Using 3D epigenomic maps of primary olfactory neuronal cells from living individuals to understand gene regulation

Suhn K. Rhie, Shannon Schreiner, Heather Witt, Chris Armoskus, Fides D. Lay, Adrian Camarena, Valeria N. Spitsyna, Yu Guo, Benjamin P. Berman, Oleg V. Evgrafov, James A. Knowles, Peggy J. Farnham*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

35 Scopus citations


As part of PsychENCODE, we developed a three-dimensional (3D) epigenomic map of primary cultured neuronal cells derived from olfactory neuroepithelium (CNON). We mapped topologically associating domains and high-resolution chromatin interactions using Hi-C and identified regulatory elements using chromatin immunoprecipitation and nucleosome positioning assays. Using epigenomic datasets from biopsies of 63 living individuals, we found that epigenetic marks at distal regulatory elements are more variable than marks at proximal regulatory elements. By integrating genotype and metadata, we identified enhancers that have different levels corresponding to differences in genetic variation, gender, smoking, and schizophrenia. Motif searches revealed that many CNON enhancers are bound by neuronal-related transcription factors. Last, we combined 3D epigenomic maps and gene expression profiles to predict enhancer-target gene interactions on a genome-wide scale. This study not only provides a framework for understanding individual epigenetic variation using a primary cell model system but also contributes valuable data resources for epigenomic studies of neuronal epithelium.

Original languageAmerican English
Article numbereaav8550
JournalScience advances
Issue number12
StatePublished - 13 Dec 2018
Externally publishedYes

Bibliographical note

Funding Information:
Data were generated as part of the PsychENCODE Consortium, supported by U01MH103392, U01MH103365, U01MH103346, U01MH103340, U01MH103339, R21MH109956, R21MH105881, R21MH105853, R21MH103877, R21MH102791, R01MH111721, R01MH110928, R01MH110927, R01MH110926, R01MH110921, R01MH110920, R01MH110905, R01MH109715, R01MH109677, R01MH105898, R01MH105898, R01MH094714, and P50MH106934 awarded to S. Akbarian (Icahn School of Medicine at Mount Sinai), G. Crawford (Duke University), S. Dracheva (Icahn School of Medicine at Mount Sinai), P. Farnham (University of Southern California), M. Gerstein (Yale University), D. Geschwind (University of California, Los Angeles), F. Goes (Johns Hopkins University), T. M. Hyde (Lieber Institute for Brain Development), A. Jaffe (Lieber Institute for Brain Development), J. A. Knowles (University of Southern California), C. Liu (SUNY Upstate Medical University), D. Pinto (Icahn School of Medicine at Mount Sinai), P. Roussos (Icahn School of Medicine at Mount Sinai), S. Sanders (University of California, San Francisco), N. Sestan (Yale University), P. Sklar (Icahn School of Medicine at Mount Sinai), M. State (University of California, San Francisco), P. Sullivan (University of North Carolina), F. Vaccarino (Yale University), D. Weinberger (Lieber Institute for Brain Development), S. Weissman (Yale University), K. White (University of Chicago), J. Willsey (University of California, San Francisco), and P. Zandi (Johns Hopkins University). We thank the ENCODE Project Consortium and Roadmap Epigenomics Mapping Consortium for data access, the USC Center for High-Performance Computing (, the UCLA Technology Center for Genomics and Bioinformatics, and Huy Dinh for advice on bioinformatics analysis This work was supported by the following grants from the NIH: NIH U01MH103346A, NIH R01CA136924, NIH K01CA229995, and NIH R01MH086874.

Publisher Copyright:
Copyright © 2018 The Authors, some rights reserved.


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