title: High-throughput mapping of regulatory DNA.
abstract: Quantifying the effects of cis-regulatory DNA on gene expression is a major challenge. Here, we present the multiplexed editing regulatory assay (MERA), a high-throughput CRISPR-Cas9-based approach that analyzes the functional impact of the regulatory genome in its native context. MERA tiles thousands of mutations across ∼40 kb of cis-regulatory genomic space and uses knock-in green fluorescent protein (GFP) reporters to read out gene activity. Using this approach, we obtain quantitative information on the contribution of cis-regulatory regions to gene expression. We identify proximal and distal regulatory elements necessary for expression of four embryonic stem cell-specific genes. We show a consistent contribution of neighboring gene promoters to gene expression and identify unmarked regulatory elements (UREs) that control gene expression but do not have typical enhancer epigenetic or chromatin features. We compare thousands of functional and nonfunctional genotypes at a genomic location and identify the base pair-resolution functional motifs of regulatory elements.
authors.affiliation: Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
authors.forename: Nisha
authors.initials: N
authors.lastname: Rajagopal
authors.affiliation: Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.|Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Sharanya
authors.initials: S
authors.lastname: Srinivasan
authors.affiliation: Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.|Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, USA.
authors.forename: Kameron
authors.initials: K
authors.lastname: Kooshesh
authors.affiliation: Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
authors.forename: Yuchun
authors.identifier: http://orcid.org/0000-0003-2357-1546
authors.initials: Y
authors.lastname: Guo
authors.affiliation: Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
authors.forename: Matthew D
authors.initials: MD
authors.lastname: Edwards
authors.affiliation: Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Budhaditya
authors.initials: B
authors.lastname: Banerjee
authors.affiliation: Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
authors.forename: Tahin
authors.initials: T
authors.lastname: Syed
authors.affiliation: Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.|Program in Cancer, Stem Cells, and Developmental Biology, University of Utrecht, Utrecht, the Netherlands.
authors.forename: Bart J M
authors.initials: BJ
authors.lastname: Emons
authors.affiliation: Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
authors.forename: David K
authors.initials: DK
authors.lastname: Gifford
authors.affiliation: Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Richard I
authors.initials: RI
authors.lastname: Sherwood
mesh_terms: D000818:Animals; D064113:CRISPR-Cas Systems / Q000235:genetics*; D002874:Chromosome Mapping / Q000379:methods*; D005786:Gene Expression Regulation; D023281:Genomics / Q000379:methods*; D051379:Mice; D050436:Regulatory Elements, Transcriptional / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*