High-density microarrays and next-generation sequencing technologies, coupled with the availability of the annotated human genomic sequence, are opening a road toward a comprehensive mapping of molecular epigenetic patterns. It is anticipated that comprehensive mapping and study of epigenetic patterns both """"""""horizontally"""""""" along the genomic sequence and """"""""vertically"""""""" across multiple differentiation and developmental stages and physiological conditions, will provide insights into human development, physiology, and disease. This vision of epigenomics calls both for novel organizational models suitable for high-throughput data-driven science and for innovative networked cyberinfrastructure. This project aims to develop such networked cyberinfrastructure and employ it to integrate and coordinate data analyses and data pipelines involving designated Reference Epigenome Mapping Centers (REMCs), NCBI, and other participants. The infrastructure builds on the now well established Genboree system which was developed in the context of numerous genome projects and has most recently been employed to coordinate the pilot stage of The Cancer Genome Atlas Project. The infrastructure will provide both scalability for further integration of new epigenomic technologies with increasing data production throughputs and adaptability to accommodate an increasing diversity of experimental and computational methodologies. Using the software-as-a-service model, web services, and semantic web technologies, the infrastructure will help integrate and coordinate efforts of REMCs, NCBI, and an increasing number of collaborating institutions and multi-disciplinary groups in the field of epigenomics working across geographic locations.

Public Health Relevance

Epigenomics is the study of heritable or stable changes in human cells that are not coded in the genomic DNA. The role of epigenomic changes in diseases as diverse as obesity, autism, and cancer is coming to light. Importantly, because epigenomic phenomena are affected by nutrition and environment, including maternal nutrition during pregnancy, increased understanding of epigenomics may lead to better health through changes in human nutrition and behavior. To better understand epigenomic phenomena in human health and disease, the NIH Roadmap Initiative in Epigenomics proposes comprehensive mapping and study of epigenomic patterns in human tissues at different developmental stages and physiological conditions. High-density microarrays and next-generation sequencing technologies, coupled with the availability of the annotated human genomic sequence, are opening a road toward a comprehensive mapping of such patterns. The amount and diversity of data produced will be very large and will require an informatic infrastructure for proper analysis. Building on the established Genboree system for collaborative genomic research over the Internet, this project aims to develop such a networked infrastructure, and employ it to integrate and to coordinate data analyses and data pipelines involving designated Reference Epigenome Mapping Centers and other participants in the NIH Roadmap Initiative in Epigenomics.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01DA025956-03
Application #
7900999
Study Section
Special Emphasis Panel (ZRG1-CB-P (50))
Program Officer
Rutter, Joni
Project Start
2008-09-20
Project End
2013-07-31
Budget Start
2010-08-01
Budget End
2011-07-31
Support Year
3
Fiscal Year
2010
Total Cost
$1,350,927
Indirect Cost
Name
Baylor College of Medicine
Department
Genetics
Type
Schools of Medicine
DUNS #
051113330
City
Houston
State
TX
Country
United States
Zip Code
77030
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Dickinson, Mary E; Flenniken, Ann M; Ji, Xiao et al. (2017) Corrigendum: High-throughput discovery of novel developmental phenotypes. Nature 551:398
Kessler, Noah J; Van Baak, Timothy E; Baker, Maria S et al. (2016) CpG methylation differences between neurons and glia are highly conserved from mouse to human. Hum Mol Genet 25:223-32
Onuchic, Vitor; Hartmaier, Ryan J; Boone, David N et al. (2016) Epigenomic Deconvolution of Breast Tumors Reveals Metabolic Coupling between Constituent Cell Types. Cell Rep 17:2075-2086
Roadmap Epigenomics Consortium; Kundaje, Anshul; Meuleman, Wouter et al. (2015) Integrative analysis of 111 reference human epigenomes. Nature 518:317-30
Amin, Viren; Harris, R Alan; Onuchic, Vitor et al. (2015) Epigenomic footprints across 111 reference epigenomes reveal tissue-specific epigenetic regulation of lincRNAs. Nat Commun 6:6370
Coarfa, Cristian; Pichot, Christina; Jackson, Andrew et al. (2014) Analysis of interactions between the epigenome and structural mutability of the genome using Genboree Workbench tools. BMC Bioinformatics 15 Suppl 7:S2
Kunde-Ramamoorthy, Govindarajan; Coarfa, Cristian; Laritsky, Eleonora et al. (2014) Comparison and quantitative verification of mapping algorithms for whole-genome bisulfite sequencing. Nucleic Acids Res 42:e43
Harris, R Alan; Shaw, Chad; Li, Jian et al. (2013) Confounding by repetitive elements and CpG islands does not explain the association between hypomethylation and genomic instability. PLoS Genet 9:e1003333
Li, Jian; Harris, R Alan; Cheung, Sau Wai et al. (2012) Genomic hypomethylation in the human germline associates with selective structural mutability in the human genome. PLoS Genet 8:e1002692

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