Data for "GOntact: using chromatin contacts to infer target genes and Gene Ontology enrichments for cis-regulatory elements"

This dataset contains processed data used in our article entitled "GOntact: using chromatin contacts to infer target genes and Gene Ontology enrichments for cis-regulatory elements". Supplementary Dataset 1. This dataset contains the main GOntact runs that were analyzed in this manuscript. This includes the inference of CRE target gene relationships for human and mouse ENCODE and Vista enhancers (subfolder “gene_CRE_associations”) and the GO enrichment analyses for Vista enhancers and hCONDELs (subfolder “GO_enrichment”), performed with several sets of parameters. The parameters used in the GOntact runs are provided within each subfolder, in a tabulated file named “GOntact_parameters.txt”. Supplementary Dataset 2. This dataset contains gene-enhancer associations obtained with 4 different approaches: The CRISPRi approach (Gasperini et al, 2019) The activity-by-contact (ABC) approach (Fulco et al, 2019). GOntact, based on PCHi-C contacts. The “regulatory domains” (GREAT) genomic proximity approach. GOntact and GREAT were run on the enhancer sets used by Gasperini et al, 2019 and Fulco et al, 2019. Supplementary Dataset 3. This dataset contains the results of the subsampling analyses that we performed to test the robustness of GOntact with respect to the quantity and quality of PCHi-C data used as an input. Supplementary Dataset 4. This dataset contains gene-enhancer associations and GO enrichment analyses performed with GOntact using Hi-C data from Rao et al, 2014 and Micro-C data from Krietenstein et al, 2020. Article abstract: Cis-regulatory elements (CREs) can be efficiently predicted genome-wide, but identifying their target genes remains challenging. Regulatory interactions between genes and CREs can take place over long genomic distances, often bypassing genes. Inferring CRE targets based on genomic proximity, as traditionally done in genomic studies, can thus be misleading. Thanks to chromosome conformation capture techniques, chromatin contacts between CREs and gene promoters can be assayed at the genome-wide scale, thus permitting more accurate predictions of CRE target genes. Here, we present a standalone computational tool and webserver named GOntact, which infers CRE target genes using chromosome conformation capture data. GOntact can be used to derive Gene Ontology (GO) enrichments for CRE sets, thus providing a basis for functional interpretation. We apply GOntact on enhancers active in several embryonic tissues, using Promoter Capture Hi-C data to infer chromatin contacts between genes and CREs. We show that GOntact predicts functional annotations that are coherent with enhancer activity. Compared to genomic proximity, GOntact predicts consistent but more specific functional annotations. With the increasing availability of high-resolution chromatin contact data, we believe that GOntact can provide better-informed target genes and functional predictions for CREs. GOntact is available at https://gontact.univ-lyon1.fr (webserver) and https://gitlab.in2p3.fr/anamaria.necsulea/GOntact (standalone command-line tool).