GREAT improves functional interpretation of cis-regulatory regions

Abstract

We developed the Genomic Regions Enrichment of Annotations Tool (GREAT) to analyze the functional significance of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. Applying GREAT to data sets from chromatin immunoprecipitation coupled with massively parallel sequencing (ChIP-seq) of multiple transcription-associated factors, including SRF, NRSF, GABP, Stat3 and p300 in different developmental contexts, we recover many functions of these factors that are missed by existing gene-based tools, and we generate testable hypotheses. The utility of GREAT is not limited to ChIP-seq, as it could also be applied to open chromatin, localized epigenomic markers and similar functional data sets, as well as comparative genomics sets.

Changes at the nuclear lamina alter binding of pioneer factor Foxa2 in aged liver

“…Although a large fraction of regions is bound by lamin B1 at both ages, a third of lamin B1‐associated regions are bound exclusively at each age. Binding sites were mapped to nearby genes using GREAT (McLean et al., 2010). Majority of regions were located distally, 5 to 500 kb from the transcription start site (TSS) in both conditions (Figure 1e).…”

“…Binding sites were mapped to 2,293 nearby genes using GREAT (McLean et al., 2010) and compared to gene expression profile of Zmpste24 mutants (Osorio et al., 2010). We identified 814 direct targets (fold change >2), while expression of 118 genes near a Foxa2 site decreased (fold change <−2).…”

“…Next, we mapped 4,434 Foxa2‐binding sites to closest genes using GREAT Chip‐Seq analysis tool (McLean et al., 2010) and computed an overlap with RNA‐Seq data set of differentially regulated genes in old livers from our previous study (Bochkis et al., 2014). Three hundred seventy‐five such genes were analyzed for enrichment using EnrichR, a collection of distinct gene set libraries (Kuleshov et al., 2016) (Figure S2).…”

“…ChIP‐Seq peaks were associated with closest genes with the GREAT analysis (parameters: single closest gene, 10,000 kb) (McLean et al., 2010). Overlap between different categories of binding sites was computed using Galaxy genome analysis tools (Hillman‐Jackson, Clements, Blankenberg, Taylor & Nekrutenko, 2012).…”

Exposure to the widely used herbicide atrazine results in deregulation of global tissue-specific RNA transcription in the third generation and is associated with a global decrease of histone trimethylation in mice

“…These data suggest that the altered activities of histone modifying enzymes in the F3 generation may contribute to the global changes in H3K4me3 mark occupancy. To investigate the genomic context of regions with altered H3K4me3 occupancy, we inspected the genes located in the vicinity of differential peaks using GREAT, v3.0.0 (66). We found changes in H3K4me3 occupancy at 722 genes in F3 ATZ-lineage males, which are specifically enriched in gene clusters corresponding to several cellular functions (Table 1).…”