Sign in
GenomicsNature Communications
Peer-reviewed journal article

Population-scale study of eRNA transcription reveals bipartite functional enhancer architecture

Katla KristjánsdóttiriD, Yeonui KwakiD, Nathaniel D. TippensiD, John T. LisiD, Hyun Min KangiD, Hojoong KwakiD

Abstract

Enhancer RNAs (eRNA) are non-coding RNAs transcribed bidirectionally from active regulatory sequences. Their expression levels correlate with the activating potentials of the enhancers, but due to their instability, eRNAs have proven difficult to quantify in large scale. To overcome this, we use capped-nascent-RNA sequencing to efficiently capture the bidirectional initiation of eRNAs. We apply this in large scale to the human lymphoblastoid cell lines from the Yoruban population, and detected nearly 75,000 eRNA transcription sites with high sensitivity and specificity. We identify genetic variants significantly associated with overall eRNA initiation levels, as well as the transcription directionality between the two divergent eRNA pairs, namely the transcription initiation and directional initiation quantitative trait loci (tiQTLs and diQTLs) respectively. High-resolution analyses of these two types of eRNA QTLs reveal distinct positions of enrichment not only at the central transcription factor (TF) binding regions but also at the flanking eRNA initiation regions, both of which are equivalently associated with mRNA expression QTLs. These two regions - the central TF binding footprint and the eRNA initiation cores - define the bipartite architecture and the function of enhancers, and may provide further insights into interpreting the significance of non-coding regulatory variants.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
66
FWCI
2.19
Field percentile
top 11%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISMau '26Gil '18Yip '24Sakaue '26Chen '24Benova '26
67% semantic matchDevelopmental Biology
Christine Mau, Benjamin Schmid, Ezzat El‐Sherif·G3 Genes Genomes Genetics·Jun 19, 2026