Perspectives on ENCODE

Abstract

ENCODE 3 (2012-2017) expanded production and added new types of assays 8 (Fig. 1, Extended Data Fig. 1), which revealed landscapes of RNA binding and the 3D organization of chromatin via methods such as chromatin interaction analysis by paired-end tagging (ChIA-PET) and Hi-C chromosome conformation capture. Phases 2 and 3 delivered 9,239 experiments (7,495 in human and 1,744 in mouse) in more than 500 cell types and tissues, including mapping of transcribed regions and transcript isoforms, regions of transcripts recognized by RNA-binding proteins, transcription factor binding regions, and regions that harbour specific histone modifications, open chromatin, and 3D chromatin interactions. The results of all of these experiments are available at the ENCODE portal (http://www.encodeproject.org). These efforts, combined with those of related projects and many other laboratories, have produced a greatly enhanced view of the human genome (Fig. 2), identifying 20,225 protein-coding and 37,595 noncoding genes

Expanded encyclopaedias of DNA elements in the human and mouse genomes

“…Across multiple data types, the increase in the scale of experimental data has provided new insights into genome organization and function, and catalysed new capabilities for deriving biological understandings and principles, as illustrated below and detailed in accompanying papers [7][8][9][10][11][12][13][14][15][16] . In summary, we:…”

GATA factor-regulated solute carrier ensemble reveals a nucleoside transporter-dependent differentiation mechanism

“…Related SLC family members Slc7a12 , Slc22a28 and Slc22a29 lacked ATAC-seq, GATA2 and GATA1 ChIP-seq peaks and served as negative controls ( Fig 4B ). These SLC genes, including Slc29a1 , shared intronic GATA1 and GATA2 occupancy [ 38 ] that overlaps with accessible chromatin identified by our prior ATAC-seq analysis [ 39 ] and candidate cis -regulatory elements (cCREs) [ 41 ], providing evidence for GATA factor-mediated transcriptional regulation through the intronic sequences.…”

Accurate prediction of cis-regulatory modules reveals a prevalent regulatory genome of humans

“…Identification of all functional elements, in particular, CRMs in genomes has been the central task in the postgenomic era, and enormous CRM function-related data have been produced(Gasperini et al, 2020; Snyder et al, 2020). Although great progresses have been made to predict CRMs in the genomes (Fishilevich et al, 2017; Gao & Qian, 2020; Moore et al, 2020; X.…”