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.

项目摘要/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，但也改变了产生患病细胞的组合物。如何控制蛋白质通过调节编码它们的基因对于健康和患病细胞至关重要。精确地了解基因调节蛋白在哪里结合，并在整个基因组中组织起来，包括他们彼此之间的相互作用，向我们告知了基因如何受到调节和错误调节。从那以后可能是数千种不同种类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的子集的产物，基因调节事件的整个“宇宙”相当实质性，因此，识别非常昂贵。一基因组数据分析中的主要瓶颈是有效且可扩展的可视化方法。这 PEGR开源平台将提供对任何数量的人类细胞测序的编程访问数据集，来自NGS处理的任何阶段，都可以提供管道分析结果机器学习测试和开发。该项目将通过自动化授权发现分析和可视化小规模和大规模数据集的结果。此架构将包括以下功能：1）一个安全的，基于云的元数据管理系统，灌输了最佳实践实验性严格，可重复性和数据共享； 2）基于星系的自动表观基因组数据处理管道，可提供易于使用的“向导”，用于标准化常见表观基因组学的标准化处理数据类型； 3）易于去雇用的开源软件包，作为传播数据，工具，并通过云服务发现。

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.