancers to their target promoters based on transcription factor (TF)-binding “signatures”. TF-binding signatures are binary string representations (e.g. 0011001...), where each position indicates binding (“1”) or not (“0”) of a TF to a CRE. We apply a cosine similarity metric to enhancer-promoter pairs linked in published studies involving CRISPRi-FlowFISH, co-expression (FANTOM), or experimental tiling-deletion (CREST-seq). We find a significant difference between TF signature similarities of linked promoter-enhancer pairs compared to unlinked pairs. Furthermore we observe that TF-binding similarity scores are CRR specific. Based on the results, new directions are proposed that may allow further improvement towards a reliable mapping of interacting CREs across the genome.
Item Metadata
Title |
Linking cis-regulatory regions using transcription factor binding signatures
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2020
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Description |
Linking cooperatively functioning cis-regulatory elements (CREs), specifically enhancers and promoters, is a challenging task. Current strategies include correlation of expression of RNA transcribed from the CREs, experimentally measured chromatin interactions (Promoter Capture Hi-C) or machine learning based computational predictions. However, all three approaches require the availability of experimental data, which is sparse for most cells and tissues. We propose a new similarity metric to link enhancers to their target promoters based on transcription factor (TF)-binding “signatures”. TF-binding signatures are binary string representations (e.g. 0011001...), where each position indicates binding (“1”) or not (“0”) of a TF to a CRE. We apply a cosine similarity metric to enhancer-promoter pairs linked in published studies involving CRISPRi-FlowFISH, co-expression (FANTOM), or experimental tiling-deletion (CREST-seq). We find a significant difference between TF signature similarities of linked promoter-enhancer pairs compared to unlinked pairs. Furthermore we observe that TF-binding similarity scores are CRR specific. Based on the results, new directions are proposed that may allow further improvement towards a reliable mapping of interacting CREs across the genome.
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Genre | |
Type | |
Language |
eng
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Date Available |
2020-06-26
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0392001
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2020-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International