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|a Goggin, Sarah M.
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|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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|a Massachusetts Institute of Technology. Department of Biology
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|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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|a Wang, Xinchen
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|a He, Liang
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|a Claussnitzer, MelinaChristine
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|a Kellis, Manolis
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|a Saadat, Alham
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|a Wang, Li
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|a Sinnott-Armstrong, Nasa
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|a Wang, Xinchen
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|a He, Liang
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|a Kellis, Manolis
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|a Claussnitzer, Melina
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|a High-resolution genome-wide functional dissection of transcriptional regulatory regions and nucleotides in human
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|b Nature Publishing Group,
|c 2019-03-26T15:50:59Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/121106
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|a Genome-wide epigenomic maps have revealed millions of putative enhancers and promoters, but experimental validation of their function and high-resolution dissection of their driver nucleotides remain limited. Here, we present HiDRA (High-resolution Dissection of Regulatory Activity), a combined experimental and computational method for high-resolution genome-wide testing and dissection of putative regulatory regions. We test ~7 million accessible DNA fragments in a single experiment, by coupling accessible chromatin extraction with self-transcribing episomal reporters (ATAC-STARR-seq). By design, fragments are highly overlapping in densely-sampled accessible regions, enabling us to pinpoint driver regulatory nucleotides by exploiting differences in activity between partially-overlapping fragments using a machine learning model (SHARPR-RE). In GM12878 lymphoblastoid cells, we find ~65,000 regions showing enhancer function, and pinpoint ~13,000 high-resolution driver elements. These are enriched for regulatory motifs, evolutionarily-conserved nucleotides, and disease-associated genetic variants from genome-wide association studies. Overall, HiDRA provides a high-throughput, high-resolution approach for dissecting regulatory regions and driver nucleotides.
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|a National Institutes of Health (U.S.) (R01 HG008155)
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|a Broad NextGen Award
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|a National Institutes of Health (U.S.) (R01 GM113708)
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|a National Institutes of Health (U.S.) (U01 HG007610)
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|a Article
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|t Nature Communications
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