Genome-scale high-resolution mapping of activating and repressive nucleotides in regulatory regions
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Author(s)
Ernst, Jason
Melnikov, Alexandre
Zhang, Xiaolan
Wang, Li
Rogov, Peter L
Mikkelsen, Tarjei
Kellis, Manolis
Date Issued
October 2016
Journal
Nature Biotechnology
Publisher
Nature Publishing Group
Citation
Ernst, Jason, et al. “Genome-Scale High-Resolution Mapping of Activating and Repressive Nucleotides in Regulatory Regions.” Nature Biotechnology 34, 11 (October 2016): 1180–1190 © 2016 Nature America, Inc
Version
Author's final manuscript
Abstract
Massively parallel reporter assays (MPRAs) enable nucleotide-resolution dissection of transcriptional regulatory regions, such as enhancers, but only few regions at a time. Here we present a combined experimental and computational approach, Systematic high-resolution activation and repression profiling with reporter tiling using MPRA (Sharpr-MPRA), that allows high-resolution analysis of thousands of regions simultaneously. Sharpr-MPRA combines dense tiling of overlapping MPRA constructs with a probabilistic graphical model to recognize functional regulatory nucleotides, and to distinguish activating and repressive nucleotides, using their inferred contribution to reporter gene expression. We used Sharpr-MPRA to test 4.6 million nucleotides spanning 15,000 putative regulatory regions tiled at 5-nucleotide resolution in two human cell types. Our results recovered known cell-type-specific regulatory motifs and evolutionarily conserved nucleotides, and distinguished known activating and repressive motifs. Our results also showed that endogenous chromatin state and DNA accessibility are both predictive of regulatory function in reporter assays, identified retroviral elements with activating roles, and uncovered 'attenuator' motifs with repressive roles in active chromatin.
MIT Department
Broad Institute of MIT and Harvard
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1038/nbt.3678
