Understanding the predeterminants of transcription factor regulatory activity
Understanding the predeterminants of transcription factor regulatory activity
批准号:
10544796
负责人:
Shaun Aengus Mahony
金额:
$45.53万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-01-01 至 2026-12-31
关键词:
3-DimensionalAffinityBehaviorBindingBinding ProteinsBinding SitesCell Differentiation processCellsChromatinCollaborationsDNA BindingDNA-Binding ProteinsDevelopmentDiseaseEnvironmentEventGenesGenomeGenomicsGoalsHealthHematopoiesisHumanHuman GenomeHuman bodyMachine LearningMethodologyModelingNeuronsPatternResearchShapesSiteSpecific qualifier valueSpecificitySystemalgorithm developmentcell typecohortcomputerized toolsgenome-widemachine learning methodneural network architecturenovelpreferenceprogramssynergismtooltranscription factorvertebrate genome
中文摘要
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英文摘要
PROJECT SUMMARY / ABSTRACT
The goal of my research program is to understand how transcription factors (TFs) direct the regulatory
programs that underlie cell fate decisions. My lab currently focuses on a fundamental step in TF regulatory
activity: how do newly induced TFs establish their DNA binding patterns? TFs should have binding affinity for
millions of sites along the typical vertebrate genome, yet only a small fraction appears to be bound in a given
cell type. Moreover, the cohort that are bound changes across cell types and developmental timepoints. We
have developed pioneering machine learning approaches for characterizing regulatory genomic events and
understanding TF binding specificity. We have collaboratively applied our computational approaches to
understand cell fate decisions in cell differentiation systems, finding new ways in which the binding of induced
TFs can be influenced by preexisting chromatin environments. This proposal aims to integrate algorithmic
development and applied analysis of regulatory systems to gain a comprehensive understanding of how
genome-wide TF binding patterns are predetermined by chromatin regulatory states.
While many have cataloged the concurrent chromatin features that coexist with TF binding sites in a static
context, this proposal focuses on the dynamic settings that are typical of cell fate decisions. How does the
chromatin landscape in a given cell type shape where a newly induced TF will bind? Theme 1 will continue our
development of machine learning methods for studying dynamic TF binding activities. We will focus on novel
neural network architectures that can separate sequence and chromatin features to explain induced TF binding
patterns. Drawing on our unique expertise and methodologies, we will ask whether integrating 3D genome
organization or protein-DNA binding subtype modes (e.g., direct vs. indirect DNA binding) can explain why
certain sites become bound by induced TFs. We will further ask if DNA binding predeterminants are
transferrable: can we predict where a given TF will bind if introduced into a new cell type?
Theme 2 will analyze how TFs interact with established chromatin environments during cell fate decisions.
We will ask how paralogous Forkhead box TFs recognize distinct binding targets, even when they have similar
DNA binding preferences and are expressed in the same chromatin environment. To understand how TF
binding sites and regulatory activities can change as cells proceed down differentiation trajectories, we will
continue long-standing collaborations that examine chromatin-dependent TF regulatory behaviors during
neuronal subtype specification and hematopoiesis. Complementary to these efforts, we will build integrative
regulatory models of temporal chromatin accessibility dynamics at the single cell level.
The two themes will synergize to provide the computational tools and applied analyses that will enable a
more complete understanding of TF regulatory specificity during cell fate decisions.
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Understanding the predeterminants of transcription factor regulatory activity
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批准号:10798541
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项目类别:
-
资助金额:$11.37万
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财政年份:2022
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负责人:Shaun Aengus Mahony
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依托单位:
Understanding the predeterminants of transcription factor regulatory activity
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批准号:10330514
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项目类别:
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资助金额:$45.56万
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财政年份:2022
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负责人:Shaun Aengus Mahony
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依托单位:
Genome-wide structural organization of proteins within human gene regulatory complexes
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批准号:10166093
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项目类别:
-
资助金额:$6.67万
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财政年份:2018
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负责人:Shaun Aengus Mahony
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依托单位:
Genome-wide structural organization of proteins within human gene regulatory complexes
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批准号:10078275
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项目类别:
-
资助金额:$45.31万
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财政年份:2018
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负责人:Shaun Aengus Mahony
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依托单位:
A 2D segmentation method for jointly characterizing epigenetic dynamics in multiple cell lines
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批准号:9751894
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项目类别:
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资助金额:$34.24万
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财政年份:2017
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负责人:Shaun Aengus Mahony
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依托单位:
海外基金