Decoding genome function with DNA methylation and human phenome data
利用 DNA 甲基化和人类表型数据解码基因组功能
基本信息
- 批准号:10501273
- 负责人:
- 金额:$ 39.02万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-08-01 至 2027-05-31
- 项目状态:未结题
- 来源:
- 关键词:Animal ModelAreaBiological AssayBiologyCell Differentiation processCell LineCell physiologyCellsChromatinCompetenceDNA MethylationDNA SequenceDNA methylation profilingDNMT3aDataDisease OutcomeElectronic Health RecordElementsEpigenetic ProcessGene ExpressionGene Expression RegulationGenesGenetic TranscriptionGenetic VariationGenomeGenomic SegmentGenomicsGenotypeHeartHepG2HepatocyteHumanImmuneIndividualLinkLiverMapsMediatingMediator of activation proteinMethylationModelingNeuronsNormal CellOutcomePathologicPatternPhenotypePopulationPrevalenceQuantitative Trait LociRecording of previous eventsRegulationRegulator GenesRegulatory ElementReporterResearchSiteSpecific qualifier valueTestingUntranslated RNAWorkXCL1 genebasecell typeclinical phenotypecomparativedemethylationembryonic stem cellepigenome editinggenetic approachgenetic manipulationgenetic variantgenome wide association studygenome-widehuman population geneticsmacrophagemammalian genomemethylation patternmonocytemultiple omicsnerve stem cellphenomeprogramsrepositorytraittranscription factortranscriptome sequencing
项目摘要
PROJECT SUMMARY
DNA methylation is an essential mediator of genome function. But considering the prevalence and distribution
of sites of methylation across the genome, exactly how DNA methylation drives cellular phenotype is unclear.
Although mammalian genomes are highly methylated, hypomethylated hotspots are scattered throughout non-
coding regions and frequently coincide with open chromatin and other gene regulatory landmarks. DNA
methylation is considered repressive to transcription, and gene regulatory elements are thought to require
demethylation to promote transcription of lineage-specifying genes. Thus, hypomethylated regions (HMRs) of
differentiated cells spotlight regions of past or present transcription factor occupancy, flagging key gene
regulatory elements involved in lineage specification (cell history) or cell-type specific gene regulation. Recent
work from our lab comparing methylation profiles across diverse cell-types demonstrates that HMR patterns are
highly predictive of cellular phenotypes. Moreover, we have discovered that cell-type specific HMRs are enriched
for genetic variants linked to specific clinical phenotypes. Together these data suggest HMRs provide important
contextual information for genome function, and when combined with human trait data, HMRs provide a powerful
means to connect genotypes to phenotypes. The objective of this proposal is to understand the functional
significance of cell-type and lineage specific HMRs and their causal relationship with genes and cellular
phenotypes. We propose that cell-type essential HMRs harbor genetic variants linked to cell-type-related
phenotypes. We further propose that, by understanding this relationship, we will uncover new hypomethylation-
dependent gene regulatory relationships that are critical for normal cell identity and function. We will perform
comparative DNA methylation profiling of diverse cell types to identify cell specific HMRs. To elucidate HMR
function, we will apply an unbiased, cutting-edge genetic approach that uses human population genetics to link
HMR genotypes to human traits recorded in the electronic health record (EHR), the most extensive repository of
phenotypic conditions of any model organism. In parallel we will probe the functional activities of HMR-defined
genomic sequences using a powerful, multi-omic approach developed by our lab to isolate “driver” HMRs in
specific cell contexts. Finally, we will use epigenome editing to understand the importance of hypomethylation
on local genome regulation. This multi-level approach will test the hypothesis that cell-type and lineage specific
HMRs are critical elements bridging genomes to phenomes. Ultimately, these studies will establish a
fundamentally new way to understand how DNA methylation bridges the connection between genomes and
phenomes, revealing important gene regulatory principles that are essential to understanding why epigenetic
instability leads to specific disease outcomes.
项目总结
项目成果
期刊论文数量(0)
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Emily Hodges其他文献
Emily Hodges的其他文献
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{{ truncateString('Emily Hodges', 18)}}的其他基金
Decoding genome function with DNA methylation and human phenome data
利用 DNA 甲基化和人类表型数据解码基因组功能
- 批准号:
10670386 - 财政年份:2022
- 资助金额:
$ 39.02万 - 项目类别:
Dissecting Genetic and Epigenetic variation in the Cancer Regulome
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8679841 - 财政年份:2015
- 资助金额:
$ 39.02万 - 项目类别:
Dissecting Genetic and Epigenetic variation in the Cancer Regulome
剖析癌症调节组中的遗传和表观遗传变异
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8989086 - 财政年份:2015
- 资助金额:
$ 39.02万 - 项目类别:
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