An integrated encyclopedia of DNA elements in the human genome

Histones regulate gene expression both positively and negatively.

“Histones regulate gene expression both positively and negatively.108”

Not all distal conserved elements are detectably enhancers, and far more of the gene-distal non-coding genome is annotated as a regulatory element than is conserved.

“Not all distal conserved elements are detectably enhancers39 and far more of the gene-distal non-coding genome is annotated as a regulatory element than is conserved60,104.”

Through projects such as ENCODE, these annotations underlie the classification of over one million candidate regulatory elements in the human genome as potential enhancers in one or more cell types.

“Through projects such as ENCODE, these annotations underlie the classification of over one million candidate regulatory elements in the human genome as potential enhancers in one or more cell types60,64.”

The number of enhancers in the human genome ranges from 400,000 to 1,000,000 according to recent estimates.

“According to recent estimates, the number of enhancers in the human genome ranges from 400,000 to 1,000,000 [22,23].”

DNase-seq and ChIP-seq from ENCODE and the Epigenomics Roadmap and pseudo-bulk single-cell ATAC-seq from CATlas focus the model towards distal regulatory elements.

“as well as DNase-seq and ChIP–seq from ENCODE and the Epigenomics Roadmap31,99 and pseudo-bulk single-cell ATAC–seq data from CATlas100,101, which focuses the model towards distal regulatory elements.”

Human TBX3 protein binds to E2F7 and E2F8 enhancers.

“Analysis of ChIP-Seq data from the ENCODE database (GSE105374) (33, 34) showed that human TBX3 protein also binds to E2F7 and E2F8 enhancers (SI Appendix, Fig. S3C)”

With the exception of genetic profile, omic profiles such as transcriptome, epigenome, proteome and metabolome differ across tissues and cell types.

“Except for genetic profile being identical across tissues and cell types, all other omic profiles (e.g. transcriptome, epigenome, proteome and metabolome) vary across tissues and cell types.”

Consortia studies have shown that omic profiles have distinct patterns across tissues and cell types.

“On the contrary, consortia studies have demonstrated distinct patterns of omic profiles across tissues and cell types (Bernstein et al., 2012; Roadmap Epigenomics et al., 2015).”

ENCODE and Roadmap Epigenomics have generated maps of histone modifications, transcription-factor binding, chromatin accessibility, three-dimensional genome structure and other regulatory annotations across hundreds of cell types and tissues.

“For example, the ENCODE and Roadmap Epigenomics projects have generated maps of histone modifications, transcription-factor binding, chromatin accessibility, three-dimensional genome structure and other regulatory annotations across hundreds of cell types and tissues107,108.”

GTEx has associated many noncoding variants with expression quantitative-trait loci.

“the Genotype-Tissue Expression (GTEx) project has associated many noncoding variants with expression quantitative-trait loci (eQTLs)”

ENCODE and Roadmap Epigenomics identified noncoding regions acting as enhancers and promoters.

“the ENCODE and Roadmap Epigenomics (Roadmap) projects have identified noncoding regions acting as enhancers and promoters (8–10).”

Consortium efforts have mapped transcriptomic, epigenomic, and proteomic landscapes in the brain.

“Collaborative and consortium-level efforts have made substantial progress by mapping transcriptomic, epigenomic and proteomic landscapes in the brain8–10.”

The increasing availability of large relevant public data sets now permits evaluation of network modules for complex regulatory relationships by combining network edges from statistical associations, time-series data, physical binding and computational predictions.

“The increasing availability of large amounts of relevant data sets within the public domain10,14 now permits the evaluation of network modules for complex regulatory relationships by combining network edges from statistical associations, time-series data, physical binding and computational predictions (FIG. 2b).”

Hidden covariates were derived for use in eQTL analyses and included in the normalization and adjustment steps.

“Next, hidden covariates were derived (for use in eQTL analyses only, as is common practice13). These covariates were then included for adjustment in the normalization and adjustment steps.”

There were 8,427 eGenes at FDR ≤ 5%, or 18 eGenes discovered per sample, consistent with a prediction from GTEx.

“There were 8,427 eGenes at FDR ≤ 5%, or 18 eGenes discovered per sample, consistent with a prediction from GTEx.”

There is an enrichment of epigenetic marks for active enhancers at the rs2238574-containing region in human CD14+ monocytes.

“We observed an enrichment of epigenetic marks for active enhancers at rs2238574-containing region in human CD14+ monocytes (Supplementary Fig. 3A).”

Bioinformatic annotation suggested that the 19p13.3 risk locus contains regulatory elements and that the risk variant(s) might confer disease susceptibility by modulating expression of target genes.

“Notably, these data suggested the presence of regulatory elements at the identified loci, and therefore the risk variant(s) might confer disease susceptibility by modulating the expression of target genes.”

ENCODE defines and annotates functional elements in human and mouse genomes using multi-omics sequencing.

“The Encyclopedia of DNA Elements (ENCODE) project consortium was piloted in 2003 and has since scaled up to define and annotate functional elements in both human and mouse genomes using multi-omics sequencing148.”