Integrative annotation of chromatin elements from ENCODE data

By Michael M. Hoffman, Jason Ernst, Steven P. Wilder, Anshul B Kundaje, Robert S. Harris, Maxwell W. Libbrecht, Belinda Giardine, Paul M. Ellenbogen, J. Bilmes, Ewan Birney and 4 more. 2012

456 citations recorded by the source corpus.

The ENCODE Project has generated a wealth of experimental information mapping diverse chromatin properties in several human cell lines. Although each such data track is independently informative toward the annotation of regulatory elements, their interrelations contain much richer information for the systematic annotation of regulatory elements. To uncover these interrelations and to generate an interpretable summary of the massive datasets of the ENCODE Project, we apply unsupervised learning methodologies, converting dozens of chromatin datasets into discrete annotation maps of regulatory regions and other chromatin elements across the human genome. These methods rediscover and summarize diverse aspects of chromatin architecture, elucidate the interplay between chromatin activity and RNA transcription, and reveal that a large proportion of the genome lies in a quiescent state, even across multiple cell types. The resulting annotation of non-coding regulatory elements correlate strongly with mammalian evolutionary constraint, and provide an unbiased approach for evaluating metrics of evolutionary constraint in human. Lastly, we use the regulatory annotations to revisit previously uncharacterized disease-associated loci, resulting in focused, testable hypotheses through the lens of the chromatin landscape.

Subfields: Molecular Biology, Plant Science

Citations in the corpus

• Iterative random forests to discover predictive and stable high-order interactions (2017, neutral): “In well-studied systems, regulatory factors such as TFs act in concert with other chromatin-associated and RNA-associated proteins, often through stereospecific interactions (5, 7); for a review see ref.”
• Joint analysis of functional genomic data and genome-wide association studies of 18 human traits (2013, unknown): “We also included as annotations the output from “genome segmentation” of the six main ENCODE cell lines 40 ; for each section of the genome in each cell line, Hoffman et al. 40 report whether the histone modifications in the region are consistent with enhancer activity, transcription start sites,…”
• GEMINI: Integrative Exploration of Genetic Variation and Genome Annotations (2013, unknown): “Integrating functional genomics annotations from ambitious projects such as ENCODE [9] will thus be”
• A three-dimensional map of the human genome at kilobase resolution reveals principles of chromatin looping (2014, unknown): “First, our peaks frequently have a known promoter at one peak locus (as annotated by ENCODE’s ChromHMM) (Hoffman et al., 2013) and a known enhancer at the other (Figure 5A).”
• Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation (2015, unknown): “Additionally curators use promoter-associated histone modification marks such as H3K4me3 from the NIH Roadmap Epigenomic Mapping Consortium (REMC; (17) and the ENCODE (Encyclopedia of DNA Elements) project (18) to verify the presence of an active promoter.”
• Ensembl regulation resources (2016, unknown): “These measurements can be used to identify regulatory elements (20–22), but also characterise disease (23).”
• DNA methylation aging clocks: challenges and recommendations (2019, unknown): “The size of the circle is proportional to the entire genome space for each functional category (~10(genome size proportion)). e-h Direct overlap comparison for four DNA methylation clocks (Horvath clock, Hannum et al. clock, PhenoAge clock, epiTOC clock) as well as Illumina array CpGs (27k, 450k, EP”
• The Ensembl Regulatory Build (2015, unknown): “Significant efforts to provide genome-wide maps of histone modifications have already proved successful in elucidating some of the basic patterns associated with promoter and enhancer regions [14,15,22,23].”
• Genomic positional conservation identifies topological anchor point (tap)RNAs linked to developmental loci (2016, unknown): “…genome-wide datasets for different human cell lines (ENCODE tier 1 lines: GM12878, H1-hESC, HSMM and K562) (The ENCODE Project Consortium, 2012; Hoffman et al., 2013), we identified a clear enrichment in H3K4 di-and tri-methylation (H3K4me2/3) and H3K9 and H3K27 acetylation (H3K9ac, H3K27ac)…”
• High-throughput functional testing of ENCODE segmentation predictions (2014, unknown): “Thus, Weak Enhancers may have more activity than”
• Stochastic variational inference for hidden Markov models (2014, unknown): “In particular, our SVIHMM runs require only under an hour for a fixed 100 iterations, the maximum iteration limit specified in the DBN-EM approach.”