Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay

被引:500
作者
Melnikov, Alexandre [1 ]
Murugan, Anand [2 ]
Zhang, Xiaolan [1 ]
Tesileanu, Tiberiu [2 ,3 ]
Wang, Li [1 ]
Rogov, Peter [1 ]
Feizi, Soheil [1 ,4 ]
Gnirke, Andreas [1 ]
Callan, Curtis G., Jr. [2 ,3 ]
Kinney, Justin B. [5 ]
Kellis, Manolis [1 ,4 ]
Lander, Eric S. [1 ,6 ,7 ]
Mikkelsen, Tarjei S. [1 ,8 ,9 ]
机构
[1] Broad Inst, Cambridge, MA USA
[2] Princeton Univ, Dept Phys, Princeton, NJ 08544 USA
[3] Inst Adv Study, Simons Ctr Syst Biol, Princeton, NJ 08540 USA
[4] MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02139 USA
[5] Cold Spring Harbor Lab, Simons Ctr Quantitat Biol, Cold Spring Harbor, NY 11724 USA
[6] MIT, Dept Biol, Cambridge, MA USA
[7] Harvard Univ, Sch Med, Dept Syst Biol, Boston, MA USA
[8] Harvard Univ, Harvard Stem Cell Inst, Cambridge, MA 02138 USA
[9] Harvard Univ, Dept Stem Cell & Regenerat Biol, Cambridge, MA 02138 USA
基金
美国国家科学基金会;
关键词
NUCLEOTIDE-SEQUENCE; GENE SYNTHESIS; ELEMENTS; DNA; INFORMATION; PROMOTERS; SELECTION; MODEL;
D O I
10.1038/nbt.2137
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 [微生物学]; 090105 [作物生产系统与生态工程];
摘要
Learning 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-beta 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.
引用
收藏
页码:271 / +
页数:9
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