Genome-wide structural organization of proteins within human gene regulatory complexes

人类基因调控复合体中蛋白质的全基因组结构组织

基本信息

批准号：
10166093
负责人：
Shaun Aengus Mahony
金额：
$ 6.67万
依托单位：
PENNSYLVANIA STATE UNIVERSITY, THE
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-01-19 至 2021-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10166093
关键词：
Architecture Binding Proteins Biological Biological Assay Cells Cloud Service Communities Complex Computer software Custom DNA Sequence DNA sequencing DNA-Binding Proteins Data Data Analyses Data Set Dependence Development Disease Engineering Environment Event Funding Galaxy Gene Expression Regulation Genes Genome Genomics Government Health Human Human Genome Laboratories Machine Learning Management Information Systems Metadata Online Systems Process Production Proteins Reagent Regulation Regulator Genes Reproducibility Resolution Resources Sampling Science Secure Services Standardization Stress Supercomputing System Testing Visualization analysis pipeline automated analysis base cell type cloud based computer infrastructure computerized tools cost data analysis pipeline data sharing data tools epigenomics experimental study genetic regulatory protein genome-wide genomic data large scale data novel open source organizational structure response

项目摘要

Project Summary/Abstract The DNA sequence of the human genome informs us as to the composition of proteins that make up healthy cells, but also altered compositions that create diseased cells. How protein production is controlled through the regulation of the genes that encode them is of critical importance for healthy and diseased cells. Knowing precisely where gene regulatory proteins bind, and are organized throughout the genome, including their interactions with each other, informs us as to how genes are regulated and mis-regulated. Since there are potentially thousands of different kinds of regulatory proteins and thousands of different kinds of human cell types and environmental responses that are a product of various subsets of regulatory proteins, the entire “universe” of gene regulatory events is quite substantial and consequently, quite costly to identify. One of the main bottlenecks in analysis of genomic data is efficient and scalable visualization approaches. The PEGR open source platform will provide programmatic access to any number of human cell sequenced datasets, from any stage of NGS processing, with the pipeline analysis results available for high-throughput machine learning testing and development. This project will empower discovery through the automated analysis and visualization of results from both small- and large-scale datasets. This architecture will include the following features: 1) a secure, cloud-based, metadata management system that instills best practices of experimental rigor, reproducibility, and data sharing; 2) automated Galaxy-based epigenomic data processing pipelines that provide easy-to-use “wizards” for standardized processing of common epigenomic data types; and 3) an easily de-ployable, open source software package as a means to disseminate data, tools, and discoveries via cloud services.

项目概要/摘要人类基因组的 DNA 序列告诉我们构成蛋白质的组成健康细胞，以及产生患病细胞的成分如何控制蛋白质的产生。通过调节编码它们的基因对于健康和患病细胞至关重要。准确了解基因调控蛋白的结合位置以及在整个基因组中的组织方式，包括它们之间的相互作用，告诉我们基因是如何被调节和被错误调节的。可能有数千种不同的调节蛋白和数千种不同的人类细胞类型和环境反应是各种调节蛋白子集的产物，基因调控事件的整个“宇宙”相当庞大，因此识别成本相当高。基因组数据分析的主要瓶颈之一是高效且可扩展的可视化方法。 PEGR 开源平台将提供对任意数量的已测序人类细胞的编程访问来自 NGS 处理任何阶段的数据集，以及可用于高通量的管道分析结果该项目将通过自动化的机器学习测试和开发来增强发现能力。该架构将包括小型和大型数据集结果的分析和可视化。具有以下功能：1）一个安全的、基于云的元数据管理系统，可灌输最佳实践 2) 基于 Galaxy 的自动化表观基因组数据处理流程为常见表观基因组的标准化处理提供易于使用的“向导” 数据类型；3) 易于部署的开源软件包作为传播数据、工具、以及通过云服务的发现。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

A ChIP-exo screen of 887 Protein Capture Reagents Program transcription factor antibodies in human cells.

DOI：
10.1101/gr.275472.121
发表时间：
2021-09
期刊：
Genome research
影响因子：
7
作者：
Lai WKM;Mariani L;Rothschild G;Smith ER;Venters BJ;Blanda TR;Kuntala PK;Bocklund K;Mairose J;Dweikat SN;Mistretta K;Rossi MJ;James D;Anderson JT;Phanor SK;Zhang W;Zhao Z;Shah AP;Novitzky K;McAnarney E;Keogh MC;Shilatifard A;Basu U;Bulyk ML;Pugh BF
通讯作者：
Pugh BF

PEGR: a management platform for ChIP-based next generation sequencing pipelines.