Expanded encyclopaedias of DNA elements in the human and mouse genomes
Name
s41586-020-2493-4.pdf
Description
Published version
Size
5.57 MB
Format
Adobe PDF
Checksum (MD5)
847a75a7bba561f3c53c188366419d5d
Author(s)
Moore, Jill E.
Purcaro, Michael J.
Pratt, Henry E.
Epstein, Charles B.
Shoresh, Noam
Adrian, Jessika
Kawli, Trupti
Davis, Carrie A.
Dobin, Alexander
Kaul, Rajinder
Date Issued
July 2020
Journal
Nature
Publisher
Springer Science and Business Media LLC
Citation
Moore, Jill E. et al. "Expanded encyclopaedias of DNA elements in the human and mouse genomes." Nature 583, 7818 (August 2020): 699–710 © 2020 The Author(s)
Version
Final published version
Abstract
The human and mouse genomes contain instructions that specify RNAs and proteins and govern the timing, magnitude, and cellular context of their production. To better delineate these elements, phase III of the Encyclopedia of DNA Elements (ENCODE) Project has expanded analysis of the cell and tissue repertoires of RNA transcription, chromatin structure and modification, DNA methylation, chromatin looping, and occupancy by transcription factors and RNA-binding proteins. Here we summarize these efforts, which have produced 5,992 new experimental datasets, including systematic determinations across mouse fetal development. All data are available through the ENCODE data portal (https://www.encodeproject.org), including phase II ENCODE1 and Roadmap Epigenomics2 data. We have developed a registry of 926,535 human and 339,815 mouse candidate cis-regulatory elements, covering 7.9 and 3.4% of their respective genomes, by integrating selected datatypes associated with gene regulation, and constructed a web-based server (SCREEN; http://screen.encodeproject.org) to provide flexible, user-defined access to this resource. Collectively, the ENCODE data and registry provide an expansive resource for the scientific community to build a better understanding of the organization and function of the human and mouse genomes.
MIT Department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1038/s41586-020-2493-4
