Year: 2014
Type: article
Abstract: Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology.
Source: PLoS Computational Biology
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,043
Funders: Pharmaceutical Research and Manufacturers of America Foundation, Vanderbilt University, Gladstone Institutes, National Institutes of Health, National Heart, Lung, and Blood Institute, National Human Genome Research Institute, National Institute of General Medical Sciences, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Neurological Disorders and Stroke, Eunice Kennedy Shriver National Institute of Child Health and Human Development
Awards: Characterization of regulatory elements leading to human limb malformations, Massively parallel, in vivo functional testing of regulatory elements, G187421119, G2296020787, What Made Us Human?, G3924846397, Characterization of neuronal gene regulatory elements associated with epilepsy, Pharmacogenomics of Membrane Transporters, Identification & functional characterization of SIM1 obesity-associated variants, The Epigenetic Landscape of Heart Development, BMI Bioinformatics Training Grant, NHLBI Pediatric Translational Consortium Administrative Coordinating Center, G677866292, G684752435, G7194235675, The Epigenetic Landscape of Heart Development, G7988530101, Pharmacogenetics of Membrane Transporters, Computational & Functional Annotation of the Zebrafish Genome Regulatory Toolbox, G8993181860, G9000267065, G9000321334, G940641476
OpenAlex ID: W1998306196