RT Journal Article
SR Electronic
T1 Comprehensive enhancer-target gene assignments improve gene set level interpretation of genome-wide regulatory data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.10.22.351049
DO 10.1101/2020.10.22.351049
A1 Tingting Qin
A1 Christopher Lee
A1 Raymond Cavalcante
A1 Peter Orchard
A1 Heming Yao
A1 Hanrui Zhang
A1 Shuze Wang
A1 Snehal Patil
A1 Alan P Boyle
A1 Maureen A Sartor
YR 2020
UL http://biorxiv.org/content/early/2020/10/23/2020.10.22.351049.abstract
AB Revealing the gene targets of distal regulatory elements is challenging yet critical for interpreting regulome data. Experiment-derived enhancer-gene links are restricted to a small set of enhancers and/or cell types, while the accuracy of genome-wide approaches remains elusive due to the lack of a systematic evaluation. We combined multiple spatial and in silico approaches for defining enhancer locations and linking them to their target genes aggregated across >500 cell types, generating 1,860 human genome-wide distal Enhancer to Target gene Definitions (EnTDefs). To evaluate performance, we used gene set enrichment testing on 87 independent ENCODE ChIP-seq datasets of 34 transcription factors (TFs) and assessed concordance of results with known TF Gene Ontology (GO) annotations., assuming that greater concordance with TF-GO annotation signifies better enrichment results and thus more accurate enhancer-to-gene assignments. Notably, the top ranked 741 (40%) EnTDefs significantly outperformed the common, naïve approach of linking distal regions to the nearest genes (FDR < 0.05), and the top 10 ranked EnTDefs performed well when applied to ChIP-seq data of other cell types. These general EnTDefs also showed comparable performance to EnTDefs generated using cell-type-specific data. Our findings illustrate the power of our approach to provide genome-wide interpretation regardless of cell type.Competing Interest StatementThe authors have declared no competing interest.