@article{88558f3463bf4bdca8b02c85e76c4af1,
title = "Global Analysis of Enhancer Targets Reveals Convergent Enhancer-Driven Regulatory Modules",
abstract = "Single-cell screens enable high-throughput functional assessment of enhancers in their endogenous genomic context. However, the design of current studies limits their application to identifying the primary gene targets of enhancers. Here, we improve the experimental and computational parameters of single-cell enhancer screens to identify the secondary gene targets of enhancers. Our analysis of >500 putative enhancers in K562 cells reveals an interwoven enhancer-driven gene regulatory network. We find that enhancers from distinct genomic loci converge to modulate the expression of common sub-modules, including the α- and β-globin loci, by directly regulating transcription factors. Our analysis suggests that several genetic variants associated with myeloid blood cell traits alter the activity of a distal enhancer of MYB (∼140 kb away), with downstream consequences on hemoglobin genes expression and cell state. These data have implications for the understanding of enhancer-associated traits and emphasize the flexibility of controlling transcriptional systems by modifying enhancer activity.",
keywords = "GWAS, enhancer, regulatory network, single-cell screen",
author = "Shiqi Xie and Daniel Armendariz and Pei Zhou and Jialei Duan and Hon, {Gary C.}",
note = "Funding Information: This work is supported by the Cancer Prevention Research Institute of Texas (CPRIT) ( RR140023 and RP190451 to G.C.H.), the NIH ( DP2GM128203 to G.C.H.), the Department of Defense ( PR172060 to G.C.H.), the Welch Foundation ( I-1926-20170325 to G.C.H.), the Burroughs Wellcome Fund ( 1019804 to G.C.H.), the Harold C. Simmons Comprehensive Cancer Center , and the Green Center for Reproductive Biology . The authors also acknowledge University of Texas (UT) Southwestern McDermott Center for providing sequencing service and BioHPC for providing high-performance computing (HPC) and storage resources. Funding Information: This work is supported by the Cancer Prevention Research Institute of Texas (CPRIT) (RR140023 and RP190451 to G.C.H.), the NIH (DP2GM128203 to G.C.H.), the Department of Defense (PR172060 to G.C.H.), the Welch Foundation (I-1926-20170325 to G.C.H.), the Burroughs Wellcome Fund (1019804 to G.C.H.), the Harold C. Simmons Comprehensive Cancer Center, and the Green Center for Reproductive Biology. The authors also acknowledge University of Texas (UT) Southwestern McDermott Center for providing sequencing service and BioHPC for providing high-performance computing (HPC) and storage resources. S.X. and G.C.H. conceived the study. S.X. G.C.H. and D.A. designed the experiments. S.X. D.A. and P.Z. performed the experiments. S.X. performed most of the computational analysis, with help from D.A. and J.D. S.X. and G.C.H. prepared the manuscript. All authors read and approved the manuscript. G.C.H. secured funding to support this project and provided intellectual support for all aspects of the work. The authors declare no competing interests. Publisher Copyright: {\textcopyright} 2019 The Author(s)",
year = "2019",
month = nov,
day = "26",
doi = "10.1016/j.celrep.2019.10.073",
language = "English (US)",
volume = "29",
pages = "2570--2578.e5",
journal = "Cell Reports",
issn = "2211-1247",
publisher = "Cell Press",
number = "9",
}