EPIP: a novel approach for condition-specific enhancer–promoter interaction prediction

Abstract

Motivation The identification of enhancer–promoter interactions (EPIs), especially condition-specific ones, is important for the study of gene transcriptional regulation. Existing experimental approaches for EPI identification are still expensive, and available computational methods either do not consider or have low performance in predicting condition-specific EPIs. Results We developed a novel computational method called EPIP to reliably predict EPIs, especially condition-specific ones. EPIP is capable of predicting interactions in samples with limited data as well as in samples with abundant data. Tested on more than eight cell lines, EPIP reliably identifies EPIs, with an average area under the receiver operating characteristic curve of 0.95 and an average area under the precision–recall curve of 0.73. Tested on condition-specific EPIPs, EPIP correctly identified 99.26% of them. Compared with two recently developed methods, EPIP outperforms them with a better accuracy. Availability and implementation The EPIP tool is freely available at http://www.cs.ucf.edu/˜xiaoman/EPIP/. Supplementary information Supplementary data are available at Bioinformatics online.

An intriguing characteristic of enhancer-promoter interactions

“…Note that the number of IEPs obtained from the above looplists was small, especially when we considered the FANTOM enhancers ( Supplementary Table S1). The reason might be, the criteria Rao et al used to define looplists was quite stringent and many true interacting genomic regions might therefore be missed (48). To capture more IEPs in these cell lines, we also defined alternative sets of IEPs with three cutoffs: 30, 50, and 100, from the normalized Hi-C contact matrices defined by Rao et al (31).…”

“…Given a normalized read cutoff, say x, if an enhancer-promoter pair overlapped with a pair of interacting genomic regions that were supported by at least x normalized Hi-C reads, we considered this EP-pair as an IEP. The cutoff 30 was used since this cutoff was likely to include of almost all known IEPs in K562 and IMR90 from other studies (6,30) without allowing too many false positives (48). The two other cutoffs were used to see how the observed enhancer characteristics may change with more stringent cutoffs.…”

“…To date, these experiments have only been carried out on a few cell lines or cell types. Although computational methods, from the early ones defining the closest genes as target genes, to the later ones considering the correlation of epigenomic signals in enhancers and those in promoters, to the current ones based on more sophisticated approaches (14,18,(33)(34)(35)(36)(37)(38)(39), have shown some success in predicting enhancer target genes, they either do not consider or have low-performance on cell-specific IEP prediction (35,48).…”

Hundreds of motif pairs may facilitate enhancer-promoter interactions

“…With the transcription start sites (TSSs) defined in GENCODE, we defined 57820 promoters, each of which was the genomic region from the upstream 1000 bps to the downstream of 100 bps the TSS of a GENCODE gene. An active promoter was then defined with these GENCODE promoters and the ENCODE RNA-seq data similarly as previously [19,24]. In this way, every positive EP pair had an active enhancer overlapping with one genomic region and an active promoter overlapping with the other genomic region of a positive pair of genomic regions, and the distance between the enhancer and the promoter was within 2.5 kilobase pairs to 2 megabase pairs (Supplementary S1).…”

“…These methods usually consider the distance, conservation, correlated activity between enhancers and promoters, etc., to identify EP interactions [13][14][15][16][17][18][19][20][21][22]. Although having shown success, they have a suboptimal performance on discovering EP interactions, especially condition-specific EP interactions [17,[23][24][25]. It is thus necessary to further investigate the characteristics of EP interactions, which may significantly facilitate the improvement of the accuracy of the existing methods.…”