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dc.contributor.authorMelnikov, Alexandre
dc.contributor.authorMurugan, Anand
dc.contributor.authorZhang, Xiaolan
dc.contributor.authorTesileanu, Tiberiu
dc.contributor.authorWang, Li
dc.contributor.authorRogov, Peter
dc.contributor.authorFeizi-Khankandi, Soheil
dc.contributor.authorGnirke, Andreas
dc.contributor.authorCallan Jr, Curtis G.
dc.contributor.authorKinney, Justin B.
dc.contributor.authorKellis, Manolis
dc.contributor.authorLander, Eric S.
dc.contributor.authorMikkelsen, Tarjei Sigurd, 1978-
dc.date.accessioned2012-10-18T18:32:29Z
dc.date.available2012-10-18T18:32:29Z
dc.date.issued2012-02
dc.date.submitted2011-08
dc.identifier.issn1087-0156
dc.identifier.issn1546-1696
dc.identifier.urihttp://hdl.handle.net/1721.1/74097
dc.description.abstractLearning to read and write the transcriptional regulatory code is of central importance to progress in genetic analysis and engineering. Here we describe a massively parallel reporter assay (MPRA) that facilitates the systematic dissection of transcriptional regulatory elements. In MPRA, microarray-synthesized DNA regulatory elements and unique sequence tags are cloned into plasmids to generate a library of reporter constructs. These constructs are transfected into cells and tag expression is assayed by high-throughput sequencing. We apply MPRA to compare >27,000 variants of two inducible enhancers in human cells: a synthetic cAMP-regulated enhancer and the virus-inducible interferon-β enhancer. We first show that the resulting data define accurate maps of functional transcription factor binding sites in both enhancers at single-nucleotide resolution. We then use the data to train quantitative sequence-activity models (QSAMs) of the two enhancers. We show that QSAMs from two cellular states can be combined to design enhancer variants that optimize potentially conflicting objectives, such as maximizing induced activity while minimizing basal activity.en_US
dc.description.sponsorshipNational Human Genome Research Institute (U.S.) (grant R01HG004037)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) ((NSF) grant PHY-0957573)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (NSF grant PHY-1022140)en_US
dc.description.sponsorshipBroad Instituteen_US
dc.language.isoen_US
dc.publisherNature Publishing Groupen_US
dc.relation.isversionofhttp://dx.doi.org/10.1038/nbt.2137en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourcePMCen_US
dc.titleRapid dissection and model-based optimization of inducible enhancers in human cells using a massively parallel reporter assayen_US
dc.typeArticleen_US
dc.identifier.citationMelnikov, Alexandre et al. “Systematic Dissection and Optimization of Inducible Enhancers in Human Cells Using a Massively Parallel Reporter Assay.” Nature Biotechnology 30.3 (2012): 271–277. Web.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biologyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorLander, Eric S.
dc.contributor.mitauthorKellis, Manolis
dc.contributor.mitauthorFeizi-Khankandi, Soheil
dc.relation.journalNature Biotechnologyen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsMelnikov, Alexandre; Murugan, Anand; Zhang, Xiaolan; Tesileanu, Tiberiu; Wang, Li; Rogov, Peter; Feizi, Soheil; Gnirke, Andreas; Callan, Curtis G; Kinney, Justin B; Kellis, Manolis; Lander, Eric S; Mikkelsen, Tarjei Sen
dc.identifier.orcidhttps://orcid.org/0000-0002-0964-0616
dspace.mitauthor.errortrue
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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