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VISION: ValIdated Systematic IntegratiON of epigenomic data

愿景：经过验证的表观基因组数据的系统整合

基本信息

批准号：
9976999
负责人：
DAVID M. BODINE
金额：
$ 118.35万
依托单位：
PENNSYLVANIA STATE UNIVERSITY, THE
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-07-18 至 2022-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9976999
关键词：
3-Dimensional Address Area Back Base Sequence Basic Science Binding Proteins Biology CISH gene Catalogs Categories Cells Chromatin Chromosomes Clinical Research Collaborations Communities Custom DNA DNA Sequence Data Data Set Databases Development Disease Elements Engineering Epigenetic Process Erythroid Cells Evolution Frequencies Gene Expression Gene Expression Regulation Genetic Genetic Transcription Genome Health Heart Hematopoiesis Hematopoietic Hematopoietic stem cells Human Human Resources Knock-out Lead Learning Machine Learning Maps Measurement Methods Modeling Modification Monitor Monoclonal Antibody R24 Mus National Institute of Diabetes and Digestive and Kidney Diseases Online Systems Output Pathologic Pattern Positioning Attribute Production Proteins Publications Publishing Recording of previous events Regulator Genes Research Research Personnel Resources Science System Technology Testing Tissues Training Transcript Translating Vision Work annotation system blood formation cell injury cell type chromosome conformation capture clinically significant data acquisition epigenome epigenomics experimental study falls gene conservation genome browser genome editing genome-wide hematopoietic differentiation improved insight interdisciplinary collaboration loss of function mouse model novel precision medicine prototype response tool transcriptome

项目摘要

Project Summary VISION: ValIdated Systematic IntegratiON of hematopoietic epigenomes Technological advances enabling the production of large numbers of rich, genome-wide, sequence-based datasets have transformed biology. However, the volume of data is overwhelming for most investigators. Also, we do not know the mechanisms by which the vast majority of epigenetic features regulate normal differentiation or lead to aberrant function in disease. We have formed an interdisciplinary, collaborative team of investigators to address the problem of how to effectively utilize the enormous amount of epigenetic data both for basic research and precision medicine. At this point, acquisition of data is no longer the major barrier to understanding mechanisms of gene regulation during normal and pathological tissue development. The chief challenges are how to: (i) integrate epigenetic data in terms that are accessible and understandable to a broad community of researchers, (ii) build validated quantitative models explaining how the dynamics of gene expression relates to epigenetic features, and (iii) translate information effectively from mouse models to potential applications in human health. These needs are addressed by the proposed ValIdated Systematic IntegratiON (VISION) of epigenetic data to analyze mouse and human hematopoiesis, a tractable system with clear clinical significance and importance to NIDDK. By pursuing the following Specific Aims, the interdisciplinary collaboration will deliver comprehensive catalogs of cis regulatory modules (CRMs), extensive chromatin interaction maps and deduced regulatory domains, validated quantitative models for gene regulation, and a guide for investigators to translate insights from mouse models to human clinical studies. These deliverables will be provided to the community in readily accessible, web-based platforms including customized genome browsers, databases with facile query interfaces, and data-driven on-line tools. Specifically, the proposed work in Aim 1 will build comprehensive, integrative catalogs of hematopoietic CRMs and transcriptomes by compiling and determining informative epigenetic features and transcript levels in hematopoietic stem and progenitor cells and in mature cells. CRMs will be predicted using the novel IDEAS (Integrative and Discriminative Epigenome Annotation System) method. Work proposed in Aim 2 will build and validate quantitative models for gene regulation informed by chromatin interaction maps and epigenetic data. Compiling and determining chromosome interaction frequencies will predict likely target genes for CRMs. Gene regulatory models will be built that predict the contributions of CRMs and specific proteins to regulated expression; these models will be validated by extensive testing using genome-editing in ten reference loci. Finally, work in Aim 3 will produce a guide for investigators to translate insights from mouse models to human clinical studies. This effort will include categorizing orthologous mouse and human genes by conservation versus divergence of expression patterns, assigning CRMs to informative categories of epigenomic evolution, and testing the interspecies functional maps experimentally by genome-editing.

愿景：验证的系统整合造血表观基因组

项目成果

期刊论文数量（39）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Epigenetic Combinatorial Patterns Predict Disease Variants.

DOI：
10.3389/fgene.2017.00071
发表时间：
2017
期刊：
Frontiers in genetics
影响因子：
3.7
作者：
Zhang Y
通讯作者：
Zhang Y

Between form and function: the complexity of genome folding.

DOI：
10.1093/hmg/ddx306
发表时间：
2017-10-01
期刊：
Human molecular genetics
影响因子：
3.5
作者：
Oudelaar AM;Hanssen LLP;Hardison RC;Kassouf MT;Hughes JR;Higgs DR
通讯作者：
Higgs DR

Single-cell RNA-sequencing reveals a distinct population of proglucagon-expressing cells specific to the mouse upper small intestine.

DOI：
10.1016/j.molmet.2017.07.014
发表时间：
2017-10
期刊：
Molecular metabolism
影响因子：
8.1
作者：
Glass LL;Calero-Nieto FJ;Jawaid W;Larraufie P;Kay RG;Göttgens B;Reimann F;Gribble FM
通讯作者：
Gribble FM

Mammalian Transcription Factor Networks: Recent Advances in Interrogating Biological Complexity.